A BAYESIAN FRAMEWORK FOR OPTIMAL INPUT ALLOCATION WITH AN UNCERTAIN STOCHASTIC PRODUCTION FUNCTION

William Griffiths ()

Australian Journal of Agricultural Economics, 1986, vol. 30, issue 2-3, 25

Abstract: A Bayesian approach is used to provide a framework for optimal input allocation for a stochastic production function with uncertain parameters. The chosen production function is a single-input version of a function which can exhibit positive or negative marginal risk. The sensitivity of optimal input allocation to the degree of risk aversion, the marginal risk parameter, and the assumed level of uncertainty about the parameters is examined. Using an example problem it is shown that parameter uncertainty will not always lead to a lower input level when a producer is risk averse. Some problems with the production function specification are uncovered, as is the incompatibility of some expected utility and stochastic assumptions.

Keywords: Research Methods/ Statistical Methods; Risk and Uncertainty (search for similar items in EconPapers)
Date: 1986
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://ageconsearch.umn.edu/record/22898/files/30020128.pdf (application/pdf)

Related works:
Journal Article: A BAYESIAN FRAMEWORK FOR OPTIMAL INPUT ALLOCATION WITH AN UNCERTAIN STOCHASTIC PRODUCTION FUNCTION (1986)
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:ags:ajaeau:22898

DOI: 10.22004/ag.econ.22898

Access Statistics for this article

More articles in Australian Journal of Agricultural Economics from Australian Agricultural and Resource Economics Society Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().