IDEAS home Printed from https://ideas.repec.org/a/ags/wjagec/32505.html

Price Forecasting With Time-Series Methods And Nonstationary Data: An Application To Monthly U.S. Cattle Prices

Author

Listed:
  • Zapata, Hector O.
  • Garcia, Philip

Abstract

The forecasting performance of various multivariate as well as univariate ARIMA models is evaluated in the presence of nonstationarity. The results indicate the importance of identifying the characteristics of the time series by testing for types of nonstationarity. Procedures that permit model specifications consistent with the system's dynamics provide the most accurate forecasts.

Suggested Citation

  • Zapata, Hector O. & Garcia, Philip, 1990. "Price Forecasting With Time-Series Methods And Nonstationary Data: An Application To Monthly U.S. Cattle Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 15(01), pages 1-10, July.
    • Handle: RePEc:ags:wjagec:32505
    DOI: 10.22004/ag.econ.32505
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/32505/files/15010123.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.32505?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. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    3. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    4. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    5. Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
    6. David A. Bessler & John L. Kling, 1986. "Forecasting Vector Autoregressions with Bayesian Priors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(1), pages 144-151.
    7. Gopal Naik & Raymond M. Leuthold, 1986. "A Note on Qualitative Forecast Evaluation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(3), pages 721-726.
    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. Franken, Jason & Parcell, Joe, 2016. "Forecasting Quality Grade and Certified Angus Beef Premiums," 2016 Conference, April 18-19, 2016, St. Louis, Missouri 285862, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    2. Elham Rahmani & Mohammad Khatami & Emma Stephens, 2024. "Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada," Sustainability, MDPI, vol. 16(5), pages 1-19, February.
    3. Covey, Ted & Bessler, David A., "undated". "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).
    4. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    5. P. Geoffrey Allen & Robert Fildes, 2005. "Levels, Differences and ECMs – Principles for Improved Econometric Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 881-904, December.
    6. Florkowski, Wojciech J. & Lai, Yue, 1997. "Cointegration Between Prices of Pecans and Other Edible Nuts: Forecasting and Implications," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35870, Western Agricultural Economics Association.
    7. Trujillo-Barrera, Andres Trujillo- & Garcia, Philip, 2013. "Price Density Forecasts in the U.S. Hog Market: Composite Procedures," 2013 Conference, April 22-23, 2013, St. Louis, Missouri 285804, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.

    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. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    2. Naci H. Mocan, 1989. "Business Cycles and Fertility Dynamics in the U.S.: A Vector-Autoregressive Model," NBER Working Papers 3177, National Bureau of Economic Research, Inc.
    3. Bierens, Herman J., 1997. "Nonparametric cointegration analysis," Journal of Econometrics, Elsevier, vol. 77(2), pages 379-404, April.
    4. Asraul Hoque, 1995. "Co-integrating relationship between terms of trade and current account deficit: the Australian evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 2(4), pages 130-133.
    5. Norah Al-Ballaa, 2005. "Test for cointegration based on two-stage least squares," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(7), pages 707-713.
    6. Athanasopoulos, George & Issler, João Victor & Guillen, Osmani Teixeira Carvalho, 2005. "Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 589, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    7. Al-Iriani, Mahmoud A., 2006. "Energy-GDP relationship revisited: An example from GCC countries using panel causality," Energy Policy, Elsevier, vol. 34(17), pages 3342-3350, November.
    8. Sanju Naraidoo & Sanjeev K. Sobhee, 2020. "An Investigation into the Intertemporal Spending Path of Local Government in Mauritius," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(4), pages 432-453, November.
    9. Abhijit Sharma & Theodore Panagiotidis, 2003. "An Analysis of Exports and Growth in India: Some Empirical Evidence (1971-2001)," Working Papers 2003004, The University of Sheffield, Department of Economics, revised Nov 2003.
    10. Carol H. Shiue & Wolfgang Keller, 2007. "Markets in China and Europe on the Eve of the Industrial Revolution," American Economic Review, American Economic Association, vol. 97(4), pages 1189-1216, September.
    11. ROY Subrata, 2020. "Gold & Stock Relation: Investors Reaction During Covid-19 Outbreak," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 72(3), pages 103-126, November.
    12. Tu, Yundong & Yao, Qiwei & Zhang, Rongmao, 2020. "Error-correction factor models for high-dimensional cointegrated time series," LSE Research Online Documents on Economics 106994, London School of Economics and Political Science, LSE Library.
    13. Lütkepohl, Helmut, 1999. "Vector autoregressions," SFB 373 Discussion Papers 1999,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    14. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    15. Myers, Robert J., 1994. "Time Series Econometrics and Commodity Price Analysis: A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 62(02), pages 1-15, August.
    16. Subrata Roy, 2020. "Gold & Stock Relation: Investors’ Reaction During Covid-19 Outbreak," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 26, pages 29-52, December.
    17. Rutkauskas Virgilijus & Gudauskaitė Laura, 2018. "Explaining the Changes of Agriculture Land Prices in Lithuania," Ekonomika (Economics), Sciendo, vol. 97(1), pages 63-75, January.
    18. Vogelvang, E., 1990. "Testing for co-integration with spot prices of some related agricultural commodities," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    19. Hadj Saadi, 2001. "Le phénomène des mouvements joints des prix internationaux de matières premières," Revue Tiers Monde, Programme National Persée, vol. 42(168), pages 865-883.
    20. F.C. Neil Myer & Mukesh K. Chaudhry & James R. Webb, 1997. "Stationarity and Co-Integration in Systems with Three National Real Estate Indices," Journal of Real Estate Research, American Real Estate Society, vol. 13(3), pages 369-381.

    More about this item

    Keywords

    ;
    ;

    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:wjagec:32505. 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/waeaaea.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.