THE NEW GLOBAL ECONOMIC ENVIRONMENT: PERSPECTIVES FOR THE FUTURE OF MARITIME TRANSPORTATION AND PORTS

Containers port planning issues:Containerization determinants and biggervessels arriving to Latin America and the Caribbean.

Ricardo J. Sánchez Senior Economic Affairs Officer

International Trade, Infrastructure and Integration DivisionUnited Nations

Economic Commission for Latin America and the Caribbean

LAC trade 2007-2019 Global trade and industrial production 2012-2019

Source: UN ECLAC (2019); International Trade Outlook for Latin America and the Caribbean 2019: Adverse global conditions leave the region lagging further behind.

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-2

-1

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1

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20

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5

Comercio Producción industrial

Trade: growth and behavior in 2019

Source: Clarksons, various editions.*Note: Latin America includes Asia, North America, Europe-Latin America.

5,9%5,6%

2,3%

0,6%

5,7%

4,3%

2,6%

5,6%

2,3%

0,7%

2,9%

5,7%

5,4%

0,6%

0,0%

1,0%

2,0%

3,0%

4,0%

5,0%

6,0%

7,0%

2013 2014 2015 2016 2017 2018 2019f

World Latin America* Source: Dynaliners

The evolution of containership nominal capacity & world and LAC throughput

Source: For Latin America, Maritime & Logistics Profile; For the world, Clarksons, various editions.

100

150

200

250

300

350

400

450

500

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019f 2020f

Ind

ix 2

00

0 =

10

0

World throughput Latin America and the Caribbean throughput Containership capacity_World

➢ In 2010: all estimates were made on the basis of nominal capacity in TEU

➢ In 2019: estimates were made for TEU, LOA and DWT

In the case of TEU estimation, the following models were used:

• Model 3: this is a pooled model in which the dynamic aspect is included through the incorporation of the lagged dependent variable

• Model 5: is an error correction model for the east coast• Model 7: is an error correction pooled model

For the LOA estimation, a pooled model in which the dynamic aspect is included through the incorporation of the lagged dependent variable

Models

➢ Total port activity (Pa)Port activity (throughput) represents the amount of cargo attended in ports on the East and West coasts, respectively, and is measured in TEUS. As a derived demand from economic activity, the port activity shows a similar behavior with global GDP.

➢ Gap with main trade routes (Gap)The gap with the main trade routes denotes the percentage difference between the maximum size (in TEUS or LOA) of the vessels that arrive to South America and those that, in the same period of time, navigate the main global trade routes.

Some explaining variables

Models with TEUModel 3

Model 5

Model 7

MAX_SAE = -245.84 - 745.17 + 0.77*MAX_SAE(-1) + 267.04*PA_SAE + 328.26*GAP_SAE(-3)

MAX_SAW = 245.84 - 745.17 + 0.77*MAX_SAW(-1) + 267.04*PA_SAW + 328.26*GAP_SAW(-3)

D(MAX_SAE) = 1919.74 - 0.68*MAX_SAE(-1) + 427.72*PA_SAE(-1) + 0.79*D(MAX_SAE(-1)) +

1.06*D(MAX_SAE(-2)) - 853.97*D(PA_SAE(-1)) - 1193.55*D(PA_SAE(-2)) - 891.95*D(PA_SAE(-3)) -

423.78*D(PA_SAE(-4)) + 835.74*D(GAP_SAE(-2)) - 1068.50*D(GAP_SAE(-4))

D(MAX_SAW(-0)) = -0.35*MAX_SAW(-1) + 396.64*PA_SAW(-1) - 0.67*D(MAX_SAW(-3)) -

169.63*D(PA_SAW(-2)) - 442.42*D(GAP_SAW(-1)) - 414.40*D(GAP_SAW(-3)) + 375.23

D(MAX_SAE(-0)) = -0.35*MAX_SAE(-1) + 396.64*PA_SAE(-1) - 0.67*D(MAX_SAE(-3)) - 169.63*D(PA_SAE(-

2)) - 442.42*D(GAP_SAE(-1)) - 414.40*D(GAP_SAE(-3)) - 450.01

Model with LOALOAMAX_SAE = -2.90 + 1.88 + 0.80*LOAMAX_SAE(-1) + 7.51*PA_SAE(-1) - 6.77*PA_SAE(-3) +

122.85*GAP_LOA_SAE(-1) + 37.62*GAP_LOA_SAE(-2) - 89.94*GAP_LOA_SAE(-3) + 2.48*@TREND

LOAMAX_SAW = 2.90 + 1.88 + 0.80*LOAMAX_SAW(-1) + 7.51*PA_SAW(-1) - 6.77*PA_SAW(-3) +

122.85*GAP_LOA_SAW(-1) + 37.62*GAP_LOA_SAW(-2) - 89.94*GAP_LOA_SAW(-3) +

2.48*@TREND

Evolution and projections of the maximum size of containerships in the world and east coast and west coast in Latin America (2010 study)

Source: World, Alphaliner; LAC BlueWaterReporting and Ricardo J. Sánchez & Daniel Perotti.

