Institute of Developing Economies, JETRO
Geographical simulation analysis for
logistics enhancement in Asia
Satoru KUMAGAI
KEOLA Souknilanh
Ikumo ISONO
October 2018
Contents
• Background of IDE-GSM
• Model and Data
• Example of analyses
• Conclusion
2
What is IDE-GSM? (IDE-Geographical Simulation Model)
• Simulate the long-term evolution of population and the location of industries, Based on Spatial Economics
• Estimate the economic impacts of infrastructure development and customs facilitation at the sub-national level.
• Traditional CBA on infrastructure needs various detailed information thus it takes time and money, and the scope of analyses is limited within nearby region or lacks ground view to consider multiple projects .
• General equilibrium frameworks enables total evaluation of economic impacts beyond directly involved regions.
• IDE-GSM provides estimation of broader impacts on transport volumes and modal shifts
Geo-economic data in IDE-GSM
2018/11/8 4
Sub-national level: 98 economies (3,017 regions) National level:+ 71 countries
GDP by sector -Agriculture/Mining -Automotive -E&E -Textile & Germent -Food Processing -Other Mfg. -Services Population
GDP per capita by region(2010)
Estimating regional GDP by Satellite Imagery
5
Nighttime Lights Imagery of Myanmar Estimated GRDP per capita
+ Land cover
Transport network data in IDE-GSM
2018/11/8 6
Over 14,000 routes, including -Road -Sea -Air -Rail
Multi-modal transport model
Road network data
Manual/Automatic Compilation of Route data
• We consider major routes connecting big cities and provinces.
• We build the dataset manually based on the maps, existing database and field surveys.
• We are trying to construct the data from the third source data (such as OSM) and script, but still adjustment is needed.
7
Trial of building route data by script
In the field trip, we could drive the fastest in this section
8
1990
ASEAN
China
JapanIndia
EU USA
16.1
8.111.3
14.0
25.8 28.0
22.629.3
36.82.71.2
24.9
23.4
11.9
8.7
4.6
3.0
92.5
52.1
1999
ASEAN
China
JapanIndia
EU USA
118.5
19.325.8
52.7
65.5 88.2
45.745.0
54.34.44.9
35.2
60.6
42.6
33.8
12.9
14.7
158.0
66.0
2009
ASEAN
China
JapanIndia
EU USA
283.9
75.9125.5
296.8
143.8 84.5
62.372.5
72.724.421.8
70.0
97.6
114.3
126.4
75.2
101.3
89.5
57.8
31.0%
2.8%
17.6%
2.3%1.2%
24.7%
22.1%15.6%
5.9%3.3%2.8%
24.3%
1 4.5 6 3.8 3.2 9 1 5.2 6.5 4 3.2 9
1995
2015
1990
1999
2009
GDP share in the world
Trade (billion USD)
Background:
Big shift in the world
economy
EU28 Japan
China
ASEAN India
9
Source: ASEAN Secretariat, “ASEAN Community in Figures: Special Edition 2014”.
