TOWARDS
A GREEN
AND RESILIENT
THAILAND
Muthukumara Mani and Hector Pollitt
September 2024
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Cover Illustration: Ho Thuy Tien.
TOWARDS
A GREEN
AND RESILIENT
THAILAND
Muthukumara Mani and Hector Pollitt
September 2024
Photo: © Praisaeng / Shutterstock.
Further permission required for reuse.
CONTENTS
Acknowledgements.........................................................................................................................................x
Acronyms & Abbreviations............................................................................................................................xi
Executive Summary.......................................................................................................................................xii
1 From Growth at Any Cost to Growing Sustainably 1
1.1. Thailand’s economic aspirations.......................................................................................................... 2
1.2. Emerging constraints on growth.......................................................................................................... 2
1.3. Cross-cutting challenges to future growth.......................................................................................... 4
1.4. Specific climate and environmental challenges ................................................................................... 4
1.4.1. Climate vulnerability .................................................................................................................................................................. 4
1.4.2. Carbon emissions and commitments .............................................................................................................................. 6
1.4.3. Degradation of natural resources........................................................................................................................................ 9
1.5. The opportunity for a new growth model that is low-carbon and climate-resilient...................... 13
2 Dealing with climate risks 15
2.1. Natural Climate Hazards.................................................................................................................. 16
2.2. Physiographic regions and major climate influences......................................................................... 17
2.3. Forests and built-up area .................................................................................................................. 18
2.4. Estimating current and future impacts of climate hazards............................................................... 19
2.4.1. Floods and sea level rise......................................................................................................................................................... 19
2.4.2. Drought and heat stress........................................................................................................................................................ 25
2.4.3. Other disasters........................................................................................................................................................................... 28
3 Transitioning to a Bio-Circular-Green Economy 31
3.1. Methodology...................................................................................................................................... 32
3.1.1. E3-Thailand Model.................................................................................................................................................................... 32
3.1.2. Input-output analysis................................................................................................................................................................ 33
3.1.3. Future Technology Transformations (FTT) model................................................................................................. 34
iv Towards a Green and Resilient Thailand
3.2. Design of the modeling scenarios.................................................................................................... 34
3.2.1. Assessing the impacts of climate change in Thailand............................................................................................. 34
3.2.2. Assessing the potential to adapt to climate change in Thailand....................................................................... 35
3.2.3. Assessing measures to reduce emissions within Thailand................................................................................... 36
3.2.4. Assessing the move to a circular economy................................................................................................................. 36
3.3. The impacts of climate change in Thailand....................................................................................... 38
3.4. Adapting to climate-induced floods ................................................................................................. 40
3.5. Reducing emissions within Thailand..................................................................................................... 41
3.6. Moving to a more circular economy.................................................................................................... 45
4 Balancing Act: Assessing Thailand’s Ecological Thresholds 47
4.1. Tipping points..................................................................................................................................... 48
4.2. An Integrated Economic-Environmental Model for Thailand.......................................................... 48
4.3. LULC Change Modeling..................................................................................................................... 49
4.4. ESM..................................................................................................................................................... 49
4.5. Model Integration and Interaction: The Dynamic IEEM+ESM Approach....................................... 50
4.6. Scenario Overview............................................................................................................................. 51
4.7. Results................................................................................................................................................. 51
5 Overall conclusion and recommendations 61
5.1. A way forward.................................................................................................................................... 62
5.2. Multi-sector participation.................................................................................................................. 62
5.3. Ecological thresholds.......................................................................................................................... 63
5.4. Action priorities................................................................................................................................ 64
5.4.1. Adaptation................................................................................................................................................................................... 64
5.4.2. Mitigation........................................................................................................................................................................................ 68
5.4.3. Circular economy..................................................................................................................................................................... 71
Towards a Green and Resilient Thailand v
Boxes
Box 1. Defining sustainable development: BCG and BCG+.............................................................. 3
Box 2. The Bangkok E-Bus Program................................................................................................. 44
Tables
Table ES1. Priority Adaptation Actions.................................................................................................. xvii
Table ES2. Priority Mitigation Actions.....................................................................................................xix
Table ES3. Priority Circular Economy Actions....................................................................................... xxii
Table 2.1. Channels of climate-related damages.................................................................................... 19
Table 2.2. Increase in expected river flood damage in 2050 from 2015 base year (USD m,
2010 prices)............................................................................................................................ 23
Table 2.3. Costs of sea level rise (SLR) and coastal erosion in 2050, USDm at 2010 prices,
compared to 2015.................................................................................................................. 25
Table 2.4. Economic cost from loss of outdoor labor productivity and indoor cooling in 2050,
USDm at 2010 prices, compared to 2015............................................................................ 27
Table 2.5. Loss of production in 2050, USDm at 2010 prices, compared to 2015............................. 28
Table 3.1. How the models in this chapter are applied......................................................................... 32
Table 3.2. How the impact channels are represented in E3M............................................................... 35
Table 3.3. Circular economy policies in the modeled scenario, targets met by 2030.......................... 37
Table 3.4. Indicative impact of climate-related policies on fiscal balances (% of GDP)....................... 45
Table 4.1. Contribution of Ecosystem Services (ES) to the economy as a cumulative difference
from the baseline in 2050 in USD million.............................................................................. 56
Table 4.2. Impacts on macro-economic indicators as a difference from the baseline in 2050 or
cumulative impact as indicated in USD million...................................................................... 57
Table 5.1. Prioritization Approach for Policy Actions............................................................................ 64
Table 5.2. Priority Adaptation Actions................................................................................................... 65
Table 5.3. Priority Mitigation Actions..................................................................................................... 68
Table 5.4. Priority Circular Economy Actions........................................................................................ 71
Table SI1. Accounts in the 2019 Social Accounting Matrix for Thailand............................................... 83
Table SI2. Reclassified Land Use Land Cover (LULC) classes and areas.............................................. 85
Table SI3. Macroeconomic results in millions of USD........................................................................... 95
Table SI4. Macroeconomic results in millions of USD, continued......................................................... 95
Table SI5. Macroeconomic results in millions of USD, continued......................................................... 96
Table SI6. Macroeconomic results in millions of USD, continued......................................................... 96
Table SI7. Macroeconomic results expressed as average growth rates over simulation period as
percentage point difference from the baseline...................................................................... 97
vi Towards a Green and Resilient Thailand
Figures
Figure ES1. Impact of different categories of climate damages on GDP................................................xiv
Figure ES2. Impact of policy interventions to safeguard wealth...............................................................xv
Figure ES3. GDP and Employment impact of carbon taxes....................................................................xvi
Figure 1.1. Per capita GDP and GHG emissions in ASEAN countries, 2018........................................... 6
Figure 1.2. Emissions by GHG and by Sector, mtCO2eq.......................................................................... 7
Figure 1.3. Thailand’s Long-Term Low Greenhouse Gas Emission Scenario........................................... 9
Figure 1.4. Resource rents as percent of Thailand’s GDP ..................................................................... 10
Figure 1.5. Components of Thailand’s national wealth per capita......................................................... 11
Figure 1.6. Components of natural resource wealth per capita over time............................................ 12
Figure 1.7. Net natural resource wealth depletion in Thailand............................................................... 12
Figure 1.8. Adjusted savings – natural resources depletion in Thailand as percent of GNI compared
to neighboring countries........................................................................................................ 13
Figure 2.1. Disaster events reported by EM-DAT between 1990 and 2018 for Thailand.................... 16
Figure 2.2. Thailand Köppen-Geiger climate classification mapped against population density............ 17
Figure 2.3. Land cover and built-up assets............................................................................................... 18
Figure 2.4. River flood hazard across Thailand ....................................................................................... 20
Figure 2.5. EAI of riverine floods on population mortality..................................................................... 21
Figure 2.6. EAI of riverine floods on built-up damage............................................................................ 21
Figure 2.7. EAI of agricultural land to riverine floods............................................................................. 22
Figure 2.8. Coastal Flood Hazard across Thailand (100-year return).................................................... 23
Figure 2.9. Expected annual impact of coastal floods - Population mortality........................................ 24
Figure 2.10. Expected annual impact of coastal floods on built-up damage............................................ 24
Figure 2.11. Frequency of drought hazard................................................................................................. 25
Figure 2.12. Heat Stress for a 20-year return period (WBGT C)............................................................ 26
Figure 2.13. Annual Population exposure to heat stress........................................................................... 27
Figure 2.14. Rainfall-triggered Landslide Hazard Index for Thailand........................................................ 29
Figure 2.15. Strong cyclone hazards........................................................................................................... 29
Figure 2.16. Expected Annual Impact over built-up land.......................................................................... 29
Figure 3.1. Overall structure of the E3-Thailand model......................................................................... 33
Figure 3.2. Share of damages avoided, %................................................................................................ 35
Figure 3.3. Impact of different categories of climate damages on GDP (RCP8.5) (% from baseline
with no climate change)......................................................................................................... 38
Figure 3.4. Impact of a major flood on GDP in the year the flood occurs (here 2030)........................ 39
Figure 3.5. Percentage change from baseline in each sector’s production............................................. 40
Towards a Green and Resilient Thailand vii
Figure 3.6. Impact of a major flood in 2030 on GDP (% from baseline) with and without flood
protection measures............................................................................................................... 41
Figure 3.7. Potential decarbonization scenarios for Thailand................................................................. 42
Figure 3.8. How the main sectors meet the criteria for effective carbon pricing.................................. 42
Figure 3.9. GDP and Employment impact of carbon taxes.................................................................... 43
Figure 3.10. EV market shares in new vehicle sales and in the vehicle fleet, %........................................ 44
Figure 3.11. Potential economic impact of moving to a circular economy.............................................. 46
Figure 4.1. Overview of the dynamic IEEM+ESM workflow applied to Thailand................................. 51
Figure 4.2. DEGRADE PES+ and POLICY PES+ carbon storage climate mitigation ecosystem
services in 2050 as a difference from the baseline in percent.............................................. 52
Figure 4.3. DEGRADE PES+ and POLICY PES+ erosion mitigation ecosystem services in 2050
as a difference from the baseline in percent.......................................................................... 53
Figure 4.4. DEGRADE PES+ and POLICY PES+ water regulation ecosystem services as a difference
from the baseline in percent.................................................................................................. 54
Figure 4.5. DEGRADE PES+ and POLICY PES+ water purification ecosystem services (nutrient
retention) as a difference from the baseline in percent ...................................................... 54
Figure 4.6. DEGRADE PES+ and POLICY PES+ crop pollination ecosystem services as a difference
from the baseline in percent ................................................................................................. 55
Figure 4.7. Baseline coastal vulnerability, index value between 1 (very low exposure) to 5 (very
high exposure)........................................................................................................................ 56
Figure 4.8. GDP trajectory as a difference from the baseline in USD million........................................ 58
Figure 4.9. Wealth trajectory as a difference from the baseline in USD million.................................... 58
Figure 4.10. Scenario impacts on employment as a difference from the baseline in 2050...................... 59
Figure 4.11. Change in number of individuals in poverty as a difference from the baseline in 2050...... 59
Figure SI1. IEEM+ESM countries indicated in green................................................................................ 81
Figure SI2. Reclassified base Land Use Land Cover (LULC) Map for 2020........................................... 85
Figure SI3. Overview of the dynamic IEEM+ESM workflow applied to Thailand................................. 88
viii Towards a Green and Resilient Thailand
Towards a Green and Resilient Thailand ix
Photo: © Freedom_Studio / Shutterstock.
Further permission required for reuse.
Photo: © WitthayaP / Shutterstock.
Further permission required for reuse.
ACKNOWLEDGEMENTS
This report was written by a core team comprising
Muthukumara Mani (TTL), Hector Pollitt (co-TTL),
Waraporn Hirunwatsiri, Sailesh Tiwari, Mattia Amadio,
Erica Honeck, Onil Banerjee, Rattanyu Dechjejaruwat,
Anil Markandya and S. Vaideeswaran. The report was
prepared under the overall direction of Mona Sur (Practice
Manager, SEAE2), Lars Christian Moller (Practice Manager,
EEAM2) and Fabrizio Zarcone (Country Manager). The
team extends thanks to Peer Reviewers, Ajay Nair, David
Kaczan, and Luis Diego Herrera Garcia for their thoughtful
comments. The team appreciates the Government of
Thailand participants for their insightful contributions to
the workshop held on June 19, 2024.
x Towards a Green and Resilient Thailand
Acronyms & Abbreviations
ANS Adjusted Net Savings
BCG Bio-Circular-Green
CCDR Country Climate and Development Reports
CET Constant Elasticity of Transformation
CGE Computable General Equilibrium
CLUE Conversion of Land Use and its Effects
Dyna-CLUE Dynamic CLUE
EIA Environmental Impact Assessments
E3M E3-Thailand Model
EV Electric vehicles
ES Ecosystem services
EPR Extended producer responsibility
ESM Ecosystem Services Modeling
FDI Foreign direct investment
FTT Future Technology Transformations
GAR Global Assessment Report
GDP Gross Domestic Product
GHG Greenhouse gases
GHS Global Human Settlement
GIS Geographic Information Systems
GNI Gorss National Income
IEEM Integrated Economic-Environmental Model
IO Input-output
InVEST Integrated Valuation of Ecosystem Services and Tradeoffs
IPPU Industrial processes and product use
LULC Land Use Land cover
LT-LEDS Long-Term Low Greenhouse Gas Emission Development Strategy
NDC Nationally Determined Contribution
RCP Relative Concentration Pathway
SAM Social Accounting Matrix
SEEA United Nations System of Environmental-Economic Accounting
SLR Sea level rise
SME Small- and medium-sized enterprises
THB Thai Baht
UNFCCC UN Framework Convention on Climate Change
WBGT Wet-Bulb Globe Temperature
Towards a Green and Resilient Thailand xi
EXECUTIVE
SUMMARY
INTRODUCTION
Thailand has made significant progress in its economic development, transitioning from a low-
income to an upper-middle-income country. Going forward, the country is facing persistent
challenges, including a deceleration in economic growth, climate vulnerability, and environmental
degradation.
