Abstract

Transport connectivity is a crucial determinant of bilateral exports. This paper presents an empirical assessment of the relationship between bilateral maritime liner shipping connectivity and exports in containerizable goods during the period 2006–2013. Making use of probed “gravity” type trade models, the paper incorporates new data on different measurements of maritime distance, as well as a unique new dataset and new bilateral connectivity indices developed by UNCTAD. The empirical investigations unequivocally show that lacking a direct maritime connection with a trade partner is associated with lower values of exports; any additional transshipment is associated with a 40% lower value of bilateral exports. Other indicators of liner shipping connectivity incorporated in the research take into consideration levels of competition and container vessel sizes. Results also indicate that the quality of bilateral connectivity as measured by several composite indices is a crucial determinant of bilateral exports. All empirical results suggest that in the absence of a bilateral connectivity indicator the impact of distance on bilateral exports in classical gravity models is likely to be overestimated.

Introduction

Maritime transport is at the core of international trade in merchandises. Around 80% of volume of goods exchanged in the world are transported via sea (UNCTAD 2008). The percentage share is even higher for most developing countries and in terms of total transport services measures in ton-kms.

The predominance of maritime transport has increased in particular for manufactured goods due to the intensification of containerized transport services. Thanks to containerization and the global liner shipping network, small and large exporters and importers of finished and intermediate containerizable goods from far away countries can trade with each-other, even if their individual trade transaction would not economically justify chartering a ship. Thanks to a network of regular container shipping services with transhipment operations in so-called hub ports, basically all countries are today connected to each other. A recent empirical study confirmed the “[e]ffects of the Container Revolution on World Trade” (Bernhofen et al. 2013). As far as North-North trade is concerned the authors found a cumulative (concurrent plus lag effects) average treatment effect of containerization over a 20 year time period amount to 790%. The cumulative effect of bilateral GATT membership is found to raise trade by an average of 285%, which is less than half the cumulative effect of full containerization.

Between 1970 and 2010, developing countries’ share in the volume of seaborne exports rose from just 18 to 56% of the world’s total (UNCTAD 2014). Despite this growing participation of developing countries in seaborne trade, evidence on maritime connections suggests that, except for few of them such as China, they may have not reached their full potential. Fugazza et al. (2013) find that the average number of direct maritime connections, meaning without involving any transhipment of the transported goods between the country of origin and their destination, is half for developing countries than what it is for developed ones.

Recent literature has emphasized the importance of transport costs and infrastructure in explaining trade and access to international markets. Based on the estimation of a gravity model using US data, Anderson and van Wincoop (2003) found that transport costs correspond to an average ad valorem tax equivalent of 21%. These 21% include both directly measured freight costs and a 9% tax equivalent of the time value of goods in transit. Using a similar empirical approach, (Clark et al. 2004) estimates reveal that for most Latin American countries, transport costs are a greater barrier to U.S. markets than import tariffs. Sánchez et al. (2003) find that port efficiency is an important determinant of shipping costs (Arvis et al. 2013). Results obtained for a sample 178 countries over the 1995–2010 period indicate that maritime transport connectivity and logistics performance are very important determinants of bilateral trade costs. UNCTAD’s Liner Shipping Connectivity Index (LSCI) and the World Bank’s Logistics Performance Index (LPI) are together a more important source of variation in trade costs than geographical distance, and the effect is particularly strong for trade relations involving the South. Recent research has examined various aspects of maritime connectivity. Kumar and Hoffmann, (2002), Marquez Ramos et al., (2007), Wilmsmeier and Martínez-Zarzoso, (2010), Wilmsmeier and Hoffmann (2008) and Wilmsmeier et al., (31) incorporate measures of “connectivity” into research on maritime transport costs. Wilmsmeier (2014) analyses the effect of liner shipping network conditions on transport costs from different regions to South America. He also shows a decreasing effect of maritime services supply on transport cost and investigates to what extent the structure of the deployed fleet for directly connected regions contributes to the level of transport costs. Asturias and Petty (2012) conclude that distance becomes statistically insignificant in a trade model when two ports are connected by a direct liner shipping service. Angeloudis et al., (2006) and Bichou, (2004) look at connectivity in the context of maritime security. McCalla et al., (2005) measure intermediacy and connectivity for Caribbean shipping networks and (Notteboom, 2006b) for seaport systems. Notteboom, (2006a) also investigates the time factor in liner shipping services. Kosowska-Stamirowska et al. (2016) provide an historical analysis of topological changes of the maritime trade network and how they translate into navigability properties of this network based on the Lloyd’s Shipping Index.

Another still burgeoning strand of the trade literature has attempted to assess the impact of maritime connectivity on bilateral exports (Wilmsmeier and Hoffmann 2008). Findings based on a sample of 189 freight rates of one company for the Caribbean show that trade routes with only indirect services (i.e., including transhipments) induce higher transport costs. Their estimates suggest that transhipment has the equivalent impact on freight rates as an increase in distance between two countries of 2612 km (Helble 2014, p. 2). Using a gravity model approach based on exports data of the 14 Pacific developing member countries of the Asian Development Bank for the time period 2011–2013 find that a direct shipping connection more than doubles trade in goods imports (Fugazza 2015). Using a gravity model approach based on a novel dataset on maritime connections for a sample of 178 countries collected over the 2006–2012 period finds that the absence of a direct connection is associated with a drop in exports value varying between 42 and 55%.

