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mengaku membenarkaf] tes is (LPSrvVSarjanaiDoktor Falsafah) ini disimpan di Perpustakaan Universiti Malaysia Sabah dengan syarat-syaraL kegunaan seperti beriku t: -
i. Tesis adalah hakmili k Universiti Malaysia Sabah . 2. Perpustakaan Universiti Malaysia Sabah dibenarkan membuat sal inan unLuk tujuan pengajian
sa haja. 3 Perpustakaan dibenarkan membuat sali nan tesis ini sebagai bahan pertukaran antara institutsi
pengaj ian tinggi . 4. Si la tandakan ( / )
D SUUT (Mengandungi maklumat yang berdarjah keselamatan atau Kepentingan Malaysia seperti yang termaktub di dalam
D AKT A RAHSIA RASMI 1972)
TERHAD (Mengandungi makl umat TERHAD yang Lelah ditentukan
I /' I· TlDAK TERHAD _ .. -- oleh organisas ilbadan di mana R!!nyelidikan dijalankan) _"'"
Disahkan Oleh
~ (TANDAT ANGAN PENUUS) (TANDATANGAN PUSTAKAWAN)
Alamat TetaR: 4 ·1· ~ , \t\'1l tD\: _~NoYlil;lI\\
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Mtw ",t,.. ~r ~ I 1 .. I~lO . A~A~\~~ t..,.i~trl )t l ,; 1 OVIJ k.'1~\'" L-rr. Nama Penyelia
Tarikh :~ ~ . ~{Jt Tarikh :l!..:. L " ,
CAT AT AN :- *Potong yang tidak berkenaan. ** Ji ka tesis ini SULIT atau TERHAD, sil a lampirkan sural daripada pihak berkuasa
! /organisasi berkenaan dengan menyatakan sekali sebab dan lempoh tesis ini perlu I
dikelaskan sebagai SUUT dan TERHAD . 1 @Tesis dimaksudkan sebagai tesis bagi lj azah Doktor Falsafah dan Sarjana secara I penyelidikan alau disertai bagi pengajian secara kerja kursus dan Laporan Proj ek Sarjana i
Muda (LPSM). - - ...
FACTORS AFFECTING THE PRICE OF RUBBER AND ITS CONTRIBUTION TOWARDS AGRICULTURE REVENUE .
YAP KOKHOW
THIS DISSERTATION IS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF BACHELOR OF SCIENCE WITH
HONOURS
MATHEMATICS WITH ECONOMICS PROGRAMME SCHOOL OF SCIENCE AND TECHNOLOGY
UNIVERSITI MALAYSIA SABAH
April 2008
ii
DECLARATION
I hereby declare that this dissertation contains my original research work. Source of
findings reviewed herein have been duly acknowledge.
30 April 2008
YAP KOKHOW
HS 2005-4782
1ll
CERTIFIED BY
Signature
1. SUPERVISOR (pn. Noraini AbduUah)
2. EXAMINER 1
(Pn. Siti Rahayu Binti Mohd Hashim)
3. EXAMINER 2
(Cik Suriani Hassan)
4. DEAN )~~7-(Supt/KS. Assoc. Prof. Dr. Shariff A. Kadir S. Omang) .,r
IV
ACKNOWLEDGEMENT
Here, I would like to express my gratitude to my supervisor, Puan Noraini Abdullah.
From project 1 to project 2, she had given me a lot of guidance, encouragements and
concepts in order to help me to complete my research on time. Under her supervision, I
had learnt a lot of skills which were very useful and applicable in my future. I had also
gained lots of experiences which I believed will enrich my life.
In addition, I would like to extend my appreciation to Dr. Caroline Geetha of
School of Business and Economics who had supervised me in Project I, our course's tutor
Miss Khunes and all of the lecturers of Mathematics with Economics Programme who
had given me lots of priceless ideas and supports.
v
ABSTRAK
Kajian ini mempunyai enam objektif iaitu meneari kuantiti optimum pengeluaran getah,
pendapatan maksimum pengeluaran getah, keuntungan maksimum pengeluaran getah,
sumbangan komoditi pertanian terhadap pendapatan keseluruhan pertanian, faktor-faktor
yang mempengaruhi harga getah dan perangkaan model ramalan bagi harga getah.
