Title
[R] frontier -- Stochastic frontier models
Syntax
frontier depvar [indepvars] [if] [in] [weight] [, options]
options Description
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Model
noconstant suppress constant term
distribution(hnormal) half-normal distribution for the inefficiency term
distribution(exponential) exponential distribution for the inefficiency term
distribution(tnormal) truncated-normal distribution for the inefficiency term
ufrom(matrix) specify untransformed log likelihood; only with d(tnormal)
cm(varlist[, noconstant]) fit conditional mean model; only with d(tnormal); use
noconstant to suppress constant term
Model 2
constraints(constraints) apply specified linear constraints
collinear keep collinear variables
uhet(varlist[, noconstant]) explanatory variables for technical inefficiency variance
function; use noconstant to suppress constant term
vhet(varlist[, noconstant]) explanatory variables for idiosyncratic error variance
function; use noconstant to suppress constant term
cost fit cost frontier model; default is production frontier
model
SE
vce(vcetype) vcetype may be oim, opg, bootstrap, or jackknife
Reporting
level(#) set confidence level; default is level(95)
nocnsreport do not display constraints
display_options control column formats, row spacing, line width, and display
of omitted variables and base and empty cells
Maximization
maximize_options control the maximization process; seldom used
coeflegend display legend instead of statistics
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indepvars and varlist may contain factor variables; see fvvarlist.
bootstrap, by, jackknife, rolling, and statsby are allowed; see prefix.
Weights are not allowed with the bootstrap prefix.
fweights, iweights, and pweights are allowed; see weight.
coeflegend does not appear in the dialog box.
See [R] frontier postestimation for features available after estimation.
Menu
Statistics > Linear models and related > Frontier models
Description
frontier fits stochastic production or cost frontier models; the default is a production
frontier model. It provides estimators for the parameters of a linear model with a
disturbance that is assumed to be a mixture of two components, which have a strictly
nonnegative and symmetric distribution, respectively. frontier can fit models in which the
nonnegative distribution component (a measurement of inefficiency) is assumed to be from a
half-normal, exponential, or truncated-normal distribution. See Kumbhakar and Lovell (2000)
for a detailed introduction to frontier analysis.
Examples
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Setup
. webuse greene9
Cobb-Douglas production function with half-normal distribution for inefficiency term
. frontier lnv lnk lnl
Cobb-Douglas production function with exponential distribution for inefficiency term
. frontier lnv lnk lnl, dist(exponential)
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Setup
. webuse frontier1
Cobb-Douglas production function with size as explanatory variable in variance function for
idiosyncratic error
. frontier lnoutput lnlabor lncapital, vhet(size)
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Setup
. webuse frontier2
Cost frontier model with truncated-normal distribution for inefficiency term
. frontier lncost lnp_k lnp_l lnout, dist(tnormal) cost
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