zsfm: Zero-Inflated Stochastic Frontier Model

In sfa: Stochastic Frontier Analysis

Zero-Inflated Stochastic Frontier Model

Description

Code to use the Zero-Inflated Stochastic Frontier Model

Usage

zsfm(formula, model_name = c("ZISF", "ZISF_Z"), 
data, maxit.bobyqa = 10000,maxit.psoptim = 1000, maxit.optim = 1000, 
REPORT = 1, trace = 0, pgtol = 0,start_val = FALSE,PSopt = FALSE, 
optHessian, inefdec = TRUE, upper = NA, 
Method = "L-BFGS-B",logit = TRUE,verbose=FALSE,rand.psoptim = NULL)

Arguments

formula	a symbolic description for the model to be estimated
model_name	model name for the estimation
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.
logit	Choice of using logit function
verbose	Logical. Print optimization progress messages? Default is FALSE.
rand.psoptim	Integer. seed for replication of psoptim. Default to NULL.

Details

Example based on: A zero inefficiency stochastic frontier model, Journal of Econometrics, S. C. Kumbhakar, C. F. Parmeter and E. G. Tsionas, 2013

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 zero-inflated stochastic frontier model estimated (ZISF or ZISF_Z).
formula	The formula used in the model specification.
jlms	Predicted technical efficiency using the Jondrow et al. (1982) conditional mean estimator (JLMS).
post.prob	Posterior probabilities of being fully efficient.
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.

Note

Standard errors require optHessian set to TRUE

Author(s)

Chris F. Parmeter and David H. Bernstein

References

S. C. Kumbhakar, C. F. Parmeter and E. G. Tsionas (2013)

See Also

panel89

Examples

library(sfa)  

eqz     <- y ~ q1 + q2 + q3 + q4 + q5 + w1 + w2 + w3 + w4 | z

data(panel89)

zsfm(formula    = eqz,
     model_name = "ZISF_Z",
     data       = panel89,
     logit      = TRUE)

sfa documentation built on Jan. 22, 2026, 1:08 a.m.