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Alternative Model Selection Using Forecast Error Variance Decompositions in Wholesale Chicken Markets

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  • McKenzie, Andrew M.
  • Goodwin, Harold L.
  • Carreira, Rita I.
Abstract
Although Vector Autoregressive models are commonly used to forecast prices, specification of these models remains an issue. Questions that arise include choice of variables and lag length. This article examines the use of Forecast Error Variance Decompositions to guide the econometrician's model specification. Forecasting performance of Variance Autoregressive models, generated from Forecast Error Variance Decompositions, is analyzed within wholesale chicken markets. Results show that the Forecast Error Variance Decomposition approach has the potential to provide superior model selections to traditional Granger Causality tests.

Suggested Citation

  • McKenzie, Andrew M. & Goodwin, Harold L. & Carreira, Rita I., 2009. "Alternative Model Selection Using Forecast Error Variance Decompositions in Wholesale Chicken Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(1), pages 227-240, April.
    • Handle: RePEc:cup:jagaec:v:41:y:2009:i:01:p:227-240_00
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    Cited by:

    1. Palma, Marco & Ribera, Luis & Bessler, David A., 2015. "Impacts of the Drug Trade on Latin American Food Production," 2015 Allied Social Sciences Association (ASSA) Annual Meeting, January 3-5, 2015, Boston, Massachusetts 189693, Agricultural and Applied Economics Association.
    2. Bukin, Kirill (Букин, Кирилл), 2015. "Diffusion of innovation: a model of evolutionary processes [Диффузия Инноваций: Модель Эволюционных Процессов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, pages 133-143.
    3. Fousekis, Panos & Tzaferi, Dimitra, 2018. "Market connectedness in the US beef supply chain," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1).

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