The government has outlined its vision for a Bio-Circular-Green (BCG) economy to create a
sustainable and competitive economic landscape to tackle these challenges. Introduced in 2021,
the BCG model seeks to combine Thailand’s biological and cultural diversity with technological
innovation to create a new growth paradigm.
Mounting evidence shows that Thailand is extremely vulnerable to climate change, with rising
sea levels, extreme weather events, and changing precipitation patterns posing significant
risks to both urban and rural areas. The nation is vulnerable to a range of natural hazards,
including floods, landslides, tropical cyclones, droughts, and coastal erosion. An uneven distribution
of climate impacts across the country highlights the need for targeted interventions to address
specific vulnerabilities. For example, Thailand’s population is predominantly concentrated in urban
areas, with rapid urbanization increasing the vulnerability of densely populated concentrations
to climate-related risks, particularly floods. Lower-income households, often residing in hazard-
prone areas, face greater challenges due to limited access to essential services. The country’s vital
agricultural sector is also significantly threatened by altered rainfall patterns and temperature
extremes, jeopardizing crop production.
The depletion of natural resources, along with environmental degradation, further exacerbate
the challenges faced by Thailand. Forest coverage is decreasing, and built-up assets, particularly in
major cities, are susceptible to the impacts of climate hazards. The country’s rich natural capital plays
a crucial role in supporting local livelihoods, and the loss of biodiversity and ecosystem functions
poses significant risks to communities and key economic sectors. For example, the total loss of
land due to coastal erosion is estimated at two square kilometers per year, with a value equal to
.04 percent of gross domestic product (GDP). Cities and economic activities in coastal areas are
especially vulnerable to coastal erosion.
Given the increasing climate challenges, this report updates Thailand’s BCG model for current
circumstances. We call it BCG+. The report uses advanced modeling and other cutting-edge
xii Towards a Green and Resilient Thailand
analytics to take a whole-of-the-economy perspective so that BCG+ is assessed within the context
of broader economic development. Beyond environmental concerns, Thailand’s economic risks,
tied to global trends and its reliance on tourism, necessitate a revised development model. The
BCG+ economy could mitigate these exposures by reducing reliance on global commodity prices
and enhancing economic resilience. By integrating measures on climate resilience, sustainable
resource management, and inclusivity in its development strategy, Thailand can work towards
achieving its vision of a BCG economy.
THE BCG+ TRANSITION
Transitioning to a BCG+ economy requires contributions from all sectors of society, with a
focus on sector-specific characteristics. Whole-economy policies such as carbon taxes need to
consider technological nuances for effectiveness. Circular production poses additional challenges
due to multiple inputs and outputs in the business model. Coordination between the public and
private sectors is imperative. The public sector must initiate change, finding financing solutions for
actions like climate adaptation, potentially through an economy wide carbon tax. Simultaneously,
private companies bear responsibility for improving efficiency, fostering innovation, and aligning
product designs with bio-circular goals.
The transition offers macro-level opportunities, showcasing potential benefits like increased
economic welfare, higher incomes, and enhanced employment levels. Technological
advancements and undiscovered productivity avenues underpin these opportunities, positioning
the BCG+ economy as a driver for economic development. Crucially, this shift safeguards Thailand
from future climate and economic risks while preserving natural capital for sustainable growth.
METHODOLOGY
Macro-level and sectoral modeling tools can identify the whole-economy effects of the BCG+
challenge. Although there is considerable uncertainty about the future economic impacts of climate
change, modeling tools can help to identify which parts of the economy are most vulnerable,
both directly and indirectly. Similarly, for climate change mitigation and other aspects of BCG+,
models can be useful in planning future policy. It is important that models are applied appropriately,
especially given data limitations related to climate change and potential climate change adaptation
measures.
The report applied a suite of advanced modeling tools. The broad coverage of the BCG+
development model means that a variety of quantitative tools is required to assess impacts. The
report uses a combination of macro-econometric, input-output, and technology diffusion modeling.
It also applies a Computable General Equilibrium model that is linked to high-resolution spatial
Land Use Land Cover (LULC) analysis and an ecosystem services model. In all cases, model results
are compared to a “business-as-usual” baseline scenario to identify the climate and policy shocks.
Executive Summary xiii
KEY FINDINGS
The report underscores that Thailand’s agriculture and fishing sectors are particularly
susceptible to climate change, a vulnerability heightened by the country’s substantial local
fishing and shrimp farming industries. This susceptibility is critical as many low-income households
rely on these sectors for their livelihoods. The potential impacts are severe: agriculture could
experience production losses ranging from $2.9 billion to $5.4 billion, while up to $26.2 billion of
fishing production value is at risk. Furthermore, heat stress will severely impact ocean ecosystems,
leading to significant fishing losses across all climate scenarios. Additionally, climate change is
already reducing productivity in outdoor labor sectors such as agriculture and construction, with
potential productivity losses doubling by 2050. Although indoor labor productivity, supported by
air conditioning, will face less of an impact, the cost of installing and maintaining cooling systems
could reach $11 billion to $17 billion annually by 2050 (Figure ES1).
Figure ES1. Impact of different categories of climate damages on GDP
1%
0%
-1%
-2%
-3%
-4%
-5%
2020 2025 2030 2035 2040 2045 2050
Cooling Agri & Fish Small floods Labor Prod
Sea level Tourism Interaction e ects Net Outcome
The report also explores the severe economic implications of approaching ecological tipping
points, such as excessive deforestation and flooding. It compares two scenarios: DEGRADE,
which involves ongoing deforestation and increased flooding, and POLICY, which includes proactive
measures to mitigate these effects. Thailand’s forest cover has already declined by 12% since 2000,
and continued deforestation could lead to substantial ecological and economic losses. Effective
policy interventions, such as halting deforestation and promoting reforestation, could mitigate these
impacts. Without action, Thailand might face up to $553 billion in GDP losses by 2050. However,
xiv Towards a Green and Resilient Thailand
strategic policies could reduce these losses by 68% and potentially enhance cumulative wealth by
$54 billion through reforestation and afforestation initiatives.
Figure ES2. Impact of policy interventions to safeguard wealth
4,000
2,000
Millions of USD
0
-2,000
-4,000
-6,000
-8,000
24
26
28
30
32
34
36
38
40
42
44
46
48
50
20
20
20
20
20
20
20
20
20
20
20
20
20
20
DEGRADE_OPT DEGRADE_PES+
POLICY_OPT POLICY_PES+
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
The report highlights that climate change could significantly affect Thailand’s economy, especially
through increased flood damage and sea-level rise. For instance, the economic impact of a major
flood in 2030 could decrease GDP by up to four percentage points. Additionally, costs related to
coastal erosion and sea-level rise are projected to increase by approximately $6 billion over time.
Addressing these risks will require comprehensive climate adaptation and mitigation strategies.
This includes implementing carbon pricing mechanisms and accelerating the transition to electric
vehicles (EVs). Carbon pricing can incentivize emission reductions and potentially boost GDP and
employment if the revenues are used to lower other taxes (Figure ES3). However, adaptation costs
could reach at least 1.6 percent of GDP by the 2030s, with the government likely covering most
of these expenses. Power sector reforms, aimed at reducing emissions, may reduce carbon tax
revenues, while fuel excise duties could initially increase but decrease with the transition to EVs.
A successful transition to a circular economy by 2030 could lead to a 1.0 percent increase
in GDP and the creation of 160,000 jobs. This shift, driven by improved waste management
practices and reduced reliance on virgin resources, offers substantial economic benefits. For
example, reducing food waste could boost agricultural and food exports, and transforming waste
into new materials could increase value added in advanced manufacturing and service sectors.
However, the success of these measures will depend on the availability of skilled workers and the
need for sector-specific assessments to ensure effective implementation.
Executive Summary xv
Figure ES3. GDP and Employment impact of carbon taxes
GDP impact, % from baseline Employment impact, % from baseline
2.5 1.2
1.0
2.0
0.8
1.5
0.6
1.0
0.4
0.5 0.2
0.0 0.0
2020 2025 2030 2035 2040 2020 2025 2030 2035 2040
NDC Ambitious NDC Ambitious
FOCUS AREAS AND RECOMMENDATIONS
While all actions in this report are valuable, some are more urgent due to their path
dependencies and the opportunities they create, such as governance enhancements leading
to larger adaptation investments. The report categorizes actions into short-term (by 2030),
medium-term (by 2040), and long-term priorities (beyond 2040-50). Certain measures, including
those improving economic and fiscal management, governance, and job creation, will advance both
climate and development goals.
Adaptation is a major focus. Thailand should prioritize planning and preparing for climate impacts
like flooding. Implementing early warning systems, improving access to essential services for lower-
income households, investing in climate-resilient infrastructure, and enforcing land use policies are
crucial. Measures such as sustainable land use and green infrastructure can reduce flood damage
and other climate risks, potentially lowering the GDP impact of major floods in 2030 by four
percentage points. Adapting existing infrastructure and addressing other climate impacts, like
reduced fish catches and heat stress, are more challenging. Overall adaptation expenses could be
at least 1.6 percent of GDP.
The study’s modeling informs key policy recommendations for climate adaptation in Thailand.
These recommendations, detailed in Table ES1, are vital for enhancing resilience and mitigating
climate impacts. Integrating these strategies into Thailand’s adaptation efforts will build a more
resilient economy, improve quality of life, and ensure a sustainable future. Investing in adaptation
protects communities and infrastructure, reduces disaster-related losses, and enhances productivity
in key sectors.
Mitigating climate change is also crucial. Thailand faces challenges in reducing its carbon footprint
and achieving carbon neutrality by 2050 amid rapid urbanization and fossil fuel reliance. Key
strategies include comprehensive policies, renewable energy investments, and clean technologies.
xvi Towards a Green and Resilient Thailand
Transitioning to renewable energy, improving energy efficiency, and promoting electric vehicles
are essential. Carbon pricing and electric vehicle adoption will help reduce emissions. Success
requires strong policies, collaboration between government and industry, and public awareness.
Key recommendations for mitigation strategies are outlined in Table ES2.
The roles of the public and private sectors in achieving carbon neutrality are distinct yet
interconnected. The public sector must craft and enforce policies, invest in renewable infrastructure,
and raise awareness. The private sector should implement these policies through innovation and
investments in clean technologies. Effective collaboration between government and industry is
essential for a unified approach to carbon mitigation.
Embracing a circular economy is vital, particularly for addressing plastic waste in the Chao
Phraya River. Transitioning to this model reduces plastic consumption, promotes recycling, and
minimizes waste. Policies like extended producer responsibility and eco-design standards can
curb plastic pollution. Investing in waste management infrastructure and recycling technology will
enable efficient waste recovery. The public sector should set regulatory frameworks and invest in
infrastructure, while the private sector should drive innovation and improve product design. Key
recommendations for transitioning to a circular economy are detailed in Table ES3.
Table ES1. Priority Adaptation Actions
Action Description Urgency Co-benefits Feasibility
Implement Given the significant projected impact of S 3 L
flood floods, Thailand must prioritize comprehensive
management flood management strategies to reduce the
strategies vulnerability of communities and infrastructure.
Key measures include investing in flood control
infrastructure like levees and flood barriers,
implementing nature-based solutions such as
wetland restoration and floodplain zoning, and
strategically locating new infrastructure away
from flood-prone areas. Enhancing resilience
through improved drainage systems and
promoting green infrastructure can further
mitigate the adverse impacts of floods. (Ministry
of Natural Resources and Environment,
Ministry of Interior, Urban Local Bodies and
Communities)
Develop Early warning systems are vital for preparedness S 3 L
early warning and reducing the risk of loss during extreme
systems weather events. Thailand should invest in advanced
and enforce technologies and community engagement for
building these systems. Enforcing building regulations to
regulations ensure structures can withstand and are elevated
above flood levels is essential. Strategic planning
Executive Summary xvii
Action Description Urgency Co-benefits Feasibility
and zoning in flood-prone areas, guided by risk S 3 L
assessments, can minimize exposure, and promote
sustainable development. (Ministry of Natural
Resources and Environment, Ministry of Interior,
Ministry of Agriculture, Local Government Units
and Community Organizations)
Enhance With the increasing threat of sea-level rise M 2 HL
coastal and coastal erosion, Thailand should enhance
resilience coastal resilience. This includes implementing
nature-based solutions like mangrove restoration
and beach nourishment and investing in hard
infrastructure like seawalls and breakwaters.
