Robustly efficient parametric frontiers via Multiplicative DEA for domestic and international operations of the Latin American airline industry

Previous studies of (parametric) aggregate frontiers have attempted to capture stochastic features of the random variables (i.e. inputs and outputs) by assuming a ‘risk’ situation (where the probability distributions of the random variables are known). The purpose of this paper is to present and test a new method invented by Charnes, Semple, Song and Thomas for the usual situations of uncertainty (where the probability distributions of the random variables involved in the technical inefficiencies are unknown) to build up global efficient production functions in the context of operations in the Latin American airline industry. This method develops an empirical efficient production function via a ‘Robustly Efficient Parametric Frontier’ in a two-stage approach. As in the Charnes et al. development using a Multiplicative-DEA model, the marginal tradeoffs of the efficient production function are immediately available instead of being harassed by discontinuities of derivatives and numerical instabilities.