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Combining Annual Econometric Forecasts With Quarterly Arima Froecasts: A Heuristic Approach

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  • Myer, Gordon L.
  • Yanagida, John F.

Abstract

Data limitations often limit the time framework in which agricultural commodities are modeled and prices forecasted. Our research provides a technique to alleviate this constraint. By combining an annual econometric model with a quarterly ARIMA model, quarterly forecasts can be made which utilize the theoretical and structural foundations in econometric modeling.

Suggested Citation

  • Myer, Gordon L. & Yanagida, John F., 1984. "Combining Annual Econometric Forecasts With Quarterly Arima Froecasts: A Heuristic Approach," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(1), pages 1-7, July.
    • Handle: RePEc:ags:wjagec:32375
    DOI: 10.22004/ag.econ.32375
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    References listed on IDEAS

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    1. Helmers, Glenn A. & Held, Larry J., 1977. "Comparison Of Livestock Price Forecasting Using Simple Techniques, Forward Pricing And Outlook Information," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 1(1), pages 1-4, June.
    2. Dale Heien, 1977. "Price Determination Processes for Agricultural Sector Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(1), pages 126-132.
    3. Jon A. Brandt & David A. Bessler, 1981. "Composite Forecasting: An Application with U.S. Hog Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(1), pages 135-140.
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    Cited by:

    1. Yu Zhao & Xi Zhang & Zhongshun Shi & Lei He, 2017. "Grain Price Forecasting Using a Hybrid Stochastic Method," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(05), pages 1-24, October.
    2. Ferenc Bakó & Judit Berkes & Cecília Szigeti, 2021. "Households’ Electricity Consumption in Hungarian Urban Areas," Energies, MDPI, vol. 14(10), pages 1-23, May.

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