THE IMPACT OF ENERGY CONSUMPTION ON ECONOMIC
GROWTH IN MALAYSIA
By
MAZLINA HASHIM
Project Paper Submitted in Partial Fulfilment of the Requirement
for the Degree of Master of Business Administration at the Putra
Business School, Universiti Putra Malaysia
August 2014
DECLARATION
I hereby declare that this project paper is based on my original work
except
for
quotations
acknowledged.
and
citations
that
have
been
duly
I also declare it has not been previously or
concurrently submitted for any other degree at UPM or other
institutions.
______________________________________
MAZLINA BINTI HASHIM
Date:
ii
Abstract of project paper presented to the Senate of Universiti Putra
Malaysia in partial fulfilment of the requirements for the degree of
Master of Business Administration
THE IMPACT OF ENERGY CONSUMPTION ON ECONOMIC
GROWTH IN MALAYSIA
By
MAZLINA HASHIM
August 2014
Supervisor:
Associate Professor Dr. Wan Azman Saini Wan Ngah
Faculty:
Putra Business School
In this study the nexus between the disaggregated energy
consumption and economic growth in Malaysia was investigated to
observe the impact of each type of the energy source on economic
development. The disaggregated energy consumption consists of
electricity, natural gas, coal and coke, and petroleum products. In
order to analyze the effect of the disaggregated energy consumption
on economic growth, Ordinary Least Square (OLS) regression
method was employed using annual data for the period of 1978 –
2012. Results of this study shown that only three types of the
disaggregated energy consumption have significant impact on the
economic growth, namely electricity, coal and coke, and petroleum
products; whereas the result for natural gas consumption turned out
iii
to be statistically insignificant. Based on the analysis, electricity and
petroleum products consumption was found to have a positive effect
on economic growth, whilst coal and coke consumption is negatively
related to the economic growth. The result of this study could imply
that any conservation policy on electricity and petroleum products
consumption may retard the economic growth. On the other hand, a
policy on conserving coal and coke consumption may be
implemented without adverse effect on the economic development.
iv
Abstrak kertas projek yang dikemukakan kepada Senat Universiti
Putra Malaysia sebagai memenuhi sebahagian keperluan untuk
Ijazah Sarjana Pentadbiran Perniagaan
IMPAK PENGGUNAAN TENAGA TERHADAP
PERTUMBUHAN EKONOMI DI MALAYSIA
Oleh
MAZLINA HASHIM
Ogos 2014
Penyelia:
Associate Professor Dr. Wan Azman Saini Wan Ngah
Fakulti:
Putra Business School
Kertas kajian ini bertujuan untuk mengenalpasti impak penggunaan
tenaga mengikut pecahan ke atas pertumbuhan ekonomi di
Malaysia. Pecahan penggunaan tenaga terdiri daripada tenaga
elektrik, gas asli, arang batu, dan produk petroleum. Untuk
menganalisa
kesan
penggunaan
tenaga
tersebut
ke
atas
pertumbuhan ekonomi, kaedah regresi “Ordinary Least Square”
(OLS) menggunakan data tahunan untuk tempoh 1978 – 2012 telah
digunapakai. Hasil kajian mendapati hanya tiga jenis penggunaan
tenaga mengikut pecahan tersebut mempunyai impak signifikan ke
atas pertumbuhan ekonomi, iaitu tenaga elektrik, arang batu dan
produk petroleum; manakala keputusan kajian ke atas penggunaan
gas asli secara statistiknya adalah tidak signifikan. Berdasarkan
analisis tersebut, penggunaan tenaga elektrik dan produk petroleum
v
didapati mempunyai kesan positif ke atas pertumbuhan ekonomi,
manakala penggunaan arang batu membawa pengaruh negatif
terhadap pertumbuhan ekonomi. Ini membayangkan bahawa
pelaksanaan dasar penjimatan penggunaan tenaga elektrik dan
produk petroleum mungkin menjejaskan pertumbuhan ekonomi.
Namun begitu, dasar penjimatan penggunaan arang batu pula boleh
dilaksanakan tanpa membawa kesan negatif terhadap pembangunan
ekonomi.
vi
ACKNOWLEDGEMENT
First and foremost, thank you the Almighty for without His blessings
this study would not have been possible. My sincere appreciation to
all lecturers and staffs at Putra Business School (PBS) for helping me
throughout this journey. Special thanks goes to my supervisor
Associate Professor Dr. Wan Azman Saini Wan Ngah for his
invaluable assistance, guidance and advice in the course of
completing this study.
I am deeply and forever thankful to my parents for their
unconditional love, sacrifices and prayers. My thanks and love to my
beloved husband for his patience, understanding and support. Last
but certainly not the least, to my family and friends and those who
have contributed in the preparation of this study, I wish to thank
them all from the bottom of my heart.
Mazlina Hashim
Kuala Lumpur
vii
TABLE OF CONTENTS
Page
DECLARATION ...................................................................................... ii
ABSTRACT..............................................................................................iii
ABSTRAK................................................................................................. v
ACKNOWLEDGEMENT......................................................................vii
LIST OF TABLES ..................................................................................... x
LIST OF FIGURES ................................................................................... x
CHAPTER 1: INTRODUCTION
1.1.
Background of the Study .......................................................... 1
1.2.
Problem Statement .................................................................... 9
1.3.
Research Objective................................................................... 11
1.4.
Significance of the Study......................................................... 12
CHAPTER 2: LITERATURE REVIEW
2.1.
Introduction ............................................................................. 14
2.2.
Previous Findings on the Energy-Growth Nexus................. 15
2.2.1. One-way causality from economic growth
to energy consumption................................................ 16
2.2.2. One-way causality from energy
consumption to economic growth.............................. 17
2.2.3. Two-way causality between energy
consumption to economic growth.............................. 18
2.2.4. No causal relationship ................................................. 19
2.3.
Concluding Remarks............................................................... 20
CHAPTER 3: RESEARCH METHODOLOGY
3.1.
Introduction ............................................................................. 25
3.2.
Estimated Model...................................................................... 25
3.3.
Data Analysis ........................................................................... 28
viii
CHAPTER 4: RESULTS AND DISCUSSION
4.1.
Introduction ............................................................................. 31
4.2.
Descriptive Statistics ............................................................... 31
4.3.