Progress of economic integration in East Asia
10
The evolution of production networks in East Asia
Source: Compiled from Hiratsuka (2006)
Thailand
•Spindle Motor
•Base
•Carriage
•Flex Cable
•Pivot
•Seal
•VCM
•Top Cover
•PCBA
•HGA
•HAS
Japan
•Cover
•Disk
•Screw
•Seal
•Ramp
•Top Cover
•Latch
•Plate Case
•Label
•Filter
•PCBA
•Suspension
USA
•Disk
•Head
•Suspension
Mexico
•Head
Taiwan
•Top Clamp
Hong Kong
•Filter
Philippines
•D. Plate
•Coil Support
•PCBA
Indonesia
•W. Suspension
•VCM
•PCBA
Malaysia
•Base
•Pivot
•Spacer
•VCM
•Card
•Top Clamp
•Disk
Singapore
•Cover
•Screw
•Pivot
•PC ADP
•Disk
China
•PCBA
•Carriage
•HGA
•Base
•Head
•Suspension
Global Purchasing by a HDD Manufacturer in 2005
11
Urbanisation
Source: ERIA(2015), originally made by Keola Souknilanh
12
Poor state of road infrastructure
National Road No.1, Bhutan
National Road No.1, Myanmar
Bypath of national road No.3, Indonesia
JAKARTA
Source: taken by Ikumo Isono
Sihanoukville airport upgrade
Highway: Kanchanaburi - Dawei
Expressway: Phnom Penh - Sihanoukville
SKRL: PP – Loc Ninh – HCMC
Mekong bridge in Neak Loung (NR1)
Reconstruction of NR3: Phnom Penh -Kampot
Dawei deep sea port
Cross-border facility at Bavet-Moc Bai
Sihanoukville port expansion
Upgrading Dawei airport
Da Nang airport: Passenger terminal
Yangon port: Quay cranes
Thilawa port improvement
Savannakhet airport improvement
Phnom Penh port rehabilitation
Da Nang port improvement
Koh Kong Industrial Estate
Poipet Industrial Estate
SKRL: Poipet - Sisophon (48km)
Pharma & biotech city in Ayutthaya
IT & ITES part in Phthum Thani CDZ
North-South High Speed Railway (to HCMC)
SEZ/FTZ in Dawei
Multimodal logistic park in Dawei
Special Border Zone at Myawadi
Route No.8: Kawkareik-Mawlamyine - Thaton
SEZ in Savannakhet
Border Trading Zone in Dansavanh
Nam Theun 2 and Nam Ngum 2 Hydropower Plant
Ports: Cai Lan, Lach Huyen
Noi Bai Airport terminal 2
Expansion of Cat Bi Airport
Rail link : Hanoi – Noibai AP, Lang Hoa Lac
Hoa Lac high tech park, Vietnam space center
ICT infrastructure enhancement
Hanoi
Yangon
Mawlamyaing
Dawei
Myawadi Khon Kaen
Vientiane
Savannakhet
Hanoi
Bangkok
Phnom Penh
Sihanoukville
MIEC
EWEC
Ho Chi Minh
Da Nang
Chennai
Bangalore
MRT network
Suvarnabhumi airport: Phase 2 development
Laem Chabang port: Phase 2 development
Highway management improvement
Bangkok
: Industrial Agglomeration
Project Progress Status
:Conceptual Stage
:Feasibility Study Stage
:Construction Stage
:Operation Stage
Legend
Selected Prospective Projects in Mekong Sub-region
Chennnai Port- Ennore Port accesssway
Outer ring road in Chennai: Phase 2
Ennore Industrial Park and SEZ
Chennai
High speed railway: Chennai - Bangalore
Expressway: Chennai - Bangalore
Bypass and express ways around HCMC
Cai Mep–Thi Vai port: development, improvement
Rail link: HCMC – Vung Tau, HCMC –My Tho
Petro-chemical complex
Transmission line: Can Tho – HCMC
Power plants in O Mon
Software technology park
Ho Chi Minh City (HCMC)
Selected Prospective Projects in Mekong Sub-region (2013)
ASEAN and East Asia still need infrastructure.
13
High demand of IDE-GSM in Asia
• High demand for transportation infrastructure
Heavy congestion in the big cities
Very poor road in rural areas
• Severe financial constraints of each country
• Poor socio-economic data
• Infrastructure improvement may change economic structure
• To prioritize infrastructure development, economic analysis using regional-wide dataset must be conducted and cannot wait for accurate data to be provided.
