An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah

The major purpose of this study is to present selected empirical results of a study employing decision-making theory as a framework for considering decision making under risk. The part icular problem involves choices between alternative crop rotations for Sevier County farmers. The study demonstrate...

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Main Author: Lakawathana, Suwaphot
Format: Others
Published: DigitalCommons@USU 1970
Subjects:
Online Access:https://digitalcommons.usu.edu/etd/2927
https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=3939&context=etd
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spelling ndltd-UTAHS-oai-digitalcommons.usu.edu-etd-39392019-10-13T06:01:22Z An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah Lakawathana, Suwaphot The major purpose of this study is to present selected empirical results of a study employing decision-making theory as a framework for considering decision making under risk. The part icular problem involves choices between alternative crop rotations for Sevier County farmers. The study demonstrates the usefulness of the Bayesian theory that gives more than a point estimation. A multiple regression mod e l using two linear terms was employed to determine the influence of s now pack and reservoir storage on water availability for irrigation purposes during July, August , and September. The Bayesian approach was employed. The optima l action or decision was first determined where only the knowledge of the~ priori probabiities of the states of nature was available. Optimal strategies were then determined where run-off observation was available and the~ poster iori probabilities of the states of nature were determined. Study results indicate that the expected va lue of the additional information is substantial and come out very close to the expected value of a perfect predictor and higher than the expected value of t he "no data" problems . It means that the Bayesian approach gives more than a point estimation a nd is us eful for farm management decision making under risk. 1970-05-01T07:00:00Z text application/pdf https://digitalcommons.usu.edu/etd/2927 https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=3939&context=etd Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu). All Graduate Theses and Dissertations DigitalCommons@USU Statistical Decision Theory Farm Management Sevier County Utah Agricultural Economics
collection NDLTD
format Others
sources NDLTD
topic Statistical Decision Theory
Farm Management
Sevier County
Utah
Agricultural Economics
spellingShingle Statistical Decision Theory
Farm Management
Sevier County
Utah
Agricultural Economics
Lakawathana, Suwaphot
An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
description The major purpose of this study is to present selected empirical results of a study employing decision-making theory as a framework for considering decision making under risk. The part icular problem involves choices between alternative crop rotations for Sevier County farmers. The study demonstrates the usefulness of the Bayesian theory that gives more than a point estimation. A multiple regression mod e l using two linear terms was employed to determine the influence of s now pack and reservoir storage on water availability for irrigation purposes during July, August , and September. The Bayesian approach was employed. The optima l action or decision was first determined where only the knowledge of the~ priori probabiities of the states of nature was available. Optimal strategies were then determined where run-off observation was available and the~ poster iori probabilities of the states of nature were determined. Study results indicate that the expected va lue of the additional information is substantial and come out very close to the expected value of a perfect predictor and higher than the expected value of t he "no data" problems . It means that the Bayesian approach gives more than a point estimation a nd is us eful for farm management decision making under risk.
author Lakawathana, Suwaphot
author_facet Lakawathana, Suwaphot
author_sort Lakawathana, Suwaphot
title An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
title_short An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
title_full An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
title_fullStr An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
title_full_unstemmed An Application of Statistical Decision Theory to Farm Management in Sevier County, Utah
title_sort application of statistical decision theory to farm management in sevier county, utah
publisher DigitalCommons@USU
publishDate 1970
url https://digitalcommons.usu.edu/etd/2927
https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=3939&context=etd
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