THE MACROECONOMIC DETERMINANTS TO THE CRUDE PALM OIL PRICES IN MALAYSIA

(1987 - 2008)

HONEY IRMAWATI BINTI HAMZAH 2003197753

BACHELOR OF BUSINESS ADMINISTRATION WITH HONOURS (BUSINESS ECONOMICS)

FACULTY OF BUSINESS MANAGEMENT UNIVERSITI TEKNOLOGI MARA

SHAH ALAM

NOVEMBER 2008

THE MACROECONOMIC DETERMINANTS TO THE CRUDE PALM OIL PRICES IN MALAYSIA

SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS OF

BBA (HONS) BUSINESS ECONOMICS

FACULTY OF BUSINESS MANAGEMENT

UiTM, SHAH ALAM

HONEY IRMAWATI BINTI HAMZAH

NOVEMBER 2008

DECLARATION OF ORIGINAL WORK

BACHELOR IN BUSINESS ADMINISTRATION (HONS) BUSINESS ECONOMICS

FACULTY OF BUSINESS MANAGEMENT

UNIVERSITI TEKNOLOGI MARA

I, HONEY IRMAWATI BINTI HAMZAH, (I/C NUMBER: 780714015248)

Hereby, declare that:

- This work has not previously been accepted in substance for any degree,

locally or oversea, and is not being concurrently submitted for this degree

or any other degrees.

- This project is the result of my independent work and investigation,

except where otherwise stated.

- All verbatim extracts has been distinguished by quotation marks and

sources of my information have been specifically and acknowledged.

Signature: Date:

(Honey Irmawati Binti Hamzah)

LETTER OF SUBMISSION

Honey Irmawati Binti Hamzah, BBA (Hons) Business Economics, Faculty of Business Management, Universiti Teknologi MARA, 40450 Shah Alam, Selangor Darul Ehsan. 20th November 2008 Puan Norizan Binti Mohammad Faculty of Business Management, University Technology of MARA, 40000 Shah Alam, Selangor Darul Ehsan. Dear Miss, Submission of Project Paper Enclosed is a report entitled “The Macroeconomic Determinants to the Crude Palm Oil Price in Malaysia” for your kind progression. I hope that my research report fulfills the requirement stated by Faculty of Business Management, Universiti Teknologi MARA (UiTM), Shah Alam. I would very much appreciate your kind understanding in reviewing my research report. Thank You, Yours Sincerely, ……………………………………. (Honey Irmawati Binti Hamzah) 2003197753 BBA (Hons.) BUSINESS ECONOMICS

IV

ACKNOWLEGDEMENT

ALHAMDULILLAH, in the name of ALLAH the All Mighty, the Most Compassionate, the Most

Merciful and Most Gracious, Praise to Allah, the One and Only, for giving me patience,

strength and ability to complete this project.

First and foremost, the author would like to express a million thanks to the Director-General

of Malaysian Palm Oil Board, Dato’ Dr. Mohd Basri Wahid for giving me a chance to

continuing my study as a fulltime student. Appreciation and gratitude are due to the Acting

Director of Economic and Industry Development Division, Dr. Faizah Mohd Shariff and Head

of Techno-Economic Unit, Encik Mohd Arif Simeh. The authors would like to thank the all

members of Techno-Economic Unit for their constructive ideas and comments.

This project could not have been written without the advisor of this research, Puan Norizan

Mohammad who not only served as the advisor of the project but also encouraged and

challenged the authors throughout the study. Also, Puan Jamaliah Mhd Khalili as a second

examiner and the other group members, who was patiently guided through the writing

process, never accepting less than the author best efforts.

Last but not least, thanks are due to Mohd Musa Sotiri, Adam Harith and Arissa Nurhawa for

their support and prayers.

