The Head of Asia Desk in OECD, Mr Kensuke Tanaka, presented some of the key findings of the OECD’s Economic Outlook for Southeast Asia, China, and India 2019. He discussed some of the growth risks and structural challenges faced by countries in the region, namely trade tension, opportunities and risks of financial technology, impact of natural disasters, digitalisation, traffic congestion, and education.

1. GROWTH AND KEY STRUCTURAL
POLICY CHALLENGES IN
EMERGING ASIA
Kensuke Tanaka, Head of Asia Desk
OECD Development Centre
7th OECD-AMRO-ADB-ADBI-ERA Asian Regional Roundtable
Session 2
18 June, Jakarta, Indonesia
Based on
“Economic Outlook for Southeast Asia, China and India”

2. 2
Growth prospects in Emerging Asia
Real GDP growth in Emerging Asia, Percent
Note: Data of India and Myanmar follow fiscal years. Myanmar’s 2018 data refers to the interim 6-month period, from April 2018 to September 2018 while the 2019 data refers to the period from October 2018 to
September 2019. Source: OECD Development Centre, Medium-term Projection Framework (MPF-2019).
Group Country 2019-23 average
ASEAN-5
countries
Indonesia 5.3
Malaysia 4.6
Philippines 6.6
Thailand 3.7
Viet Nam 6.5
Brunei
Darussalam &
Singapore
Brunei Darussalam 2.0
Singapore 2.7
CLM countries Cambodia 6.9
Lao PDR 7.0
Myanmar 7.0
China & India China 5.9
India 7.3
Average of ASEAN-10 5.2
Average of Emerging Asia 6.1

3. 3
• Trade tension
• Financial market: opportunities and
risks of Fintech
• Natural disaster response
• Digitalization
• Traffic congestion
• Education
Growth Risks and Structural Challenges

4. 4
Impact of trade frictions will differ
by country
0
2
4
6
8
10
12
14
16
Brunei
Cambodia
India
Indonesia
LaoPDR
Malaysia
Myanmar
Philippines
Singapore
Thailand
VietNam
Industrial supplies, primary Industrial supplies, processed
Fuels and lubricants, primary Parts and accessories of capital goods (except transport equipment)
Parts and accessories of transport equipment Food and beverages, primary, mainly for industry
Food and beverages, processed, mainly for industry Fuels and lubricants, processed (other than motor spirit)
%
Note: Calculations were based on BEC classification.
Source: OECD Development Centre calculation based on UN Comtrade data.
Intermediate goods exports to China as a percentage of GDP, 2017

5. • Impact through GVC
• Trade diversion
• Adjustment speed
• Short-term and long-term….

6. Fintech’s use has broadened
Service Description
Remittance, money
transfer and mobile
payments
 Web-based or application-based electronic platforms for local or
overseas monetary transfers or payments for goods and services
acquired
 Remittance fees, if any, are generally more competitive than those
offered by traditional financial institutions
 Widespread in Emerging Asia
Alternative risk
assessment for
insurance and lending
 Alternative insurance and credit scoring services using machine
learning tools and big data to assess the risks involved
 Used to obtain tailored insurance policies or loan packages even in the
absence of traditional documentary requirements
 Relatively at its nascent stage in Emerging Asia
Lending and capital
raising platforms
 Platforms that support peer-to-peer lending services as well as
donation, debt and equity crowdfunding, which link investors and
capital recipients directly
 Gaining ground in many Emerging Asian countries
Wealth management  Utilises machine learning tools in managing various types of financial
assets, which include but not limited to robo advisors and algorithmic
trading
 Relatively at its nascent stage in Emerging Asia
Platforms comparing
features of financial
products
 Data aggregators focusing on the characteristics of financial products
that are available in the market such as loan packages and insurance
policies
 Compare interest rates, premiums and charges among other features
that potential clients will likely get from different insurers and lenders
based on the data they provide
 Available in many Emerging Asian countries

7. Mitigating the risk of Fintech
Country Regulatory
sandbox
Lending and
capital raising
Data protection and
cyber security
Brunei Darussalam X X X
Cambodia *1 nci *1
China *2 X X
India *3 X X
Indonesia X X X
Lao PDR nci nci X
Malaysia X X X
Myanmar nci nci *4
Philippines *5 *5 X
Singapore X X X
Thailand X X *6
Viet Nam *7 *7 X

8. 8
Mitigation of impact of natural
disasters
0
10
20
30
40
50
60
70
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Brunei
Darussalam
Cambodia
China
India
Indonesia
LaoPDR
Malaysia
Myanmar
Philippines
Singapore
Thailand
VietNam
Earthquake and Volcanic activity, LHS Flood, LHS Storm, LHS Others, LHS Total incidents per year, RHS
Incidence% of GDP
Source: EM-DAT & OECD Development Centre calculations using World Bank data.

