Wednesday, November 7, 2007 - 9:35 AM
243-1

Using Multivariate Stochastic Dominance for Empirical Evaluation of Water Quality Tradeoffs at the Farm Level.

Eihab Fathelrahman1, James C. Ascough II2, Dana Hoag3, Ramesh Kanwar4, Robert Malone5, Philip Heilman6, and Liwang Ma2. (1) USDA-ARS-NPA, Agricultural Systems Research Unit, 2150 Centre Ave., Bldg. D., Suite 200, Fort Collins, CO 80526, (2) USDA-ARS-NPA, Agricultural Systems Research Unit, 2150 Centre Ave., Bldg. D, Suite 200, Fort Collins, CO 80526, (3) Dept. Agriculture and Resource Economics, Colorado State University, B330 Clark Building, Fort Collins, CO 80523, (4) Agricultural and Biosystems Engineering, Iowa State University, 104 Davidson Hall, Ames, IA 50011, (5) USDA-ARS National Soil Tilth Laboratory, USDA-ARS, 2150 Pammel Drive, Ames, IA 50011, (6) Southwest Watershed Research Center, USDA-ARS, 2000 East Allen Road, Tucson, AZ 85704

Profit-maximizing producers use pesticides such Atrazine, Alachlor, and Metachlor to protect their crops against yield losses caused by competition from weeds and insects. Since the extent of pest damage varies from year-to-year according to uncertain factors like weather and pest population dynamics, pest management is essentially risk management. Risk-averse producers view pesticides as an insurance policy. Excess pesticide residues are prone to surface runoff or leaching to ground water - a recent USGS survey of water streams in the U.S. showed that pesticides were detected in one or more water samples from every stream system sampled. The objective of this study is to analyze the tradeoffs between the economics of corn and soybean production on one hand, and the combined ecological effect of pesticide application and fate on the other. Our presentation is divided into four sections. In the first section we describe multivariate stochastic dominance (MVSD), an analytical approach appropriate for multidimensional risk management problems. The second section includes procedural steps to compare private profit of the farm against simulated societal profit. Societal profit is farm profit adjusted for the (negative) pesticide externality value. We based the data analysis on economic budgeting and pesticide concentration in the soil profile data collected from 1994 to 2003 on 36 experimental plots at the Northeastern Research Farm in Nashua, IA. The third section outlines the application of the MVSD approach to analyze the tradeoffs between private profit at the farm level and simulated distributions of societal profit that considers potential damage to groundwater quality at the farm level. The last section includes a discussion of the challenges and possibilities involving creation of a reduced empirical model using MVSD as a tool for the tradeoff analyses. Finally, we also discuss the policy implications from this exercise.