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Use Of Asymmetric-Cycle Autoregressive Models To Improve Forecasting Of Agricultural Time Series Variables

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  • Ramirez, Octavio A.
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    Abstract

    Threshold autoregressive (TAR) models can accommodate the asymmetric cycling behavior observed in some time series data. This study develops a procedure to estimate TAR models when the conditional mean of the dependent variable is function of one or more exogenous factors while allowing for heteroskedasticity, i.e. for different levels of variation in upward versus downward cycles. The formulas to obtain predictions from TAR models are derived. Monte Carlo simulation analyses suggest that TAR models can significantly improve forecasting precision. Substantial gains in forecasting precision, in comparison with AR models, are in fact found when applying the proposed procedure to the modeling of U.S. quarterly soybeans future prices and Brazilian coffee spot prices. The estimated TAR models also provide useful insights on the markedly different dynamics of the upward versus the downward cycles exhibited by U.S. soybeans and Brazilian coffee prices.

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    File URL: http://purl.umn.edu/21365
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    Bibliographic Info

    Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2006 Annual meeting, July 23-26, Long Beach, CA with number 21365.

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    Date of creation: 2006
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    Handle: RePEc:ags:aaea06:21365

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    Keywords: Research Methods/ Statistical Methods;

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    1. Maurice Obstfeld and Alan M. Taylor., 1997. "Nonlinear Aspects of Goods-Market Arbitrage and Adjustment: Heckscher's Commodity Points Revisited," Center for International and Development Economics Research (CIDER) Working Papers C97-088, University of California at Berkeley.
    2. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-45, August.
    3. Barry K. Goodwin & Nicholas E. Piggott, 2001. "Spatial Market Integration in the Presence of Threshold Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 302-317.
    4. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-76, April.
    5. Enders, Walter & Granger, C. W. J., 1998. "Unit Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Staff General Research Papers 1388, Iowa State University, Department of Economics.
    6. Bradley, Michael D & Jansen, Dennis W, 1997. "Nonlinear Business Cycle Dynamics: Cross-country Evidence on the Persistence of Aggregate Shocks," Economic Inquiry, Western Economic Association International, vol. 35(3), pages 495-509, July.
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