The impact of oil price on inflation - The case of Vietnam.pdf

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES
HO CHI MINH CITY THE HAGUE
VIETNAM THE NETHERLANDS
VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
THE IMPACT OF OIL PRICE ON INFLATION
THE CASE OF VIET NAM
A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
By
TRUONG NGO TRONG NGHIA
Academic Supervisor:
DR. NGUYEN VAN NGAI
HO CHI MINH CITY, NOVEMBER 2012

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Acknowledgement
Over two years not so long but it is one of the most interesting periods of my life
with many impressive memories. I would like to take this opportunity to express my
deep gratitude to the Vietnam-Netherlands Master Program for Economics of
Development for organizing many helpful and exciting curriculums.
For the completion of this thesis, I have indebted to many people who have given
me their continued support, advice and guidance.
First of all, I would like to express my sincere gratitude to my supervisor Dr.
Nguyen Van Ngai who gave me valuable guidelines, comments, suggestions, and
inspiration for the successful completion of this study. Besides, his friendly and
thoughtful instructions have given me a great deal of encouragements to overcome
difficulties in the whole research process.
I am also thankful to Dr. Nguyen Trong Hoai, Dr. Nguyen Hoang Nam, Dr. Tu Van
Binh, MBA Ly Thi Minh Chau, Tutor-Mr. Phung Thanh Binh and all lecturers and
program administrators in the Vietnam – The Netherlands Program for M.A. in
Development Economics. They gave me advanced knowledge and help me kindly
during the course.
I would like to express my heartfelt thank to all my classmates in MDE15, MDE16,
especially Tran Tuyet Hanh, Tran Van Long, Le Trong Binh, Vo Thi Ngoc Trinh,
Le Anh Khang, Nguyen Van Dung, Nguyen Xuan Phap, Nguyen Le Thao Nguyen
and other classmates for their continuous support and encouragement.
Last but not least, I would like to express my deepest thanks to my parents, my
brother, my close friends who have always given the most favorable environment
and kept encouraging me that made me feel more confident during my study.

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Certification
“I certify that the content in this thesis has not already been submitted for any
degree and has not submitted for any other degree until now.
I certify that this thesis is done from the best of my knowledge. All the aids that I
received during the time in preparing the thesis as same as all sources used have
been acknowledged in my thesis.”
Signature
Truong Ngo Trong Nghia
Date: / / 2012

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Abstract
A steep upward trend in the price of crude oil in recent years, reaching a spike
record in middle of 2008, has led to increasing concern about its impacts on
macroeconomic, both abroad and in Vietnam. In this study, using the vector auto
regression approach (VAR) with monthly dataset from 2001M1 to 2010M10, I
attempt to empirically investigate the dynamic effects of oil price and Vietnam
macroeconomics. Focusing on the reduced-form of causal relationships between
world oil price (expressed in Vietnamese price) and macroeconomic variables, I
have used both linear and non linear form of oil prices to get the results of their
impact on price level and output. In empirical analysis, I find consistent evidence
that oil price shocks have a significant effect on output and price level in short term.
In detail, my research finds a weak and positive statistically significant association
between oil price shocks and price level. The output is more highly sensitive and I
find an empirical evidence about the negative impact of oil price shocks on
economic growth although it’s not straight forward. I also assert the existence of
asymmetric impact of oil price proxies’ changes on economic growth rate.
Key words: inflation, GDP, oil price shock, VAR models, Cointegration, Granger
causality, Phillips curve

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TABLE OF CONTENTS
Acknowledgement.........................................................................................................ii
List of Tables.................................................................................................................4
List of Figures ...............................................................................................................5
List of Acronyms...........................................................................................................6
Chapter 1: Introduction ................................................................................................7
1.1 Problem statement..................................................................................................7
1.2 Research Objectives...............................................................................................8
1.3 Research Questions ................................................................................................8
1.4 Scope and methodology of the Study ....................................................................9
1.5 Thesis structure ....................................................................................................10
Chapter 2: Literature Review ....................................................................................11
2.1 Review oil shocks in history ................................................................................11
2.1.1 Suez Crisis in period 1956-1957.......................................................................14
2.1.2 OPEC Embargo in 1973-1974: .........................................................................14
2.1.3 Iranian revolution and oil price fluctuation in 1979 .........................................15
2.1.4 Iran-Iraq War in 1980-1981 ..............................................................................15
2.1.5 The great price collapse in 1981-1986..............................................................15
2.1.6 First Persian Gulf War in 1990-1991................................................................16
2.1.7 The downtrend of oil price in 2001...................................................................16
2.1.8 Growing demand and stagnant supply.............................................................17
2.2 How higher oil prices affect the economy ...........................................................18
2.2.1. Why oil shock seems to be the big economic headache ...................................18

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2.2.2 The scenario of oil price and inflation in Vietnam ............................................21
2.3 Review price level and inflation theories.............................................................22
2.4 The transmission mechanism of oil price shocks.................................................25
2.5 Approaches to estimate oil impact on macro economy variables........................30
2.6 Empirical studies about the oil price-macroeconomic relationship.....................32
2.7 Conceptual Framework .........................................................................................44
Chapter 3: Model Specification and Data ..................................................................45
3.1 Analytical Framework..........................................................................................45
3.2 Model Specifications............................................................................................46
3.3 Steps of Estimation ..............................................................................................50
3.3.1 Descriptive statistics..........................................................................................50
3.3.2 Unit root testing.................................................................................................50
3.3.3 Granger Causality Test......................................................................................51
3.3.4 Impulse response functions...............................................................................53
3.3.5 Variance decomposition....................................................................................53
3.4 Data Sources.........................................................................................................53
Chapter 4: The impact of oil price on inflation-the case of Vietnam ........................56
4.1 Descriptive Statistics............................................................................................56
4.2 Unit Root Test......................................................................................................57
4.3 Var Granger Causality Test..................................................................................58
4.4 Impulse Responses and Variance Decompositions..............................................61
4.5 Asymmetric Impacts ............................................................................................65
4.6 Result comparisons ..............................................................................................70

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Chapter 5: Conclusion and Policy Implication ..........................................................73
5.1 Conclusions...........................................................................................................73
5.2 Policy Implication .................................................................................................75
5.3 Limitation and Further Studies..............................................................................78
5.3.1 Limitation...........................................................................................................78
5.3.2 Further Studies ...................................................................................................79
References ...................................................................................................................81
Appendix .....................................................................................................................88

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List of Tables
Table 2.1: Summary results of empirical studies........................................................40
Table 3.1 The definition of variables in the model.....................................................55
Table 4.1: Description statistic of key variables.........................................................56
Table 4.2: Augment Dickey-Fuller test.......................................................................57
Table 4.3: Philips-Perron test......................................................................................58
Table 4.4: Optimal lag length......................................................................................59
Table 4.5: VAR Granger- CausalityTest.....................................................................60
Table 4.6: Variance Decompositions for Var Model..................................................62
Table 4.7: Granger causality test of proxies of oil price shocks.................................65
Table 4.8: Accumulated Response of PC_IP_SA to non-linear oil price shocks .......68

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List of Figures
Figure 2.1: Price of oil in 2009 dollars, 1973:M1-2010:M10. Price of West Texas
Intermediate deflated by CPI (Hamilton, 2011)..........................................................12
Figure 2.2: The natural logarithm of the real price of oil, 1861-2009, in 2009 U.S.
dollars..........................................................................................................................12
Figure 2.3: When oil prices head up, the US turns grey: the oil market and US
recessions ....................................................................................................................18
Figure 2.4: Illustration of oil price and macroeconomic variables in level ................21
Figure 2.5: Factor contributions of price level............................................................23
Figure 2.6: Cost-push inflation in the AS-AD model .................................................24
Figure 2.7: Demand-pull inflation in the AS-AD model ............................................25
Figure 2.8: Two round effects of oil price increases...................................................26
Figure 2.9: Mix transmission channels of oil price shocks.........................................27
Figure 2.10: Conceptual framework ...........................................................................44
Figure 4.1: The relationships of variables...................................................................60
Figure 4.2: The impulse response functions for basic model .....................................62
Figure 4.3: The variance decompositions of variables ...............................................64
Figure 4.4: The impulse response functions of output to negative oil price changes.66
Figure 4.5: The impulse response functions of price level to net oil price increase...69

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List of Acronyms
AIC: Akaike Information Criterion
AR: Autoregressive
ARCH: Autoregressive Conditional Heteroskedasticity
CPI: Consumer Price Index
GARCH: Generalized Autoregressive Conditional Heteroskedasticity
INF: Inflation
OLS: Ordinary least squares
OPEC: Organization of Petroleum Exporting Countries
PPI: Producer Price Index
SBV: State Bank of Vietnam
SC: Schwartz criterion
UK: the United Kingdom
US: the United States of America
VAR: Vector Auto Regressive
WTI: West Texas Intermediate