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2.500

5.000

7.500

10.000

12.500

15.000

17.500

20.000

22.500

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Mill

ion

s TE

U

Max_WCSA Max_ECSA Max_World Projection WCSA Projection ECSA

Model with LOA

AssumptionsPa_saw Pa_sae Gap_saw Gap_sae

Historical 6% 4% -7% -2%

Positive 7% 5% -7% -2%

Negative 5% 4% -7% -2%

Negative_2 3% 3% -7% -2%

0

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2018(observed)

2019 2020 2021 2022 2023 2024 2025

Historical Projection

SAW SAE 400 LOA

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2018 (observed) 2019 2020 2021 2022 2023 2024 2025

Positive scenarioSAW SAE 400 LOA

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2018(observed)

2019 2020 2021 2022 2023 2024 2025

Negative scenario 1SAW SAE 400 LOA

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2018(observed)

2019 2020 2021 2022 2023 2024 2025

Negative scenario 2SAW SAE 400 LOA

MODEL with TEU: Evolution and projections of the maximum size of containerships in the world and ECSA and WCSA (2019 study)

Source: World, Alphaliner; LAC BlueWaterReporting and Ricardo J. Sánchez & Daniel Perotti.

Xiamen

Kwangyang

Tanjung Pelepas

Singapore

Yantian

Shanghai

Ningbo

Busan

Qingdao

Xingang

Dalian

Yangshan

Felixstowe

Gdansk

Aarhus

GothenburgHamburg

Wilhelmshaven

Antwerp

Bremerhaven

Liverpool

Algeciras

London

Rotterdam

MarseilleMiami

HoustonSavannah

Charleston

Virginia

N.Y./N.J.Oakland

Seattle/Tacoma

Long Beach

World megaships ports

South hemisphere? NCSA-WCSA: Cartagena, Posorja, Callao?

12

Current situation ECSA

GDP and containers (teu) per capita

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2000 2005 2010 2015 2018 2000 2005 2010 2015 2018

Contenedores per cápita(SG)

2000 = 4.252005 = 5.442010 =5.742018 =6.49

Spearman correlation (model 3)

0.0000 0.1031 0.0000 0.0011 0.0000 0.0036 0.0000 0.0000

519 519 348 519 519 519 519 519 519

rhcepib2 -0.4162* -0.0716 -0.2929* -0.1428* -0.3821* 0.1275* -0.2293* -0.3433* 1.0000

0.0000 0.0000 0.0000 0.0000 0.0084 0.0000 0.0204

519 519 348 522 519 519 519 522

MHVAsh_ind~2 0.2479* 0.1914* 0.6019* -0.3189* 0.1156* -0.3508* 0.1018* 1.0000

0.0000 0.0000 0.6018 0.0272 0.0000 0.0000

519 519 348 519 519 519 519

ICImp 0.4330* -0.2204* -0.0281 0.0970* 0.4701* 0.3259* 1.0000

0.0022 0.6351 0.0000 0.0000 0.0000

519 519 348 519 519 519

ICExp 0.1344* 0.0209 -0.4569* 0.2782* 0.2262* 1.0000

0.0000 0.0000 0.0094 0.0000

519 519 348 519 519

ga 0.4803* -0.2912* -0.1391* 0.3014* 1.0000

0.0001 0.0625 0.0022

519 519 348 522

fdi 0.1664* 0.0818 -0.1636* 1.0000

0.0000 0.0000

348 348 348

LSCI 0.2658* 0.2708* 1.0000

0.0000

519 519

urbanpop 0.2261* 1.0000

519

rateteu 1.0000

rateteu urbanpop LSCI fdi ga ICExp ICImp MHVAsh~2 rhcepib2

Sig. level

Number of obs

rho

Key

Ricardo J. Sánchez

Senior Economic Affairs Officer

United Nations Economic Commission for Latin America and the Caribbean

+56 2 2210-2257Ricardo.SANCHEZ@UN.org

http://www.eclac.org/transporte

Thanks a lot !!!