The efficiency of the container port industry has been variously studied utilising either Data Envelopment Analysis (DEA) or Stochastic Frontier Analysis (SFA). Given the strengths and weaknesses associated with these two approaches, the efficiency estimates and scale properties derived from these analyses are not always convincing. This paper applies both approaches to the same set of container port data for the world's largest container ports and compares the results obtained. A high degree of correlation is found between the efficiency estimates derived from all the models applied, suggesting that results are relatively robust to the DEA models applied or the distributional assumptions under SFA. High levels of technical efficiency are associated with scale, greater private-sector participation and with transhipment as opposed to gateway ports. In analysing the implications of the results for management and policy makers, a number of shortcomings of applying a cross-sectional approach to an industry characterised by significant, lumpy and risky investments are identified and the potential benefits of a dynamic analysis, based on panel data, are enumerated. © 2005 Elsevier Ltd. All rights reserved.
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