DEA tends to dominate the methodologies. There are however many methodological debates among port specialists and efficiency specialists. For instance, Park and De (2004) using data on 11 Korean ports for 1999 compare all the methods available and suggest a new 4 stages DEA to increase the robustness of the results. There is also a more conceptual debates on the number of port activities that need to be covered by efficiency studies. The matter is not a simple one since many of the activities are competitive while a few, more obviously the port infrastructure, are not. Moreover, while it is obvious to all that there is a complementarity between all activities, there is no uniform view on how to address it in the context of efficiency measures or even whether it needs to be addressed. For instance, some argue that all equipment, including equipment owned and operated by independent competitive providers, must be included in the assessment of the performance of the port authorities responsible for the basic infrastructure. Many more disagree with this vision arguing instead that there is an interest in assessing the performance of the regulated monopoly independently of the performance boost or penalty that independent competitive providers may generate. At best, when information is available, the competitive segments of the port should enter as environmental variables.

In practice, the response to the debate is generally settled by data availability. In general, the focus of the assessments in ports tends to be the production side rather than the cost side mainly because of data constraints. But these constraints are so binding that they also drive other choices. They explain why most articles focus on _Cobb-Douglas_ rather than _Translogs._ Most studies also focus on data panels than time series. There are however a few very real policy aspects that cannot be ignored. For instance, most studies explicitly recognize the multiproduct nature of the port business, although a few focus on aggregate output measures. The most common is to see a disaggregation between general, dry-bulk, liquid-bulk and containerized cargo. On the input side, labor and capital tend to be present in every study. Everyone seems to agree on the labor variable but there is no consistency in the way the capital variable is being measured. Only a few studies have accounted for environmental variables (i.e. Is it a mainland port or an island? Is some of the cargo delivered by pipeline? ...).

It may be useful here to point to some very pragmatic implementation issues in the estimation of efficiency in the sector. It is not unusual also to see changes in the definitions of some of the variables during the periods of assessment. In the case of labor for instance, reforms tend to lead to major outsourcing policies. In this context, the employment data may end up comparing apples and oranges over time if the researcher is not careful. Indeed, the post reform data would only pick up employees under the port authority payroll and cover the others under the costs of service contracts. The risk is however limited for studies focusing on port authorities since they tend to be quite narrowly focused and are associated with very little outsourcing. For studies attempting to have a wider coverage of port services, the issue is more problematic.

With these limitations in mind, the few papers available provide a number of useful lessons. These can be separated in two types. From a market structure viewpoint, the research provides useful insights to any policymaker in developing countries. First, with respect to size, Cullinane et al. (2002) show that the size is directly influencing efficiency, at least in container terminals. Second, container terminals located in hub ports tend to be more technically efficient than those in feeder ports as documented by 15