There are the various constructs
that are adopted for measuring the performance of all countries which are
selected as sample in this study as Japan, United Satiates of America (USA) and
United Kingdom (UK). The dynamics of each country’s economic performance can be
easily captured by these constructs which are; inflation,
output gap, unemployment and IT. The research sturdy is conducted by
using the secondary which is leading towards the preexisting data that is used
for another projects. Both of the research method are used in this study as
quantitative and qualitative. In order to attain the final results the sector
data is used. Particularly, time series data is used. The datasets are between-2018
and collected as quarterly. This study discusses about the 2008 FED crisis and
there is comparisons between three countries in the form of before and after
2008(Kibbe, 2011).
The performance of the country is
affected by the monetary policy as well as stock market is one of the most
important major indicators that can affect the country’s performance(Kerongo Maatwa Meshack, 2016). The country’s
economic performance variables inflation rate, output growth and real exchange
rate is effecting the monetary policy and due to this stock markets are also
effected. E-views is used to analyzing the data because it’s referred as the
one of the most important and authentic software for analyzing the time series
data(Eviews, 2019). It is one of the ideal packages to
efficiently and quickly managing data. E-views used to perform statistical analysis and econometrics. This tool is also used for model simulations
and generating forecast. Tables for publication and high quality graphs can be
generated by using this software. This tool is used for inclusion and various
other applications
Empirical strategy the impact
of monetary policy on stock markets of Japan, USA and UK
The empirical strategy is
commonly followed by the equation of regression which is also known as the
estimation equation. It can be explains about the intercepts as what the person
is thinking about the x and y variables, particularly for that at where Y is the dependent variable and X is the
independent variable. The Structural Vector Auto Regression (SVAR) is applied
on this data. For each countries the impulse rate functions is estimated by
utilizing the data for particular period of 1990-2018. The first difference
of algorithm is the growth rate. The order of the variables in the VAR model is similar to the studies of (Chuku, 2009).
Stationary Test of the impact of monetary policy on stock markets of
Japan, USA and UK
Stationary Test is the one of the
most important tests which is used to measure the effectiveness and authentication
of the data.This tests tells about either regression can be applied on the
particular data or not. If the
significance level is less than 0.05 it shows data is accurate for regression
analysis. As depicted in the study of the (Lee, 2010)
The effects of monetary policy on Stock markets of Japan, USA and UK
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above given graph is
representing the level of the Inflation, Output Gap, Unemployment and IT along
with its years in Japan. The values are not constant in this graph for all of
these variables. It represents the gradual and abrupt fluctuations. As in the
above image the Output Gap remains between -1 to 2 during 1994- 2008. Meanwhile
in 2009 there were abrupt fluctuations and the value of output Gap reached at
-6 than it reached at 1 in 2010. There
is gradual fluctuations in the unemployment which shows unemployment’s is occur
all time in Japan from 1994 to 2018. There is gradual fluctuation occurs in the
inflation rate of the Japan during 1994 to 2018 but in 2009 it reached at -2
which shows the bad conditions of Japan meanwhile in 2014 it was 3 and the
situation of country was good. These results are more similar with the study of
(Gambacorta, 2014).
United Kingdom (UK)
The above given graph is
representing the level of the Inflation, Output Gap, Unemployment and IT along
with its years in UK. With the references of the study of(Miyao, 2002) the values are not
constant in this graph for all of these variables. It represents the gradual
and abrupt fluctuations. As in the above image the Output Gap remains 0 to 1.7 during
1994-2008. Meanwhile in 2009 there were abrupt fluctuations and the value of output
Gap reached at -3 than it reached at -1.6 in 2010. There is abrupt fluctuations in the
unemployment which shows unemployment’s is occur all time in UK from 1994 to
2018. In 1994 the unemployment rate was 10. There is gradual fluctuation occurs
in the inflation rate of the UK during 1994 to 2018 but in 2009 it reached at 4.2
which shows the good conditions of UK. The stock market price as IT was least in UK
as 1-2.
United Sates of America (USA)
The above given graph is
representing the level of the Inflation, Output Gap, Unemployment and IT along
with its years in USA. The values are not constant in this graph for all of
these variables. It represents the gradual and abrupt fluctuations. As in the
above image the Output Gap remains 0 to 2.1 during 1994-2000. Meanwhile in 2009
there were abrupt fluctuations and the value of output Gap reached at -3 than
it reached at 0in 2018. There is abrupt
fluctuations in the unemployment which shows unemployment’s is occur all time
in USA from 1994 to 2018. In 2010 the unemployment rate was 10. There is
gradual fluctuation occurs in the inflation rate of the USA during 1994 to 2018
but in 2009 it reached at -1 which shows the good conditions of USA. The stock market price as IT was least in USA
as 1-2. As depicted in the study of (Caggiano, 2014)
Vector auto regression
Japan
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/23/19 Time: 15:25
|
|
|
Sample
(adjusted): 1995Q1 2018Q4
|
|
Included
observations: 93 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
-3.198354
|
0.638574
|
-5.008584
|
0.0000
|
INFLATION
|
0.007516
|
0.116024
|
0.064777
|
0.9485
|
OUTPUTGAP
|
0.207719
|
0.073821
|
2.813841
|
0.0060
|
UNEMPLOYMENT
|
0.762235
|
0.150138
|
5.076889
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.285089
|
Mean
dependent var
|
-0.030866
|
Adjusted
R-squared
|
0.260991
|
S.D.