Honey Irmawati Binti Hamzah

NOVEMBER 2008

V

TABLE OF CONTENTS

PAGE

ACKNOWLEGDEMENT IV

LIST OF TABLES V

LIST OF FIGURES VI

LIST OF ABBREVIATIONS VII

LIST OF DEFINITIONS OF TERMS VIII

ABSTRACT IX

CHAPTERS

1 INTRODUCTION 1

1.1 Background of the Study 1

1.2 Problem Statement 4

1.3 Research Objectives 5

1.4 Significance of the Study 6

1.5 Research Question 6

1.6 Limitations 6

1.7 Scope of the Study 7

1.8 Definition of Term 8

1.8.1 Definitions for Crude Palm Oil 8

1.8.2 Definition for Exports 9

1.8.3 Definitions for Exchange Rate 9

1.8.4 Definitions for Consumer Price Index 10

1.8.5 Definitions for Price 10

VI

2 LITERATURE REVIEW 11

2.1 Introduction 11

2.2 Findings of Price of Crude Palm Oil 12

3 RESEARCH DESIGN AND METHODOLOGHY 16

3.1 Data and Source of Data 16

3.2 Theoretical Framework 17

3.3 Variable 18

3.4 Sample Size 19

3.5 Research Design 19

3.5.1 Type and nature of the study 19

3.5.2 Data Analytical Technique Used 19

3.6 Methodology 20

3.6.1 Multiple Regression Analysis 20

3.6.2 Regression Model 21

3.6.3 Statistical Test 21

3.6.4 Analysis of the Regression 22

3.6.5 Research Hypotheses 23

4 RESULT OF DATA ANALYSIS 24

4.1 Problem in Multiple Regression Analysis 25

4.1.1 Multicollinearity 25

4.1.1.1 The Consequences of Multicollinearity 26

4.1.1.2 The Detection of Multicollinearity 26

VII

4.1.2 Serial Correlation 27

4.1.2.1 The Consequences of Serial Correlation 27

4.1.2.2 The Detection of Serial Correlation 28

4.2 Hypothesis Testing 30

4.2.1 The t-test 30

4.2.2 The F-test 32

4.3 Interpretation of the Result 33

5 CONCLUSIONS AND RECOMENDATIONS 34

5.1 Conclusions 34

5.2 Recommendations 35

REFERENCES

APPENDICES

APPENDIX 1 Table of Data

APPENDIX 2 Result from E-Views

APPENDIX 3 Result from SPSS

APPENDIX 4 Line Graphs of the Variables

APPENDIX 5 Durbin Watson Table

APPENDIX 6 Student’s t Distribution

APPENDIX 7 Critical Values of the F distribution at a 5 Percent

Significance Level

VIII

LIST OF TABLES

Table 1 Gross Export Performance for 2006 and 2007 2

Table 2 Movements of Ringgit 3

Table 3 Results for E-Views 24

Table 4 The VIF of the Coefficients 27

Table 5 The Decision Rules of Durbin – Watson Statistic 29

Table 6 The t-Value of the Variable 31

Table 7 The F-Statistic of the Overall Variable 32

IX

LIST OF FIGURES

Figure 1 Crude Palm Oil Price Movement from 1980 until 2007 (RM/Tonne) 5

Figure 2 The Schematic Diagram 17

Figure 3 Durbin – Watson d Statistic 30

X

LIST OF ABBREVIATIONS

MPIC Ministry of Plantation Industries and Commodities

MPOB Malaysian Palm Oil Board

IMF International Monetary Fund

DW Durbin Watson

Ho Null Hypothesis

Ha Alternative Hypothesis

OLS Ordinary Least Square

R² Coefficient of Determination

RM Ringgit Malaysia

USD US dollar

SPSS Statistical Package for Social Science

U.S United States

VIF Variance Inflation Factors

CPO Crude Palm Oil

CPI Consumer Price Index

ANOVA Analysis of Variance

XI

LIST OF DEFINITIONS OF TERMS

Definitions for Crude Palm Oil

Definitions for Exports

Definitions for Exchange Rate

Definitions for Consumer Price Index

Definition for Price

XII

ABSTRACT

The main objective of this study is to explore different influences of crude palm oil price

fluctuations to the economic growth in Malaysia. The other objective is to determine the main

effects of the price fluctuations. The data for this study were obtained from the publications of

Ministry of Plantation Industries and Commodities, Malaysian Palm Oil Board and International

Monetary Fund. The data covered the period of 1980 to 2007. The macroeconomics variables

that impact the fluctuations of palm oil price are exchange rate; export value of palm oil and

consumer price index. The most significant factor that contributes to the fluctuation of CPO

price is exporting value of palm oil. Therefore, the variability of the price of CPO may impact the

economy growth of the country in terms of trade balance.

1

CHAPTER 1

INTRODUCTION

1.1 BACKGROUND OF THE STUDY

Malaysia’s fifty one years of nationhood marks another milestone in its economic

development. Upon independence, the nation was highly reliant on tin and rubber and more

than half of the populations were in poverty. Today, Malaysia’s achievements in their broad-

based and diversified economy have contributed growth to the economy.

At present, Malaysia is not only the largest producer and exporter of palm oil, but also

the biggest exporter of oils and fats in the world. The Malaysian oil palm industry continues to

contribute significantly to the country's economic development.

Under the 9th Malaysian Plan (RMK 9, 2006-2010), the agricultural sector will be the

third engine of growth for the economy, after the manufacturing and services sector. The

agriculture sector is targeted to grow at five to six per cent during RMK 9 with significant

contribution from the oil palm, rubber, cocoa, timber, and pepper.

Plantation industries and commodities remain an important sub-sector of the

agricultural sector contributing five per cent to the GDP and providing employment

opportunities to 1.5 million people. Its contribution to the country’s export earnings averaged

RM60 billion per annum during the period under review (2001 to January-June 2005). The

development of the plantation industries and commodities sector will continue to be given

emphasis in other national development plans such as the Outline Perspective Plan 3

(OPP3, 2001-2010), National Agricultural Policy (NAP), and Third Industrial Master Plan

(IMP3, 2006- 2015).

The gross exports strengthened by 7.5% in the fourth quarter of 2007 (3Q: 0.9%)

due, mainly to the marked increase in commodity exports amidst the substantial rise in

2

commodity prices. See table 1 below. The above also contributed to the strong growth in

agriculture exports by 25.0% in the year 2007.

Table 1: Gross Export Performance for 2006 and 2007

2006 2007

4Q Year 3Q 4Q Year

Annual Change (%)

Gross Exports 6.6 10.3 0.9 7.5 2.7

Manufacturing 5.7 107.0 -2.0 2.9 0.3

Agriculture 22.1 12.5 29.9 40.2 25.0

Minerals 0.5 8.6 6.6 23.6 8.1

Source: Department of Statistics, Malaysia

Majority of the increase in the agricultural export is due to exceptionally excellent

performance in receipts from palm oil exports (66.2%) combined with rising in prices. Palm

oil prices strengthened to RM2,530.50 per tonne, representing an increase of more than

RM1,000 in comparison to the corresponding period in 2006.

The export earnings of the primary commodities recorded an excellent performance in

2007 with total export earnings recorded at RM89.6 billion as in comparison to RM76.05

billion in 2006 comprised of the exports value of palm oil, rubber products, cocoa and cocoa

products, tobacco and pepper which were caused by higher commodities prices during the

year. The rise in commodities prices had also increased the revenue for the plantation

companies and provided remunerative income for the smallholder.

The year 2007 remarks, the upward trend of the ringgit exchange rate against US

dollar. The upward ringgit pressure was, to a certain extent, balanced by the demand for

foreign currencies to fund larger outward direct and portfolio investment, repayment and

prepayment of external loans by both the public and private sectors and the repatriation of

profits and dividends by non-residents. The strengthening of the ringgit was also punctuated

3

by several external events during the year, such as the global equity correction in the first

quarter and the global financial disruptions following the developments in the US housing

market in the third quarter, which has been restraining effect on regional currencies,

including ringgit. The upward trend in the ringgit however, disrupted by the withdrawals of

funds from the region following the correction in the Shanghai equity market in February, and

US sub-prime mortgage crisis, particularly in the period of June until September in the same

year. These disruptions proved to be temporary as the ringgit resumed its appreciating trend,

arising from the positive investor sentiment towards the Malaysian economy. For the year

2007, the ringgit appreciated by 6.8% against the US dollar to end of the year at the dollar

exchange rate of RM3.3065. The performance of ringgit exhibited a mixed performance

against other major currencies, appreciating against the Japanese yen (0.5%), but

depreciating against the euro (-4.7%). See table 2 below. The euro strengthened due to

market expectations of a widening interest rate differential in its favour.

Table 2: Movements of the Ringgit

RM to one unit of foreign currency Annual change (%)

2006 2007 2007

US dollar 3.5315 3.3065 6.8

100 Japanese yen 2.9675 2.9534 0.5

Euro 4.640 4.8756 -4.7

Source: Bank Negara Malaysia

The competitiveness of palm oil in the international market is influenced by exchange

rate regime in exporting countries. With the introduction of fixed exchange rate in Malaysia

since 1 September 1999, the Malaysian Ringgit (RM) depreciated by 34.3% in comparison to

the pre crisis level of RM2.50 = US$1. The claim that the fixed exchange rate between ringgit

4

and US dollar has made Malaysian palm oil competitiveness among other low cost producers

on account of exchange rate variations is yet to be proven.

