IDEAS home Printed from https://ideas.repec.org/a/ags/remaae/12478.html
   My bibliography  Save this article

Forecasting N.S.W. Beef Production: An Evaluation of Alternative Techniques

Author

Listed:
  • Gellatly, Colin

Abstract

This paper reports on the evaluation of the performance of several forecasting methods used to forecast New South Wales quarterly beef production, one quarter ahead. The forecasting procedures used are a single equation regression model, a Box-Jenkins univariate time series model, a forecasting committee's judgement and a naive model. Absolute accuracy and relative accuracy measures are used to evaluate ex ante forecasts. Although the evaluation gave some mixed results according to the criteria used, it appears that the forecasting committee performed better than the alternative forecasting procedures considered in this study. However, the results indicate that the committee's performance was not much better than that of a naive (no change) model, indicating there is room for improvement.

Suggested Citation

  • Gellatly, Colin, 1979. "Forecasting N.S.W. Beef Production: An Evaluation of Alternative Techniques," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 47(02), pages 1-14, August.
    • Handle: RePEc:ags:remaae:12478
    DOI: 10.22004/ag.econ.12478
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/12478/files/47020081.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.12478?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    2. N.C. Mackrell, 1974. "Techniques of Short Term Forecasting," RBA Research Discussion Papers rdp36, Reserve Bank of Australia.
    3. M. E. Burns, 1973. "A Note on the Choice of Data in Econometric Studies," The Economic Record, The Economic Society of Australia, vol. 49(1), pages 24-30, March.
    4. Raymond M. Leuthold, 1975. "On the Use of Theil's Inequality Coefficients," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 57(2), pages 344-346.
    5. Burns, M E, 1973. "A Note on the Choice of Data in Econometric Studies," The Economic Record, The Economic Society of Australia, vol. 49(125), pages 24-30, March.
    6. Ryland, G.J., 1975. "Forecasting Crop Quality," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 43(02), pages 1-16, June.
    7. John W. Freebairn, 1975. "Forecasting For Australian Agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 19(3), pages 154-174, December.
    8. Mervin Daub, 1973. "On the Accuracy of Canadian Short-term Economic Forecasts," Canadian Journal of Economics, Canadian Economics Association, vol. 6(1), pages 90-107, February.
    9. Phoebus J. Dhrymes & E. Philip Howrey & Saul H. Hymans & Jan Kmenta & Edward E. Leamer & Richard E. Quandt & James B. Ramsey & Harold T. Shapiro & Victor Zarnowitz, 1972. "Criteria for Evaluation of Econometric Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 291-324, National Bureau of Economic Research, Inc.
    10. Kym Anderson, 1974. "Distributed Lags And Barley Acreage Response Analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 18(2), pages 119-132, August.
    11. M. N. Bhattacharyya, 1974. "Forecasting the Demand for Telephones in Australia," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(1), pages 1-10, March.
    Full references (including those not matched with items on IDEAS)

    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. Freebairn, John W., 1975. "Forecasting For Australian Agriculture," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 19(3), pages 1-21, December.
    2. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    3. John McDonald, 1974. "Errors in Economic Time Series: Some Implications for Estimation in Econometric Models," The Economic Record, The Economic Society of Australia, vol. 50(2), pages 278-286, June.
    4. R. P. Albon & T. J. Valentine, 1977. "The Sectoral Demand for Bank Loans in Australia," The Economic Record, The Economic Society of Australia, vol. 53(2), pages 167-181, June.
    5. Adam Elbourne & Henk Kranendonk & Rob Luginbuhl & Bert Smid & Martin Vromans, 2008. "Evaluating CPB's published GDP growth forecasts; a comparison with individual and pooled VAR based forecasts," CPB Document 172, CPB Netherlands Bureau for Economic Policy Analysis.
    6. Dwight R. Sanders & Mark R. Manfredo, 2008. "Multiple horizons and information in USDA production forecasts," Agribusiness, John Wiley & Sons, Ltd., vol. 24(1), pages 55-66.
    7. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
    8. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    9. Jan Jacobs & Jan-Egbert Sturm, 2009. "The information content of KOF indicators on Swiss current account data revisions," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2008(2), pages 161-181.
    10. Christina Ziegler, 2009. "Testing Predicitive Ability of Business Cycle Indicators for the Euro Area," ifo Working Paper Series 69, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    11. repec:kap:iaecre:v:14:y:2008:i:1:p:112-124 is not listed on IDEAS
    12. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
    13. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisions of German Industrial Production Statistics and Ifo Indicators," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
    14. Baris Soybilgen & Ege Yazgan, 2017. "An evaluation of inflation expectations in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(1), pages 1-31–38.
    15. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    16. Pericoli, Marcello & Taboga, Marco, 2012. "Bond risk premia, macroeconomic fundamentals and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 42-65.
    17. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
    18. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    19. Michael P. Clements, 2014. "US Inflation Expectations and Heterogeneous Loss Functions, 1968–2010," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 1-14, January.
    20. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    21. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.

    More about this item

    Keywords

    Livestock Production/Industries;

    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:ags:remaae:12478. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaresea.html .

    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.