Kuantiti optimum pengeluaran getah dapat dieari dengan melukiskan graf marginal kos
dengan marginal pendapatan. Pendapatan maksimum pengeluaran getah akan diperoleh
dengan mendarabkan kuantiti optimum pengeluaran getah dengan harga optimal getah.
Hasil tolak pendapatan maksimum pengeluaran getah dengan jumlah kos pengeluaran
getah akan mendapat keuntungan maksimum pengeluaran getah. Faktor-faktor yang
menpengaruhi harga getah dieari dengan menggunakan model regressi. Satu model yang
terbaik akan dipilih pada akhimya dan pembolehubah-pembolehubah yang terdapat
dalarn model terbaik itu mewakili faktor-faktor yang menpengaruhi harga getah. Harga
ramal an boleh didapati dengan menggantikan pembolehubah-pembolehubah yang
berkenaan ke dalam model terbaik itu. Sumbangan komoditi pertanian terhadap
pendapatan keseluruhan pertanian juga dapat dieari dengan menggunakan analisasi
regressi. Satu model akhir yang terbaik sekali akan dipilih dan pembolebubah
pembolehubah yang terdapat di dalam model terse but adalah faktor-faktor yang
menyumbang kepada pendapatan keseluruhan pertanian.
VI
ABSTRACT
There are six objectives in this research. They are to determine the optimal quantity of
rubber production, the maximum revenue of rubber, maximum profit of rubber, looking
into the contribution of agricultural commodity towards agriculture revenue, factors that
influence the price of rubber and obtain a forecasting model of the rubber's price. Firstly,
the optimal quantity of rubber production is determined by plotting the graph of marginal
cost and marginal revenue. Maximum revenue will be obtained by multiplying the
optimal quantity of rubber with the rubber's optimal price. This is followed by the
substracting the total cost of rubber production from maximum revenue in order to fmd
the maximum profit. Secondly, the factors that influence the price of rubber are found by
doing multiple regression. Eventually, a final best model will be acquired and the
variables on the fmal best model are the factors that affect the price of rubber. By
substituting the data into variables of the final best model, the price of rubber can be
predicted. Lastly, the contribution of agriculture commodity toward agriculture revenue is
also determined through multiple regression analysis. The models will be examined and a
final best model will be obtained. Factors that contribute towards the agriculture revenue
will be in the final best model.
