Forecasting Accuracy, Rational Expectations And Market Efficiency In The Us Beef Cattle Industry
Recent studies have tested whether futures prices respond to U.S. Department of Agriculture inventory reports in accordance with the efficient markets hypothesis. These studies use survey forecasts to identify the anticipated and unanticipated information contained in a report. However, this approach implicitly assumes that survey forecasts be an unbiased and efficient predictor of the data in the USDA report. Furthermore, previous studies have not tested the bias and efficiency properties of USDA preliminary estimates as predictors of final revised USDA figures. This study introduces a framework for conducting tests of the efficient markets hypothesis in the presence of biased and inefficient survey forecasts, and preliminary USDA estimates that are biased and inefficient predictors of final revised figures. The approach is applied to the US beef cattle industry and results are quite different from those obtained using conventional analysis.
|Date of creation:||1999|
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- Abel, Andrew B. & Mishkin, Frederic S., 1983.
"An integrated view of tests of rationality, market efficiency and the short-run neutrality of monetary policy,"
Journal of Monetary Economics,
Elsevier, vol. 11(1), pages 3-24.
- Andrew B. Abel & Frederic S. Mishkin, 1981. "An Integrated View of Tests of Rationality, Market Efficiency, and the Short-Run Neutrality of Monetary Policy," NBER Working Papers 0726, National Bureau of Economic Research, Inc.
- Bonham, Carl S & Dacy, Douglas C, 1991. "In Search of a "Strictly Rational" Forecast," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 245-53, May.
- Tilman Ehrbeck & Robert Waldmann, 1996. "Why Are Professional Forecasters Biased? Agency versus Behavioral Explanations," The Quarterly Journal of Economics, Oxford University Press, vol. 111(1), pages 21-40.
- Cooley, Thomas F & DeCanio, Stephen J, 1977. "Rational Expectations in American Agriculture, 1867-1914," The Review of Economics and Statistics, MIT Press, vol. 59(1), pages 9-17, February.
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