Correlation Analysis................................................................ 32
4.4.
Ordinary Least Square Regression......................................... 33
4.4.1. Analysis between electricity consumption
and economic growth.................................................. 33
4.4.2. Analysis between natural gas consumption
and economic growth.................................................. 36
4.4.3. Analysis between coal and coke consumption
and economic growth.................................................. 37
4.4.4. Analysis between petroleum products
consumption and economic growth .......................... 39
CHAPTER 5: CONCLUSION
5.1.
Summary .................................................................................. 42
5.2.
Limitations of the Study.......................................................... 44
5.3.
Recommendations ................................................................... 45
REFERENCES ....................................................................................... 47
APPENDICES
Appendix A: Original Data from Malaysian Energy
Information Hub ...................................................... 52
Appendix B:
Original Data from World Development
Indicators .................................................................. 54
ix
LIST OF TABLES
Table 1: Summary of Literature Review .............................................. 22
Table 2: Descriptive Statistics ............................................................... 31
Table 3: Correlation Analysis................................................................ 32
Table 4: Results using Electricity Consumption (EL) ......................... 34
Table 5: Results using Natural Gas Consumption (NG) .................... 36
Table 6: Results using Coal and Coke Consumption (CC)................. 38
Table 7: Results using Petroleum Products Consumption (PP)......... 40
LIST OF FIGURES
Figure 1: Final Energy Consumption in Malaysia ............................... 3
Figure 2: Energy Consumption by Type of Energy Sources ................ 4
Figure 3: Energy Consumption for Petroleum Products...................... 5
Figure 4: Energy Policies in Malaysia .................................................... 8
x
CHAPTER 1
INTRODUCTION
1.1.
Background of the Study
The global energy sector has been facing several major challenges
such as volatile energy prices, depleting fossil fuel reserves, shortage
in fuel supply and the increasingly apparent effects of global
warming. All these situations are challenging as the world’s overall
demand for energy continues to rise and this trend appears to
continue in the coming decades due to global economic development
and population growth.
The energy scenario in Malaysia follows similar trends of increasing
energy demand. Based on the National Energy Balance 2012
published by the Energy Commission, Malaysia the final energy
consumption recorded a growth of 7.5 percent when compared with
that of the previous year. In 2011, Malaysia’s energy demand has
also experienced an increase of 4.8 percent from the previous year.
Thus, it is interesting to study how economic growth is correlated to
energy consumption or vice versa. In this study, the terms energy
consumption and energy demand have the same meaning and will
be used interchangeably.
1
Malaysia has been experiencing considerably strong economic
growth, with average growth rate of more than 7 percent per year
recorded prior to the Asian financial crisis in 1997 – 1998. After
suffering from the financial turmoil that recorded negative growth in
1998, Malaysia’s economy picked up again beginning from 1999,
which was reflected in its record of growth rate at an average of 5.5
percent per year during 2000 to 2008. However, the economy was
being hit again in the global financial crisis in 2008/2009 which saw
the world’s major economies experiencing among the worst
economic downturn.
At the energy forefront, Malaysia’s energy usage has been on the
rise. As a rapidly developing country that aspires to become a
developed nation in the year 2020, Malaysia’s energy demand
continues to climb in order to meet the needs of its people and
industries. This could be seen to be in line with the economic growth
whereby the final energy consumption showed increasing trend as
depicted in Figure 1.
2
50,000
45,000
40,000
Final energy consumption
35,000
ktoe
30,000
25,000
20,000
15,000
10,000
5,000
1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
year
Figure 1: Final Energy Consumption in Malaysia
It can be seen from Figure 1 that the final energy consumption
follows similar pattern to the economic growth whereby the
consumption shrunk (recorded negative growth) during the Asian
financial crisis and global economic downturn in 1997 and 2008
respectively. Nonetheless, the total final energy consumption still
continues to rise. A closer look at the energy consumption by type of
energy sources is shown in Figure 2 below.
3
Natural Gas
Petroleum products
Coal and Coke
Electricity
50000
45000
40000
ktoe
35000
30000
25000
20000
15000
10000
5000
0
1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
year
Figure 2: Energy Consumption by Type of Energy Sources
From Figure 2, we can see that the final energy consumption for
petroleum products was the highest (constituted approximately 53
percent of the total energy consumption in 2012). The highest
contributors to the total consumption for petroleum products are
petrol and diesel (36.2 percent and 35.5 percent respectively in 2012).
The breakdown of the final energy consumption for petroleum
products is shown in Figure 3 below.
4
Diesel
Fuel Oil
Motor Petrol
LPG
Kerosene
ATF and AV Gas
Non-Energy
Refinery Gas
27000
24000
21000
ktoe
18000
15000
12000
9000
6000
3000
0
1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
year
Figure 3: Energy Consumption for Petroleum Products
In order to safeguard energy security in the country, the Malaysian
government has introduced and implemented a few energy related
policies, most notably:

National Petroleum Policy (1975) – this policy aims at
regulating the fast-growing oil and gas industry in the
country and to ensure greater Malaysian participation and
control in the management and operation of the nation’s
petroleum industry.

National Energy Policy (1979) – this is the principal national
policy governing the power sector in Malaysia which was
formulated with a three-fold objectives encompassing the
5
supply
objective,
the
utilization
objective
and
the
environmental objective. The policy includes broad guidelines
on long-term energy objectives and strategies with the main
aim of ensuring efficient, secure and environmentally
sustainable supply of energy in the future based on the three
principal energy objectives.

National Depletion Policy (1980) – which was introduced to
safeguard the exploitation of oil and gas reserves and extend
the life of these domestic non-renewable energy sources in the
country. Malaysia’s production of oil had increased rapidly
from 1975 to 1979 that without intervention there was a risk
that reserves would have been fast running low. This policy
was later complemented with the Four-Fuel Diversification
Strategy in 1981 which saw the inclusion of coal as the fourth
fuel after oil, gas and hydropower. This policy was then
further updated by the Five-Fuel Diversification Strategy in
2001, with the introduction of renewable energy as a fifth fuel
source in order to further diversify the country’s energy
sources.
6
As a result of the above energy policies, the fuel mix for the power
sector in Malaysia has changed quite substantially in terms of the
usage of major fuel sources for electricity generation:

Oil usage has decreased from around 80 percent in 1981 to less
than 1 percent in 2008;

The share of gas has increased from about 3 percent in 1981 to
around 63 percent in 2008; and

The use of coal which began in the late 1980s has increased to
around 29 percent by 2008.