14
IDE-GSM: the model
We don’t have:
• Government expenditure
• Taxes
• Savings and investments
• Foreign exchange fluctuation
• Inflation/Deflation caused by change in the money supply
We have
• Firms
• Consumers
• Natural population growth
• Migration within a country
• Price fluctuation by domestic and international competition
15 15
Specification of Industries
Agricultural Sector
Mobile Labor Transport costs Manufacturing Sector
-Input-Output structure in M-sector
Service Sector
Transport costs
-Dixit-Stiglitz monopolistic competition
Transport costs All regions
-Dixit-Stiglitz monopolistic competition
-Constant-returns technology & monopolistic competition
16
Utility function
15
1
5
1
S
jjMA
S
j
MASjM
j
A QQQU
1
0
1
1
0
1
)(
)(
S
S
SS
S
jM
jM
jMjM
jM
jj
diiqQ
diiqQ
n
SS
n
MM
•Agriculture • 5 manufacturing • Service
17
1
0
1
) (
A
A
A
A
di i q Q R
A A
Wage and Price Index
• Agricultural sector
Nominal wage
Price Index
18
)(
)(
)()()(
1
rprL
rFrArw A
A
AA
)1(
1
1
)1()1()()(
AAA
R
s
A
srAA TrprG
• Manufacturing sector
Price index
Nominal wage
19
)1(
1
1
)1()1(11)()()()()(
MMMMM
R
s
M
srMMMMM TsGswsAsLrG
wM (r)
AM (r)
1
M E(s)s1
R
TrsM 1 M
GM (s)(1 M )
1
M
GM (r)1
1
Wage and Price Index(cont.)
• Service sector
Price index
Nominal wage
)1(
1
1
)1()1(1)()()()(
SSSS
R
s
S
srSSSS TswsAsLrG
S
SS
sGTsYrArw S
R
s
S
rsSS
1
)1(
1
1)()()()(
20
Wage and Price Index(cont.)
Labor migration
• Labor migration among sectors within a region
• Labor migration in a country
21
Agriculture 3.8 0.61 0.040
Automotive 4 0.57 0.020
Electronics 6 0.56 0.026
Textile 8.4 0.64 0.018
Food 5.1 0.61 0.033
Others 5.3 0.59 0.172
Service 3 1.00 0.687
Mining 5.6 0.25 0.004
Parameters specifying each industry
• Elasticity of substitution:
• Share of labor input:
• Share in consumption:
22
Transport Costs
First, we estimate firms’ behaviors on modal choice by MNL.
• Firms tend to use trucks for domestic partners.
• Larger the distance between trading partners, the more likely the firms are to choose air or sea.
• Machineries industry tend to use air transports for foreign partners without smooth border transaction at the borders.
Truck as a basis
Coef. S.D. Coef. S.D.
Abroad 3.573 *** 0.736 2.915 *** 0.428
ln Distance (Food as a basis) 0.444 *** 0.170 1.268 *** 0.167
*Textiles 0.104 0.126 -0.151 0.094
*Machineries 0.300 ** 0.135 0.112 0.086
*Automobile 0.201 0.174 -0.104 0.154
*Others 0.148 0.106 -0.068 0.066
Constant -5.711 *** 0.760 -9.621 *** 0.993
Country dummy: Indonesia as a basis
Philippines -0.336 0.470 0.364 0.446
Thailand -2.239 ** 0.904 -0.794 0.624
Vietnam -2.483 *** 0.683 -0.437 0.419
Statistics
Observations
Pseudo R-squared
Log likelihood
Air
1,312
0.3407
-321.5
Sea
23
Second, we develop a simple linear transport cost function with the parameters on time sensitiveness.
• A representative firm in machineries industry will make a choice between truck and air transport and choose the mode with the higher probability of the MNL result.
• A representative firm in the other industries will make a choice between truck and sea transport and choose the mode with the higher probability of the MNL result.
Air Sea Air Sea
Food 60,300,000 3,699 19,254 371
Textiles 2,022,900 11,218 2,968 825
Machineries 44,009 1,899 361 229
Automobile 225,394 7,693 886 628
Others 684,540 5,909 1,634 520
Domestic International
Probability Equivalent Distance with Truck (Kilometer): Domestic and International Transportation from Bangkok
24
Modal Mix of E&E Industry (from Ayutthaya, Thailand)
To Lamphun, Thailand To Phnom Penh To KL
Food Textile Machineries Automobile Others
ctime s 15.7 17.2 1803.3 16.9 16.5
Truck Sea Air Unit Source
cdist M 1 0.24 45.2 US$/km Map
Speed M 38.5 14.7 800 km/hour Estimation
ttrans MDom
0 11.671 9.01 hours Estimation
ttrans MIntl
13.224 14.972 12.813 hours Estimation & Map
ctrans MDom
0 190 690 US$ Map
ctrans MIntl
500 N.A. N.A. US$ Map
25
Making Scenarios: Trade Costs in GSM 26
26
Development of economic corridors
27
Scenario Speed of
trailers
Time required at
national borders
Money costs at
national borders
Without Baseline 38.5 km/h 13.2 hours 500 USD
With Corridor +
Facilitation 60 km/h 6 hours 250 USD
Upgrading roads
≈
Customs Facilitations
How to Estimate the Economic Impacts?
