Contents and main findings of the thesis: The thesis concentrates on analyzethe impact of liner shipping connectivity and other factors such as GDP, GDPper capita, exchange rate, trade o
The rationale of the research
International trade is a vital component of the global economy, significantly influencing the growth of the marine logistics industry The United Nations Conference on Trade and Development (2015) highlights that maritime transport is essential for international trade, accounting for approximately 80% of global trade and over 70% of its value The shipping industry facilitates economic activities across different regions, with container shipping services increasingly popular for transporting manufactured goods This network allows exporters and importers to engage in trade without the need for chartering ships for every transaction Today, a comprehensive network of regular container shipping services connects nearly all countries through hub ports Additionally, data on maritime shipping and ports is crucial for understanding international trade growth, as evidenced by the World Bank's investment of over US$ 21.4 billion in more than 360 port and waterway projects since the 1950s.
Z and Kneller (2016) highlighted the correlation between the early adoption of port containerization and trade development between countries The liner shipping connectivity index (LSCI), established by the United Nations Conference on Trade and Development (UNCTAD) in 2004, serves as a key metric for assessing maritime transport It measures the integration of individual economies within the global liner shipping network (GLSN) Notably, liner shipping, which involves transporting goods via ocean-going container ships on set routes, represents approximately 70% of the cargo value moved by sea (UNCTAD, 2017) This study seeks to explore the impact of liner shipping connectivity on international trade by evaluating merchandise exports and imports.
Aims and objectives
This research aims to assess the impact of liner shipping connectivity on global trade, incorporating factors such as total trade, the liner shipping connectivity index, GDP, GDP per capita, exchange rates, trade openness, and political stability By exploring the long-term effects of liner shipping connectivity on international trade, this study contributes to the existing empirical literature Additionally, it offers recommendations for Vietnam to enhance its maritime transportation to boost international trade.
This study aims to establish the relationship between liner shipping connectivity and foreign trade across nearly all countries It examines how factors such as GDP, GDP per capita, exchange rates, trade openness, and political stability influence international merchandise trade, utilizing high-quality, updated World Bank data The objective is to provide precise estimates of the effects of liner shipping connectivity on international trade, ultimately recommending actionable strategies for Vietnam to enhance the efficiency of maritime transport for long-term benefits in global trade The analysis is conducted quantitatively, leading to well-informed recommendations.
The theory of time allocation plays a crucial role in economic development research, serving as a foundational model in this thesis.
Scope of research
In regard to the research content
Liner shipping is crucial for the import and export of goods in international trade, serving as a key indicator of maritime connectivity and operational efficiency in ocean freight This study focuses on analyzing the impact of maritime connectivity, particularly liner shipping connectivity, on the movement of goods between countries, highlighting the significance of sea transport in facilitating international trade.
In regard to the research space
This study enhances existing research by examining liner shipping connectivity and merchandise trade across 113 countries globally Additionally, it explores key macroeconomic factors influencing international trade, including GDP, GDP per capita, exchange rates, trade openness, and political stability.
In regard to the research time
The research examines the influence of liner shipping connectivity on international trade from 2011 to 2020, utilizing a contemporary dataset to improve the relevance and applicability of the findings.
Research questions
This research tried to answer the following questions:
1) What are the impacts of liner shipping connectivity on international trade?
2) What are the recommendations for Vietnam to increase liner shipping connectivity and the efficiency of maritime transport?
Research method
I conducted a study on this subject using logical reasoning and gathered secondary data from the World Bank for at least 113 countries However, the dataset used in the study has some information gaps.
To achieve the appropriate format for the dataset, I utilized Microsoft Excel and STATA software during the cleaning process The resulting data is converted into panel data, showcasing information across multiple time periods.
For this topic, the author uses the ordinary least squares (OLS), fixed effect model (FEM) and random effects model (REM) as data analysis methods.
Structure of the research
Besides the introduction, conclusion, list of references and appendices, the thesis includes 5 chapters:
Chapter 1: Theoretical background on liner shipping connectivity, international trade and the impact of liner shipping connectivity on international trade.
Chapter 3: Current situation of liner shipping connectivity and international maritime trade.
Chapter 4: Model specification, research methodology and estimation results.Chapter 5: Research discuss and recommendations for Vietnam.
THEORETICAL BACKGROUND ON THE IMPACT OF
Definition of liner shipping
Liner shipping, as defined by the World Shipping Council, is the transportation of goods via high-capacity ocean-going vessels that follow fixed routes and schedules This innovative service has transformed global logistics, enabling even small importers and exporters to engage in international trade With the advent of containerized liner shipping, these businesses can now utilize a shared network of global routes to efficiently transport their goods, a process that was previously impractical due to the high costs of chartering entire ships for limited cargo.
Liner shipping companies efficiently manage port arrivals by aligning their ship schedules with anticipated cargo traffic levels Additionally, port operators enhance revenue by optimizing container capacity on ships based on current cargo trends.
C Ernest Fayle defines liner services as a fleet of ships, owned or managed collectively, that operates on a fixed schedule between designated ports These services act as common carriers, transporting goods or passengers that are prepared for shipment by the scheduled sailing dates This distinction highlights the difference between trucker services and liner services.
A liner service operates on a fixed itinerary, requiring participation in a regular schedule and the acceptance of cargo from all customers, regardless of capacity An example of this is CMA CGM’s South China Sea Service, which connects Asia with the West Coast of North America.
Figure 1.1: CMA CGM’s South China Sea Service between Asia and West
The six-port liner service operates weekly, connecting Vung Tau, Nansha, Hong Kong, Yantian, Kaohsiung, and Long Beach Utilizing seven vessels, this service completes a round voyage in 49 days, encompassing the journey from Vung Tau to these ports and back.
The liner shipping industry, a key segment of the freight market, focuses on the transportation of goods in secured closed containers on vessels Originating in the mid-19th century from adaptations of sailing ships, liner shipping has evolved to become the dominant sector in maritime transport, now responsible for over 50% of all containers moved by sea.
Liners run on established routes and adhere to set schedules connecting designated ports Typically, they are owned or managed by major shipping firms that also operate tramp cargo ships and various other cargo vessels.