Further to this, the more recent policies include:

National
Green
Technology
Policy
(2009)
–
which
emphasized that green technology shall be a driver for the
country’s sustainable economic development based on four
pillars namely energy, environment, economy and social.

National Renewable Energy Policy and Action Plan (2009) –
which was designed to enhance the utilization of indigenous
renewable energy (RE) resources to contribute towards
national
electricity
supply
socioeconomic development.
7
security
and
sustainable

New Energy Policy and 10th Malaysia Plan (2010) – The New
Energy Policy addresses economic efficiency, security of
supply, and social and environmental objectives supported
through five pillars namely energy pricing, energy supply,
energy efficiency, governance, and change management.
All the energy-related policies were formulated with the intention to
promote sustainable economic growth, ensuring energy supply
security while keeping a check on the environment. The evolution of
energy policies in Malaysia can be illustrated in Figure 4 below.
Figure 4: Energy Policies in Malaysia
8
1.2.
Problem Statement
The various policies introduced over the years marked the
Government’s continuous initiatives to avoid the country’s overdependence on a specific energy sources and to ensure sufficient and
reliable energy at affordable prices. Despite the efforts of the
Government to ensure diversification in energy sources in Malaysia,
fossil fuels still dominate the shares of energy mix in the country as
can be seen from Figure 1 and Figure 2 above though their shares in
the mix have been changed over time.
The attempt to investigate and determine the linkage between
energy consumption and economic growth is not new and has been
undertaken quite extensively over the past few decades. The survey
of past literatures showed that the consumption-growth nexus has
been a well-studied topic all over the world. Apart from the
relationship between energy consumption and economic growth,
some other variables were also included in the previous studies,
most notably pollutant emissions (most of the time measured by
carbon dioxide emissions) and foreign direct investment (FDI).
However, to date, the empirical evidence remains ambiguous such
that it is debatable among economists and policy makers. As will be
9
discussed in more detail in the Literature Review section, numerous
studies have been conducted by researchers and/or economists
and/or policy makers globally about this subject and have also been
among the most debated topics in energy economics.
Similarly, a number of studies regarding the linkage between energy
consumption and economic growth have also been conducted in
Malaysia such as studies by Ang (2008), Tang (2008), Chandran et. al.
(2010), and Azlina and Nik Hashim (2012).
Nevertheless, the
previous studies were carried out based on time series data of either
energy or electricity consumption during different time periods and
mostly the earlier studies also made use of inputs obtained only from
time series data in the World Development Indicators (WDI)
published by the World Bank.
Another issue regarding this subject is that some of the earlier
studies used small sample sizes. According to Chandran et. al.
(2010), "In this regard, Lee (2005) and Mah (2000) have cautioned
researchers on the use of short data spans, which eventually lower
the power of the co-integration analysis. Mah (2000) stated that the
error correction model (Engle and Granger, 1987), Johansen (1988)
and Johansen and Juselius (1990) methods are unreliable for studies
that have small sample" (p.606). Hence, the results obtained from
10
previous studies regarding the co-integration and causal relationship
between economic growth and energy consumption in Malaysia
have been varied and inconclusive.
Thus, it will be imperative to study the relationship between the
disaggregated energy consumption and economic growth in
Malaysia as it will add support to reduce the concerns over the
ambiguity of the linkage between the variables.
1.3.
Research Objective
Based on the problem identified in section 1.2, this study attempts to
address the question regarding the relationship between energy
consumption and economic growth in Malaysia. More specifically,
the principal aim of this study is to investigate the impact of
disaggregated energy consumption namely electricity, natural gas,
coal and coke, and petroleum products on economic growth in
Malaysia using annual data for the period of 1978 – 2012. The
question this research seeks to answer is: what is the impact of a
specific type of energy consumption on economic growth in
Malaysia?
11
1.4.
Significance of the Study
Based on the literature review, previous studies done mostly
investigated the relationship between economic growth and
aggregated energy consumption or only electricity consumption.
However, this study is novel in that it will re-examine the linkage
between economic growth and disaggregated energy consumption
based on different types of energy sources in Malaysia. This study is
also significant in the sense that the analysis will be done based on
the published data from Malaysia especially for the energy
consumption data. The sample period used in this investigation is
also significantly different from the previous studies conducted for
the case of Malaysia.
According to the National Energy Balance as published by the
Energy Commission, the disaggregated energy consumption in
Malaysia includes electricity, natural gas, coal and coke, petroleum
products and others. Others refer to hydro power, solar, biomass,
biogas and biodiesel; however, as the total final consumption of
these resources is negligible, it will not be taken into consideration.
Thus, the disaggregated energy consumption in this study would be
electricity, natural gas, coal and coke, and petroleum products.
12
This study will use data of gross domestic product (GDP) per capita
to denote economic growth, and disaggregated energy consumption
data to find the relationship between these two variables. A third
variable will also be introduced, that is the energy price such that the
result obtained will be more significant. However, price of energy
differs in various sectors (such as residential and industrial sectors)
and are not readily available – thus consumer price index (CPI) is to
be used as proxy for energy prices.
13
CHAPTER 2
LITERATURE REVIEW
2.1.
Introduction
Due to the importance of energy in fueling the economy of any
country, the literature pertaining to the relationship between energy
consumption and economic growth has been well documented.
According to Kohler (2013), “This link has been examined
extensively in the literature since the seminal work of Kraft and Kraft
(1978) in an attempt to explore whether economic growth stimulates
energy consumption or vice versa. Whilst Kraft and Kraft (1978)
found that the causal relationship runs from economic growth to
energy in the United States and the reverse does not hold true,
studies for other countries reveal conflicting results” (p.1043).
Since the pioneering work by Kraft and Kraft (1978), the energy
consumption and economic growth nexus has a growing literature.
The purpose of this chapter is to provide a review of literature on the
empirical evidence relating to the linkage involving the energy
consumption and economic growth. These empirical investigations
based on past literatures can be categorized into four segments:
14
1) One-way
causality
from
economic
growth
to
energy
consumption
2) One-way causality from energy consumption to economic
growth
3) Two-way
causality
between
energy
consumption
and
economic growth
4) No causal relationship
2.2.
