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Appendix to Part II: Data Requirements for the SPICS

II.1 Data Sets for South Pacific Island Countries—SPICs

In this section we describe the data sets collected for the case study of the South Pacific Island Countries. We also include statistical analyses to describe the status quo of these countries. To begin, the collected variables are summarised in Table II.1 and fully described in the next sections. One of the limitations of the study, however, has been the lack of robust and comprehensive data sets for the

Fig. II.1 Visualisation of the geographic location of the container ports considered in the study

© Springer International Publishing AG 2017 113 F.R. Medda et al., Collaborative Approach to Trade, Advances in Spatial Science, DOI 10.1007/978-3-319-47039-9 Table II.1 List of model variables and collected data sets SPICS the for Requirements Data II: Part to Appendix 114 Completeness Model Notation Variable Information Unit Year (% or no.) Source component n ¼ 1, 2, ..., Ports (35) Container ports in SPICS Latitude, – 100% www.sea-rates.com Horizontal N and relevant Pacific RIM Longitude Containerisation countries International sw (u) Throughput Volumes handled per year TEU Various 69% – Port Authorities website (or TON) – Secretariat of the Pacific Community (2011) Max_draft Max Draft Max Draft Mt 2011 100% Secretariat of the Pacific Community (2011) Vessel_size Max vessel size Size of the largest vessel mLOA 2011 80% Secretariat of the Pacific that has visited each port (or dwt) Community (2011)

Rij,k Container Shipping Container services that Non- Various 54 shipping – Asian Development Services (CSS) operate in SPICs ports dimensional services Bank Report (2004) – shipping lines LPI_EC Efficiency of cus- Efficiency of customs Non- 2010 62% World Bank toms: Logistics clearance process dimensional Performance Index (LPI) Internet_users Internet Users Population with access to Percentage 2010 100% World Bank the worldwide network www.internetworldstats.com Ease_business Ease of Doing Measures if a country’s Ranking 2012 77% World Bank Business regulatory environment is conducive to business LSCI Liner Shipping Captures countries’ Non- 2010 91% UNCTAD Connectivity Index connectivity to global dimensional shipping networks LPI Logistics Perfor- Reflects perceptions of Non- 2010 62% World Bank mance Index: a country’s logistics dimensional Overall operations I1Dt esfrSuhPcfi sadCutisSIs115 Countries—SPICs Island Pacific South for Sets Data II.1 Ei,k; Ij,k Supply/demand Import/export at country US$ 2010–2012 100% UN Trade Dataset Vertical level by product GDP GDP GDP US$ Until 2012 100% – World Bank – IMF TA Economic Free trade agreements Non- Various 4 Agreements WTO Agreement between SPICs and between dimensional (SPARTECA, SPICs and major Pacific PICTA, Rim countries PACER, APEC) Migration M Major demographic figures Various Until 2012 100% World Bank Cult Cultural ties Cultural links Non- 2005 100% CEPII dimensional Lang Common Language Common language Non- 2005 100% CEPII dimensional

TCuv , k Transport cost US$/TEU 100% Transport huv , k Handling cost Handling cost per unit US$/TEU 100% Korea Maritime Institute cost τuv Port tariff US$/TEU 76% b duv Travel time Travel time between ports Days 100% Own elaboration on GIS map (distance) and vessel speed T. Notteboom and P. Cariou (2009) cpe Fuel cost IFO 380 prices for the US$/ton 2013 100% Asian-Pacific market in Nov 2013 ε Vessel Fuel Vessel fuel consumption tons/day 2009 100% T. Notteboom and P. Cariou Efficiency according to vessel size (2009) and travel speed 116 Appendix to Part II: Data Requirements for the SPICS region under consideration. For this reason, the data have been drawn from different sources and merged together in order to produce a satisfactory and robust data set. Below in Fig. II.1 is the geo-referred visualisation of the 35 ports under examination.