Liner shipping is the most economical method for transporting cargo, utilizing various vessels such as container ships, bulk carriers, tankers, and specialty ships.
Types of liner shipping
Cargo ships - they come in a variety of sizes and have big hydraulic hatches that cover the hold Perishable goods are sometimes stored in dedicated refrigerated compartments on these ships.
Container ships — with 20-40ft long containers that can be readily loaded and unloaded into and off the vessel for ultimate road or rail transit
Bulk carriers are primarily used to transport wood chips, cereals, and other goods that are put into the hold directly.
Refrigerated ships, sometimes known as Reefers, are vessels that transport perishable goods that require temperature control, such as meat, fish, and dairy products.
Roll-on/roll-off ships are specialized cargo vessels designed for the transportation of wheeled goods, including automobiles These ships are equipped with built-in ramps, enabling drivers to easily drive vehicles directly onto and off the vessel.
Tankers are vessels that transport oil or other liquids or gases.
Barges — to improve storage space, cargo container ships frequently pull barges behind them.
Advantages and disadvantages of liner shipping
Sea freight is crucial for international trade, responsible for 80% of the total volume of goods transported globally Each year, approximately 6,000 billion tons of goods are moved via sea, covering a distance of around 25 trillion tons of nautical miles.
Maritime transportation, specially liner shipping plays a crucial role in international trade because:
Ships are the most efficient mode of transportation for moving large cargo loads, boasting a storage capacity that far exceeds that of railways, aircraft, and trucks.
Container shipping is the most cost-effective transportation method, as these ships typically set sail fully loaded, which minimizes the cost per container Additionally, importers and exporters have the option to share a container with others if they do not need the entire space for their goods.
It is secure and dependable: Ships are less weather-dependent than planes, therefore weather rarely delays their departures or arrivals.
Slow Speed: Ocean transportation is a slower mode of transport that is only suitable for goods having a long lead time Ocean freight might take up months to deliver goods
Ocean transportation carries significant risks due to the extended duration from the loading port to the destination port, which can lead to potential delays and weather-related issues that may damage cargo.
Many regions face a significant lack of infrastructure, particularly in port and terminal facilities, which hinders the ability to accommodate large container ships Additionally, establishing container-based networks typically demands a considerable initial investment.
Delays are possible: Ships operate every week, and a variety of challenges develop on a regular basis It's always possible that the delivery will be delayed.
Liner Shipping Connectivity Index
Liner Shipping Connectivity Index (LSCI) is one of the most important indexes that can assess the marine transport performance of a country.
The United Nations Conference on Trade and Development (UNCTAD) developed the liner shipping connectivity index (LSCI) to evaluate the shipping linkages of countries, with a baseline value of 100 established in 2004 This index, which encompasses data from 157 economies, provides an annual and comprehensive overview of global interconnectedness in marine freight transport A higher LSCI score indicates a greater ability for economies to engage in international trade and reflects the capacity of container transport firms to enhance their market reach The LSCI is calculated based on five key components: (1) the number of shipping lines servicing a country, (2) the size of the largest vessel in service (measured in TEU), (3) the number of services connecting a country to others, (4) the total number of vessels operating in a country, and (5) the total capacity of these vessels (also in TEU).
1 The total number of ships deployed from and to the ports of a country This element could suggest a high frequency of services or a large number of berths at ports The greater the number of ships passing through a country, the stronger the connectivity.
2 The overall container carrying capacity of ships that provide services from and to the ports of a country, expressed in Twenty-foot Equivalent Units (TEU) The count will be based on the ship's total capacity As a result, a greater total TEU capacity is likely to imply more available space, and an opportunity value to perform more trade shipping more cargo-filled containers, or schedule at the lowest rate possible when ships have enough available capacity, appealing businesses to ship at the best price.
3 The number of businesses that offer services from and to a country's ports.The number of companies does not always imply that they are owned by the particular country Foreign corporations move most of a country's trade,and all major liner shipping carriers do business by transporting imports and exports from other countries When more carriers compete for commerce in a country, exporters and importers have more options and pay lower freight costs.
4 The number of liner services connecting the ports of a country This factor determines how efficiently containers travel via liner shipping More particularly, how those containers can move with the fewest connections necessary, possibly even without the requirement for transshipments, to reach their destination.
5 The largest ship that departs from or arrives at a country's port, as calculated in total TEU This component is utilized as a measure of infrastructure and economies of scale Ports must provide enough equipment, such as cranes, and dredge their access channels in an attempt to attract the largest ships to dock.
The components (1) to (5) are closely related to trade and production due to transport costs Fewer transshipments (1) or more direct connections (2) indicate firm-level scale economies, resulting in lower average costs and competitive pricing As shipping is capacity-driven and involves quantity rivalry, an increase in service providers (4) is likely to reduce prices due to heightened competition and lower mark-up pricing Additionally, more direct connections (3) can lower average costs, but they may also indicate market segmentation, which aligns with Krugman's new trade theory (1980) regarding profits from product variety and market heterogeneity.
The impact of liner shipping connectivity on international trade 10 1.3 The gravity model in international trade
Liner container transport is the predominant method for shipping manufactured goods, utilizing container ships that follow established routes to load and unload cargo at various ports This system enhances accessibility to export markets through reliable ship schedules and a comprehensive cargo network, making shipping services highly preferred The rise of containerized transportation has significantly increased sea transport's market share, especially for manufactured products Containerization enables small and large exporters and importers of containerizable goods to engage in trade across vast distances, even when individual transactions do not justify chartering an entire ship Today, a global network of regular container shipping services connects nearly all countries, facilitated by transshipment operations at key hub ports.
A high Liner Shipping Connectivity Index score reflects enhanced access to inland and port facilities, emphasizing the importance of regular port connectivity This index assesses both transportation connectivity and the facilitation of international trade By integrating into the transportation network, countries can capture a larger market share and achieve strategic goals across broader geographic areas Consequently, nations with strong maritime connectivity rankings tend to foster a positive environment for international commerce (Varbanova, 2017: 193).