However, inflation as measured by annual percentage change in the Consumer Price

Index (CPI) in the first seven months of 2007 eased significantly to2.0% (January – July 2006

: 3.6%), due to better supply conditions, keen competition, effective price monitoring as well

as strengthening of ringgit. The increase in CPI was largely due to higher prices of food and

non-alcoholic beverages, transport, rental and utilities. This group accounted for 87.4% of the

total increase in CPI.

1.2 PROBLEM STATEMENT

Malaysian palm oil is subjected to have significant price fluctuations. The palm oil

prices fluctuated without any clear trend or cyclical pattern in the last three decades. This has

been giving an impact towards the growth of the economy of Malaysia. The average price of

oil palm products in the domestic market rose sharply in 2007. The prices have risen sharply

by more than 67% over the past year. The sharp rises of CPO prices pose serious

challenges to the growth of the economy in the country. Refer to chart 1 below.

Therefore, it is important to know the impact of the variability changes in prices to the

Malaysian economic growth. This study also intends to investigate the macroeconomics

effects of the price variability in crude palm oil in Malaysia.

5

Chart 1: Crude Palm Oil Price Movement from 1980 until 2007 (RM/Tonne)

Source: Malaysian Palm Oil Board

The problem statement for this study is to look at the factors that influence the trend

of CPO price. Based on the preliminary study that has been done, the main macroeconomics

factors that contribute to the change in CPO price are export earnings, exchange rate and

consumer prices index.

1.3 RESEARCH OBJECTIVES

It is important to establish the flow of the study by highlighting its purpose. There are two (2)

objectives to this study.

The primary objective of this study is to explore different influences of the fluctuations

of crude palm oil price to the economic growth in Malaysia.

The secondary objective of this study is to identify the main cause(s) of crude palm oil

prices fluctuations.

6

1.4 SIGNIFICANCE OF THE STUDY

The significance of this study is to define the relationship of the variable in macroeconomics

with crude palm oil prices.

This research will investigate the influences of crude palm oil prices to the

macroeconomic variables in Malaysia. This study aims to remedy the scarcity of studies

regarding the influences of crude palm oil price to the nation's economic growth.

This research will also analyze the trend of CPO price. Thus, enabling the

government, exporters and also shareholders to forecast the price and make the most out of

economic decisions, specifically in contributing to the profit maximization of the firm while

ensuring growth of the country.

1.5 RESEARCH QUESTIONS

Specifically, the study is set to answer of the following questions:

1. How crude palm oil prices are determined?

2. What is the most significant variable to determine crude palm oil price?

1.6 LIMITATIONS

The study has certain limitations that need to be taken into account when considering the

study and its contributions.

This study has focused on a phenomenon that is a very extensive and major, which is in

the macroeconomic variable. Clearly, this represents a challenging task for research

7

regardless of the more specific interests that the study may have. In this study, the wide

knowledge and understanding about the macroeconomic perspective is much needed. It is

very essential to study its theory to have more supportive result and build of theoretical

framework. On the other hand, this also represents the whole idea of making a research. By

understanding something about this more in depth, we also can learn more bout it in a

practical view. Such as, the contribution of palm oil towards the industry of agriculture to the

growth of the country.

More specifically, they are also limitations of the data availability. For example, CPI

inflation rate is only available for the year 1980 until current. The sample size for the CPI is

particularly small. A small sample size has a greater probability that the observation just

happened to be particularly good or particularly bad. Therefore, it is harder to find significant

relationships from the data, as statistical tests normally require a larger sample size to justify

the hypothesis that the effect did not just happen by chance alone.

As a conclusion, some of these limitations can be seen as fruitful avenues for future

research under the same theme. It is highly interesting needed to see the results of such a

study.

1.7 SCOPE OF THE STUDY

The prices of CPO used in the analysis were obtained from 1980 to2007, spanning a 27 year

period. There are three (3) important aspects that will be focused on:-

- Factors that have impact of the fluctuations in the price of CPO.

- The modeling of the multiple regression

- The analysis of the most important factor in determining the fluctuations of the price

of CPO.

8

In this research, there is an abstract that explain the background of the study as well as

the general objective of this study. The results from the finding are based on the overall

objective in this study.

To evaluate the findings this study has to include the background of the study,

problem statement, the objective and overall significance of the research.

The method that has been used to evaluate the findings along with the sketch of

schematic diagram of dependent, and independent variable are explained through the

theoretical framework.

In establishing the relationship between the dependent and independent variables we

have developed the three hypotheses that engaged in the course of the study.

The data used in this research is secondary data. From the data collected, E-views

and SPSS are vital to regress and develop a statistical relation from the data. They have

provided sophisticated data analysis, regression and forecasting tools on Windows-based

computers.

Result of data analysis will discussed based on the result where the interpretation of

R2, t-test, Durbin Watson and F-test had been interpreted.

1.8 DEFINITION OF TERMS

1.8.1 DEFINITIONS FOR CRUDE PALM OIL

From the http://www.thefreedictionary.com/palm+oil palm oil is yellowish fatty oil obtained

especially from the crushed nuts of an African palm (Elaeis Guineensis) and used in the

manufacture of soaps, chocolates, cosmetics, and candles. It is also known that palm oil

history was long recognized in West African countries, and among West African people it is

in widespread use as cooking oil. European merchants trading with West Africa occasionally

9

purchased palm oil for use in Europe, but as the oil were bulky and cheap, and due to the

much higher profits available from slave-trading, palm oil remained rare outside West Africa

from http://www.answers.com/topic/palm-oil?cat=health.

According to the Wikipedia http://www.answers.com/topic/palm-oil, palm fruit is the source of

both palm oil (extracted from palm fruit) and palm kernel oil (extracted from the fruit seeds).

Babassu oil is extracted from the kernels of the Babassu palm. Palm oil itself is reddish

because it contains a high amount of beta carotene. It is used as cooking oil, to make

margarine and is a component of many processed foods. Boiling it a few minutes destroy the

carotenoids and the oil becomes white. Palm oil is the only vegetable oils relatively high in

saturated fats (such as coconut oil) and thus semi-solid at room temperature.