Analytical contributions, including those cited previously, dealing with the assessment of transport costs components or with the assessment of connectivity on bilateral exports are based on either single dimension indicators, such as the existence or not a direct maritime connection, or on bilateral indicators of connectivity constructed using unilateral measures of the later and as such lacking a true bilateral nature. Hoffmann et al. (2014) first propose a truly bilateral index of liner shipping connectivity, the Liner Shipping Bilateral Connectivity Index (LSBCI). Their LSBCI is an extension of UNCTAD’s already existing country-level Liner Shipping Connectivity Index (LSCI) (UNCTAD STAT, n.d.) based on a proper bilateralization transformation. Computation of the index for the year 2010 reveals that the top 100 LSBCIs are found on connections between 23 countries and that the top 250 LSBCIs are found on connections between 41 countries. The highest LSBCI values are obtained for intra-regional routes, notably intra-Europa and intra-Asia. Several Asia-Europe connections are also among the top 20.

This paper builds on (Fugazza 2015) and (Hoffmann et al. 2014). It contributes to both the literature on maritime connectivity and its definition and on the literature on the impact of trade costs and their components on trade. Its contribution is twofold. First it presents a revised version of the LSBCI which provides an overall view of maritime connectivity.^Footnote1 Second, the impact of the revised LSBCI and of its components on bilateral exports of containerizable goods is assessed using a comprehensive set of country pairs observed for 8 years during the period 2006–2013.

The rest of the paper is organized as follows. Next section presents the data used for the construction of the LSBCI and the empirical exercise. Components of the proposed LSBCI section discusses the components of the revised version of the LSBCI and presents some descriptive statistics. Stylized facts of the revised LSBCI are commented in The LSBCI section. Empirical analysis section is dedicated to the assessment of the impact of the revised LSBCI and of its components on bilateral exports of containerizable goods. Concluding remarks section concludes.

Data

In order to identify the role of maritime connectivity on bilateral exports, our empirical assessment follows a two-step approach.

The first and most conspicuous step consists in constructing a revised version of the LSBCI. The underlying raw data is obtained from Lloyds List Intelligence (formally Containerisation International On-line) (“Lloyd’s List Intelligence – Containers,” n.d.). The dataset gives all the existing direct country pair connections and includes inter alia the number of ships sailing in this route, the TEU capacity of the largest vessel per direct route, the number of operators per route (both those who operate their own vessels and those who do not). The information is obtained annually, in the month of May. The data covers the reported deployment of all containerships at a given point in time. This methodology allows for comparisons over time, as the “sample” is always complete. UNCTAD started the systematic annual gathering of data in 2004 on the country level and in 2006 on the pair-of-country level. In addition to the LSBCI itself and its components which are defined and discussed in detail in next section, two novel variables are retrieved from this data: a variable indicating the number of transhipments necessary to connect any pair of countries and, the effective maritime distance to be covered between any pair of countries. Note that only in the case of a direct maritime connection, the effective (computed) maritime distance coincides with sea distance. Note also that information on the number of transhipments necessary to connect any pair of countries is symmetric: if two transhipments are necessary to move containers from country C to country D, then the same number of transhipments is necessary to move containers in the opposite direction from D to C.

The second step consists in merging the above dataset with a set of gravity variables. Exports data is retrieved from UN COMTRADE, the reference international trade statistics database. Geography and policy variables are extracted from the CEPII gravity dataset as described in Mayer (2011). GDP data is taken from UNCTADstat database. Once merged these two datasets allow us to assess the impact of bilateral maritime connectivity. This is discussed in Empirical analysis section.

Components of the proposed LSBCI

The LSBCI is meant to reflect specifically the liner shipping connectivity between pairs of countries. In that context other aspects of connectivity such as distance are excluded. Distance between countries, and the level of overall connectivity of individual countries are of course also relevant for bilateral trade or trade costs. However, as regards the bilateral liner shipping connectivity as such, we aim at capturing this as a stand-alone factor.

With respect to the (Hoffmann et al. 2014) version of the LSBCI we replace the component reflecting the number of common connections that are reached with a single transhipment with the geometric mean of the number of direct connections for country in the pair. We are then proposing to include the following 5 components in the LSBCI: 1) the number of transhipments required to get from country j to country k; 2) the number of common direct connections; 3) the geometric mean of the number of direct connections each of the two countries; 4) the level of competition on services that connect country pairs; 5) the size of the largest ships on the weakest route.

The following sections briefly discuss the rationale for the inclusion of each component and present some stylized facts. The latter are based on a sample of 138 coastal countries (9453 country pairs) whose connectivity has been informed once a year during the period running from 2006 to 2013. The year 2007 is not reported due to unavailability of observations.