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Forecasting Wheat Yields: An Application of Parametric Time Series Modeling

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  • Andrew Schmitz
  • Donald G. Watts

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.

Suggested Citation

  • Andrew Schmitz & Donald G. Watts, 1970. "Forecasting Wheat Yields: An Application of Parametric Time Series Modeling," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 52(2), pages 247-254.
    • Handle: RePEc:oup:ajagec:v:52:y:1970:i:2:p:247-254.
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    File URL: http://hdl.handle.net/10.2307/1237496
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    Cited by:

    1. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    2. Miller, Stephen E., 1982. "Predicting Time Series Turning Points with Arima Models," Working Papers 116869, Clemson University, Department of Agricultural and Applied Economics.
    3. Pope, Rulon D. & Kramer, Randall A. & Green, Richard D. & Gardner, B. Delworth, 1979. "An Evaluation Of Econometric Models Of U.S. Farmland Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 4(1), pages 1-14, July.
    4. Nevala, M., 1977. "On methods for forecasting production aid consumption of agricultural products," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 40.

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