Standard and Bayesian Random Coefficient Model Estimation of US Corn–Soybean Farmer Risk Attitudes

Part of the Studies in Productivity and Efficiency book series (SIPE, volume 7)


We estimated standard and Bayesian random coefficient models (RCMs) to examine the risk attitudes of US corn–soybean farmers by revenue class using national survey data covering the 2000–2006 growing seasons. Attitudes toward risk are shown to depend on revenue class, with the magnitude of the effect being relatively small. The hypothesis of risk-neutral preferences is not rejected for small- or medium-revenue farmers but is rejected, in favor of a very slight level of risk tolerance, for large- and very large-revenue farmers and for the entire sample of farmer types. The hypothesis of downside risk neutrality is not rejected for small-revenue farmers but is rejected, in favor of a very slight level of downside risk aversion, for medium-, large-, and very large-revenue farmers. Although risk neutrality is rejected for the entire sample of farmer types, the magnitudes of our estimates of the coefficients of absolute risk aversion and absolute downside risk aversion are extremely small. This suggests that the frequent assumption of risk-neutral preferences adopted in the agricultural economics literature is justifiable for the case of US corn–soybean farmers during 2000–2006.


Posterior Distribution Annual Change Risk Attitude Risk Tolerance Farm Type 
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.


  1. Antle, J. (1983), Testing the stochastic structure of production: A flexible moment-based approach, Journal of Business & Economic Statistics 1(3): 192–201.Google Scholar
  2. Antle, J. (1987), Econometric estimation of producers’ risk attitudes, American Journal of Agricultural Economics 69(3): 509–522.CrossRefGoogle Scholar
  3. Antle, J. (1989), Nonstructural risk attitude estimation, American Journal of Agricultural Economics 71(3): 774–784.CrossRefGoogle Scholar
  4. Arrow, K. (1965), Aspects of the Theory of Risk Bearing, Yrjö Johnssonin Säätiö, Helsinki.Google Scholar
  5. Chavas, J. (2004), Risk Analysis in Theory and Practice, Elsevier, San Diego, CA.Google Scholar
  6. Chavas, J., Holt, M. (1996), Economic behavior under uncertainty: A joint analysis of risk preferences and technology, Review of Economics and Statistics 78(2): 329–335.CrossRefGoogle Scholar
  7. Gardebroek, C. (2006), Comparing risk attitudes of organic and non-organic farmers with a Bayesian random coefficient model, European Review of Agricultural Economics 33(4): 485–510.CrossRefGoogle Scholar
  8. Just, R., Pope, R. (1979), On the relationship of input decisions and risk, In J. Roumasset, J.-M. Boussard, I. Singh (eds.), Risk, Uncertainty and Agricultural Development, Agricultural Development Council, New York, NY, 177–197.Google Scholar
  9. Just, R., Pope, R. (2002), A Comprehensive Assessment of the Role of Risk in U.S. Agriculture, Kluwer, Norwell.Google Scholar
  10. Koop, G. (2003), Bayesian Econometrics, Wiley, Chichester.Google Scholar
  11. Pennings, J., Smidts, A. (2000), Assessing the construct validity of risk attitude, Management Science, 46(10), 1337–1348.CrossRefGoogle Scholar
  12. Pratt, J. (1964), Risk aversion in the small and in the large, Econometrica 32(1–2): 122–136.CrossRefGoogle Scholar
  13. Roumasset, J., Boussard, J.-M., Singh, I., eds. (1979), Risk, Uncertainty and Agricultural Development, Agricultural Development Council, New York, NY.Google Scholar
  14. Swamy, P. (1970), Efficient inference in a random coefficient regression model, Econometrica 38(2): 311–323.CrossRefGoogle Scholar
  15. Swamy, P. (1971), Statistics Inference in Random Coefficient Regression Models, Springer, New York, NY.CrossRefGoogle Scholar
  16. U.S. Department of Agriculture, National Agricultural Statistics Service (USDA-NASS). (1996–2007), Agricultural Prices Summary, USDA-NASS, Washington, DC.Google Scholar
  17. U.S. Department of Agriculture, National Agricultural Statistics Service (USDA-NASS). (2005), Agricultural Statistics 2005, U.S. Government Printing Office, Washington, DC.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Michael Livingston
    • 1
  • Ken Erickson
    • 1
  • Ashok Mishra
    • 2
  1. 1.US Department of AgricultureEconomic Research ServiceWashingtonUSA
  2. 2.Department of Agricultural Economics and AgribusinessLouisiana State UniversityBaton RougeUSA

Personalised recommendations