Chapter 4

Datas Analysis

4.0: Introduction

In this chapter, I will analysis all the results from the trial that I apply for this research paper. This research consist twosome of trials that are conducted in order to prove the goodness of tantrum of the theoretical account. It is ca n’t be denied that, the variableness of export monetary value of rough palm oil Malaysia is really of import to Malaysia state ‘s economic system, as Malaysia is the 2nd largest exporter of Crude Palm Oil ( CPO ) in the universe. Therefore, look intoing the impact of involvement rate, exchange rate and petroleum oil monetary value towards export monetary value of CPO Malaysia is necessary because it might impact Malaysia ‘s GDP growing and besides many related sectors which have to a great extent dependent on the usage of rough palm oil.

The aims of this research paper are to analyze the impact of the petroleum oil monetary values and economic variables towards Malaysia Palm Oil market with apply VECM and Granger Causality trial by E-VIEWS package. VECM is an method to prove the long term and short term relationship between the independent variables and dependent variables, whereas Granger causality trial was a statistical construct on predict the causality relation between two variables.

4.1: Unit of measurement Root Test

H0: I? = 0 ( There is unit root )

Hour angle: I? & lt ; 0 ( There is no unit root )

First, in order to gauge and develop a theoretical account, we have to look into whether the clip series is contains unit root ( non-stationary ) or no unit root ( stationary ) . Gujarat ( 2003 ) , Enders ( 2004 ) , Pindyck and Rubinfeld ( 1998 ) proposed that most of the clip series variables were non-stationary ( contains unit root ) , with non changeless mean and discrepancy. A series was stationary indicates it ‘s average and auto-covariance do non depended on clip. Time series informations that are non-stationary can leaded to specious arrested development consequence. Box and Jenkins ( 1970 ) proposed that incorporate clip series should be transformed into stationary by differencing before used modellization. Hence, the pre-requirement for arrested development analysis is to taking unit roots. During this research paper, the Augmented Dickey-Fuller ( ADF ) and Phillips-Perron ( PP ) Trials are utilised to find whether the clip series are stationary or non stationary. The Table 2 as below is the results of the unit root trial ( ADF & A ; PP trial ) for all the variables of this research paper.

Table 2: Summary of Unit Root Test Results for All Variables

Seriess

ADF Test

PP Test

Degree

1st Difference

Degree

1st Difference

CPO

-1.6860

-11.7859 ***

-1.4296

-16.5917 ***

Bull

-1.5996

-9.4752 ***

-1.4078

-9.4282 ***

Erbium

-2.3198

-14.5476 ***

-2.283507

-14.5763 ***

Iridium

-1.8749

-7.0636 ***

-1.800291

-10.2398 ***

Note: *** Statistically significance at 0.01 degree

** Statistically significance at 0.05 degree

* Statistically significance at 0.10 degree

As shown on the Table 2, the clip series for all the variables are contains unit root ( non-stationary ) in flat term on both ADF Test and PP Test. It is because the ADF and PP test statistic value for all the clip series are greater than the “ Mackinon critical values ” at all three degree, and besides the p-value show that the ADF and PP test statistic is non statistically important at 0.05 degrees. Therefore, do non reject void hypothesis, the variables CPO, COP, ER, and IR are contains unit root and the clip series are non stationary in degree.

Once we found that all the variables are non stationary in degree, so we go for the unit root trial for all variables in their first difference degree. Harmonizing to the consequences indicates on the Table 2, it shows that all the variables clip series are no contain unit root ( stationary ) on the first difference degree. It is because the ADF and PP test statistic value for all the clip series are smaller than the “ Mackinon critical values ” at all three degree, and besides the p-value show that the ADF and PP test statistic is statistically important at 0.01 degrees. Hence, reject the void hypothesis. In conclude, the variables CPO, COP, ER, and IR are no contains unit root and the clip series are stationary in the first difference degree. When this demand has been met, the petroleum oil monetary values, involvement rate, exchange rate and export monetary value of rough palm oil are said to be co-integrated. The motions of these independent variables and dependent variable are shown in Figure 3.0

Figure 3.0: Co-integration between independent variables and dependant variable

4.2: Johansen Co-integration Rank Test

Determination of optimum slowdown

First of all, in order to execute Johansen co-integration rank trial, we have to choose the optimum slowdown before proceed to the co-integration trial. Harmonizing to the tabular array 3 below, it indicates that the optimum slowdown for the theoretical account is lag 2. The optimum slowdown length be chosen are base on the lowest AIC standard. The critical values used in this trial are 0.05.