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Chapter 1: Introduction
1.1 Problem statement
Most of nations, oil industry plays critical roles for the development in
economic, industrial, and social activities. In fact, oil price volatility not only brings a
negative effect on the GDP growth for country because of increasing of input costs,
but also influences foreign exchange markets, generates higher interest rate, leads to
monetary and financial instability, and last but not least produces inflation.
In recent years, although Vietnam is to start a crude oil exporter but we still
import a large amount of petrol. The volatile oil prices and oil shocks potentially
cause vulnerability of the economy Vietnam. The story of inflation is going on and
will certainly create bad impacts. Inflation was rather low from 1996 to 2006. But
after 2006, high inflation returned to Vietnam’s economy with two-digit rate. At the
early beginning of the year 2011, Viet Nam has to face with the very high pressure of
inflation. On 24 February, 2011, the Viet Nam’s Government has to issue the 11 The
Resolution of "package solution" to control inflation, stabilize macro-economy,
ensuring social security.
Because of the inflation in Viet Nam is so hot up to now. This study tries to
make the researches on two aspects as follows:
First, most of the empirical studies focused primarily on the relationship
between oil price and macroeconomics in the economy of the developed countries
such as US or OECD countries (e.g. Brown et at, 1995, 1999, 2004; Cunado and
Gracia, 2003; Darrat and Otis, 1996; Hamilton, 1983, 1996, 1999, 2000, 2009, 2011;
Hooker, 1996, 1999; Jimenez and Sanchez, 2004, 2005; Katsuya, 2008; Lee et al,
2002; Mork, 1989, 1994; Mory, 1993; Nagy, 2000; Webber, 2006…). Although some
researches of developing countries in Africa (e.g. Aliyu, 2009; Chhiber & Shafik,
1990; Farrell, 2001; Kiptui, 2009; Nkomo, 2006) could be identified, just few studies
of Asian developing countries with relatively high inﬂation rates could be found. In

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the Vietnamese context, very few studies have been done. Therefore, more empirical
researches are needed in the context of Vietnamese economy.
Second, this study is informative and useful for authorities through some
evidences. One important is the Granger causality between macroeconomic variables
and oil prices in the short term. In addition, the evidence of asymmetrical relationship
between the oil price changes–inflation rate and in oil price changes–economic growth
rate will be presented. All these evidences above pass through some results of impulse
response and affective decomposition in Vietnam. They will have reliable economical
basis to propose and implement policies in order to alleviate significantly negative
impact of oil shocks as same as to develop the economy less dependently on
petroleum.
1.2 Research Objectives
With the respect to the period of 2001-2010, this study aims mainly the impact
of oil price on inflation in Vietnam. Following the main objectives for the case of
Vietnam, the study is attempted:
- To analyze the effect of oil prices on macro economies, especially the
price level and output.
- To find out the evidence of asymmetries when oil price is in trend of
increasing and in trend of decreasing throughout examining the
relationship between proxies of oil price changes and inflation rates and
proxies of oil price changes and economic growth rate.
- To suggest policies to stabilize macroeconomic.
1.3 Research Questions
In order to meet these objectives, the thesis will attempt to answer the following
questions:
Main question:
- What are the impacts of oil price and its proxies on the macro economy
in the context of Vietnam over the period of 2001-2010?

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Sub-questions:
- Which are the directions of the causality relationships among oil price,
price level and output?
- How are the impacts of oil price on the macroeconomics?
- Are there any different impacts of proxies of oil price on inflation rate
and economic growth rate of Vietnam when oil price is in trend of
increasing and in trend of decreasing?
- What policies should be implied to mitigate the bad impacts of oil price
and to develop Vietnam macro economy more sustainably?
1.4 Scope and methodology of the sstudy
This study applies both qualitative and quantitative method. The first one will
be concerned later on a little bit in section 2.2.2. The second one will be concerned
mainly in section 2.6 and others next.
The quantitative method will apply the econometric techniques related to
Vector Auto-regression (VAR) model with monthly time series dataset from 2001M1
to 2010M10, with the following macro indicators: world oil price, consumer price
index, industrial production, money supply and exchange rate, taken from IMF’s
International Finance Statistic (IFS), IMF’s Direction of Trade (DOT) and Vietnam
General Statistic Office (GSO).
To carry out above objectives, I will apply the descriptive statistic and the
econometric techniques. In this study, the overview of all variables will be shown out
by the descriptive statistic as the first step. It is the full collection of max-min-mean
values, variation of all original and transformed data. Thus, we have an overview and
an evaluation about the used data quality.
With regarding to the analyzing time series data, the econometric techniques
related to vector auto regression (VAR) model will be employed to answer key
questions. Firstly, unit root test is used to examine for stationary of all variables by the
validation of t-test and F-test. Secondly, optimal lag lengths for VAR model are
chosen by different criteria to have the best model. VAR Granger causality test will
help us answer the first sub question whether the effect of oil price to inflation and

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output of economy. Then, impulse responses and variance decompositions are two
popular techniques of VAR model to answer next sub questions. Next, asymmetric
testing procedures with some proxies of oil price are used to explore the last sub
question. Collecting from those empirical results, we can conclude the role of oil price
in the context of Vietnam and propose the appropriate policies for Vietnam’s
economy.
1.5 Thesis structure
The thesis is organized in four chapters. Chapter 1 is introduction. Chapter 2
covers literature review and empirical studies. Chapter 3 presents the research
methodology. Chapter 4 reports the findings and discussion. Chapter 5 presents the
conclusion, suggests some practical policy implications, and discusses the limitation
and direction for further studies.

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Chapter 2: Literature Review
This chapter concerns about the overview of oil shocks in history, the serious impacts
of high oil prices on world economics, the scenario of oil price and inflation in
Vietnam. It also includes the review inflation theories, the transmission mechanism of
oil price shocks, the approaches to estimate oil price impacts and summary results of
empirical studies about the oil price-macroeconomic relationship.
2.1 Review oil shocks in history
Definition of oil shock
One of the clearest definitions of an “oil shock”, Wakeford (2006, p2) stated
that: “Oil shocks are usually defined in terms of price fluctuations, but these may in
turn emanate from changes in either the supply of or the demand for oil. In practice it
is unlikely for demand to grow rapidly enough to cause a price shock unless it is
motivated by fears of supply shortages. Historically, as is indicated in the following
section, the supply side has been primarily responsible for observed oil price shocks,
at least as an initial trigger”.
At least, there are two important attributes of a price shock. The first one is the
amplitude of the price increase which can be measured in absolute values or in
percentage changes. The second is one of timing including the speed and durable spell
of oil price increases. In which, three cases can happen: (1) A sharp and sustaining
price increase that can be called a “break” (e.g. occurring within a few quarters); (2) A
rapid and temporary price increase that is called a “spike”; and (3) a slowly sustaining
rise can be called a “trend”. The speed of an oil shock can harm directly economies
because it affects the ability of economies to adjust by them while able adjustments
are typically restricted in the short run. The durability of oil price increasing impacts
obviously the overall performance of many economies and extent of the
consequences.
According to Nkomo (2006: 10), vulnerable level of a particular oil-importing
country to oil shocks depends on some dimensions of the economy: the dependence
on oil importing activity or the oil consumption imported in percentage of the whole

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world; the dependence on oil resource or the proportion of oil use over the total
energy use; and the intensity of energy or the spending energy cost in percentage of
the real gross domestic product’s value. Furthermore, the developed countries could
be less vulnerable than the developing countries during the period times of oil price
shock affects; especially industrial mine and production industrialization are
considered as the important sectors being get serious impacts.
Figure 2.1: Price of oil in 2009 dollars, 1973:M1-2010:M10
Price of West Texas Intermediate deflated by CPI (Hamilton, 2011).
Measure price of oil
As the figure 2.1 showed out, many oil shocks had at least a doubling of the oil
price within a year or two. And in history, there were three eras in the determination
of international crude oil prices (Nkomo, 2006). Global oil companies determined
mainly oil prices until the 1970s. Since then the Organization of Petroleum Exporting
Countries (OPEC) set the price via its output decisions based on its influence power
and its oil export capacity. Since the late 1980s, world oil prices were set by a market-

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related pricing system which linked oil prices to the ‘market price’ of a particular
reference crude (Farrell et al., 2001: 69). Now, two important reference prices, Brent
and West Texas Intermediate (WTI) are determined on the London and New York
futures exchanges, respectively.
Figure 2.2: The natural logarithm of the real price of oil, 1861-2009, in 2009 U.S.
dollars.
Data source: Statistical Review of World Energy 2010, BP; Jenkins (1985,
Table 18); and Historical Statistics of the United States.
Key oil shocks
According to Hamilton (2011), key post-World-War-II oil shocks reviews
include the Suez Crisis of 1956-57, the OPEC oil embargo of 1973-1974, the Iranian
revolution of 1978-1979, the Iran-Iraq War initiated in 1980, the first Persian Gulf
War in 1990-91, and the oil price spike of 2007-2008. Each of the major postwar oil
shocks since 1973 which is closely connected with political conflict and economic
downturns that followed.

