Forecasting Seasonally Cointegrated Systems: Supply Response in Austrian Agriculture

Abstract: This paper examines the relevance of incorporating seasonality in agricultural supply models. Former studies have eliminated the problem of seasonality by using seasonally adjusted data. Recent developments in cointegration techniques allow the comprehensive modelling of error-correcting s...

Ausführliche Beschreibung

Bibliographische Detailangaben
Link(s) zu Dokument(en):IHS Publikation
Hauptverfasser: Jumah, Adusei, Kunst, Robert M.
Format: IHS Series NonPeerReviewed
Sprache:Englisch
Veröffentlicht: Institut für Höhere Studien 1995
Beschreibung
Zusammenfassung:Abstract: This paper examines the relevance of incorporating seasonality in agricultural supply models. Former studies have eliminated the problem of seasonality by using seasonally adjusted data. Recent developments in cointegration techniques allow the comprehensive modelling of error-correcting structures in the presence of seasonality. We consider a four-variables model for Austrian agriculture. Series on the producer price for soy beans, bulls and pigs, as well as the stock of breeding sows are included. A vector autoregression incorporating seasonal cointegration is estimated. A tentative interpretation of long-run and seasonal features is considered. The model is also used to generate forecasts for the supply of pigs in Austria.;