Vll
CONTENTS
Page Number
DECLARATION II
CERTIFICATION III
ACKNOWLEDGEMENT IV
ABSTRAK V
ABSTRACT VI
LIST OF CONTENTS Vll
LIST OF TABLES Xl
LIST OF FIGURES xii
LIST OF SYMBOLS xiv
CHAPTER 1 INTRODUCTION 1
1.1 Introduction 1
1.1.1 Marketing
1.1.2 Price 2
1.1.3 Labor 3
1.1.4 Production 3
1.1.5 Land 4
1.1.6 Rainfall 4
1.1.7 Population 5
1.1.8 GDP of Agriculture 5
1.1.9 GDP 6
1.2 Background 6
1.3 Problem Statement 8
1.4 Research Objectives 8
1.5 Scope Of Study 9
1.6 Significance Of Study 10
1.7 Organisation Of Study 10
1.8 Assumptions And Limitations 11 .
1.9 Definition Of Terms 12
Vlll
1.9.1 Short Run 12
1.9.2 LongRun 12
1.9.3 Overstocking 12
1.9.4 Understocking 13
1.9.5 Marginal Cost 13
1.9.6 Marginal Revenue 13
1.9.7 Profit 14
1.9.8 Opportunity Cost ]4
CHAPTER 2 Literature Review 15
2.1 Introduction 15
2.2 Literature Review 15
2.2.1 Perfect Competition 15
2.2.2 Short Run And Long Run Under Perfect Competition 18
2.2.3 Price And Ouput Determination Under Perfect Competition 22
2.3 Previous Research 23
CHAPTER 3 Methodology 30
3.1 Data 30
3.2 Model Specification 30
3.2.1 Model I And Model n 30
3.2.2 Optimal Price, Optimal Quantity And Maximum Revenue 32
3.2.3 Simultaneous Equation 33
3.2.4 Variables 34
3.3 Descriptive Analysis 34
3.4 Multiple Regression 36
3.5 Ordinary Least Square Method COLS) 44
3.6 Multicollinearity 45
3.7 R Square (R2) and Adjusted R Square Method C R2) 47 3.8 Model Selection Criteria 48
3.9 Enhancement of best model selected 50
IX
3.9.1 The Wald Test 50
3.10 Randomness Test 52
3.11 Forecasting 54
CHAPTER 4 Data Analyze And Empirical Results 55
4.1 Overview 55
4.2 Modell 56
4.2.1 Assumption Testing 56
a. Multicollinearity Test 56
b. Remedy of Multicollinearity Effect 59
c. Normality Test 61
d. Model Transformation 62
4.2.2 Multiple Regression Analysis 64
a. Individual t-Test 64
b. Global F-Test 66
c. Best Model Selection 68
d. Randomness Test 69
e. Forecasting 72
4.3 Model II 73
4.3.1 Assumption Testing 73
a. Normality Test 73
b. Model Transformation 75
c. Test of Multicollinearity 76
4.3.2 Multiple Regression Analysis 78
a. Individual t-Test 78
b. Global F-Test 80
c. Best Model Selection 81
d. Randomness Test 82
4.4 Optimal Quantity Of Rubber Production 85
CHAPTER 5 Discussion And Conclusion
5.1
5.2
5.3
5.4
5.5
5.6
5.7
Overview
Modell
Model II
Optimal Quantity, Maximum Revenue and Maximum Profit
Limitations
Suggestions For Future Works
Conclusions
REFERENCE
APPENDIX
88
88
88
90
91
92
93
94
96
100
x
LIST OF TABLES
No. Table Page Number
3.1
3.2
Calculation Of Combination Model For Six Dependent Variables.
Existence Of Multicollinearity
40
46
Xl
XlI
LIST OF FIGURES
No. Figure Page Number
2.1 Marginal Cost Curve (MC) Intersects Demand Curve 17
2.2 The Demand Curve Of A Perfectly Competitive Firm 18
2.3 SMC, SATC And SA VC Curves 19
2.4 LMC And LAC Curves 21
2.5 TC, TVC And TFC Curves 23
3.1 Scatterplots Of Residuals 37
3.2 Examples OfHomoscedasticity And Heteroscedasticity 39
3.3 The Rejection Region For Student-t Distribution 53
4.1 Multicollinearity test of Model I 58
4.2 Multicollinearity test on transformed model of Model I 61
4.3 K-S Test on Model I after model minimization 62
4.4 K-S Test after model transformation for Model I 64
4.5 Detrended Normal Q-Q Plot of X B 65
4.6 Coefficient table of model 3.1 of Model I 66
4.7 ANOVA table of model 12.7 of Model I 68
4.8 K-S Test on residuals 72
4.9 K-S Test on Model II 75
4.10 K-S Test for Model II after model transformation 77
4.11 Test of multicollinearity for Model 11 after mode transformation 78
4.12 Coefficient table for model 24.2 of Model II 79
4.13 ANOVA table for model 24.2 of Model II
4.14 K-S Test on residuals
4.15 Marginal cost and marginal revenue curve
81
85
86
Xlll
XIV
LIST OF SYMBOLS
< less than
> greater than
~ less than or equal
~ greater than or equal
= equal
;I; not equal
+ addition
subtraction
x multiplication
division
L summation
n number of observations
k number of parameters
Chapter 1
INTRODUCTION
1.1 INTRODUCTION
1.1.1 Marketing
Marketing exists in both profit and non-profit organization. Kotler (2005) stated that a
market-focused or customer-focused organization first determines what its potential
customers' desires and then builds the product or service. Marketing theory and practice
is justified in the belief that customers use a product and service because they have a need,
or because a product or service provides a perceived benefit. Two major factors of
marketing are the recruitment of new customers and the retention and expansion of
relationships with existing customers.
2
However, marketing exists at micro-level which relates to customers and the
organizations that serve them. While macro-level of marketing connects the entire
production-distribution system.
