efficiencies.semsfa {semsfa} | R Documentation |
Prediction of the individual efficiency score
Description
This function calculates and returns efficiency estimates from semiparametric stochastic frontier models estimated with semsfa()
.
Usage
efficiencies.semsfa(semobj, log.output = TRUE, ...)
Arguments
semobj |
a stochastic frontier model object returned by |
log.output |
logical. Is the dependent variable logged? |
... |
further arguments to the summary method are currently ignored |
Details
The estimation of the individual efficiency score for a particular point (x,y)
on a production frontier might be obtained from the Jondrow et al. (1982) procedure. Defining:
\sigma^2=\sigma_u^2+\sigma_v^2, u_{*}(x) = -\sigma_u^2 \epsilon/\sigma^2, \sigma_{*}^2=\sigma_u^2 \sigma_v^2/\sigma^2
it can be shown that:
u|\epsilon ~ N^+(\mu_{*}(x),\sigma_{*}^{2}(x)).
We can use this distribution to obtain point previsions of u
trought the mean of the conditional distribution:
E(u|\epsilon)=\mu_{*} + \sigma_{*} f(-\mu_{*}/\sigma_{*})/(1-F(\mu_{*}/\sigma_{*}))
where f
and F
represent the standard Normal density and cumulative distribution function, respectively; alternative formulas for cost frontier models are easy to get (please see Kumbhakar and Lovell, 2000).
If the response variable is measured in logs, a point estimate of the efficiency is then provided by \exp(-u) \in (0,1)
; otherwise, (fitt-u)/fitt
where fitt
is the estimated output evaluated at the frontier, given the inputs.
Value
An object of class semsfa
containing the following additional results:
u |
the prediction of the individual efficiency score |
efficiencies |
point estimate of the efficiency |
Author(s)
Giancarlo Ferrara and Francesco Vidoli
References
Jondrow, J., Lovell, C.A.K., Materov, I.S., Schmidt, P., 1982. On the estimation of technical inefficiency in stochastic frontier production models. Journal of Econometrics 19, 233-238.
Kumbhakar, S.C., Lovell, C.A.K., 2000. Stochastic Frontier Analysis. Cambridge University Press, New York.
See Also
semsfa
, summary.semsfa
, plot.semsfa
.
Examples
set.seed(0)
n<-200
#generate data
x<- runif(n, 1, 2)
fy<- 2+30*x-5*x^2
v<- rnorm(n, 0, 1)
u<- abs(rnorm(n,0,2.5))
#production frontier
y <- fy + v - u
dati<-data.frame(y,x)
#first-step: gam, second-step: fan (default)
o<-semsfa(y~s(x),dati,sem.method="gam")
#calculate efficiencies
a<-efficiencies.semsfa(o)