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How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?

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  • Lan-Fen Chu
  • Michael McAleer
  • Chi-Chung Chen

    ()
    (National Chung Hsing University)

Abstract

This paper analyzes two indexes in order to capture the volatility inherent in El Niños Southern Oscillations (ENSO), develops the relationship between the strength of ENSO and greenhouse gas emissions, which increase as the economy grows, with carbon dioxide being the major greenhouse gas, and examines how these gases affect the frequency and strength of El Niño on the global economy. The empirical results show that both the ARMA(1,1)- GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility accurately, and that 1998 is a turning point, which indicates that the ENSO strength has increased since 1998. Moreover, the increasing ENSO strength is due to the increase in greenhouse gas emissions. The ENSO strengths for Sea Surface Temperature (SST) are predicted for the year 2030 to increase from 29.62% to 81.5% if global CO2 emissions increase by 40% to 110%, respectively. This indicates that we will be faced with even stronger El Niño or La Niña effects in the future if global greenhouse gas emissions continue to increase unabated

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Bibliographic Info

Article provided by Lifescience Global in its journal Journal of Reviews on Global Economics.

Volume (Year): 1 (2012)
Issue (Month): ()
Pages: 1-12

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Handle: RePEc:lif:jrgelg:v:1:y:2012:p:1-12

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Keywords: El Niños Southern Oscillations (ENSO); Greenhouse Gas Emissions; Global Economy; Southern Oscillation Index (SOI); Sea Surface Temperature (SST); Volatility;

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  1. Jose Angelo Divino & Michael McAleer, 2009. "Modelling Sustainable International Tourism Demand to the Brazilian Amazon," CIRJE F-Series, CIRJE, Faculty of Economics, University of Tokyo CIRJE-F-650, CIRJE, Faculty of Economics, University of Tokyo.
  2. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 19(02), pages 280-310, April.
  3. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, Elsevier, vol. 139(2), pages 259-284, August.
  4. Shiqing Ling & Michael McAleer, 2001. "Necessary and Sufficient Moment Conditions for the GARCH(r,s) and Asymmetric Power GARCH(r,s) Models," ISER Discussion Paper, Institute of Social and Economic Research, Osaka University 0534, Institute of Social and Economic Research, Osaka University.
  5. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, Elsevier, vol. 106(1), pages 109-117, January.
  6. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 21(01), pages 232-261, February.
  7. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  8. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  9. Nelson, Daniel B., 1990. "Stationarity and Persistence in the GARCH(1,1) Model," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 6(03), pages 318-334, September.
  10. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche, Centre interuniversitaire de recherche en économie quantitative, CIREQ 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  11. Allan D. Brunner, 1998. "El Nino and world primary commodity prices: warm water or hot air?," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.) 608, Board of Governors of the Federal Reserve System (U.S.).
  12. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, Econometric Society, vol. 49(4), pages 1057-72, June.
  13. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 15(4), pages 117-128, Fall.
  14. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, Elsevier, vol. 64(3), pages 625-633, January.
  15. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper, Institute of Social and Economic Research, Osaka University 0548, Institute of Social and Economic Research, Osaka University.
  16. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, Econometric Society, vol. 61(4), pages 821-56, July.
  17. Guy Debelle & Glenn Stevens, 1995. "Monetary Policy Goals for Inflation in Australia," RBA Research Discussion Papers, Reserve Bank of Australia rdp9503, Reserve Bank of Australia.
  18. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 18(01), pages 17-39, February.
  19. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, Econometric Society, vol. 50(4), pages 987-1007, July.
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