dependent var
|
1.053339
|
S.E.
of regression
|
0.905510
|
Akaike
info criterion
|
2.681421
|
Sum
squared resid
|
72.97536
|
Schwarz
criterion
|
2.790350
|
Log
likelihood
|
-120.6861
|
Hannan-Quinn
criter.
|
2.725403
|
F-statistic
|
11.83036
|
Durbin-Watson
stat
|
0.154003
|
Prob(F-statistic)
|
0.000001
|
|
|
|
|
|
|
|
|
|
|
|
|
|
United States of America
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/21/19 Time: 19:32
|
|
|
Sample
(adjusted): 1995Q1 2018Q4
|
|
Included
observations: 96 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
1.557590
|
0.178373
|
8.732200
|
0.0000
|
INFLATION
|
0.163609
|
0.036893
|
4.434746
|
0.0000
|
OUTPUTGAP
|
-0.126177
|
0.042790
|
-2.948764
|
0.0040
|
UNEMPLOYMENT
|
-0.104735
|
0.025696
|
-4.076004
|
0.0001
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.308955
|
Mean dependent
var
|
1.315118
|
Adjusted
R-squared
|
0.286421
|
S.D.
dependent var
|
0.411912
|
S.E.
of regression
|
0.347957
|
Akaike
info criterion
|
0.767296
|
Sum
squared resid
|
11.13880
|
Schwarz
criterion
|
0.874144
|
Log
likelihood
|
-32.83023
|
Hannan-Quinn
criter.
|
0.810486
|
F-statistic
|
13.71058
|
Durbin-Watson
stat
|
0.167650
|
Prob(F-statistic)
|
0.000000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
United Kingdom
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/23/19 Time: 16:56
|
|
|
Sample
(adjusted): 1995Q1 2018Q4
|
|
Included
observations: 96 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
0.456824
|
0.270394
|
1.689475
|
0.0945
|
INFLATION
|
-0.016956
|
0.077510
|
-0.218761
|
0.8273
|
OUTPUTGAP
|
0.086012
|
0.055271
|
1.556190
|
0.1231
|
UNEMPLOYENT
|
0.145141
|
0.050279
|
2.886734
|
0.0049
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.100192
|
Mean
dependent var
|
1.296884
|
Adjusted
R-squared
|
0.070850
|
S.D.
dependent var
|
0.548872
|
S.E.
of regression
|
0.529071
|
Akaike
info criterion
|
1.605385
|
Sum
squared resid
|
25.75227
|
Schwarz
criterion
|
1.712233
|
Log
likelihood
|
-73.05848
|
Hannan-Quinn
criter.
|
1.648575
|
F-statistic
|
3.414676
|
Durbin-Watson
stat
|
0.049627
|
Prob(F-statistic)
|
0.020674
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interpretation
of the impact of monetary policy on stock markets of Japan, USA and UK
After conducting the regression
analysis for all of these countries Japan, Uk, and USA it has been observed
that one standard deviation of monetary policy is statically significant for
all countries as for UK it is variants 0.5% from its mean value, in USA it
variants 0.4% and 1.05% for Japan. The coefficients (inflation,
output gap, and unemployment) values are 0.007516,
0.207719 and 0.762235 respectively. It shows that there is positive
relationship among monetary policy and stick market price in Japan and the
level of significance for two variables are less than 0.05 meanwhile for 0.9485
for inflation rate. It represents that there is positiverelationship among
inflation rate and stock market price in Japan but not significant. As
indicated in the study of (Kurihara, 2006). The value of the R square is 0.285089
it means due to the 1% change in IT (stock market price) inflation, output gap,
and unemployment will be changed 28%.
The coefficients (inflation, output gap, and unemployment) values are 0.163609, -0.126177and -0.104735 respectively. It shows
that there is positive relationship among inflation and stock market price in USA
meanwhile output gap, and unemployment have negative relationship with stock
market priceand the level of significance for all variables are less than 0.05.
It represents that there is positive significant relationship among inflation
rate and stock market price in USA but there is negative significant
relationship among output gap, unemployment and stock market price. The value
of the R square is 0.308955it means due to the 1% change in IT (stock market
price) inflation, output gap, and unemployment will be changed 30% in United
States of America(Roy, 2012).
The coefficients (inflation, output gap, and unemployment) values are -0.016956, 0.086012 and 0.145141 respectively. It shows
that there is positive relationship among output gap, unemployment and stock
market price in UK meanwhile inflation have negative relationship with stock
market price and the level of significance for two variables are greater than
0.05 meanwhile for unemployment significant value is 0.0049. It represents that
there is positive insignificant relationship among output gap and stock market
price in United Kingdom but there is negative insignificant relationship among Inflation
and stock market price in UK. Unemployment has positive significant
relationship with IT (Stock market price). The value of the R square is 0.100192
it means due to the 1% change in IT (stock market price) inflation, output gap,
and unemployment will be changed 10% in UK. The results are seemed as (Ioannidis, 2008)
Wald Test of the impact of monetary policy on stock markets
of Japan, USA and UK
Wald
Test:
|
|
|
Equation:
Untitled
|
|
|
|
|
|
|
|
|
|
Test
Statistic
|
Value
|
df
|
Probability
|
|
|
|
|
|
|
|
|
F-statistic
|
19.74850
|
(2,
89)
|
0.0000
|
Chi-square
|
39.49700
|
2
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
Null
Hypothesis: C(2)=C(3)=0.5
|
|
Null Hypothesis
Summary:
|
|
|
|
|
|
|
|
|
|
Normalized
Restriction (= 0)
|
Value
|
Std.