II.2 The Shipping Network

Maritime shipping is the dominant mode of transport for international trade for the SPICs and is the main focus of the model. We reconstruct the container trade shipping network within SPICs and between SPICs and major Pacific RIM coun- tries. The remainder of this section is dedicated to the description of the shipping network we have reconstructed from the available sources.

Port Selection

We have collected information on 35 container ports in 25 countries in the region: 12 belong to major Pacific RIM countries and 23 to the SPICs. The collection has been performed such that we have selected any container port in the SPICs which is served by at least one international liner service. For modelling purposes, we have chosen one port for each Pacific RIM country that has trade relationships with SPICs. In Table II.2 we report the list of container ports included in our case study. As reported in Table II.3 below for each port (or at the national level for economic variables), we introduce the following information: Throughput, Max Draft, Logistics Performance Index (Efficiency of Customs) (LPI), Internet Users, Ease of Doing Business, Liner Shipping Connectivity Index (LSCI), Logistics Performance Index (LPI) (Overall), and Port Fees. Most of the selected variables in Table II.3 have a high variance since our data set comprises both international hubs (e.g., Hong Kong, Singapore, Busan, etc.) and under-developed ports in the SPICs. As expected, ports in the SPICs show low traffic volumes and poor port characteristics (Table II.3). In Fig. II.2 we visualise throughput and Fig. II.3 shows the maximum vessel draft allowed for ports in our case study. We use vessel maximum draft as a proxy for ports’ technical characteristics. It is noteworthy that, although ports in the SPICs are on average poorly equipped, some ports (e.g., in PNG, and Atoll) can accommodate fairly large vessels. In Figs. II.4, II.5 and II.6 we visualise GDP, Ease of Doing Business, and percentage of Internet Users, respectively, in our case study countries. As expected, SPIC countries all have very low GDP, and new business activity has relatively high difficulty in getting started. Although the SPICs are better positioned than some of the strong emergent economies (e.g., India, China and Indonesia), a less rosy picture appears when we consider the percentage of people with Internet access. Apart II.2 The Shipping Network 117

Table II.2 Container ports and countries examined in our case study Country List of ports (3-digit code) American (S) (APW), (PPG) (R) (BNE) China (R) Hong Kong (HKG) Fiji (S) (LTA), (SUV) (S) Port of Guam (GUM) Indonesia (R) Jakarta (JKT) India (R) Calcutta (CCU) Japan (R) Nagoya (NGO) (S) Betio (TRW) South Korea (R) Busan (BNU) Majuro Atoll (S) Majuro Atoll (MAJ) (S) Noumea (NOU) Malaysia (R) Port Kelang (PKL) (R) Tauranga (TRG) Philippines (R) Manila (MNL) (S) Koror (KOR) (S) Kimbe (KIM), Lae (LAE), Madang (MAG), Oro Bay (ORO), (PMB), Rabaul (RAB) French (S) (PPT) Singapore (R) Singapore (SIN) (S) (HIR), Noro (NOR) Thailand (R) Bangkok (BKK) (S) Nukualofa (TBU) (S) (FUN) USA (R) Los Angeles (LAX) (S) (VLI), Santo (GBS) (S)—SPICs and (R)—Pacific RIM countries

Table II.3 Relevant statistics of port variables N Min Max Mean Std. dev. Variance Skew. Kurtos. Throughput 29 2000 2.8E+7 3,446,542 6,997,488 4.9E+13 2.59 6.41 Max Draft 35 6.4 22 11.68 3.56 12.64 1.25 2.24 Efficiency 22 1.95 4.02 2.7 0.7185 0.5162 0.46 À1.42 customs (LPI) Internet users 35 2 83.7 29.01 28.57 816.19 0.86 À0.82 Ease of Doing 27 1 133 72.11 45.08 2032.54 À0.47 À1.39 Business LSCI 31 2.9 143.6 27.0 35.6527 1271.2 1.82 2.61 Total LPI 22 1.91 4.22 2.8 0.85 0.73 0.39 À1.49 Port fees 35 489.9 10,421 4056 2412 5,819,234 0.74 0.16 118 Appendix to Part II: Data Requirements for the SPICS