The Liner Transportation Connectivity Index (LTCI) highlights the growing trend of regional freight transportation, emphasizing the importance of robust connections within ports and safe hinterland access This network not only reduces transportation costs but also fosters economic prosperity through access to vast export markets Despite economic challenges, the density of transportation services and geographical expansion indicate a significant volume of international trade The LSCI serves as a crucial tool for assessing transportation connection levels, facilitating trade, and enabling liner operators to strategize for increased market share Countries with high LSCI ratings are more engaged in international trade, characterized by higher exports and transshipments through liner shipping hubs, although the low proportion of direct links suggests an anticipated increase in transshipments.
The development of liner transportation networks is shaped by the strategic objectives of cargo businesses responding to sender service demands Consequently, trade movements influence the positioning of ports within these networks Key factors such as the number of ships, service frequency, port capacity, and cargo specifications play a crucial role in network structure Transportation service frequency is affected by the loading capacity of equipment, the number of port calls, and stops at intermediate ports (Varbanova, 2017:192) Additionally, marine transportation volume is influenced by transportation costs and service availability, with infrastructure, port location, and international trade facilitation measures all contributing to the connectivity of transportation networks.
A port's key features include its connectivity to the hinterland, robust infrastructure, and capacity, along with pier and dock accessibility Additionally, customs transactions, transportation corridor regulations, and port management policies play crucial roles in the international transportation network Effective ground transportation from ports, advanced logistics systems, and the safety of domestic transport are vital for reducing international trade costs.
1.3 The gravity model in international trade
The gravity model is a crucial instrument in international trade, widely utilized in numerous scholarly articles and research studies Its significance lies in its ability to estimate the impacts of trade-related policies, making it a focal point for researchers With the growing availability of data from both developing and developed nations, the gravity model serves as an excellent foundation for addressing various research inquiries related to policy formulation and implementation, a concept initially introduced by Tinbergen.
The force model, introduced in 1962, analyzes the impact of various factors on international trade across different regions, time periods, and market segments Disdier and Head (2008) utilized this model to assess the effect of geographical distance on exports, drawing from a dataset of 1,052 observations Additionally, Leamer and Levinsohn (1995) noted that the force model offers a comprehensive and persuasive perspective on empirical economics.
The gravity model in trade illustrates that trade flows are directly proportional to the gross domestic product (GDP) of countries and inversely proportional to the geographical distance between them This model draws parallels to Newton's gravity formula in physics, hence its name Tibergen's (1962) foundational formula for the gravity model encapsulates these relationships succinctly.
F =AGDP GDP DIS ij i β1 j β2 β3 e u ij where:
Fij: the trade flow between countries i and j
A: the coefficient of attraction or hindrance
GDPi and β : gross domestic product of country i and its coefficient 1
GDPj and β : gross domestic product of country j and its coefficients 2
DIS and β : distance between 2 countries i, j and its coefficient.2 uij: random error ln(F ij )=A+ β 1 ln(GDP i )+ β 2 ln(GDP j )+ β 3 ln(DIS)+u ij
Scholars have expanded the gravity model in trade analysis by incorporating additional factors beyond just economic size and geographical distance For instance, Thai Tri Do (2006) included population and real exchange rates, while Rault et al (2007) introduced economic disparity between countries and trade agreements as dummy variables in their model.
LITERATURE REVIEW
Liner shipping connectivity and international trade
In the era of globalization, countries are increasingly interconnected through the global supply chain, making it crucial to evaluate their trade competitiveness based on this integration (Christopher, 2016) The global maritime freight network serves as the backbone of this supply chain, highlighting the importance of "liner shipping connectivity" as a key area of research in shipping and logistics.
In the realm of maritime logistics, connectivity refers to the extent to which countries or ports are integrated into the global transportation network, as described in 2019 This concept highlights the significance of a position within the liner shipping network.
Recent studies highlight the critical impact of transport costs and infrastructure on trade and access to international markets Anderson and van Wincoop (2003) found that transportation expenses represent an average ad valorem tax equivalent of 21%, based on a gravity model analysis of US data Additionally, Arvis et al (2013) identified port efficiency as a key determinant of shipping costs Furthermore, research involving 178 countries from 1995 to 2010 indicates that maritime transport connectivity and logistics effectiveness are significant predictors of bilateral trade costs.
The Liner Shipping Connectivity Index (LSCI) from UNCTAD and the Logistics Performance Index (LPI) from the World Bank significantly influence trade costs, particularly for trade connections with the South, more so than geographical distance Research by Wilmsmeier and Hoffmann (2008) indicates that enhanced port infrastructure and liner shipping connectivity (LSC) lead to reduced freight charges in the Caribbean This reduction in costs has the potential to stimulate increased manufacturing and promote economic growth.
Arvis et al (2013a) found that the liner shipping connectivity index (LSCI) and logistics performance index (LPI) significantly predict trade costs across 178 countries Helble (2014a) demonstrated that direct transit linkages can more than double trade volume Additionally, Petty and Asturias (2012) noted that increased shipping line connections to a port lead to lower prices and make distance a statistically insignificant factor.
According to UNCTAD (2014), reliable and frequent line services are crucial for connecting to international markets, enhancing the global competitiveness of a country's products Sea shipping plays a vital role in developing shipping networks and ports, with the port's appeal and service diversity serving as indicators of trade competitiveness (Ojala & Hoffmann, 2010) The growth of container transportation is closely linked to the overall expansion of the shipping network.
Ayberk Şeker (2020) emphasized that a high liner shipping connectivity index signifies improved access to port and hinterland facilities, necessitating frequent connections between ports This index reflects both the network connectivity in transportation and the ease of international trade Enhanced connectivity enables countries to capture larger market shares and achieve strategic objectives across broader geographical areas Consequently, nations with elevated liner shipping connectivity index scores engage more actively in international trade (Varbanova, 2017: 193).
Gross domestic product and international trade
The relationship between GDP and international trade has garnered significant attention from economists in recent years, with numerous studies highlighting its importance A notable study involving 100 countries revealed that GDP positively influences international trade (Khan, 2005) Furthermore, factors such as economic growth rate, inflation rate, interest rates, and exchange rates also play a crucial role in shaping international trade dynamics Overall, these findings underscore the strong impact of GDP on international trade.
