The Bayesian Decision Model with more than One Predictor—An Application to the Stocking Rate Problem

Freddie C. White and Vernon Eidman

Journal of Agricultural and Applied Economics, 1971, vol. 3, issue 1, 95-102

Abstract: The variables a manager faces in making decisions may be divided into two broad categories—those which are determined by the manager and those which are outside of his control. Agricultural economists have made many efforts to develop expectation models for one or more of the uncontrollable variables facing farmers and have suggested procedures for utilizing the resulting expectations. Recent developments in statistical decision theory provide a logically consistent framework for incorporating the predictions of expectation models [4, pp. 192-196]. Applications of Bayesian analysis utilizing predictions of one uncontrollable variable have been reported in the literature [1, 3]. However, many decision problems logically require expectations of two uncontrollable variables (such as price and yield) or more. This article illustrates a method of including predictors for more than one uncontrollable variable in the Bayesian framework, and reports some empirical results of an application to a stocking rate problem.

Date: 1971
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)

Related works:
Journal Article: THE BAYESIAN DECISION MODEL WITH MORE THAN ONE PREDICTOR--AN APPLICATION TO THE STOCKING RATE PROBLEM (1971)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cup:jagaec:v:3:y:1971:i:01:p:95-102_01

Access Statistics for this article

More articles in Journal of Agricultural and Applied Economics from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().