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2.1.1 Suez Crisis in period 1956-1957
The crisis begun from Egyptian President Nasser nationalized the Suez Canal
in July of 1956. Hoping to regain the power of canal controlling, France and Britain
encouraged Israel to invade Egypt’s Sinai territories on October 29, and in short time
later they succeeded by their own military forces. During the war, 40 ships were sunk
and blocked around the canal. In order to get through, 1-1/2 million barrels of oil were
transported per day. They established the pumping stations for the Iraq Petroleum
Company’s pipeline. Through these stations, an additional half-million barrels moved
per day to Syria arriving to ports in the eastern Mediterranean. They were also
sabotaged. That occupied 10.1% of total world output by that time. It is a bigger
fraction of world production that would be seed of the subsequent oil shocks. That
case would be experienced study in the following decades. .
And overall U.S. exportations of goods and services started to fall after the first
quarter of 1957. That is proven to be an 18% decline over the next year (Hamilton,
2011).
2.1.2 OPEC Embargo in 1973-1974:
An attack on Israel was led by Egypt and Syria beginning on October 6, 1973.
On October 17, some members of the OPEC, the Arab members announced an
embargo on oil exportation. They punished all countries viewed as supporting Israel
that were followed the significant cutbacks in OPEC’s total oil production. In
November the capacity of production from Arab members of OPEC was down 4.4
mb/d compared with what it was in September, a shortfall corresponding to 7.5% of
global supply side. The consequences later, on January 1974 the Persian Gulf
countries doubled the price of oil.
Frech and Lee (1987) estimated that the time was spent for waiting in queues to
buy gasoline added more 12% to the cost of gasoline in December 1973 and 50% in
March 1974 in USA urban. The problem was evaluated to be more severe in rural
areas, with respectively estimated costs of 24% and 84%.

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2.1.3 Iranian revolution and oil price fluctuation in 1979
The beginning of a turbulent decade in the Middle East was remarked by the
Arab-Israeli War in 1973. In defiance of the Arab states, Iran increased the oil
production bypass the 1973-74 embargoes. At the beginning of 1978, Iran exported
5.4 millions of crude oil barrels per day which were up more than 17 percent of
OPEC. But that met a public resistance in 1978, strikes spread out on the oil sector
through the fall of 1978. It caused the oil production of Iran downed by 4.8 mb/d (or
7% of world production at the time) from October 1978 to January 1979.
Frech and Lee (1987) estimated that the opportunity cost of waste time queuing
added about a third to the cost when Americans bought gasoline on May of 1979.
During 12 months, gasoline queues were again a hot phenomenon and price of oil
barrel increased from $15.85 to $39.5. That was the premise of crisis lasting 30 month
in U.S.A. In 1980, the increasing of oil price hiked the inflation rate to get peak 13.5
percent.
2.1.4 Iran-Iraq War in 1980-1981
In 1979, Iranian production recovered to about half of its pre-revolutionary
levels. But it was reduced again when Iraq launched a war against Iran in September
of 1980. The total lost of production from both countries amounted to about 6% of
world production at that time within a few months.
This shortage in supply side caused the real price of oil was double during the
period 1978-1981. In the contrary, during that period there was a negative reaction in
demand side in which fuel demands decreased 13 percent on some main oil
consumption markets such as U.S.A, Japan, and Europe.
2.1.5 The great price collapse in 1981-1986
The consequences of oil crises in 1973 and in 1979 were the reasons that the
economic growth of the industrial countries, oil demands all over the world slowed
down from 1981 to 1986.

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This really caused oil price strongly felt from $35 in 1981 to lower than $10 in
1986. While this event was a motivation for development on the demand side of oil
consumers, vice versa this delegated an “oil shock” for the producers.
2.1.6 First Persian Gulf War in 1990-1991
By 1990, Iraqi production recovered its levels of the late 1970s. Due to this
country invaded Kuwait on August 1990, its production collapsed again and it parallel
induced Kuwait’s substantial production down. At that time, both countries accounted
for nearly 9% of world production. Then, the oil exporting embargo with Iraq and
Kuwait was enforced by United Nations Organization. It rejected 5 million barrels per
day out of the market and pushed the oil price increase. Despite oil price did not
exceed the peak of 1979 and 1979-1980 crises, as fever it lasted within nine months.
External expression during 2 months, the price of each barrel doubled from $17 to $36
per barrel.
This crisis may be the reason that led the USA recession to the collapse of
financial market. Other powerful countries also were rolled in recession because they
had to suffer indirect influence such as Japan, Australia, England and Canada.
2.1.7 The downtrend of oil price in 2001
In the summer of 1997, Asian crisis started with Thailand, South Korea, and
other countries. Like a domino effect, it spread out their currency with serious stresses
to the financial system. At the end of 1998, the dollar oil price followed the crisis
falling below $12 a barrel. In 1999, the world petroleum consumption restored to
strong growth. But after 2000, the world economy declined. Especially after the event
of September 11th terrorism, the oil price trended to decrease more. A broader global
economic downturn happened and the tenth postwar U.S. recession began in March of
2001. In 2001, due to the decreasing of consumption rate contributed to oil price fall,
the price was only $20 per barrel.

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2.1.8 Growing demand and stagnant supply
Global economic growth in 2004 and 2005 was quite impressive, with the IMF
estimating that real gross world product grew at an average annual rate of 4.7%
(Hamilton, 2009b). Over this period, world oil consumption grew up 5 mb/d and 3%
per year on average. Even though there was initially enough excess capacity on supply
side to keep production growing along with demands, these strong demand pressures
were the key to make the oil price increase steadily. In recent years, one of the most
important suppliers has been Saudi Arabia. This nation contributed 13% of global
field production in 2005 and kept an active role as the world’s residual supplier during
the 1980s and 1990s. They could decide to increase their production whenever
needed. But in the event, Saudi production was 850,000 barrels a day lower in 2007
than it had been in 2005. However, oil demands continued to grow, along with world
real GDP increasing an additional 5% per year in 2006 and 2007. That was a faster
rate of economic growth in which oil consumption accompanied the 5 mb/d increasing
during 2003 - 2005. Especially, China increased its own consumption by 840,000
barrels a day from 2005 to 2007.
In the short-run, according to Hamilton (2009a), price elasticity of oil demand
has been quite low and may have been even smaller over the last decade (Hughes,
Knittel, and Sperling, 2008). It means a little bit demand increase needs a
compensation of large price increase. With no more oil being produced, a large shift
of the demand curve in case of the increasing limit on supply side led a raise of oil
price from $55 a barrel in 2005 to $142 a barrel in 2008.
On December of 2007, the USA recession began again that was likewise the
worst in postwar experience, but of course the financial crisis rather than any oil-
related disruptions were the leading contributing factor of that downturn.

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2.2 How higher oil prices affect the economy
2.2.1. Why oil shock seems to be the big economic headache
Why we should worry
In 2008, oil prices reached USD150 per barrel. Shortly afterwards, the global
economy collapsed. Based on HSBC (2011, February), at that time many problems
occurred such as the imploding US housing market, the beginnings of a securitization
crisis, the collapse of Lehman Brothers. Nevertheless events in three years ago, much
evidence were shown that substantial changing oil prices are so hot news for the
global economy.
Figure 2.3 shows the level of oil prices in real terms (adjusted using the US
consumer price index) tracked against US recessions. Seemingly like a cycle,
increases in oil prices of more than 100% lead to declining GDP.
Figure 2.3: When oil prices head up, the US turns grey: the oil market and
US recessions
Source: Thomson Reuters Datastream
As oil prices approach historical record levels, there are some debates to
discuss how is important the impact of oil price changes on the global economy have
been clarified. Quite recently, according to Rasmussen and Roitman (2012, February)-
two IMF economists found that generally there has been a relationship between oil
price rises and good times in the global economy. They concluded that causing of the
oil price shocks there were lagged negative effects on the output of OECD economies