1.8.2 DEFINITIONS FOR EXPORTS

Exports can be definite as the: 1) actual shipment of any covered goods or items; 2) the

electronic or digital transmission of any covered goods, items or related goods or items; 3)

any release or disclosure, including verbal disclosures or visual inspections, or any

technology, software or technical data to any foreign national; or 4) actual use or application

of covered technology on behalf of or for the benefit of any foreign entity or person anywhere

under the http://www.access.gpo.gov/nara/cfr (EAR)

1.8.3 DEFINITIONS FOR EXCHANGE RATE

Exchange rate can be defined as the rate at which one currency may be converted into

another. Generally, one unit of the home currency is expressed in terms of another currency

under the http://www.investorwords.com/4036/rate_of_exchange.html.

10

1.8.4 DEFINITIONS FOR CONSUMER PRICE INDEX

Consumer price index can be defined as the measure of changes in the purchasing power of

a currency and the rate of inflation. CPI expresses the current prices of a 'basket' of goods

and services in terms of the prices during the same period in a previous year, to show effect

of inflation on purchasing power. Moreover, called cost of living index (COLI), it is one of the

best-known lagging indicators. See also producer price index under

http://www.businessdictionary.com/definition/consumer-price-index-CPI.html

1.8.5 DEFINITION FOR PRICE

The definitions for price can be explained as the amount of money for which anything is

bought, sold or offered for sale under http://pimsleur.english-test.net/definitions/definition-of-

security-struggle-liberal-price.

11

CHAPTER 2

LITERATURE REVIEW

2.1 INTRODUCTION

Economics studies the allocation of scarce productive resources that includes workers,

machines, and land to different productive activities, particularly in factories, offices, farms,

labor, and machinery whose purpose is to generate commodities that will satisfy consumer’s

needs. In brief, economics is hailed as the science of rational choice under conditions of

scarcity (Varoufakis 1998). Therefore, economists have to focus on the way in which

individuals, groups, business enterprises, and government seek to achieve efficiently any

economy objectives or policy they select. It is also trying to explain the behavior of the

economy by building hypotheses or theories. Specific versions of these theories are

sometimes referred to as economics models. These models are implications of the real world

that are potentially useful in illustrating some key feature of how the world works.

As well as, macroeconomics is looking at the output of the economy as a whole and is

concerned with aggregate questions relating to inflation, unemployment, the balance of

payments, and business cycles. In macroeconomics, the value of all other goods and

services produce is averaged together. This results into studying the movement of aggregate

national product. The prices of all goods and services consumed are also averaged together

and discuss the general price level for the entire economy.

12

2.2 FINDINGS OF PRICE OF CRUDE PALM OIL

Eduardo, B., et. al (1994) said that the marked fluctuations in commodity prices and

volumes in recent years, a comprehensive analysis of the macroeconomic factors having an

impact on commodity markets becomes an important factor in policy design, particularly for

those countries that rely heavily on primary commodity exports and that are facing

substantial terms – of - trade shocks.

The study done by Mad Nasir S. and Fatimah (1997) said that, in short term, price

movements of fats and oils (including palm oil) mainly reflect changes in weather conditions,

in inventories, in exchange rates, and in the price of substitutes.

Dehn, Jahn (2000) also said that per capita growth rates are significantly reduced by large

discrete negative commodity price shocks.

In the study done by Yusof B. (2002) saw the currency depreciate significantly and this of

course impacted positively on the palm oil industry as prices of palm oil are quoted in US$.

Also study done by Basri and Zaimah (2002) the real prices of Malaysian palm oil was

calculated by deflating nominal prices of Malaysian palm oil by the Malaysian consumer

prices index or CPI (1900=100).

Meanwhile the study done by Wayan R. (2004) has make conclusions that the oil palm has a

significant contribution to economic growth, poverty and alleviation, and equity improvement.

The positive contribution to economic growth is indicated by the growth of investment, output

and foreign exchange earnings. The study also said that the oil palm related industries have

a significant contribution to household welfare in term of income and asset.

13

Mohd Nasir A. et al (2004) said that the export have become significant component in term

of influencing the co-movement in price of palm oil in the market. The study also reveals that

the export is expected to be positive related to the CPO price.

The study done by Mohammad Alias and Tuck Cheong Tang (2005) said that the

significance of the relative price level lends empirical support for some form of price policy.

Even though price determination is left to the forces of supply and demand with minimal

government intervention, an instance of the effect of price policy, through an indirect channel,

can be seen from the response of the industry to the pegging of the ringgit to the US dollar in

September 1998.

Faizah, S et al (2006) said that the price of palm oil the study found that the price of palm oil

plays a very significant role in the short and long – runs. The ECM method was used to

quantify the short-run and long-run effects of the explanatory variables on the dependent

variables.

Basri, et al (2007) said that the domestic price of CPO lagged one year and economic crisis

were significant at 10% level. Any attempt to adjust the domestic CPO price toward its

equilibrium level had a direct effect on the current domestic price of CPO. Furthermore, the

world economic crisis also significantly increased the domestic price of CPO.

Also the study done by Amna A. et al (2007) shows that the palm oil prices as well as the

national income are significant determinants of palm oil demand across the 10 models. The

prices of substitute oils in almost all countries have been found to play an important role in

shaping the palm oil demand. Other factors such as high palm oil discount, the 1970s world

petroleum prices boom, the anti-palm oil campaign, trade embargo on Libya and Iraq, and

14

exchange rate also proved to be important factors affecting import demand for palm oil in

some MENA countries.

Ahmad Borhan, A N et al (2007), said that the palm oil closing stock has been used to

gauge the palm oil market outlook, as it acts as proxy for the underlying supply and demand

fundamentals. The volume of palm oil stock has become a strong psychological factor that

can indicate a bullish or bearish outlook for the industry, presumably under the belief that

stock affects market prices.

Meanwhile study done by Mohd Basri, W et al (2007) said that the spikes in the palm oil

price is mainly due to the demand and supply imbalance of oils and fats especially for

soybean oil. The trends of the price keep arising since mid 2006. The impacts of the trend

are on the consumption, trade, price competitiveness, and investment in oil palm/palm oil

and biodiesel production.