The marketing concept implies that an organization aims all of its efforts in a
coordinated and integrated manner, and simultaneously satisfying its customer and
achieving its corporate goals.
Kotler (2005) also emphasized that marketing strategies are often designed to
influence consumer decision making and lead to profitable exchanges. After all, variables
in marketing mix can be categorized into just four fundamental elements: product, price,
place and promotion that are known as the 4Ps in marketing. For a marketing plan to be
successful, the mix of the four Ps must reflect the wants and desires of the consumers in
the target market.
1.1.2 Price
Peter and Donnelly (2004) defined price as the amount of money charged for a product or
service. Pricing is one of the marketing mix strategies that is used to achieve company's
goal. A company's pricing decisions are affected by both internal company factors and
external environmental factors. Internal factors affecting pricing include the company's
marketing objectives, marketing mix strategy, costs, and organizational considerations.
3
Meanwhile, nature of the market, demand, competition and other environmental factors
such as economy, resellers and government are among the external factors.
Price decisions must be coordinated with product design, distribution, and
promotion to fonn an effective marketing mix which is known as the "4P" of the
marketing mix.
1.1.3 Labor (quantity of workers)
Begg et al. (2003) argued that all inputs of a firm can be adjusted in the long run. In
producing any particular output by the cheapest available technique, a rise in the price of
labour relative to capital makes the finn switch to more capital-intensive technique and
vIce-versa.
In the short run, the firm has fixed factors of production and fixed production
techniques. The firm can vary output by varying its input such as labor. Thus, a rise in the
price of one factor not merely changes factor intensity at a given output but also changes
the profit-maximizing level of output.
1.1.4 Production (quantity of production)
Case and Fair (2007) said that production is the process through which inputs are
combined and transformed into output. In this research, the number of production of
rubber was focused. Quantity of production can be affected by many reasons such as
4
amount of land management, labor, technology, cost of production and other inputs. For
instance, a firm with a plentiful supply of inexpensive labor but not much capital, the
optimal method of production will involve labor-intensive technique. In contrast, capital
intensive technique is appropriate for a finn with high labor cost.
1.1.5 Land (total area of planted bectareage)
Case and Fair (2007) also stated that land is fixed in supply and its price is demand
determined. Price of land is determined by households and firms in other words. In this
research, the total area of the planted hectareage of rubber is varies due to many reasons.
According to Tarnin (1992), the factors could be the increasing cost of production, the
sluggish rate of productivity and the problems in structural change from primary
commodity sector to modem structure.
1.1.6 Rainfall
The sustainability of food supply could also be affected by climate change. Moreover,
increases in temperature and changes in rainfall pattern could affect yields directly. They
could also fasten the spread of fungus and diseases directly or indirectly, thus affecting
yield. The most vulnerable to these changes are the northern Peninsular Malaysia as well
as the coastal areas of Sabah and Sarawak. Changing climate can affect the agriculture
industry. Based on agricultural cycle, increasing in rainfall is not good for rubber. Rubber
plantations could suffer due to lost of tapping days and crop washouts (Tamin, 1992).
5
1.1.7 Population
Mankiw (2007) expressed that the most direct effect is on the size of the labor force. A
large population means more workers to produce goods and services. At the same time, it
means more people to consume those goods and services and vice versa. Applying into
this research, large population means more labor forces to work in rubber estates and thus
increases in productivity. Furthermore, there will be more customers consuming rubber's
products.
1.1.8 Gross Domestic Product (GDP) Of Agriculture Sector
Agriculture remains an important sector of Malaysia'S economy. It contributed 12 percent
to the national GDP and provided employment for 16 percent of the population. The three
main plantation: rubber, palm oil, and cocoa had dominated agricultural exports
(Yearbook of Statistic Malaysia, 2006).
Nonetheless, these three plantations had declined steadily during the last two
decades. In this research, the relationship between these three plantations and the
agriculture's GDP would be determined. Moreover, GDP of Malaysia was also embraced
into the research model.
6
1.1.9 Gross Domestic Product (GDP)
Mankiw (2007) defined gross domestic product (GOP) as the market value of all final
goods and services produced within a country in a given period of time. Gross domestic
product of Malaysia is being considered in this particular research.
Basically, gross domestic product's components include consumption by
households, investment by household, government purchases and country's net exports.