Developing coastal zone management plans
that integrate climate considerations and involve
local communities is crucial for sustainable
coastal adaptation. (Department of Marine and
Coastal Resources, Department of National
Parks, Wildlife and Plant Conservation. Local
Community Groups)
Promote Climate change poses significant risks to M 1 L
climate-smart Thailand's agriculture, crucial for food security
agriculture and livelihoods. To build resilience, Thailand
should promote climate-smart practices like
crop diversification, water-efficient irrigation,
and soil conservation. Providing farmers with
access to climate information and extension
services will help them to adapt and minimize
crop losses. (Ministry of Agriculture and
Cooperatives, Ministry of Natural Resources
and Environment, Local Government Units and
Community Organizations, Research Institutions
and Academia)
Strengthen As urbanization accelerates, cities in Thailand L 2 LL
urban face increased climate-related risks like
resilience heatwaves, urban flooding, and infrastructure
damage. Investing in green infrastructure, such
as parks and green roofs, can mitigate the
urban heat island effect and reduce flood risk.
Integrating climate considerations into urban
planning and design, including climate-responsive
building codes and sustainable transport
systems, will enhance urban resilience and
promote sustainable development. (Ministry of
Interior, Ministry of Natural Resources and
xviii Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Environment, Ministry of Digital Economy L 2 LL
and Society, Local Government Units and
City Planning Authorities, Private Sector and
Industry)
Enhance Recognizing the importance of local L 2 L
community- knowledge and community participation,
based Thailand should prioritize community-based
adaptation adaptation approaches. Empowering local
communities to implement tailored adaptation
measures will enhance grassroots resilience.
Supporting community-led initiatives, such as
climate-resilient agriculture and disaster risk
reduction activities, can build social cohesion
and strengthen adaptive capacity. (Ministry
of Agriculture and Cooperatives, Ministry
of Natural Resources and Environment,
Local Government Units and Community
Organizations)
Invest in Climate-proofing infrastructure investments is M 2 L
climate- essential for reducing vulnerability to climate
resilient change impacts. Thailand should integrate
infrastructure climate considerations into infrastructure
planning, design, and maintenance across
sectors like transportation, energy, and water
management. This includes incorporating climate
risk assessments, designing infrastructure to
withstand extreme weather, and ensuring robust
maintenance and monitoring systems. (Ministry
of Transport, Ministry of Energy, Ministry of
Interior. Local Government Units and Municipal
Authorities, Private Sector and Industry)
Table ES2. Priority Mitigation Actions
Action Description Urgency Co-benefits Feasibility
Implement Introducing carbon pricing mechanisms, such S 2 HL
carbon pricing as a carbon tax or emissions trading scheme,
mechanisms in Thailand can incentivize businesses to
reduce carbon emissions. These mechanisms
encourage cleaner technologies and practices,
leading to reduced emissions. Revenue from
carbon pricing can be reinvested in climate
mitigation and adaptation efforts, enhancing
Thailand's resilience to climate change.
Executive Summary xix
Action Description Urgency Co-benefits Feasibility
(Ministry of Finance, Ministry of Environment S 2 HL
and Natural Resources, Ministry of Industry,
Ministry of Energy, Ministry of Agriculture and
Cooperatives, Private Sector and Industry)
Power sector The Government of Thailand should prioritize S 3 L
reforms power sector reforms to enhance the
effectiveness of carbon taxes. By aligning
energy pricing with carbon reduction goals,
these reforms would encourage investment in
cleaner technologies and support a smoother
transition to a low-carbon economy. (Ministry
of Energy, Electricity Generating Authority of
Thailand, Ministry of Finance, Energy Regulatory
Commission, Department of Alternative Energy,
Development and Efficiency, Private Sector
and Industry, International Organizations and
Development Partners)
Utilize carbon The revenue generated from carbon taxes S 3 HL
tax revenues could be channeled into a dedicated climate
to support fund, supporting other critical climate policies
other climate and initiatives, further accelerating the country's
policy transition to a low-carbon climate resilient
economy. (Ministry of Finance, Ministry of
Energy, Office of the National Economic
and Social Development Council. Climate
Change Department, Ministry of Environment
and Natural Resources, Energy Regulatory
Commission)
Collaborate for Collaborating with international organizations M 2 L
electric vehicle and private sector partners can accelerate
transition Thailand’s transition to electric vehicles
(EVs). By sharing knowledge, expertise, and
resources, Thailand can address barriers to EV
adoption, such as high upfront costs and limited
charging infrastructure. These partnerships
can also foster domestic EV manufacturing
capabilities, creating new opportunities for
economic growth and innovation. (Automobile
Manufacturers, Charging Infrastructure
Providers, Energy Companies, Ministry of
Energy, Ministry of Transport, Thailand Board
of Investment)
xx Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Implement a Thailand can promote widespread EV adoption M 2 L
comprehensive through a comprehensive policy package. This
EV policy could include incentives for EV purchases,
package subsidies for charging infrastructure, and tax
breaks for manufacturers. By addressing both
supply and demand-side barriers, Thailand can
create a supportive environment for EV uptake,
reduce GHG emissions from transportation,
and improve urban air quality. (Ministry of
Energy, Ministry of Transport, Department of
Land Transport Electricity Generating Authority
of Thailand, Thailand Board of Investment,
Ministry of Finance, National Science and
Technology Development Agency. Office of the
National Economic and Social Development
Council)
Implement Thailand can mitigate climate change and L 2 L
afforestation protect ecosystems by implementing
and forest afforestation and forest restoration measures.
restoration Restoring degraded forests and expanding
measures green cover will sequester carbon dioxide,
enhance biodiversity, and provide economic
benefits such as job creation in forestry and
opportunities for ecotourism. These measures
are essential for Thailand’s long-term climate
resilience and sustainability. (Ministry of Natural
Resources and Environment, Department of
National Parks, Wildlife and Plant Conservation,
Royal Forest Department, Department of
Land Development, Ministry of Agriculture and
Cooperatives, Office of the National Economic
and Social Development Council, Local
Government Units and Municipal Authorities,
Private Sector and Non-Governmental
Organizations)
Enhancing Improving energy efficiency in Thailand is M 2 L
Energy essential for reducing consumption and
Efficiency greenhouse gas emissions. Measures include
adopting strict efficiency standards, promoting
energy-efficient building designs, and using
smart grid technologies. Incentives for energy
audits and savings technologies, along with
public awareness campaigns and training, will
Executive Summary xxi
Action Description Urgency Co-benefits Feasibility
support a transition to a greener economy
and lower overall energy demand. (Ministry
of Energy, Department of Alternative Energy
Development and Efficiency, Energy Regulatory
Commission, Ministry of Interior, Office of the
National Economic and Social Development
Council, Thai Green Building Institute, Local
Government Units and Municipal Authorities,
Private Sector and Industry Associations)
Table ES3. Priority Circular Economy Actions
Action Description Urgency Co-benefits Feasibility
Policy The Thai government should create a M 2 HL
Framework comprehensive policy framework for a circular
for Circular economy, including regulations, incentives,
Economy and guidelines to promote sustainable design,
resource efficiency, and waste reduction.
Setting clear targets and timelines will guide
and hold stakeholders accountable across
sectors. (Ministry of Natural Resources and
Environment, Department of Environmental
Quality Promotion, Ministry of Industry,
Office of the National Economic and Social
Development Council, Department of Industrial
Works, Thailand Board of Investment, Local
Government Units and Municipal Authorities)
Support Thailand should leverage innovation and M 3 L
Innovation and technology to advance the circular economy.
Technology Investing in research and development will
help scale up technologies for recycling,
remanufacturing, and resource recovery.
Embracing digital technologies and data analytics
can optimize resource use and support circular
business models. By fostering a culture of
innovation, Thailand can lead in sustainable
resource management and circular solutions.
(Ministry of Science and Technology, National
Science and Technology Development Agency,
Ministry of Industry, Department of Industrial
Works Office of the National Economic and
Social Development Council, Thailand Board
of Investment, Private Sector and Industry
Associations, Universities and Research
Institutions)
xxii Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Circular Promoting circular procurement practices is M 2 HL
Procurement essential for driving demand for sustainable
products and services in Thailand. The
government can lead by incorporating
circularity criteria into public procurement.
Clear guidelines for evaluating product and
service circularity will encourage businesses to
adopt circular practices. By boosting market
demand for circular products, Thailand can
foster innovation, investment, and progress
toward sustainability goals. (Ministry of Finance,
Office of the Public Procurement, Ministry
of Commerce, Department of Internal
Trade, Ministry of Industry, Thailand Board of
Investment, Office of the National Economic
and Social Development Council, Private Sector
and Industry Associations, Environmental Non-
Governmental Organizations)
Product Design Thailand can encourage businesses to focus M 2 L
Improvements on eco-design principles, such as durability,
repairability, and recyclability, in product
development. Offering incentives and support
for sustainable design will help reduce waste and
improve resource efficiency. Designing products
for easy disassembly and component reuse can
extend their lifespan, minimize new resource
extraction, and reduce environmental impact.
(Ministry of Industry, Department of Industrial
Works, National Science and Technology
Development Agency, Thailand Board of
Investment, Office of the National Economic
and Social Development Council, Private Sector
and Industry Associations, Environmental Non-
Governmental Organizations, Universities and
Research Institutions)
Enhanced Thailand should develop and invest in robust M 2 M
Material recycling infrastructure and technologies
Recycling to facilitate efficient collection, sorting,
and processing of recyclable materials. By
establishing comprehensive recycling programs
and promoting consumer awareness and
participation, Thailand can increase recycling
rates and divert more waste from landfills.
Partnering with the private sector and
Executive Summary xxiii
Action Description Urgency Co-benefits Feasibility
incentivizing investment in recycling facilities
can accelerate the transition to a circular
economy. (Ministry of Natural Resources and
Environment, Department of Environmental
Quality Promotion, Department of Local
Administration, Ministry of Industry, National
Science and Technology Development
Agency, Thailand Board of Investment, Local
Government Units and Municipal Authorities,
Private Sector and Industry Associations)
xxiv Towards a Green and Resilient Thailand
1
FROM GROWTH AT ANY COST
TO GROWING SUSTAINABLY
Chapter 1. From Growth at Any Cost to Growing Sustainably 1
Photo: © Chaiyaporn Baokaew / Shutterstock.
Further permission required for reuse.
1. FROM GROWTH AT ANY COST TO GROWING
SUSTAINABLY
1.1. THAILAND’S ECONOMIC ASPIRATIONS
Thailand is working towards achieving the status of a high-income economy by 2037, guided by
the principles of “security, prosperity, and sustainability” outlined in its 20-year 2017 National
Strategy Preparation Act. The National Strategy outlines five key objectives: economic prosperity,
social well-being, human resource development and empowerment, environmental protection,
and public sector governance. However, both the pre-pandemic economic slowdown and the
pandemic’s impact present challenges to Thailand’s ambitious goals.
The current focus of Thailand’s 4.0 vision is on innovation, reducing dependence on commodities,
and transitioning towards a Bio-Circular-Green (BCG) economy model. This model proposes
to integrate bio-economy, circular economy, and green economy concepts to create high-value,
eco-friendly products, as well as a services-oriented economy with reduced resource inputs that
preserves natural and biological resources. The 20-year National Strategy emphasizes investment,
sustainable industrial development, resilient infrastructure, digital transformation, green tourism,
small- and medium-sized enterprises (SMEs), human capital, and support for the service sector.
The government aims to implement policies supporting this new framework to attract investment,
enhance the business environment, and promote sustainable development. Despite existing
economic challenges, the government remains committed to stimulating growth and job creation,
improving competitiveness, and enhancing the overall well-being of the population and the
environment.
This report examines the link between economic growth and the natural
environment in Thailand. It updates the current BCG model and places a
particular focus on the challenge from climate change. The report finds that
an expansion of the BCG framework (see Box 1) presents opportunities to
enhance both the quality and quantity of future economic growth. It places a
focus on resilience to the increasing threat of climate shocks and shows the need
to develop a holistic approach to economically, socially, and environmentally
sustainable development.
1.2. EMERGING CONSTRAINTS ON GROWTH
Thailand has achieved significant development progress over the past 40
years, moving from a low-income to an upper-middle-income country. The
economy experienced substantial growth, averaging 7.5 percent annually from
1960 to 1996 and maintaining a 5 percent growth rate during 1999-2005, even
amid the challenges of the Asian financial crisis. The economic expansion resulted
in the creation of millions of new jobs, playing a vital role in reducing poverty.
2 Towards a Green and Resilient Thailand
Other improvements included increased access to education for children, and health insurance
coverage for much of the population.
Box 1. Defining sustainable development: BCG and BCG+
Thailand’s government introduced the BCG model in 2021 as a way of promoting inclusive and
sustainable growth. The BCG model aims to combine Thailand’s biological and cultural diversity with
technological innovation to create a new growth paradigm.
The BCG strategy focuses on four sectors:
• Food and agriculture
• Human health
• Bio-based material and energy
• Tourism and the creative economy
Thailand’s BCG strategic plan covers 1) promoting sustainable resource use; 2) strengthening
communities; 3) using technology to boost competitiveness, and 4) building resilience.
This report updates the BCG model for current circumstances, which we call BCG+. We place more
emphasis on resilience to climate shocks that impact Thailand. We also focus more on measures to
reduce Thailand’s emissions because technology advances have created opportunities for policies to
reduce emissions while simultaneously cutting energy costs. The sustainable use of Thailand’s natural
resources is explored. Finally, while recognizing the importance of the four BCG sectors to Thailand’s
economy, this report takes a whole-economy perspective so that BCG+ is assessed within the context
of broader economic development.