Previous Findings on the Energy-Growth Nexus
This section will discuss the findings of the previous studies on this
subject. The major purpose of these studies were to determine
whether the usage of energy is directly contributing to the
development of the economy or whether the amount of energy
consumed in an economy is dictated by the growth of that particular
economy. As mentioned earlier, there is a huge collection of these
studies
which
differ
mostly
in
terms
of
the
econometric
methodologies employed, the countries being researched, and the
time periods in which the researches were conducted. Quite
interestingly, the findings of these studies have also been rather
mixed and ambiguous.
15
The survey of some past literatures regarding the economic growth–
energy consumption nexus is summarized in Table 1. As can be seen
from the Table 1, the consensus conclusions pertaining to the
connection between energy consumption and economic growth
cannot be achieved and this will be discussed in more detail in the
next sub-sections.
2.2.1. One-way causality from economic growth to energy
consumption
The findings based on the works of the pioneers in this field, i.e.
Kraft and Kraft (1978) whom analyzed the relationship between
economic growth which was measured in terms of the country’s
gross national product (GNP) and energy consumption, presented
evidence to support that there is a one-way causality running from
the economic growth (GNP) to energy use in the United States. The
result from this study thus implies that policies related to energy
conservation should not have adverse effect on the country’s
economy.
Other studies that have found similar uni-directional causality
running from economic growth to energy consumption include the
studies by Ang (2008) and Azlina (2011) for the case of Malaysia,
16
Soytas and Sari (2003) for Italy and Korea, Lise and Montfort (2007)
in Turkey, Lee (2006) in France, Italy and Japan, Zhang and Cheng
(2009) for the case of China, Mozumder and Marathe (2007) for the
case of Bangladesh and Ozturk et. al. (2010) for the case of some of
the low-income countries. The findings from these studies suggest
that energy demand was driven primarily by economic development
in those countries.
2.2.2. One-way causality from energy consumption to economic
growth
On the other hand, there have been a lot of studies that contradicted
the findings in sub-section 2.2.1 whereby such studies discovered
opposite direction of the causal linkage. Results of those studies
found a one-way causality running from energy consumption to the
economic growth supporting the notion that the higher the
consumption of energy in a country, the higher the economic
growth, but the reverse does not hold true.
These studies include Chandran et. al. (2010) for Malaysia, Lee (2005)
for developing countries, Narayan and Smyth (2008) for G7
countries, Menyah and Rufael (2010) for South Africa, Apergis and
Payne (2010) for South America, Tsani (2010) for Greece and Al-
17
mulali and Che Normee (2013) for emerging countries. In this case,
the results seem to support the view that energy is the essential
parameter that determines the development of a country’s economy.
2.2.3. Two-way
causality
between
energy
consumption
to
economic growth
Apart from the uni-directional or one-way causality, a bi-directional
or two-way causality relationship also exist between the two
parameters which means that both energy demand and economic
development cause each other. Evidence of this bi-directional
causality which gave the impression that there is a symbiotic
relationship between energy consumption and economic growth in
certain countries is also prevalent in some other research works.
Such findings suggest that both energy consumption and economic
growth have direct effect on each other at the same time and these
results have been reported by various researchers including Tang
(2008) for Malaysia, Tsai and Pao (2011) for BRIC countries, Hou
(2009) for China, Oh and Lee (2004) in Korea, Belloumi (2009) in
Tunisia, Paul and Bhattacharya (2004) for India, Saboori and
Sulaiman (2013) for ASEAN countries and Salahuddin and Khan
(2013) for Australia.
18
2.2.4. No causal relationship
Finally, there have also been various studies that did not find any
causal relationship linking the economic growth and energy
consumption. This type of findings of no causality in either direction
implies that neither energy usage nor economic activities have any
direct impact on each other. The first of this finding started in 1980
where Akarca and Long (1980) contested the earlier findings by Kraft
and Kraft (1978) since their studies found no causal linkage between
economy and energy consumption in the United States.
These results were further supported by the studies of Huang et. al.
(2008) in low income countries, Balcilar et. al. (2010) in G7 countries,
Acaravci and Ozturk (2010) in Albania, Bulgaria and Romania,
Payne (2009) in the USA, Jafari et. al. (2012) for the case of Indonesia,
Fallahi (2011) in the USA, Jobert and Karanfil (2007) and Altinay and
Karagol (2004), both for the case of Turkey. One of the earliest
studies by Masih and Masih (1996) also arrived at the same
conclusion that no causality exist between economic development
and energy consumption in Malaysia, Singapore and the Philippines
Further from the literature survey, there are also mixed results found
by some researchers. Wolde-Rufael (2006) found that some African
19
countries have unidirectional causality running from economic
growth to electricity consumption, while a bi-directional causality
relationship between the two variables was found in the rest of the
African countries. Similarly, Yoo and Kwak (2010) found that the
causal relationship varied across the South American countries
whereby the causal relationship was unidirectional running from
electricity consumption to economic growth in Argentina, Brazil,
Chile, Colombia and Ecuador. However, in the same study by Yoo
and Kwak (2010), the causal relationship was found to be bidirectional in Venezuela, whilst no causal link was found between
the two variables in Peru.
2.3.
Concluding Remarks
Despite the numerous literatures that has explored the nexus
between energy consumption and economic development; the
results of the studies were found to be mixed and remain
ambiguous. Such varied preceding result within similar context that
is otherwise appears to be straightforward warrant further study. As
cited by Chandran et. al. (2010), “According to Masih and Masih
(1998) and Hondroyiannis et. al. (2002) the main reason for these
conflicting empirical results is due to differences in institutions,
structural reforms, and policies adopted by different countries. In
20
addition, the use of different econometric estimation techniques and
sample periods also influences the results” (p.607).
Likewise for the case of Malaysia, the survey of the literature gave
diverse results regarding the causal linkage and the direction
between the energy consumption and economic growth in a
particular country. These varied and rather controversial findings
may probably due to the differences in the available data, the time
period of the study and the methodologies employed. From this
literature review, it was found that most of the studies used total
energy consumption without disaggregating it into the various
energy sources.