Table 3: Summary of Lag Length Selection

A Lag

LogL

Lawrencium

FPE

AIC

Scandium

Headquarters

0

A 27.83757

NAA

A 9.25e-06

-0.239574

-0.173376

-0.212782

1

A 1249.216

A 2381.381

A 5.07e-11

-12.35393

A -12.02294*

A -12.21997*

2

A 1272.524

A 44.50729

A A 4.71e-11*

A -12.42737*

-11.83160

-12.18625

3

A 1286.624

A A 26.35846*

A 4.80e-11

-12.40828

-11.54772

-12.05999

4

A 1292.300

A 10.38249

A 5.33e-11

-12.30452

-11.17917

-11.84906

A * indicates lag order selected by the standard

Johansen Co-integration Test

H0: The variables are non co-integrated.

Hour angle: The variables are co-integrated.

Engle and Granger ( 1987 ) proposed that a additive combination of two or more non stationary series might be stationary. When there is a stationary additive presence, the non-stationary clip series were said to be co-integration. The long term relationship between the variables can be interpreted by the co-integration equation which it called as stationary additive combination. Co-integration rank is estimated utilizing Johansen methodological analysis. Johansen ‘s attack derives two likeliness calculators for the CI rank: a hint trial and a maximal Eigen value trial. The results of Trace and Max-eigenvalue statistics for proving the co-integration between the variables export monetary value of rough palm oil Malaysia ( LN_CPO ) , rough oil monetary values ( LN_COP ) , exchange Rate ( LN_ER ) and involvement rate ( LN_IR ) are shown in the Table 4.

Table 4: Johansen Co-integration Rank Test Results

Unrestricted Cointegration Rank Test ( Trace )

Hypothesized

Trace

0.05

No. of CE ( s )

Eigenvalue

Statistic

Critical Value

Prob. **

None *

A 0.111095

A 66.91048

A 63.87610

A 0.0272

At most 1 *

A 0.088841

A 43.35756

A 42.91525

A 0.0451

At most 2

A 0.072276

A 24.75000

A 25.87211

A 0.0685

At most 3

A 0.047561

A 9.745895

A 12.51798

A 0.1392

A Trace trial indicates 2 cointegrating eqn ( s ) at the 0.05 degree

Unrestricted Cointegration Rank Test ( Maximum Eigenvalue )

Hypothesized

Max-Eigen

0.05

No. of CE ( s )

Eigenvalue

Statistic

Critical Value

Prob. **

None

A 0.111095

A 23.55292

A 32.11832

A 0.3789

At most 1

A 0.088841

A 18.60756

A 25.82321

A 0.3324

At most 2

A 0.072276

A 15.00411

A 19.38704

A 0.1934

At most 3

A 0.047561

A 9.745895

A 12.51798

A 0.1392

A Max-eigenvalue trial indicates no cointegration at the 0.05 degree

Assuming for additive deterministic with intercept, tendency in CE and no tendency in VAR, the Trace statistic value of 66.91 and 43.36 at none and at most one co-integration are greater than its critical value of 63.88 and 42.92. Therefore, harmonizing to the Trace statistic consequences, we need to reject void hypothesis and conclude that the Trace Test indicates there is 2 co-integrating equation with statistically significance at 0.05 degree. Besides, it besides means that the long-run equilibrium between the variables were met and the variable are co-integrated.

However, the Max-Eigen statistic value of 23.55, 18.61, 15.00 and 9.75 at none, at most one, at most two and at most three co-integration are smaller than its critical value of 32.12, 25.82, 19.39 and 12.52. Therefore, base on the Max-Eigen statistic consequences, we do non reject void hypothesis and conclude that the Max-Eigen trial indicates there is no co-integrating equation with statistically significance at 0.05 degree. Furthermore, it besides indicates that the long term equilibrium between variable were non met and the variable are no cointegrated.

Although the Max-Eigen statistic value indicates there is no co-integrating equation, but the Trace statistic value had indicates that there is 2 co-integrating equation. Hence, we could reason that there is co-integration between the independent variables and dependent variables. Once there is co-integration among variables, the VECM theoretical account can be conducted.

