Economic Risk Analysis of Agricultural Tillage Systems Using the SMART Stochastic Efficiency Software Package

Authors: Ascough Ii, James; FATHELRAHMAN, EIHAB - Colorado State University; Vandenberg, Bruce; Green, Timothy; HOAG, DANA - Colorado State University

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/2/2009
Publication Date: 7/24/2009
Citation: Ascough II, J.C., Fathelrahman, E.M., Vandenberg, B.C., Green, T.R., Hoag, D.L. 2009. Economic Risk Analysis of Agricultural Tillage Systems Using the SMART Stochastic Efficiency Software Package. World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. p. 463-469.

Interpretive Summary: The Screening and Multivariate Analysis for Risk and Tradeoffs (SMART) software package (both web-based and MS Excel spreadsheet applications) has been developed for integrated economic and environmental risk analysis through ranking of risky alternatives using the CE and SERF concepts. The SMART software also functions as a risk visualization tool for graphically displaying the CEs at various levels of decision maker attitude towards risk (e.g., risk neutral, moderately risk averse, or extremely risk averse). This paper provides a brief overview of the SMART risk analysis framework, and then describes use of the web-based tool to evaluate the efficacy of the SERF methodology for analyzing conventional and conservation tillage systems using 14 years (1990-2003) of economic budget data (collected from 36 experimental plots at the Iowa State University Northeast Research Station near Nashua, Iowa, USA). Specifically, the SERF approach implemented in SMART is used to examine which of three different tillage systems (chisel plow, no-till, and ridge-till) on continuous corn and corn-soybean rotation cropping systems are the most risk-efficient in terms of maximizing economic profitability (net return) across a range of risk aversion preferences. In addition to the SERF analysis, an economic analysis of the tillage system alternatives is also performed using decision criteria and simple statistical measures. Finally, we demonstrate the use of a complementary method, the probability of target value or Stop Light approach, for analyzing and visually displaying the probabilistic information contained in the tillage system cumulative density functions (CDFs). Decision criteria analysis of the economic measures alone provided somewhat contradictive and non-conclusive rankings, e.g., examination of the decision criteria results for corn net return showed that different tillage system alternatives were the highest ranked depending on the decision criterion. SERF analysis results for corn net return showed that the no-till tillage system was preferred across the entire range of risk aversion (risk neutral to strongly risk averse). For the Stop Light analysis, the no-till tillage system was also preferred, regardless of whether the objective of the decision maker is minimizing risk or maximizing net return.

Technical Abstract: Recently, a variant of stochastic dominance called stochastic efficiency with respect to a function (SERF) has been developed and applied. Unlike traditional stochastic dominance approaches, SERF uses the concept of certainty equivalents (CEs) to rank a set of risk-efficient alternatives instead of finding a subset of dominated alternatives. The Screening and Multivariate Analysis for Risk and Tradeoffs (SMART) software package (both web-based and MS Excel spreadsheet applications) has been developed for integrated economic and environmental risk analysis through ranking of risky alternatives using the CE and SERF concepts. The SMART software also functions as a risk visualization tool for graphically displaying the CEs at various levels of decision maker attitude towards risk (e.g., risk neutral, moderately risk averse, or extremely risk averse). This paper provides a brief overview of the SMART risk analysis framework, and then describes use of the web-based tool to evaluate the efficacy of the SERF methodology for analyzing conventional and conservation tillage systems using 14 years (1990-2003) of economic budget data (collected from 36 experimental plots at the Iowa State University Northeast Research Station near Nashua, Iowa, USA). Specifically, the SERF approach implemented in SMART is used to examine which of three different tillage systems (chisel plow, no-till, and ridge-till) on continuous corn and corn-soybean rotation cropping systems are the most risk-efficient in terms of maximizing economic profitability (net return) across a range of risk aversion preferences. In addition to the SERF analysis, an economic analysis of the tillage system alternatives is also performed using decision criteria and simple statistical measures. Finally, we demonstrate the use of a complementary method, the probability of target value or Stop Light approach, for analyzing and visually displaying the probabilistic information contained in the tillage system cumulative density functions (CDFs). Decision criteria analysis of the economic measures alone provided somewhat contradictive and non-conclusive rankings, e.g., examination of the decision criteria results for corn net return showed that different tillage system alternatives were the highest ranked depending on the decision criterion. SERF analysis results for corn net return showed that the no-till tillage system was preferred across the entire range of risk aversion (risk neutral to strongly risk averse). For the Stop Light analysis, the no-till tillage system was also preferred, regardless of whether the objective of the decision maker is minimizing risk or maximizing net return.