Transcript Oil Price Fluctuations and Macroeconomic Performances in

Oil Price Fluctuations and Macroeconomic
Performances in Asian and Oceanic Economies
Youngho Chang
Division of Economics
Nanyang Technological University
30th USAEE/IAEE North American Conference
9 – 12 October 2011
Capital Hilton, Washington, D.C.
1
Outline
• Introduction
– Oil price fluctuations and the economy
– Causality between oil prices and macroeconomic variables
• Objectives
• Data
• Test Results and Interpretations
– Impulse response
– Variance decomposition
• Conclusions
2
Oil Price Fluctuations and the Economy
• Macroeconomic implications of oil price shocks identified since the 1970s
• Research largely indicated a negative relationship, with oil price increases
preceding almost all recessions in the United States after World War II
– Hamilton (1983, 1996 and 2004)
– Gisser and Goodwin (1986)
– Burbridge and Harrison (1984)
• Since then, other country studies have been conducted that further
support this stand;
– New Zealand (Gounder and Barleet, 2007)
– Greece (Papapetrou, 2001)
• However, a declining oil-price and macroeconomic relationship has also
been found
– Mork et al. (1989, 1994)
– Abeysinghe (2001)
3
Summary of Literature Review
Author
Hamilton
Gisser and Goodwin
Burbridge and Harrison
Year
Countries observed Macroeconomic Variables
1983, 1996, 2003
USA
GDP
1986
1984
5 OECD countries
Several
Conclusions
Significant negative relationship
Negative and relatively stable relationship
Substantial initial impact on macroeconomic indicators;
also a declining impact of oil price shocks
Jiménez-Rodríguez
and Sánchez
Gounder and Bartleet
Papapetrou
Hooker
Mork et al.
Abeysinghe and Wilson
2005
Several
GDP
Significant impact on macroeconomy
2007
2001
1996
1990, 1994
2000
New Zealand
Greece
USA
GDP and inflation
Direct relationship for GDP, indirect relationship with inflation
Significant negative casual relationship
Changing and unstable oil price-macroeconomic relationship
Several
Several
Chang and Wong
2003
Singapore
Blanchard and Gali
Barsky and Kilian
Kilian
Ferderer
Lardic and Mignon
Cunado and Gracia
Fuhrer
Hooker
Barksy and Kilian
LeBlanc and Chinn
Lescaroux and Mignon
Chen
Cunado and Gracia
Kumar
Loungani
Burbidge and Harrison
Darby
Hamilton
Gisser and Goodwin
Uri
Dorgul
Carruth et al
2007
2001, 2004
2009
1996
2006
2005
1995
2002
2004
2004
2008
2009
2005
2005
1986
1984
1982
1983
1986
1996
2010
1998
Several
GDP
GDP, inflation
and unemployment
GDP and inflation
USA
Declining oil price-macroeconomic relationship
Marginal impact on macroeconomic indicators
Changing impact of oil prices
Limited impact of oil price shocks
Little or no impact of oil price shocks
GDP
USA and Europe
6 Asian countries
Asymmetric relationship
Significant pass through effect to inflation
USA
Inflation
Significant impact on inflation
Moderate impact on inflation
Several
Declining impact on inflation
6 Asian countries
India
USA
5 OECD countries
Several
Short run effect on inflation
Significant impact on inflation
USA
Significant relationship
Unemployment
Long run relationship
Turkey
USA
Lagged effect on unemployment
4
Causality between Oil Prices
and Macroeconomic Variables
• Early studies have found the inverse relationship with oil price and
particularly GDP (Hamilton, 1983)
• Most studies indicated causality running from oil price to real GDP or
economic growth, especially for oil-importing countries
– Lescaroux and Mignon (2008); Du, He and Wei (2010); Cunado and
Gracia (2005)
• However, there are also studies which show no causality between the two
– Bartleet and Gounder (2007); Li, Ran and Voon (2010)
• General results of causality running from oil price to inflation has been
found
– Lescaroux and Mignon (2008); Du, He and Wei (2010); Cunado and
Garcia (2005); Jalles (2009)
• For unemployment, most countries indicated a causality running from oil
price to unemployment
– (Lescaroux and Mignon, 2008)
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Summary of Granger Causality Studies
GDP
Author
Lescaroux and Mignon
Year
2008
Du, He and Wei
2010
Hanabusa
2009
Prasad, Narayan and
Narayan
Jalles
Li, Ran and Voon
Bartleet and Gounder
2007
Author
Lescaroux and Mignon
Year
2008
Du, He and Wei
2010
Cunado and Grancia
Jalles
2005
2009
Author
Lescaroux and Mignon
Year
2008
Li, Ran and Voon
2010
2009
2010
2007
Oil Price→GDP
GDP→Oil Price
Saudi Arabia, UK, and to a less extent,
Qatar
GDP↔Oil Price
No Causality
China: Sample fom 2003-2008 shows causality
at 1% and 5% level of significance.