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in which a 25% of oil price increase was related with 0.3% of output decline of oil
importing countries for over two years.
With the same topic research, Li (2012) examined the global economic growth
affects in the situation of the oil price changes. He argued that there have been
significant negative impacts of oil price rises on world economic growth. By the
evidence, the analysis of the data from a time-series of 1971 - 2010 showed that there
was a relationship between an increase in real oil price by 10 dollars and a reduction
of world economic growth rate by between 0.4 and 1% in the following year.
So as oil prices approach historical hikes, that the global economy is seriously
vulnerable. Wherever oil prices eventually end up, it is possible to tease out some of
the more important economic effects. There are immediate winners (net oil producers
and exporters) and losers (consumers and importers) despite any given shift in oil
prices. It is not only a straight-forward redistribution of income but also a big problem
occurs.
HSBC Bank emphasized that for global demand, one of the most important
matters is the marginal propensity to spend of oil producing nations relative to oil
consuming nations. In general, that is higher for oil consuming nations than producers
(for example, comparring the balance of payments position of the US with Saudi
Arabia). Therefore, a big increase in oil prices intends to dampen global demand.
Oil prices as a tax
It’s obvious that for net oil consuming nations, higher oil prices have an effect
similar to an extra in indirect taxes. The target to smooth over the effects of higher oil
prices is either to offset by an tax cut on importing price or to subsidize the
downstream of oil products (subsidizes are simply negative taxes). By these ways,
inflationary pressures can be suppressed and real incomes can be conserved for a
while at least.
The second round effects: demand, supply and inflation

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The confidence of business and consumer can easily be vanished by higher oil
prices because of both the immediate harming real incomes and the uncertainty
generating of future real income (how long do oil prices stay at the higher level or,
worse, will oil prices go up even further?). In this situation, economic activities are
weak for a while or even slow down further; these are called second round effects.
Besides, in theory, a lower level of demand should be sufficient to prevent any
initial raising inflation. But there are two additional worries as the follows:
 If a country’s capital stock was installed on the foundation that the oil
prices would average, for instance, USD80 per barrel in given year but oil
prices got double that year, at least some of the capital stock would be loss
and even be scrapped. By another way, when demand in an economy was
down because of higher oil price, this affected directly supply potential
economy and led to the uncertainties over the amount of spare capacity.
 What happens if nominal wages are increased when rising price level
simply has been pressing down real wages? HSBC Bank gives an argument
that at the moment, this seems that the emerging countries are suffering
from risky more than the developed world. But in reality, there are a plenty
of Western policymakers who are now increasing nervous. Obviously,
interest rate is considered to rise by three members of the Bank of
England’s Monetary Policy Committee (MPC). That is reflecting the
worries about wage growth and rising inflationary expectations.
In history, there were lots of areas of great uncertainty. Following the big event
in 1991 (Iraq invasion of Kuwait), the Bank of Japan prioritized to protect macro
economy from the near-term inflation threat associated with the higher oil prices and
ignore the affect of deflationary forces that made against an appearance of the whole
Japanese economy. In fact, with high interesting rate, the inflation came down.
Although the policy worked but the consequence as we actually known, the longer-
term costs were enormous including stagnation, economic underperformance and
deflation.
Experienced from history, in 2005, the interest rate was cut by the Bank of
England’s decision in the light of a low inflation and a beginning steady increase of

21
oil prices. Over the medium term, the interest rates in the Western world are published
nearly at zero with the confidence of controlling inflation ability. But later on, this
confidence was less after the oil price reached a spike in middle of 2008. Finally, the
reason that fears of inflation are back, the interest rate has been considered to be up.
2.2.2 The scenario of oil price and inflation in Vietnam
As we have concerned before, by qualitative method, the overall picture of the
macro economy will be drawn with some variables including consumer price index,
industrial production, oil price, money supply as the following figure 2.4.
Figure 2.4: Illustration of oil price and macroeconomic variables in level
60
80
100
120
140
160
180
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
01 02 03 04 05 06 07 08 09 10
CPI_SA IP_SA
VOP M2
Note: CPI_SA is seasonal adjustment in regard to consumer price index; IP_SA is
seasonal adjustment in regard to industrial production; VOP is world crude oil price
(transformed to Vietnamese oil price); M2 is money supply
Source: by author
It is clear that crude oil price (VOP) was in uptrend year by year with high
variation from 2001 to 2010. VOP was increasing gradually during the period
2001M1-2007M6. It reached 1.1 million VND/barrel in 2007M7. Then it temporarily

22
downed a little bit before started to be rising up incredibly. It’s up to peak at 2.2
million VND/barrel in the middle of 2008 (up over 100% after 1 year). After that it
had fallen off freely, turned back under 1 mil VND/barrel at the end of 2008.
Moving along with oil price VOP, seasonal adjustment in regard to consumer
price index (CPI_SA) was also increasing gradually year by year (the based year 2005
with index value of 100). After approached the value of 125 at the end of 2007, it’s
raising very sharply, reached peak 150 at the end of 2008 (up over 20% after 1 year).
Parallel, the moving of money supply (M2) was a little bit similar to CPI_SA
graph. But it was different during the period 2007-2008 (none sharply increasing).
While the moving of the industrial output (IP_SA) is nearly linearity with the slope
very small. It seemly there is exists that the constraint or gripper holds back the
uptrend of the output (quite flat). From 2007M12 to 2008M12, the growth rate of
IP_SA just got 13% with high deviation.
Are there special relationships among VOP, IP_SA, CPI_SA?! Whether can the
increase of VOP be factor to explain the increase of CPI_SA after a few months?! Or
could the increase of VOP impact on the moving of IP_SA badly way? We will
explore the Granger causal relationships among them by the quantitative method in
section 2.6 and chapter 3.
2.3 Review price level and inflation theories
Definition
In economics, “inflation is a rise in the general level of prices of goods and
services in an economy over a period of time. A chief measure of price inflation is the
inflation rate, the annualized percentage change in a general price index (normally the
Consumer Price Index) over time”1
. So the proxy of measuring price level is
calculation CPI from the basket of goods and services.
And many factors can contribution of changing in price level due to changing
CPI that we can focus as following figure:
1
It’s available at : http://en.wikipedia.org/wiki/Inflation

23
Figure 2.5: Factor contributions of price level
Role of inflation in whole economy
Inflation affects multiply both positive and negative side on the economy. In
this research, the negative effect of inflation is only referred to. One of the negative
impacts of inflation is that the real value of money and other related items reduce over
time. Unpredicted future inflation could harm savings and investment situation. In
details, it triggers a decrease of productive capital investment as well as an increase of
savings in non-producing assets (e.g. selling stocks and buying gold). Overall
economic productivity rates thus can be reduced.
Category type of inflations
According to Keynesian view, there are three major types of inflation, as part
of what Robert J. Gordon (1990) called “triangle model”:
Price level
Price of Tradable
World Prices
(oil price,
rice price
and price of
other
imported
inputs)
Price of Non-tradable
Exchange rate Aggregate Demand Aggregate Supply
Money and credit
Interesting rate
Income
Wealth
Government
spending and taxes
Import and
domestic input cost
Supply side
mark-up
Exchange rate

24
The most important one which is often mentioned in this research is cost-push
inflation. It is also call “supply shock inflation”, is caused by a drop in aggregate
supply (potential output). Cost-push inflation is an inflation that results from an initial
increase in costs. In general, natural disasters or the increase of input prices lead to
rising costs. The increased costs come from an increase of wage rate and raw
materials price (e.g. oil).
Figure 2.6: Cost-push inflation in the AS-AD model
Source:
http://www.bized.co.uk/virtual/bank/economics/mpol/inflation/causes/theories2.htm
Demand-pull inflation happens when the level of aggregate demand grows
faster than the underlying level of supply. It is caused usually by increasing private
and government spending, etc. Demand-pull inflation helps the economic growth fast
because the great demand and favorable conditions of market would encourage
expending production and investment.
Aggregate demand is made up of all spending in the economy as the following
formula:
AD = C + I + G + (X-M)

25
Where:
C stands for consumer expenditure.
I stand for investment.
G stands for the government expenditure.
X and M respectively stand for exports and imports.
Figure 2.7: Demand-pull inflation in the AS-AD model
Source:
http://www.bized.co.uk/virtual/bank/economics/mpol/inflation/causes/theories1.htm
Thirdly, the last type is called the inflation expectation. It is resulted from
adaptive expectations and has a close relationship in term of “price/wage spiral”. It
reflects a phenomenon that workers try to request a raise in an effort to keep their
annual income higher the rate of inflation, which makes businesses tend to pass the
increase in labor cost on their consumer with higher ware prices. Thus, it turns around
as a “vicious circle’.
2.4 The transmission mechanism of oil price shocks
According to Schneider (2004), oil price shocks affect the economy through
different channels: the supply side (higher production costs, reallocation of resources),
the demand side (income effects, uncertainties) and the terms of trade.
On the demand side, the general prices level is increased by oil price shock,
which directly absorbed into the real disposable incomes. As a result, the demand

