Can Indirect Approaches Represent Risk Behavior Adequately?

  • Rulon D. Pope
  • Atanu Saha
Chapter
Part of the Natural Resource Management and Policy book series (NRMP, volume 23)

Abstract

In order to answer the question posed as the title to this chapter, one must have a clear picture of the relevant risk issues and the questions that need to be asked and hopefully answered. This set of economic issues involving risk in agriculture is quite broad, but we take as a typical and no doubt an easier one the supply and income response to policy changes such as the 1996 Farm Bill or policies that mitigate production uncertainty (Lin et al. 2000, Holt 1999, Goodwin and Vandeveer 2000, Ramaswami 1993). Inherent in any formal econometric indirect approach is considerable structure. Conventionally, agricultural economists have focused on static expected utility of wealth models of choice (Anderson, Dillon, and Hardaker 1977). This is not to say that behavioral anomalies (relative to expected utility maximization) are not considered important, but at this juncture, alternatives to expected utility seem to be viewed as having insufficient net benefit in most agricultural applications. Expected utility models are relatively easy to interpret and convenient to apply, yet still present many significant challenges, as will be apparent below. Further, intertemporal models of choice also are central to many if not most agricultural questions (e.g., Saha, Innes, and Pope 1993, Taylor 1984). Yet these considerations magnify the difficulties of coherently applying economic theory, and are not discussed here. In this chapter, we focus on the application of static indirect expected utility including mean-variance and conditional moment methods to agricultural risk problems. We use simple calculus tools and production uncertainty to illustrate the benefits and costs of applying risk responsive models to behavior.1

Keywords

Cost Function Risk Aversion Expected Utility Risk Preference Input Price 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Rulon D. Pope
    • 1
  • Atanu Saha
    • 1
  1. 1.Utah, and Analysis Group/EconomicsBrigham Young UniversityNew YorkUSA

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