Err.
|
|
|
|
|
|
|
|
|
-0.5
+ C(2)
|
-0.492484
|
0.116024
|
-0.5
+ C(3)
|
-0.292281
|
0.073821
|
|
|
|
|
|
|
|
|
Restrictions
are linear in coefficients.
|
The above given tables is representing the
analysis of the Wald Test in Japan. In order to the
appearance of the variables the coefficients are assigned in the specificationsFor
the PR terms the coefficients are labeled as C(2)=C(3)=0.5.
It is indicated by the low probability values which is 0.000 that the null
hypothesis is strongly rejected because it is equal to 0.5. Such kind of the
results can carefully accepted without any extra analysis. It is
reported by the above given analysis the standard error for C (2) is 0.116024 and C (3)is 0.073821.
In the residual of the estimated equation the presence of theserial correlation
indicated. The null hypothesis rejected in case of the uncorrected, serial
correlation for residuals. Invalid statics inference for the coefficients of(De Maio, 2008).
Wald
Test:
|
|
|
Equation:
Untitled
|
|
|
|
|
|
|
|
|
|
Test
Statistic
|
Value
|
df
|
Probability
|
|
|
|
|
|
|
|
|
F-statistic
|
228.7279
|
(2,
92)
|
0.0000
|
Chi-square
|
457.4558
|
2
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
Null
Hypothesis: C(2)=C(3)=0.5
|
|
Null
Hypothesis Summary:
|
|
|
|
|
|
|
|
|
|
Normalized
Restriction (= 0)
|
Value
|
Std.
Err.
|
|
|
|
|
|
|
|
|
-0.5
+ C(2)
|
-0.336391
|
0.036893
|
-0.5
+ C(3)
|
-0.626177
|
0.042790
|
|
|
|
|
|
|
|
|
Restrictions
are linear in coefficients.
|
The above given tables is representing the
analysis of the Wald Test in USA. In order to the appearance of the variables
the coefficients are assigned in the specifications For the PR terms the
coefficients are labeled as C(2)=C(3)=0.5. It
is indicated by the low probability values which is 0.000 that the null
hypothesis is strongly rejected because it is equal to 0.5. Such kind of the
results can carefully accepted without any extra analysis. It is
reported by the above given analysis the standard error for C (2) is 0.036893 and C (3) is 0.042790.
In the residual of the estimated equation the presence of the serial correlation
indicated. The null hypothesis rejected in case of the uncorrected, serial
correlation for residuals. Invalid statics inference for the coefficients.
Wald
Test:
|
|
|
Equation:
Untitled
|
|
|
|
|
|
|
|
|
|
Test Statistic
|
Value
|
df
|
Probability
|
|
|
|
|
|
|
|
|
F-statistic
|
60.78016
|
(2,
92)
|
0.0000
|
Chi-square
|
121.5603
|
2
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
Null
Hypothesis: C(2)=C(3)=0.5
|
|
Null
Hypothesis Summary:
|
|
|
|
|
|
|
|
|
|
Normalized
Restriction (= 0)
|
Value
|
Std.
Err.
|
|
|
|
|
|
|
|
|
-0.5
+ C(2)
|
-0.516956
|
0.077510
|
-0.5
+ C(3)
|
-0.413988
|
0.055271
|
|
|
|
|
|
|
|
|
Restrictions
are linear in coefficients.
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above given tables is representing the
analysis of the Wald Test in UK. In order to the appearance of the variables
the coefficients are assigned in the specifications For the PR terms the
coefficients are labeled as C(2)=C(3)=0.5. It
is indicated by the low probability values which is 0.000 that the null
hypothesis is strongly rejected because it is equal to 0.5. Such kind of the
results can carefully accepted without any extra analysis. It is
reported by the above given analysis the standard error for C (2) is 0.077510 and C (3) is 0.055271.
In the residual of the estimated equation the presence of the serial correlation
indicated. The null hypothesis rejected in case of the uncorrected, serial
correlation for residuals. Invalid statics inference for the coefficients.
Interpretation of the impact
of monetary policy on stock markets of Japan, USA and UK
The above said graph represents
the annual data on the X-axis and the time period span from the year 1996 to
2018. The variables of interest include inflation, output gap and unemployment.
The above graph belongs to JAPAN and it is containing the information against
three parameters i.e., residual, actual and fitted. The graph values against
these determinants demonstrate that they all are showing the same behavior
i.e., they are gradually increasing or decreasing to a certain level against a
specified year. The residual and the actual graphs have shown the abrupt
fluctuations at certain points. For the year 2003, residual value got decreased
and reached to a negative value (-1) from 2. For the year 2016, actual value
got decreased and reached to 0 from 2.
Interpretation of the impact
of monetary policy on stock markets of Japan, USA and UK
The above graph belongs to UK and
it is also containing the information against three parameters i.e., residual,
actual and fitted. The graph values against these determinants also demonstrate
that they all are showing the same behavior i.e., they are gradually increasing
or decreasing to a certain level against a specified year. There is no abrupt
behavior for any parameter rather it is the gradual one. The fluctuation to the
values of market shares is slow for every of the year.