Hence the study done by Ramli, A et al (2007) said that the important of biodiesel as a

renewable fuel have giving an impact towards the price. The demand would reduce the

volume of palm oil available in the market and putting upward pressure on its price and those

of other vegetable oils. The increase in demand for biodiesel has led to its increased

production, thus, requiring additional palm oil. This analysis shows the effect to be positive as

price is increased higher that without any biodiesel demand. The country also benefited

through higher export earnings and higher corporate tax. However, it is not been favorable to

the licensees of biodiesel plants. It has said that it was due to the forecasting of the price of

palm oil remain high in the last few months of 2007 and even higher in 2008 which is making

the economics of producing biodiesel questionable.

15

Study done by Obasi O. Ukoha (2007) said that inflation impacts positively on price

variations among agricultural commodities.

Beside that, other research from Al-Amin et al (2008) said that the import price shocks by

15% decreases the domestic production of building and construction sector by 25.87%,

hotel, restaurant and entertainment sector by 12.04%, industry sector by 12.02%, agriculture

sector by 11.01%, and electricity and gas sector by 9.55% from the baseline. The external

price shocks falls the domestic production and imports in all industry level. Therefore, these

impacts are very sensitive to the importing countries. The import price shock causes the

household income, household consumption and household savings decreases as well as

social welfare. It is also said that causes the decreases in the real GDP, nominal GDP and

government revenue and significant negative impact goes on investment and fixed capital

investment. Malaysia is now experiencing the external price shocks especially on oils

markets. Therefore, the other alternative is they have to use substitute of imported petroleum

and other raw materials in agriculture, industry, transport and utility sectors, which could

stimulate the economy. Additionally the removal of tariff and export tax had improved

domestic production, promotes exports and could mitigate the effects of international price

shocks through increasing competitiveness of the economy. However, this could further been

studied carefully, otherwise it may not benefited at all.

Finally, the study done by Simone Pfuderer and Maria del Castillo (2008) said that the

changes in agricultural prices have historically not been fully reflected in consumer prices.

16

CHAPTER 3

RESEARCH DESIGN AND METHODOLOGHY

3.1 DATA AND SOURCE OF DATA

In this study, secondary data will be incorporated. Secondary data can be used, among other

things, for forecasting prices by constructing models based on past price figures, and through

extrapolation. The secondary sources will come from published articles and numerical and

archival from the government. These and related studies on crude palm oil prices and

economic condition will also be included. The advantage of seeking secondary data sources

is savings in time and costs of acquiring information. However, secondary data as the sole

source of information has the drawback of becoming obsolete, and not meeting the specific

needs of the particular situation. Hence, it is important to refer to.

To achieve the objectives of this study, the data for this study will be collected from the year

1980 until 2007. The type of the data is the time series data.

The sources of the data are taken from various publications by Ministry of Plantation

Industries and Commodities (MPIC), Malaysian Palm Oil Board (MPOB), and International

Monetary Fund (IMF).

17

3.2 THEORETICAL FRAMEWORK

The theoretical framework is the foundation on which the entire research project is found.

This theory flows logically from the documentation of previous research. Hence, the

theoretical framework discusses the interrelationships among the variables which can help to

postulate or hypothesize and test certain relationships. Thus, it is also to improve the

understanding of the dynamics of this research.

Based on the literature review, the model of the research can be build. Below is the

schematic diagram of the list of dependent and independent variables. They are export of

palm oil, exchange rate and consumer price index that affect the price of CPO.

Figure 1: The Schematic Diagram

Dependent Variable Independent Variable

There are three (3) proxies that were use for the variables:-

VARIABLE PROXY

Price of CPO Annual Domestic Price of CPO

Export Value of Palm Oil Annual Export Value of Palm Oil

Exchange Rate (RM to USD) Annual Exchange Rate

Inflation Rate Annual Average of Consumer Price Index

Price of CPO

Inflation Rate Index

Exchange Rate (RM to USD)

Export Value of Palm Oil

18

3.3 VARIABLE

The dependant variable is price of crude palm oil, which is the variable of primary interest.

The variation is attempted to be explained by the three independent variables of, (1)

Exchange rate, (2) Export value of palm oil, and (3) Consumer Price Index (Inflation).

Export

In economics, an export is any good or commodity, transported from one country to another

country in a legitimate fashion, typically for use in trade. Export is an important part of

international trade. Its counterpart is import. Export is the taken for this study from the export

value of the palm oil in RM million.

Exchange rate

Exchange rate can be defined as the rate at which one currency may be converted into

another.

Consumer Price Index

Consumer price index can be defined as the measure of changes in the purchasing power of

a currency and the rate of inflation. CPI expresses the current prices of a 'basket' of goods

and services in terms of the prices during the same period in a previous year, to show effect

of inflation on purchasing power.

19

3.4 SAMPLE SIZE

Determining sample size is a very important issue because samples that are too large may

waste time, resources and money, while samples that are too small may lead to inaccurate

results (iSixSigma Staff, 2000).

The sample size of this study consists of 27 years, which is from the year 1980 until

2007.

3.5 RESEARCH DESIGN

3.5.1 Type and nature of the study

The research is descriptive in nature. A descriptive research intends to present facts that

concern the nature and status of the situation and to describe present conditions, events and

systems based on the impressions and reactions of the respondents of the research

(Creswell, 1994). A descriptive research is also concern with relationships and practices that

exists, beliefs and processes that are ongoing, effects that are being felt and trends that are

developing (Best, 1970).

3.5.2 Data analytical Technique Used

After the data have been collected, the next step is to analyze them from the research

hypotheses. Data analysis for this study is using with various software programs such as

SPSS and E-views.

20

SPSS (originally, Statistical Package for the Social Sciences) is a computer

application that provides statistical analysis of data. It allows for in-depth data access and

preparation, analytical reporting, graphics and modeling. More analytical power can be

added by using optional SPSS modules.

This study has also used E-views to develop an econometrics equation and statistical

relations from the data. E-views have provided sophisticated data analysis, econometric

techniques and evaluation on the study.

Both analytical technique used is vital to develop the accurate figures for the analysis

and result. It can be used to test the hypotheses and run the multiple regressions.

3.6 METHODOLOGHY

3.6.1 Multiple Regressions Analysis

A multiple regression analysis involves estimation, testing and diagnostic procedures

designed to fit the multiple regression model

0 1 1 2 2( ) .... k kE y

to a set of data. The general purpose of multiple regressions is to learn more about the

relationship between several independent or predictor variables and a dependent or criterion

variable.

For this study, the data for export value of palm oil (in RM), exchange rate (RM to

USD), and consumer price index (%) has been compiled to be regress. Once this information

has been compiled, it would be interesting to see whether and how these measures relate to

the price of CPO.