For more than a decade, though, Thailand has faced a persistent growth challenge marked
by a prolonged and noticeable deceleration in economic growth. The pivotal moment in this
trajectory was the Asian financial crisis of 1997, which inflicted substantial economic damage,
created a reluctance to embrace change, and resulted in a stagnation of reform efforts. In the
aftermath of the crisis, Thailand encountered a series of adverse economic shocks, particularly
impacting potential growth with a significant decline in investments, that accounted for about two-
thirds of the average GDP decrease that occurred between the periods of 1980-1996 and 2000-
2019.
The challenge has been further accentuated by a policy emphasis on consumption, which has
inadvertently strengthened a cycle of low investment and slow economic growth. Focusing on
consumption has increased environmental pressures and has led to lower investment and capacity
for long-term growth. The pandemic caused further disruption to Thailand’s economy, with GDP
falling by 6.2 percent in 2020 and recovery taking longer than in peer countries. Economic slowdown
in China and high energy prices linked to the continued war in Ukraine will also continue to hinder
growth. In the medium term, the expected annual growth rate is 3 percent.
Chapter 1. From Growth at Any Cost to Growing Sustainably 3
1.3. CROSS-CUTTING CHALLENGES TO FUTURE GROWTH
Thailand confronts multifaceted challenges across various human capital dimensions. The
educational system is yielding poor outcomes, with diminishing educational spending and increasing
inefficiencies. Social exclusion is pervasive among vulnerable groups, such as the elderly, persons
with disabilities, women, irregular migrants, ethnic minorities, and those residing in conflict areas.
Policies aimed at supporting these populations lack precision. The demographic transition towards
an aging population poses a significant challenge, straining the public health system and escalating
associated costs.
Thailand is grappling with significant economic challenges stemming from a loss of
competitiveness in the manufacturing sector. These challenges have led to a decline in its share
of global production and a lag in advanced service sectors. Ongoing challenges in financial resource
allocation persist, characterized by high household indebtedness and limited access to finance for
small and medium-sized enterprises (SMEs). Furthermore, the slow adoption of technology and
innovation poses a significant barrier to progress in transitioning towards a Bio-Circular-Green
(BCG) economy model. Addressing these multifaceted issues is imperative for revitalizing economic
growth and fostering a more sustainable and competitive economic landscape in Thailand.
1.4. SPECIFIC CLIMATE AND ENVIRONMENTAL CHALLENGES
Since the launch of the BCG economic model, several specific environmental issues have risen
in prominence: (i) climate vulnerability, (ii) carbon emissions and commitments made to reduce
them, and (iii) degradation of natural resources.
1.4.1. Climate vulnerability
Thailand is highly vulnerable to climate change, ranking as the world’s eighth most-impacted
country by extreme weather events in the last two decades. The country is especially vulnerable
to the effects of climate change because of its long coastlines, fragile agriculture system, susceptibility
to extreme weather events (tropical storms, floods, and droughts), and poorly planned urban
expansion. Recent model projections show that, in the absence of action to prevent urban flooding,
most of the Greater Bangkok area could be underwater by 2050 (Climate Central, 2019), displacing
an estimated 12 million people — many of them already living below the poverty level. Climate-
related disasters affect medium-term growth potential, with large and long-lasting macroeconomic
effects, and come with significant social costs in terms of lost lives, food insecurity, and deterioration
in human capital. Specifically, the relatively poor North and North-Eastern regions of Thailand are
highly vulnerable. If unaddressed, climate change has the potential to exacerbate inequality in the
country.
A combination of sea level rise and changing weather patterns could further accelerate erosion
along Thailand’s long coastlines. The Third Biennial Update Report (Ministry of Natural Resources
and Environment, 2020) concludes that about 600 kilometers (23 percent of Thailand’s coastline)
4 Towards a Green and Resilient Thailand
is affected by an erosion rate of one to five meters per year. The total loss of land is estimated
at two square kilometers per year, with a value of 6 billion Thai baht (THB), which is .04 percent
of gross domestic product (GDP). Cities and economic activities in coastal areas are especially
vulnerable to coastal erosion.
Bangkok is particularly vulnerable to flooding and coastal erosion. The Thai capital and most
populous city lies on the delta of the Chao Phraya River, approximately 25 kilometers inland from
the Gulf of Thailand. The area is less than two meters above sea level and sits on former marshy land
that is subject to periodic flooding. In addition, Bangkok is sinking because of excessive underground
water use and the weight of large-scale high-rise development, suggesting that permanent water
incursion may become possible. Thailand’s Third Biennial Update Report to the United Nations
notes that Bangkok is one of the most vulnerable cities in the world to the effects of changing
rainfall patterns, sea level rises, and coastal erosion.
Thailand is also vulnerable to droughts and water shortages, with particularly adverse effects on
the agriculture sector. Changes in weather patterns resulting from climate change are increasing
the frequency of localized droughts and water shortages, as well as flooding. Agriculture (which
accounts for about 9 percent of GDP) is particularly vulnerable to water shortages, with highly
water-intensive rice production especially susceptible. A lack of rainfall also contributes to the
overuse of fresh water from aquifers, leading to land subsidence and sinking in the central part of
the country characterized by low-lying land of high economic value. Costs to the government in
providing compensation (mainly to farmers) are expected to increase. In 2019, the government
reportedly provided a one-off payment of THB 25 billion (0.15 percent of GDP) to farmers to
compensate directly for damage to crops from drought and flooding. Further measures to support
affected farmers were also announced with a cost of THB 60 billion (0.36 percent of GDP).
Other important economic sectors, including tourism and manufacturing, are also exposed to
the impacts of climate change. Tourism, which is mainly located on coastlines and accounts for
an estimated 12 percent of GDP, is vulnerable to flooding and coastal erosion. The manufacturing
of goods for exports is concentrated in and around Bangkok and its perimeter and is therefore
also vulnerable to flooding. Water supply, although small in economic terms, provides a critical
input to several other sectors (including agriculture and tourism). Careful management of water
resources will be important in reducing subsidence and preventing low-lying coastal areas from
sinking further, but will become more difficult if the frequency of droughts increases.
Oceans are an important resource for the prosperity of Thailand. Despite their importance,
the sustainability of oceans is under threat because of overfishing, degradation of mangroves and
coral reefs, and marine plastic debris that significantly impact the economy of coastal areas. Climate
change has added to these pressures and may also lead to an increase in their cumulative impacts.
Wildfires are becoming a common occurrence in Northern Thailand, happening every dry
season, and exacerbated by climate change. Nearly 20 percent of the forested area of Northern
Thailand burned down in the first four months of 2020, causing dangerous levels of air pollution. A
total of 25,518 hectares (ha) burned in all of Thailand that year, causing $380 million in damages.
Chapter 1. From Growth at Any Cost to Growing Sustainably 5
While the 2020 fires were among the worst in recent years, they were not a singular event, with
some resulting from the drought and scorching heat while others were caused by crop burning
— a common method to clear farmland that has also caused very high levels of air pollution in
Northern Thailand. Long-term exposure to PM2.5 and PM10 particles emitted by wildfires can
result in cardiovascular and respiratory diseases, as well as cancer.
In pursuing the BCG economic model, Thailand needs to address these climate change risks
as a priority. Climate-related disasters affect medium-term growth potential, with large and long-
lasting macroeconomic effects, and come with significant social costs in terms of lost lives, food
insecurity, and deterioration in human capital. Specifically, the relatively poor north and north-
eastern parts of Thailand are highly vulnerable to climate change. If unaddressed, climate change
will become the main obstacle to the sustainability of the country in pursuing the BCG economic
model.
1.4.2. Carbon emissions and commitments
Thailand is not a major contributor to climate change, but its emissions are expected to
grow. The nation’s greenhouse gas (GHG) emissions accounted for 0.88 percent of the total global
emissions in 2022 and constituted the world’s 20th largest emitter country. Its per capita emissions
are comfortably below the global average but are higher than those in several other ASEAN
countries, reflecting its higher income levels (Figure 1.1). Thailand’s emissions per unit of GDP are
also above the global average rate.
Figure 1.1. Per capita GDP and GHG emissions in ASEAN countries, 2018
100
Brunei
Vietnam
tCO2e per capita
Philippines
Singapore
Malaysia
10
Laos
Thailand
Cambodia
Myanmar Indonesia
1
1000 10000 100000
GDP per capita (US$)
Source: CAIT and WDI Databases; Note: Emissions exclude LULUCF
6 Towards a Green and Resilient Thailand
Although from a low base, Thailand’s GHG emissions have more than doubled since 1990.
China and India saw much larger growth in emissions over this time (285 percent and 175 percent,
respectively) but also experienced faster GDP growth. Nevertheless, Thailand’s GHG intensity of
GDP has moderately declined since 1990.
Industry, power, transport, and agriculture account for most of Thailand’s GHG emissions. In
2018, the power sector contributed 21 percent of Thailand’s total GHG emissions (Figure 1.2).
Industry accounted for a 26 percent share, transport 18 percent, and agriculture 17 percent. The
remaining emissions are attributed to other energy production (7 percent), waste (6 percent),
and buildings (4 percent). Most power sector GHG emissions are CO2 and most agricultural
emissions are methane and nitrous dioxide. Industrial emissions include a growing proportion from
F-gases. The industry, power, transport and agricultural sectors all face different decarbonization
challenges in coming decades, and the availability of technological options to reduce emissions
varies substantially across these sectors.
Figure 1.2. Emissions by GHG and by Sector, mtCO2eq
By emission type By sector
300 500
450
250
400
350
200
300
150 250
200
100 150
100
50
50
0 0
1990 1995 2000 2005 2010 2015 2020 1990 1995 2000 2005 2010 2015 2020
CO2 CH4 Power Other energy Industry
N2O F gases Transport Buildings & other Agriculture
Waste
Source: EDGAR database (edgar.jrc.ec.europa.eu/dataset_ghg60 and data.europa.eu/doi/10.2904/JRC_DATASET_
EDGAR) and World Bank staff calculations.
Emissions in the power sector have begun to plateau in recent years with the increasing
adoption of renewable sources. Power sector emissions have long accounted for a large share
of Thailand’s GHGs, with fossil fuel dependence causing environmental degradation and imposing
economic and health costs. More recently, a greater use of solar, wind, and liquid biofuels for
electricity generation has slowed the growth of emissions from electricity and heat consumption
Chapter 1. From Growth at Any Cost to Growing Sustainably 7
and from the energy sector overall (Climate Watch, 2023). In 2019, 42 percent of electricity
was generated from renewable sources, compared to 34 percent from fossil fuels such as coal
(IEA Energy and Carbon Tracker, 2020). These green technology shifts have also contributed to
generating more green jobs and reducing the cost of electricity for households and businesses in
Thailand.
Since 2018, industrial processes and product use (IPPU) have been the second largest
contributors to GHG emissions in Thailand, followed closely by the agriculture sector. In
2020, the IPPU sector accounted for approximately 20 percent of GHG emissions in Thailand,
while the agriculture sector accounted for approximately 15 percent of overall emissions. GHG
emissions from industrial processes are driven primarily by mineral production — constituting
about 60 percent of IPPU emissions in 2016 — as well as the production of chemicals, metals, and
non-energy products from fuels and solvents.
The challenge for Thailand is that no country has transitioned to high-income status while
simultaneously reducing emissions. Although overall progress has been made in reducing emissions
while growing GDP, results at the country level have been mixed. Decoupling GDP growth from
GHG emissions also can be temporary, and decoupled countries may revert to increasing emissions
to maintain economic expansion. Nevertheless, there are encouraging signs of relative decoupling
in Thailand, where the rate of emissions growth is slower than that of economic growth. From
1990 to 2022, the growth of real GDP (212 percent) surpassed the growth of all GHG emissions
(109 percent) and CO2 emissions from energy (206 percent) during the same period, indicating
(at best) relative decoupling but not absolute decoupling.
Thailand has committed to achieving carbon neutrality by 2050 and net zero emissions by
2065, while the country is also aspiring to become a high-income economy by 2037. In line
with the global commitments made by countries under the Paris Agreement, Thailand submitted
a new Long-Term Low Greenhouse Gas Emission Development Strategy (LT-LEDS) to the UN
Framework Convention on Climate Change (UNFCCC) in 2021, pledging to peak emissions
by 2030 (Figure 1.3). The LT-LEDS is consistent with Thailand’s current Nationally Determined
Contribution (NDC) and will guide the country towards low-carbon development as a basis for
enhancing its subsequent NDCs. It builds on previous plans and lays out an approach for emission
reductions, with a strong focus on the electricity and transport sectors. Achieving both targets
is a challenging task; advanced technology and bio-circular-green alternative business models will
be needed to boost the country’s economic productivity while reducing GHG emissions and
addressing other sustainability issues.