United Sates of America (USA)
Interpretation of the impact
of monetary policy on stock markets of Japan, USA and UK
The above graph belongs to USA
and it is also containing the information against three parameters i.e.,
residual, actual and fitted. The graph values against these determinants also
demonstrate that they all are showing the same behavior i.e., they are
gradually increasing or decreasing to a certain level against a specified year.
There is no abrupt behavior for any parameter rather it is the gradual one. The
fluctuation to the values of market shares is slow for every of the year
Chow
Breakpoint Test: 2018Q1
|
|
Null
Hypothesis: No breaks at specified breakpoints
|
Varying
regressors: All equation variables
|
|
Equation
Sample: 1995Q1 2018Q4
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
4.802704
|
|
Prob.
F(4,85)
|
0.0015
|
Log
likelihood ratio
|
18.95011
|
|
Prob.
Chi-Square(4)
|
0.0008
|
Wald
Statistic
|
19.21082
|
|
Prob.
Chi-Square(4)
|
0.0007
|
|
|
|
|
|
|
|
|
|
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above said Chow test is
helping to determine the existence of the break points in the study data. For
every test that is a part of break-point, F-Test value is the same. It is also
used as an assumption for Chow test. The value of F-statistics is change for
every Country (Japan, UK and USA). The degree of freedom (Prob. F) is (4, 85)
for Japan and it is different for the other countries of the current study. For
Japan, the p-value of F-statistics is 0.0015. This value is less than 5%. So,
H0 is rejected. This rejection of null hypothesis indicates that there exist
structural breaks in the data for Japan.
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/21/19 Time: 01:17
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 92 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
-2.939135
|
0.654929
|
-4.487719
|
0.0000
|
INFLATION
|
0.087255
|
0.119650
|
0.729249
|
0.4678
|
OUTPUTGAP
|
0.005255
|
0.013701
|
0.383521
|
0.7023
|
UNEMPLOYMENT
|
0.694131
|
0.153520
|
4.521447
|
0.0000
|
S(-1)
|
-0.004368
|
0.004588
|
-0.952040
|
0.3437
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.264380
|
Mean dependent
var
|
-0.047285
|
Adjusted
R-squared
|
0.230559
|
S.D.
dependent var
|
1.047076
|
S.E.
of regression
|
0.918473
|
Akaike
info criterion
|
2.720606
|
Sum
squared resid
|
73.39249
|
Schwarz
criterion
|
2.857660
|
Log
likelihood
|
-120.1479
|
Hannan-Quinn
criter.
|
2.775922
|
F-statistic
|
7.816902
|
Durbin-Watson
stat
|
0.108578
|
Prob(F-statistic)
|
0.000020
|
|
|
|
|
|
|
|
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above said table shows that
the value of probability statistics for unemployment is less than 0.05 which
shows that there exists data significance for this study variable. This value
is greater than 0.05 for the other study variables which shows insignificance.
The overall value of R-square shows that for 1% change in the independent
variables (inflation, output gap and unemployment) there exists 26% change in
the dependent variable IT for Japan data.
Chow
Breakpoint Test: 2008Q1
|
|
Null
Hypothesis: No breaks at specified breakpoints
|
Varying
regressors: All equation variables
|
|
Equation
Sample: 1995Q1 2018Q4
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
84.89420
|
|
Prob.
F(4,88)
|
0.0000
|
Log
likelihood ratio
|
151.7565
|
|
Prob.
Chi-Square(4)
|
0.0000
|
Wald
Statistic
|
339.5768
|
|
Prob.
Chi-Square(4)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above table shows that the
value of F-statistics is change for UK. It is 84.89420. The degree of freedom
(Prob. F) is (4, 88) for United Kingdom and it is similar to United States of
America. For UK, the p-value of F-statistics is 0.0000. This value is less than
5%. So, H0 is rejected. This rejection of null hypothesis indicates that there
exist structural breaks in the data for United Kingdom
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/23/19 Time: 17:07
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 95 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
0.531592
|
0.283179
|
1.877227
|
0.0637
|
INFLATION
|
-0.014072
|
0.078689
|
-0.178830
|
0.8585
|
OUTPUTGAP
|
0.070926
|
0.059655
|
1.188943
|
0.2376
|
UNEMPLOYENT
|
0.129796
|
0.052894
|
2.453909
|
0.0161
|
S(-1)
|
0.001737
|
0.004089
|
0.424815
|
0.6720
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.086156
|
Mean
dependent var
|
1.287811
|
Adjusted
R-squared
|
0.045541
|
S.D.
dependent var
|
0.544497
|
S.E.
of regression
|
0.531954
|
Akaike
info criterion
|
1.626678
|
Sum
squared resid
|
25.46780
|
Schwarz
criterion
|
1.761093
|
Log
likelihood
|
-72.26721
|
Hannan-Quinn
criter.
|
1.680992
|
F-statistic
|
2.121277
|
Durbin-Watson
stat
|
0.046975
|
Prob(F-statistic)
|
0.084604
|
|
|
|
|
|
|
|
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above said table shows that
the value of probability statistics for all the independent variables is
greater than 0.05 which shows data insignificance for these variables with the
dependent variable IT. The overall value of R-square shows that for 1% change
in the independent variables (inflation, output gap and unemployment) there
exists 0.08 points change in the dependent variable IT for UK data.
Chow
Breakpoint Test: 2008Q1
|
|
Null
Hypothesis: No breaks at specified breakpoints
|
Varying
regressors: All equation variables
|
|
Equation
Sample: 1995Q1 2018Q4
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
48.95387
|
|
Prob.
