Positive Mathematical Programming with Generalized Risk
Quirino Paris
No 181605, Working Papers from University of California, Davis, Department of Agricultural and Resource Economics
Abstract:
Price risk in a mathematical programming framework has been confined for a long time to a constant risk aversion specification originally introduced by Freund in 1956. This paper extends the treatment of risk in a mathematical programming framework along the lines suggested by Meyer (1987) who demonstrated the equivalence of expected utility and a wide class of probability distributions that differ only by location and scale. This paper shows how to formulate a PMP specification that allows the estimation of the preference parameters and calibrates the model to the base data within an admissible small deviation. The PMP approach under generalized risk allows also the estimation of output supply elasticities. The approach is applied to a sample of large farms.
Keywords: Productivity Analysis; Research Methods/Statistical Methods; Risk and Uncertainty (search for similar items in EconPapers)
Pages: 27
Date: 2014-04-01
New Economics Papers: this item is included in nep-ore and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://ageconsearch.umn.edu/record/181605/files/14-004.pdf (application/pdf)
Related works:
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:ucdavw:181605
DOI: 10.22004/ag.econ.181605
Access Statistics for this paper
More papers in Working Papers from University of California, Davis, Department of Agricultural and Resource Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().