CPB

Changing Demand for
Maritime Trade
Discussion Paper

178
Pierre Cariou
Kedge Business School,
Bordeaux

Roundtable

Corporate Partnership
Board

178
Pierre Cariou
Kedge Business School,
Bordeaux

Roundtable

Changing Demand for
Maritime Trade
Discussion Paper

The International Transport ForumThe International Transport Forum is an intergovernmental organisation with 60 member countries. It acts
as a think tank for transport policy and organises the Annual Summit of transport ministers. ITF is the only
global body that covers all transport modes. The ITF is politically autonomous and administratively
integrated with the OECD.
The ITF works for transport policies that improve peoples’ lives. Our mission is to foster a deeper
understanding of the role of transport in economic growth, environmental sustainability and social
inclusion and to raise the public profile of transport policy.
The ITF organises global dialogue for better transport. We act as a platform for discussion and prenegotiation of policy issues across all transport modes. We analyse trends, share knowledge and promoteexchange among transport decision-makers and civil society. The ITF’s Annual Summit is the world’s largest
gathering of transport ministers and the leading global platform for dialogue on transport policy.
The Members of the Forum are: Albania, Armenia, Argentina, Australia, Austria, Azerbaijan, Belarus,
Belgium, Bosnia and Herzegovina, Bulgaria, Canada, Chile, China (People’s Republic of), Croatia,
Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, India,
Ireland, Israel, Italy, Japan, Kazakhstan, Korea, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta,
Mexico, Republic of Moldova, Montenegro, Morocco, the Netherlands, New Zealand, North Macedonia,
Norway, Poland, Portugal, Romania, Russian Federation, Serbia, Slovak Republic, Slovenia, Spain, Sweden,
Switzerland, Tunisia, Turkey, Ukraine, the United Arab Emirates, the United Kingdom and theUnited States.

International Transport Forum
2 rue André Pascal
F-75775 Paris Cedex 16
contact@itf-oecd.org
www.itf-oecd.org

ITF Discussion Papers
ITF Discussion Papers make economic research, commissioned or carried out in-house at ITF, available toresearchers and practitioners. They describe preliminary results or research in progress by the author(s)and are published to stimulate discussion on a broad range of issues on which the ITF works. Any findings,
interpretations and conclusions expressed herein are those of the authors and do not necessarily reflect
the views of the International Transport Forum or the OECD. Neither the OECD, ITF nor the authors
guarantee the accuracy of any data or other information contained in this publication and accept no
responsibility whatsoever for any consequence of their use. This document and any map included herein
are without prejudice to the status of or sovereignty over any territory, to the delimitation of international
frontiers and boundaries and to the name of any territory, city or area. Comments on Discussion Papers
are welcome.
Cite this work as: Cariou, P. (2020), “Changing Demand for Maritime Trade”, International Transport Forum
Discussion Papers, No. 2020/04, OECD Publishing, Paris.

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table of contents
Introduction .................................................................................................................................... 4Long-term changes predicted for maritime trades .......................................................................... 4
World population and GDP per capita outlooks ............................................................................ 11World population outlook ......................................................................................................... 13
World GDP outlook ................................................................................................................... 15
World and maritime trade outlooks .............................................................................................. 18
World trade outlook ................................................................................................................. 18
Maritime trades outlook ........................................................................................................... 20
Drivers of future maritime trade ................................................................................................... 22
Conclusions ................................................................................................................................... 26
Notes ............................................................................................................................................ 28
References .................................................................................................................................... 29

Figures
1. World seaborne trade by cargo type, 1970-2017 (in Metric ton in millions) ............................. 5
2. Growth rates of world seaborne trade by cargo type, 1970-2017 ............................................. 6
3. Predicted versus actual maritime trades as a function of GDP per capita ................................ 11
4. World population by region share in 2010 and 2100 (SSP1) .................................................... 13
5. Changes in global value chain trade intensity ........................................................................... 25

Tables
1. World seaborne trade by types of cargo, 1970-2017 (in Metric ton in millions) ........................ 7
2. World seaborne trade by types of cargo, 1970-2017 (in billions of tons-miles) ......................... 8
3. World seaborne trade by group of economies, 1970-2017 (in Metric ton in millions) .............. 9
4. Estimates of the log Maritime trades (unloaded) as a function of log GDP per capita ............ 10
5. World population outlook 2010-2100 in billion and Annual Growth Rate* ............................. 13
6. Share of population older than 65 as a share of population aged 15-64.................................. 15
7. Annual average GDP per capita growth rates per Shared Socio-economic Pathways .............. 16
8. Projected GDP per capita annual growth rate in OECD, non-OECD and selected countries..... 17
9. Forecasted Total Primary Energy Demand (Mtoe) ................................................................... 19
10. World trade to income elasticity (goods) ............................................................................... 19
11. DNV forecasts to 2050 ............................................................................................................ 21
12. Top-15 importers/exporters in 2017 in thousands of Twenty Equivalent Unit (TEU) ............. 23© OECD/ITF 2020

3

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Introduction
The future of maritime trade demand is uncertain by nature. Foresight of what possible future maritime
trade flows could look like will allow for effective planning of transport infrastructure such as ports andtheir connections to roads, railways and inland waterways. Due to the diversity of commodities
transported at sea (oil, coal, iron ore, grain, general and containerised cargoes, etc.), each trade could be
subject to a specific analysis. Such division of analysis acknowledges that maritime flows are affected by alarge variety of factors, such the level of integration and of regionalisation of the global economy,prospects on world population and GDP per capita as well as the future organisation of Global Value Chains(GVCs). The diversification of energy supplies and transitions towards renewable energy will also have asignificant impact on maritime trades with maritime transport still being a fossil-based industry.
The objective of this paper is to discuss these elements and to provide a holistic view on future maritime
trade development. It addresses the following questions:

How will economic globalisation evolve and translate into World population and trade outlook?

What are the likely pathways for maritime trades?

How will economic globalisation evolve and what does it imply for maritime trade?

The paper first sets the scene (section 1) derived from an analysis of the evolution in maritime trades
during the last 50 years. It then discusses findings from studies on long-term World population and GDP
per capita growth outlook, which are still the main drivers of future maritime trades (section 2). World
trades are then analysed together with some maritime demand outlook (section 3) while additional drivers
related, in particular, to changes in technology, Global Value Chains and regionalisation of trades are finallydiscussed (section 4).

Long-term changes predicted for maritime trades
The world economy has been subject to profound changes over the last century. These changes have
impacted the volume, pattern and composition of maritime trades. Looking back, world trades havefollowed three main stages (Baldwin, 2006, 2011, 2013, 2016; Gonzales and Jouanjean 2017; WTO 2013,2018).
The first stage of development in international trades was largely driven by falling transport costs referredas ‘first unbundling’ or ‘traditional trade’. This stage ended in the middle of the 20th century. Technologicaladvancements made in transport, and in particular for shipping and railways, have played a major role inthese trade evolutions (WTO 2018) as they enabled the separation of production and consumption acrossnational borders. During this phase, maritime transportation experienced large growth rates, mostly
supported by energy and general cargo trades.

4© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

The extension of Global Value Chains (GVCs) saw a reduction in transport and in coordination costs during
the second stage (1945-2000). This led to further fragmentation in the production processes acrossnational borders. Trades in intermediate and in manufactured products flourished, and particularly inemerging economies that were the main drivers of growth (Baldwin, 2006; Baldwin, 2016). This phase wasalso supported by technological changes in ocean shipping (WTO, 2018) where containerisation is regularly
mentioned as a major contributor to the decline in the cost of transport (Levinson, 2008; Hummels, 2007).
Digitally-enabled trade since 2000 marks the third stage of world trade. It is driven by further reductions
in transport and coordination costs, that is coupled with a considerable fall in the costs through thetransfer of data or information (Gonzales and Jouanjean, 2017; WTO, 2018). These elements imply thatnew profound changes in the world economy may emerge, that will once again impact the volume, patternand composition of world and maritime trades. As shipping remains a derived demand (Stopford, 2009),
the long-term evolution in international maritime trades is in line with changes in the world economy.
The main evolutions in maritime trades during the last 50 years (Corbett and Winebrake , 2008; UNCTAD,
2018a) can be summarised by two points (Figure 1, Tables 1-3):


A general increase in maritime transport volume and tonnes per-mile of approximatively 3.1%3.8% per year from 1970 to 2017, mostly supported by developments in dry bulk and container
trades. During this period, the share of dry bulk commodities has increased from 43% to 54% andfrom 2% to 17% for containers, while the share of oil trades decreased from 55% in 1970 to 29%
of maritime trades in 2017, although still growing at 1.5%-2% per year.



Since the 90s, even more since 2000, an increase in maritime trades of developing countries(increasing its share from 51% in 2000 to 59% in 2017) drives the growth of international maritime
trades.
Figure 1. World seaborne trade by cargo type, 1970-2017 (in Metric ton in millions)

Source: Author’s elaboration based on UNCTAD (2000-2018).

© OECD/ITF 2020

5

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Figure 2. Growth rates of world seaborne trade by cargo type, 1970-2017

Source: Author’s elaboration based on UNCTAD (2000-2018).

6© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 1. World seaborne trade by types of cargo, 1970-2017 (in Metric ton in millions)
1970

Share

1970-1980*

1980

Share

1980-1990*

1990

Share

1990-2000*

Oil and Gas

1440

55%

2.7%

1871

51%

-0.6%

1755

44%

2.1%

Main Bulk Commodities

448

17%

3.1%

608

16%

5.0%

988

25%

2.7%

Other Bulk Commodities

667

26%

5.3%

1123

30%

-0.9%

1031

26%

6.5%

Containers

50**

2%

7.4%

102

3%

8.7%

234

6%

9.8%

Total Goods

2605

100%

3.6%

3704

100%

0.8%

4008

100%

4.1%

2000

Share

2000-2010*

2010

Share

2010-2017*

2017

Share

1970-2017*

Oil and Gas

2163

36%

2.5%

2772

33%

1.8%

3146

29%

1.7%

Main Bulk Commodities

1295

22%

6.1%

2335

28%

4.6%

3196

30%

4.4%

Other Bulk Commodities

1928

32%

0.5%

2022

24%

3.2%

2526

24%

2.9%

Containers

598

10%

7.9%

1280

15%

5.3%

1834

17%

8.1%

Total Goods

5984

100%

3.5%

8409

100%

3.5%

10702

100%

3.1%

Notes: * Annual Average Growth Rate. ** Estimated in 1970.
Source: Author’s elaboration based on UNCTAD (2000-2018).

© OECD/ITF 2020

7

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 2. World seaborne trade by types of cargo, 1970-2017 (in billions of tons-miles)
1970

Share

1970-1980*

1980

Share

1980-1990*

1990

Share

1990-2000*

Oil and Gas

6 487

61%

3.8%

9 405

56%

-1.8%

7 821

46%

3.3%

Main Bulk Commodities

2 049

19%

5.9%

3 652

22%

3.0%

4 900

29%

2.9%

Other Bulk Commodities

2 118

20%

5.8%

3 720

22%

1.8%

4 440

26%

9.4%

Containers

NA

NA

NA

NA

NA

NA

NA

NA

NA

Total Goods

10 654100%

4.6%

16 777100%

0,2%

17 161

100%

6,2%

2000

Share

2000-2010*

2010

Share

2010-2017*

2017

Share

1970-2017*

Oil and Gas

10 77834%

2.1%

13 25130%

2.6%

15 86927%

2.0%

Main Bulk Commodities

6 509

21%

6.6%

12 33628%

4.9%

17 21729%

4.7%

Other Bulk Commodities

10 87135%

1.3%

12 42828%

4.1%

16 46428%

4.6%

Containers

3 111

10%

7.8%

6 588

15%

5.4%

9 535

16%

NA

Total Goods

31 269100%

3.6%

44 603100%

4.1%

59 085100%

3.8%

Note: * Annual Average Growth Rate
Source: Author’s elaboration based on UNCTAD (2000-2018).

8© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 3. World seaborne trade by group of economies, 1970-2017 (in Metric ton in millions)
1970

Share

1970-1980*

1980

Share

1980-1990*

1990

Share

1990-2000*

Developed economies

781

30%

5.8%

1 370

37%

2.5%

1 756

44%

4.1%

Transition economies

154

6%

4.9%

248

7%

1.2%

281

7%

2.0%

Developing economies

1 670

64%

2.2%

2 085

56%

-0.6%

1 972

49%

4.4%

World

2 605

100%

3.6%

3 704

100%

0.8%

4 008

100%

4.1%

2000

Share

2000-2010*

2010

Share

2010-2017*

2017

Share

1970-2017*

Developed economies

2 621

44%

0.9%

2 865

34%

2.5%

3 675

34%

3.4%

Transition economies

341

6%

4.2%

516

6%

2.6%

664

6%

3.2%

Developing economies

3 022

51%

5.2%

5 028

60%

2.4%

6 363

59%

3.0%

World

5 984

100%

3.5%

8 409

100%

2.4%

10 702100%

3.1%

Note: * Annual Average Growth Rate
Source: Author’s elaboration based on UNCTAD (2000-2018).

© OECD/ITF 2020

9

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

This initial analysis raises two important questions:First, is the decrease of energy trades in total maritime transportation (from roughly 60% in 1970
to 30% in 2017) likely to continue?



Second, is the rise in dry bulk cargoes and container trades, the main driver of shipping markets
over the last 50 years and the rise in developing countries since 2000, going to continue in the
future?

The first bullet importantly asks, whether these trades, which have still been increasing in absolute value
since 1970 (+1.5 to 2% on a yearly basis) are going to decrease? And what will be the new composition ofenergy trades, considering the new environment towards decarbonisation? The second point addresses
the general reduction in international trades mostly explained by a slowdown of developing countries(around 2.5% per year from 2010 to 2017). All questions apply to a large range of products, from crudeoil, oil products, dry cargoes (iron ore, coal, grain…) to manufactured products (electronics and textiles).
This paper focuses on a more holistic approach and focuses on the main drivers of future maritime trades.
It proposes that long-term maritime trades will still mostly be driven by changes in GDP per capita and its
associated effects such as the need for industrial production. Although many studies (IMO, 2014; DNV,
2017; UNCTAD, 2018b) stress a decoupling effect with GDP per capita over the last years, and in particularfor energy-related trades (CE Delft, 2019).
Table 4 and Figure 3 show the results (linear regression in log) of maritime trade forecasts as a function of
GDP per capita. There is still a strong relationship between GDP per capita and maritime trades with a R2of 0.97 for Total goods, 0.92 for Petroleum Product and Gas and 0.99 for Dry cargo. This differs to crude
oil trades, where geopolitical events and future energy transition pathways have a strong impact that
explains significant deviation (R2=0.62) from GDP-based evolutions1. In the long run, the total maritime
trade-GDP per capita elasticity is at around 2 and is higher, as expected, for dry cargo (2.74) that includes
containerised cargoes. These results confirm that future maritime trades should still be mostly driven by
outlooks based on world population and GDP per capita (excluding crude oil trade) that will be the focus
of Section 2. The Section 3 will then discuss the implications for future maritime demand (Section 3) while
additional future drivers are presented in a last section (Section 4).
Table 4. Estimates of the log Maritime trades (unloaded) as a function of log GDP per capita(1970-2016)
Variables