F(4,88)
|
0.0000
|
Log likelihood
ratio
|
112.4148
|
|
Prob.
Chi-Square(4)
|
0.0000
|
Wald
Statistic
|
195.8155
|
|
Prob.
Chi-Square(4)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
Interpretation of the impact of
monetary policy on stock markets of Japan, USA and UK
The above table shows that the
value of F-statistics is change for United States of America. It is 48.95387.
The degree of freedom (Prob. F) is (4, 88) for United States of America and it
is similar to United Kingdom. For USA, the p-value of F-statistics is 0.0000.
This value is less than 5%. So, H0 is rejected. This rejection of null
hypothesis indicates that there exist structural breaks in the data for United
States of America.
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/21/19 Time: 19:37
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 95 after adjustments
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
1.551502
|
0.178057
|
8.713507
|
0.0000
|
INFLATION
|
0.158599
|
0.036976
|
4.289289
|
0.0000
|
OUTPUTGAP
|
-0.129676
|
0.045180
|
-2.870180
|
0.0051
|
UNEMPLOYMENT
|
-0.103921
|
0.025581
|
-4.062450
|
0.0001
|
S(-1)
|
0.000834
|
0.002389
|
0.349022
|
0.7279
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.309782
|
Mean
dependent var
|
1.307775
|
Adjusted
R-squared
|
0.279106
|
S.D. dependent
var
|
0.407732
|
S.E.
of regression
|
0.346187
|
Akaike
info criterion
|
0.767520
|
Sum
squared resid
|
10.78608
|
Schwarz
criterion
|
0.901935
|
Log
likelihood
|
-31.45720
|
Hannan-Quinn
criter.
|
0.821834
|
F-statistic
|
10.09839
|
Durbin-Watson
stat
|
0.166569
|
Prob(F-statistic)
|
0.000001
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interpretation of the impact of monetary policy on stock markets of
Japan, USA and UK
The above said table shows that
the value of probability statistics for inflation is less than 0.05 which shows
that there exists data significance for this study variable. This value is
greater than 0.05 for the other study variables which shows insignificance. The
overall value of R-square shows that for 1% change in the independent variables
(inflation, output gap and unemployment) there exists 3% change in the
dependent variable IT for United States of America data
Heteroskedasticity Test: White of the impact of
monetary policy on stock markets of Japan, USA and UK
Japan
Heteroskedasticity
Test: White
|
|
Null
hypothesis: Homoskedasticity
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
8.942305
|
Prob.
F(14,77)
|
0.0000
|
Obs*R-squared
|
56.96404
|
Prob.
Chi-Square(14)
|
0.0000
|
Scaled
explained SS
|
62.30831
|
Prob.
Chi-Square(14)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
United Kingdom
|
|
|
|
|
|
Heteroskedasticity
Test: White
|
|
|
|
|
|
|
|
Null
hypothesis: Homoskedasticity
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
3.386089
|
Prob.
F(14,80)
|
0.0003
|
|
|
Obs*R-squared
|
35.34782
|
Prob.
Chi-Square(14)
|
0.0013
|
|
|
Scaled
explained SS
|
15.51256
|
Prob.
Chi-Square(14)
|
0.3440
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
USA
Heteroskedasticity
Test: White
|
|
Null
hypothesis: Homoskedasticity
|
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
4.385772
|
Prob.
F(14,80)
|
0.0000
|
Obs*R-squared
|
41.25208
|
Prob.
Chi-Square(14)
|
0.0002
|
Scaled
explained SS
|
22.11176
|
Prob.
Chi-Square(14)
|
0.0763
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interpretation
of the impact of monetary policy on
stock markets of Japan, USA and UK
The white test is referred as the
statistical test which can establishes either errors in the variance of the
regression model is constant or not.The value of the F statics for data of
Japan is 8.942305 and it shows the fitness of the
model for further analysis. The value of
the Obs R- squared is 56.96404 it represent that there is 56% effects on the
independent variables.The probability Chi-squared is less than 0.05. The
value of the F statics for data of UK is 3.386089 and
it shows the fitness of the model for further analysis. The value of the Obs R- squared is 35.34782
it represent that there is 35% effects on the independent variables. The
probability Chi-squared is less than 0.05.The probability Chi-squared is less
than 0.05. The value of the F statics for data of USA is 4.385772 and it shows the fitness of the model for further
analysis. The value of the Obs R-
squared is 41.25208 it represent that there is 41% effects on the independent
variables. The probability Chi-squared is less than 0.05.
Breusch-Godfrey Serial Correlation LM Test
of the impact
of monetary policy on stock markets of Japan, USA and UK
Japan
Breusch-Godfrey
Serial Correlation LM Test:
|
|
Null
hypothesis: No serial correlation at up to 2 lags
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
98.87671
|
Prob.
F(2,85)
|
0.0000
|
Obs*R-squared
|
64.34339
|
Prob.
Chi-Square(2)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
UK
Breusch-Godfrey
Serial Correlation LM Test:
|
|
Null
hypothesis: No serial correlation at up to 2 lags
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
717.3880
|
Prob.
F(2,88)
|
0.0000
|
Obs*R-squared
|
89.51003
|
Prob.
Chi-Square(2)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
USA
Breusch-Godfrey
Serial Correlation LM Test:
|
|
Null
hypothesis: No serial correlation at up to 2 lags
|
|
|
|
|
|
|
|
|
|
|
F-statistic
|
242.7437
|
Prob.
