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The Greek shipping estimation model

Marios Papaspyrou () and Athanasios Petralias ()
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Marios Papaspyrou: Bank of Greece
Athanasios Petralias: Bank of Greece

Economic Bulletin, 2019, issue 49, 28-39

Abstract: The Greek Shipping Estimation Model aims to provide a coherent statistical framework for the estimation of Balance of Payments (BoP) items related to shipping activity, based on administrative sources and commercial databases. Given the multi-territorial nature of the shipping sector and its complex group structures, the estimation of shipping activity is one of the most challenging tasks in terms of official statistics. This is of particular importance to Greece, whose merchant fleet plays a strategic role in the transportation of commodities across the world. The statistical framework presented in this study may well be applied by other countries for BoP compilation purposes, as well as by researchers and analysts seeking to estimate revenues and expenses related to shipping activity. The Greek Shipping Estimation Model adopts a granular-level approach, with vessel-by-vessel characterisation, involving three steps. Firstly, the cluster, the main counterparts and the types of BoP transactions that take place and can be estimated are defined. Secondly, the population is defined, including companies that are legal owners, operators or ship managers, and the vessels to be taken into account. Finally, all BoP transactions for a given vessel are estimated on a monthly basis. The maritime cluster structure is discussed, along with guidelines on how to define the resident population in line with the economic ownership principle. A detailed statistical framework for the estimation of all shipping-related transactions is presented, including vessels’ revenues, bunker costs, port expenses, manning costs, administrative costs, and other BoP items.

Keywords: shipping; maritime cluster; sea transport services; balance of payments (search for similar items in EconPapers)
JEL-codes: C8 F1 F23 F32 L9 (search for similar items in EconPapers)
Date: 2019
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