26
decreases. Moreover, oil prices impact more a round when inflexible nominal wage;
wage index and price contribute partly to inflation.
On the supply side, the indirect effect of oil shocks through the substantial
increases in transportation and telecommunications, garments and household goods
and equipment, prices of housing and construction materials.
On the term of trade, economy is affected by the changes of the international
environment through oil price shocks. Jumped import prices lead to worsen the terms
of trade and welfare losses falling as well. Thus, the monetary policy is important to
economy stability.
Furthermore, oil imported countries are particular examples. Oil exported
nations get profits due to higher export revenues but diminishes from global demand
reducing.
By the simple way to explain the transition mechanism, rise in oil prices pass
through 2 round effects on the domestic economy (Kiptui, 2009). As shown in figure
2.8 below, the first round in short term effects of an oil price shock is transferred
directly to wages and producer prices through the pricing structure of the economy.
The second round in the longer term effects results in slowing down of economic
activity with a possible downward impact on the inflationary pressures.
Figure 2.8: Two round effects of oil price increases
Oil prices 
Inflation 
Wage-price
spiral 
Policy response:
tightening monetary
policy?!
Consumers’
disposable income 
Profits 
Economic
growth 
Inflation 
Uncertainty: timing,
magnitude and
exchange rate effects
Policy response:
loosening monetary
policy?!
1 st
round:
Short term effects
2 nd
round:
Long term effects

27
Source: Adopted from the Royal Bank of Scotland Group Economics (2004)
Other more complex mechanisms, according to Brown and Yücel (2002), oil-
price changes affect the performances of macroeconomic variables through the
following six transmission channels as following:
 Supply-side shock effect: a change of marginal product cost rooted from oil
price shock leading to affect output directly;
 Wealth transfer effect: referring to the dissimilar marginal consumption rate of
average trade surplus and petrodollar;
 Inflation effect: focusing the relationship between oil price and domestic
inflation;
 Real balance effect: analyzing the alternation of monetary policy and money
demand;
 Sector adjustment effect: measuring the adjustment in industrial structure cost.
In fact, it could help to clarify the asymmetric influence of oil price shocks; and
 Unexpected effect: investigating the fluctuation of oil price and its results in the
uncertainty.
Most of the industrialized nations have proved the above transmission
channels.
Figure 2.9: Mix transmission channels of oil price shocks

28
CPI 
Monetary Policy:
Controlling
Inflation
Cost of living&
producing 
Real balance
of currency 
Md 
Interesting 
Interesting  Investment 
Output Long term)
(Capacity Utilization 
7
9
Oil prices 
Output  Short term)

Unemployment 
Income 
Inflation  PPI 
Output Long term)
Profit 
Supply shock
effect
Price shock
1
2
5
Investment

Md 
Interesting 
3
4
6
8
Note: Arrow indicates incomplete transfer (insignificant relationship)
Source: Adapted from Tang et al., (2010)
It cannot deny that crude oil plays an important role to industrial production as
main raw materials. Its price fluctuation effects directly output. Arrow (1) in Figure
2.9 shows the reduction of production caused by the oil price shocks, which make an
increase in the marginal cost of almost industries. It means the effect of supply side
shock. It can recover in term of capacity when outputs reduce due to cutting down the
capacity utilization.
Micro
Foundation
For
Price/Monetary
Transmission
Mechanism
4

29
Nevertheless, the oil price shocks affect to the output in the long run through
Monetary Transmission Mechanism/Price (referring arrow (3)) because cost shocks of
upper stream industries would be transferred from sectors and producers to end-users.
For regarding developed industrial sectors, shock of inflation could move from upper-
stream to down-stream2
. Consequently, the profit of producer would be affected and
contemporarily fall the real balance of consumers because both of them bear a part of
overall cost increase.
As the real output and consumption reduce, this transmission finishes. Almost
developed nations reflex this status. However, there is a little different in some
countries. For example China, limited domestic demand and hard price competition of
export field forced to control price and producer surplus (Arrow (4)).
The down-stream producers decrease their profit to compensate the price rising
as their capital limitation. This tends to reduce their investment. The production
expansion depends on the investment. For example, the potential output capacity
cannot retrieve in a short run even as cost shock passes, the investment decrease
would drag on long term output decrease (Arrow (5)).
The net influence of oil price shock on interest rate is not clear because a
reduction in investment could diminish money demand in the market while a decrease
in real balance could expand it. This is proved in the Arrow (8) and Arrow (9). So, the
monetary policy is no need to apply in this situation. Yet, in the fact that monetary
authorities still set up the policy targets aiming at control inflation if cost shocks
included oil price increase doubt to cause inflation. It is really terrible for long term
output to apply a tightening monetary policy because the interest rate will be
increased and the investment will be decreased. (Arrow (7)).
2
“The downstream oil sector is a term commonly used to refer to the refining of crude oil, and the selling and
distribution of natural gas and products derived from crude oil. Such products include liquified petroleum gas
(LPG), gasoline or petrol, jet fuel, diesel oil, other fuel oils, asphalt and petroleum coke.
The upstream oil sector is a term commonly used to refer to the searching for and the recovery and production
of crude oil and natural gas. The upstream oil sector is also known as the exploration and production (E&P)
sector” (Wikipedia, 2011; Available from:
http://en.wikipedia.org/wiki/Downstream_%28petroleum_industry%29)

30
2.5 Approaches to estimate oil impact on macro economy variables
There are lots of models, among them we concern on three type popular models
that economists have been used to estimate as following:
1. Oil price standard in Phillips curve- Mark A. Hooker (1999):
Hooker (1999) used Phillips curve framework to estimate the effects of oil
price increasing on U.S. inflation. Before 1980, oil shocks played considerably to core
inflation. On the contrary, the research revealed that the change of oil price effected
inflation via the price index rate but no through core measurement since 1980.
Michael Leblanc (2004) estimates the effect of oil price changes on inflation for the
U.S.A, the U.K, France, Germany, and Japan using an augmented Phillips curve
framework. The statistical estimates suggest current oil price increases are likely to
have a modest effect on inflation in the U.S, Japan, and Europe. Applying the same
methodology, Moses Kiptui (2009) proved that the sharp increase in world oil price in
2002-2008 was associated with high inflation in Kenya.
Moses Kiptui (2009) estimates a generalized Phillips curve as follows:
   












 









m
i
i
m
i
i
m
i
i
m
i
i
t
t
t
i
t
t
i
t EXCH
oilp
y
y
CPI
CPI
1 0 0 0
1
1
1
1 )
( 



 (1)
Where ΔCPI is the change in the logarithm of the annual CPI index, y is real
GDP, y--
is the Hodrick-Precott filtered trend of real output , ΔOILP is the annual
change in the logarithm of the price in US dollars of a barrel of Dubai Petroleum since
most of the country’s imports come from the Persian Gulf. ΔEXCH is the change in
the logarithm of the annual average nominal exchange rate.
2. Vector auto regressive model (VAR model):
By another methodology, Burbidge and Harrison (1984), Brown and Yucel
(1999), Abeysinghe (2001) conducted vector auto regressions (VAR) and computed
impulse responses to oil prices with VAR model; or Structural Vector Autoregressive
(SVAR) models (Jimenez Rodriguez and Sanchez, 2004; Cologni and Manera, 2008).
In additional, Camen (2006) used a VAR system with monthly data for the periods
from February 1996 to April 2005 and found that: rice price and oil price are

31
important which play the important role for commodity prices and exchange rate. All
their results induced the same conclusion that there is an increasing of price level after
oil price spike.
When the variables are stationary in levels, a VAR model is employed. The
VAR model proposed by Sims (1980) can be written as follows:
Y(t)= k + A1Y(t-1)+ A2Y(t-2)+….+ ApY(t-p)+ u(t); u(t) ~ i.i.d.(0,Σ) (2)
Where Y(t) is an (n x 1) vector of variables, k is an (n x 1) vector of intercept
terms, A is an ( n x n) matrix of coefficient, p is the number of lags, u(t) is an (n x 1)
vector of error term for t= 1,2,….T. In addition, u (t) is an independently and
identically distributed (i.i.d) with zero mean; E (u (t)) =0 and an (n x n) symmetric
variance- covariance matrix Σ.
3. Vector error correction model (VECM):
If the variables are non-stationary, a vector error correction (VEC) model is
usually used because of the VAR in differences containing only information on short-
run relationships between the variables. In recent researches, Katsuya (2008), Jin
(2008) and Aliyu (2009) used VEC model (VECM) to examine the impact of oil
prices on the macroeconomic variables such as inflation, real effective exchange rate
and real GDP for Russia, Russia-Japan-China, Nigeria respectively.
The VECM developed by Johansen (1988) can be written as follows:
ΔZ (t) =k + Γ (1) ΔZ (t-1) + …..+ Γ (p-1) ΔZ (t - p +1) + Z (t-1) + u (t) (3)
Z (t) = [Y (t), X (t), W (t)…]
Where Z (t) is the vector of many variables, Δ is the different operator; Γ
denotes an (n x n) matrix of coefficient and contains information regarding the short-
run relationships among variables.  is a (n x n) coefficient matrix contained
information regarding the long run relationships. We decomposed as =αβ’, where α
and β’ are (n x r) adjustment and coin-integration matrices or long run matrix of
coefficients respectively.

