## Stata 15 help for frontier_postestimation

```
[R] frontier postestimation -- Postestimation tools for frontier

Postestimation commands

The following postestimation commands are available after frontier:

Command            Description
-------------------------------------------------------------------------
contrast           contrasts and ANOVA-style joint tests of estimates
estat ic           Akaike's and Schwarz's Bayesian information criteria
(AIC and BIC)
estat summarize    summary statistics for the estimation sample
estat vce          variance-covariance matrix of the estimators (VCE)
hausman            Hausman's specification test
lincom             point estimates, standard errors, testing, and
inference for linear combinations of coefficients
lrtest             likelihood-ratio test
margins            marginal means, predictive margins, marginal effects,
and average marginal effects
marginsplot        graph the results from margins (profile plots,
interaction plots, etc.)
nlcom              point estimates, standard errors, testing, and
inference for nonlinear combinations of coefficients
predict            predictions, residuals, influence statistics, and
other diagnostic measures
predictnl          point estimates, standard errors, testing, and
inference for generalized predictions
pwcompare          pairwise comparisons of estimates
test               Wald tests of simple and composite linear hypotheses
testnl             Wald tests of nonlinear hypotheses
-------------------------------------------------------------------------

Syntax for predict

predict [type] newvar [if] [in] [, statistic]

predict [type] {stub*|newvar_xb newvar_v newvar_u} [if] [in] , scores

statistic          Description
-------------------------------------------------------------------------
Main
xb               linear prediction; the default
stdp             standard error of the prediction
u                estimates of minus the natural log of the technical
efficiency via E(u|e)
m                estimates of minus the natural log of the technical
efficiency via M(u|e)
te               estimates of the technical efficiency via
E{exp(-su)|e}
s =  1, for production functions
s = -1, for cost functions
-------------------------------------------------------------------------
These statistics are available both in and out of sample; type
predict...if e(sample)... if wanted only for the estimation sample.

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as linear
predictions, standard errors, and estimates of technical efficiency.

Options for predict

+------+
----+ Main +-------------------------------------------------------------

xb, the default, calculates the linear prediction.

stdp calculates the standard error of the linear prediction.

u produces estimates of minus the natural log of the technical efficiency
via E(u|e).

m produces estimates of minus the natural log of the technical efficiency
via M(u|e).

te produces estimates of the technical efficiency via E{exp(-su)|e}.

scores calculates equation-level score variables.

The first new variable will contain the derivative of the log
likelihood with respect to the regression equation.

The second new variable will contain the derivative of the log
likelihood with respect to the second equation (lnsig2v).

The third new variable will contain the derivative of the log
likelihood with respect to the third equation (lnsig2u).

Syntax for margins

margins [marginlist] [, options]

margins [marginlist] , predict(statistic ...) [options]

statistic          Description
-------------------------------------------------------------------------
xb                 linear prediction; the default
stdp               not allowed with margins
u                  not allowed with margins
m                  not allowed with margins
te                 not allowed with margins
-------------------------------------------------------------------------

Statistics not allowed with margins are functions of stochastic
quantities other than e(b).

For the full syntax, see [R] margins.

Statistics > Postestimation

Description for margins

margins estimates margins of response for linear predictions.

Examples

Setup
. webuse greene9

Fit stochastic frontier model and use capital to model the idiosyncratic
error variance
. frontier lnv lnk lnl, vhet(capital)

Estimate technical efficiency
. predict efficiency, te

Use mean of conditional error distribution to estimate minus log
efficiency
. predict mlogeffmean, u

Use mode of conditional error distribution to estimate minus log
efficiency
. predict mlogeffmode, m

```