ESTIMATORS AND HYPOTHESIS TESTS FOR A STOCHASTIC FRONTIER FUNCTION - A MONTE-CARLO ANALYSIS

This paper uses Monte Carlo experimentation to investigate the finite sample properties of the maximum likelihood (ML) and corrected ordinar y least squares (COLS) estimators of the half-normal stochastic fronti er production function. Results indicate substantial bias in both ML a nd COLS when the percentage contribution of inefficiency in the compos ed error (denoted by gamma) is small, and also that Mt, should be use d in preference to COLS because of large mean square error advantages when gamma is greater than 50%. The performance of a number of tests of the existence of technical inefficiency is also investigated. The W ald and likelihood ratio (LR) tests are shown to have incorrect size. A one-sided LR test and a test of the significance of the third moment of the OLS residuals are suggested as alternatives, and are shown to have correct size, with the one-sided LR test having the better power of the two.