Total goods

Crude oil

Petroleum Product and Gas

Dry cargo

GDP per Capita

2.027***

0.708***

2.142***

2.744***(41.94)(8.60)(22.77)(65.64)-9.546***1.033-12.851***-16.492***(-22.17)(1.41)(-15.34)(-44.29)

Observations

47

47

47

47

R-squared

0.975

0.622

0.920

0.990

Constant

Notes: *** Significance levels are 1%. ** Significance levels are 5%. * Significance levels are 10%
Source: Cariou (2019) based on data from UNCTAD (2018a). Initial Trade data in Metric tons in Million and Gross
Domestic Product (GDP) per capita in constant (2010) prices, annual, 1970-2016.

10© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Figure 3. Predicted versus actual maritime trades as a function of GDP per capita

Source: Cariou (2019) based on UNCTAD (2000-18).

World population and GDP per capita outlooks
World population and GDP per capita growth are the main drivers of trades. Long-term evolutions forthese two variables are subject to particular attention by two main streams of research.


Those devoted to assess the contribution of international trades to climate change and future
greenhouse gas (GHG) emissions (for instance IPCC 2000; IMO 2014; CE Delft 2019).

Those devoted to predict future world trades (for instance WTO, 2018), or to change in GVCs
supply chains (for instance McKinsey Global Institute 2019; Deutsche Post, 2012).

These two streams are based on alternative futures and share common drivers such as world population,
GDP future development and their respective locations. The first stream of research, initiated by theInternational Panel on Climate Change (IPCC, 2000) is built upon the definition of storylines. Each storyline
is based on different assumptions on demographic changes, economic developments and technologicalchanges, which can be summarised as follows:© OECD/ITF 2020

11

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178



The first storyline describes a future world of very rapid economic growth, global population thatpeaks in mid-century. This is the A1 scenario. It splits into three groups according to hypothesis
on fossil intensity and balance across fossil or non-fossil sources. Major underlying themes areconvergence among regions, capacity building, and increased cultural and social interactions,with a substantial reduction in regional differences in per capita income.

The second storyline (the A2 scenario) describes a heterogeneous world. Fertility patterns acrossregions converge very slowly, which results in a continuously increasing global population while
economic development is primarily regionally oriented. Per capita economic growth andtechnological change are slower than in other storylines.



The third storyline and scenario family (B1) describes a convergent world with the same global
population pattern as the A1 storyline, but with rapid changes in economic structures toward a
service and information economy. It leads to the introduction of clean and resource-efficienttechnologies and an emphasis on global solutions to sustainable economic, social, andenvironmental challenges.



The fourth storyline and scenario family (B2) describes a world with local solutions to sustainableeconomic, social, and environmental issues. Global population growths at a rate lower than A2.
While the scenario is also oriented toward environmental protection and social equity, it focuseson local and regional levels.

These model-based scenarios lead to 26 different sub-scenarios that explore the possible environmental
trends in relation to population and income development, technology development, lifestyle change andevolving production and consumption patterns (Van Vurren et al. 2017). A new set of five scenarios (Van
Vurren et al., 2014) or Shared Socio-economic Pathways (SSPs) serve as a basis for most estimations on
future transport demand and GHG emissions since 2006. See for instance in the 2014 IMO study on GHG.
These five scenarios are based on the following narratives:12

SSP 1. Sustainable development. This proceeds at a reasonably high pace, inequalities arelessened, technological change is rapid and directed toward environmentally-friendly processes,
including use of lower carbon energy sources and high productivity of land.



SSP 2 Moderate. An intermediate case between SSP1 and SSP3 or middle of the road scenario.



SSP 3 High for mitigation and adaptation. Unmitigated emissions are high due to moderate
economic growth, a rapidly growing population, and slow technological change in the energy
sector, making mitigation difficult. Inequality is high, and a regionalised world leads to reduced
trade flows.



SSP 4 High for adaptation, low for mitigation. A mixed world, with relatively rapid technologicaldevelopment in low-carbon energy sources in key emitting regions, leading to relatively large
mitigative capacity in places where it mattered most to global emissions. This highly unequal
world leads to a large number of poor people across countries that face high adaptation
challenges.



SSP 5 High for mitigation, low for adaptation. In the absence of climate policies, energy demandis high and most of this demand is met with carbon-based fuels. Investments in alternative energy
technologies are low, and there are few readily available options for mitigation. SSP 5 or ‘‘fossilfuelled development’’ characterises a growth-oriented world that uses conventional
technologies (in particular fossil fuel-based energy conversion technologies) and therefore faces
high mitigation challenges.

© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

From these five scenarios, two recent studies by Samir and Lutz (2017) and Leimbach et al. (2017) shedlight on the underlying assumptions regarding future changes in world population and GDP per capita.

World population outlook
For world population future annual growth rates (Samir and Lutz, 2017), the five SSP assumptions range
from 0.5% in 2010 to 0.9% in 2050 and from -0.4% in 2050 to 0.5% in 2100 (Table 5). Under these different
assumptions, the world population would increase from 6.8 billion in 2010 to 8.4 (SSP1) or 9.9 (SSP3) in
2050 and then stabilise or slightly decrease up to 2100 (except for SSP3 which predicts 12.6 billion by2100).
Table 5. World population outlook 2010-2100 in billion and Annual Growth Rate*
SSP1

SSP2

SSP3

SSP4

SSP5

2010

6 871

6 871

6 871

6 871

6 871

2050

8 461

9 166

9 951

9 122

8 559

2100

6 881

9 000

12 627

9 267

7 363

2010-2050*

0.5%

0.7%

0.9%

0.7%

0.6%

2050-2100*

-0.4%

0.0%

0.5%

0.0%

-0.3%

Source: Author’s elaboration based on Samir and Lutz (2017).

The share of Asia in world population is similar whatever the SSP assumptions, although differences inregional growth rates exist. Asia displays a decrease in population from 60% in 2010 to approximatively
55% by 2050. The share of African populations increases by 5% to reach approximatively 20%-25% of theworld population in 2050 (Figure 4 for SSP1), while the share of the other main regions remains fairly
constant. In 2100, the share of Asia is 44%-53% against 25%-39% for Africa.
Figure 4. World population by region share in 2010 and 2100 (SSP1)© OECD/ITF 2020

13

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Source: Author’s elaboration based on Samir and Lutz (2017).

The International Energy Agency (IEA) (2019) forecasts consider an increase in world population of 0.9%
per year from 2107 to 2040, in-line with SSP3. The world population is estimated at 9.1 billion by 2040,
with 50% in Asia and 22% in Africa being the two largest shares. Fontagné and Fouré (2013) scenarios are
based on fertility and account for the potential, but limited effects of migrations that could mostly takeplace in Europe and North America. Furthermore, the impact on population growth remains affected byan ageing population for which a general decline in the share of working population in total population is
expected. Table 6 shows the result for a selection of 20 countries, and depicts a rise in the share of
population aged more than 65 years from 20% in 2011 to 46% in 2060 compared to the 15-64 year-old
groups.

14© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 6. Share of population older than 65 as a share of population aged 15-64
2011

2030

2060

2011

2030

2060

Argentina

16.5

20.8

35.9

India

7.7

12.2

25.4

Australia

20.3

31.5

42.8

Indonesia

8.3

15.1

36.1

Brazil

10.6

20.0

43.6

Italy

30.9

41.1

56.7

Canada

20.8

37.8

44.9

Japan

36.9

52.9

68.6

Chile

13.8

26.5

47.0

Korea

15.9

37.3

64.3

China

11.5

23.9

51.8

Russia

17.7

29.4

42.4

Denmark

25.7

37.0

43.5

South Africa

7.3

11.6

18.7

France

25.9

39.1

46.6

Spain

25.2

35.5

56.4

Germany

31.2

47.2

59.9

United Kingdom

25.2

34.8

42.1

Greece

28.9

37.7

56.7

United States

20.0

32.7

36.8

All 20 countries

20.0

31.2

46.0

Source: Author’s elaboration based on Johansson et al. (2012).

World GDP outlook
Gross domestic product (GDP) per capita outlook accounts for previous projections of world population
and are adjusted according to the SSP1-SSP5 scenarios. Leimbach et al. (2017) summarise the main
implications for High-, Middle- and Low-income countries in Table 7. Depending on the scenarios theCompound Annual Growth Rate World income over 2010-2040 would increase by 3% in the SSP1-secnario
and by 1.9% in the SSP2-scenario, while projected growth over 2040-2100 would range between 2.2% for
the SSP1-scenario to 0.5% in the SSP3-scenario. The most striking element, common in most long-term
forecasts, is a convergence over time of populations amongst higher, middle and lower countries.
Out of the five scenarios, SSP3 is the closest to the latest projections by Guillemette and Turner(2018) of
the OECD. Previous OECD forecasts from Johansson et al. (2012) are reported in Table 8 and conclude thatthe growth rate of non-OECD countries should continue to outpace that for OECD countries, but with thedifference narrowing over the coming decades. Non-OECD country growth will decline from over 7% peryear over the last decade, to around 5% in the 2020s and to about half that by the 2050s (2.5% from 2050).
For OECD countries, the average GDP growth is estimated at 1.75% to 2.25% per year. This convergenceis reinforced by the fact that determinants such as the aging of populations is likely to lower the GDP per
capita growth rate despite an expected increase in the overall world population. Cross-country differencesin living standards is expected to persist by 2060 despite a faster growth for low-income and emerging
countries. Finally, IEA (2019) prospects on future GDP growth are more optimistic, with a prediction of
3.4% growth per year from 2017 to 2040, mostly supported by China and Southeast Asia (approximately
4.5%).

© OECD/ITF 2020

15

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 7. Annual average GDP per capita growth rates per Shared Socio-economic Pathways
SSP1

SSP2

SSP3

2010–2040

2040–2100

2010–2100

2010–2040

2040–2100

2010–2100

2010–2040

2040–2100

2010–2100

High income countries

1.3%

0.9%

1.0%

1.4%

0.9%

1.1%

1.1%

0.4%

0.6%

Middle income countries

4.4%

1.9%

2.8%

4.0%

1.9%

2.7%

3.4%

0.9%

1.8%

Low income countries

4.2%

3.9%

4.1%

3.7%

3.3%

3.5%

2.7%

1.0%

1.6%

World

3.0%

1.8%

2.2%

2.7%

1.7%

2.0%

1.9%

0.5%

1.0%

SSP4

SSP5

2010–2040

2040–2100

2010–2100

2010–2040

2040–2100

2010–2100

High income countries

1.5%

0.9%

1.1%

1.5%

1.7%

1.6%

Middle income countries

4.3%

1.8%

2.7%

4.5%

2.6%

3.3%

Low income countries

3.3%

1.8%

2.3%

4.0%

4.5%

4.4%

World

2.7%

1.1%

1.7%

3.1%

2.5%

2.8%

Source: Author’s elaboration based on Leimbach et al. (2017).

16© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 8. Projected GDP per capita annual growth rate in OECD, non-OECD and selected countries
1995-20112011-2030

2030-2060

2011-2060

1995-20112011-2030

2030-2060

2011-2060

Argentina

2.6

2.9

1.9

2.3

Italy

0.6

0.9

1.5

1.3

Australia

1.9

3.0

1.7

1.8

Japan

0.8

1.4

1.9

1.7

Brazil

2.1

3.4

2.1

2.6

Korea

4.0

2.5

1.4

1.8

Canada

1.6

1.3

1.8

1.6

Russia

5.4

3.2

1.7

2.3

Chile

2.8

3.4

2.0

2.5

South Africa

2.1

3.4

2.3

2.7

China

9.3

6.4

2.8

4.2

Spain

1.9

1.6

1.3

1.4

Denmark

1.1

1.0

2.0

1.6

United Kingdom

1.9

1.3

1.8

1.6

France

1.1

1.6

1.2

1.3

United States

1.5

1.5

1.5

1.5

Germany

1.4

1.5

1.5

1.5

Greece

1.9

1.7

1.3

1.4

World

2.5

3.1

2.3

2.6

India

5.8

5.6

3.6

4.4

OECD

1.5

1.7

1.7

1.7

Indonesia

3.1

4.5

3.3

3.8

Non-OECD

5.6

5.2

2.7

3.7

Source: Author’s elaboration based on Johansson et al. (2012)© OECD/ITF 2020

17

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

World and maritime trade outlooks
World trade outlook
The strength of the relationships between world population, GDP growth and international trade haschanged over time, and is likely to be subject to further changes in the future. The strength of these
relationships is weaker for specific trades, such as for energy trades that are still representing a significant
share of maritime transport demand.
For fossil-based trades, the general rise in awareness towards global warming has put these energy
markets under scrutiny. This impacts demand for liquid bulk and a large share of dry bulk cargoes (coal)for which pathways to energy transition will guide future trade volumes. According to the International
Energy Agency (IEA, 2019), medium- to long-term energy projections based on the World Energy Model(WEM) are leading to the following conclusions. Oil demand remains highly dependent on the future
outlook of developing countries and is not as favourable as during the last 30 years. This is relevant despite
the United States increasingly leading the expansion in global oil supplies, and even if geopolitical will stillplay a critical role on the oil/energy markets. The incorporation of policy ambition toward the energy
sector as well as of various Sustainable Development Scenarios (SDS) are likely to lead to profound changes
in global energy trades and in the composition of such trades. This is reflected by the two IEA scenarios:

The New Policies Scenario (NPS) that incorporates existing energy policies as well as an
assessment of the results likely to stem from the implementation of announced policy intentions.



The Sustainable Development Scenario (SDS) that outlines an integrated approach to achieving
internationally-agreed objectives on climate change, air quality and universal access to modern
energy.

Table 9 reports IEA estimates on world Total Primary Energy Demand (TPED) up to 2040, under the two
scenarios. Estimates stress an average annual growth rate from 2017 to 2040 at 1.0% under the NPS and-0.1% under SDS, against 2.0% for the 2000-17 period. The decline in demand is the largest for coal (from0.1% to -3.6%) and oil (from 0.4% to -1.5%) which remain the two main energy-related maritime markets.

18© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 9. Forecasted Total Primary Energy Demand (Mtoe)
2000

2017

2040 (NPS)

2040 (SDS)AAGR 200017

AAGR 201740 (NPS)AAGR 201740 (SDS)

Oil

3 665

4 435

4 894

3 156

1.1%

0.4%

-1.5%

Coal

2 308

3 750

3 808

1 597

2.9%

0.1%

-3.6%

Natural Gas

2 071

3 107

4 435

3 437

2.4%

1.6%

0.4%

Bioenergy

1 022

1 385

1 850

1 503

1.8%

1.3%

0.4%

Nuclear

675

687

971

1 292

0.1%

1.5%

2.8%

Hydro

225

353

531

601

2.7%

1.8%

2.3%

Oher Renewable

60

253

1 222

2 131

8.8%

7.1%

9.7%

Total

10 026

13 97017 71113 717

2.0%

1.0%

-0.1%

Source: IEA (2019).

Fontagné and Fouré (2013) studied the long-term perspectives of the World trade for commodities which
are more dependent on the long-term trade to GDP relationship such as for other dry bulk (iron ore, grain,sugar, etc.), general and containerised cargoes (Table 10). Their study shows the development oftrade/GDP elasticities since 1950, which peaked during the 1990s, when the indicator reached 2.82. Thiselement is also underlined by UNCTAD (2017) that mentions a trade-GDP elasticity at 1.3 in 1970-1985,
2.2 in 1986-2000, 1.3 in the 2000s and 0.7 in 2008-2013.
Table 10. World trade to income elasticity (goods)
1950-59

1960-69

1970-79

1980-89

1990-99

2000-09

1950-2009

1.62

1.54

1.31

1.19

2.82

1.42

1.64

Source: Fontagné and Fouré (2013).

Fontagné and Fouré (2013) forecasts are based on a high and low simulation, from a combination ofchanges in GDP, comparative advantage and trade costs. In the ‘high sim’ scenario, the expected elasticity
is at 1.49 from 2012 to 2035, at a level far below the 1990-99 period (2.82) and similar to when many
global value chains were not established (1960-69). Under the ‘low sim’ scenario, the forecast for 20122035 is of a lower elasticity (0.69). Finally, for developed countries, the future trade to income elasticity
ranges from 1.00 (Low Sim) to 1.78 (High Sim), while for developing countries, the respective elasticities
are from 0.38 to 1.19.
The low scenario estimates a 1.1% average annual growth rate of world exports up to 2035 for developing
countries and 1.8% for developed countries. This is between 8.5% and 4.5% respectively in the highscenario (WTO, 2013). These estimates are formed by combining macroeconomics and trade scenarios.
Furthermore, the rise of developing countries is bound to continue as well as intra-regional trades. This is
in line with other studies that predict a general long-term slowdown of global trade due to aging
populations, to a decline in GDP growth, and to a decrease of income elasticity and in particular for primary
goods and investment goods (UNCTAD, 2017).

© OECD/ITF 2020

19

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Maritime trades outlook
Future maritime demand is directly impacted by world trade outlook. IMO (2014) estimates are in line with
the IPCC approach. Shipping projection scenarios are based on Representative Concentration Pathways(RCPs) for future demand of coal and oil transport and on Shared Socioeconomic Pathways (SSPs) for future
economic growth. This leads to the development of four main scenarios of maritime transport demandcalled Business-As-Usual Scenarios (BAU). For each BAU, three policy scenarios are set, with an increased
action on energy efficiency, on emissions or on both.
Historical and projected data on consumption of coal and oil are used to build future trends for energy
related trades. Changes in demand for these commodities are not directly related to GDP, contrary to noncoal dry bulk and container trades. The four estimates on future transport work (tonne-miles) are of anannual growth rate ranging from approximatively 1.3% to -1.2% for oil and from 2.7% to -1.7% for coal.
For dry bulk cargoes (except coal), the expected growth is from 3.2% to 5.7% per year while for other dry
cargoes, estimates are from 1.9% to 4.5% to 2050.
DNV (2017) forecasts provide a comprehensive analysis of future maritime trades with an expected 35%
rise in seaborne trade to 2030 and an additional 12% growth thereafter (Table 11). The global annual
increase in tonne-miles is 2.2% over the period 2015-2030 and 0.8% per year from 2030 to 2040. The
increase in seaborne transportation occurs for all trade segments, except crude oil and oil products which
peak around 2030. This reflects the major transition in the world energy system. Trade in individual energy
commodities will decline with coal first, crude oil and then oil products. Natural gas – as liquefied naturalgas (LNG) and liquid petroleum gas (LPG) - will experience sustained growth, as gas takes over as the largest
energy source.
Bulk trades are expected to rise. Estimates are of an average growth in bulk of 1.8% per year in tonnemiles to 2030, and 0.5%-0.7% per year thereafter, driven by strong increases in grain, moderate rises inore and other minor bulk, and a decline in coal. The increase in non-coal bulk trades (mostly iron ore andgrain) in the Asian regions compensates the reduction in coal transportation.

20© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Table 11. DNV forecasts to 2050
Million tonnes per year

Annual Average Growth Rate

2015

2030

2040

2050

2015-2030

2030-2040

2040-2050

Crude oil

1 870

2 250

1 990

1 540

1.2%

-1.2%

-2.5%

Oil products

1 020

1 330

1 220

1 030

1.8%

-0.9%

-1.7%

Natural Gas

330

640

700

770

4.5%

0.9%

1.0%

Bulk

4 820

6 080

6 330

6 640

1.6%

0.4%

0.5%

Container

1 660

2 660

3 390

4 040

3.2%

2.5%

1.8%

Other Cargo

1 120

1 650

1 940

2 260

2.6%

1.6%

1.5%

Total

10 82014 61015570

16 280

2.0%

0.6%

0.4%

Billion tonne-miles/year

Annual Average Growth Rate

Crude oil

8 990

11 240

9 880

7 500

1.5%

-1.3%

-2.7%

Oil products

2 910

3 910

3 560

3 000

2.0%

-0.9%

-1.7%

Natural Gas

1 420

2 900

3 210

3 570

4.9%

1.0%

1.1%

Bulk

26 62034 69037 13039 100

1.8%

0.7%

0.5%

Container

8 290

13 290

16 91020 100

3.2%

2.4%

1.7%

Other Cargo

5 090

7 600

8 950

10 370

2.7%

1.6%

1.5%

Total

53 32073 63079 64083 640

2.2%

0.8%

0.5%

Source: DNV (2017).

Container growth is high according to DNV (2017), and follows GDP growth. The trade will experience thestrongest growth of all segments, as measured by tonne-miles, with 3.2% per year on average to 2030. It
will thereafter decline to average 2.1% per year. Over the entire forecasting period to 2050, the annual
growth will average 2.6% for container tonne-miles and 2.4% for global GDP or a container trade-GDP
multiplier (trade growth relative to GDP growth) at 1.1. DNV (2017) also projects that container growth isimminent for all regions, and the Indian Subcontinent is subject to the strongest growth, followed by China,
South East Asia and Sub-Saharan Africa.

