certainty {ceRtainty}  R Documentation 
Certainty equivalent computation
certainty(data, ival, fval, utility, wealth = 0)
data 

ival 
The initial value for the RAC vector to employ (scalar). 
fval 
The final value for the RAC vector to employ (scalar). 
utility 
Indicator of utility function: "ExpNeg" for the Exponential Negative utility, and "Power" for the Power utility function. 
wealth 
The initial agent wealth. By default is zero. 
This function computes the certainty equivalent values
using profit as inputs. Works with data.frames
with 3 or
more observations. Consider each column as a different treatment
or project.
This function produces three objects: CE_values
is a table with treatment by columns and certainty values by row;
RAC
is a vector with the absolute risk aversion
coefficients (ARAC) if the Power utility function was implemented,
or the relative risk aversion coefficient (RRAC) if the
Exponential Negative utility function was implemented. The length
of this vector is the same as the number of profit observations
in the original dataset; and, CE_plot
is a graph using plot
function, to compare the different CEs computed.
Hardaker, J.B., Richardson, J.W., Lien, G., & Schumann, K.D. (2004). Stochastic efficiency analysis with risk aversion bounds: a simplified approach. Australian Journal of Agricultural and Resource Economics, 48(2), 253270.
## Example 1. Using profit data from ceRtainty package data(profitSWG) # Storing CE values using Power utility function c1 < certainty(data = profitSWG, ival = .5, fval = 4, utility = "Power") c1$CE_values # Table with CE values c1$RAC # RAC vector used in CE computation c1$CE_plot() # Invoking the CE plot # To use the ExpNeg function, it is required the RRAC (ARAC/wealth) # so we can compute the mean value among all profit in the dataset. # Mean value among all profit value mean(sapply(profitSWG,mean)) # 5081.844 # Storing CE values using Power utility function c1 < certainty(data = profitSWG, ival = .5/5082, fval = 4/5082, utility = "ExpNeg") c1$CE_values # Table with CE values c1$RAC # RAC vector used in CE computation c1$CE_plot() # Invoking the CE plot ## Example 2. Using the example values of Hardaker et al. (2004) dt < data.frame(treatment=c(100,125,135,142,147,150,153,158,163,175,195)) # Storing CE values using Power utility function. Hardaker use an # unique RAC value (0.005) c2 < certainty(data = dt, ival = .005, fval = .005, utility = "Power") # or c2 < certainty(data = dt, ival = .005, fval = .005, utility = "ExpNeg") c2$CE_values c2$RAC c2$CE_plot()