Ports and Networks: Strategies, Operations and Perspectives. Journal of Shipping and Trade 2 (1): 2–18. Liner Shipping Connectivity as Determinant of Trade. ![]() Geneva: United Nations Conference on Trade and Development (UNCTAD). Policy Issues in International Trade and Commodities. Bilateral Liner Shipping Connectivity Since 2006. Building a Dataset for Bilateral Maritime Connectivity. Advances in Shipping Data Analysis and Modelling. Journal of Development Economics 75 (2): 417–450.ĭucruet, C. Port Efficiency, Maritime Transport Costs and Bilateral Trade. College Station: Stata Press.Ĭlark, X., D. Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods. Political Science Research and Methods 3 (1): 133–153.īhargava, A., and J.D. Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data. CESifo, Center for Economic Studies and Ifo Institute. Estimating the Effects of the Container Revolution on World Trade. Accessed 20 July 2018.īernhofen, D.M., Z. A Model of Trade with Endogenous Transportation Costs. World Bank-Economic Premise: 1–4.Īsturias, J., and S. Trade Costs and Development: A New Data Set. ![]() Presented to International Association of Maritime Economist Conference, Melbourne.Īrvis, J.-F., B. Security and reliability of the liner container shipping network: Analysis of robustness using a complex network framework. American Economic Review 93: 170–192.Īngeloudis, P., K. Gravity with Gravitas: a Solution to the Border Puzzle. The variable maximum ship size does not seem to have a positive bearing on trade, suggesting that countries may not need to try to accommodate ever larger ships to maintain their foreign trade competitiveness.Īnderson, J.E., and E.V. The estimated long-run effects are stronger than the short-run effects, suggesting that shippers take time to adjust their demand to changes in connectivity. The results show that GDP, the number of common direct connections and the level of competition have a positive and significant effect on trade flows, while the number of transshipments and the direct and sailing distances have a negative and significant impact, both in the short and long run. We apply the quasi-maximum likelihood method to estimate the parameters of a dynamic panel data model. In addition to connectivity, measured by five separate components, we also consider the effects on trade of sailing distances, the direct (air) distance and the gross domestic product (GDP) of 142 trading partners. Since shipping connectivity reduces trade costs, which in turn improves trade, this paper aims to analyse the short- and long-run impacts of the liner shipping bilateral connectivity on South Africa’s trade flows.
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