© OECD/ITF 2020

21

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Drivers of future maritime trade
Future maritime predictions will be impacted by drivers that mostly relate to energy use, emissions,transport and technology development (ITF, 2019). The ITF Transport Outlook (2019) investigates how
socio-economic changes (population, GDP trade and transport policies) affect transport demand ingeneral, and includes an analysis on the impacts for maritime demand. It concludes that freight growth
will triple by 2050, and that maritime transportation will continue to dominate freight (70% of total freightwith 120 000 billion tonne-km by 2030 and 250 000 by 2050) under the current situation. The growth will
be mostly supported by traffic related to Asia, Africa and the trades in the Indian and Pacific oceans. The
implementation of New Policies Scenario (IEA, 2019) should lead to a decrease of oil and coal demand by
33% and 50% respectively by 2035. Current and future disruptions related to logistics efficiency andtechnology (e-commerce, 3D printing, new trade routes, energy transition) could lower maritime demand
to 160 000 tonne-km by 2050 (instead of 250 000 under current situation). Under such scenarios, maritime
demand would stabilise from 2019 to 2030, and the increase in maritime demand from 2019 to 2050
would be at approximatively 2.3% per year compared to 3.8% for the last 50 years.
DNV (2017) states that particular attention should be given to decarbonisation and to environmental
awareness that could lead to a further decline in trade for oil and coal. This would create the likely
advantage for biomass/biofuel and hydrogen trades. The development of the circular economy could also
represent a major game changer as it will impact the volume and type of cargos transported at sea. Grainthat accounts for approximatively 10% of bulk trade could experience some major changes, mostly
dependent on assumptions on world population. Future trade volume, pattern and modal shifts could also
be significantly impacted by the development of new routes, such as the One Belt One Road for rail or by
the opening of Arctic shipping.
Technological developments will also affect the future of maritime trade. McKinsey Global Institute (2018)states for instance that the adoption of electric vehicles could disrupt automotive value chains and tradeas battery-powered electric vehicles have only 20 to 30 moving parts in their drivetrains, compared to 130
to 170 moving parts in an internal combustion engine. Additive manufacturing and 3D printing can reduce
the need for long-distance trades as on-demand production near the consumer replaces the global
distribution of mass-produced goods. The increased use of robotics could enable reshoring of production
for developed countries, shortening global value chains, and potentially reducing demand for seaborne
transport.
The digitalisation and innovation of the shipping industry are further factors that will affect future trade.
Steamships and containerisation were crucial and initial drivers of world trade development. Digitalisationand innovation (big data and artificial intelligence (AI)) could further reduce maritime transportation andcoordination costs; reinforcing competitiveness in the shipping industry and therefore change the general
outlook. This is suggested by the Danish Ship Finance (2017) analysis on future maritime outlooks. They
predict long-term growth in seaborne trade volumes, averaging about 1% per annum until 2030 which isabout half of DNV forecasts for 2015-2030. This is because global consumer patterns are being redirected
towards activities that are not as trade- and energy-intensive as in the past and that are often domestically
produced (e.g. health care, leisure spending). A shift towards different vessel types, smaller parcel sizes
and in some segments even fewer cargoes shipped are expected, due to the combined effects of the fourthindustrial revolution (e.g. artificial intelligence, robotics, the internet of things, 3D printing anddigitalisation) and the ageing consumer base. This means that the trade dynamics are expected to be

22© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

redefined. Trade volumes may stagnate, travel distances may shorten and the efficiency of the world fleet
could improve considerably.
These changes are largely dependent on strategies put in place by global value chains (GVCs) (McKinsey
Global Institute, 2019) and have been subject to five major structural shifts since 2000.
1. goods-producing value chains have grown less trade-intensive
2. services play a growing and undervalued role in global value chains
3. trade based on labour-cost arbitrage is declining in some value chains
4. global value chains are growing more knowledge-intensive
5. value chains are becoming more regional and less global.
These changes are particularly important for containerised shipping markets which heavily rely on goodsproducing GVCs. Table 12 reports the list of the top-15 US importers/exporters in 2017 as well as theirrespective shares in the top-100 importers/exporters. Almost 50% of the top-100 US container imports
are done by companies belonging to the retail sector (49.7%), where Walmart (12.9%), Target (8.7%), andHome Depot (5.7%) account for 37%. On the export side (around 50% less than imports), thepaper/recycling/packaging sector is the largest industry using containers, with around 30% of all exports.
Table 12. Top-15 importers/exporters in 2017 in thousands of Twenty Equivalent Unit (TEU)
Rank

Top 15 – US Importer

TEU

Share

Sector1

Walmart

874.8

12.9%

Retail2

Target

590.3

8.7%

Retail3Home Depot

388

5.7%

Retail4

Lowe's

287.5

4.3%

Retail5

Dole Food

220.2

3.3%

Fruit and vegetables

6

Samsung America

184.8

2.7%

Conglomerate

7

Family Dollar Stores/Dollar Tree

168.4

2.5%

Retail8

LG Group

161.6

2.4%

Conglomerate

9Philips Electronics North America

142.9

2.1%

Electronics

10

IKEA International

120.5

1.8%

Retail11

Chiquita Brands International

117.5

1.7%

Fresh fruit and vegetables

12

Nike

116.3

1.7%

Footwear and apparel

13

Newell Brands

115.4

1.7%

Outdoor and home goods

14

Costco Wholesale

111.7

1.7%

Retail

15

Sears Holdings

103.2

1.5%

Retail-consumer goods

Rank

Top 15 – US Exporters

TEU

Share

Sector1

America Chung Nam

284.5

7.5%

Paper and plastics recyclables

2International Paper

248.4

6.5%

Paper/packaging

3

Ralison International

130.1

3.4%

Paper/recyclables© OECD/ITF 2020

23

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

4

Koch Industries

120.8

3.2%

Conglomerate

5International Forest Products

109.4

2.9%

Packaging/paper products/pulp/recyclables

6

DeLong

106.6

2.8%

Animal feed/grain

7

WM Recycle America

75.3

2.0%

Diversified/recyclables

8

Shintech

73.8

1.9%

Chemicals

9Louis Dreyfus Commodities

68.2

1.8%

Cotton/diversified

10

WestRock

66.3

1.7%

Paper/packaging

11

JBS USA

65.4

1.7%

Refrigerated meats/poultry

12

ExxonMobil Chemical

63.4

1.7%

Chemicals

13

Newport CH International

62.1

1.6%

Paper/metals/plastics recyclables

14

BMW of North America

61.6

1,6%

Automotive goods

15

Cargill

57.5

1.5%

Conglomerate

Source: Author’s elaboration based on Journal of Commerce (2018)

These imports and exports are subject to a decrease in trade intensity, measured as gross exports as ashare of gross outputs. For instance, (Figure 5), the share of export in production declined by 12.4
percentage points in 2007-17 compared to 2000-07 for computers and electronics and -10.3% for textile
and apparel.
McKinsey Global Institute (2019) states three main factors that explain these changes in trade intensity:


growing demand in China and the rest of the developing world, which enables these countries to
consume more of what they producethe development of more comprehensive domestic supply chains in those countries, reducing
their imports of intermediate goodsand the growing impact of new technologies (for instance, automation in production reduces thevalue of labour-cost arbitrage and enables location decisions based on proximity to customers).

