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Abstract

This study examines the benets of nonlinear time series modelling to improve forecast accuracy of the El Nino Southern Oscillation (ENSO) phenomenon. The paper adopts a smooth transition autoregressive (STAR) modelling framework to assess the potentially regime-dependent dynamics of sea surface temperature anomaly. The results reveal STAR-type nonlinearities in ENSO dynamics, resulting in superior out-of-sample forecast performance of STAR over the linear autoregressive models. The advantage of nonlinear models is especially apparent in the short- and intermediate-term forecasts. These results are of interest to researchers and policy makers in the elds of climate dynamics, agricultural production, and environmental management.

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File URL: http://mpra.ub.uni-muenchen.de/36890/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 36890.

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Date of creation: Jan 2012
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Handle: RePEc:pra:mprapa:36890

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Web page: http://mpra.ub.uni-muenchen.de
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Related research

Keywords: El Nino Southern Oscillation; Out-of-Sample Forecasting; Smooth Transition Autoregression;

Find related papers by JEL classification:

• C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
• C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
• Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters

This paper has been announced in the following NEP Reports:

• NEP-ALL-2012-03-08 (All new papers)
• NEP-ENV-2012-03-08 (Environmental Economics)
• NEP-FOR-2012-03-08 (Forecasting)

References

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1. Sarantis, Nicholas, 1999. "Modeling non-linearities in real effective exchange rates," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 27-45, January.
2. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
   
   • Teräsvirta, Timo & van Dijk, Dick & Medeiros, Marcelo, 2004. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," Working Paper Series in Economics and Finance 561, Stockholm School of Economics, revised 04 Nov 2004.
   • Timo Teräsvirta & Dick van Dijk & Marcelo Cunha Medeiros, 2004. "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination," Textos para discussão 485, Department of Economics PUC-Rio (Brazil).
3. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
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.
   
   • Allan D. Brunner, 1998. "El Nino and world primary commodity prices: warm water or hot air?," International Finance Discussion Papers 608, Board of Governors of the Federal Reserve System (U.S.).
   • Allan D. Brunner, 2000. "El Nino and World Primary Commodity Prices: Warm Water or Hot Air?," IMF Working Papers 00/203, International Monetary Fund.
5. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
6. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
7. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
   
   • Costas Milas & Philip Rothman, 2007. "Out-of-Sample Forecasting of Unemployment Rates with Pooled STVECM Forecasts," Working Paper Series 49-07, The Rimini Centre for Economic Analysis, revised Jul 2007.
8. Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
   
   • Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
   
   • Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
   • Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
10. Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
    
    • Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
11. Hall, Anthony D. & Skalin, Joakim & Teräsvirta, Timo, 1998. "A nonlinear time series model of El Niño," Working Paper Series in Economics and Finance 263, Stockholm School of Economics.
12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
13. David Ubilava, 2012. "El Niño, La Niña, and world coffee price dynamics," Agricultural Economics, International Association of Agricultural Economists, vol. 43(1), pages 17-26, 01.
14. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised 05 Oct 1998.
    
    • Skalin, Joakim & Ter svirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(02), pages 202-241, April.
15. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.

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