frontierQuad {frontier} | R Documentation |
This is a convenient interface for estimating
quadratic or translog stochastic frontier functions
using frontier
.
frontierQuad( yName, xNames, shifterNames = NULL, zNames = NULL, data, lrTests = FALSE, ... )
yName |
string: name of the endogenous variable. |
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;
if |
lrTests |
logical. If |
... |
further arguments passed to |
frontierQuad
returns a list of class frontierQuad
(and frontier
)
containing the same elements as returned by frontier
.
If argument lrTest
is set to TRUE
,
the returned object has a component lrTests
that contains the results of likelihood-ratio tests
of the statistical significance of each X variable.
Arne Henningsen
# example included in FRONTIER 4.1 (cross-section data) data( front41Data ) front41Data$logOutput <- log( front41Data$output ) front41Data$logCapital <- log( front41Data$capital ) front41Data$logLabour <- log( front41Data$labour ) # estimate the translog function translog <- frontierQuad( yName = "logOutput", xNames = c( "logCapital", "logLabour" ), data = front41Data ) translog # estimate the same model using sfa() translog2 <- sfa( logOutput ~ logCapital + logLabour + I( 0.5 * logCapital^2 ) + I( logCapital * logLabour ) + I( 0.5 * logLabour^2 ), data = front41Data ) translog2 all.equal( coef( translog ), coef( translog2 ), check.attributes = FALSE )