Copula-Based Stochastic Frontier Models

Provides estimation procedures for copula-based stochastic frontier models for cross-sectional data. The package implements maximum likelihood estimation of stochastic frontier models allowing flexible dependence structures between inefficiency and noise terms through various copula families (e.g., Gaussian and Student-t). It enables estimation of technical efficiency scores, log-likelihood values, and information criteria (AIC and BIC). The implemented framework builds upon stochastic frontier analysis introduced by Aigner, Lovell and Schmidt (1977) and the copula theory described in Joe (2014, ISBN:9781466583221). Empirical applications of copula-based stochastic frontier models can be found in Wiboonpongse et al. (2015) and Maneejuk et al. (2017, ISBN:9783319562176).

copulaSFM

#To install this package, you have to install devtools package

library(devtools)

install_github("woraphonyamaka/copulaSFM", force=TRUE)

library(copulaSFM)