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

  • Minkang Zhu (a1), Daniel B. Taylor (a1), Subhash C. Sarin (a2) and Randall A. Kramer (a3)

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-determined 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.

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