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Adaptive Expectations, the Exponentially Weighted Forecast, and Optimal Statistical Predictors: A Revisit

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  • Bessler, David A.

Abstract

Relationships between adaptive expectations, the exponentially weighted moving average, and optimal Univariate statistical predictors are reviewed We show that the behavioral-based adaptive expectations are a subclass of both the exponentially weighted moving average and the (0,1,1) ARIMA model The applicability of the adaptive expectations model to 25 empirical price and quantity series is investigated The adaptive expectations behavior and the optimal statistical forecasts are equivalent for 13 senes-11 on Yields and 2 on prices Numerous price series, while exhibiting the general form o[ the adaptive expectations (a (0,1,1) ARIMA process), did not have a coefficient o[ expectations within the originally hypothesized range The behavior consistent with the model underlying these price series would be trend extrapolation rather than averaging (averaging the most recent observation and Its forecast) Series measured at monthly or quarterly Intervals were not adequately modeled by adaptive expectations or as a (0,1,1) ARIMA process

Suggested Citation

  • Bessler, David A., 1982. "Adaptive Expectations, the Exponentially Weighted Forecast, and Optimal Statistical Predictors: A Revisit," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 34(2), pages 1-8, April.
    • Handle: RePEc:ags:uersja:148819
    DOI: 10.22004/ag.econ.148819
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    Citations

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    Cited by:

    1. Timothy Park & Frances Antonovitz, 1990. "Basis risk and optimal decision making for California feedlots," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 10(3), pages 259-271, June.
    2. Skold, Karl Durwood, 1989. "The integration of alternative information systems: an application to the Hogs and Pigs report," ISU General Staff Papers 1989010108000010239, Iowa State University, Department of Economics.
    3. Ardian Harri & Cumhur Erdem & Keith H. Coble & Thomas O. Knight, 2009. "Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 163-182.
    4. Bessler, David A., 1985. "The Forecast In Risk Analysis," Regional Research Projects > 1985: S-180 Annual Meeting, March 24-27, 1985, Charleston, South Carolina 271795, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.
    5. Shonkwiler, John Scott & Hinckley, Suzanne, 1985. "A Generalized Supply Response/Factor Demand Model And Its Application To The Feeder Cattle Market," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 10(2), pages 1-9, December.
    6. Xiaojie Xu & Yun Zhang, 2023. "Coking coal futures price index forecasting with the neural network," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 349-359, June.
    7. Xiaojie Xu & Yun Zhang, 2022. "Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network," Economics Bulletin, AccessEcon, vol. 42(3), pages 1266-1279.

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