F(2,88)
|
0.0000
|
Obs*R-squared
|
80.42252
|
Prob.
Chi-Square(2)
|
0.0000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interpretation
of the impact of monetary policy on
stock markets of Japan, USA and UK
This is the test which is used to
auto correlation in case of any errors in the model of regression. The use of
residual made by it from the model that is beings considered in regression
analysis and from all of these test statistics is derived in the form ofF-statistics. The value of the F-statistics is98.87671 for
the data of Japan which is more than 10 and it represent that null hypothesis
is true for full model. The F-statics value is 717.3880, 242.7437 for UK and
USA respectively. It means null hypothesis is true for this complete model.
HAC standard errors & covariance
(Bartlett kernel, Newey-West fixed
Japan
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/23/19 Time: 15:44
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 92 after adjustments
|
|
HAC
standard errors & covariance (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
-3.477724
|
1.741795
|
-1.996633
|
0.0490
|
INFLATION
|
0.018872
|
0.172436
|
0.109444
|
0.9131
|
OUTPUTGAP
|
0.256079
|
0.101065
|
2.533815
|
0.0131
|
UNEMPLOYMENT
|
0.821844
|
0.386524
|
2.126241
|
0.0363
|
S(-1)
|
-0.006265
|
0.005145
|
-1.217750
|
0.2266
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.357275
|
Mean
dependent var
|
-0.047285
|
Adjusted
R-squared
|
0.327725
|
S.D.
dependent var
|
1.047076
|
S.E.
of regression
|
0.858523
|
Akaike
info criterion
|
2.585609
|
Sum
squared resid
|
64.12437
|
Schwarz
criterion
|
2.722662
|
Log
likelihood
|
-113.9380
|
Hannan-Quinn
criter.
|
2.640925
|
F-statistic
|
12.09031
|
Durbin-Watson
stat
|
0.228105
|
Prob(F-statistic)
|
0.000000
|
Wald
F-statistic
|
3.255777
|
Prob(Wald
F-statistic)
|
0.015433
|
|
|
|
|
|
|
|
|
|
|
|
|
|
United Kingdom
of the impact of monetary policy on
stock markets of Japan, USA and UK
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/23/19 Time: 17:12
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 95 after adjustments
|
|
HAC
standard errors & covariance (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
0.531592
|
0.637258
|
0.834186
|
0.4064
|
INFLATION
|
-0.014072
|
0.143074
|
-0.098354
|
0.9219
|
OUTPUTGAP
|
0.070926
|
0.078531
|
0.903163
|
0.3689
|
UNEMPLOYENT
|
0.129796
|
0.120081
|
1.080906
|
0.2826
|
S(-1)
|
0.001737
|
0.005650
|
0.307451
|
0.7592
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.086156
|
Mean
dependent var
|
1.287811
|
Adjusted
R-squared
|
0.045541
|
S.D.
dependent var
|
0.544497
|
S.E.
of regression
|
0.531954
|
Akaike
info criterion
|
1.626678
|
Sum
squared resid
|
25.46780
|
Schwarz
criterion
|
1.761093
|
Log
likelihood
|
-72.26721
|
Hannan-Quinn
criter.
|
1.680992
|
F-statistic
|
2.121277
|
Durbin-Watson
stat
|
0.046975
|
Prob(F-statistic)
|
0.084604
|
Wald
F-statistic
|
0.634759
|
Prob(Wald
F-statistic)
|
0.639007
|
|
|
|
|
|
|
|
|
|
|
|
|
|
United States of
America of the impact of
monetary policy on stock markets of Japan, USA and UK
Dependent
Variable: IT
|
|
|
Method:
Least Squares
|
|
|
Date:
08/21/19 Time: 19:42
|
|
|
Sample
(adjusted): 1995Q2 2018Q4
|
|
Included
observations: 95 after adjustments
|
|
HAC
standard errors & covariance (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
1.551502
|
0.357423
|
4.340800
|
0.0000
|
INFLATION
|
0.158599
|
0.052325
|
3.031043
|
0.0032
|
OUTPUTGAP
|
-0.129676
|
0.066942
|
-1.937123
|
0.0559
|
UNEMPLOYMENT
|
-0.103921
|
0.049994
|
-2.078670
|
0.0405
|
S(-1)
|
0.000834
|
0.003357
|
0.248414
|
0.8044
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.309782
|
Mean
dependent var
|
1.307775
|
Adjusted
R-squared
|
0.279106
|
S.D.
dependent var
|
0.407732
|
S.E.
of regression
|
0.346187
|
Akaike
info criterion
|
0.767520
|
Sum
squared resid
|
10.78608
|
Schwarz
criterion
|
0.901935
|
Log
likelihood
|
-31.45720
|
Hannan-Quinn
criter.
|
0.821834
|
F-statistic
|
10.09839
|
Durbin-Watson
stat
|
0.166569
|
Prob(F-statistic)
|
0.000001
|
Wald
F-statistic
|
4.673895
|
Prob(Wald
F-statistic)
|
0.001790
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Interpretation
of the impact of monetary policy on
stock markets of Japan, USA and UK
The above given result of the HAC standard errors & covariance illustrates the test
statics as well as values of associated probability. The test statistics are carried by using the
test regression that is reported below.The
R square is observed by this labeled by the statistic. It represent that no serial
correlation is occurred. The (effectively) zero probability value strongly
indicates the presence of serial correlation in the residuals(Gregoriou, 2009).
