Containers port planning issues - RDwebaapa.files.cms-plus.com/2019Seminars/RICARDO_SANCHEZ.pdfLAC...
Transcript of Containers port planning issues - RDwebaapa.files.cms-plus.com/2019Seminars/RICARDO_SANCHEZ.pdfLAC...
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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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.
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2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019f 2020f
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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
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10.000
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15.000
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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%
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2019 2020 2021 2022 2023 2024 2025
Historical Projection
SAW SAE 400 LOA
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Positive scenarioSAW SAE 400 LOA
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Negative scenario 1SAW SAE 400 LOA
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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?
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Current situation ECSA
GDP and containers (teu) per capita
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70.000Eg
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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 [email protected]
http://www.eclac.org/transporte
Thanks a lot !!!