Ewing (2016) examined the connection between Gross Domestic Product (GDP) and international trade from 1980 to 2015, utilizing the ordinary least squares (OLS) method to determine any significant relationship His findings indicated that GDP does not influence international trade, challenging the common belief held by many Western economists Additionally, Nweze (2018) found a negative relationship between GDP and international trade when other factors are excluded.
Research by E Sowell (2016) indicates that international trade is significantly influenced by a country's GDP Countries with higher GDP tend to engage in more international trade, driven by greater purchasing power and demand for goods The article presents data showing that all six analyzed countries experienced positive GDP growth alongside increased international trade While this data does not conclusively establish GDP as the sole factor affecting international trade, it suggests that GDP plays a crucial role in shaping trade dynamics.
Numerous studies indicate a positive correlation between exports and economic growth, suggesting that exports can enhance economic development (Ullah et al., 2009) While the link between export-led growth is well established, the direction of causality remains contested In developing economies, manufacturing sectors may experience significant transformations due to learning, technological advancements, and foreign direct investment (FDI) Even in the absence of formal free trade policies, output can still increase in certain cases Producers may export excess goods when domestic demand lags behind output growth, leading to a potential boost in economic growth through increased exports Conversely, if domestic demand grows faster than industrial output, exports may decline, indicating that rising domestic demand can elevate local production while simultaneously reducing export levels (Lee and Huang, 2002).
GDP per capita and international trade
A country's economic growth rate is measured by GDP per capita Were
In a comparative analysis of African countries, standard growth regression was employed (2015), while Winters and Masters (2013) provided a concise evaluation of empirical studies on the relationship between trade openness and economic growth While earlier research primarily concentrated on exports, it has been suggested that imports also contribute to economic growth Various studies utilizing econometric and non-parametric techniques, including the ARDL model, have been conducted in China (Kong et al 2021; Lin 2000; Sun and Heshmati 2010) These studies reveal a positive correlation between trade volume growth and GDP per capita growth, highlighting the significance of international trade and the structure of high-tech export-oriented trade.
David (2019) demonstrated that GDP per capita for both source and destination countries significantly influences international trade Utilizing a panel data analysis, his research applied the gravity model to examine bilateral trade, exports, and imports between six GCC nations and eight developed countries from 2001 to 2012 The study employed random effects (RE) and ordinary least squares (OLS) techniques, concluding that GDP per capita positively impacts international trade.
Exchange rate and international trade
Exchange rates significantly influence international trade, with extensive research examining the effects of exchange rate volatility The literature presents two contrasting views: one suggests that exchange rate uncertainty has no effect on trade, while the other argues the opposite Numerous studies indicate that both exchange rate levels and volatility play a crucial role in trade dynamics, yet many findings remain inconclusive and contradictory (Aristeriou, Masatci, & Pilbeam, 2016; Dell'Ariccia, 1999; Mukherjee & Pozo, 2011; Rose, 2000).
Between 1965 and 1975, Hooper and Kohlhagen (1978) examined the impact of exchange rate uncertainty on US-German trade, concluding that there was no statistically significant effect Similarly, Gotur (1985) analyzed trade volumes among the United States, Germany, France, Japan, and the United Kingdom, arriving at a comparable conclusion.
An IMF study from 1984 revealed that most empirical research did not find a significant connection between exchange rate fluctuations and trade volume, yet this does not eliminate the potential for such a relationship Bacchetta and van Wincoop (2000) explored this connection and discovered that shocks in exchange rate changes can influence other macroeconomic variables, potentially reducing the exchange rate's effect on trade.
In their 2003 study, the authors investigate the covariance between exchange rate movements and key economic variables, concluding that the critical factor is not merely the fluctuations in exchange rates, but rather how these fluctuations amplify or mitigate the risks faced by businesses and consumers They employ the gravity equation specification to present their findings.
(2001) and the IMF (2004) to evaluate the influence of exchange rate volatility on trade Their empirical findings imply that exchange rate volatility has no effect on export volume.
Critics argue that exchange rate volatility is not a major concern for international trade, as firms can hedge this risk and fixed costs in exports diminish its relevance UNCTAD (2013) explores this by comparing two models: one incorporating exchange rate volatility and misalignment, and the other adjusting for the Balassa-Samuelson effect Their panel analysis confirms that exchange rate fluctuations have minimal impact on trade, yet highlights a significant effect of currency error correction adjustment, revealing that underpricing enhances exports while limiting imports Additionally, Huchet-Bourdon and Korinek (2011) note that exports are more responsive to changes in real exchange rate levels than to fluctuations, particularly affecting agricultural exports.
Gala (2008) highlights the crucial role of competitive currencies in the economic development of East and Southeast Asian countries Marquez and Schindler (2006) analyze the impact of the real exchange rate on China's global trade, revealing that currency appreciation diminishes China's export share while slightly boosting its import share Appuhamilage and Senanayake (2010) find that the depreciation of the Sri Lankan rupee against the Chinese yuan significantly benefits Sri Lanka's exports to China, although price reductions from Sri Lanka negatively affect imports from China Baek (2012) further investigates the dynamics of exports and imports in this context.
71 items between the United States and South Korea and concluded that the exchange rate has an impact on Korea's exports and imports from the United States.
The International Monetary Fund (IMF) (2015a) investigates the relationship between real exchange rates, commodity prices, and trade volumes, confirming previous research findings The study indicates that currency depreciation leads to higher export and import prices, resulting in increased exports and reduced imports Notably, a weaker financial system in the exporting economy, particularly during banking crises, amplifies the growth in exports While the IMF identifies a weakening connection between exchange rates and trade for certain economies due to global value chains, it finds no evidence supporting a disconnect between trade and exchange rates.