Standard errors & covariance computed
using estimation weighting matrix
|
instrument specification: inflation(-1)
inflation(-2) output gap(-1) output gap(-2) unemployment(-1) unemployment(-2)
|
|
Japan
Dependent
Variable: IT
|
|
|
Method:
Generalized Method of Moments
|
|
Date:
08/23/19 Time: 15:48
|
|
|
Sample
(adjusted): 1995Q3 2018Q4
|
|
Included
observations: 91 after adjustments
|
|
Linear
estimation with 1 weight update
|
|
Estimation
weighting matrix: HAC (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
Standard
errors & covariance computed using estimation weighting matrix
|
Instrument
specification: INFLATION(-1) INFLATION(-2) OUTPUTGAP(-1)
|
OUTPUTGAP(-2)
UNEMPLOYMENT(-1) UNEMPLOYMENT(-2)
|
Constant
added to instrument list
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
-3.675220
|
1.406869
|
-2.612339
|
0.0106
|
INFLATION
|
0.040330
|
0.164805
|
0.244716
|
0.8073
|
OUTPUTGAP
|
0.368843
|
0.120402
|
3.063430
|
0.0029
|
UNEMPLOYMENT
|
0.859934
|
0.326642
|
2.632654
|
0.0100
|
S(-1)
|
-0.023762
|
0.008375
|
-2.837433
|
0.0057
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.246751
|
Mean
dependent var
|
-0.060842
|
Adjusted
R-squared
|
0.211717
|
S.D.
dependent var
|
1.044726
|
S.E.
of regression
|
0.927564
|
Sum
squared resid
|
73.99222
|
Durbin-Watson
stat
|
0.447644
|
J-statistic
|
0.005530
|
Instrument
rank
|
7
|
Prob(J-statistic)
|
0.997239
|
|
|
|
|
|
|
|
|
|
|
USA
Dependent
Variable: IT
|
|
|
Method:
Generalized Method of Moments
|
|
Date:
08/21/19 Time: 19:44
|
|
|
Sample
(adjusted): 1995Q3 2018Q4
|
|
Included
observations: 94 after adjustments
|
|
Linear
estimation with 1 weight update
|
|
Estimation
weighting matrix: HAC (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
Standard
errors & covariance computed using estimation weighting matrix
|
Instrument
specification: INFLATION(-1) INFLATION(-2) OUTPUTGAP(-1)
|
OUTPUTGAP(-2)
UNEMPLOYMENT(-1) UNEMPLOYMENT(-2)
|
Constant
added to instrument list
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
1.898206
|
0.301026
|
6.305779
|
0.0000
|
INFLATION
|
0.140782
|
0.048610
|
2.896158
|
0.0047
|
OUTPUTGAP
|
-0.163490
|
0.062988
|
-2.595574
|
0.0110
|
UNEMPLOYMENT
|
-0.148646
|
0.045212
|
-3.287744
|
0.0014
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.261979
|
Mean
dependent var
|
1.301581
|
Adjusted
R-squared
|
0.237378
|
S.D.
dependent var
|
0.405399
|
S.E.
of regression
|
0.354027
|
Sum
squared resid
|
11.28018
|
Durbin-Watson
stat
|
0.158024
|
J-statistic
|
8.560404
|
Instrument
rank
|
7
|
Prob(J-statistic)
|
0.035744
|
|
|
|
|
|
|
|
|
|
|
UK
Dependent
Variable: IT
|
|
|
Method:
Generalized Method of Moments
|
|
Date:
08/23/19 Time: 17:14
|
|
|
Sample
(adjusted): 1995Q3 2018Q4
|
|
Included
observations: 94 after adjustments
|
|
Linear
estimation with 1 weight update
|
|
Estimation
weighting matrix: HAC (Bartlett kernel, Newey-West fixed
|
bandwidth
= 4.0000)
|
|
|
Standard
errors & covariance computed using estimation weighting matrix
|
Instrument
specification: INFLATION(-1) INFLATION(-2) OUTPUTGAP(-1)
|
OUTPUTGAP(-2)
UNEMPLOYENT(-1) UNEMPLOYENT(-2)
|
Constant
added to instrument list
|
|
|
|
|
|
|
|
|
|
|
|
Variable
|
Coefficient
|
Std.
Error
|
t-Statistic
|
Prob.
|
|
|
|
|
|
|
|
|
|
|
C
|
0.506287
|
0.653400
|
0.774851
|
0.4405
|
INFLATION
|
0.006609
|
0.117480
|
0.056257
|
0.9553
|
OUTPUTGAP
|
0.080926
|
0.089713
|
0.902047
|
0.3695
|
UNEMPLOYENT
|
0.132242
|
0.125488
|
1.053824
|
0.2948
|
S(-1)
|
-0.001851
|
0.006020
|
-0.307455
|
0.7592
|
|
|
|
|
|
|
|
|
|
|
R-squared
|
0.061600
|
Mean
dependent var
|
1.279071
|
Adjusted
R-squared
|
0.019425
|
S.D.
dependent var
|
0.540677
|
S.E.
of regression
|
0.535400
|
Sum
squared resid
|
25.51211
|
Durbin-Watson
stat
|
0.052117
|
J-statistic
|
0.238791
|
Instrument
rank
|
7
|
Prob(J-statistic)
|
0.887457
|
|
|
|
|
|
|
|
|
|
|
Interpretation
of the impact of monetary policy on stock
markets of Japan, USA and UK
The above given analysis are representing that
all of the variables has positive significant relationship with the dependent variables
and it shows if the unemployment and inflation sustain up to specified limit
than the stock price will increase. If it will not sustain from its specified
limit than the stock price will decrease.
