1. 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.

2. Outline Introduction Objectives Data Test Results and Interpretations
Oil price fluctuations and the economy
Causality between oil prices and macroeconomic variables
Objectives
Data
Test Results and Interpretations
Impulse response
Variance decomposition
Conclusions

3. 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)

4. Summary of Literature Review
This table summarizes several key research results on the relationship between oil-price fluctuations and various macroeconomic indicators

5. 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)

6. Summary of Granger Causality Studies
Note: → denotes the direction of Granger-Causality while ↔denotes bi-directional Granger-Causality

7. 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

8. Vector Autoregression Model (VAR)
Investigate the relationship between oil price and the macroeconomic variables
When they are not cointegrated
Equation:
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

9. Data Variables Scope Sources Type of Oil
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

10. 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

11. 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

12. 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

13. 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

14. 33 (shaded) out of 49 pairs of variables proceeded with the cointegration test

15. Cointegration Test Engle-Granger cointegration test
The critical value calculated according to the equation is 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

16. Cointegration Test GDP and Oil Price CPI and Oil Price
Australia, India, Japan, South Korea and Thailand
No cointegration
CPI and Oil Price
India, Indonesia, Laos, Taiwan and Thailand
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

17. Observations of cointegration
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

18. Shaded boxes indicate cointegration
“-“ represents no cointegration between the variables (not integrated of the same order)

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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)

25. 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

26. 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

27. 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.

28. Granger-Causality 
According to the results, the GC generally runs from oil prices to other variables. Causality runs from oil prices to GDP in China, Myanmar and India. All other countries see bi-directional causality between the two variables. For the cointegrated series, only Laos showed no causal relationship between oil price and GDP, but this can be attributed to insufficient data. For the non-cointegrated series, Japan and Thailand did not show any causality between the two variables
In bold, Granger-Causality runs from oil price to the considered variable at 10% significance level.

29. Conclusions
Countries are classified according to their macroeconomic characteristics to form three broad categories
Asian countries that export oil and are in a position to gain an advantage from a positive oil price shock
Small open economies for which trade plays a big role in their economic activity
Large, rapidly growing economies

30. Conclusions Asian Oil-exporting economies Small open economies
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
Small open economies
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
China is highly dependent on coal, whereas India is dependent on combustible renewable sources and coal for its energy needs

31. Thank you for your attention!