Disaggregating energy consumption into the different types of
energy sources would be able to show the effect of each source of
energy on the economic growth that can provide more insights into
policy implications. Thus, it has motivated me to investigate the
impact of the disaggregated energy consumption based on different
energy sources that is electricity, natural gas, coal and coke and
petroleum products on the economic growth in Malaysia.
21
Table 1: Summary of Literature Review
Authors
Country
Period
Methodology
Major findings
Soytas and
Sari (2003)
Italy,
Korea
1950 1992
Co-integration
VECM
GDP → energy
Paul and
Battacharya
(2004)
India
19501996
GDP ↔ energy
18
developing
countries
Johansen;
Granger
causality
19752001
Full-modified
OLS
Turkey
19602003
Johansen;
Granger
causality
Lee (2005)
Jobert and
Karanfil
(2007)
Mozumder
and Marathe
(2007)
No causal
relationship
Electricity &
GDP are cointegrated
GDP →
Electricity
Bangladesh
19711999
Ang (2008)
Malaysia
19711999
Huang et. al.
(2008)
Low
income
countries
19722002
Narayan and
Smyth (2008)
G7
countries
19722002
Tang (2008)
Malaysia
19722003
Granger
causality
ARDL
Energy & GDP
are co-integrated
GDP ↔ energy
Hou (2009)
China
19532006
ADF; Johansen
co-integration;
Hsiao’s
Granger
Energy & GDP
are not cointegrated
GDP ↔ energy
Payne (2009)
USA
19492006
Toda and
Yamamoto
No causal
relationship
Zhang and
Cheng (2009)
China
19602007
Toda and
Yamamoto
GDP → energy
Acaravci and
Ozturk (2010)
Albania
Bulgaria
Romania
19902006
Pedroni cointegration
No causal
relationship
Balcilar et. al.
(2010)
G7
countries
19602006
Granger
causality
No causal
relationship
22
Johansen;
VECM
Energy & GDP
are co-integrated
Energy → GDP
Johansen;
Granger
causality VECM
GMM-SYS,
panel VAR
model
Panel cointegration
Granger
causality
Energy & GDP
are co-integrated
GDP → energy
No causal
relationship
Energy → GDP
Authors
Country
Menyah and
Rufael (2010)
South
Africa
Period
Methodology
Major findings
19652006
Bound test cointegration,
Granger
Energy → GDP
Chandran et.
al. (2010)
Malaysia
19712003
ARDL
Ozturk et. al.
(2010)
Low
income
countries
Electricity &
GDP are cointegrated
Electricity →
GDP
19712005
Pedroni(1999);
Pedroni (2001)
GDP ↔ energy
Tsani (2010)
Greece
Azlina (2011)
Malaysia
19602006
19702009
Fallahi (2011)
USA
19602005
Tsai and Pao
(2011)
BRIC
countries
19802007
Toda and
Yamamoto
Co-integration
VECM
Markovswitching
VAR; Granger
Co-integration;
Granger
causality –
VECM
Jafari et. al.
(2012)
Indonesia
19712007
Al-mulali and
Che Normee
(2013)
16
emerging
countries
19802008
Saboori and
Sulaiman
(2013)
ASEAN
countries
19712009
Australia
19652007
Turkey
19702003
Apergis and
Payne (2010)
South
America
19802005
Oh and Lee
(2004)
Korea
19701999
Belloumi
(2009)
Tunisia
19712004
Salahuddin
and Khan
(2013)
Lise and
Montfort
(2007)
23
TodaYamamoto
Pedroni cointegration;
Granger
causality
ARDL;
Granger
causality VECM
Johansen;
VAR; Granger
causality
ADF; ECM;
Granger
Pedroni cointegration;
Granger
Johansen &
Juselius;
Granger
Granger
VECM
Energy → GDP
GDP → energy
No causal
relationship
Co-integrated;
GDP ↔ energy
No causal
relationship
Energy & GDP
are co-integrated
Energy → GDP
Energy & GDP
are co-integrated
GDP ↔ energy
Energy & GDP
not co-integrated
Energy → GDP
GDP → energy
Energy → GDP
GDP ↔ energy
GDP ↔ energy
Authors
Country
Period
Methodology
Major findings
Altinay and
Turkey
Karagol (2004)
19502000
Hsiao’s
Granger
No causal
relationship
Payne (2009)
19492006
Toda and
Yamamoto
No causal
relationship
USA
Note: → indicates unidirectional causal relationship; ↔ indicates bidirectional causal relationship
24
CHAPTER 3
RESEARCH METHODOLOGY
3.1.
Introduction
The purpose of this study is to examine the relationship between
disaggregated energy consumption and economic growth in
Malaysia. The study begins with the problem statement followed by
the research question and objectives of the study. This will be a
quantitative study whereby the required data and information will
be gathered from secondary sources, and in this case the major
sources of data collection would be the World Development
Indicators (WDI) and the National Energy Balance, Malaysian
Energy Information Hub.
3.2.
Estimated Model
In this study, multivariate framework will be used to model the
economic growth – energy consumption nexus. The model
specification can be expressed as follows:
=
+
+
(1)
+
25
Where,
RGDPC
=
Real GDP Per capita (base=2005)
EC
=
Energy consumptions, which includes
a)
EL = electricity
b) NG = natural gas
c)
CC = coal and coke
d) PP = petroleum products
P
=
Consumer price index (2005=100)
ε
=
Error term
t
=
Time index
The variables considered in this study are as follows:

Gross domestic product (GDP) per capita as the dependent
variable (DV) – which is the main and most commonly used
indicator for economic growth. The per capita basis is chosen
in order to account for changes in population structure (i.e.
population growth). The data for this variable was sourced
from WDI of the World Bank database and the series are PPP
adjusted in constant 2000 US Dollars.
26

Disaggregated energy consumption as the independent
variable (IV) – which is based on different energy sources
namely electricity, natural gas, coal and coke and petroleum
products measured in kilo tons of oil equivalent (ktoe). The
data for this variable was sourced from the Malaysian Energy
Information Hub.

Consumer price index (CPI) as independent variable (IV) –
which is used as the proxy to overall price level given its
importance in influencing growth and energy consumption.
The data was sourced from the WDI.
This study utilises secondary data covering the period of 1978 to
2012. This period of study was chosen because the required data was
not available for earlier periods.