Japan: In mean, with a 9-month lag, and in
In mean, with a 6-month lag. In variance,
variance with a lag of 1-month.
with a lag of 1 month.
Fiji Islands: In the long run, at 5% significance
level.
France
Hong Kong
New Zealand for
Economic Growth
CPI
Oil Price→CPI
CPI→Oil Price
Oil prices have a large influence on CPI for the
United Arab Emirates, United Kingdom, Mexico
and Libya
China: Similar to the results for the causality in
the GDP section, there are no significance in the
1995-2001 period sample but there are causality
running from oil price to CPI at the 1% and 5%
level, but not the other way round.
Japan; Singapore; Thailand
France
UNEMPLOYMENT
Oil Price→Unemployment
Unemployment→Oil Price
Great influence of oil prices on the
Four oil importing countries (China,
unemployment rate in the United States,
Greece, Spain and the United States)
Luxembourg, France, Canada andVenezuela
CPI↔Oil Price
No Causality
Unemployment↔Oil
Price
No Causality
Hong Kong
Note: → denotes the direction of Granger-Causality while ↔denotes bi-directional Granger-Causality
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Objectives
• To explore the impact of oil price fluctuations on
macroeconomic variables for economies in ASEAN,
the Asia-Oceanic Region and South Asia
• To investigate the varied patterns of the impact by
different categories of economies in the region
– Oil-exporting economies
– Small-open economies
– Large countries with rapid economic growth
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Vector Autoregression Model (VAR)
• Investigate the relationship between oil price and the macroeconomic
variables
– When they are not cointegrated
• Equation:
o
o
o
o
y is an n-vector of endogenous variables
Bk is an (n × n) matrix of regression coefficients to be estimated.
The error term, ut, is assumed to be independent and identically
distributed with a zero mean and constant variance.
Selection of the appropriate lag length, p, is important. 4 is chosen
8
Data
• Variables
– GDP, CPI and unemployment rate
• Scope
– 17 countries (Asia-Pacific and ASEAN region)
• Sources
– CEIC data manager
– International Financial Statistics (IFS) CD-ROM 2010
– Specific government sources and websites
• Type of Oil
– Dubai crude “Arab Gulf Dubai” measured in FOB $US/BBL
9
Unit Root Tests for Stationarity
• Phillip-Perron (PP) unit root tests are conducted
• Null hypothesis
– Series are non-stationary
– If the p-value is less that 0.1 (10% level of significance), the
null hypothesis of non-stationarity is rejected
10
Unit Root Tests for Stationarity: GDP
• GDP Time-Series
– All series show non-stationarity except for the Philippines
and Vietnam
• Oil Price Series Corresponding to the GDP
– All except for the Philippines
*Brunei and Vietnam were not be examined due to
different orders of integration
11
Unit Root Tests for Stationarity: CPI
• CPI Time-Series
– Australia, Brunei, China, Japan, the Philippines and South
Korea
• Null hypothesis of non-stationarity is rejected
• All other countries are non-stationary
• Oil Price Series Corresponding to the CPI
– The Philippines: Null hypothesis for is rejected
– Other countries: Rejected for the first differences
– Australia, Brunei, China, Japan and South Korea
• Not studied due to different orders of integration
12
Unit Root Tests for Stationarity: Unemployment
• Unemployment Rate Series
– More varied results due to smaller sample sizes
– Brunei, Cambodia, Malaysia and Thailand
• Null hypothesis of non-stationarity is rejected
– The remaining countries (except for China and Vietnam)
• Rejected for the first differences
• Oil Price Series Corresponding to the Unemployment
Rate
– Non-stationarity is rejected only for Indonesia
– The remaining series except Cambodia
• Rejected for first differences
– Analysis omitted for 7 countries due to different order of integration
13
33 (shaded) out of 49 pairs of variables proceeded
with the cointegration test
Australia
Brunei
Cambodia
China