It therefore means that regionalisation is occurring and could accelerate with automation. Automation
reduces the importance of labour costs and with the increase in services goods that increase theimportance of speed to market. Transport costs account for around 37% for goods flows, but falls to 17%
for services flows (WTO, 2018). Information and transaction costs (around 20% for goods and 30% forservices), borders and trade policy barriers costs (around 15% for each) and logistics cost (around 10%each), are now taking an increase share in total trade costs. This suggests that maritime trade’s ability toprovide lower transportation costs may no longer be the main driver to explain the price to move cargofrom origin to destination.

24© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Figure 5. Changes in global value chain trade intensity

Source: McKinsey Global Institute (2019).

Costs related to time delays and uncertainty, for which shipping is far less competitive, will increase. The
Hummels and Schaur (2013) study shows that the most time-sensitive trade flows involve the parts andcomponents trade, which has a time sensitivity 60% higher than other goods and in particular officeequipment, electric power machinery and photographic equipment (Hummels 2001). The Djankov, Freundand Pham (2010) study on the cost of time delay in trade find that each additional day of delay reduces
trade by at least 1% and by 7% for agricultural goods while Cariou (2011) and Maloni Paul and Gligor (2013)
have shown how liner shipping strategies such as slow steaming impact shippers. Furthermore, thedevelopment of strategic alliances has reduced the differentiation amongst liner shipping services and arealso impacting shippers (ITF, 2018).
Value chains are emerging that are less trade-intensive and less based on cost-labour arbitrage. In addition
to the need for time-to-market with more intra-regional trades, this could lead to a profound move toward
back-shoring or reshoring (Kinkel 2012, 2014). The Kinkel (2014) analysis of German data from theEuropean Manufacturing Survey (EMS) stresses that around 400 to 700 German companies would back-© OECD/ITF 2020

25

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

shore production capacities per year. The cost-based advantage from relocation to low-wage countries
seem to diminish more and more, while market-related expansion investments in emerging markets are
gaining significance.
The Tate (2014) survey of 320 companies indicated that 40% of these companies perceived a trend toward
reshoring to the United States. The 2008 recession in the United States provided the motivation forcompanies to re-evaluate their global supply-chain strategies (Ellram Tate and Feitzinger, 2013; Ellram,
Tate and Petterden, 2013). Simultaneously, the rising cost of labour in developing countries, high oil prices,increased transportation costs and a growing awareness of global supply chain risk have contributed tomake the United States a more attractive location.
Gadde and Jonsson (2019) investigate the 2025 outlook for the Swedish textile industry in offshoring andreshoring. The analysis of 119 Swedish buyers of textiles and apparels shows that Swedish textile firms are
increasingly sourcing from Europe to enhance supply chain responsiveness through nearshoring in relation
to customers. Strategies in Asia represent another pattern. If China still accounts for more than half of thetotal sourcing volume, while Bangladesh, India, and Vietnam represent about 10% each, more than onethird of the Swedish firms expect their sourcing in China to decrease. Part of this change reflects the
movement of sourcing to Europe to enhance geographical proximity, while other Swedish firms forecast
increasing sourcing in Bangladesh to benefit from low cost, which is a sign of extended offshoring. Theseelements reinforce the idea that the intraregional share of global goods trade should continue to increase.
This is supported by the WTO (2018) who lists an increase by 2.7 percentage points since 2013, in particularin Asia and Europe.

Conclusions
The objective of this report was to provide a long-term view on future maritime demand. The main
conclusions are as follows:26

Shipping remains a derived demand and maritime demand will continue to largely depend on the
future changes in the world economy, world population and in GDP. The substantial growth rates
in maritime trades, that were explained by the process of globalisation and by the increase indeveloping countries GDP per capita, are not likely to continue.

A general convergence should take place between GDP per capita growth rates amongst
developing and developed countries in the long run. In a world where demand is increasingly forservices rather than for goods, the globalisation process based on low labour-cost differentials
and on a massive outsourcing of production that stimulated trades has reached its limit.

The general trend towards a decarbonisation of the world economy is impacting the two largest
commodities transported at sea: crude oil and coal. This trend is not new. The share of energytrades in total maritime trades has already declined in the last 50 years. But in the near future,
we could expect that these commodities will be subject to a decrease in the volume of trade.



The new demand for smaller and low-value packages of physical goods, where goods are
increasingly bundled with services and require faster transit time, will induce a new type of© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

maritime demand. The development of maritime trades is questionable based on the costadvantage of shipping compared to other means of transport for this new type of demand. The
relocation of production to be nearer to consumption centres could also reduce the mean
distance to travel, and the competitiveness of shipping towards other means of transport.
Core services in traditional maritime business models will be lose their value in a digital world.
Vessels will still be needed to perform the task of moving cargo from port to port, but it is thedata this generates rather than the cargo itself that will start to be monetised. This is not only
from port to port but through the entire value chain, from origin to destination.

Advancements of digital technologies brings new opportunities. Digitalisation is likely to boost
trades but considered goods and service trade policies will play an important role in achieving
this.

Innovations in the shipping industry, first steamships and then containerisation, were the main drivers of
the first and the second phase of development of world trades during the last century. Now, the criticalquestion is whether or not new maritime innovations will take place to tackle the challenges of the new
era of digitally-enabled trade?

© OECD/ITF 2020

27

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Notes

1 The study by CE Delft (2019) uses oil and coal world consumption instead of world GDP for trends in energy-related maritime trade demand as
well as non-linear projection methods to account for future decelerated growth.

28© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

References
Baldwin R. (2016), The Great Convergence, Cambridge, MA: Harvard University Press.
Baldwin R. (2013), “Global supply chains: why they emerged, why they matter, and where they aregoing”, in Elms, D. K. and Low, P. (eds), Global Value Chains in a Changing World, Geneva: World Trade
Organization (WTO).
Baldwin R. (2011), “Trade and Industrialization after Globalization’s 2nd Unbundling: How Building andJoining a Supply Chain are Different and Why it Matters”, NBER Working Paper 17716.
Baldwin R. (2006), Globalisation: the great unbundling(s), Helsinki: Prime Minister’s Office Economic
Council of Finland, https://pdfs.semanticscholar.org/ac4f/
a1e76d01d9f7c9f991b352abdb60d2a15e4f.pdf (accessed on 08 April 2020).
Cariou P. (2011), “Is slow steaming a sustainable means of reducing CO2 emissions from container
shipping”, Transportation Research Part D (16), pp. 260-264.
CE Delft (2019), Update of maritime greenhouse gas emission projections,
https://www.cedelft.eu/en/publications/2258/update-of-maritime-greenhouse-gas-emission-projections(accessed on 08 April 2020)
Corbett J.J. et al. (2008), The Impacts of Globalisation on International Maritime Transport Activity: Past
trends and future perspectives, Global Forum on Transport and Environment in a Globalising World 10-12
November, Guadalajara, Mexico. http://www.oecd.org/greengrowth/greening-transport/41763672.pdf
Danish Ship Finance (2017), Shipping Market Review, May 2017.
https://www.shipfinance.dk/media/1735/shipping-market-review-may-2017.pdf
Danish Ship Finance and Rainmaking (2018), Maritime Trend Report: Observations and perspectives on
the future of the maritime Industry, https://www.shipfinance.dk/media/1910/maritime-trend-report.pdf(accessed on 08 April 2020).
Deutsche Post (2012), Delivering tomorrow, Logistics 2050 A Scenario Study,
https://www.dhl.com/content/dam/Local_Images/g0/aboutus/SpecialInterest/Logistics2050/szenario_study_logistics_2050.pdf , (accessed on 08 April 2020).
Djankov S., C. Freund and C.S. Pham (2010), “Trading on Time”, Review of Economics and Statistics, Vol.
92(1), pp. 166-173.
DNV (2017), Maritime Forecast to 2050, Energy Transition Outlook 2017,https://eto.dnvgl.com/2017/maritime (accessed on 08 April 2020).
Ellram L.M., W.L. Tate and E.G. Feitzinger (2013), “Factor‐market rivalry and competition for supply chain
resources”, Journal of Supply Chain Management, Vol. 49 (1), pp. 29–46.
Ellram L.M., W.L. Tate and K.J. Petterden (2013), “Offshoring and reshoring: an update on the
manufacturing location decision”, Journal of Supply Chain Management, Vol. 49 (2), pp. 14–22.
Fontagné L. and J. Fouré (2013), “Opening a Pandora’s box: Modelling world trade patterns at the 2035
horizon”, CEPII Working Paper 22, Paris.

