Frontier Techniques: Contrasting the Performance of (Single-) Truncated Order Regression Methods and Replicated Moments

Abstract

This research contrasts three econometric alternatives for stochastic efficiency frontier analysis: order – inter-quantile – and inverse order regression under the assumption of truncated error term distribution, and replicated moment estimation. The demonstration departs from a simple linear regression form of the effective frontier; truncated (at zero) errors are then added to it for simulation purposes. For order regression, experiments with the standard normal, uniform, exponential, Cauchy and logistic error terms are provided. For complex error structures we rely on normal distributions only. The three alternatives would perform satisfactorily for simple error disturbances, especially if they are normal. With more than one residual added to the dependent variable, the weight of the unrestricted range one can blur the conclusions regarding observation efficiency.Stochastic Frontier Model, Generalized Method of Order Statistics, Minimum Distance Method of Order Statistics, Inverse Order Regression, Replicated Moments, Linear Models.