Abstract
This paper proposes two alternative estimators for the semiparametric smooth coefficient stochastic frontier model which do not require parametric specification of the parameters of the distribution of inefficiency to identify all of the model primitives. These new estimators offer avenues for testing for correct specification. A small Monte Carlo simulation study reveals that the new methods perform similarly when correct specification is present and that the existing smooth coefficient estimator can perform poorly when it is incorrectly specified.
•Smooth coefficient estimation of stochastic frontier model becoming popular.•Propose three different semiparametric smooth coefficient estimators.•New estimators robust to potential misspecification of scaling function.•Simulations reveal expected and realistic performance.