© OECD/ITF 2020

29

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Gadde L-E. and P. Jonsson (2019), “Future changes in sourcing patterns: 2025 outlook for the Swedish
textile industry”, Journal of Purchasing & Supply Management, Vol. 20, (2014), pp. 66–68.
Guillemette, Y. and D. Turner (2018), "The Long View: Scenarios for the World Economy to 2060", OECD
Economic Policy Papers, No. 22, OECD Publishing, Paris, https://doi.org/10.1787/b4f4e03e-en.
Hummels D. L. (2007), “Transportation Costs and International Trade in the Second Era of Globalization”,
Journal of Economic Perspectives, Vol. 21(3), pp. 131-154.
Hummels D.L. (2001), “Time as a trade Barrier”, GTAP Working Paper No. 18.
Hummels D.L. and G. Schaur (2013), “Time as a Trade Barrier”, American Economic Review, Vol. 103 (7),pp. 2935-59.
IEA (2019), Oil 2019: Analysis and Forecasts to 2024, IEA, Paris,
https://doi.org/10.1787/oil_mar-2019-en.
IMO (2014), Third IMO Greenhouse Gas Study, International Maritime Organization, London, UK.
http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/Documents/MEPC%20
67-INF.3%20-%20Third%20IMO%20GHG%20Study%202014%20%20Final%20Report%20(Secretariat).pdf
Intergovernmental Panel on Climate Change (2000), Emission scenarios, http://sedac.ipccdata.org/ddc/sres/ , (accessed on 08 April 2020).
ITF (2018), The impact of alliances in container shipping. International Transport Forum.
ITF (2019), ITF Transport Outlook 2019, OECD Publishing, Paris, https://doi.org/10.1787/transp_outlooken-2019-en
Johansson, Å., et al. (2012), "Looking to 2060: Long-Term Global Growth Prospects: A Going for GrowthReport", OECD Economic Policy Papers, No. 3, OECD Publishing, Paris,
https://doi.org/10.1787/5k8zxpjsggf0-en.
Kinkel, S. (2014), “Future and impact of backshoring—Some conclusions from 15 years of research on
German practices”, Journal of Purchasing & Supply Management, Vol. 20 (2014), pp. 63–65.
Kinkel, S. (2012), “Trends in production relocation and back-shoring activities: changing patterns in thecourse of the global economic crisis”, International Journal of Operation & Production and Management,
Vol. 32 (6), pp. 696–720.
Leimbach, M. et al. (2017). “Future growth patterns of world regions – A GDP scenario approach”, Global
Environmental Change, Vol. 42 (2017), pp. 215–225.
Levinson, M. (2008), The Box: How the Shipping Container Made the World Smaller and the World
Economy Bigger, Princeton University Press.
López González, J. and M. Jouanjean (2017), "Digital Trade: Developing a Framework for Analysis", OECD
Trade Policy Papers, No. 205, OECD Publishing, Paris, https://doi.org/10.1787/524c8c83-en.
Maloni, M., J.A. Paul and D.M. Gligor (2013), “Slow steaming impacts on carriers and shippers”, Maritime
Economics & Logistics, Vol. 15(2), pp. 151-171.
McKinsey Global Institute (2019), Globalization in transition: The future of trade and value chains,
January, https://www.mckinsey.com/featured-insights/innovation-and-growth/globalization-intransition-the-future-of-trade-and-value-chains (accessed on 08 April 2020).

30© OECD/ITF 2020

CHANGING DEMAND FOR MARITIME TRADE | DISCUSSION PAPER | ITF ROUNDTABLE 178

Nakicenovic, N. et al (2000), Special Report on Emissions Scenarios: A Special Report of Working Group IIIof the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, U.K., 599 pp.
Available online at: http://www.grida.no/climate/ipcc/emission/index.htm (accessed on 08 April 2020).
Nelson, J. (2013), Evaluating Supply Chain Risks with Single vs. Multiple Vendor Sourcing Strategies.
Retrieved December 4, 2013, http://spendmatters.com/2013/02/28/evaluating-supply-chain-risks-withsingle-vs-multiple-vendor-sourcing-strategies/
Samir, K.C. and W. Lutz (2017), “The human core of the shared socioeconomic pathways: Population
scenarios by age, sex and level of education for all countries to 2100”, Global Environmental Change,
Vol. 42, pp. 181-192.
Stopford, M. (2009), Maritime economics. Third Edition, Routledge, London and New York.
Tate, W.L. (2014), “Offshoring and reshoring: U.S. insights and research challenges”, Journal of
Purchasing & Supply Management, Vol. 20 (2014), pp. 66–68.
UNCTAD (2018a), 50 Years of Review of Maritime transport 1968-2018: Reflecting on the past, exploring
the future. UNCTAD publication. https://unctad.org/en/PublicationsLibrary/dtl2018d1_en.pdf
UNCTAD (2018b), Review of Maritime Transport. UNCTAD/RMT/2018.
https://unctad.org/en/PublicationsLibrary/rmt2018_en.pdf
UNCTAD (2017), Review of Maritime Transport. UNCTAD/RMT/2017.
https://unctad.org/en/PublicationsLibrary/rmt2017_en.pdf
van Vuuren D.P. et al. (2017), “Energy, land-use and greenhouse gas emissions trajectories under a green
growth paradigm”, Global Environmental Change, Vol. 42, pp. 237–250.
van Vuuren D.P. et al. (2014), “A new scenario framework for Climate Change Research: scenario matrix
architecture”, Climatic Change, Vol. 122, pp. 373–386.
WTO (2018), The future of world trade: How digital technologies are transforming global commerce.
WTO publication. https://www.wto-ilibrary.org/trade-monitoring/world-trade-report-2018_f309483f-en
WTO (2013), Factors shaping the future of world trade, WTO publication.
https://www.wto.org/english/res_e/booksp_e/world_trade_report13_e.pdf© OECD/ITF 202031

Changing Demand for
Maritime Trade
This paper analyses the main drivers for maritime trade growth overthe last decades and suggests possible drivers for the development ofmaritime trade in the future.

International Transport Forum
2 rue André Pascal
F-75775 Paris Cedex 16+33 (0)1 73 31 25 00
contact@itf-oecd.org
www.itf-oecd.org

Published: 07/2020 | Photo credit: Aun Photographer/Shutterstock

All resources from the Roundtable on Future Maritime Trade Flows areavailable at:www.itf-oecd.org/future-maritime-trade-flows-roundtable