Fig. II.2 Geo-referred visualisation of Port Throughput

Fig. II.3 Geo-referred visualisation of Maximum allowed vessel Draft II.2 The Shipping Network 119

Fig. II.4 Geo-referred visualisation of national GDP in 2010

Fig. II.5 Geo-referred visualisation of national Ease of Doing Business. Small values are associated with countries where it is easier to start up a business 120 Appendix to Part II: Data Requirements for the SPICS

Fig. II.6 Geo-referred visualisation of national percentages of Internet Users from the more dynamic examples of PNG and the Solomon Islands, most of the SPICs have low to medium values of Internet usage.

Container Shipping Services

We construct the shipping network in the study region by collecting information from 14 shipping companies. We have surveyed a total of 54 container services in the region and included every port in the SPICs that is served by at least one shipping service; in other words, we have collected and analysed the data for 23 ports in the SPICs (shown below in Table II.4). Moreover, we have considered one port for each country outside the SPICs that has trade relationships with the SPICs (12 ports). The reasons for selecting only one port for each neighbour country are: (i) we suppose that the transport cost from a port in the SPICs to any port in a selected neighbour country does not fluctuate substantially (for example, we assume transport cost between Suva and Brisbane or Suva and Melbourne to be similar); and (ii) we do not have detailed information on supply and demand locations within each country. We do, however, have information on trade flows (Imports and Exports) between countries, but no data on ports of origin and ports of destination of these trade flows. In Fig. II.7 we visualise 22 out of 54 container II.2 The Shipping Network 121

Table II.4 List of No. of container services 14 container shipping Shipping company included in our data set companies in operation in the ANL 10 SPICs and Pacific Rim countries included in our CMA CGM 1 study CONTI7 1 GRETER BALI HAI 1 HAMBURG SUD 1 MARIANNA SHIP. LTD 2 MATSON 5 OOCL 1 PACIFIC DIRECT LINE 1 PACIFIC FORUM LINE 7 PIL 6 SEA TRADE 1 SWIRE 15 ZIM 2 Total 54

Fig. II.7 Geo-referred visualisation of a sample of 22 container services 122 Appendix to Part II: Data Requirements for the SPICS services operating in the SPICs: different colours represent different container services. We report our analysis of the complete list of the 14 examined shipping companies and the number of services that each company operates in SPICs below in Table II.4. In the vertical model component we examine the complete set of interactions between layers of the Multilayer model. Shown in Fig. II.8 are the envisioned layers: Trade, Cultural Links (Cult) and Common Language (Lang), Trade Agree- ments (TA), and Container Shipping Network (CSN). The Container Shipping Network used in the study has been described in the previous section; we focus on the remaining variables next.

Fig. II.8 A simplified visualisation of the Vertical Interaction model. Depicted from top to bottom: bilateral trade flows, trade agreements, cultural links, common language, and container shipping network II.2 The Shipping Network 123

Trade

In order to reconstruct the trade flows between countries in our case study we have utilised the UN COMTRADE data set. Data on the bilateral trade of SPICs with its major trading neighbours in the period 2010–2012 have been collected from www. trademap.org and covers around 95% of bilateral trade between SPICs and trade partners in the region. Some SPICs also have trade relationships with other coun- tries outside the Pacific RIM and neighbouring areas (in Southern Africa, South America and Europe). We have excluded these countries from our model due to scant information at our disposal on the international container shipping network. Trade volumes are given in values (US$) divided into 100 commodity cate- gories, according to the 2-digit Harmonised System (HS2). In order to ease the analysis and interpretation of trade patterns, we aggregate the 100 HS2 categories into 15 categories HS1, shown in Table II.5. Immediately after, in Fig. II.9,we