21

Due to the complexity of the calculations involved, these procedures are almost

always implemented with a regression program from one of several computer packages.

Such as, Statistical Package for the Social Sciences (SPSS) and E-views programs.

3.5.2 REGRESSION MODEL

PCPO = β0 + β1EX + β2ER+ β3CPI (model1)

Where,

PCPO = Malaysian Crude Palm Oil Price (RM/tonnes)

ER = Exchange Rate (RM - USD)

EX = Exports (in Value (RM million))

CPI = Consumer Prices Index (Inflation rate (%))

3.5.3 STATISTICAL TEST

There three (3) types of statistical test were used in this study.

Student t-test

A t-test is use to compare two small sets of quantitative data when samples are collected

independently of one another. The confidence interval normally used is 95%. As a rule of

thumb, if the t-test is more than 2 it indicates that a significant relationship between the

dependent variable and the independent variable.

F-test

It can be also known as Analysis of Variance (ANOVA). F-test can be used to test whether

any of the independent variables has an effect on the dependent variable. The standard error

22

of estimation can help to indicate how good a regression model can predict the dependent

variable. F-test is used to test the strength of the relationship between the dependent and

independent variables. It measures how well a linear model fits a set of data or to know the

significant of the whole model. The level significance that were used in this research is 5

percent

Coefficient of Determination

In statistics, the coefficient of determination, R2, is the proportion of variability in data set that

is accounted for by a statistical model.R2 is a statistic that will give some information about

the goodness of fit of a model. In regression, the R2 coefficient of determination is a

statistical measure of how well the regression line approximates the real data points. A R2 of

1.0 indicates that the regression line perfectly fits the data.

3.5.4 ANALYSIS OF REGRESSIONS

Coefficients of the Multiple Regressions

The size of the coefficient for each independent variable gives the size of the effect that

variable is having on the dependent variable, and the sign on the coefficient (positive or

negative) gives the direction of the effect. In regression with multiple independent variables,

the coefficient tells that how much the dependent variable is expected to increase when that

independent variable increases by one, holding all the other independent variables constant.

Coefficient of Determination (R-squared)

The R-squared of the regression is the fraction of the variation in the dependent variable that

is accounted for the independent variables. For example is r is 0.95, therefore, 95 percent of

variance in the dependent variables are explained by the independent variables. The

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remaining of 5 percent of the variation is come from the omitted independent variables that

has not included in the regression model.

3.5.5 RESEARCH HYPOTHESES

Once the important variables have been identified in the theoretical framework, the

test, whether the relationships have been theorized or significant is been developed.

Formulating such testable statements are called hypotheses testing. Hypothesis testing is

usually to explain the nature of certain relationships, or establish the differences among the

independence of two or more factors. As for this study, we develop three hypotheses. These

hypotheses are for the use of a t-test, an ANOVA and a multiple regression analysis. The

result and their interpretation will be discussed in chapter 4 later.

The paper will work on the following assumptions:

HO1: There is no significant relationship between prices of crude palm oil to the export

HA1: There is significant relationship between prices of crude palm oil to the export

HO1: There is no significant relationship between prices of crude palm oil to the exchange

rate

HA1: There is significant relationship between prices of crude palm oil to the exchange rate

HO1: There is no significant relationship between prices of crude palm oil to the consumer

price index

HA1: There is significant relationship between prices of crude palm oil to the consumer price

index.

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CHAPTER 4

RESULT OF DATA ANALYSIS

The table below shows the result of dependent and independent variable by using E-Views.

Table 3: Result from E-Views

Dependent Variable: MPOP

Method: Least Squares

Sample: 1980 2007

Included observations: 28

Variable Coefficient Std. Error t-Statistic Prob.

C 392.3168 478.8249 0.819332 0.4207

ER 119.2955 166.7431 0.715445 0.4812

EXPORT 0.024788 0.009095 2.725543 0.0118

CPI 43.91776 34.88542 1.258915 0.2202

R-squared 0.515093 Mean dependent var 1203.071

Adjusted R-squared 0.454480 S.D. dependent var 455.0144

S.E. of regression 336.0707 Akaike info criterion 14.60408

Sum squared resid 2710644. Schwarz criterion 14.79440

Log likelihood -200.4572 F-statistic 8.498011

Durbin-Watson stat 1.612000 Prob(F-statistic) 0.000506

25

The equation of this regression is:

MPOP = 392.32 + 119.30ER + 0.025EXPORT + 43.92CPI

(166.743) (0.0091) (34.885)

t = 0.715 2.726 1.259

R-squared = 0.52 N = 28 (annual 1980 -2007) Durbin Watson = 1.61

(model 2)

The figures in parentheses are values of the standard error.

4.1 PROBLEM IN MULTIPLE REGRESSION ANALYSIS

There are three (3) types of problem in multiple regression analysis that violate the classical

assumptions of the regression. However, since the data are time series, so we only

explained the multicollinearity and serial correlation. The heteroskedasticity is more likely

happened in the cross-sectional models than time-series models.

4.1.1 Multicollinearity

Multicollinearity occurs when variables are so highly correlated with each other that it is

difficult to come up with reliable estimates of their individual regression coefficients. When

two variables are highly correlated, they are basically measuring the same phenomenon or

construct. In other words, when two variables are highly correlated, they both convey

essentially the same information. Multicollinearity problem is the violation of Classical

Assumption VI. There are two types of multicollinearity.

Perfect multicollinearity means that one independent variable has an exact linear

relationship with another independent variable with no error term.

Meanwhile, Imperfect multicollinearity means that there is a linear relationship the

variables, but there is some error in the relationship.

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4.1.1.1 The Consequences of Multicollinearity

The major consequences of multicollinearity are:

1. Estimates will remain unbiased. Even if an equation has significant multicollinearity,

the estimates of the βs will still be centered on the true population βs if all the Classical

Assumptions are met for a correctly specified equation.

2. The variances and standard errors of the estimates will increase. Since two or more

of the explanatory variables are significantly related, it becomes difficult to precisely identify

the separate effects of the multicollinear variables. Therefore, it will make large errors in

estimating the βs.

3. R2 and F-test still indicate strong goodness of fit. If R2 is high, for example is 0.8, the

F-test in most cases will reject the hypothesis that the partial slope coefficients are

simultaneously equal to zero, but the individual t-test will show that none or very few of the

partial slope coefficients are statistically different from zero (not significant).

