Forecasting Wheat Yields: An Application of Parametric Time Series Modeling

Andrew Schmitz and Donald G. Watts

American Journal of Agricultural Economics, 1970, vol. 52, issue 2, 247-254

Abstract: The purpose of this paper is to use a recent development in statisical theory known as parametric modeling to forecast wheat yields in the United States, Canada, Australia, and Argentina. The essence of this approach is that the data are used for identifying and estimating random components in the form of moving average and autoregressive processes. It does not identify and measure structural relationships as is attempted when forecasting with econometric models. Exponential smoothing is also used to forecast yields in the United States and Canada. The Thiel coefficient is then computed to determine the forecasting accuracy of parametric modeling compared with exponential smoothing.

Date: 1970
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:52:y:1970:i:2:p:247-254.

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