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.

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

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)

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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.

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.

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

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

Thank you for your attention!