4.3: Vector Error Correction Model ( VECM )

VECM was a method developed to use in non-stationary informations that presence co-integration relationship ( Gilbert, 1986 ) ( Henry and Ericsson, 2001 ) . The existed of co-integration between variables indicates a long term relationship among the variables under consideration. Therefore, VECM is conducted for future analysis on the long-run and short-run relationship between independent variables and dependent variables. An optimum slowdown interval of 1 1 is apply in this method. The Table 5 as below shows the result of the VECM appraisal for the export monetary value of Crude Palm Oil Malaysia theoretical account.

As shown in the Table 5, the results shows that the Crude Oil Price ( LN_COP ) , Exchange Rate ( LN_ER ) , and Interest Rate ( LN_IR ) are accounted about 11.02 % of short term Export monetary value of Crude Palm Oil Malaysia ( LN_CPO ) in VECM equation. Furthermore, the VECM appraisals besides reveal that the explanatory variables viz. Crude Oil Prices ( LN_COPt-1 ) , and Export monetary value of Crude Palm Oil Malaysia ( LN_CPOt-1 ) in previous/ lag period were the most of import variables that influence the current month export monetary value of rough palm oil Malaysia in short term at important degree of 0.10 and 0.05 degree severally. However, the explanatory variables viz. exchange rate ( LN_ERt-1 ) and involvement rate ( LN_IR t-1 ) in the previous/lag period were non the most of import variables that affect the export monetary value of rough palm oil Malaysia ( LN_CPOt ) in short term, as their p-value are non statistically significance at 0.10 degree

On the other manus, harmonizing to the LN_CPO co-integration equation, International Crude Oil Price ( LN_COPt-1 ) in previous/lag period exerted positive influence in long term export monetary value of rough palm oil Malaysia at important degree of 0.05. However, the Interest Rate ( LN_IR t-1 ) exerted negative influence in long term export monetary value of rough palm oil Malaysia at important degree at 0.10. Furthermore, harmonizing to the consequence shown in Table 5, the explanatory variables viz. exchange rate ( LN_ER t-1 ) in the previous/lag period does n’t non exerted either positive and negative influence in the export monetary value of rough palm oil Malaysia in long term, as it ‘s p-value is non statistically significance at the 0.10 degree.

VECM equation of Export Price of Crude Palm Oil Malaysia ( LN_CPO ) theoretical account:

LN_CPOt = 0.00866 + 0.1978 LN_COPt-1 + 0.2251 LN_ERt-1 – 5.2583 LN_IRt-1 –

t-statistic = [ 1.8521* ] [ 0.7267 ] [ -0.1178 ]

0.0420 LN_CPOt-1 – 0.0087Et

[ -3.7615** ] [ 0.9651 ]

R2 = 0.1102 Adj. R2 = 0.0874

Co-integration equation for Export Price of Crude Palm Oil Malaysia ( LN_CPO ) theoretical account:

-0.0550 LN_CPOt-1 + 0.0478 LN_COP t-1 – 0.0046 LN_ERt-1 – 0.0092 LN_IRt-1 = 0

[ -2.2874** ] [ 3.0182** ] [ -0.8178 ] [ -1.9157* ]

Table 5: VECM Test Results ( LN_CPO )

Mistake Correction:

D ( LN_CPO_ )

D ( LN_COP_ )

D ( LN_ER_ )

D ( LN_IR_ )

CointEq1

-0.055006

A 0.047830

-0.004594

-0.009221

A ( 0.02409 )

A ( 0.01585 )

A ( 0.00562 )

A ( 0.00481 )

[ -2.28373 ]

[ 3.01821 ]

[ -0.81780 ]

[ -1.91569 ]

D ( LN_CPO_ ( -1 ) )

-0.260771

-0.005792

-0.002886

-0.025874

A ( 0.06933 )

A ( 0.04561 )

A ( 0.01617 )

A ( 0.01385 )

[ -3.76153 ]

[ -0.12698 ]

[ -0.17849 ]

[ -1.86768 ]

D ( LN_COP_ ( -1 ) )

A 0.197828

A 0.245905

-0.002413

A 0.015411

A ( 0.10681 )

A ( 0.07028 )

A ( 0.02491 )

A ( 0.02135 )

[ 1.85207 ]

[ 3.49902 ]

[ -0.09687 ]

[ 0.72200 ]

D ( LN_ER_ ( -1 ) )

A 0.225100

-0.153126

A 0.039858

-0.112162

A ( 0.30975 )

A ( 0.20380 )

A ( 0.07224 )

A ( 0.06190 )

