sfm: sfm

In davidhbernstein/sfm: Stochastic Frontier Models

sfm

Description

Cross-sectional stochastic frontier models are estimated with the sfm() call. For panel models, see the psfm() call.

Usage

sfm(formula, model_name = c("NHN", "NHN_Z", "NE", "NE_Z", "THT", "NTN", "NR"), data, maxit.bobyqa = 10000, maxit.psoptim = 1000, maxit.optim = 1000, REPORT = 1, trace = 2, pgtol = 0, start_val = FALSE, PSopt = FALSE, bob = TRUE, optHessian = TRUE, inefdec = TRUE, upper = NA, Method = "L-BFGS-B")

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/F)
bob	use bobyqa optimization routine (T/F)
optHessian	Logical. Should a numerically differentiated Hessian matrix be returned? (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.

Note

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.

Author(s)

David Bernstein

References

NA

Examples

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)

cs.nez      <-  sfm(formula    = y_pcs_z ~ x1 +x2| z,    model_name = "NE",                 
                    data       = cs_data_trial,          PSopt      = TRUE)

cs.nhn       <- sfm(formula    = y_pcs ~ x1 +x2,         model_name = "NHN", 
                    data       = cs_data_trial,          PSopt      = TRUE)

cs.ne        <- sfm(formula    = y_pcs_e ~ x1 +x2,       model_name = "NE", 
                    data       = cs_data_trial)

davidhbernstein/sfm documentation built on Feb. 28, 2025, 1:17 a.m.