Table II.5 HS1 and HS2 commodity classification HS1 HS2 codes HS1 HS2 codes Animals and animal products 01–05 Textiles 50–63 Vegetable products 06–15 Footwear 64–67 Foodstuffs 16–24 Stone and glass 68–71 Mineral products 25–27 Metals 72–83 Chemical and allied industries 28–38 Machinery/electrical 84–85 Plastics/rubber 39–40 Transportation 86–89 Raw hide, leather, etc. 41–43 Miscellaneous 90–99 Wood and wood products 44–49

Fig. II.9 Exports (left) and imports (right) in the SPICs by HS1 classification 124 Appendix to Part II: Data Requirements for the SPICS visualise total Exports and Imports by HS1 commodity classification. In general, the South Pacific Island Countries (SPICs) export raw materials and import manufactured goods and processed products (machinery, chemicals, plastics, trans- portation, food, etc.). Next in Fig. II.10 we represent the network generated by trade flows. Papua New Guinea (PNG) is by far the country with the highest total trade. Within countries outside SPICs, Australia is the leading trading partner. When we examine the graph in Fig. II.11 of total Imports and Exports in SPICs, the imbalance between trade flows is striking. Imports are shown to be twice as much as SPICs Exports, with the exception of the Solomon Islands.

Fig. II.10 Trade flows between countries in the period 2010–2012. SPICs countries are visualised in red. Linked colours identify country of origin, and link width is proportional to trade value II.3 Cultural Links and Common Language 125

Fig. II.11 Imports and exports for SPICs between 2010 and 2012

II.3 Cultural Links and Common Language

We use the CEPII data set1 in order to account for cultural and language similarities between countries. Language similarities are considered through a dummy variable which is assigned to each couple of countries in our data set: value 1 represents the existence of a cultural link when one or more languages are spoken by at least 9% of the population in two countries. Cultural linkages are taken into consideration through the existence of colonial links between countries.

Trade Agreements

South Pacific Island Countries participate in four trade agreements: SPARTECA, PICTA, PACER, and APEC. A brief description of each trade agreement is given in the remainder of this section. South Pacific Regional Trade and Economic Cooperation Agreement (SPARTECA) SPARTECA was signed in 1981 between Australia, New Zealand and 14 countries of the South Pacific Forum. It allows duty free access to the products of Forum

1http://www.cepii.fr/anglaisgraph/workpap/pdf/2011/wp2011-25.pdf 126 Appendix to Part II: Data Requirements for the SPICS

Island Countries (FICs) to the markets of Australia and New Zealand, subject to ‘Rules of Origin’ regulations. The aim is to redress the unequal trade relationships between the two groups. The Pacific Island Countries Trade Agreement (PICTA) PICTA is a free trade agreement among the 14 Forum Island Countries (FICs). Under this agreement virtually all barriers (import tariffs and quotas) to merchan- dise trade between FIC countries is to be removed. The initial PICTA, which covers only Trade in Goods (TIG), was ratified by (10) FICs. The agreement was signed in 2001 and came into force in 2006. Fiji ratified the agreement in 2002. The Pacific Agreement on Closer Economic Relations (PACER) The PACER is a framework agreement setting out the basis for the future devel- opment of trade relations among all 14 Forum members. The PACER provides for free trade to be established gradually among Forum members, in line with the ‘stepping stone’ approach preferred by the FICs—i.e. as the name suggests, the Agreement sets a framework for free trade in the region to be established at the appropriate ‘pace’, reflecting the different development status of the members. Asia-Pacific Economic Cooperation (APEC) The APEC is a Forum for 21 Pacific Rim member economies seeking to promote free trade and economic cooperation throughout the Asia-Pacific region.

II.4 Transport Costs for SPICS

Another important variable collected and estimated for the present study is trans- port cost. The transport cost for a route linking two ports is calculated by measuring the information on port fees and the voyage costs due to vessel fuel consumption.