Given that the values of the variables are very large, we therefore
transform the variables into logarithmic form to make the data
smaller and have a better fit when conducting the regression. Thus,
the basic model will be expressed in logarithmic form and will be
used throughout this research as follows:
=
+
+
+
27
(2)
Since the aim of this study is to investigate the impact of the
disaggregated energy consumption (namely electricity, natural gas,
coal and coke, and petroleum products) on economic growth, four
sets of Ordinary Least Square (OLS) regressions will be conducted.
3.3.
Data Analysis
In order to estimate Equation (2), this study uses the Ordinary Least
Square (OLS) regression method which was first described by Carl
Friedrich Gauss, a German Mathematician. The OLS method is
specified by an equation with certain parameters to observed data.
This method is extensively used in regression analysis and
estimation as it can provide a unique estimator of β with a lower
possible error term.
The first step of the analysis is to compute the parameters of interest
in Equation (2). This is important in order to determine the nature of
linkages between GDP per capita and energy consumption. If the
value of coefficient is negative, the relationship is negative and vice
versa.
The next thing to check is the statistical significance of the model. In
this case, the t-statistics would be useful for making inferences about
28
the regression coefficients. The t-statistics is the coefficient estimate
divided by the standard error and the standard error is the square
root of the variance of the regression coefficient. This can be checked
by looking at the P-values, which are the probabilities that the
coefficients are not statistically significant. Generally, a P-value of
less than 0.1 is accepted as significant.
The overall significant of the regression line can also be using the Fstatistics i.e. by looking at the “Significance F” value in the result.
This measures the likelihood that the model as a whole describes a
relationship that emerged at random, rather than a real relationship.
As with the P-value, the lower the significance F value, the greater
the chance that the relationships in the model are real.
In addition to the t-statistics and F-statistics, the R-square statistics
will also be used to analyze the results. The R-square statistics
represents the percent of the total variation in the dependent variable
that is explained by the independent variables, i.e., the model's
overall “goodness of fit”. R-squared (R2) which is the coefficient of
multiple determination is defined as:
=
29
where RSS is the residual sum of squares. In this analysis the value
of R-squared is checked to determine whether the regression line is
best in explaining the data. The line is assumed to be best when the
value of R-squared is nearest to 1.
30
CHAPTER 4
RESULTS AND DISCUSSION
4.1.
Introduction
In this chapter the empirical results of the relationship between the
dependent variable (economic growth) and the independent
variables (disaggregated energy consumption namely electricity,
natural gas, coal and coke, and petroleum products and CPI) are
presented.
4.2.
Descriptive Statistics
The descriptive statistics for the variables used in this study covering
the period of 1978 – 2012 are given in Table 2 and generally there
seems to be no extreme deviation from normal distribution.
Table 2: Descriptive Statistics
ln EL
ln NG
ln CC
ln PP
ln GDPC
ln P
Mean
7.9501
7.1581
6.2354
9.4666
8.2683
4.3370
Maximum
9.2114
9.2307
7.5099
10.1207
8.8226
4.7844
Minimum
6.4036
3.4340
3.1355
8.4020
7.6349
3.7536
Standard
Deviation
0.9077
1.8714
1.1445
0.5730
0.3679
0.2972
31
4.3.
Correlation Analysis
As this study envisaged investigating the relationship between the
variables, correlation analysis was conducted to give an overview of
what variables tend to go up and down together and in what
direction. Table 3 shows the correlation between the variables.
Table 3: Correlation Analysis
EL
EL
NG
CC
PP
GDPC
P
1
NG
0.9760
1
CC
0.9749
0.9554
1
PP
0.9686
0.9318
0.9464
1
GDPC
0.9843
0.9504
0.9683
0.9870
1
P
0.9843
0.9514
0.9731
0.9809
0.9904
1
From Table 3 we can see that the variables are positively related and
the strength of the association is very high since the value of the
Pearson’s correlation coefficient (r) is close to positive (+) 1 for each
of the variable. The positive correlation indicates that the variables
increase or decrease together in the same direction.
32
4.4.
Ordinary Least Square Regression
Correlation provides a general indicator of the linear relationship
between variables; however, it does not allow prediction of one
variable based on the other. Thus, in order to analyze the effect of
independent to the dependent variables, Ordinary Least Square
(OLS) regression is used to estimate Equation (2).
Four sets of regression analyses were conducted based on each of the
type of energy source (disaggregated energy consumption). The
following sub-sections will discuss the results of the OLS regression
for the different energy sources respectively.
4.4.1. Analysis between electricity consumption and economic
growth
Table 4 presents the results of the OLS regression using electricity
consumption as an indicator for energy consumption.
33
Table 4: Results using Electricity Consumption (EL)
Coefficients
Standard Error
t Stat
P-value
Intercept
4.708
0.319
14.745
8.040E-16
ln EL
0.337
0.058
5.763
2.157E-06
ln P
0.204
0.178
1.141
0.262
Regression Statistics
Multiple R
0.9943
R Square
0.9886
Adjusted R Square
0.9879
Standard Error
0.0405
Observations
35
ANOVA
df
SS
MS
F
Significance
F
Regression
2
4.548
2.274
1388.089
8.084E-32
Residual
32
0.052
0.002
Total
34
4.601
Based on the results in Table 4, the equation can be expressed as
follows:
= 4.708 + 0.337
+ 0.204
34
+
It can be seen that the value of coefficient for ln EL (electricity
consumption) is positive, indicating a positive relationship between
electricity consumption and the economic growth. In other words,
for each percentage point of increase in electricity consumption, the
economic growth goes up by 0.337 percent.
The significance of the relationship between each independent
variable (electricity consumption and CPI) and the economic growth
(dependent variable) can be estimated using the t-statistics by
looking at the P-value of each of the variable. According to Table 4,
the P-value of ln EL is found to be much less than 0.05. However, the
other independent variable in this model namely CPI (ln P) turned
out to be statistically insignificant with a P-value of 0.262.
The result also shown that the value of R-squared (R2) is very high
(0.9886) that can be interpreted that the data fits the statistical model
very well, meaning that 98.86 percent of the variance in the observed
values of the dependent variable is explained by the model. The
significance F value that indicates the overall significance of the
regression line was also found to be very small.
35
On the basis of this analysis, it was established that electricity
consumption is statistically significant with a highly positive impact
on economic growth.