8 Towards a Green and Resilient Thailand
Figure 1.3. Thailand’s Long-Term Low Greenhouse Gas Emission Scenario
350
Carbon dioxide emissions/removals (MtCO2)
300
250
200
150
100
50
0
-50
-100
-150
2015 2020 2025 2030 2035 2040 2045 2050
LULUCF Energy IPPU
Agriculture Waste Net Emissions
Source: LT-LEDS, 2021
1.4.3. Degradation of natural resources
Thailand’s rich natural capital has played a key role in supporting local livelihoods. Natural
resources such as forests, watersheds, marine and coastal ecosystems, and mineral resources have
supported Thailand’s industries and driven its economic growth. Multiple forms of capital interact
to generate goods and services, and adequately valuing natural capital will help to achieve more
sustainable development. For example, fish productivity will depend on fish stocks (natural capital),
which in turn depend on the distribution and quality of natural habitats (natural capital), fishing
boats (manufactured capital and financial capital), skills of fishermen (human capital), and on fishing
policies and governance (social capital) (Guerry et al., 2015).
Natural resources have been one of the key drivers of Thailand’s development, especially
from 2003 to 2014. In this period the value of natural resource rents as a share of GDP more
than doubled compared to 1990, reaching a peak of 3.6 percent of GDP in 2008 (Figure 1.5). The
majority of these natural resource’s rents come from oil, natural gas, and forests.
As recognized in the BCG strategy, Thailand’s biodiversity is among the richest in Southeast
Asia. Thailand’s ecosystems account for 8-to-10 percent of plant and animal varieties in the world.
Biodiversity supports ecosystem functions that provide benefits to communities and help sustain
livelihoods, as well as key sectors of the country’s economy (e.g. agriculture, forestry, and tourism).
Some ecosystems provide indirect or non-market values such as forested riparian buffers that
prevent erosion and sediment runoffs and improve water quality, mangroves that stabilize coasts
and limit damages from storm surges, and forests and marine environments that store carbon and
provide recreational opportunities.
Chapter 1. From Growth at Any Cost to Growing Sustainably 9
Figure 1.4. Resource rents as percent of Thailand’s GDP
Resource rents as percent of Thailand's GDP
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Coal rents (% of GDP) Forest rents (% of GDP) Mineral rents (% of GDP)
Natural gas rents (% of GDP) Oil rents (% of GDP)
While Thailand’s economic growth has relied heavily on natural resources, it has also degraded
local environments. The enforcement and monitoring of the implementation of Environmental
Impact Assessments (EIAs) remain a challenge. There is limited awareness and engagement on
environmental issues, resistance to change from stakeholders who may be negatively affected by
environmental regulations and policies, and inadequate government resources and systems in place.
Despite substantial socio-economic benefits, biodiversity remains undervalued in Thailand and
is facing multiple threats. These threats include climate change, illegal wildlife hunting and logging,
forest fires, forest clearing, expansion of urban areas and land use changes, livestock overgrazing,
destructive fishing practices, pollution, and invasive alien species (CBD, 2023). More than 13
percent of all species in the country are estimated to be threatened with extinction (Department
of International Organizations - Ministry of Foreign Affairs of Thailand, 2021).
Water availability is falling because of excessive water consumption from rice production.
As one of the world’s largest rice exporters, Thailand’s agricultural sector —dominated by rice
cultivation — demands vast amounts of water for irrigation. Traditional rice farming methods, which
rely heavily on flooding fields, exacerbate this problem. This practice not only depletes local water
resources but also leaves them susceptible to climate variability, such as prolonged dry seasons
and unpredictable rainfall patterns. Consequently, the competition for water between agricultural
needs and other sectors — including urban and industrial use — increases to make sustainable
management of water resources imperative to support both food security and economic stability
in Thailand.
10 Towards a Green and Resilient Thailand
Despite efforts to increase forest coverage, the overall share of forested land in Thailand
is decreasing. In 2020, forests covered 31.6 percent of Thailand’s land mass, down from a
corresponding share of 33.4 percent in 2008. Despite efforts by several agencies in Thailand
to promote reforestation, satellite images show that the level of forest coverage is decreasing
by around 0.3 percent per year. Some forest has been degraded because of natural forest fires.
However, the main reasons for deforestation are human encroachment and illegal logging. At
sea, mangrove forests have been cleared for shrimp farming, with the pollution from these farms
causing further damage.
The value of renewable natural capital per capita decreased by 21 percent between 1998
and 2018 (Figure 1.5). There were declines specifically in the values of fisheries, mangroves, and
protected areas (Figure 1.6). During the same period, the value of produced capital increased (by
nearly 27 percent), as did non-renewable assets (nearly 157 percent) and human capital (over 41
percent).
of Thailand’s
Figure 1.5. ComponentsComponents of national wealth
Thailand's per
national capita
wealth per capita
$90,000
$80,000
$70,000
$19,277 $23,394
$21,014
$60,000
USD per capita
$17,791
$18,438 $6,160 $5,404
$50,000 $884 $6,401 $513
$7,992 $793
$40,000 $6,830 $470
$200
$30,000
$48,713 $45,128 $49,159
$20,000 $34,837
$41,252
$10,000
$0 -$2,969 -$298 -$1,145 -$255
-$1,661
1998 2003 2008 2013 2018
Human capital per capita Natural capital per capita, nonrenewable assets
Natural capital per capita, renewable Net foreign assets per capita
Produced capital per capita
Adjusted Net Savings (ANS), which serves as a crucial gauge for sustainable development, has
declined notably since 2020. ANS measures national savings defined as national income minus
total consumption, plus net transfers – adjusted for gains on education spending and losses on
consumption of fixed capital, depletion of minerals and forests, and air pollution. A negative ANS
could indicate unsustainable development, i.e. diminishing assets to fuel present growth. Although
ANS has increased since 1990, it showed a sharp decline from 2019 ($1,114 per capita) to 2020
($797 per capita) (Figure 1.7). Economic losses, particularly due to natural resource depletion and
carbon dioxide and particulate emission damage, rose steeply from $38 to $230 per capita per
year from1990 to 2020. Overall, ANS was at its lowest in 2001 at $183 per capita.
Chapter 1. From Growth at Any Cost to Growing Sustainably 11
Figure 1.6. Components of natural resource wealth per capita over time
$9,000
$8,000
$7,000
USD per capita
$6,000
$5,000
$4,000
$3,000
$2,000
$1,000
$0
18
95
96
97
98
99
00
01
02
03
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20
20
20
Agricultural land: cropland Fisheries Forests: ecosystem services
Forests: timber Mangroves Coal (non-renewable)
Gas (non-renewable) Minerals (non-renewable) Oil (non-renewable)
Protected areas
Figure 1.7. Net natural resource wealth depletion in Thailand
-1200 1200
-1000 1000
-800 800
Current US$, per capita
-600 600
-400 400
-200 200
0 0
200 -200
400 -400
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
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2001
2002
2003
2004
2005
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2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Adjusted savings: carbon dioxide damage (current US$)
Adjusted savings: mineral depletion (current US$)
Adjusted savings: particulate emission damage (current US$)
Adjusted savings: energy depletion (current US$)
Adjusted net savings, including particulate emission damage (current US$)
12 Towards a Green and Resilient Thailand
Thailand has similar rates of natural wealth depletion to China. It is leveraging a greater share of
its natural resources to promote GDP growth than Vietnam, Philippines, and Cambodia, but less
than Lao PDR and Indonesia (Figure 1.8).
Figure 1.8. Adjusted savings – natural resources depletion in Thailand as percent of GNI
compared to neighboring countries
Adjusted savings: natural resources depletion (% of GNI) 2020
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
Lao PDR Indonesia Thailand China Viet Nam Philippines Cambodia
Poor air quality is estimated to have caused 32,211 premature deaths a year and cost the
economy $33 billion (6 percent of GDP) in 2019. Air pollution, particularly from PM2.5 and
PM10, continues to be a major challenge, costing the economy in terms of health expenses and
human resource productivity. Air pollution is normally found in industrial zones, cities, and areas
with high levels of agricultural burning and forest fires. Despite plans and acts to address air quality,
enforcement remains a challenge.
A shift to a more circular economy could reduce pressure on natural resources in Thailand.
The circular economy model aims to limit the extraction of non-renewable resources and limit
generation of waste. Aspects of the circular economy include extending product lifetimes, sharing
durable goods, and the repair, reuse, and recycling of materials. It contrasts to the current linear
mode of production in which materials are extracted, used in final products, and converted to
waste.
1.5. THE OPPORTUNITY FOR A NEW GROWTH MODEL THAT IS
LOW-CARBON AND CLIMATE-RESILIENT
Despite the challenges from economic growth constraints, an opportunity still exists for a
new growth model that combines biodiversity, low carbon policies, and climate resilience.
This opportunity can be developed from the BCG economic model. The current model aims
to apply the concepts of bio-economy, circular economy, and green economy to develop high-
value products and services that are eco-friendly and require less resource input, while conserving
Chapter 1. From Growth at Any Cost to Growing Sustainably 13
natural and biological resources. This report uses modeling approaches to focus specifically on
resilience to extreme weather events that will become more common because of climate change,
and ways to reduce domestic airborne emissions. The report shows that adopting this ‘BCG+’
model could help alleviate some of the constraints to growth described in Section 1.2.
The new BCG+ growth model will require the introduction of policies to decouple economic
growth from environmental and natural resource impacts, while managing biodiversity and
climate change challenges. Advances in technology may encourage the adoption of some
sustainable practices, but policy will be needed to drive the direction of change. For example,
incentives may be needed to generate shifts that will affect the use and management of Thailand’s
natural assets and induce a reallocation of all factors of production, transforming the structure
of demand (consumption) and supply (production), including the adoption of bio-circular-green
technology options. In pursuing green growth, Thailand needs to adopt aggressive strategies in the
near term in the main emitting sectors (energy, industry, and agriculture) and enhance its sinks
(forestry), combined with carbon pricing to create incentives for behavioral changes in businesses
and households. The country also needs measures to reduce local air pollution, improve labor
productivity, and bolster Thailand’s competitiveness in a decarbonizing world. Because Thailand’s
economy is highly dependent on trade and foreign direct investment (FDI), the low-carbon
transition in other countries will have important implications for its future development path.
Thailand will also need to prioritize low-carbon development to lower emissions, and to ensure
future trade and industrial competitiveness.
In this report, the focus is on the transition toward a BCG+ model and its implications. Chapter
2 assesses the risks that Thailand faces due to climate change by analyzing the vulnerabilities of
key sectors like agriculture, tourism, and infrastructure to climate-related events such as extreme
weather events, sea-level rise, and changing precipitation patterns from a spatial perspective.
Chapter 3 elaborates on the prospects of green growth within the BCG framework, highlighting
opportunities for sustainable development and economic progress. It discusses strategies such as
renewable energy adoption, sustainable resource management, and eco-friendly practices across
various sectors. Chapter 4 examines the concept of natural tipping points — the critical thresholds
in ecosystems beyond which rapid and often irreversible changes occur — and explores how these
tipping points could be reached or mitigated within the context of transitioning to a BCG economy.
Recommendations are summarized in Chapter 5.
14 Towards a Green and Resilient Thailand
2
DEALING WITH CLIMATE RISKS
Chapter 2. Dealing with Climate Risks 15
Photo: © WitthayaP / Shutterstock.
Further permission required for reuse.
2. DEALING WITH
CLIMATE RISKS
2.1. NATURAL CLIMATE HAZARDS
Thailand is vulnerable to a range of natural hazards, including floods, landslides, tropical
cyclones, droughts, and coastal erosion. From 1960 to 2023, Thailand recorded a total of 159
natural disasters (EM-DAT). Figure 2.1 illustrates the distribution of these disasters by province
(ADM level 1) in the 30 most affected regions. Exceptionally heavy monsoon rains have frequently
led to widespread flooding, particularly in low-lying areas and river plains with inadequate drainage
systems and deforestation. Over the course of 63 years, there were 96 recorded flood events.
Several urban areas, including Bangkok, are highly susceptible to pluvial flooding, which impacts
transportation, infrastructure, and the livelihoods of residents. In the northern and western
mountainous regions, steep slopes make landslides a common occurrence during the wet season.
The southern coastal regions are at risk of tropical storms and cyclones, which bring heavy
rainfall, strong winds, and storm surges. More than 45 such events have been recorded between
1960 and 2023. The peak period for tropical storms typically falls between May and November.
Figure 2.1. Disaster events reported by EM-DAT between 1990 and 2018 for Thailand
Chiang Rai 13 15 1 5
Nakhon Si Thammarat 3 28 2
Surat Thani 5 22
Chumphon 3 19 2
Narathiwat 22
Songkhla 1 20
Satun 5 15 1
Phatthalung 1 19
Nakhon Sawan 2 13 5
Yala 19
Ubon Ratchathani 4 14 1
Trang 1 18
ADM1 Unit
Sukhothai 3 11 5
Phrae 6 9 4
Phichit 3 13 3
Kalasin 3 10 6
Phitsanulok 5 11 2
Tak 7 9 1
Surin 8 8 1
Chai Nat 1 11 1 4
Pattani 16
Lampang 6 5 5
Chiang Mai 5 7 1 3
Phra Nakhon Si Ayutthaya 1 12 2
Phetchabun 3 10 1 1
Mae Hong Son 6 1 6 2
Loei 5 3 1 6
Krabi 2 1 10 2
Khon Kaen 3 6 6
0 5 10 15 20 25 30 35
Storm Landside Flood Extreme Temperature Drought
Source: EM-DAT
16 Towards a Green and Resilient Thailand
Droughts are also a periodic challenge in Thailand, primarily affecting the northeastern and
central regions, with 12 drought-related events recorded in the last five years. In certain
provinces, extreme heat stress can be a concern during the hot season, although this has only been
recorded in two instances according to EM-DAT.