Voyage Cost

Voyage cost includes the fuel cost of a vessel during its journey from one port to another. To calculate voyage cost we include distance between ports, fuel price, and vessel technical specifications that determine its fuel consumption. The fuel price in our study is based on the price for the IFO 380 bunker in the Asian and South Pacific market (Singapore) in November 2012, which was reported at US$616 per tonne (PDVSA 2013). Total fuel consumption in a vessel depends, among several factors, on vessel size and average speed. In order to estimate a typical vessel size for our study, we have conducted a survey among shipping companies that publishes schedules and deployed vessels in their websites (Table II.6). Results show that a typical container/cargo ship has Gross Tonnage (GT) of around 12,200 tonnes and deadweight tonnage (DWT) of 15,600 tonnes. II.4 Transport Costs for SPICS 127

Table II.6 Containerships deployed in the SPICS Companya Vessel namea GTb DWTb Visited SPICs portsa Pacific Forum Line CAPITAINE 9422 13,064 Suva, Lautoka, Tawara Betio, Wallis, (& PDL & PIL) WALLIS Futuna, Funafuti, Tarawa Betio, Majuro Pacific Forum Line CAPITAINE 9422 12,814 Suva, Apia, Nukuafola,Noumea, Port (& PDL) TASMAN Vila, Lautoka, Pago Pago Pacific Forum Line TIARE 3972 4152 Nukuafola (& PIL) MOANA Pacific Forum Line SOUTHERN 9684 12,502 Nukuafola, Apia, Pago Pago (& PDL) LILY Pacific Forum Line FORUM 9422 13,058 Suva, Apia, Nukuafola, Pago Pago, (& PDL) SAMOA III Noumea, Port Vila, Lautoka Swire Shipping NINGPO 16,801 22,900 Noumea, Lautoka, Suva, Port Moresby, Wallys and Futuna, Lae, Rabaul, Madang, Santo, Honiaria, Port Vila, Noro Swire Shipping SHANTUNG 25,483 30,814 Lautoka, Suva, Lae, Honiaria, Noro, Port Vila, Noumea, Rabaul, Kimbe, Oro Bay, Madang, Honiara, Swire Shipping NGANKIN 16,801 22,900 Honiara, Noumea, Lautoka, Suva, Wallis, Port Moresby, Lae Swire Shipping SOOCHOW 25,483 30,721 Lae, Honiara, Noumea, Noro, Port Vila, Majuro, Tarawa Betio, Lautoka, Suva, Rabaul, Kimbe, Oro Bay, Madang Swire Shipping SHANSI 25,483 30,700 Lautoka, Suva, Honiara, Noro, Lae, Rabaul, Oro Bay, Kimbe, Madang, Port Vila, Noumea, Majuro, Tarawa Betio Swire Shipping ISLAND 10,352 10,553 Lae, Oro Bay, Kimbe, Rabaul, Noro, CHIEF Honiara, Port Moresby Swire Shipping KWEILIN 18,468 23,586 Noro, Honiara, Lae, Kimbe Swire Shipping PAPUAN 10,350 13,550 Lae, Oro Bay, Rabaul, Madang, CHIEF Santo, Suva, Lautoka, Apia, Pago Pago, Majuro, Tarawa Betio, Swire Shipping HIGHLAND 10,357 10,775 Oro Bay, Lae, Rabaul, Madang, CHIEF Santo, Lautoka, Suva, Majuro, Tarawa Betio, Apia, Pago Pago Swire Shipping SHAOSHING 25,483 30,814 Lautoka, Suva, Lae, Honiara, Noumea, Port Vila, Majuro, Tarawa Betio, Rabaul, Kimbe, Oro Bay, Madang Matson LILOA 5234 5650 Lautoka, Suva, Apia, Pago Pago, Nukualofa Matson OLOMANA 5025 5642 Lautoka, Suva, Apia, Pago Pago, Nukualofa Matson IMUA 4246 6288 Honiara, Noro, Suva, Port Vila, Santo (continued) 128 Appendix to Part II: Data Requirements for the SPICS

