Stata 15 help for xtfrontier

[XT] xtfrontier -- Stochastic frontier models for panel data

Syntax

Time-invariant model

xtfrontier depvar [indepvars] [if] [in] [weight] , ti [ti_options]

Time-varying decay model

xtfrontier depvar [indepvars] [if] [in] [weight] , tvd [tvd_options]

ti_options Description ------------------------------------------------------------------------- Model noconstant suppress constant term ti use time-invariant model cost fit cost frontier model constraints(constraints) apply specified linear constraints collinear keep collinear variables

SE vce(vcetype) vcetype may be oim, bootstrap, or jackknife

Reporting level(#) set confidence level; default is level(95) nocnsreport do not display constraints display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Maximization maximize_options control the maximization process; seldom used

coeflegend display legend instead of statistics -------------------------------------------------------------------------

tvd_options Description ------------------------------------------------------------------------- Model noconstant suppress constant term tvd use time-varying decay model cost fit cost frontier model constraints(constraints) apply specified linear constraints collinear keep collinear variables

SE vce(vcetype) vcetype may be oim, bootstrap, or jackknife

Reporting level(#) set confidence level; default is level(95) nocnsreport do not display constraints display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Maximization maximize_options control the maximization process; seldom used

coeflegend display legend instead of statistics -------------------------------------------------------------------------

A panel variable must be specified. For xtfrontier, tvd, a time variable must also be specified. Use xtset. indepvars may contain factor variables; see fvvarlist. depvars and indepvars may contain time-series operators; see tsvarlist. by, fp, and statsby are allowed; see prefix. fweights and iweights are allowed; see weight. Weights must be constant within panel. coeflegend does not appear in the dialog box. See [XT] xtfrontier postestimation for features available after estimation.

Menu

Statistics > Longitudinal/panel data > Frontier models

Description

xtfrontier fits stochastic production or cost frontier models for panel data where the disturbance term is a mixture of an inefficiency term and the idiosyncratic error. xtfrontier can fit a time-invariant model, in which the inefficiency term is assumed to have a truncated-normal distribution, or a time-varying decay model, in which the inefficiency term is modeled as a truncated-normal random variable multiplied by a function of time.

xtfrontier expects that the dependent variable and independent variables are on the natural logarithm scale; this transformation must be performed before estimation takes place.

Options for time-invariant model

+-------+ ----+ Model +------------------------------------------------------------

noconstant; see [R] estimation options.

ti specifies that the parameters of the time-invariant technical inefficiency model be estimated.

cost specifies the frontier model be fit in terms of a cost function instead of a production function. By default, xtfrontier fits a production frontier model.

constraints(constraints), collinear; see [R] estimation options.

+----+ ----+ SE +---------------------------------------------------------------

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (oim) and that use bootstrap or jackknife methods (bootstrap, jackknife); see [XT] vce_options.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#); see [R] estimation options.

nocnsreport; see [R] estimation options.

display_options: noci, nopvalues, noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options.

+--------------+ ----+ Maximization +-----------------------------------------------------

maximize_options: difficult, technique(algorithm_spec), iterate(#), [no]log, trace, gradient, showstep, hessian, showtolerance, tolerance(#), ltolerance(#), nrtolerance(#), nonrtolerance, and from(init_specs); see [R] maximize. These options are seldom used.

The following option is available with xtfrontier but is not shown in the dialog box:

coeflegend; see [R] estimation options.

Options for time-varying decay model

+-------+ ----+ Model +------------------------------------------------------------

noconstant; see [R] estimation options.

tvd specifies that the parameters of the time-varying decay model be estimated.

cost specifies the frontier model be fit in terms of a cost function instead of a production function. By default, xtfrontier fits a production frontier model.

constraints(constraints), collinear; see [R] estimation options.

+----+ ----+ SE +---------------------------------------------------------------

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (oim) and that use bootstrap or jackknife methods (bootstrap, jackknife); see [XT] vce_options.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#); see [R] estimation options.

nocnsreport; see [R] estimation options.

display_options: noci, nopvalues, noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options.

+--------------+ ----+ Maximization +-----------------------------------------------------

maximize_options: difficult, technique(algorithm_spec), iterate(#), [no]log, trace, gradient, showstep, hessian, showtolerance, tolerance(#), ltolerance(#), nrtolerance(#), nonrtolerance, and from(init_specs); see [R] maximize. These options are seldom used.

The following option is available with xtfrontier but is not shown in the dialog box:

coeflegend; see [R] estimation options.

Examples

Setup . webuse xtfrontier1

Time-invariant model . xtfrontier lnwidgets lnmachines lnworkers, ti

Time-varying decay model . xtfrontier lnwidgets lnmachines lnworkers, tvd

Time-varying decay model with a constraint . constraint 1 [eta]_cons = 0 . xtfrontier lnwidgets lnmachines lnworkers, tvd constraints(1)

Stored results

xtfrontier stores the following in e():

Scalars e(N) number of observations e(N_g) number of groups e(k) number of parameters e(k_eq) number of equations in e(b) e(k_eq_model) number of equations in overall model test e(k_dv) number of dependent variables e(df_m) model degrees of freedom e(ll) log likelihood e(g_min) minimum number of observations per group e(g_avg) average number of observations per group e(g_max) maximum number of observations per group e(sigma2) sigma2 e(gamma) gamma e(Tcon) 1 if panels balanced, 0 otherwise e(sigma_u) standard deviation of technical inefficiency e(sigma_v) standard deviation of random error e(chi2) chi-squared e(p) p-value for model test e(rank) rank of e(V) e(ic) number of iterations e(rc) return code e(converged) 1 if converged, 0 otherwise

Macros e(cmd) xtfrontier e(cmdline) command as typed e(depvar) name of dependent variable e(ivar) variable denoting groups e(tvar) variable denoting time within groups e(function) production or cost e(model) ti, after time-invariant model; tvd, after time-varying decay model e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(chi2type) Wald; type of model chi-squared test e(vce) vcetype specified in vce() e(opt) type of optimization e(which) max or min; whether optimizer is to perform maximization or minimization e(ml_method) type of ml method e(user) name of likelihood-evaluator program e(technique) maximization technique e(properties) b V e(predict) program used to implement predict e(asbalanced) factor variables fvset as asbalanced e(asobserved) factor variables fvset as asobserved

Matrices e(b) coefficient vector e(Cns) constraints matrix e(ilog) iteration log (up to 20 iterations) e(gradient) gradient vector e(V) variance-covariance matrix of the estimators

Functions e(sample) marks estimation sample


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index