2.2. PHYSIOGRAPHIC REGIONS AND MAJOR CLIMATE INFLUENCES
Thailand’s climate is primarily shaped by its location in the tropical monsoon zone of mainland
Southeast Asia and specific topographic features that impact rainfall distribution. The climate-
related risks are therefore not uniform across the country and depend on several factors,
including the likelihood and intensity of a hazard, the exposure of people and their assets to these
hazards, and their vulnerability to various risks. The wet season, spanning from May to October, is
predominantly influenced by the southwest monsoon. During this period, the central, northern,
and north-eastern regions receive substantial rainfall, with the highest precipitation levels occurring
in September. Thailand is situated within the tropical zone and experiences two major climatic
domains (as shown in Figure 2.2). The northern part of the country, including cities like Chiang Mai
and Chiang Rai, features cooler temperatures, especially in the mountainous areas. In contrast, the
southern region maintains a more consistent temperature throughout the year, with warm and
humid conditions due to its proximity to the equator.
Figure 2.2. Thailand Köppen-Geiger climate classification mapped against population density
Source: Fathom Global Models and UN 2020 estimates
Chapter 2. Dealing with Climate Risks 17
The importance of Bangkok makes Thailand’s economy highly exposed to floods and other
climate events. Since the 1960s, there has been a notable migration of people to urban centers,
including Bangkok and other cities like Chiang Mai in the north, Nakhon Ratchasima (Khorat), Khon
Kaen, and Ubon Ratchathani in the northeast, Pattaya in the southeast, and Hat Yai in the far south.
Currently, 51.1 percent of the population resides in urban areas. The high density of population
and industry around Bangkok is a key vulnerability for Thailand. Low-income households in Bangkok
may be particularly vulnerable to floods. Generally, households with lower incomes are less resilient
to climate-related impacts because they often reside in areas that are poor and prone to hazards.
They also have limited access to critical services such as healthcare, education, and early warning
systems. Additionally, these areas tend to be more densely populated.
2.3. FORESTS AND BUILT-UP AREA
Forested areas encompass a significant portion of the country, particularly in the rugged
western and northern regions. The central and eastern plains consist mainly of agricultural land,
with rice paddies dominating the landscape. Thailand’s land cover is continually changing due to
various factors, including deforestation, urban expansion, evolving agricultural practices, and shifts
in land-use policies. Data from the 2020 Global Human Settlement layer (GHS) indicates that
built-up assets are primarily concentrated in major cities in Thailand, especially in Bangkok and its
surrounding urban areas. This distribution strongly correlates with population density (Figure 2.3).
Figure 2.3. Land cover and built-up assets
Source: ESA 2021 and GHS-BUILT-S 2020
18 Towards a Green and Resilient Thailand
2.4. ESTIMATING CURRENT AND FUTURE IMPACTS OF CLIMATE
HAZARDS
There are two distinct methods of estimating the impacts of climate change on national
economies. These methods are usually referred to as “top-down” and “bottom-up” approaches.
Top-down methods use econometric techniques to explore the relationship between GDP and
temperature change; a summary of estimates is provided in Kahn et al (2019). Bottom-up methods
assess different types of climate impacts individually and rely more on physical data to estimate
impacts. We use the bottom-up approach in this report because it gives more sectoral granularity
and provides more insight for potential policy responses. This is the same approach that has been
used in most of the World Bank’s Country Climate and Development Reports (CCDRs). The
impact channels used in this report are listed in Table 2.1. For most impact channels, average
estimates of climate impacts are derived on an annual basis for RCP2.6, RCP4.5, RCP6.0, and
RCP8.5. As the land cover changes, the exposure to potential hazards increases. And, the built-up
assets — particularly urban infrastructure — are susceptible to the vagaries of the climate hazards.
There is considerable uncertainty about the Table 2.1. Channels of climate-related damages
scale of future climate impacts on Thailand’s
Loss of labor productivity:
economy. Various methodological constraints
Agriculture forestry and fish
exist in the published studies, including issues in
Construction
identifying impacts and the question of whether
climate impacts affect production levels or rates River Flood Damage
of economic growth. Distributional impacts Tropical Cyclones
and how these might feedback to macro-level
outcomes have rarely been explored. Many Losses in Agriculture: Rice
of the climate impacts, in particular relating to Losses in Agriculture: Other Crops
extreme weather events, are highly uncertain Losses from fisheries
themselves. Therefore, the modeling of climate
impacts presented in the following sections Additional costs of cooling
follows a dual approach. First, estimates of Losses in tourism
GDP impacts are provided based on the figures
Losses from sea level rise including coastal
below. Second, the models are used to assess
erosion
what might happen in a year when large climate
shocks occur. Such “risk-based” thinking is Source: Staff analysis
now becoming more common for planning
purposes (Dembo, 2021), including within the
financial sector.
2.4.1. Floods and sea level rise
Floods are the most frequent natural hazard in Thailand, especially during the latter part of
the monsoon season (July to October). Nearly every year, the country records significant river
and pluvial floods. On average, these floods affect between 100,000 and 800,000 people annually
(EM-DAT 2023).
Chapter 2. Dealing with Climate Risks 19
Thailand has faced catastrophic floods in the past. One of the most recent events occurred in
October 2010 when exceptional monsoon rains over the northeastern and central regions led
to the Chao Phraya River overflowing. This flood affected nearly 7 million people and more than
25,000 villages in 38 provinces, resulting in more than 230 fatalities. In March 2011, an unusual
amount of rainfall during the late dry season caused widespread flooding in 50 provinces, leading
to approximately 160,000 ha of land being submerged and at least 53 fatalities.
In July 2011, heavy monsoon rains triggered
Figure 2.4. River flood hazard across Thailand by tropical storms caused significant floods
in the northern, northeastern, and central
regions along the Mekong, Mun, Chi,
and Chao Phraya basins. The floodwaters
eventually reached Bangkok in October, and
in some regions, flooding persisted until mid-
January 2012. The total impact was severe,
with 13.6 million people affected in 65
provinces and 815 deaths, making it one of
the most severe flood events in the country’s
history. In October 2013, severe monsoon
flooding affected 28 provinces, particularly the
eastern provinces of Sa Kaeo, Prachin Buri, and
Chon Buri. It led to 39 fatalities and affected
more than 3 million people. In December
2014, the southern provinces of Narathiwat
and Songkhla were hit by monsoon floods,
causing 15 deaths. In January 2017, persistent
monsoon rains resulted in flooding in the
southern regions, impacting 1.8 million people
and causing 95 deaths.
River floods with water depths of up to
five meters or more are most prominent
Source: Staff analysis
in the central floodplains along the Chao
Phraya basin. This area includes many urban
and agricultural areas. Significant flood extents are also observed in the eastern Mun and Chi
catchments. Figure 2.4 illustrates the geographic distribution of hazard intensity for river flooding
events with a 100-year return period.
The highest absolute and relative risk of human mortality resulting from river flood events,
accounting for over 4,000 people annually on average, is concentrated along the Mekong River.
This risk is particularly pronounced in areas such as Nong Khai, situated on the northeastern border
with Lao PDR, and Mukdahan, located on the eastern border. Western states like Kanchanaburi
and Tak expose more than 1,500 people to mortality risk. This calculation does not include water
accumulation in urban areas, which is a significant factor contributing to pluvial flood hazards. Figure
2.5 below illustrates the population mortality risk associated with these factors.
20 Towards a Green and Resilient Thailand
Figure 2.5. EAI of riverine floods on population mortality
River Floods - Population EAI (Mortality risk)
5,000 1.0%
4,000 0.8%
3,000 0.6%
2,000 0.4%
1,000 0.2%
0 0.0%
Nong Khai
Mukdahan
Kanchanaburi
Chiang Rai
Chiang Mai
Nonthaburi
Pathum Thani
Loei
Uttaradit
Tak
EAI Population [#] EAI Population [%]
Source: World Bank CCDR Studies, August 2023.
The risk to built-up areas is distributed in a somewhat different pattern. The largest risk is
concentrated in the central districts located in the Chao Phraya catchment, particularly in regions
such as Pathum Thani’s southeastern districts, Phra Nakhon, Chiang Mai, and Kanchanaburi.
Additionally, areas along the Mekong River are also significantly at risk (Figure 2.6).
Figure 2.6. EAI of riverine floods on built-up damage
River Floods - Built-up EAI (Damage)
500 5.0%
400 4.0%
300 3.0%
200 2.0%
100 1.0%
0 0.0%
Pathum Thani
Phra Nakhon
Si Ayutthaya
Chiang Mai
Kanchanburi
Nakhon Pathon
Nonthaburi
Nong Khai
Nakhon Sawan
Chiang Rai
Bangkok
EAI Built-up[ha] EAI Built-up [%]
Source: World Bank CCDR Studies, August 2023.
Chapter 2. Dealing with Climate Risks 21
The exposure of agricultural crops to flooding is primarily concentrated in the central plains,
particularly along the Chao Phraya basin. Nakhon Ratchasima stands out with the largest relative
exposure, covering more than 200 square kilometers of cropland. However, the relative distribution
of exposure presents a different picture, with the highest relative exposure found in Sing Buri,
where 8.6 percent of its 70 square kilometers of cropland is exposed (Figure 2.7). Some of the
most vital crops in Thailand, such as rice and sugarcane, can endure prolonged submersion during
the vegetative phase. The figure below provides insights into the impacts on agriculture.
Figure 2.7. EAI of agricultural land to riverine floods
River Floods - Agriculture EAE
(exposure > 0.5m flood depth)
25,000 7.5%
20,000 6.0%
15,000 4.5%
10,000 3.0%
5,000 1.5%
0 0.0%
Nakhon Ratchasima
Nakhon Sawan
Chiang Rai
Phra Nakhon
Nong Khai
Phetchabun
Phichit
Kamphaeng Phet
Roi Et
Si Ayutthaya
Phitsanulok
EAE cropland [ha] EAE cropland [%]
Source: Staff estimates
The scale of flood damages will increase but the magnitudes are uncertain and depend on
when floods occur. A warming climate leads to unpredictable rainfall patterns and increased risks
of flooding. The risk of floods like the one in 2011, which was estimated to be a one-in-50-year
event, could increase substantially. It is estimated that a one-in-50-year flood in 2030 could have
double the impact of the 2011 floods.1 The estimated values presented in Table 2.2 are based on
a different modeling approach and are much smaller in magnitude. They are compared to a 2015
base year with damages of $127 million. The figures in Table 2.2 are used in the macroeconomic
modeling in the following chapters. The estimated impacts are small, especially in the context of
GDP that is growing over the projection period. However, the range of potential impacts illustrates
the degree of uncertainty over future flood impacts; this is further explored in the modeling below.
1 WRI Aqueduct model.
22 Towards a Green and Resilient Thailand
Table 2.2. Increase in expected river flood damage in 2050 from 2015 base year (USD m, 2010
prices)
RCP2.6 RCP4.5 RCP6.0 RCP8.5
Percent increase 11.1 17.1 14.9 36.6
Source: Climate Analytics
Coastal floods, often accompanied by coastal
Figure 2.8. Coastal Flood Hazard across
erosion, occur when seawater inundated
Thailand (100-year return)
low-lying coastal areas, leading to temporary
or prolonged flooding. These events can be
triggered by factors including tropical storms,
monsoons, and high tides. Thailand has taken
various measures to address this challenge,
including the construction of flood defense
measures such as seawalls, dikes, and flood
barriers, along with regulations like coastal
zoning and land-use control. Despite these
efforts, coastal flooding remains a significant
concern in certain districts.
According to the OECD (2007), Bangkok
ranks as the seventh-most exposed city
to coastal flooding globally in terms of its
population (900,000), and tenth in terms
of exposed assets ($39 billion). Figure 2.8
illustrates the coastal areas prone to flooding.
The most severe impacts occur within the
Gulf of Thailand, particularly around the
Source: Fathom Global Models, FATHOMv2 Bangkok metropolitan area, the city of Rayong,
and in the southern districts of Songkhla and
Phatthalung. The subsequent two figures indicate the expected impact on population mortality
and infrastructure (Figures 2.9 and 2.10).
The costs to Thailand’s economy of future impacts of sea level rise and coastal erosion are
moderate but will continue to increase. The figures in Table 2.3 are estimated using damage
increases that occur despite dikes being built, according to Lincke and Hinkel (2018). The difference
between the scenarios is limited; under all scenarios, an increase in costs of around $6 billion is
expected.
