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

Author

Listed:
  • Lan-Fen Chu

    (National Science and Technology Center for Disaster Taiwan)

  • M. McAleer

    (Econometric Institute Erasmus School of Economics Erasmus University Rotterdam and Institute of Economic Research Kyoto University andDepartment of Quantitative Economics Complutense University of Madrid)

  • Chi-Chung Chen

    (Department of Applied Economics National Chung Hsing University Taiwan)

Abstract

This paper analyzes two indexes in order to capture the volatility inherent in El Ninos 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 Nino 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 Nino or La Nina effects in the future if global greenhouse gas emissions continue to increase unabated.

Suggested Citation

  • Lan-Fen Chu & M. McAleer & Chi-Chung Chen, 2012. "How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?," KIER Working Papers 829, Kyoto University, Institute of Economic Research.
    • Handle: RePEc:kyo:wpaper:829
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    References listed on IDEAS

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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Guy Debelle & Glenn Stevens, 1995. "Monetary Policy Goals for Inflation in Australia," RBA Research Discussion Papers rdp9503, Reserve Bank of Australia.
    4. Allan D. Brunner, 2002. "El Niño and World Primary Commodity Prices: Warm Water or Hot Air?," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 176-183, February.
    5. Ling, Shiqing & McAleer, Michael, 2002. "NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS," Econometric Theory, Cambridge University Press, vol. 18(3), pages 722-729, June.
    6. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    8. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    9. Divino, J.A. & McAleer, M.J., 2008. "Modelling sustainable international tourism demand to the Brazilian Amazon," Econometric Institute Research Papers EI 2008-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    11. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    12. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    13. A. Timmermann & J. Oberhuber & A. Bacher & M. Esch & M. Latif & E. Roeckner, 1999. "Increased El Niño frequency in a climate model forced by future greenhouse warming," Nature, Nature, vol. 398(6729), pages 694-697, April.
    14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    15. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    16. Chen, Chi-Chung & McCarl, Bruce A., 2000. "The Value Of Enso Information To Agriculture: Consideration Of Event Strength And Trade," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-18, December.
    17. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    18. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
    19. Shiqing Ling & W. K. Li, 1997. "Diagnostic checking of nonlinear multivariate time series with multivariate arch errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(5), pages 447-464, September.
    20. Hall, Anthony D. & Skalin, Joakim & Teräsvirta, Timo, 1998. "A nonlinear time series model of El Niño," SSE/EFI Working Paper Series in Economics and Finance 263, Stockholm School of Economics.
    21. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    22. Nelson, Daniel B., 1990. "Stationarity and Persistence in the GARCH(1,1) Model," Econometric Theory, Cambridge University Press, vol. 6(3), pages 318-334, September.
    23. Carrasco, Marine & Chen, Xiaohong, 2002. "Mixing And Moment Properties Of Various Garch And Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 18(1), pages 17-39, February.
    24. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Glen Livingston & Darfiana Nur, 2020. "Bayesian inference of smooth transition autoregressive (STAR)(k)–GARCH(l, m) models," Statistical Papers, Springer, vol. 61(6), pages 2449-2482, December.

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    More about this item

    Keywords

    El Ninos Southern Oscillations (ENSO); Greenhouse Gas Emissions; Global Economy; Southern Oscillation Index (SOI); Sea Surface Temperature (SST); Volatility.;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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