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Forecasting accuracy, rational expec...

Schaefer, Matthew Phillip.

Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry./
Author:	Schaefer, Matthew Phillip.
Description:	1 online resource (96 pages)
Notes:	Source: Masters Abstracts International, Volume: 38-04, page: 8780.
Contained By:	Masters Abstracts International38-04.
Subject:	Agricultural economics. -
Online resource:	click for full text (PQDT)
ISBN:	9780599686779

Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry.
Schaefer, Matthew Phillip.

Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry. - 1 online resource (96 pages)

Source: Masters Abstracts International, Volume: 38-04, page: 8780.

Thesis (M.S.)--Michigan State University, 1999.

Includes bibliographical references

Recent studies have tested whether futures prices respond to U.S. Department of Agriculture inventory reports in accordance with the efficient market hypothesis. These studies use survey forecasts to identify the anticipated and unanticipated information contained in a report. However, this approach implicitly assumes the survey forecast to 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 the conventional analysis.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780599686779Subjects--Topical Terms:

1179138
Agricultural economics.
Index Terms--Genre/Form:

554714
Electronic books.

Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry.
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100 1 $a Schaefer, Matthew Phillip. $3 1195368
245 1 0 $a Forecasting accuracy, rational expectations, and market efficiency in the United States beef cattle industry.
264 0 $c 1999
300 $a 1 online resource (96 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 38-04, page: 8780.
502 $a Thesis (M.S.)--Michigan State University, 1999.
504 $a Includes bibliographical references
520 $a Recent studies have tested whether futures prices respond to U.S. Department of Agriculture inventory reports in accordance with the efficient market hypothesis. These studies use survey forecasts to identify the anticipated and unanticipated information contained in a report. However, this approach implicitly assumes the survey forecast to 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 the conventional analysis.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Agricultural economics. $3 1179138
655 7 $a Electronic books. $2 local $3 554714
690 $a 0503
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Michigan State University. $3 810490
773 0 $t Masters Abstracts International $g 38-04.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1398649 $z click for full text (PQDT)

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