Chapter 2. Dealing with Climate Risks 23
Figure 2.9. Expected annual impact of coastal floods - Population mortality
Coastal Floods - Population EAI (Risk mortality)
700 0.025%
600
0.020%
500
400 0.015%
300 0.010%
200
0.005%
100
0 0.000%
Satun
Ranong
Rayong
Phangnga
Bangkok
Phetchaburi
Chanthaburi
Phatthalung
Samut Prakan
Samut Sakhon
EAI population [#] EAI population [%]
Source: Fathom Global Models, FATHOMv2
Figure 2.10. Expected annual impact of coastal floods on built-up damage
Coastal Floods - Built-up EAI (Damage)
160 1.6%
140 1.4%
120 1.2%
100 1.0%
80 0.8%
60 0.6%
40 0.4%
20 0.2%
0 0.0%
Samut Songkhram
Rayong
Ranong
Phangnga
Bangkok
Phetchaburi
Chanthaburi
Phatthalung
Samut Prakan
Samut Sakhon
EAI Built-up [ha] EAI Built-up [%]
Source: Fathom Global Models, FATHOMv2
24 Towards a Green and Resilient Thailand
Table 2.3. Costs of sea level rise (SLR) and coastal erosion in 2050, USDm at 2010 prices,
compared to 2015
RCP2.6 RCP4.5 RCP6.0 RCP8.5
SLR and erosion 6696.2 5915.2 5603.8 6379.4
Source: Staff calculations derived from Cheung et al. (2010)
2.4.2. Drought and heat stress
Drought poses a significant concern to Thailand, where most of the agricultural production is
concentrated in the central and eastern plains. Thailand has experienced several drought events,
including in 1995-1996 and 2005-2006, that had a profound impact on key crop production,
leading to food scarcity and economic challenges for farmers (Figure 2.11). The impact of drought
on crops can vary widely, depending on factors such as the severity and duration of the drought,
the region in question, and the specific water requirements of the crops involved. Additionally, the
effects on crops and the broader agricultural sector can be influenced by agricultural practices,
water management strategies, and government policies.
Figure 2.11. Frequency of drought hazard
Chapter 2. Dealing with Climate Risks 25
Figure 2.12. Heat Stress for a 20-year return Thailand experiences exposure to high annual
period (WBGT C) average temperatures, which can rise above
32°C during the dry season, particularly in
the central plain. To assess the probability of
heat stress, one of the key measures used is the
Wet-Bulb Globe Temperature (WBGT), which
considers both temperature and humidity —
critical factors in determining heat stress. In
the analysis conducted, three return periods
for heat events were considered: once every
five, 20, and 100 years. Figure 2.12 illustrates
the modeled maximum heat for the 20- year
return period scenario. In this scenario, WBGT
values exceeding 32°C are commonly observed
in the central and eastern plains, which includes
major metropolitan areas like Bangkok and
other significant urban centers.
Population exposure to heat stress is
substantial. Figure 2.13 illustrates the annual
expected population exposure, which
combines all the hazard probability scenarios. In
this combined assessment, more than 2 million
people residing in Bangkok, along with several
Source: Fathom Global Models, FATHOMv2 hundred thousand individuals living in densely
populated urban centers situated in the Chao
Phraya basin, face annual exposure to severe heat stress. This exposure has significant implications
of heat stress for public health and the economy.
Climate change already impacts outdoor labor productivity; losses could double by 2050.
Climate change is already reducing labor productivity in the agriculture and construction sectors
by 4.5 percent. The loss of productivity will continue to grow in all climate scenarios because
of increased temperature, with work becoming difficult on days of extreme heat and humidity.
Impacts range from 6.5 percent loss (RCP2.6) to 9.6 percent loss (RCP8.5) by 2050 (Table 2.4).
Although the figures appear substantial, the macroeconomic impact of these productivity losses in
the modeled scenarios appears modest because half the impact is already included in the historical
data. Indoor labor productivity will be affected by much less because of air conditioning, but the
annual costs of installing and running cooling systems could reach $11-17 billion annually by 2050
(see below).
26 Towards a Green and Resilient Thailand
Figure 2.13. Annual Population exposure to heat stress
Heat Stress - Population EAE
(exposure to very strong heat stress)
2.5
2.0
1.5
Millions
1.0
0.5
0.0
Songkhla
Khon Kaen
Chon Buri
Bangkok
Chiang Mai
Nonthaburi
Samut Prakan
Pathum Thani
Ubon Ratchathani
EAE Population [#] Nakhon Ratchasima EAE Population [%]
Source: Fathom Global Models, FATHOMv2
Table 2.4. Economic cost from loss of outdoor labor productivity and indoor cooling in 2050,
USDm at 2010 prices, compared to 2015
RCP2.6 RCP4.5 RCP6.0 RCP8.5
Outdoor costs 6.4 7.8 7.3 9.6
Cooling costs 11590.7 13764.0 13039.6 16661.7
Source: Climate Analytics
Heat stress will also affect the oceans and losses from fishing will be substantial in all climate
scenarios, far exceeding those from agriculture. The data in Table 2.5 for loss of crop production
in RCP8.5 are taken from IFPRI (2019), with a quadratic function used to estimate values for other
RCPs and over time. The total agricultural impacts range from $2.9 billion in RCP2.6 to $5.4 billion
in RCP8.5. The scale of impact does not vary much between the RCPs for rice, with most of the
variation in impacts between the RCPs occurring in other crops. However, these impacts are by far
exceeded by potential loss of fishing production. The fishing impacts are estimated from O´Reilly
et al. (2003) and Cheung et al. (2010) and cover both inland and marine fisheries. The figures for
RCP4.5 are used and applied to other RCPs based on temperature differentials. The results show
that up to $26.2 billion of production value is at risk, by far exceeding potential impacts from lost
crop production.
Chapter 2. Dealing with Climate Risks 27
Table 2.5. Loss of production in 2050, USDm at 2010 prices, compared to 2015
RCP2.6 RCP4.5 RCP6.0 RCP8.5
Rice 1635.1 1941.7 1839.5 2350.5
Other crops 1276.6 1835.2 2221.5 2838.6
Fishing 18256.1 21679.1 20538.1 26243.1
Source: Staff calculations derived from IFPRI (2019), O´Reilly et al. (2003) and Cheung et al. (2010)
Other impact channels suggest substantial costs to Thailand across all the climate scenarios.
Estimates of the costs of cooling are derived from the DARA (2012) global study and projections
of cooling requirements in Baumert and Selman (2003). The economic valuations draw on a wide
range of engineering and economic literature, and local energy prices are used. Data for RCP4.5
are extrapolated linearly following DARA (2012) to give estimates for the other RCPs. Substantial
costs are estimated for all scenarios, with a range of $11.6 billion in RCP2.6 to $16.7 billion in
RCP8.5. Losses from tourism are expected to be smaller, with a similar relative variation between
climate scenarios. Data are taken from Hamilton et al (2005) and Roson and Sartori (2016).
2.4.3. Other disasters
The intensity of landslides can be magnified by factors such as land use changes and deforestation.
Data from the NASA Global Landslide Catalogue for the period 2007-2022 has recorded a limited
number of landslide events. Among these events, eight are reported as significant in size, occurring
primarily in the rugged terrain of the northeastern and southern regions of the country (Figure
2.13). Because of a lack of data, landslides are not included in the modeling in this report.
Thailand is only marginally affected by tropical cyclones. Often, cyclone events in the southwest
Pacific do not reach the country, or they only partially affect the northeastern regions, including
Isan and Northern Thailand. A combination of the IBTrACS v4 database (Kenneth et al., 2010) and
GAR 2015 probabilistic wind hazard layers can be used to identify the regions most exposed to
hazardous wind intensity. Figure 2.14 below illustrates the areas most exposed to hazardous wind
intensity, and Figure 2.15 depicts the potential impact on built-up areas. The impacts of cyclones
are included in the modeling in this report but have only a small effect on results.
28 Towards a Green and Resilient Thailand
Figure 2.14. Rainfall-triggered Landslide Figure 2.15. Strong cyclone hazards
Hazard Index for Thailand
Source: Global Assessment Report (GAR) 2015 and
Source: ARUP 2016 IBTrACS v4 database
Figure 2.16. Expected Annual Impact over built-up land
Chapter 2. Dealing with Climate Risks 29
30 Towards a Green and Resilient Thailand
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Further permission required for reuse.
3
TRANSITIONING TO
A BIO-CIRCULAR-GREEN
ECONOMY
Chapter 3. Transitioning to a Bio-Circular-Green Economy 31
Photo: © teera.noisakran / Shutterstock.
Further permission required for reuse.
3. TRANSITIONING TO A
BIO-CIRCULAR-GREEN ECONOMY
3.1. METHODOLOGY
Transitioning to a BCG+ economy would require substantial economic
reform across all major sectors of the economy. As with any transition, there
will be winners and losers from the reforms. This chapter explores the effects of
possible BCG+ reforms across sectors and identifies potential outcomes at the
macro-economic level. It uses a set of sectoral macro-economic modeling tools
to quantify impacts where feasible.
The quantitative analysis in this chapter is based on three modeling tools, which are described
briefly below. The models have different purposes and levels of detail; Table 3.1 describes how
they are applied to the different scenarios.
Table 3.1. How the models in this chapter are applied
Topic area Models applied
Impacts of climate change E3-Thailand, input-output model
Adaptation measures E3-Thailand
Reducing emissions in Thailand E3-Thailand, FTT models
Circular economy E3-Thailand
3.1.1. E3-Thailand Model
The E3-Thailand model (E3M) is a comprehensive macro-econometric model designed for
assessing the macro-economic impacts of climate change mitigation and adaptation policies.
It was originally developed to evaluate the impacts of carbon pricing instruments in the context
of Thailand’s NDC targets and provides a full macro-economic framework. The model includes a
detailed sectoral disaggregation, with 42 economic sectors, 28 consumer spending categories, and
24 users of five different energy carriers. This level of granularity makes it well-suited for assessing
the economic impacts of broader sustainability policies. The model integrates the Thai economy,
energy consumption, and emissions into a single modeling system, allowing for a comprehensive
analysis of different policy scenarios and their potential effects on the economy, energy sector, and
GHG emissions (see Figure 3.1).
E3M is based on a demand-driven framework, in contrast to Computable General Equilibrium
(CGE) models. While both approaches share the common objective of analyzing policy impacts
on the economy, E3M stands out by incorporating empirical data and utilizing econometric
techniques. This allows the model to capture realistically the complexity of the economy, accounting
for factors like imperfect knowledge, bounded rationality, and flexible markets (Mercure et al.,
32 Towards a Green and Resilient Thailand
2016). By reflecting observed behavior, E3M provides an authentic representation of the economy,
considering both the efficiency of resource allocation and the impact of policies on aggregate
demand while encompassing stimuli or austerity effects (Mercure et al., 2019; Pollitt and Mercure,
2018).
Figure 3.1. Overall structure of the E3-Thailand model
Emissions trading scheme EMISSIONS
Environmental taxes (emissions statistics) Energy use
Environmental policy
e.g. carbon tax, ETS
ECONOMY Economic activity & ENERGY
(national accounts) general prices (energy statistics)
Economic policies Global oil price
Demographic change Energy policies
Energy use, prices
& taxes
3.1.2. Input-output analysis
The macro-economic modeling in E3M is supported by a flexible input-output framework.
While E3M already incorporates an input-output (IO) core, a separate IO analysis was conducted
to evaluate potential supply-chain constraints. Like E3M, the IO analysis within this chapter considers
multiplier effects between outputs and inputs, such as the interdependence of car and engine
production. However, the IO analysis also explores bottleneck supply-chain effects in the reverse
direction, anticipating scenarios in which a decline in engine production affects car production.
These supply-chain effects are inherently uncertain because of various behavioral responses that
could prevent bottlenecks (Hallegatte, 2014). Companies, for example, might adapt by switching
suppliers, importing crucial components, or maintaining stocks of key inputs to mitigate supply
disruptions. As a result, the IO analysis presents a range of potential impacts, contingent on different
assumptions regarding preparedness in managing disruptions to their supply chains.
Chapter 3. Transitioning to a Bio-Circular-Green Economy 33
3.1.3. Future Technology Transformations (FTT) model
The FTT models are designed to assess the diffusion paths of low-carbon technologies. The
models are based on the spread of information and the interaction between adopters and non-
adopters (Mercure, 2012). They draw a nuanced parallel, likening the diffusion process to the
intricate dynamics observed in the spread of an infectious disease. This comparison delves into
the multi-faceted aspects of both phenomena, emphasizing not only their propagation through
a population but also the complex interplay of factors influencing their trajectories. The model
assumes that contact with other adopters and exposure to information on the innovation leads
to potential adoption. The flow of new adopters is a function of the stock of existing adopters.
As the stock of existing adopters increases, the risk of “contagion” also increases, resulting in an
exponential rise in the flow of new adopters. However, as the stock approaches the total number
of potential adopters, the flow gradually decreases and eventually becomes zero. The diffusion of
the innovation follows a symmetric S-shaped function over time. In this chapter, FTT modeling is
used to assess the potential adoption of electric vehicles (EVs) in Thailand (Mercure et al., 2018).
3.2. DESIGN OF THE MODELING SCENARIOS
The scenarios in this chapter assess climate impacts, possible adaptation responses to these
impacts, measures to reduce GHG emissions, and policies to improve the circularity of Thailand’s
economy. The first scenario assesses the potential economic impacts of climate change in Thailand,
based on the results of the analysis in Section 2.4. The second scenario evaluates the effects of
adaptation measures aimed at reducing these impacts. The third scenario considers measures for
Thailand to reduce its GHG emissions. Lastly, the analysis extends to include a scenario based on a
move toward a circular economy. While the climate impact and adaptation scenarios are modeled
up to 2050 because impacts grow over time, the scenarios in which Thailand reduces its emissions
and adopts a circular economy are assessed to a 2040 timeframe, reflecting more the interests
of policymakers. Findings are compared with a baseline case that incorporates existing policies
without additional climate policies and with no climate impacts beyond those seen today. The
baseline extrapolates historical data, including current Thai policies but excluding supplementary
climate policies. Population growth aligns with the UN’s constant fertility scenario, and GDP growth
is projected slightly below 3 percent per annum. The sectoral mix in Thailand follows historical
trends, with the share of agriculture and manufacturing in GDP gradually decreasing and the
services sector’s share increasing.
