IDEAS home Printed from https://ideas.repec.org/a/cup/jagaec/v20y1988i02p73-80_01.html
   My bibliography  Save this article

Forecasting Agricultural Prices Using a Bayesian Composite Approach

Author

Listed:
  • McIntosh, Christopher S.
  • Bessler, David A.

Abstract

Forecast users and market analysts need quality forecast information to improve their decision-making abilities. When more than one forecast is available, the analyst can improve forecast accuracy by using a composite forecast. One of several approaches to forming composite forecasts is a Bayesian approach using matrix beta priors. This paper explains the matrix beta approach and applies it to three individual forecasts of U.S. hog prices. The Bayesian composite forecast is evaluated relative to composites made from simple averages, restricted least squares, and an adaptive weighting technique.

Suggested Citation

  • McIntosh, Christopher S. & Bessler, David A., 1988. "Forecasting Agricultural Prices Using a Bayesian Composite Approach," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 20(2), pages 73-80, December.
    • Handle: RePEc:cup:jagaec:v:20:y:1988:i:02:p:73-80_01
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0081305200017611/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bessler, David A & Chamberlain, Peter J, 1987. "On Bayesian composite forecasting," Omega, Elsevier, vol. 15(1), pages 43-48.
    2. Ashley, R & Granger, C W J & Schmalensee, R, 1980. "Advertising and Aggregate Consumption: An Analysis of Causality," Econometrica, Econometric Society, vol. 48(5), pages 1149-1167, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    2. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    3. Tronstad, Russell, 1991. "The Effects of Firm Size and Production Cost Levels on Dynamically Optimal After-Tax Cotton Storage and Hedging Decisions," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 23(1), pages 165-179, July.
    4. 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.
    5. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    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, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    2. Covey, Ted & Bessler, David A., 1991. "The Role of Futures in Daily Forward Pricing," 1991 Annual Meeting, August 4-7, Manhattan, Kansas 271282, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Henry Bryant & Michael Haigh, 2004. "Bid-ask spreads in commodity futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(13), pages 923-936.
    4. Ashley, Richard, 2003. "Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?," International Journal of Forecasting, Elsevier, vol. 19(2), pages 229-239.
    5. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    6. Pär Stockhammar & Pär Österholm, 2018. "Do inflation expectations granger cause inflation?," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(2), pages 403-431, August.
    7. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    8. Imad Moosa & Kelly Burns, 2014. "Error correction modelling and dynamic specifications as a conduit to outperforming the random walk in exchange rate forecasting," Applied Economics, Taylor & Francis Journals, vol. 46(25), pages 3107-3118, September.
    9. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Causality and predictability in distribution: The ethanol–food price relation revisited," Energy Economics, Elsevier, vol. 42(C), pages 152-160.
    10. Zapata, Hector O. & Gil, Jose M., 1999. "Cointegration and causality in international agricultural economics research," Agricultural Economics, Blackwell, vol. 20(1), pages 1-9, January.
    11. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
    12. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    13. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-840, November.
    14. Fullerton, Thomas M. & Kelley, Brian W., 2008. "El Paso Housing Sector Econometric Forecast Accuracy," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 40(1), pages 385-402, April.
    15. Hudson, Michael A. & Capps, Oral, Jr., 1984. "Forecasting Ex-Vessel Prices for Hard Blue Crabs in the Chesapeake Bay Region: Individual and Composite Methods," Journal of the Northeastern Agricultural Economics Council, Northeastern Agricultural and Resource Economics Association, vol. 13(1), pages 1-7, April.
    16. Francisco F. R. Ramos, 1996. "Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance," Econometrics 9601003, University Library of Munich, Germany.
    17. Benedetto Molinari & Francesco Turino, 2018. "Advertising and Aggregate Consumption: A Bayesian DSGE Assessment," Economic Journal, Royal Economic Society, vol. 128(613), pages 2106-2130, August.
    18. Ye, Haichun & Ashley, Richard & Guerard, John, 2015. "Comparing the effectiveness of traditional vs. mechanized identification methods in post-sample forecasting for a macroeconomic Granger causality analysis," International Journal of Forecasting, Elsevier, vol. 31(2), pages 488-500.
    19. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    20. Monticini, Andrea & Ravazzolo, Francesco, 2014. "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 304-315.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:jagaec:v:20:y:1988:i:02:p:73-80_01. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/aae .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.