A frontier-based hierarchical clustering for airport benchmarking

Abstract

Clustering airports is a necessary step for the proper identification of efficiency benchmarks. This paper introduces a cost frontier-based hierarchical clustering procedure, which is intended to represent an improvement over the very broad, unidimensional airport typologies usually found in benchmarking studies. Starting from the cost function parameters estimated in a previous study, a cross-section of worldwide airports is clustered according to the relevant outputs and input prices, with the cost elasticities and factor shares serving as optimal variable weights. The resulting hierarchical classification is used to identify the efficiency benchmarks.