Summary of the results of
the impact of monetary policy on stock markets of Japan, USA and UK
The results are analyzed by using
the E-views because this tool is
also used for model simulations and generating forecast. There are four constructs that are chosen as
variables in this study and these are; inflation,
output gap, unemployment and IT. IT is dependent variable meanwhile the
remaining three are independent variables. It is one of the ideal packages to
efficiently and quickly managing data. The equation of the regression is used
as the empirical strategy in this study. All of tests are conducted by using
the VAR and SVAR model of regression. Firstly, the stationary test is applied
to measure the effectiveness and authentication of the data. This tests tells
about either regression can be applied on the particular data or not. All of
the values are shown as significant because these are less than 0.05 which
shows data is reliable for regression and cross correlation analysis.
The effects of monetary policy on
Stock markets are measured by generating the trends line among the time (years)
and values. The scale is set out with the difference of 2. All of the trends
lines are not constant because the fluctuation is existed in these trends
lines. There is gradual fluctuation occurs in the inflation rate of the Japan
during 1994 to 2018 but in 2009 it reached at -2 which shows the bad conditions
of Japan and it was due to 2008 FED crisis. In 2009 there were abrupt
fluctuations and the value of output Gap reached at -3 than it reached at -1.6
in 2010 in United Kingdom.
In 2009 there were abrupt
fluctuations and the value of output Gap reached at -3. The regression results shows the positive
relationship of dependent and independent variables as; there is positive relationship among monetary policy and stick market
price in Japan and the level of significance for two variables are less than
0.05 meanwhile for 0.9485 for inflation rate. It means inflation rate has
positive insignificant relationship with the IT. The results are concluded by
the data of Japan all of the variables has positive significant relationship
with IT meanwhile according to the financial report of USA output gap and
unemployment have negative and inflation has positive significant relationship.
According to the financial report of UK Inflation rate have significant
negative relationship with IT.
The
Wald Test is conducted to measure the probability of data. It is indicated by
the low probability value which is 0.000 that the null hypothesis is strongly
rejected because it is equal to 0.5. Such kind of the results can carefully
accept without any extra analysis. The null hypothesis is strongly rejected
because it is equal to 0.5 for the data of all countries. The residual
and the actual graphs have shown the abrupt fluctuations at certain points. For
the year 2003, residual value got decreased and reached to a negative value
(-1) from 2. The fluctuation to the values of market shares is slow for every
of the year. Chow test is helping to determine the existence of the break
points in the study data. For every test that is a part of break-point, F-Test
value is the same. The value of F-statistics is change for every Country
(Japan, UK and USA).
References of the impact of
monetary policy on stock markets of Japan, USA and UK
Caggiano, G. C. E. &. G. N., 2014. Uncertainty
shocks and unemployment dynamics in US recessions.. Journal of Monetary
Economics, 67(1), pp. 78-92..
Chuku,
C. A., 2009. Measuring the effects of monetary policy innovations in Nigeria: A
structural vector autoregressive (SVAR) approach.. African Journal of
Accounting, Economics, Finance and Banking Research, 5(5).
De
Maio, A. &. I. S., 2008. Coincidence of the Rao test, Wald test, and GLRT
in partially homogeneous environment.. IEEE Signal Processing Letters, 15, ,
pp. 385-388..
Eviews,
2019. An Introduction to EViews. [Online]
Available at: https://www.eviews.com/home.html
Gambacorta,
L. H. B. &. P. G., 2014. The effectiveness of unconventional monetary
policy at the zero lower bound: A cross‐country analysis.. Journal of Money,
Credit and Banking, 46(4), pp. 615-642..
Gregoriou,
A. K. A. M. R. &. M. A., 2009. Monetary policy shocks and stock returns: evidence
from the British market.. Financial Markets and Portfolio Management,, 23(4),
pp. 401-410.
Ioannidis,
C. &. K. A., 2008. The impact of monetary policy on stock prices. Journal
of policy modeling, 30(1), pp. 33-53..
Kerongo
Maatwa Meshack, M. W. N., 2016. THE EFFECT OF MONETARY POLICY ON FINANCIAL
PERFORMANCE OF THE COMMERCIAL BANKS LISTED ON THE NAIROBI SECURITIES EXCHANGE. International
Journal of Finance and Accounting, Vol.1(1), pp. 74 - 87,.
Kibbe,
M., 2011. The Federal Reserve Deserves Blame For The Financial Crisis, s.l.:
forbes.
Kurihara,
Y., 2006. The relationship between exchange rate and stock prices during the
quantitative easing policy in Japan.. International Journal of Business, 11(4),
p. 375..
Lee,
C. C. L. J. D. &. L. C. C., 2010. Stock prices and the efficient market
hypothesis: Evidence from a panel stationary test with structural breaks.. Japan
and the world economy, 22(1), pp. 49-58..
Miyao,
R., 2002. The effects of monetary policy in Japan.. Journal of Money, Credit
and Banking,, pp. 376-392..
Roy,
A. G., 2012. US Foreign Indebtedness, Monetary Policy, and Economic Growth.. Journal
of Economic & Management Perspectives, 6(2), pp. , 196.