32
2.6 Empirical studies about the oil price-macroeconomic relationship
The early empirical studies about the link between inflation and
macroeconomic were investigated by Hamilton (2003), one of the most famous
economists in energy field. He argued that except one time in 1960, most of the events
of post-World War II (WWII) U.S. recessions had at least partial impacts of oil-price
increases.
Following Hamilton’s paper series, there are lots of the researches on many
economic aspects. In which, the relationship between the oil-price shocks and the
whole performance of economic aggregate has been explored during the four decades
in many nations by Burbidge and Harrison(1984); Gisser and Goodwin (1986); Mork
(1989, 1994); Mork et al. (1994); Lee et al. (1995); Cologni and Manera (2008)...
In recent years, Tang et al. (2010) suggested to broadly classify most of those
studies into three categories. The first category is the large group of gathering
researches on the theoretical mechanisms and channels in which the oil-price increase
is investigated as a major factor that can retard the economic activities (Hamilton,
1983, 1996, 2000; Mork ,1989; Mory ,1993,1994; Lee, Ni and Ratti, 1995; Hooker,
1996; Lee et al., 2002; Brown and Yücel, 2002; Cunado and Perez de Gracia, 2003,
2005; Jimenez and Sanchez, 2005; Grounder and Bartleet, 2007; Katsuya, 2008; Jin,
2008; Aliyu, 2009; Du et al., 2010…). The second category focuses mainly on the
empirical investigation on the relationship between oil-price change and national
aggregate economic activity. Either symmetric or asymmetric, either linear or non-
linear, the mathematical relationship were verified most of the developed countries
during the 1970s up to now (Burbidge and Harrison, 1994; Gisser and Goodwin,
1986; Chaudhuri, 2000; Cunado and Perez de Gracia, 2003, 2005; Gounder and
Bartleet, 2007; Mohammad and Gunther, 2007; Cologni and Manera, 2008; Kiptui,
2009; Weiqi et al., 2009; Limin et al., 2010…). The remaining studies focus on
analyzing the role of macroeconomic policies to be able to cope with the impact of oil
price shocks. All the elements can weaken the negative impact of oil price fluctuations
in aggregate economic activities have also been studied and carefully analyzed over
time. And other factors can impact economy beside oil price effects have been
considered (Ferder, 1996; Bernanke et al., 1997; Hamilton and Herrera, 2001; Hooker,

33
2002; Leduc and Sill, 2004; Huang et al., 2005; Blanchard and Gali, 2007…). Indeed,
the majority of studies are concentrating to propose appropriate monetary policies for
coping with the oil supply shock. Meanwhile, the slowdown of total output and
inflation are widely considered as the two inevitable impacts of oil-price fluctuations
in the world wide context.
First category
On the empirical side, Hamilton (1983, 1996) had lots of contributions in
which most of U.S. recessions were preceded by increases in the price of oil. That
suggested oil price increases had an essential role as one of the main cause of
recessions.
Mork (1989), Lee et al. (1995) and Hamilton (1996) introduced non-linear
transformations of oil prices to examine the negative relationship between increasing
oil prices and economic downturns as well as to re-confirm the existence of Granger
causality between both variables.
Mork (1989) examined whether Hamilton’s outcomes were still accurate in the
case of the 1980s’ oil market collapse, also considered real oil price. Furthermore, that
allowed an asymmetric response of the US economic activity to oil price changes in
which the real prices of oil were separately specified increases and decreases by
different variables. In details, the impacts of oil price increases on economic activities
were different from those of decreases, and even the latter’s were not statistically
significant in most cases. Furthermore, an asymmetric relationship for the US also
found by Mory (1993). A little bit different from the confirmations of Loungani
(1986) and Hamilton (1988) about the oil-induced dislocations, Mory argued that the
macroeconomics would be recessionary whether initial triggered by price increases or
decreases.
Mork et al. (1994) observed Japan, Germany, USA, Norway and Canada. They
found that the USA was negatively impacted by both oil price increases and decreases,
while Canadan and German were less affected; the outcomes of all the rest were
impacted unclearly.

34
After a long time researching, Lee, Ni and Ratti (1995) focused on volatility,
maintaining that “an oil shock is likely to have greater impact in an environment
where oil prices have been stable than in an environment where oil price movement
has been frequent and erratic” because price changes in a volatile environment are
likely to be soon reversed. Economists used the Garch model to study the conditional
variance through real price changes. In all sample periods, they got the evidence of an
asymmetry between the positive effects and negative normalized shocks. Positive non-
normalized shocks in real oil price were strongly related to positive unemployment
and negative real growth. Meanwhile, negative oil price shock impacts were
insignificant.
Jimenez-Rodriguez and Sanchez (2005) assessed empirically the effects of oil
price shocks on the real economic activity of the main industrialized countries using
multivariate VAR analysis, combined with both linear and non-linear models. They
had the evidence of a non-linear impact of oil prices on real GDP. In details, their
results analyzed that oil price increases intervened with more impact on GDP growth
than that of oil price declines. Specially, among oil importing countries, oil price
increases had a negative impact on economic activity in all cases excluding Norway
and Japan. A negative impact of oil price shock of 1.1% on European Union countries
after eight quarters following the shock and a positive impact to the tune of 0.89 %
and 1.1 % in the case of Norway and Japan respectively were recorded. Surprisingly,
one phenomenon was exhibited: while it was expected an oil price shock which had
positive effects on the GDP growth in a net oil exporting country as England; but in
reality, the oil price increase 100% actually led to loss of British GDP growth rate
more than 1% after the first year in all specifications. The explanation was because of
an extensive literature highlighted that the unexpected result of oil price hikes has
done many facts. In which, that led to a large real exchange rate appreciation of the
pound, which was being described as the Dutch disease in the literature3
.
3
“The Dutch Disease is the standard example of the Paradox of Plenty. In the 1970s large revenues to the Dutch
state from the extraction of natural gas led to the temptation to build a welfare state that was unsustainable in the
long run. The competitive ability of the private sector was reduced and the industrial sector experienced a
setback from which it took many years to recover. In the case of oil exporting countries, this is even more likely

35
Katsuya (2008), he researched the relation between oil prices and Russian
economy from 1997Q1 to 2007Q4 used the VAR model. But in his data, the variables
were non-stationary, so a vector error correction (VEC) model was suitable for the
research. The analysis led to the finding that a 1% increase in oil prices contributed to
real GDP growth by 0.25% over the next 12 quarters, whereas that to inflation by
0.36% over the corresponding periods.
Jin (2008), in a recent research into the impact of oil price shocks and exchange
rate volatility on economic growth, he showed that the oil price increases caused
negative effect on economic growth in Japan and China. On the other hand, an
appreciation of the real exchange rate led to a positive GDP growth in Russia.
Aliyu (2009) showed that there was a unidirectional relationship in which the
oil price shock Granger cause real GDP of the Nigerian economy. In additions, the oil
price shock and the appreciation of real exchange rate had both positive impacts on
real economic growth through a long-run vector error correction model applied.
Moreover, based on the Hamilton’s (1983) linear specification, Jin (2008) and Aliyu
(2009) were also confirmed the existence of a symmetric oil-real GDP relationship.
By applying VAR and Structure VAR, Du et al (2010) found out the break
point of relationship between the world oil price and China’s macro-economy. Before
the break date (2002:M1), China had policy for the oil price regulation, so that the
correlation between the world oil price and domestic oil price of China was not strong
enough. It caused the impact of the world oil price on China’s macro-economy was
not significant. After the break date, due to the oil price reforms, the relationship
between the world oil price and China’s macro-economy became much more
significant. Furthermore, Granger causality tests showed that China’s macro-economy
could not affect the world oil price while China’s GDP and CPI were both positively
correlated with the world oil price. And the impulse-response functions of the linear
impact model showed the largest impact reached in the second month and disappeared
completely after about 12 months. Unlike most of the developed countries
investigated in the existing literature, a 100% increase of the world oil price
because abundant petroleum revenues change the calculations of even the prudent rulers, thus making learning
more difficult, not only between countries but also within them”.