28
2010 2015
with infrastructure projects
already completed by 2015
Baseline
with no or limited development
projects by 2020
Alternative Scenarios
with corridor development by 2020
2030
Compare the differences
(10 years after)
GRP
Economic Impact
(% compared with
the baseline in 2030)
2020
Example 1:
Kuala Lumpur-Singapore high-speed rail (HSR)
• Only passengers can use HSR, no freight
• HSR’s cost per km:
8x of conventional train
2x of road
1 /2 of air
• Waiting time at stations
Longer waiting time => Lower frequency
• Over 200km/h (average speed)
The speed of conventional train is 40km/h
29
- 0
0 - 10
10 - 20
20 - 30
30 - 50
50 - 100
100 - 200
200 - 300
300 -
(Million USD)
Malaysia 1,005
Labuan -3 Johor 611
Kedah 17
Kelantan -8 Melaka -16 N. Sembilan -8 Pahang -26 P. Pinang 51
Perak 39
Perlis 3
Selangor 136
Terengganu -16 Sabah -24 Sarawak -32 Kuala Lumpur 278
Singapore 88
TOTAL 1,093
KL
Singap
ore
Iskand
ar
B. Pah
at
Mu
ar
Ayer Kero
h
Seremb
an
Pu
trajaya
Example 1: SG-KL HSR, result
30
31
https://www.nst.com.my/news/nation/2018/07/395111/japanese-study-finds-malaysia-could-make-us1589bil-annually-hsr
http://beltandroad.zaobao.com/beltandroad/news/story20180729-879026
Reported by Local
Newspapers
Example 2:
Infrastructure development in ASEAN
• Proposing a set of infrastructure development projects to achieve both high economic impact in one country and positive impacts in many provinces.
• Assuming additional NTB reductions.
32
Economic Impact in 2040
Source: ERIA (2010)
Japan's ministerial meeting for economic cooperation and infrastructure development (2013)
Analysis (previous version) is adopted as regional/national policy
Master Plan on ASEAN Connectivity (2010)
Source: ASEAN (2010) Source: Prime minister's office website
33
Comprehensive Asia Development Plan, independent research by ERIA
Example 3: Highways in Mongolia
• Some positive impacts are observed mainly Eastern Mongolia and Northeast China.
Source: Calculated by IDE-GSM
(Compared with Baseline in 2030)
Example 3: Changes in Traffic
Source: Calculated by IDE-GSM
• Traffic between Northeast China and Northwest China, through Mongolia East-West increased.
(Compared with Baseline in 2030)
Example 4:
Suez-Koper Link
• We incorporated NUTS 2 level data for EU while EU is still considered as a rest of world in the model.
• A new shipping link between Suez, Egypt and Koper, Slovenia will benefit some regions in Europe and many regions in East Asia.
Economic Impact in 2030
36
Dilemma in making a CGE model in Asia
2018/11/8 37
More realistic model
Lack of data
Parameters and data required
Need to estimate/interpolate data/parameters
Model should be realistic but simple
Dilemma in Making a CGE model in Asia
2018/11/8 38
Huge diversity in economic structure
Drastically changing in economic structure
Parameters and data required
Parameters/data should be changing dynamically
Model should be realistic but simple
Dilemma in Making a CGE model in Asia
2018/11/8 39
Rapidly developing infrastructure project
No integrated data set/ standard model
High demand in CGE analysis on the project
Model/data should be developed at a time
Model should be realistic but simple
Conclusion
• A CGM model for Asia should be realistic, but simple.
• There is no data and no standard model in Asia, but cannot wait for perfect data/model. Agile system development is required.
• There might be a ‘free lunch’ in Asia …? Often, the source of finance for infrastructure is outside country and term and conditions are not determined. So, a tool like IDE-GSM is required, before conducting detailed CBA.
40
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