4.4.2. Analysis between natural gas consumption and economic
growth
Table 5 presents the results of the OLS regression using natural gas
consumption as the independent variable.
Table 5: Results using Natural Gas Consumption (NG)
Coefficients
Standard Error
t Stat
P-value
Intercept
2.685
0.287
9.360
1.115E-10
ln NG
-0.015
0.014
-1.118
0.272
ln P
1.313
0.087
15.167
3.641E-16
Regression Statistics
Multiple R
0.9888
R Square
0.9777
Adjusted R Square
0.9763
Standard Error
0.0567
Observations
35
ANOVA
df
SS
MS
F
Significance
F
Regression
2
4.498
2.249
699.904
3.875E-27
Residual
32
0.103
0.003
Total
34
4.601
36
Based on the results in Table 5, the equation can be expressed as
follows:
= 2.685 − 0.015
+ 1.313
+
The result shows a negative relationship between natural gas
consumption and economic growth. However, even though the Rsquared value is very high at 0.9777, the P-value of ln NG which is
0.272 indicates insignificant relationship. This result implies that
natural gas consumption does not have a significant impact on the
economic development.
4.4.3. Analysis between coal and coke consumption and economic
growth
Table 6 shows the results of regression using coal and coke
consumption as the independent variable.
37
Table 6: Results using Coal and Coke Consumption (CC)
Coefficients
Standard Error
t Stat
P-value
Intercept
2.497
0.256
9.766
4.030E-11
ln CC
-0.050
0.023
-2.153
0.0389
ln P
1.402
0.089
15.792
1.159E-16
Regression Statistics
Multiple R
0.9898
R Square
0.9797
Adjusted R Square
0.9784
Standard Error
0.0540
Observations
35
ANOVA
df
SS
MS
F
Significance
F
Regression
2
4.508
2.254
772.807
8.210E-28
Residual
32
0.093
0.003
Total
34
4.601
According to the result shown in Table 6, the equation can be written
as below:
= 2.497 − 0.050
+ 1.402
38
+
We can see from the regression results that coal and coke
consumption relates to the economic growth in a negative manner as
the coefficient of ln CC turned out to be negative. The P-value for ln
CC of 0.0389 indicates statistical significance of the variable at the 5
percent level. The other independent variable (ln P) was also
statistically significant with a very low P-value.
The significance F value was found to be extremely low, thus
suggesting
an
overall
significance
of
the
regression
line.
Furthermore, the value of R-squared is also very high (0.9797)
signifying a considerably good fit to the model. Hence, it can be
interpreted from this result that coal and coke consumption has a
high impact on the economic growth.
4.4.4. Analysis between petroleum products consumption and
economic growth
Finally the results of regression using petroleum products as the
independent variable are presented in Table 7.
39
Table 7: Results using Petroleum Products Consumption (PP)
Coefficients
Standard Error
t Stat
P-value
Intercept
2.524
0.132
19.097
4.682E-19
ln PP
0.347
0.064
5.433
5.628E-06
ln P
0.567
0.123
4.605
6.240E-05
Regression Statistics
Multiple R
0.9939
R Square
0.9879
Adjusted R Square
0.9872
Standard Error
0.0417
Observations
35
ANOVA
df
SS
MS
F
Significance
F
Regression
2
4.545
2.273
1308.607
2.054E-31
Residual
32
0.056
0.002
Total
34
4.601
Based on Table 7, the equation of the model can be expressed as
follows:
= 2.524 + 0.347
+ 0.567
40
+
In this analysis, it was found that petroleum products consumption
is positively related to the economic growth, denoted by the positive
coefficient for ln PP as shown in Table 7.
The exceptionally low P-values of both independent variables (ln PP
and ln P) indicate that these variables are statistically significant. The
high value of R-squared (0.9879) also suggested “goodness of fit” to
the model with an overall significance of the regression line as
evidenced by the extremely low value of significance F. Therefore, on
the basis of this regression analysis it can be deduced that the impact
of petroleum products consumption on the economic growth is
significant.
In summary, the findings of this study show that only electricity,
coal and coke, and petroleum products consumptions are found to
be important determinants of GDP growth. However, the impact of
coal and coke is negative.
41
CHAPTER 5
CONCLUSION
5.1.
Summary
Survey of the literature reveals that there have been profound
interests in exploring the relationship between energy consumption
and the economic growth. However, most of the research have found
that the relationship between the variables to be varied and not
completely conclusive.
The key research question this paper attempted to answer is to
determine the impact of a specific type of energy consumption on
economic growth in Malaysia. Different from earlier research, this
paper studied the nexus based on the disaggregated energy
consumption namely electricity, natural gas, coal and coke, and
petroleum products using annual time series data for the period of
1978 – 2012.
In this study data of gross domestic product (GDP) per capita was
used to denote economic growth, and a third variable was also
introduced, that is the overall energy price level (using CPI as the
42
proxy) due to its effects on both energy consumption and economic
growth such that the result obtained will be more significant.
By employing the Ordinary Least Square (OLS) regression method,
four sets of analyses was conducted using the different types of the
energy sources as the independent variables. This study found that
three types of the disaggregated energy consumption have
significant impact on the economic growth, namely electricity, coal
and coke and petroleum products. The result for natural gas
consumption as an indicator for energy consumption, however,
shown that it is statistically insignificant.
Based
on
the
analysis,
electricity
and
petroleum
products
consumption was found to be positively related to the economic
growth which indicates that higher economic development is
expected when more electricity and petroleum products are
consumed. This result is congruent with the growth hypothesis
which means that energy consumption is vital in the process of
economic prosperity.
On the other hand, the analysis also revealed that coal and coke
consumption have a negative impact on economic growth (an
increase in coal and coke consumption will suppress the growth).
43
This negative relationship is anticipated and may be explained by
the fact that Malaysia is heavily dependent on imported coal, thus
exposed to price fluctuations. Therefore, higher government
spending is expected with increased coal and coke consumption.
5.2.
Limitations of the Study
There are a number of shortcomings in this study that is deemed to
be worth mentioning. Firstly, the limitation is in terms of the data
used in this study. As mentioned previously, a third variable that is
the overall energy price level was introduced in the analysis.
However, price of energy differs in various sectors (such as
residential, commercial and industrial sectors) and generally are not
readily available; thus consumer price index (CPI) was used as proxy
for energy prices.
