frontierTranslogRay {frontier} | R Documentation |
This is a convenient interface for estimating
translog ray stochastic frontier functions
using frontier
.
frontierTranslogRay( yNames, xNames, shifterNames = NULL, zNames = NULL, data, ... )
yNames |
a vector of two character strings containing the names of the two dependent variables. |
xNames |
a vector of strings containing the names of the X variables (exogenous variables of the production or cost function) that should be included as linear, quadratic, and interaction terms. |
shifterNames |
a vector of strings containing the names of the X variables that should be included as shifters only (not in quadratic or interaction terms). |
zNames |
a vector of strings containing the names of the Z variables (variables explaining the efficiency level). |
data |
a (panel) data frame that contains the data
(see documentation of frontier )
NOTE: the variables in yNames and xNames
are logarithmized internally and hence must be in natural units,
while the variables in shifterNames and zNames
are NOT logarithmized internally and hence must be specified
as they should be used in the model. |
... |
further arguments passed to frontierQuad
and possibly further to frontier . |
frontierTranslogRay
returns a list of class frontierTranslogRay
(as well as frontierQuad
and frontier
)
containing almost the same elements as returned by frontier
.
Additionally, it includes following objects:
distance |
the “distance” from the origin (zero) to the point of the dependent variables. |
theta |
the “direction” from the origin (zero) to the point of the dependent variables. |
Arne Henningsen and Geraldine Henningsen
Löthgren, M. (1997) Generalized stochastic frontier production models, Economics Letters, 57, 255-259.
Löthgren, M. (1997) A Multiple Output Stochastic Ray Frontier Production Model, Working Paper Series in Economics and Finance, No. 158, Stockholm School of Economics.
Löthgren, M. (2000) Specification and estimation of stochastic multiple-output production and technical inefficiency Applied Economics, 32, 1533-1540.
## preparing data data( germanFarms ) # quantity of crop outputs germanFarms$qCrop <- germanFarms$vCrop / germanFarms$pOutput # quantity of animal outputs germanFarms$qAnimal <- germanFarms$vAnimal / germanFarms$pOutput # quantity of variable inputs germanFarms$qVarInput <- germanFarms$vVarInput / germanFarms$pVarInput # estimate a translog ray production function estResultRay <- frontierTranslogRay( yNames = c( "qCrop", "qAnimal" ), xNames = c( "qLabor", "land", "qVarInput" ), data = germanFarms ) summary( estResultRay )