[ 0.72672 ]

[ -0.75136 ]

[ 0.55176 ]

[ -1.81204 ]

D ( LN_IR_ ( -1 ) )

-0.041978

A 0.456429

A 0.075003

A 0.305977

A ( 0.35638 )

A ( 0.23448 )

A ( 0.08311 )

A ( 0.07122 )

[ -0.11779 ]

[ 1.94656 ]

[ 0.90242 ]

[ 4.29642 ]

C

A 0.008359

A 0.007912

A 0.000983

-0.000764

A ( 0.00866 )

A ( 0.00570 )

A ( 0.00202 )

A ( 0.00173 )

[ 0.96509 ]

[ 1.38834 ]

[ 0.48659 ]

[ -0.44136 ]

A R-squared

A 0.110186

A 0.101158

A 0.014622

A 0.154092

A Adj. R-squared

A 0.087370

A 0.078111

-0.010644

A 0.132402

4.4: Granger Causality Test

Through using the Granger Causality Test, we can foretell the causality relation and way between two variables. Economic theory proves that there is ever Granger Causality in at least one way. The optimum slowdown 2 is chosen in using Granger-Causality Test base on the consequences of Johansen Co-integration Test in subdivision 4.2, Table 3. The Table 6 shown the Pairwise Granger-Causality Test Results for export monetary value of Crude Palm Oil Malaysia ( LN_CPO ) theoretical account.

Table 6: Pairwise Granger-Causality Test Results ( LN_CPO theoretical account )

A Null Hypothesis:

Ob river

F-Statistic

Prob.A

A LN_COP_ does non Granger Cause LN_CPO_

A 201

A 2.74376

0.0668

*

A LN_CPO_ does non Granger Cause LN_COP_

aˆˆ

A 0.30318

0.7388

A LN_ER_ does non Granger Cause LN_CPO_

A 201

A 0.85827

0.4255

A LN_CPO_ does non Granger Cause LN_ER_

aˆˆ

A 1.19396

0.3052

A LN_IR_ does non Granger Cause LN_CPO_

A 201

A 0.23405

0.7915

A LN_CPO_ does non Granger Cause LN_IR_

aˆˆ

A 2.48412

0.0860

*

Base on the Table 6 on above, in the Granger-causality trial, F-statistic of the two variables of Crude Oil Price and export monetary value of Crude Palm Oil Malaysia ( LN_COPi? LN_CPO ) is significance at 0.10 degree, this consequences indicates that the void hypothesis of LN_COP does non Granger-cause LN_CPO should be rejected. Therefore, there is a variable LN_COP “ granger-causes ” a variable LN_CPO. On the other manus, F-statistic of the two variables LN_CPO i? LN_COP is non significance at 0.10 degree, this indicates that the void hypothesis of LN_CPO does non Granger-cause LN_COP should non be rejected. Therefore, the way of a Granger causality relationship of LN_COP and LN_CPO is uni-direction ( LN_COP i? LN_CPO ) . Then, there is co-integrated and besides a long term equilibrium relationship between the two variables of Crude Oil Price ( LN_COP ) and export monetary value of Crude Palm Oil Malaysia ( LN_CPO ) .

Furthermore, in the Engle-Granger trial, F-statistic of the two variables of Interest Rate and export monetary value of Crude Palm Oil Malaysia ( LN_IRi? LN_CPO ) is non significance at 0.10 degree, this consequences indicates that the void hypothesis of LN_IR does non Granger-cause LN_CPO should non be rejected. However, the F-statistic of the two variables LN_CPOi? LN_IR is significance at 0.10 degree, it indicates that the void hypothesis of LN_CPO does non Granger-cause LN_IR should be rejected. Therefore, there is a variable LN_CPO “ granger-cause ” a variable LN_IR, and the way of a Granger causality relationship of LN_CPO and LN_IR is uni-direction ( LN_CPOi? LN_IR ) . In conclude, there is co-integrated and besides a long term equilibrium relationship between the two variables of LN_CPO and LN_IR.

However, the F-statistic of the two variables of Exchange Rate and export monetary value of Crude Palm Oil Malaysia ( LN_ERi? LN_CPO ) and LN_CPOi? LN_ER both are non significance at 0.10 degree. There is besides non a variable LN_ER “ Granger-causes ” a variable LN_CPO. Therefore, there is no co-integrated and besides no long-run equilibrium relationship between the two variable LN_ER and LN_CPO.