4.1.1.2 The Detection of Multicollinearity

The variance inflation factor (VIF) is a method of detecting the severity of multicollinearity by

looking at the extent to which a given explanatory variable can be explained by all the other

explanatory variables in an equation. A high VIF indicates that multicollinearity has increased

the estimated variance of the estimated coefficient by quite a bit, yielding a decreased a t-

score.

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By using SPSS software application, the VIF of the 3 independent variables are

stated as below.

Table 4: The VIF of the Coefficient

Model VIF( ̂ i)

Exchange Rate 2.123

Export 2.095

CPI 1.049

The higher the VIF of the coefficient, the more severe the effects of multicollinearity. As a

rule of thumb is that if VIF (βi) > 5, the multicollinearity is severe. Therefore, we can

conclude that, the problem of multicollinearity does not exist in this model.

4.1.2 Serial Correlation

Serial correlation occurs when Classical Assumption IV, which assumes uncorrelated

observations of the error term, is violated in a correctly specified equation.

4.1.2.1 The Consequences of Serial Correlation

The major consequences of the serial correlation are:

1. Under estimates the standard errors. The consequences will be an inflated t-value

where statistically insignificant coefficients appear to be significant.

2. Estimates are unbiased. ( E( ̂ ) = β )

3. Estimators are no longer efficient (i.e. they do not have the lowest variance)

4. Observed errors follow a pattern.

5. Underestimate variance of the error term. This will results in R2 being exaggerated

and incorrect F-test.

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4.1.2.2 The Detection of Serial Correlation

The most popular method of detecting the presence of serial correlation is known as the

Durbin-Watson d statistic.

The advantage of the d statistic is that it is based on the estimated residuals, which

are routinely computed in regression analysis. Therefore, it is now a common practice to

report the Durbin-Watson d along with summary measures, such as R2, adjusted R2, t-test

and F-test.

The actual test procedure can be explained better with the aid of figure 2, which

shows that the limits of d are 0 and 4.

Figure 2: Durbin-Watson d statistic.

Reject Ho Reject Ho

Evidence of

positive

serial-

correlation

Zone of

indecision

Do not reject Ho or Ha

or both

Zone of

indecision Evidence of

negative

serial-

correlation

0 dL du 2 4-du 4-dL 4 d

The hypotheses are:

H0 : ρ ≤ 0 (no positive serial correlation)

Ha : ρ > 0 (positive serial correlation exist)

29

To test the null hypotheses of no positive serial correlation the Durbin-Watson d statistic

must be compared to two different critical d-values, dL and dU found in the tables that follow:

1. The critical value of 5 percent one –sided level of significance (10 percent of two-

sided level of significance)

2. The number of explanatory variables (k) = 3

3. The number of observations (N) = 28, dL = 1.18 and dU= 1.65

Therefore, any computed Durbin–Watson statistic less than 1.18 would lead to the

rejection of the null hypotheses. For computed DW d-values between 1.18 and 1.65, the test

is inconclusive, and for values greater than 1.65, we can say that there is no evidence of

positive serial correlation at 5 percent significance level. The conclusion can be referring

from the table of the decision rules of Durbin-Watson statistic below.

Table 5: The Decision Rules of Durbin-Watson Statistic

In this research, the computed DW d-value is 1.61, so we can conclude that the test

is inconclusive1. Therefore, for this research we can conclude that there is no serial

correlation exists in this model.

1 The inconclusive region is troubling, but the development of exact Dublin-Watson tests may eliminate this problem in the near future. The computer program of SHAZAM, allow user the option of calculating an exact Dublin-Watson probability (of first order serial correlation).

Null hypotheses Decision If

H0 : ρ ≤ 0 (No positive serial correlation) Reject 0 < d < dL

H0 : ρ ≤ 0 (No positive serial correlation) No decision dL ≤ d ≤ dU

H0 : ρ ≥ 0 (No negative serial correlation) Reject 4 - dL < d < 4

H0 : ρ ≥ 0 (No negative serial correlation) No decision 4 – dU ≤ d ≤ 4 – dL

H0 : ρ = 0 (No positive or negative serial correlation) Do not Reject dU < d < 4 - dU

30

4.2 HYPOTHESIS TESTING

There are two test types to prove my hypothesis testing. The t-test is the test that

econometrician usually use to test hypotheses about individual regression slope coefficients.

Whereby, the F-test is a formal hypothesis test that is designed to deal with a null hypothesis

that contains multiple hypotheses about a group of coefficients.

4.2.1 The t-test

The two-sided t-test was used to test hypotheses that should be rejected if each estimated

coefficients are significantly different from zero, or specific non-zero value, in either direction.

The hypothesis for this test is below.

Ho : β = 0

Ha : β ≠ 0

As figure 3 illustrate, a two-sided test implies two different rejection regions (one

positive and one negative) surrounding the “acceptance” region.

Figure 3: Two-Sided t-Test

Acceptance region

Rejection region Rejection region

-1.711 0 +1.711

31

The critical values of the t-distribution at 10 percent level of significance of two-sided

region are +1.711 and -1.711.

For β1 Reject Ho if | 0.64 | > 1.711. In this case we can conclude that the estimated

value of log β1 is smaller than critical value. So we do not reject Ho. Therefore, log β1 is not

significantly related to the price of CPO.

For β2 Reject Ho if | 2.58 | > 1.711. In this case, we can conclude that the estimated

value of β2 is greater than critical value. So we can reject Ho. Therefore, export is significantly

related to the price of CPO.

For β3 Reject Ho if | 1.33 | > 1.711. In this case, we can conclude that the estimated

value of β3 is smaller than critical value. So we can reject Ho. Therefore, log of CPI is not

significantly related to the price of CPO.

We can also using p-value approach to test the hypotheses. Below is the result,

indication the probability of the t-test. Therefore, we can conclude that only variable export is

significant at 0.05 significance level to the price of CPO.

Table 7: The t-value of The Variable

Variable Estimated t-value Prob. Interpretation

ER 0.715445 0.4812 Not significant

EXPORT 2.725543 0.0118 Significant

CPI 1.258915 0.2202 Not significant

32

4.2.2 The F-test

Although R2 and Adjusted R2 measure the overall degree of fit of an equation, they don’t

provide a formal hypothesis test of that overall fit. Therefore, F-test is needed to test overall

significance. The hypothesis for the F-test is as below.

Ho : β1 = β2 = β3 = 0

Ha : Ho is not true.

