Risk Response Models and Their Use in Agricultural Policy Evaluation

The previous two papers have discussed the possible effects that proposed public policy may have on risk and uncertainty in the ag-ricultural economic environment. According-ly, I will argue that, before we can adequately evaluate policies which create new degrees of risk for agricultural producers, we must have better quantitative knowledge of how farmers will respond to changing risk in adjusting input and production decisions. I will then consider models for estimation of the effects of chang-ing risk in agricultural supply response. Response by decision makers to changes in risk has long been recognized as an important economic phenomenon. The study of decision makers ' behavior toward risk began to be popularized as early as 1948 with the work of Friedman and Savage and later by the work of Markowitz and Tobin. Many agricultural ex-periment stations began during the mid-1950s to evaluate the risk associated with various agricultural enterprises (Heady, Kehrberg, and Jebe; Carter and Dean). These studies have freely acknowledged the importance of both price and production-related risk in de-termining agricultural input decisions and, hence, output. With increased interest in risk, research has centered on stochastic program-ming models and nonlinear objective criteria (indicative of utility maximization) which could be used to determine optimal reactions to changing risk. But while much work has been undertaken to determine the risk in-volved in farm decisions and how farmers should react to changing risk, it is my conten-tion that the implications of risk for positive response studies have been seriously ne-glected. In fact, the effects of risk on optimal input decisions have been examined through norma-tive programming approaches (e.g. Freund) Richard E. Just is an assistant professor of agricultural and re-source economics at the University of California-Berkeley.