Trade openness and international trade
Recent research has explored the link between trade openness and economic growth, with key studies by Dollar (1992), Sachs and Warner (1995), Edwards (1998), and Frankel and Romer (1999) providing empirical support for a positive relationship However, Rodrik and Rodriguez (2000) raised concerns regarding the methodologies and criteria used to assess trade openness A review by Rodriguez (2007) of studies by Dollar and Kraay (2002), Warner (2003), and Wacziarg and Welch (2003) concluded that traditional trade policy metrics do not correlate with economic growth In contrast, Abbas (2014) presented evidence suggesting that trade openness may negatively impact economic growth.
Panagariya (2004) evaluated the argument by Rodrik and Rodriguez (2000), concluding that the evidence from cross-country growth regression supports the validity of outward-oriented policies He notes that disagreements stem from the difficulty in quantifying the protective effects of specific trade barriers While Rodrik and Rodriguez criticize the positive link between trade openness and economic growth, Bhagwati and Srinivasan (2001) find their arguments unconvincing Additionally, Warner (2003) emphasizes that crucial data is often overlooked, highlighting the negative impact of trade restrictions on economic growth.
Political stability and international trade
Trade fosters economic growth, which in turn promotes peace and stability within a nation (Sachs et al., 1995) By providing alternative income sources for rebels, trade can mitigate internal conflict and bolster government authority, thereby discouraging rebellions (Collier and Hoeffler, 1998; Fearon and Laitin, 2003; De Soysa, 2002) Despite this, research on the relationship between trade and political unrest remains limited Notably, politically stable countries tend to have higher export levels (Srivastava and Green, 1986), and democratic governments and political coalitions also play a significant role in this dynamic (Morrow et al.).
(1998), encourage bilateral trade Summary (1989) explains how foreign political variables influence the trade of industrial items in the United States.
Bashir et al (2013) examined the impact of foreign political instability on Chinese exports using data from 121 importing countries between 1988 and 2011 Their analysis, employing alternative dynamic panels and the dynamic system generalized method of moments (SGMM), revealed that foreign political instability negatively affects Chinese exports, while the actual exchange rate and income positively influence them Political instability is known to hinder trade, with stable governments typically exporting more (Srivastava and Green, 1986) Fosu (2003) noted that political instability diminishes expected returns, prompting capital flight and subsequently reducing exports Additionally, factors such as slowing economic growth, income, interest rates, domestic price levels, unemployment, and currency rates also affect imports in politically unstable countries (Collins, 1996; Roubini, 1991).
For a sample of 30 Sub-Saharan African countries from 1967 to 1986, Fosu
A study conducted in 2003 established a connection between political instability and export performance The regression analysis, utilizing Ordinary Least Squares (OLS) estimates and the Hausman-Wu test, indicates that political instability negatively impacts exports to a greater extent than it affects total GDP.
CURRENT SITUATION OF LINER SHIPPING
Current situation of liner shipping connectivity of the world
The global status of liner shipping connectivity has been steadily improving, as it plays a crucial role in enhancing international trade The liner shipping connectivity index is a key metric that reflects this development Figure 3.1 illustrates the country and port-level liner shipping connectivity worldwide in 2020.
Figure 3.1: Country and Port Level Liner Shipping Connectivity of the world in 2020
The LSCI distribution reveals a strong concentration among a few key ports that act as vital gateways for global trade Countries with the highest LSCI values, such as China and Singapore, are heavily involved in international commerce, ranking first and second, respectively, while Korea Rep follows in third place Other notable traders in the top 20 include the United States, Malaysia, Hong Kong, the United Kingdom, and the Netherlands Spain, Belgium, Japan, and Germany also achieve high scores due to their significant transshipment activities Notably, despite its small size, Vietnam ranks among the top 20 LSCI countries with a score of 79.77808 in 2020.
Table 3 1: Top 20 highest LSCI countries in 2020
The Top 20 countries with the highest LSCI index reveal that high rankings are not solely held by large nations; for instance, Singapore and Vietnam, despite their small geographical areas and limited seaport networks, rank prominently Notably, ASEAN countries like Singapore, Malaysia, and Vietnam exhibit high LSCI scores, indicating their potential as regional transportation hubs This advantage leverages Southeast Asia's geographical position, fostering economic growth and creating a conducive environment for commercial activities The high LSCI index reflects ASEAN's ports' strong international connectivity, showcasing their capability to serve as vital links between regional harbors and global markets For example, cargo from Tanjung Priok, Indonesia, is often transshipped in Singapore or Tanjung Pelepas, Malaysia, before reaching destinations like Bangkok, while Chinese exports from Ningbo are routed through Malaysia's Port Klang to Dubai.
Many African countries, despite having strong historical ties to Europe and developing new connections with Asia, struggle with global connectivity This results in a low average score on the LSCI, as they are well-connected to certain economic partners but poorly linked to others Consequently, trade with a broader range of countries is hindered due to insufficient direct connectivity, leading to limited or non-existent trade flows.
Countries along the same coast, such as Chile, Peru, and Ecuador, benefit from shared services that enhance their connectivity and trade opportunities Empirical evidence suggests that nations sharing an ocean engage in more trade with each other Additionally, each common connection increases the potential for trade through a single transshipment The greater the number of shared connections between two countries, like traveling from Brazil to Ecuador via Panama, Jamaica, or the Bahamas, the more interconnected and trade-friendly they become.
Countries sharing the same coastline, such as Chile, Peru, and Ecuador, benefit from enhanced connectivity through common services, facilitating greater trade opportunities Research indicates that nations located along the same ocean engage in more frequent trade with one another Additionally, each shared connection provides an alternative route for transshipment, improving trade efficiency The presence of multiple connections, such as routes from Brazil to Ecuador via Panama, Jamaica, or the Bahamas, strengthens the trade relationships between these countries.
International maritime trade of the world in the recent years
The improvement in liner shipping connectivity has led to increased international trade for countries with a high Liner Shipping Connectivity Index (LSCI) However, according to UNCTAD 2020, the growth of international maritime trade slowed in 2019, reaching its lowest level since the 2008-2009 global financial crisis Long-term trade conflicts and significant policy uncertainty have hindered global economic production and maritime trade expansion, resulting in a mere 0.5 percent increase in maritime trade volume in 2019, compared to 2.8 percent in 2018, totaling 11.08 billion tons Additionally, global GDP growth fell to 2.5 percent in 2019, down from 3.1 percent in 2018, and 1.1 percentage points below the historical average from 2001 to 2008 The negative impact of trade tensions between the world's two largest economies further squeezed manufacturing operations, leading to a 0.5 percent decline in global commerce in goods.