36
cumulatively increased GDP and CPI of China by about 9% and 2%, respectively. The
results of non-linear models also informed there was an asymmetric impact of the
world oil price on China’s GDP.
Second category
By VAR model, Burbidge and Harrison (1984) found that consumer price
index (CPI) and oil price have positive relationship in Germany and Japan, and larger
effect in the UK.
Chaudhuri (2000) concluded that although oil does not exist in products but in
does influence goods price. Oil price fluctuation can affect the necessary goods price.
Cunado and Perez de Gracia (2003) researched the effect of oil prices on
production and inflation of European countries. VAR model was used with quarterly
data for the duration from 1960 to 1999, and the result was that oil price had a
constant impact on inflation and had inverse effects on production growth rate in the
short term.
With regarding to Cunado and Perez de Gracia (2005), both economic activity
and price indexes were significantly affected by oil prices in the short run, especially
these impacts were more significant when oil price shocks were defined in local
currencies in all analyzed countries. Moreover, they found evidence of asymmetries in
the oil prices–macro economy relationship.
Gounder and Bartleet (2007) had the proof in which the higher inflation and the
higher unemployment resulting from energy price shock or energy crisis on the
demand-side. In fact, at the same time, the ‘oil crises’ of the 1970s and early 1980s led
to rise both inflation and unemployment as the ‘stagflation’ phenomenon. The non-
linear transformations of oil prices were also applied to re-establish the negative
relationship between increases in oil prices and economic downturns, as well as to
expose Granger causality between both variables.
Using VAR model in the case of Iran, Mohammad and Gunther (2007)
conducted the result that if the oil prices changed either negatively or positively, the
inflation would be seriously increased. Moreover, there was a close relationship
between industrial growth and positive oil price changes.

37
Kiptui (2009) estimated a generalized Phillips curve. Oil prices had positive
significant effects on inflation in Kenya, that 10 per cent increasing in oil prices
conducted 0.5 per cent inflation up in the short- run and 1 per cent up in the long-run.
In the context of China, according to Wiki, Lebo, and Zhongziang (2009),
increasing oil price affected inflation and interest rate positively while Chinese
investment and output were seriously affected by higher oil prices. In addition, by
Limin, Yanan, and Chu (2010), that there were close relationships among the world
oil price, economic growth and inflation although the impact was non-linear.
Others
Beside the evidence that oil market disruptions affected the U.S. economy
through the several shocks and uncertainty channels over the 1970 to 1990 sample
period, the Research of Ferder (1996) induced some important findings as followings:
The tightening monetary policy was applied to response to oil price increases,
this evidence could explain a part of the oil price-output correlation. In particular, the
non borrowed reserve growth was fallen and the Federal funds rate was raised
following oil price increases. These two tools of monetary policy all affected the
output growth. However, the monetary variables had a weaker and less significant
impact than the oil price variables. It suggested the monetary channel provided a
partial explanation for reason why oil price increases adversely affected the economy.
The Federal funds rate was raised by the Federal Reserve in response to oil
price increases as well as it hoped to be low as much as in response to oil price
decreases. Moreover, the inclusion of monetary variables into output equations could
not effect on the coefficients of oil price increases and decreases to converge in value.
Therefore, the monetary policy channel was hard to explain the asymmetry problem as
a puzzle. In contrast, when oil price volatility was introduced into the output equations
oil price volatility rose both positively and negatively and the coefficients of oil price
increases and decreases that became much closer in value. Thus a partial solution to
answer the asymmetry puzzle was revealed by the spectral shocks and uncertainty
channels.

38
By Bernanke, Gertler and Watson (1997), the role of monetary policy was
considered as the central factor rather than a factor contributing to discontinuity in the
relationship between oil price and GDP. Indeed, a positive increase in oil price was
followed by a rise in the federal fund rate and the reduction in U.S. output was
accounted for about two-thirds to three-quarters in the reaction of this kind of
monetary policy tightening subsequent to an oil shock. Unfortunately, they found that
the role of monetary policy in the 1970s was more stable than the recent periods.
Hamilton and Herrera (2001) re-examined Bernanke et al. (1997) and arrived at
some contrary conclusions. There were the relative contributions of monetary policy
in which oil price shocks related to the following recessions in 1973, 1979-80, and
1990. Through the impulse response functions, they argued that the potential of
monetary policy fighting against the contraction cause of consequences of an oil price
shock was not as great as proposed by the analysis of Bernanke, Gertler, and Watson.
In other words, they said that oil shocks caused a bigger effect on the economy rather
than as Bernanke et al suggested in the VAR.
By Hooker (2002), the changing weight of oil prices as an explanatory variable
in a traditional Phillips curve specification for the U.S. economy was analyzed
empirically. His results showed that the pass-through from oil prices to price levels
has become negligible since the early eighties, but the evidence to certify a significant
role of the decline in energy intensity, the deregulation of energy industries, or
changes in monetary policy as the factor behind this lower pass-through could not be
found. In addition, he opined that the energy price shocks might be a trigger for an
external inflation spike as the immediate result had been recorded in the literature.
When the inflation was not caused by an increase in domestic money supply, just was
the results from oil price movements, it could drive the negative consequences for real
balances.
According to Cunado and Gracia (2005), the asymmetric relation was
convinced European countries of a truth. In addition, asymmetric relation of oil
change impact couldn’t be explained by supply theory. Therefore, in order to explore
that relation, other theories such as monetary policies, asymmetry in petroleum
product prices, and adjustment costs were employed. Through which, monetary policy

39
theory could explain the asymmetric response of GDP to oil changes. Rather, when
nominal income would fall down by sudden inflation in case there was an oil price
increase, monetary policy hardly couldn’t remain the nominal GDP as the same
before. Furthermore, from the oil price changes–inflation rate relationship in the cases
of Thailand, Malaysia, South Korea, and Japan and from the oil price changes–
economic growth rate relationship only in the case of South Korea, the evidences of
these asymmetric relations were found.
The same matter on a group of industrialized nations also was researched and
was compared the results with those of the 1970s (Blanchard and Gali, 2007). There
was an argued that due to the smaller energy intensity, the more flexible labor market,
and the better changes in monetary policies, the effects of oil price shocks on the
economies nowadays is weaker.
The following table summarized the above-reviewed empirical studies in
sequence of time as below:

40
Table 2.1: Summary results of eempirical studies
Authors Data Models-
Methodology
Main Results
Hamilton
(1983)
USA;
Quarterly
1949-1972
VAR
(Y, OP, MP, IP, UN,
W, INF)
Oil price upswing caused slower
productivity after 3-4 quarters later by
slower output growth with a recovery
beginning after 6-7 quarters.
Burbidge and
Harrison (1984)
US, Japan,
Germany, UK,
Canada;
Monthly 1961-
1982
VAR
(Y, OP, MP, IP, R,
W, INF)
Consumer price index (CPI) and oil price
had positive relationship in Germany and
Japan, and larger effect in the UK
Gisser and
Goodwin
(1986)
USA;
Quarterly
1961-1982
OLS
(Y, OP, MP, FP,
UN, I, INF)
They found the impact of oil price shocks is
little or no support for the form of cost-push
inflation.
Mork (1989) USA;
Quarterly
1949-1988
VAR
(Y, OP, MP, IP, UN,
W, INF)
They presented an even stronger negative
correlation between oil price increase and
output growth than Hamilton’s results.
Mory (1993) USA; Annual
1952-1990
OLS
(Y, OP, MP, GOV)
Some evidences of an asymmetric effect of
oil price spikes on the US economy were
presented.
Lee, Ni and
Ratti, (1995)
USA;
Quarterly
1949-1992
VAR
(Y, OPV, MP, IP,
UN, W, INF)
The negative sum suggested that there was a
decline in the level of GNP over 24 horizons
following an oil shock. An asymmetry in
effects was found
Darrat et
al.,(1996)
USA;
Quarterly
1960-1993
VAR
(Y, OP, MP, FP, W,
R)
Multivariate VAR-causality model
suggested that oil prices were not a major
cause of U.S. business cycles.
Ferderer (1996) USA; Monthly
1970-1990
VAR
(Y, OPV, OPV MP)
The Federal funds rate and oil price
volatility explained 27% and 22% of the
forecast error variance for industrial
production at the 24-month horizon.

