I am using the moments-based approach to calculate the risk premium of growing a specific crop. As proposed by Chavas (Kim and Chavas,2003 and Chavas et al,2009) I used CRRA risk preference. Then incorporate moments (variance and skewness) into the equation used by Antle (1987). I got a problem as variance and skewness are in large numbers (into the power of 10^7 sometimes) the calculated risk premium is a huge number. I guessed that there is something wrong here. Can anyone suggest of a source of information of the detailed risk calculation using the moments-based approach?
You check on these article, they may provide some insights:
http://www.ucl.ac.uk/cserge/JAE.pdf
http://eprints.lse.ac.uk/37585/1/Risk_preferences_and_voluntary_agri-environmental_schemes_does_risk_aversion_explain_the_uptake_of_the_Rural_Environment_Protection_Scheme%28lsero%29.pdf
http://personal.lse.ac.uk/difalco/AJAE_Difalco.pdf
I have a suggestion. When the computer computes more than the fourth power of the variable, it produces the dragon-lattice phenomenon, the error increases, the result is not allowed.
The solution is to preprocess. Vector computations are used to calculate the value of the universal variable and the specific variable. Finally, the statistical method is used to calculate the accuracy.
You need to research closely and compare it with the researchers' ideas
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