Critical value for F-statistic at alpha 0.05 is 3.01

Therefore, F-value 8.59 is greater than F-statistic and we should reject Ho. We can conclude

that at least one of the coefficients is not equal to zero. This implies that there is significant in

the relationship between independent variable and dependent variable as a whole. The table

7 below shows the probability value of the F-statistic.

Table 8: The F-statistic of The Overall Variable

Value

F-statistic 8.498011

Prob(F-statistic) 0.000506

It can also be interpreted as; the F-test is 8.498011 which using the p-value is 0.00475 where

it means that, as a group, all the independent variables are significant relationship with the

dependent variable at 0.05 significance level.

33

4.3 INTERPRETATION OF THE RESULT

The results of estimates are generally in accordance with theories and hypotheses. This can

be seen from the sign, which generally are expected. So the model that we use is model 2

that is as below:

MPOP = 392.32 + 119.30ER + 0.025EXPORT + 43.92CPI

First, lets interpret this result of the multiple regressions. As expected, there is a

positive relationship between exchange rate (RM to USD) and domestic price of CPO. If the

exchange rate is increase (depreciate) the domestic price will increase. On average, the

domestic price increase about RM119.30 if the exchange rate increases by RM1.

The sign for export also indicates that a positive relationship with price of CPO. On

average, the domestic price increase RM0.24 when export increases by RM10.

CPI also indicates a positive relationship where, when the increase in CPI will also

increase in price of CPO. On average, increases in 1 percent of inflation will make the price

of CPO increases by RM43.92.

The R-squared is 0.515093, which shows that, 52% of the variations in the price of

crude palm oil can be explained by the exchange rate, export and consumer price index. The

48% of the variations can be explained by other omitted independent variables.

34

CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS

5.1 CONCLUSIONS

The result shows that the effect of the fluctuation in price of CPO is determined by the

exchange rate, export of palm oil and also consumer price index. The export of palm oil is

significantly related to price of CPO.

Based on the study done by Mohd Nasir A. et al (2004), the export has become a significant

component in terms of influencing the co-movement in price of palm oil in the market. The

study also reveals that the export is expected to be positive in relation to the CPO price.

However, exchange rate and consumer price index are not significantly related to price of

CPO. The study done by Mohammad Alias and Tuck Cheong Tang (2005) reveal that the

significance of the relative price level lends empirical support for some form of price policy. It

can be seen from the response of the industry to the pegging of the ringgit to the US dollar in

September 1998. For this reason, the fluctuations of price of CPO not mainly reflected by the

changes in the exchange rate regime in Malaysia. Even though it will impact in a positive

trend towards the price of CPO.

The consumer price index reveals that it is not significantly related to the price of CPO.

Based from the literature review on Simone Pfuderer and Maria del Castillo (2008), the

changes in agricultural prices have historically not been fully reflected in consumer prices. It

also revealed that the share of the crude palm oil in the consumer product is smaller in

comparison to the end of the product price. Thus, the study said that only extreme and

prolonged peaks in price could lead to slightly higher consumer prices.

The conclusion from this research is that the fluctuations of price of CPO are not fully

impacted the growth of the economy in Malaysia. However, it will significantly be impacted if

the trade of palm oil increases. Thus, it can also reflect the growth of the industry. This has

35

given many contributions to the export earning from the agriculture sector to the growth of

the economy in Malaysia.

The volatility of commodity prices affects the income of smallholder who depends on

commodities for their livelihood. Therefore, the Government has introduced several

measures to assist smallholder in time of depressed prices, such as promoting integrated

farming to diversify risks and providing grants for replanting with other remunerative crops.

5.2 RECOMMENDATIONS

There are several recommendations that can be made from this study.

Firstly, more research and development (R&D) undertaken by both the public and

private sectors should be done. It has contributed significantly to the remarkable

development of Malaysia’s palm oil industry. Such efforts will continue to increase the use of

palm oil, which will generate added value to oil palm products.

From the result, we can see export value of palm oil is significant to the variability of

the price of CPO. Currently, Malaysia’s palm oil exports are in the form of basic products,

and they have to compete directly with those from competitively priced neighbouring

countries. This has affected Malaysia’s palm oil market share in countries such as India, the

EU, Bangladesh and the People in Republic of China. In order to contribute to the economic

growth, Malaysia needs to continue to diversify and promote its products into higher value

added intermediate products such as biodiesel as well as finished products to enhance its

image as an exporter of high quality products for the world market. Therefore, it is important

as Malaysia’s position as the leading producer and exporter of high quality palm oil products.

There s a need to formulate a national brand to project the sustainability and high quality

standards of Malaysia palm oil.

36

Other factors that can help are to promote the export of palm oil are shipping and

freight rates. The rates are major factors in determining the growth of palm oil exports as well

its competitiveness.

Competition in the world market is increasing in tandem. This situation is being fully

exploited by some of the major palm oil importing countries by way of tariff preferential

treatments for CPO (tariff escalation between crude and processed palm oil). Malaysia palm

oil is unable to enjoy the tariff, as export of CPO is not fully encouraged by the country in

order to maintain the supply for domestic consumption. Therefore, Malaysia has been

imposed with the export duty for CPO. However, the study done by Nasir Amirrudin, 2003

said that the Malaysia has allowed duty free exports of CPO by certain selected big

companies and there is no duty on exports of processed of palm oil (PPO).

Currently, the main thrust of the future development of the oil palm industry is to

become modern, dynamic and competitive industry by 2020. This industry is expected to

experience growth momentum in the production and export of palm oil in tandem with the

expected increase in demand of the world market, which by then will be fully liberalized. The

competition among Malaysia and other palm oil as well as oilseeds producing countries in

the global oils and fats market, is expected to become mere intense with regards to price

competitiveness and quality.

For contributing towards more of this research topic, it can also be expanded to other

macroeconomics variables. Therefore, this type of research should encourage further study

as it contributes significantly not only towards the Malaysian Palm Oil Board but also to the

government to make their policy.

This research can be also being expanded another methodology. The forecasting is a

useful tool to predict the price of CPO. It is vital to facilitate efficient decisions to the market

forces. They are also important on giving information to the producer for the decision making

37

and getting the profit for their firm directly and contributing to the growth of the economy,

indirectly.

In the personal opinion that the researcher should conduct further additional studies

in this matter because it will give a more thorough understanding, especially in relation to the

researcher role and current position. It is also presenting the opportunity to contribute by

publishing a journal under current job capacity. This will also help develop a confidence and

prepare for a better job position, a position that comes by understanding the job scope more.

38

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