9. Firms need to make more effective use of
ICT tools…

10. 10
Use of digital technologies affects aggregate
and firm productivity
Note: Average TFP in firms with websites and/or using email is presented as a percentage of the average TFP of firms using neither technology, so 100%
represents no difference in the average productivity of these two groups. Cambodia and Lao PDR were excluded from this analysis because they contained too
few (fewer than 100) observations with sufficient data.
Source: OECD Development Centre’s calculations, using World Bank (2017), Enterprise Surveys, World Bank, Washington, D.C.
Average TFP in manufacturing firms with ICT use as a percent of
average TFP in firms without ICT use
Percent

11. Source: ASEAN Secretariat.
ASEAN Smart Cities Network pilot cities
countries Cities
Brunei Darussalam Bandar Seri Begawan
Cambodia Battambang, Phnom Penh, Siem Reap
Indonesia Banyuwangi, DKI Jakarta, Makassar
Lao PDR Luang Prabang, Vientiane
Malaysia Johor Bahru, Kota Kinabalu, Kuala Lumpur, Kuching
Myanmar Mandalay, Nay Pyi Taw, Yangon
Philippines Cebu City, Davao City, Manila
Singapore Singapore
Thailand Bangkok, Chonburi, Phuket
Viet Nam Da Nang, Ha Noi, Ho Chi Minh City

12. 12
Traffic congestion is
a pressing issue
Note: Travel Time Index is defined as peak hour travel time divided by free-flow hour travel time, where 1=no congestion and higher values indicate worse traffic. In travel time figures, markers refer to average travel time at a
specific hour in the day while the vertical bars represent the ranges of travel time. Traffic congestion data are based either on the entire specified road if possible or a selected representative segment of a specified road. Data are
not necessarily comparable across the five areas shown above.
Source: OECD Development Centre calculations based on data from Google Maps (accessed on 24th September/2018).

13. 13
Mass transport systems are catching up
City Bus Bus Rapid
Transit
Metro and
light rail
Bandar Seri Begawan, Brunei
Darussalam
✓
Phnom Penh, Cambodia ✓
Jakarta, Indonesia* ✓ ✓
Vientiane, Lao PDR ✓
Kuala Lumpur, Malaysia ✓ ✓
Yangon, Myanmar ✓
Manila, the Philippines ✓ ✓
Singapore, Singapore ✓ ✓
Bangkok, Thailand ✓ ✓ ✓
Hanoi, Viet Nam* ✓ ✓
Ho Chi Minh City, Viet Nam* ✓
Beijing, China ✓ ✓ ✓
Shanghai, China ✓ ✓
Delhi, India ✓ ✓
Mumbai, India ✓ ✓
Publicly accessible transportation modes in selected Emerging Asian cities
Note: (*) Metro or light rail system currently under construction.
Source: OECD Development Centre compilation, using national sources.

14. 14
• Infrastructure and mass transportation expansion
and upgrade
• Price-based and non-price-based vehicle
ownership and use policies (e.g. vehicle purchase
tax, license quota, fuel tax, road rationing, road use
charge and parking fee)
• Effective use of ICT and big data
• Flexible work arrangements
• Improving urban planning
Traffic congestion policy options

15. Price-based and non-price-based policies
need to be effectively used
Source: OECD Development Centre.
Price-based Non-price-based
Vehicle
ownership
• Vehicle purchase
taxes
• Recurring taxes and
charges
• License quotas
Vehicle use
• Fuel taxes and
subsidies
• Road use pricing and
parking fees
• Road rationing

16. Managing transportation demand through
flexible working arrangements
Source: Eurofund (2018), European Working Conditions Survey (database).
Employees’ working hours flexibility in European countries, 2015
0
10
20
30
40
50
60
70
80
90
100
They are set by the company/organisation with no possibility for changes
You can adapt your working hours within certain limits (e.g. flextime)
You can choose between several fixed working schedules determined by the company/organisation
Your working hours are entirely determined by yourself%

17. Quality of education is important
Note: ASEAN Average is the average PISA score of Indonesia, Malaysia, Singapore,
Thailand and Viet Nam.
Source: OECD, PISA 2015 database.
OECD PISA score in Southeast Asia and OECD countries, 2015
Average for all students
300
350
400
450
500
Reading Mathematics Science
ASEAN Average OECD Average