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Can Cattle Basis Forecasts Be Improved? A Bayesian Model Averaging Approach

  • Nicholas D. Payne (a1), Berna Karali (a1) and Jeffrey H. Dorfman (a2)

Abstract

Basis forecasting is important for producers and consumers of agricultural commodities in their risk management decisions. However, the best performing forecasting model found in previous studies varies substantially. Given this inconsistency, we take a Bayesian approach, which addresses model uncertainty by combining forecasts from different models. Results show model performance differs by location and forecast horizon, but the forecast from the Bayesian approach often performs favorably. In some cases, however, the simple moving averages have lower forecast errors. Besides the nearby basis, we also examine basis in a specific month and find that regression-based models outperform others in longer horizons.

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Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

*Corresponding author. Email: bkarali@uga.edu

References

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Barry, D., and Hartigan, J.A.. “A Bayesian Analysis for Change Point Problems.” Journal of the American Statistical Association 88, 421(1993):309–19.
Dhuyvetter, K.C., and Kastens, T.L.. “Forecasting Crop Basis: Practical Alternatives.” Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, Chicago, IL. Urbana-Champaign: University of Illinois at Urbana-Champaign, 1998, pp. 4967.
Dorfman, J.H.A Numerical Bayesian Test for Cointegration of AR Processes.” Journal of Econometrics 66, 1–2(1995):289324.
Erdman, C., and Emerson, J.W.. “bcp: An R package for Performing a Bayesian Analysis of Change Point Problems.” Journal of Statistical Software 23, 3(2007):113.
Garcia, P., and Good, D.. “An Analysis of the Factors Influencing the Illinois Corn Basis, 1971–1981.” Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, Chicago, IL. Urbana-Champaign: University of Illinois at Urbana-Champaign, 1983, pp. 306–26.
Hatchett, R.B., Brorsen, B.W., and Anderson, K.B.. “Optimal Length of Moving Average to Forecast Futures Basis.” Journal of Agricultural and Resource Economics 35, 1(2010):1833.
Hauser, R.J., Garcia, P., and Tumblin, A.D.. “Basis Expectations and Soybean Hedging Effectiveness.” North Central Journal of Agricultural Economics 12, 1(1990):125–36.
Hoeting, J.A., Madigan, D., Raftery, A.E., and Volinsky, C.T.. “Bayesian Model Averaging: A Tutorial.” Statistical Science 14, 4(1999):382417.
Irwin, S.H., Garcia, P., Good, D.L., and Kunda, E.L.. Poor Convergence Performance of CBT Corn, Soybean, and Wheat Futures Contracts: Causes and Solutions. Urbana-Champaign: Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Marketing and Outlook Research Report 2009–02, March 2009.
Jiang, B., and Hayenga, M.. “Corn and Soybean Basis Behavior and Forecasting: Fundamental and Alternative Approaches.” Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, Chicago, IL. Urbana-Champaign: University of Illinois at Urbana-Champaign, 1997, pp. 125–40.
Koop, G. Bayesian Econometrics. Chichester, UK: Wiley, 2003.
Martin, L., Groenewegen, J.L., and Pidgeon, E.. “Factors Affecting Corn Basis in Southwestern Ontario.” American Journal of Agricultural Economics 62, 1(1980):107–12.
Sanders, D.J., and Baker, T.G.. “Forecasting Corn and Soybean Basis Using Regime-Switching Models.” Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, Chicago, IL. Urbana-Champaign: University of Illinois at Urbana-Champaign, 2012, pp. 118.
Sanders, D.R., and Manfredo, M.R.. “Forecasting Basis Levels in the Soybean Complex: A Comparison of Time Series Models.” Journal of Agricultural and Applied Economics 38, 3(2006):513–23.
Taylor, M.R., Dhuyvetter, K.C., and Kastens, T.L.. “Forecasting Crop Basis Using Historical Averages Supplemented with Current Market Information.” Journal of Agricultural and Resource Economics 31, 3(2006):549–67.
Tomek, W.G.Commodity Futures Prices as Forecasts.” Review of Agricultural Economics 19, 1(1997):2344.
Tonsor, G.T., Dhuyvetter, K.C., and Mintert, J.R.. “Improving Cattle Basis Forecasting.” Journal of Agricultural and Resource Economics 29, 2(2004):228–41.

Keywords

Can Cattle Basis Forecasts Be Improved? A Bayesian Model Averaging Approach

  • Nicholas D. Payne (a1), Berna Karali (a1) and Jeffrey H. Dorfman (a2)

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