Arbeitspapier

Forecasting seasonally cointegrated systems: Supply response in Austrian agriculture

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.

Language: Englisch

Bibliographic citation: Series: Reihe Ökonomie / Economics Series ; No. 11

Classification: Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Forecasting Models; Simulation Methods
Agriculture: Aggregate Supply and Demand Analysis; Prices

Subject: seasonality
agricultural supply response
cointegration
time series

Event: Geistige Schöpfung

(who): Jumah, Adusei
Kunst, Robert M.

Event: Veröffentlichung

(who): Institute for Advanced Studies (IHS)

(where): Vienna

(when): 1995

Handle: http://hdl.handle.net/10419/68561

Last update: 10.03.2025, 11:43 AM CET

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Object type

Arbeitspapier

Associated

Jumah, Adusei
Kunst, Robert M.
Institute for Advanced Studies (IHS)

Time of origin

1995

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Forecasting seasonally cointegrated systems: Supply response in Austrian agriculture

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