Table II.6 (continued) Companya Vessel namea GTb DWTb Visited SPICs portsa Matson CAPE NATI 18,326 23,400 Honiara, Port Moresby, Lae, Rabaul (& New Pacific Line) Matson CAPE 18,326 23,327 Honiara, Port Moresby, Lae, Rabaul (& New Pacific NASSAU Line) Pacific Direct Line SOUTHERN 9422 13,064 Port Vila, Santo, Suva, Noumea, (& PFL) MOANA Lautoka Pacific Direct Line SOFRANA 9935 12,343 Noumea SURVILLE Pacific Direct Line SOFRANA 9684 12,502 Noumea, Honiara TOURVILLE Pacific Direct Line SOUTHERN 9725 12,985 Papeete (& PIL) TRADER Pacific Direct Line KOTA 16,772 24,650 Papeete WARUNA Pacific Direct Line SOUTHERN 5234 6030 Suva, Wallys, Futuna, Tarawa Betio, (& PIL) PEARL Fiji, Funafuti Pacific Interna- SOUTHERN 9684 12,502 Fiji, Lautoka, Apia tional Lines FLEUR Pacific Interna- SOUTHERN 9420 13,058 Nukualofa, Apia tional Lines LILY 3 Pacific Interna- DANNY 5994 9606 Fiji, Honiara tional Lines ROSE Pacific Interna- SOUTHERN 5316 7708 Honiara tional Lines PHOENIX Pacific Interna- PAPUA 10,350 13,550 Fiji, Tarawa Betio, Majuro tional Lines CHIEF Average total 12,248 15,652 Average (vessels with GT < 20,000 9,978 13,029 tonne) aSource: shipping company websites: www.pacificforumline.com, www.swireshipping.com, www.matson.co.nz, www.pdl123.co.nz, and www.pilship.com bSource: www.marinetraffic.com

We have taken a conservative approach to estimate the average vessel size and consider vessels with GT under 20,000 tonnes. In this case a typical vessel (average value) operating in the SPICs has GT of 10,000 tonnes and DWT of 13,000 tonnes. In the study we have selected as an archetypal vessel size that of Capitaine Wallis for two main reasons. First, if we consider the size of the average vessel operating in the SPICS, the value is lower than the size of Capitaine Wallis. However, since this is a strong hypothesis and we are also assuming in our model that vessels always travel fully loaded, we prefer to maintain a cautious attitude. II.4 Transport Costs for SPICS 129

Table II.7 Main technical Factor Value characteristics of sample Vessel size (TEU) 700 vessel used in our study Gross tonnage 9422 DWT 13,064 LOA 145.9 m Fuel efficiency 50 tonnes/day

Second, we have observed that Capitaine Wallis is largely used in SPICs by three shipping companies that operate various services in cooperation using this vessel. Table II.7 shows the technical specifications of the vessels assumed in our study. According to the study by Notteboom and Cariou (2009), vessels smaller than 1100 TEUs traveling at an average speed of 19 knots (35.2 km/h), consume approxi- mately 50 tonnes of fuel per day of travel. Number of days of journey depends on the distance between two ports and determines the total fuel consumed. Voyage cost plays a significant role in the transport cost by being its principal component. Initial results obtained from simulations have revealed that the voyage cost per unit is between 51% and 907% higher than the port fee per unit. The long distance between ports, as well as economies of scale in the number of TEUs transported in a vessel, determine the difference between the two cost components of the transport cost. When examining the transport cost, the highest levels of this cost can be attributed to the links connecting ports in the SPICs with major ports outside the SPICs region (e.g., Singapore, Hong Kong, Manila, and Los Angeles) despite the fact that the latter ports tend to have relatively low port fees. In these cases the condition of the SPICs as a remote area was confirmed to have the significant impact of increasing the transport cost when linking to foreign markets, mainly due to the voyage cost. When analysing the transport cost within the SPICs region, we found that for the particular cases of Honiara and Pago Pago, links connecting these ports show a higher transport cost compared with other links among the SPICs as a consequence of the high port fees attributed to these ports. Conversely, lower transport costs were observed in the links connecting Oro Bay, Lautoka, and Funafuti ports due to their lower port fees, their convenient location in relative proximity to other ports in the region, and the lack of links connecting to ports outside the SPICs.

