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This paper explores the relationship between output specialisation, diversification, size and technical efficiency in ports. Using a sample of Spanish port authorities observed over the period 1993-2012, we calculate a normalised Herfindahl-Hirschman index of overall specialisation and indices of relative specialisation in the individual cargoes. An output distance frontier is estimated using non-parametric Data Envelopment Analysis techniques to calculate technical efficiency. These efficiency scores are then used to test that relationship with a bootstrapped truncated regression. We find that both overall and relative output specialisation have a positive influence on technical efficiency. Moreover, the positive effects of specialisation on technical efficiency is reinforced for larger ports, which are in a better position to take advantage of economies of scale and which can also attract different types of cargo (enjoying also economies of scope) and therefore protect themselves from adverse demand conditions. Our results underline the trade-off for smaller port authorities between efficiency gains from specialisation and their vulnerability to market conditions for their main output.

Port efficiency and port clustering are two aspects that have received different degrees of attention in the existing literature. While the actual estimation of port efficiency has been extensively studied, the existing literature has paid little attention to developing robust methodologies for port classification. In this paper, we review the literature on classification methods for port efficiency, and present an approach that combines stochastic frontier analysis, clustering and self-organized maps (SOM). Cluster methodologies that build on the estimated cost function parameters could group ports into performance metrics categories. This helps when setting improvement targets for ports as a function of their specific cluster. The methodology is applied to a database of Spanish port authorities. The dendrogram features three clusters and five outlier Spanish Port Authorities. SOM are employed to track the temporal evolution of Spanish Port Authorities that are of special interest for some reasons (i.e. outliers). Results show that use of a combination of cost frontier and cluster methods to define robust port typology and SOMs, jointly or in isolation, offers useful information to the decision-makers.

Cargo handling activities involve various heterogeneous outputs, e.g. general cargo, containers, dry and liquid bulk, and so on. These activities in ports, however, have been usually analysed using aggregate descriptions of output such as total tons moved. The main purpose of this paper is to show that ignoring this heterogeneity may lead to two types of problems: (i) the underestimation of the relevance of key dimensions (i.e. marginal costs per product and economies of scope) and (ii) a bias in the estimates of the relevance of other dimensions (economies of scale). To do so, we rely on a unique new dataset on three cargo handling firms operating in a Spanish port between 1991 and 1999. We use it to estimate both a multi-output cost for these three operators as well as an aggregate cost function. The policy conclusions are derived from an explicit and detailed comparison of these two sets of estimates.