Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-25T06:00:30.489Z Has data issue: false hasContentIssue false
  • English
  • Français

Rationality of U.S. Department of Agriculture Livestock Price Forecasts: A Unified Approach

Published online by Cambridge University Press:  28 April 2015

Dwight R. Sanders  and
Mark R. Manfredo
Dwight R. Sanders
Affiliation:
Department of Agribusiness Economics, Southern Illinois University, Carbondale, IL
Mark R. Manfredo
Affiliation:
Morrison School of Agribusiness and Resource Management, Arizona State University, Mesa, AZ
Get access Rights & Permissions [Opens in a new window]

Abstract

This research presents a systematic and unified approach to evaluating forecast rationality that considers the potential of nonstationarity in forecasts and realized values. The approach is applied to one-quarter ahead U.S. Department of Agriculture livestock price forecasts from 1982 through 2004. Results show that forecasts and realized prices are integrated of the same order, and those that are nonstationary are cointegrated. However, the stationary price forecasts for hogs, turkeys, eggs, and milk are biased and improperly scaled, and forecast errors tend to be repeated. Similarly, nonstationary forecasts for cattle and broilers are also biased and irrational in the long run, but short-run dynamics are rational.

Keywords

forecast evaluationlivestock pricesrationalityC53Q13
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 39 , Issue 1 , April 2007 , pp. 75 - 85
Copyright
Copyright © Southern Agricultural Economics Association 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggarwal, R., Mohanty, S., and Song, F.. “Are Survey Forecasts of Macroeconomic Variables Rational?” Journal of Business 68(1995):99–119.CrossRefGoogle Scholar
Balke, N.S., and Fomby, B.. “Threshold Cointegration.” International Economic Review 38(1997):627–45.CrossRefGoogle Scholar
Cheung, Y.W., and Chinn, M.D.. “Integration, Cointegration and the Forecast Consistency of Structural Exchange Rate Models.” Journal of International Money and Finance 17(1998):813–30.CrossRefGoogle Scholar
Dequan, H., and Holt, M.. “Efficiency of Forest Commodity Futures.” Paper presented at the American Agricultural Economics Association Annual Meeting, Denver, Colorado, August 1-4, 2004.Google Scholar
Elam, E.W., and Holder, S.H.. “An Evaluation of the Rice Outlook and Situation Price Forecasts.” Southern Journal of Agricultural Economics 17(1985):155–61.Google Scholar
Enders, W.Applied Econometric Time Series. New York: John Wiley & Sons, 1995.Google Scholar
Granger, C.W.J.and Newbold, P.. Forecasting Economic Time Series. New York: Academic Press, 1986.Google Scholar
Grant, A.P., and Thomas, L.B.. “Inflationary Expectations and Rationality Revisited.” Economics Letters 62(1999):331–38.CrossRefGoogle Scholar
Green, J. Personal Communication, Livestock, Dairy, and Poultry Analyst, World Agricultural Outlook Board, USDA, March 2006.Google Scholar
Kastens, T.L., Schroeder, T.C., and Plain, R.. “Evaluation of Extension and USDA Price and Production Forecasts.” Journal of Agricultural and Resource Economics 23(1998):244–61.Google Scholar
Kwiatkowski, D., Phillips, P.C., Schmidt, P., and Shin, Y.. “Testing the Null Hypothesis of Statio-narity against the Alternative of a Unit Root.” Journal of Econometrics 54(1992):159–78.CrossRefGoogle Scholar
McKenzie, A.M., and Holt, M.T.. “Market Efficiency in Agricultural Futures Markets.” Applied Economics 34(2002):1519–32.CrossRefGoogle Scholar
McKenzie, A.M., Jiang, B., Djundaidi, H., Hoffman, L., and Wailes, E.. “Unbiasedness and Market Efficiency Tests of the U. S. Rice Futures Market.” Review of Agricultural Economics 24(2002):474–93.CrossRefGoogle Scholar
Pindyck, R.S., and Rubinfeld, D.L.. Econometric Models and Economic Forecasts. New York: Irwin/McGraw-Hill, 1998.Google Scholar
Pons, J. “The Accuracy of IMF and OECD Forecasts for G7 Countries.” Journal of Forecasting 19(2000):53–63.3.0.CO;2-J>CrossRefGoogle Scholar
Pons, J. “The Rationality of Price Forecasts: A Directional Analysis.” Applied Financial Economics 11(2001):287–90.CrossRefGoogle Scholar
Rapach, D.E. “The Long-Run Relationship between Inflation and Real Stock Prices.” Journal of Macroeconomics 24(2002):331–51.CrossRefGoogle Scholar
Sanders, D.R., and Manfredo, M.R.. “USDA Livestock Price Forecasts: A Comprehensive Evaluation.” Journal of Agricultural and Resource Economics 28(2003):316–34.Google Scholar
SHAZAM. User's Reference Manual Version 7.0. New York: McGraw-Hill, 1993.Google Scholar
Wang, P., and Jones, T.. “Testing for Efficiency and Rationality in Foreign Exchange Markets—A Review of the Literature and Research on Foreign Exchange Market Efficiency and Rationality with Comments.” Journal of International Money and Finance 21(2002):223–39.CrossRefGoogle Scholar
Yang, J., and Leatham, D.J.. “Market Efficiency of U. S. Grain Markets: Application of Cointegration Tests.” Agribusiness: An International Journal 14(1998):107–12.3.0.CO;2-6>CrossRefGoogle Scholar
Zivot, E. “Cointegration and Forward and Spot Exchange Rate Regressions.” Journal of International Money and Finance 19(2000):785–812.CrossRefGoogle Scholar
Zulauf, CR., Irwin, S.H., Ropp, J.E., and Sberna, A.J.. “A Reappraisal of the Forecasting Performance of Corn and Soybean New Crop Futures.” Journal of Futures Markets 19(1999):603–18.3.0.CO;2-U>CrossRefGoogle Scholar