sfa (version 1.0.4)

sfm: sfm

Description

Implementation of the cross-sectional stochastic frontier model across an array of distributional assumptions for both v and u (user specified). For panel models, see the psfm() call.

Usage

sfm(formula, model_name, data,maxit.bobyqa,maxit.psoptim,maxit.optim,REPORT,
trace,pgtol,start_val,PSopt,optHessian,inefdec,upper,Method,eta,alpha,verbose=FALSE,
rand.psoptim=NULL)

Value

An object of class "sfareg" containing the following components:

out

A matrix with parameter estimates, standard errors, and t-values.

opt

A list containing the optimization results from the final optimization procedure.

total_time

The total computation time for model estimation.

start_v

The starting values used in the optimization.

model_name

The name of the stochastic frontier model estimated.

formula

The formula used in the model specification.

exp_u_hat

Predicted technical efficiency (expected values). Available for models: NHN, NHN_Z, NR, NG, and NNAK.

med_u_hat

Predicted technical efficiency (median values). Available only for the NHN model.

coefficients

A vector of estimated parameters.

std.errors

A vector of standard errors for the estimated parameters (NA if optHessian = FALSE).

t.values

A vector of t-values for the estimated parameters (NA if optHessian = FALSE).

call

The matched call.

Arguments

formula

a symbolic description for the model to be estimated

model_name

model name for the estimation includes the: normal-half normal (NHN), normal-exponential (NE), student's t-half t (THT), Normal-Rayleigh (NR), and the normal-truncated normal (NTN).

data

A data set

maxit.bobyqa

Maximum number of iterations for the bobyqa optimization routine

maxit.psoptim

Maximum number of iterations for the psoptim optimization routine

maxit.optim

Maximum number of iterations for the optim optimization routine

REPORT

reporting parameter

trace

trace

pgtol

pgtol

start_val

starting value (optional)

PSopt

use psoptim optimization routine (T or F)

optHessian

Logical. Should a numerically differentiated Hessian matrix be returned while using the optim routine? (for optim routine)

inefdec

Production or cost function

upper

Vector of upper values for the optim package.

Method

The method to be used for optim. See 'Details' within optim.

eta

Parameter used for psi-divergence.

alpha

Parameter used for MDPD.

verbose

Logical. Print optimization progress messages? Default is FALSE.

rand.psoptim

Integer. seed for replication of psoptim. Default to NULL.

Author

David H. Bernstein and Alexander Stead

Details

The options include the Normal-Half Normal (NHN), Normal-exponential (NE), Student's t-Half t (THT), and the Normal-Truncated Normal (NTN). NHN_Z and NE_Z are extensions for the NHN and NE models that allow for modeling the u-component of those models with determinants of inefficiency.

Outputs include E[exp(-u)|e] given by exp_u_hat, following Battese and Coelli (1988, JoE), where appropriate.

See Also

see also

Examples

# \donttest{
library(sfa)     

cs_data_trial   <- data_gen_cs(N= 1000, rand   = 1,  sig_u  = 0.3, sig_v  = 0.3, 
cons   = 0.5,       beta1  = 0.5,   beta2  = 0.5, a      = 4, mu     = 1)

cs.nhnz     <-  sfm(formula    = y_pcs_z ~ x1 +x2| z,    model_name = "NHN",                  
                    data       = cs_data_trial,          PSopt      = TRUE)
# }