Estimating the Relative Efficiency of European Container Ports: A Stochastic Frontier Analysis
Kevin Cullinane and
Dong-Wook Song
Research in Transportation Economics, 2006, vol. 16, issue 1, 85-115
Abstract:
This paper estimates the relative technical efficiency of a sample of European container ports using the cross-sectional version of the [`]stochastic frontier model' under the assumption that the functional form of the production frontier is the log-linear Cobb-Douglas function. The estimated efficiency measures are broadly similar for the three assumed error distributions that were tested. From the results of the analysis, it is concluded that the size of a port or terminal is closely correlated with its efficiency. Ports in the United Kingdom were found to have the most efficient infrastructure usage; a finding consistent with the shortage of container-handling capacity. Scandinavian and Eastern European container terminals yielded the lowest estimates of relative efficiency. Geographical location (being displaced from the mainline intercontinental container trades) and below average size are possible explanations for this result.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (46)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0739-8859(06)16005-9
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:retrec:v:16:y:2006:i:1:p:85-115
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_2&version=01
Access Statistics for this article
Research in Transportation Economics is currently edited by M. Dresner
More articles in Research in Transportation Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().