However, gross domestic product is not a perfect measure of economic well-being. For
example, it omits goods and services that have never been brought into the market such as
illegal drugs and vegetables that are produced and consumed by households themselves
(Mankiw, 2007).
1.2 BACKGROUND
Rubber's hectarages experienced a rapid decline from 1991600 hectarages in year 1982 to
1348400 hectarages in year 2003. This was indicative of massive shift from rubber to
other agricultural plantations, a phenomenon which has been dragged by relative
profitability. The rapidity and the magnitude of the shift may result a massive change in
the structure of rubber industry and may exert an adverse effect to the growth of the
industry as a whole (Tamin, 1992).
7
However, according to Yearbook of Statistic Malaysia (2006), Malaysia was the
third biggest producer of natural rubber in the world, and its well-established and superior
quality was widely used as a benchmark in the international market. The Malaysian
rubber industry produced a broad range of products from natural rubber as well as
rubberwood products. Malaysia has also successfully established itself as a major
producer and exporter of rubber and rubber products globally. Main importers of
Malaysian rubber and rubber products were the United States of America, United
Kingdom, Japan, Germany and Italy. In 2001, Malaysia's total exports of rubber were
valued at RM 4.05 billion.
Finished rubber products included rubber gloves, footwear, tyres, condoms and
prophylactic sheaths. Malaysian rubber was also employed in the building, contraction
and automotive industry for a variety of uses. Malaysia's biggest export product was
rubber gloves, whereby Malaysia was estimated to control over 60% of the global rubber
glove market.
Malaysia invested heavily in research and development in the rubber industry in
order to develop innovative and new uses for its rubber. In 2004, the rubber products
sector contributed RM 19.6 billion to the country's export earnings, comprising RM 5.2
billion of natural rubber, RM 7.9 billion of manufactured goods and RM 6.5 billion of
rubberwood products.
8
1.3 PROBLEM STATEMENT
In certain industry, especially industries where seasonal factors or trend play an important
role in deciding accurate demand or supply is vital in deciding the price of a product.
Accuracy in measuring demand and supply is vital because we need to make cost
effective order quantities. Uncertainty can take place in agriculture goods due to supply
yields, climate, transportation delay, shipment accidents and so on. Thus, buyers opt for
either overstocking or understocking. Overstocking can lead a buyer to eventually dispose
the stock at a lower price while understocking can lead to lost of sales through increase in
price. Due to the high amount of uncertainty, buyers feel it would be appropriate to find
the optimum price and quantity of an agriculture good, such as rubber to maximize
revenue and eventually the profit. Since agriculture goods belong to a perfect competition,
the condition to obtain optimal pricing, quantity and revenue are MR = MC = P where
MR equal to marginal revenue, MC equal to marginal cost and P equal to the price of
product. The aim of the study is to determine the optimum price of rubber, quantity of
rubber and revenue of rubber.
1.4 RESEARCH OBJECTIVES
i.) To determine for the optimal quantity of rubber.
ii.) To determine for the maximum revenue of rubber.
iii.) To look for the maximum profit of rubber.
iv.) To determine the factors influence the price of good.
9
v.) To create a forecasting model of rubber's price.
vi.) To look into the contribution of agriculture commodity toward agriculture
revenue.
1.5 SCOPE OF STUDY
The research was made on Malaysia's rubber. The compilation of rubber data for
reference from year 1982 until year 2003 were taken from the Annual Census of Rubber
Estates in Malaysia except for years 1993, 1994, 1996, 1997, 1999,2001 and 2003 for
which the data were obtained from Monthly Rubber Censuses. The data of rubber
includes the price of rubber, the number of workers, the salaries of workers, the
production of rubber and the planted hectareages of rubber (Yearbook of Statistic
Malaysia, 2006).
The population data were obtained from years 1982-2003 in Malaysia. For years
1991-1999, the data were compiled based on Population Census data. For the period
2000-2003, the data were compiled based on the 2000 Population Census data.
The gross domestic product (GDP) in Malaysia's agriculture sector was taken
from years 1982-2003. For years 1982-1986, the agriculture' s GDP had mixed with other
sectors like livestock, forestry and fishing.
96
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