Port Fees

For each port in our case study the associated port fee is the cost for each vessel entering the port at any period in the year and for a time span in the port not exceeding 3 days. The port fee includes entrance fees, dockage and anchorage charges, pilotage fee, and tug service charges. In other words, we consider all of the 130 Appendix to Part II: Data Requirements for the SPICS port fees that are not related to container movements. Data on port fees was obtained from different Port Authority websites (P.A.W.), direct contact with Port Authorities by email or phone (P.A.D.), and from the Korean Maritime Industry (KMI). Table II.8 summarises the port fees for the ports in our case study.

Table II.8 Estimated port fees per entry for a vessel with characteristics Entrance fee Dockage and Port US$ anchorage Pilotage Tug service Total Reference Apia 486.3 2530 1264.3 (incl. in Pilot.) 4280.6 KMI Pago Pago 486.3 2530 1264.3 (incl. in Pilot.) 4280.6 KMI Brisbane 177 1138 2071 (incl. in Pilot.) 3386 P.A.D. Hong Kong 417 1496 645 Na 2365 P.A.W. Lautoka 1020 188.7 1443 (incl. in Pilot.) 2651.7 KMI Suva 1020 188.7 1443 (incl. in Pilot.) 2651.7 KMI Port of Guam 312.6 177.3 na Na 489.9 P.A.W. Jakarta – – – – 2000a Calcutta 1022 2677.2 1610 (incl. in Pilot.) 5309.2 P.A.W. Nagoya 256.46 1116 na Na 1372.5 P.A.W. Tarawa Betio 530 290 400 Na 1220 KMI Busan 593 292 204 1401 2490 P.A.D. Majuro Atoll – – – – 1300a Noumea – – – – 6800a Port Kelang – – – – 2500a Tauranga 10,421.04 (incl. in (incl. in (incl. in 10,421.04 P.A.D. entr. fee) entr. fee)entr. fee) Manila 787 379 na na 1166 P.A.W. Koror – – – – 6800a Kimbe 103 2976 1023 2600 6702 KMI Lae 207 2976 1023 2600 6806 KMI Madang 103 2976 1023 2600 6702 KMI Oro Bay 103 2976 1023 2600 6702 KMI Port Moresby 207 2976 1023 2600 6806 KMI Rabaul 103 2976 1023 2600 6702 KMI Papeete – – – – 2000a Singapore 712.5 502.5 360 420 1995 P.A.W. Honiara 870 381.2 1450 na 2681.2 KMI Noro 870 381.2 1450 na 2681.2 KMI Bangkok – – – – 2000a Nukualofa 516 0 600 2400 3516 P.A.W. Funafuti – – – – 1300a Los Angeles na 1322 2641 (incl. in Pilot.) 3963 P.A.W. Port Vila – – – – 1300a Santo – – – – 1300a aDue to a lack of available information, the fee for these ports was approximated based on the figures for ports with similar characteristics II.4 Transport Costs for SPICS 131

In the remainder of this section we report the calculations we have implemented to estimate each charge included in the port fee. Values are reported by countries since in our set of ports the few countries with more than one port apply the same tariffs for all of their ports. Samoa Entrance fee: US$0.05 per GT Dockage: US$0.07 per GT per day Anchorage: US$78 per hour Pilotage and Tug Service: US$0.13 per GT

Australia The Port of Brisbane charges fees by moved container (for entrance and dockage/ anchorage rates). The website of the port of Brisbane provides information of containers moved each quarter aggregated by country of arrival/destination. We have estimated the average number of containers moved in the port of Brisbane from/to SPICs as follows: we consider New Caledonia as representative country of SPICs where port of Noumea handles the largest share of container traffic of New Caledonia. Thus, the national figures of New Caledonia well approximate the traffic between ports of Brisbane and Noumea. We calculate the average number of containers moved in each quarter and divide it by an estimated frequency of service of 15 days. We have found that on average in the port of Brisbane 40 containers are moved during each visit of a vessel from/to SPICs and we assume that this is the value charged due to entrance and dockage/anchorage fees. Entrance fee: US$4.4 per container Dockage: US$28.5 per container Anchorage: included in Dockage Pilotage: US$2071 per service Tug Service: included in pilotage

China Entrance fee: US$43 per 100 tonnes or part thereof on each occasion of entry Dockage: US$60 for each 8 m in length of a vessel to be berthed alongside the seawall Anchorage: US$0.02 per tonne Pilotage: US$0.065 per tonne of the ship’s gross registered tonnage Tug Service: n.a.