Another limitation is a relatively small number of observations used
in this study, which are 35 observations; thus there is room for
improvement. Higher number of observations would generally
increase the accuracy and result in more robust findings for the
study. There is also limitation in terms of omitted variable bias that
could have been accounted for with the inclusion of other additional
44
variables that could contribute towards GDP. Such variables include
labour, capital, and foreign trades or exports.
Finally, the study is also limited to the nexus between the
disaggregated energy consumption and the economic growth.
However, it does not tell whether the relationship exists in the shortrun or the long-run.
5.3.
Recommendations
The result of this study indicates that economic growth is positively
dependent on electricity and petroleum products consumption; thus
suggesting any conservation policy on the consumption of these two
energy sources may have an adverse effect on the economic growth.
In this regard, a more suitable policy may be one that relates to
efficient consumption of energy resources or more sustainable type
of energy sources such as renewable energy.
On the contrary,
the relationship between
coal and coke
consumption and economic growth was established as negative
based on this study. This result could also imply that a policy on
reducing coal and coke consumption or more efficient usage of this
energy source may be implemented without dampening the
45
economic development since the relationship was found to be
negative.
Nonetheless, if similar research needs to be conducted in the future,
it may be prudent to consider taking the GDP value of the relevant
sector(s) with the highest energy consumption such as the industrial
and/or manufacturing sector(s) instead of the overall real GDP per
capita. This could be more reflective of the impact of the
disaggregated energy consumption on the output growth. In
addition, future research may also consider including renewable
energy consumption in the analysis.
46
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50
APPENDICES
Appendix A: Original Data from Malaysian Energy Information Hub
Year
Final Energy Demand by Fuel Type (ktoe)
1978
1877
Fuel
Oil
709
1979
2112
807
1178
114
358
207
231
25
33
33
684
1980
2368
846
1317
121
351
255
269
23
35
53
747
1981
2811
734
1423
124
368
285
270
26
39
99
800
1982
3094
422
1529
135
364
346
314
24
46
93
866
1983
3051
604
1756
174
352
338
320
26
45
249
935
1984
2901
528
1925
188
357
371
315
37
134
270
1019
1985
2773
554
2088
229
310
288
386
28
515
362
1079
1986
2803
489
2178
271
301
429
382
27
1056
268
1164
1987
3026
529
2297
330
269
435
358
27
1132
327
1253
1988
3275
598
2451
379
255
459
366
33
1058
189
1393
1989
3816
785
2585
415
211
499
313
11
1070
595
1548
1990
4421
883
2901
548
203
630
229
10
1093
513
1715
1991
4873
945
3135
612
180
690
467
12
1125
599
1925
1992
5291
1088
3326
733
160
764
565
0
1368
672
2218
1993
5339
1293
3666
1119
148
875
625
10
1716
487
2450
1994
5643
1392
4139
926
152
978
654
10
1863
598
2932
Diesel
Motor
Petrol
1010
337
ATF &
AV Gas
215
NonEnergy
180
Refinery
Gas
27
Natural
Gas
31
Coal &
Coke
23
LPG
Kerosene
101
52
Electricity
604
Biodiesel
Year
Final Energy Demand by Fuel Type (ktoe)
1995
5810
Fuel
Oil
1506
1996
6735
1770
5205
1215
197
1335
742
4
2474
727
3777
1997
7314
1978
5586
1245
169
1439
843
4
2465
740
4384
1998
6252
1678
5854
1301
165
1619
615
4
2726
767
4577
1999
6506
1792
6793
1523
162
1424
579
3
3023
608
4815
2000
7627
1875
6387
1362
131
1574
622
3
3863
991
5263
2001
8116
1497
6827
1392
99
1762
626
4
4621
977
5594
2002
8042
1590
6948
1542
92
1785
633
6
5644
1086
5922
2003
8539
1256
7360
1436
93
1852
632
7
5886
1212
6313
2004
9262
1463
7839
1542
86
2056
626
11
6490
1305
6642
2005
8672
1954
8211
1509
82
2010
564
10
6981
1348
6943
2006
8540
1901
7518
1520
79
2152
672
12
7562
1335
7272
2007
9512
2203
8600
1475
76
2155
823
9
7708
1361
7683
2008
9167
1963
8842
1475
75
2112
818
0
7818
1713
7986
2009
8634
1291
8766
2506
30
2120
799
0
6800
1613
8286
2010
8388
478
9560
2920
20
2380
657
0
6254
1826
8993
2011
8712
414
8155
2892
19
2553
1178
0
8515
1759
9235
24
2012
8757
768
8919
2891
38
2522
739
10206
1744
10011
115
Diesel
Motor
Petrol
4548
177
ATF &
AV Gas
1160
NonEnergy
718
Refinery
Gas
8
Natural
Gas
1935
Coal &
Coke
712
LPG
Kerosene
2215
53
Electricity
Biodiesel
3375
Appendix B: Original Data from World Development Indicators
1978
GDP per capita
(constant 2005 US$)
2069.181384
Consumer price index
(2005 = 100)
42.67267479
1979
2210.233513
44.23213404
1980
2318.238155
47.18459339
1981
2418.614522
51.76149895
1982
2498.262276
54.77344883
1983
2586.232921
56.80238635
1984
2713.108895
59.01613019
1985
2609.321549
59.22059676
1986
2564.967661
59.65705425
1987
2625.224166
59.83006442
1988
2802.469316
61.35963166
1989
2969.159342
63.08580137
1990
3147.08807
64.73726213
1991
3355.571355
67.55872781
1992
3559.517075
70.7794066
1993
3813.189065
73.28258074
1994
4060.355831
76.01233529
1995
4347.815999
78.635198
1996
4662.48099
81.37843364
1997
4878.608007
83.54514631
1998
4408.533561
87.94826125
1999
4568.553441
90.3620552
2000
4861.857591
91.74887802
2001
4783.877734
93.04876211
2002
4940.986535
94.73096506
2003
5126.855916
95.67146943
2004
5372.234083
97.12428107
2005
5553.943582
100
2006
5756.408216
103.6092356
2007
6007.900573
105.7097608
2008
6185.512962
111.4611986
2009
5984.915281
112.1113612
2010
6318.901213
114.0285071
2011
6531.320564
117.6774194
2012
6786.185307
119.6254064
Year
54