The COVID-19 pandemic significantly affected global maritime trade and supply chains in 2020, yet maritime transportation largely managed to endure the challenges While carriers successfully absorbed the initial shock and adjusted to reduced demand, port and landside operations faced difficulties in adapting Additionally, seafarers encountered a critical crew-change crisis According to UNCTAD, global economic output and goods commerce decreased by 5.4 percent, with international maritime shipments dropping by 3.8 percent to 10.65 billion tons.
Figure 3.2: International maritime trade, by region, 2020 (percentage share in total tonnage)
According to UNCTAD's Review of Maritime Transport 2021, Asia solidified its dominance in global maritime trade in 2020, maintaining a 41% share of total goods loaded and increasing its volume of goods discharged The pandemic significantly impacted Asian trade, particularly on the Transpacific route, where container volumes to North America dropped 13% in early 2020 but rebounded by 36% by the third quarter, resulting in a 2.8% overall gain for the route In contrast, trade between Asia and Europe decreased by 2.6% Despite a slight decline of 0.4% in container port throughput, Asia's resilient containerized trade and rapid export recovery reinforced its status as the global hub for container traffic, handling about two-thirds of it Additionally, Asia's liner shipping connectivity outperformed other regions, with China, Hong Kong, Malaysia, South Korea, and Singapore ranking among the top six most-connected economies in 2020.
In 2020, the Americas ranked second in seaborne import and export volume While liner shipping connectivity remains resilient, the maritime supply chain in Latin America and the Caribbean faces significant challenges, including ensuring staff presence and transporting goods from ports to the mainland The impact of these issues varies by location, with transshipment ports experiencing the most severe effects.
International shipping market in recent years
The global shipping industry has struggled to recover from the economic crisis between 2008 and 2020, following a period of rapid growth from 2005 to 2007 that resulted in an oversupply of ships This oversupply caused a significant imbalance in supply and demand, leading to a sharp decline in freight rates across all segments, including tankers, dry cargo ships, and container ships The Baltic Dry Index (BDI) plummeted to a historic low of 290 points on February 11, 2016, representing only 2.45% of its peak in 2008, and remained mostly below 1,500 points from 2016 to 2020 Similarly, the Baltic Clean Tanker Index (BCIY) for product oil tankers fell to a record low of 306 points on October 1, 2020, while the World Container Index for container ships fluctuated around $2,000/FEU during the same period.
Shipping activities have been significantly impacted by various political and economic factors, including the Central American trade war, US-Iran tensions, the political crisis in North Africa, the nuclear situation in Korea, Japan's earthquake and tsunami, China's economic downturn, and the complexities surrounding the UK's exit from the EU These developments have exacerbated global economic challenges Additionally, rising input costs, such as loan interest, exchange rate fluctuations, and particularly fuel expenses, alongside the implementation of IMO 2020 emission regulations, have severely affected shipping operations Consequently, many major shipping companies, including Korea's Hanjin Shipping, have faced dire financial situations, with some even declaring bankruptcy.
In 2020, the onset of the Covid-19 pandemic significantly impacted the shipping market, leading to a sharp decline in demand across dry ships, oil tankers, and container ships However, by mid-2020, the market began to recover, with the container shipping sector leading the resurgence, followed by the dry cargo ship market in early 2021 By the end of September 2021, the World Container Index had surged over fivefold to reach 10,377 USD/FEU, while the Baltic Dry Index (BDI) exceeded 5,000 points, peaking at 5,409 points in early October 2021.
Development trend of international shipping fleet
In 2020, the international shipping fleet comprised 98,140 ships with a deadweight tonnage (DWT) of 100 or more, totaling approximately 2.061 billion DWT This marked a 4.1% increase compared to 2019, representing the highest growth rate since 2014, although it remains below the levels seen in 2004.
As of 2012, bulk carriers and liquid cargo vessels represented the largest segments of the global fleet, comprising 42.6% and 28.7%, respectively The fastest-growing category was specialized ships, particularly liquefied gas carriers, which saw a growth rate of 7.25% from 2019 to 2020, followed by oil tankers and container ships at 5% According to maritime magazine ALPHALINER, there is a notable trend towards larger container ships, with sizes ranging from 18,000 to 24,000 TEUs By May 2020, there were 117 such vessels, collectively handling 2.36 million TEUs, which accounted for 10% of the global container throughput.
The global fleet's average age is 21.3 years by the number of ships and 10.76 years in deadweight tonnage (DWT) The youngest vessels include bulk carriers at 9.28 years, container ships at 9.91 years, and oil tankers at 10.38 years, while cargo ships average 19.46 years Notably, the largest ships are predominantly in the 0-4 year age group, with oil tankers exhibiting the highest average size, followed by bulk carriers and container ships Over time, vessel sizes have increased significantly to enhance cost optimization and operational efficiency.
Table 3 2: Growth rate of world dry cargo fleet
Rate of increase in number of vessel (%) 2.03 1.3 2.78 1.82 1.64 1.31
Average growth rate vessel size 1.31 1.83 0.95 0.87 2.46 1.73
In recent years, the global freighter fleet has experienced slow growth, with tonnage increasing by only 2.71% to 4.13% and the number of vessels rising by 1.3% to 2.78% To reduce operating costs, vessel sizes are increasing, particularly with the emergence of super container ships capable of carrying 23,000 to 24,000 TEU Additionally, to comply with the International Maritime Organization's stringent environmental regulations, many new ships are being designed to run on LPG fuel or are being equipped with emission scrubbers.
Over the past four years, the global dry cargo fleet has experienced modest growth rates of 2.92% in 2018, 3.96% in 2019, and 3.77% in 2020 As of September 1, 2021, only 669 dry cargo ships have been ordered for construction.