India
Indonesia
Japan
Laos
Malaysia
lnGDP
lnOil_GDP
I(1)
I(1)
I(2)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
lnCPI
lnOil_CPI
I(0)
I(1)
I(0)
I(1)
I(1)
I(1)
I(0)
I(1)
I(1)
I(1)
I(1)
I(1)
I(0)
I(1)
I(1)
I(1)
I(1)
I(1)
UN
lnOil_UN
I(1)
I(1)
I(0)
I(1)
I(0)
I(2)
I(2)
I(1)
-
I(1)
I(0)
I(1)
I(1)
-
I(0)
I(1)
Myanmar
New
Zealand
lnGDP
lnOil_GDP
I(1)
I(1)
I(1)
I(1)
I(0)
I(0)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(0)
I(1)
lnCPI
lnOil_CPI
I(1)
I(1)
I(1)
I(1)
I(0)
I(0)
I(1)
I(1)
I(0)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
UN
lnOil_UN
-
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(1)
I(0)
I(1)
I(2)
I(1)
Philippines Singapore
South
Korea
Taiwan
Thailand
Vietnam
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Cointegration Test
• Engle-Granger cointegration test
• The critical value calculated according to the equation is -1.61
by MacKinnon (2010)
• If the absolute value of the statistic is greater than |-1.61|
– Null hypothesis is rejected
– Proceed with Vector Error Correction model (VECM)
• If the absolute value of the statistic is less than |-1.61|
– No cointegration between the two variables
– Variance auto-regression (VAR) model adopted
15
Cointegration Test
• GDP and Oil Price
– Australia, India, Japan, South Korea and Thailand
• No cointegration
• CPI and Oil Price
– India, Indonesia, Laos, Taiwan and Thailand
• No cointegration
– Malaysia, Myanmar, New Zealand, Singapore and Vietnam
• Cointegration detected
• Unemployment Rate and Oil Price
– Australia, Japan, New Zealand, the Philippines, Singapore,
South Korea and Taiwan
• Cointegration
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Cointegration Test
• Observations of cointegration
– GDP and oil price series: 9 countries
– CPI and oil price series: 6 countries
– Unemployment rate and oil price series: 7
countries
• Mainly in developed Asian countries
• Australia, Japan, New Zealand, Singapore, South Korea
and Taiwan
• Developing nations studied have no cointegrating
relationship
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• Shaded boxes indicate cointegration
• “-“ represents no cointegration between the variables (not integrated of the
same order)
Australia
Brunei
Cambodia
China
India
Indonesia
Japan
Laos
Malaysia
lnGDP on
lnOil_GDP
-0.467643
-
-4.342324
-2.433306
0.198985
-2.712333
-1.277553
-3.550048
-3.117576
lnCPI on
lnOil_CPI
-
-
-2.369161
-
0.333649
-0.179834
-
-1.233173
-2.657299
UN on
lnOil_UN
-2.217284
-
-
-
-
-
-2.160321
-
-
Myanmar New Zealand Philippines
Singapore South Korea
Taiwan
Thailand
Vietnam
lnGDP on
lnOil_GDP
-3.381828
-2.701918
-
-2.014756
-1.106708
-1.728377
-1.382402
-
lnCPI on
lnOil_CPI
-1.746361
-3.012051
-
-1.819914
-
-1.171726
0.103821
-1.626163
UN on
lnOil_UN
-
-1.921504
-2.238887
-1.793251
-2.758843
-2.864638
-
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Vector Error Correction Model (VECM)
• For two cointegrated variables, the VECM describes
the data-generating process
• The Error Correction Term (ECT) shows how fast the
relationship between the two variables converges
towards its long-run equilibrium
• Impulse-Response Analysis
• Variance Decomposition
19
Impulse Response Functions
• Impact of a one standard deviation shock to the real
oil price on three variables
– GDP
– CPI
– Unemployment Rate
• Study of the 8-year impact
• Depicted through graphical means
20
Impulse Response Analysis for GDP
Varied impact of an oil price shock on GDP
• Singapore and Taiwan
– Small-open economies
– Delayed negative impact
– Consistent with findings of previous
studies
• Malaysia and Indonesia
– Net oil exporters in the past
– Long-run positive impact on GDP due
to critical nature of oil, short run
inelastic demand
– Strong support from some studies
21
Impulse Response Analysis for GDP
Varied impact of an oil price shock on GDP
• China
–
–
–
–
Large economy with strong growth
Positive GDP impact from oil shock
Most energy needs met by coal, not oil
Robust economic growth in the past
