The truncated bivariate normal stochastic frontier model (TBN-SFM), which is globally unidentifiable on its natural parameter space, has been recently shown to be locally near-identifiable even under the identifying parametric restrictions. Maximum Likelihood estimation of such a model is...

This paper examines the identifiability of the standard single-equation stochastic frontier models with uncorrelated and correlated error components giving, inter alia, mathematical content to the notion of "near-identifiability" of a statistical model. It is seen that these models are at least...