58.1 million DWT, equal to 6.2% of the current dry cargo fleet, of which the largest proportion is Handymax (38%) and Panamax (30%) This is the lowest number in the past 8 years since October 2003 Meanwhile, the number of dry cargo ships to be demolished is also very modest According to the statistics of Clarksosn andBIMCO, in the first 9 months of 2021, the number of dry cargo ships demolished only reached 4.8 million DWT, BIMCO's forecast, this number will increase to 7 million DWT for the whole year of 2021, down 57% over the same period in 2020.The low growth rate of the dry cargo fleet will last for at least 2 years, as it takes at least 24 months from order to handover.
MODEL SPECIFICATION, RESEARCH
Model specification
In this study, I use the gravity model to indicate the impacts of independent variables on international trade and especially the impact of liner shipping connectivity on international trade.
The model in this study is built on the basis of the formula of Tinbergen
In 1962, the study builds upon earlier models, refining and integrating new elements discussed in chapter 2 It highlights the connection between international trade and various influencing factors, particularly emphasizing liner shipping connectivity, which is articulated through a specific formula.
The total trade of country "i" at time "t" (TTR) is modeled as a function of several key variables: the liner shipping connectivity index (LSCI), gross domestic product (GDP), GDP per capita, trade openness, and political stability, along with an error term (ε) This equation, represented as TTR = β0 + β1LSCI + β2GDP + β3GDPpercapita + β4ER + β5TradeOpenness + β6PoliticalStability + ε, reflects the complex interplay of factors influencing international trade The use of this approach is widely accepted in the literature, acknowledging that various elements can significantly impact trade dynamics.
This study focuses on key variables including Total Trade, Liner Shipping Connectivity, Gross Domestic Product (GDP), GDP per Capita, Exchange Rate, Trade Openness, and Political Stability, along with their respective indicators The indicators utilized in this research are sourced from the World Bank (2020).
Table 4 1: Sign and meaning of variables in model
Dependent variable Total trade TTR
Liner shipping connectivity index LSCI
Trade openness TradeOpenness Political Stability PoliticalStability
Total trade refers to the sum of a country's merchandise exports and imports In this analysis, total trade is calculated by combining the total merchandise exports with the total merchandise imports The World Bank defines merchandise exports as the free on board (f.o.b.) value of goods sent to other countries, while merchandise imports are defined as the cost, insurance, and freight (c.i.f.) value of goods received from abroad, both measured in current U.S dollars.
This article evaluates the impact of the Liner Shipping Connectivity Index (LSCI) on international trade, specifically focusing on the exchange of goods between countries The total trade index is determined by the combined merchandise exports and imports, measured in current US dollars.
The LSCI provides for the evaluation of container shipping maritime connectivity, as well as comparisons across nations and over time It is built around five annual data points:
(1) The number of shipping lines servicing a country
(2) The size of the largest vessel used on these services (in TEU)
(3) The number of services connecting a country to the other countries
(4) The total number of vessels deployed in a country
(5) The total capacity of those vessels (in TEU)
Hypothesis 1: Liner shipping connectivity has positive impacts on international trade
GDP (Gross Domestic Product) is the total monetary or market value of all finished goods and services produced within a country's borders in a given time period
GDP can be calculated in 3 ways:
Method 1: Expenditure method: add up all the expenditures within that country for purchasing and using services, including household expenditure (C), government spending government (G), total investment (I), net exports (NX)
Method 2: Cost method to calculate total wages (W), interest (I), profit (Pr) rental costs (R), net indirect taxes (Ti) and depreciation of fixed assets (De) generated in the domestic economy
Method 3 involves calculating GDP by summing the added value at each production stage within a specific timeframe Essentially, GDP serves as a key indicator for evaluating the overall growth rate and development level of a country or region Economic development typically leads to increased demand for imports and exports, which in turn drives the need for enhanced transportation of goods across borders.
In this article, I will estimate the impact of economic growth on international trade with the proxy variable GDP in this paper
Hypothesis 2: GDP has positive impacts on international trade
The third independent variable in the model is economic growth, represented by GDP per capita The World Bank defines GDP per capita as the gross domestic product divided by the midyear population It encompasses the total gross value added by all resident producers in the economy, including product taxes and excluding subsidies not accounted for in product value This measure is calculated in current U.S dollars without accounting for depreciation of fabricated assets or the depletion and degradation of natural resources.
As GDP per capita increases, the potential for international trade to increase increases as well As a result, I have:
Hypothesis 3: GDP per capita has a positive impact on international trade
The official exchange rate is determined by the government or the legal exchange market, reflecting a monthly average calculated annually, specifically comparing the local currency to the US dollar.
The exchange rate has an inverse relationship with merchandise trade, as supported by theory and previous studies When the domestic currency's exchange rate increases, the foreign currency earnings from exports decline, leading to reduced revenue in local currency terms This discourages export activities, resulting in an overall decrease in export performance.
When the domestic currency appreciates or the exchange rate rises, import turnover tends to increase This is because higher currency value makes imports cheaper, resulting in lower import costs and a subsequent rise in import quantities.
Therefore, the impact of exchange rate on international trade depends on the volume of merchandise export compared to merchandise import of a country As a result, in this study, I will have:
Hypothesis 4: Exchange rate has an impact on international trade.
Trade openness refers to how accessible a nation's markets are to foreign competition, indicating the level of integration of foreign companies and individuals within the domestic economy An economy is deemed "open" when it facilitates the free movement of capital across borders, removes tariffs on imports and exports, ensures non-discriminatory treatment for foreign businesses, and permits foreign ownership of domestic companies without restrictions.
Trade openness significantly influences international trade by enabling countries to specialize in the production of goods and services they are most efficient at, while importing others For instance, when one country lacks oil but another has it, an open trading relationship allows both nations to refine oil and access resources at reduced costs This specialization enhances production efficiency and lowers overall costs Consequently, trade openness fosters increased trade between countries Thus, Hypothesis 5 posits that trade openness positively impacts international trade.
Political stability and the absence of violence, as reported by the Worldwide Governance Indicators, assess the likelihood of government destabilization through unconstitutional or violent means, including terrorism A stable political environment enhances trade relationships and encourages foreign investment, leading to an increase in merchandise trade Therefore, it can be hypothesized that political stability positively impacts international trade.
