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Composite and Outlook Forecast Accuracy

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  • Colino, Evelyn V.
  • Irwin, Scott H.
  • Garcia, Philip
  • Etienne, Xiaoli

Abstract

This paper investigates whether the accuracy of outlook hog price forecasts can be improved using composite forecasts in an out-of-sample context. Price forecasts from four widely-recognized outlook programs are combined with futures-based forecasts, ARMA, and unrestricted Vector Autoregressive (VAR) models. Quarterly data are available from 1975.I through 2007.IV for Illinois/Purdue and 1975.I-2010.IV for Iowa, Missouri, and USDA forecasts, which allow for a relatively long out-of-sample evaluation after permitting model specification and appropriate composite-weight training periods. Results show that futures and numerous composite procedures outperform outlook forecasts, but no-change forecasts are inferior to outlook forecasts. At intermediate horizons, OLS composite procedures perform well. The superiority of futures and composite forecasts decreases at longer horizons except for an equal-weighted approach. Importantly, with few exceptions, nothing outperforms the equal-weight approach significantly in any program or horizon. In addition, the equal-weight approach as well as other composite approaches can generally produce larger trading profits compared to outlook forecasts. Overall, findings favor the use of equal-weighted composites, consistent with previous empirical findings and recent theoretical papers.

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Bibliographic Info

Article provided by Western Agricultural Economics Association in its journal Journal of Agricultural and Resource Economics.

Volume (Year): 37 (2012)
Issue (Month): 2 (August)
Pages:

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Handle: RePEc:ags:jlaare:134270

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Web page: http://waeaonline.org/
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Related research

Keywords: forecast combination; futures; out-of-sample; outlook; time-series; Agribusiness;

References

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Cited by:
  1. Isengildina-Massa, Olga & Sharp, Julia L., 2013. "Interval Forecast Comparison," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150791, Agricultural and Applied Economics Association.

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