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Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method

Author

Listed:
  • Amiri, Arshia
  • Bakhshoodeh, Mohamad
  • Najafi, Bahaeddin

Abstract

This paper, we studied the ability of geostatistical models (ordinary kriging (OK) and Inverse distance weighting (IDW)), adaptive neuro-fuzzy inference system (ANFIS) and Winter method for prediction of seasonality in prices of potatoes and onions in Iran over the seasonal period 1986_2001. Results show that the best estimators in order are winter method, ANFIS and geostatistical methods. The results indicate that Winter and ANFIS had powerful results for prediction the prices while geostatistical models were not useful in this respect.

Suggested Citation

  • Amiri, Arshia & Bakhshoodeh, Mohamad & Najafi, Bahaeddin, 2011. "Forecasting seasonality in prices of potatoes and onions: challenge between geostatistical models, neuro fuzzy approach and Winter method," MPRA Paper 34093, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:34093
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    File URL: https://mpra.ub.uni-muenchen.de/34093/1/MPRA_paper_34093.pdf
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    References listed on IDEAS

    as
    1. Zou, Hui & Yang, Yuhong, 2004. "Combining time series models for forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 69-84.
    2. Taylor, James W., 2003. "Exponential smoothing with a damped multiplicative trend," International Journal of Forecasting, Elsevier, vol. 19(4), pages 715-725.
    3. J. Scott Armstrong & Kesten C. Green, 2005. "Demand Forecasting: Evidence-based Methods," Monash Econometrics and Business Statistics Working Papers 24/05, Monash University, Department of Econometrics and Business Statistics.
    4. Granger, C. W. J. & Newbold, P., 1976. "The use of R2 to determine the appropriate transformation of regression variables," Journal of Econometrics, Elsevier, vol. 4(3), pages 205-210, August.
    5. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
    6. Joutz, Frederick L. & Trost, Robert P. & Hallahan, Charles B. & Clauson, Annette L. & Denbaly, Mark, 2000. "Retail Food Price Forecasting At Ers: The Process, Methodology, And Performance From 1984 To 1997," Technical Bulletins 33575, United States Department of Agriculture, Economic Research Service.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Price; Geostatistical model; Kiriging; Inverse distance weighting; Winter’s method; Adaptive neuro fuzzy inference system; Potatoes; Onions; Iran;

    JEL classification:

    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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