Forecast evaluations in meat demand analysis

Zijun Wang and David Bessler ()
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Zijun Wang: Private Enterprise Research Center, Academic Building West, Room 3028, Texas A&M University, College Station, Texas 77843-4231., E-mail: z-wang@tamu.edu, Postal: Private Enterprise Research Center, Academic Building West, Room 3028, Texas A&M University, College Station, Texas 77843-4231., E-mail: z-wang@tamu.edu

Agribusiness, 2003, vol. 19, issue 4, 505-523

Abstract: This article offers a comparison of short-term forecasting ability of five demand systems with an application to U.S. meat consumption. Four static demand systems (AIDS, Rotterdam, AIM, and DGM) and a dynamic Vector Error Correction Model (VECM) are considered. We tested the equality of mean square forecast errors. We also investigated the possibility of forecast encompassing among competing models. In general, the dynamic VECM model performed best, followed by the simple causal DGM model. Among three static systems, the AIDS model slightly leads the competition. Furthermore, this article provides the first evidence in literature on whether imposition of homogeneity restrictions on a cointegration space can improve the forecast accuracy of a VECM model: it does when it holds. [EconLit citations: Q10; C53]. © 2003 Wiley Periodicals, Inc. Agribusiness 19: 505-523, 2003.

Date: 2003
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:wly:agribz:v:19:y:2003:i:4:p:505-523

DOI: 10.1002/agr.10074

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