Marginal cost estimations in airports: multiproductive cost functions and stochastic frontiers: an international airports case study

Abstract

Regarding some regulation fields, such as optimal investments and pricing policies, marginal cost estimations for infrastructure intensive transport services is always a challenging effort in order to provide some basis for important areas of economic regulation. The lack of comparable data among airports is one of the causes which could explain the relative scarcity of this literature in the previous studies. In this paper, we estimate different specifications and methods, using mono and multi product translog specifications and a technical efficiency stochastic frontier. We also estimate long and short run cost functions, using a pooled database of financial data on 41 airports across Europe, North America, Asia and Australia for the period 1991-2005. We find significant economies of scale using Work Load Units (WLU) and Air Traffic Movements (ATM) as output measures. Additionally, we provide individual long and short run marginal costs estimates for each output measure, and for every airport under study. The variability of our marginal cost estimations lead us to further deviate from the assumption of neoclassical theory, and to study the existence of some important levels of inefficiency regarding airports performance. For this reason, we consider the stochastic frontier analysis which partially solves this matter.