A method of moments estimator for a stochastic frontier model with errors in variables

We propose a method of moment estimator for a stochastic frontier (SF) model in which one of the independent variables is measured with errors. The estimator requires only minimal distributional assumption on the measurement error, has no need for additional data and is computationally inexpensive. A Monte Carlo study and an empirical example show favorable performances by this estimator.