41
Hooker (1996a) USA;
Quarterly
1947-1974
VAR
(Y, OP, MP, IP,
INF)
10% increase in oil price caused GDP to
slow down by 0.6% in the third and fourth
quarter after the shock.
Hooker (1996b) USA;
Quarterly
1974-1994
VAR
(Y, OP, MP, IP,
INF)
They could not foresee the unemployment
rate or GDP growth by oil price levels.
Hamilton
(1996)
USA;
Quarterly
1948-1994
OLS
(Y, OP, MP, INF,
IP)
The relation between GDP increase and net
oil price increase was statistically
meaningful.
Hooker (1999) USA;
Quarterly
1979-1998
ECM
(Y, TB, UN, OP, IP)
Suggested that different monetary policy
(particularly prior to the oil shocks) could
have substantial impact on inflation.
Hamilton
(2000)
Quarterly
1949:1999
OLS with lags
variables
(Y, Yt-1, Yt-2, Yt-3 ,Yt-
4; OP t-1, OPt-2, OPt-3,
OPt-4; OP+
t-1, OP+
t-2,
OP+
t-3, OP+
t-4)
Price increases caused more impact than the
decreases did. From 1949 to 1980 a 10%
increase in oil prices resulted four quarters
later in a level of GDP growth that was 1.4%
lower.
Nagi Elthony et
al., (2000)
Kuwait;
Quarterly data
1984-1998
VAR, VECM
(OILR, OPLP,
EXDEV, EXCON,
CPI, M2,
IMPORTS)
The empirical evidence indicated that oil
price shocks and hence oil revenues had a
notable impact on government expenditure,
both development and current.
Lee, Ni and
Ratti., (2002)
Japan;
Monthly
1960-1996
VAR
(Y, OPV, MP, INF,
R, CP, GOV)
In response to a shock in oil price, output
decline occurred after a 10-month delay and
the decline was short-lived.
Cunado and
Perez
de Gracia
(2003)
15 European
Countries;
Quarterly
1960-1999
VAR
(Y, OP, INF)
The result was that oil price had constant
impact on inflation in short term but had
inverse effects on production growth rate.

42
Cunado and
Perez
de Gracia
(2005)
6 Asian
Countries;
Quarterly
1975Q1–
2002Q2
Bivariate VARs with
lags variables (Y,IF,
constructed proxies
of oil shocks: OP,
OP+
, OP-
, SOPI,
NOPI4, NOPI12)
The impact was higher when oil prices were
measured in local currency, which could be
due to the role of exchange rates or national
price variations on macroeconomic
variables.
Jimenez-
Rodriguez and
Sanchez(2005)
9 OECD
Countries;
Quarterly
1972-2001
VAR
(Y, OPV, INF, R, W,
EX)
The conclusion was drawn that price
increases had greater effect on GDP growth
than the decreases...
Blanchard and
Gali (2007)
6 developed
countries;
Quarterly
1960:1-2005:4
Multivariate VARs,
Rolling bivariate
VARs; 6-variable
VAR: OP, GDP-
DEF, INF,W, GDP,
EM
They discovered that the weak reaction of
the economies in recent period was due to
smaller energy intensity, a more flexible
labor market, and better changes in
monetary policies.
Gounder and
Bartleet (2007)
New Zealand;
Quarterly
1989-2006
VAR
(Y, OPV, W, EX
INF)
They found that the largest negative impact
of NOPI innovations to GDP occurred in the
third quarter and remains negative over 2
years in new Zealand. They reported a
cumulative effect of 0.7 percent of GDP
growth for New Zealand.
Katsuya (2008) Russia;
Quarterly
1997Q1 -
2007Q4
VECM
(UOP, GDP, IF)
The result showed that real GDP growth by
0, 25 percent was caused by 1 percent
increase in oil prices, whereas that to
inflation by 0, 36 percent over the next
twelve quarters.
Jin (2008) Russia, Japan
and China
Quarterly;
1999-2007
VECM
(Y, EX, OP)
Specifically, a 10% permanent increase in
international oil prices was associated with a
5.16% growth in Russian GDP and a 1.07%
decrease in Japanese GDP.
Aliyu (2009) Nigeria;
Quarterly
VECM
(Y, EX, OP)
The results tally were very well with the
coefficient of oil price shock of 0.77

43
1986-2007 reported using a linear oil price model for
the Nigerian economy.
Du et al.,
(2010)
China;
Monthly
1995:1-
2008:12
VAR, Structure
VAR
(OP, GDP, CPI,M1,
R)
The impulse-response functions of the linear
impact model showed that China’s GDP and
CPI were both positively correlated with the
world oil price.
Source: adapted from Gounder and Bartleet (2007), Aliyu (2009) and author
improved.
Notes: VAR is Vector Auto regression, VECM is Vector Error Correction Model, Y is
economic growth, MP is Monetary Policy, OP is oil prices, UOP is converted from US dollars per
barrel to the Russian rubles per barrel, IP is import prices, UN is unemployment, W is wages, INF is
inflation, R is interest rate, I is investment, OPV is oil price volatility, CP is commodity prices, GDP
is Gross domestic product, GOV is Government expenditures, EX is exchange rate, TB is treasury
Bill rate, OILP is Oil Price of Kuwaiti Blend Crude, OILR is Oil Revenue, EXDEV is Government
Development Expenditure, EXCON is Government Current Expenditure, CPI is Consumer Price
Index, M1 is Money Supply, M2 is Money Demand (M2 Definition), IMPORTS is Value of Imports
of Goods & Services; Proxies of oil prices: OP+
(Oil price increase), OP-
(Oil price decrease), SOPI
(Scaled oil price increases), NOPI4 (Net oil price increases from the past 4 quarters), NOPI12 (Net oil
price increases from the past 12 quarters)
Seeing the table above, it’s obvious that VAR approach is also inspired by the
existence of a large empirical literature using VARs. Why? The most advantage of
VAR models is that they can simultaneously estimates the interrelationship between
more than one endogenous variable. So in this study I employ vector auto regression
(VAR) models to examine oil shocks transmission mechanism, which focuses
primarily on reduced-form relationships between oil price and macroeconomic using a
small number of variables. We will concern more in section 2 of chapter 3.

44
2.7 Conceptual Framework
In this section, we will test the validity of transmission mechanisms of oil price
shock in Vietnam, by checking the statistical relationships between key variables on
transmission chains shown in Fig. 2.9 step by step. We start checking the relationship
between oil price and domestic consumer price index CPI. Based on Fig. 2.9, this
relationship is corresponding to the arrows 3 and 6. Then, we will test the direct
impact of oil price change to economic output with proxy IP (Industrial Production
Index), i.e. the short-term impact, indicated by arrow 1. For more concise, let’s
modify and improve the Fig.2.9 become a simple framework as below:
Figure 2.10: Conceptual framework
Sources: Author’s calculation
Short tem effects:
Hypothesis testing:
 Granger causality
tests (exist short term
relation ships?!)
 Asymmetric tests
CPI
GDP/IP
Econometric
technique of
VAR models
OIL
PRICE
Tải bản FULL (93 trang): https://bit.ly/3zCKkd4
Dự phòng: fb.com/TaiHo123doc.net

45
Chapter 3: Model Specification and Data
After here, the analytical framework and model specifications are introduced. Then,
the steps of estimation and data sources are mentioned.
3.1 Analytical Framework
Estimation strategy
First, stationary is check in each variable. Second, the short-run dynamic
behavior between oil prices and macroeconomic variables is studies and Granger
causality. Third, Impulse Response Functions, Variance Decompositions are to be
used. Finally, asymmetries in the proxies of oil price changes and macroeconomic
relationships are tested.
Granger causality tests – short run relationships
Impulse Response Functions, Variance Decompositions tests
Conclusion
Unit root testing (ADL and PP tests)
Asymmetric testing procedure
Tải bản FULL (93 trang): https://bit.ly/3zCKkd4
Dự phòng: fb.com/TaiHo123doc.net

46
3.2 Model Specifications
The VAR system is based on empirical regularities embedded in the data. As
we have concerned before, one of the most advantage of VAR models is that they can
simultaneously estimates the interrelationship between more than one endogenous
variable. So the VAR technique is suitable for this study because of its ability to
expose the dynamic structure of the model as well as it helps us to avoid imposing
excessive identifying restrictions associated with many different economic theories.
There are some kinds of VAR models. One of the typical VAR models can be
expressed as a system of reduced form equations in which each of the endogenous
variables is regressed on its own lagged values and the lagged values of all other
variables. A reduced-form VAR model can be expressed in matrix form as,
yt A (L)*yt-1 B*xt µt (3.9)
Where yt is the vector of endogenous variables, is the vector of constants, xt is the
vector of exogenous variables and μt is the vector of serially uncorrelated disturbances
that have zero mean and a time invariant covariance matrix (generalization of a white
noise process). A and B are coefficient matrices, L is the lag-operator.
In this study, the vector of endogenous variables yt consisted of three variables:
percentage changing of consumer price index (PC_CPI_SA), percentage changing of
industrial production (PC_IP_SA) and percentage changing of oil price (PC_VOP)
yt = [PC_CPI_SA, PC_IP_SA, PC_VOP]
The vector of exogenous variables xt for model contained percentage changing of
money supply (PC_M2) in other to examine the effect of monetary policy; in light of
the global crisis, dummy variable (DBP) was used for break point of 2 month of peak
oil price in middle of 2008; trend was used for time varying. When these variables
were treated as exogenous variables, their contemporaneous impact on the
endogenous variables could be accepted, but not used for a feedback.
xt = (PC_M2, DBP, TREND, PC_M2*TREND, DBP*TREND)
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