despite increases in oil prices
– Contradictory conclusions from some
studies
•
New-Zealand
– Another small open economy
– Immediate negative impact followed by
positive trend
– Positive and delayed effect from trading
partners, China and Australia
22
Impulse Response Analysis for CPI
• Malaysia, New Zealand, Singapore
Vietnam
– Instantaneous increase after oil price
shock
– But the inflationary increase is small
– Improved Central Bank credibility in
fighting inflation
– Even smaller impact for oil exporting
nations
• Cambodia
– Lagged inflationary impact
– Transmission through trading
partners such as Vietnam and
Thailand
23
Impulse Response Analysis for Unemployment
•
•
•
•
Australia, Japan, New Zealand, Singapore,
South Korea
– Lagged positive impact of an oil price
shock on the unemployment rate
– Increase in unemployment rate after
four or five years; support from past
study
– However, scale of increase is nominal
Taiwan
– No lag; immediate uptick
– Flexible labor market
Australia
– Delayed positive impact, but subsiding
effect on unemployment rate
– Commodity-linked economy; benefits
from commodity price increase
Long-lasting impact on unemployment rate
(3 years)
24
Variance Decomposition
• Impact of real oil price fluctuations on the long-run
volatility of three variables
– GDP
– CPI
– Unemployment Rate
• Study of the 8-year impact
• Depicted through graphical means
25
Variance Decomposition for GDP
• Most economies including Cambodia, China, Indonesia,
Malaysia, Myanmar, Singapore
– An oil price shock is a considerable source of GDP volatility
– Impact not uniform over time
• Increasing impact for China and Indonesia
• Decreasing impact for Cambodia and Singapore
26
Variance Decomposition for CPI and
Unemployment
•
Substantial source of disturbance to CPI
volatility over all examined countries
– Oil price shocks account for over 10%
of CPI variance with an increasing
impact over time
– Limited studies for comparison
– New Zealand and Singapore CPI
volatility through oil has been
studied previously
•
Little research has examined the
importance of an oil price shock on
unemployment rate
– Varied results across economies
– Substantial impact on New Zealand,
Philippines and Taiwan, but negligible
for Australia, Japan and Singapore.
27
Granger-Causality
GDP
CPI
Emerging and Developing Economies
Cambodia
China
Indonesia
Laos
Malaysia
Myanmar
India
Thailand
Cambodia
India
Indonesia
Laos
Malaysia
Myanmar
Thailand
Vietnam
Advanced Economies
Australia
New Zealand
Singapore
Taiwan
Japan
South Korea
New Zealand
Singapore
Taiwan
Unemployment
Rate
India
Philippines
Australia
Japan
New Zealand
Singapore
South Korea
Taiwan
In bold, Granger-Causality runs from oil price to the considered variable at 10%
significance level.
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Conclusions
• Countries are classified according to their
macroeconomic characteristics to form three broad
categories
1. Asian countries that export oil and are in a position to gain
an advantage from a positive oil price shock
2. Small open economies for which trade plays a big role in
their economic activity
3. Large, rapidly growing economies
29
Conclusions
1.
Asian Oil-exporting economies
–
–
–
–
2.
Small open economies
–
–
–
3.
Includes Malaysia and Indonesia
Increase in the oil price causes their GDP to increase
Large percentage of the volatility in GDP is contributed by oil price variance
Signifies that oil price plays a substantial role in influencing their GDP
Includes Singapore, New Zealand and Taiwan
Negatively impacted by an oil price shock in the short-run but improves in
the long-run
Indirect positive effect through major trading partners causes resurgence in
their economic activity
Large and fast growing economies
–
–
–
Includes China and India
Negligible impact of an oil price shock on GDP
Small reliance on oil as a source of energy
30
Thank you for your attention!
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