Fiji Entrance fee: US$2.2 per 100 GRT plus US$806.25 for each entry Dockage: included in anchorage 132 Appendix to Part II: Data Requirements for the SPICS

Anchorage: US$4.826 for each 100 GRT Pilotage: US$0.1075 per GRT plus fixed charge of US$397.75 Tug Service: included in pilotage

Guam Entrance fee: US$54.81 plus US$40.84 for each additional 2000 gross tonnes Dockage: US$59.11 per day Anchorage: US$253.44 per day Pilotage: n.a. Tug Service: n.a.

India Entrance fee: US$0.105 per GRT Dockage: included in anchorage Anchorage: US$0.138 per GRT per hour Pilotage: fixed rate Tug Service: included in pilotage

Japan Entrance fee: US$0.03 per GRT Dockage: US$0.10 per GRT Anchorage: included in dockage Pilotage: no rates found for pilotage Tug Service: no rates found for tug service

Kiribati Entrance fee: US$0.30 per metre length Dockage: US$2 per metre length Anchorage: included in dockage Pilotage: US$0.05 per GRT with a max of US$400 Tug Service: no rates found for tug service

New Zealand Entrance fee: Port of Tauranga apply a fixed fee which includes all port tariffs Dockage: included in entrance fee Anchorage: included in entrance fee II.4 Transport Costs for SPICS 133

Pilotage: included in entrance fee Tug Service: included in entrance fee

Philippines Entrance fee: US$0.081 per GRT Dockage: US$0.020 per GRT Anchorage: included in dockage Pilotage: no rates found for pilotage Tug Service: no rates found for tug service

PNG Entrance fee: value per entrance Dockage: US$0.69 per LOA per hour Anchorage: US$65.61 per LOA per year Pilotage: US$0.3 per GT + US$86 (pilot fee) + US$251.9 (pilot boat charge) Tug Service: US$2600

Singapore The rates reported are the best approximation to be found in the Port Authority website. As Singapore is a privately owned port, PSA Corporation adopts a market- based approach, in that shipping companies are offered special offers according to their long-term contracts. Entrance fee: US$7.5 per 100 GRT Dockage: US$0.05 per GRT Anchorage: included in dockage Pilotage: vessel above 6000 GT and up to 12,000 GT Tug Service: vessel above 5000 GT and up to 10,000 GT

Solomon Islands Entrance fee: US$6 per metre of length Dockage: US$1.94 per 100 GT Anchorage: US$4.3 per metre of length Pilotage: US$10 per metre of length Tug Service: no rates found for tug service 134 Appendix to Part II: Data Requirements for the SPICS

South Korea Entrance fee: US$0.10 per GT Dockage: US$0.03 per GT Anchorage: US$0.02 per GT Pilotage: US$204 per call Tug Service: US$1401 per call

Tonga Entrance fee: US$0.05 per GT Dockage: n.a. Anchorage: n.a. Pilotage: launch hire, per hour running Tug Service: tug hire, per hour running

USA Entrance fee: n.a. Dockage: fixed rate (class: between 135 and 150 metres of length) Anchorage: included in dockage Pilotage: US$0.0034 per GT + US$591 Tug Service: included in pilotage

Reference

Notteboom TE, Cariou P (2009) Fuel surcharge practices of container shipping lines: is it about cost recovery or revenue-making? Proceedings of the International Association of Maritime Economists (IAME) 2009 Conference, Copenhagen, June