Chance Constrained Programming Models for Risk-Based Economic and Policy Analysis of Soil Conservation

Minkang Zhu, Daniel B. Taylor, Subhash C. Sarin and Randall Kramer ()
Additional contact information
Minkang Zhu: Virginia Polytechnic Institute and State University
Daniel B. Taylor: Virginia Polytechnic Institute and State University
Subhash C. Sarin: Virginia Polytechnic Institute and State University

Agricultural and Resource Economics Review, 1994, vol. 23, issue 1, pages 58-65

Abstract: The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models can provide information on the trade-offs among pre-deterrnined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.

Date: 1994

Downloads: (external link)
http://agecon.lib.umn.edu/cgi-bin/pdf_view.pl?paperid=5930&ftype=.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this article

More articles in Agricultural and Resource Economics Review from Northeastern Agricultural and Resource Economics Association
Contact information at EDIRC.
Series data maintained by David R. Just ().