Table 4 2: Expected results of the variables in the models
Variable Expected sign of coefficients Basis
Liner shipping connectivity + Şeker, Ayberk (2020)
Gross Domestic Product + Ho, Catherine S F (2013)
GDP per capita + Matyas (1997)/Dell'Ariccia
Hooper and Kohlhagen (1978)/ Bacchetta and van Wincoop (2000)
Trade Openness + Abbas (2014/ Rodrik and
Political Stability + Cukierman et al 1992
Data and variables description
This study aims to explore the effects of liner shipping connectivity on international trade To enhance the accuracy of the results, the analysis incorporates the GDP of the country as an additional variable influencing international trade.
The liner shipping connectivity index is a crucial factor in assessing a country's logistics performance An econometric analysis involving 113 coastal economies worldwide was conducted to explore the impact of liner shipping connections on international trade, with GDP included as an independent variable Data from the World Bank (2020) was utilized, focusing on panel data from 2011 to 2020, covering a decade The selection of countries and the sample period was determined by data availability, resulting in a balanced panel In this study, total trade, defined as the sum of merchandise exports and imports, serves as the dependent variable, with all trade data also sourced from the World Bank (2020).
In addition to GDP per capita, the model incorporates exchange rate, trade openness, and political stability to enhance the accuracy of the research findings, with all variables sourced from the World Bank 2020.
The interpretation and data sources for each variable in the analysis are presented in Table 4.3 below
Table 4.3 Definition of variables and data sources.
Type of variable Variable Definition Unit Data source
The sum of merchandise export and merchandise import
Independent variable LSCI Liner shipping connectivity index Score World bank
Independent variable GDP Gross Domestic
Independent variable GDPpercapita GDP per capita Dollar World bank
Independent variable ER Official exchange rate LCU per
Independent variable TradeOpenness Trade (%GDP) % World bank
Political Stability and Absence of Violence/Terrorism:
This study utilized secondary data sourced from the World Bank, covering the period from 2011 to 2020 across 113 countries The subsequent sections will detail the specific data for all variables included in the analysis.
Table 4.4: Description of the variables
Variable Obs Mean Std Dev Min Max
Through the descriptive statistics table, the values calculated based on Stata,
I get the following values: minimum value; maximum value; mean of 113 coastal economies for 10 years from 2011 to 2020
The analysis of total trade reveals 1,130 observations, with an average value of USD 260 billion from 2011 to 2020 Notably, China recorded the highest total trade value of USD 4,647 billion in 2020, highlighting its efficiency in international goods trade In contrast, Sao Tome and Principe reported a minimum value of USD 143 million in 2012, indicating significant inefficiencies in its international trade.
The Liner Shipping Connectivity Index, comprising 1,130 observations, averaged 31.33 from 2011 to 2020 China's impressive score of 162.37 in 2020 highlights its shipping efficiency, while Moldova's minimum value of 0.64 reflects significant restrictions in container shipping within the country.
The dataset includes 1,130 observations of Gross Domestic Product (GDP) from 2011 to 2020, with an average GDP of USD 641 billion The highest recorded GDP value is USD 21,433 billion, attributed to a specific country.
In 2019, the United States demonstrated significant economic development, while Sao Tome and Principe recorded a minimum economic value of USD 235 million in 2011, highlighting the progress of its economy.
The dataset includes 1,108 observations for GDP per capita, with an average value of \$15,603.53 from 2011 to 2020 Norway recorded the highest GDP per capita at \$102,913.45 in 2021, highlighting its large economic scale, while Turkey had the lowest at \$71,991 in 2014, indicating a smaller economic scale.
The dataset includes 1,104 observations of exchange rates from 2011 to 2020, with an average exchange rate of 1259.639 The highest recorded exchange rate is 42,000, attributed to the United Arab Emirates in 2016, highlighting the country's significant economic strength Conversely, the lowest exchange rate is 0.3, observed in the United Kingdom in 2015.
Trade openness is represented by 1,065 observations, with an average value of 88.3% from 2011 to 2020 Notably, Hong Kong recorded the highest trade openness at 442.62% in 2013, indicating a highly open trade environment In contrast, Sudan exhibited the lowest trade openness at just 0.8% in 2020.
The analysis of Political Stability and Absence of Violence/Terrorism reveals 1,130 observations, with an average score of -0.16 from 2011 to 2020 Notably, Iceland achieved the highest score of 1.6 in 2019, indicating significant political stability, while Sudan recorded the lowest score of 0.8 in 2020, highlighting ongoing challenges in governance.
4.2.3 Estimation method and Econometric tests
This thesis employs the panel data estimation method, specifically utilizing the pooled least squares (Pooled OLS) approach It examines two models: the random effects model (REM) and the fixed effects model (FEM) According to the Stata user manual, the research model is structured as a pooled model.
The model examines the relationship between total trade (Y) and various explanatory variables (Xi) It can be expressed as a Pooled OLS model, represented by the equation: \$$\ln(TTR) = \beta_0 + \beta_1 \ln(LSCI) + \beta_2 \ln(GDP) + \beta_3 \ln(GDP \text{ per capita}) + \beta_4 \ln(ER) + \beta_5 \text{Trade Openness} + \beta_6 \text{Political Stability} + \epsilon\$$ This formulation highlights the impact of factors such as economic indicators and political conditions on trade dynamics.
Pooled regression, a method of least squares (OLS) estimation, is suitable only when there are no separate country and time factors According to Gujarati (2004), neglecting these dimensions can lead to biased estimation results Therefore, fixed effects (FEM) and random effects (REM) models are more appropriate as they account for both time and individual factors The FEM model recognizes that each entity, such as a country, possesses unique characteristics that influence the explanatory variables, allowing for a correlation between the residuals and these variables By controlling for these time-constant characteristics, FEM enables the estimation of the net effects of regressors on the dependent variable, ensuring that the unique traits of each entity do not correlate with those of others.
The REM model has the following form:
Where u is the random error reflecting the difference of countries whosei mean is 0 and variance is σ 2e