3.2.1. Assessing the impacts of climate change in Thailand
The modeled scenario incorporates the analysis from Chapter 2 and further assesses the
risk from large flood events. Chapter 2 outlines Thailand’s current climate vulnerabilities and
attempts to quantify the future impacts of climate change. These results are fed into E3M to obtain
estimates of economy-wide impacts including indirect effects, as well as impacts on jobs and other
macro-economic indicators (Table 3.2); agriculture is impacted through multiple channels. The
limitations in data and methodology to estimate climate impacts are acknowledged, so the analysis
34 Towards a Green and Resilient Thailand
is supplemented by a separate scenario that assesses the impacts of a large flood in 2030. The
modeled scenarios give a range of outcomes that cover potential worst-case impacts in a single
year, but are grounded in more widely available data.
Table 3.2. How the impact channels are represented in E3M
Impact Channel How entered to model
Loss of labor productivity:
Production loss in the agriculture and construction
Agriculture, forestry, and fish;
sectors
Construction
River flood damage Loss of production in all sectors
Tropical cyclones Loss of production in all sectors
Losses in agriculture: rice
Loss of production in agriculture
Losses in agriculture: other crops
Losses from fisheries Loss of production in agriculture
Reduced household expenditure to compensate
Additional costs of cooling
cooling costs
Losses in tourism Reduced demand for hotels and catering
Loss of production in agriculture (because it is
Sea level rise and coastal erosion
agricultural land lost)
3.2.2. Assessing the potential to adapt to climate change in Thailand
There is substantial uncertainty about the potential to adapt to climate change in Thailand, but
adaptation investment opportunities that offer a high return are likely. Thailand is not unique in
having limited data on potential climate adaptation measures (both on potential costs and damages
averted). However, the extensive exposure of Thailand to floods and other climate events means
that there are likely to be adaptation options with potentially high returns.
In this chapter, we use data from the World
Figure 3.2. Share of damages avoided, %
Bank’s Unbreakable and Lifelines reports
60 (Hallegatte et al., 2019) to estimate adaptation
costs and avoided damages. Although carried
45 out at a relatively aggregate level, and focusing
on adaptation in infrastructure, the data suggest
30 that damages could be reduced substantially
at a relatively low financial cost. Some of the
15 adaptation measures will have almost no direct
cost, for example enforcing existing building
0 regulations or preventing new building on flood
2020 2025 2030 2035 2040 2045 plains. Others, such as climate-proofing large-
Source: ARUP 2016 scale new investments, could have larger costs.
Chapter 3. Transitioning to a Bio-Circular-Green Economy 35
Both the investment costs and the avoided damages are entered into E3M to give an overall
estimate of economic impact. The adaptation measures only apply to new infrastructure, so the
share of damages reduced depends on the proportion of new infrastructure in the capital stock.
Figure 3.2 shows the share of avoided damages in the adaptation scenario.
3.2.3. Assessing measures to reduce emissions within Thailand
As indicated earlier, Thailand faces the imperative to consolidate and augment its existing
policies to fulfill its current climate targets. The trajectory of Thailand’s emissions in the post-
economic recovery from COVID-19 remains uncertain. While emission levels are anticipated to
be significantly lower than the baseline values outlined in Thailand’s NDC, additional efforts may
be necessary to achieve emissions reductions in line with existing targets, especially if the 2030
goal is elevated. Hence, it is crucial to explore how emissions can be further reduced by identifying
sectors and employing various policy instruments.
Affecting substantial emissions reductions in Thailand will require a diverse set of policies. The
climate change mitigation policy analysis in the scenario involves two distinct modeling exercises.
First, utilizing the E3M, the focus is on assessing the potential impacts of carbon pricing, a topic
aligned with current government interests. The carbon price is applied to all energy-related CO2
emissions in the economy. Revenues from the carbon tax are split equally to reduce income and
employers’ labor taxes so that the overall scenario is revenue neutral. Second, a detailed examination
is conducted on the measures required to meet Thailand’s ambitious targets for the adoption of
EVs. This exercise, using the FTT technology diffusion model, underscores the significance of policy
interaction in addressing issues related to technological change. The main scenario tested involves a
combination of policies, including substantial public investments in EV infrastructure, electrification
of the public fleet (scheduled for 2025), support for the electrification of taxis, and incentives for
EV purchases.2
3.2.4. Assessing the move to a circular economy
Moving beyond the scope of climate change, the transition towards a circular economy is
pivotal for long-term economic sustainability. A circular economy revolves around the perpetual
reuse of resources, contrasting with the traditional linear model of extraction, consumption, and
disposal. In a world constrained by finite mineral resources, the circular economy stands out as
the truly sustainable approach. Key principles involve not only recycling but also product reuse
and adjustments in consumption patterns to minimize material usage. For a country like Thailand
that is heavily reliant on imported raw materials, embracing the circular economy offers economic
security benefits, making it an integral aspect of the Bio-Circular-Green economy.
2 The modeled scenario includes mandated electrification of 5 percent of the vehicle fleet (including taxis and public
vehicles), plus building infrastructure for another 5 percent. Fuel taxes equivalent to $25/tCO2 (in addition to existing
duties) are also added.
36 Towards a Green and Resilient Thailand
The circular economy scenario amalgamates a spectrum of policies aiming to instigate reforms
across various sectors of the economy. While interpretations of the circular economy vary, the
scenario incorporates elements aligned with either already announced policies/targets or those
considered achievable for Thailand (Table 3.3). The scenario’s targets and quantifications stem
from sectoral analyses within the report, externally published literature, and expert judgments
from the report team (World Bank, 2022). In E3M, most scenario inputs manifest as changes in
input-output co-efficients, dictating transaction volumes between different economic sectors. For
example, a measure to recycle steel would alter the quantity of inputs from non-energy mining
to basic metals while increasing the contribution from the waste management sector to basic
metals. Changes in final consumption, such as clothing and equipment, are factored into household
budget share calculations, with model parameters determining the allocation of remaining income
for other purchases. The scenario results intentionally exclude any initial investment effects due
to their inherent uncertainty. Consequently, these outcomes should be regarded as long-term
results. The pivotal question of how to finance the requisite investments and whether they would
potentially impact other economic activities in Thailand remains a crucial consideration for the
future.
Table 3.3. Circular economy policies in the modeled scenario, targets met by 2030
Measure Description
Eco-design initiative Manufacturing sectors reduce material input by 10% (excluding specific
interventions described below).
Reduced food waste Food waste in supply chains falls from 30% to 10%. Remaining
production is exported.
Plastic recycling The share of plastics that are reused or recycled increases to 55%. It is
noted that Thailand has a target of 100% reusable plastics by 2027 in its
national roadmap on plastic waste management.
Increased product lifetimes The lifetimes of clothes and durable goods is extended by 10%.
Sharing economy Purchases of vehicles falls by 3%, clothing by 6%, and durable goods by
5% (European Commission, 2018).
Textile recycling Consumption of chemical inputs (e.g. polyester) by textiles reduced by
25%.
Recycled steel The share of recycled steel increases to 40%.
Reduced cement use The overall volume of cement used by the construction sector falls by
20%. Half of this reduction is replaced by recovered materials. A quarter
is replaced by wood and a small share from agricultural residues. The
remaining reductions come from efficiency gains.
Electric vehicles The penetration rate of EVs in the fleet reaches 30%, matching results in
Section 3.5.
Chapter 3. Transitioning to a Bio-Circular-Green Economy 37
3.3. THE IMPACTS OF CLIMATE CHANGE IN THAILAND
The data gathered in Section 2.4 suggest that, although climate change could have limited
impacts on GDP, the risk of catastrophic events has increased. In this bottom-up modeling
exercise, estimates of climate damages from academic literature, often presented as “average
annual losses,” are aggregated. The model adds indirect and multiplier effects to get a whole-
economy estimate of losses. Figure 3.3 depicts the outcomes of this modeling exercise, revealing
relatively modest impacts reflected in the model results, with GDP losses reaching only 2.5 percent
by 2050. Initially, the most significant impacts stem from the loss of agricultural and fishing capacity
(with a high emphasis on fishing), with cooling costs gradually becoming more important.
Figure 3.3. Impact of different categories of climate damages on GDP (RCP8.5) (% from
baseline with no climate change)
1%
0%
-1%
-2%
-3%
-4%
-5%
2020 2025 2030 2035 2040 2045 2050
Cooling Agri & Fish Small floods Labor Prod
Sea level Tourism Interaction e ects Net Outcome
Source: World Bank Staff estimates based on E3-Thailand model
However, it is crucial to approach the interpretation of these small impacts with caution and
not conclude that they indicate minimal climate risk in Thailand. It is important to recognize
that analyses of expected losses and risks are addressing different questions. The primary concern
is the risk and loss of welfare resulting from extreme weather events, particularly floods. While
the modeled impacts might have limited long-term effects on GDP if all damaged capital stock
is repaired or replaced, there could be a substantial short-term loss of welfare and increases in
private and public debts associated with rebuilding lost capital.
38 Towards a Green and Resilient Thailand
The analysis can therefore be enhanced by
Figure 3.4. Impact of a major flood on GDP
incorporating a distinct scenario featuring a
in the year the flood occurs (here 2030)
significant flood event. The scenario assesses
0
what would happen if a large flood occurred in
-2 2030. The likelihood of this flood occurring in
-4
a given year is comparable to that of the 2011
floods, i.e., approximately 1 in 50. However,
-6 the severity of the 2030 flood exceeds that of
-8 2011, attributed to a confluence of economic
development and climate change, thereby
-10 heightening its potential impact. Estimates
-12 derived from the Aqueduct Floods model3
suggest that a similar flood in 2030 could
-14 yield double the economic repercussions
RCP8.5 RCP8.5 with a major flood
of the 2011 event. The outcomes from the
in 2030
E3M match this finding, revealing a potential
Note: percentage of change in GDP considering all production loss of nearly 10 percent (Figure
climate damages in Section for RCP8.5 and RCP8.5
with the additional 2030 flood described above. 3.4). The enduring consequences of such a
Source: World Bank Staff estimates based on E3- flood hinge on the extent of infrastructure
Thailand model reconstruction. Repeated flood occurrences
could lead to slower rebuilding rates, resulting
in more pronounced and lasting negative
impacts on economic growth.
Climate change is poised to have the most significant impact on Thailand’s agriculture and
fishing sectors. To assess distributional outcomes, the study examined 42 different sectors,
consolidating them into eight broad economic categories (Figure 3.5). Each sector’s performance
was compared against the baseline, providing insights into the extent of change induced by various
factors or interventions. This approach allows for a sector-specific analysis of the variations from
the baseline, offering a detailed perspective on the potential impacts of different scenarios on
each economic sector. The modeling clearly indicates that the agriculture and fishing sectors are
exceptionally exposed to climate change, a vulnerability exacerbated by Thailand’s substantial local
fishing industry and shrimp farming. While these findings align with global patterns, Thailand faces
a heightened risk due to its unique economic landscape.
Production losses in agriculture and fishing could impact vulnerable populations and increase
poverty. The implications of substantial and sustained production losses in agriculture and fishing
are profound because many of the lowest-income households in Thailand depend on these sectors
for their livelihoods. This vulnerability has the potential to significantly impact poverty rates in the
country, underscoring the urgent need for targeted strategies to address the specific challenges
faced by these key sectors.
3 https://www.wri.org/aqueduct/tools
Chapter 3. Transitioning to a Bio-Circular-Green Economy 39
Figure 3.5. Percentage change from baseline in each sector’s production
0%
-5%
-10%
-15%
-20%
-25%
-30%
-35%
2020 2025 2030 2035 2040 2045 2050
Agriculture and fishing Energy and mining Basic manufacturing
Advanced manufacturing Construction Transport
Other services Public services
Source: World Bank Staff estimates based on E3-Thailand model
3.4. ADAPTING TO CLIMATE-INDUCED FLOODS
Implementing measures to adapt to climate change could significantly reduce the damages
caused by floods, particularly through flood mitigation strategies. These efforts could lead to
a decrease in the GDP impact of a major flood in 2030 by four percentage points (Figure 3.6).
The focus should be on safeguarding new infrastructure by strategic placement, avoiding flood-
prone areas when possible, and enhancing resilience to climate events. However, adapting existing
infrastructure presents challenges, and human vulnerabilities will persist, particularly in the face
of other climate change impacts such as shifts in fishing patterns and increased heat stress for
outdoor workers. As a result, adaptation is recognized as a partial solution to the overarching
climate challenge. While efforts to adjust and enhance infrastructure resilience are essential, it is
crucial to acknowledge the limitations in addressing all aspects of the complex and multifaceted
challenges posed by climate change. Recognizing the partial nature of adaptation underscores the
need for comprehensive strategies that encompass mitigation, resilience-building, and broader
climate policies to tackle effectively the complexities of climate change.
While the costs associated with a flood prevention program need not be excessively high
if managed carefully, there are effective and economic “soft” climate adaptation measures
available. These measures encompass the development of early warning systems, the enforcement
of building regulations, and a strategic approach to construction in flood-prone areas. In Thailand,
40 Towards a Green and Resilient Thailand
there are potential low-cost options to enhance infrastructure, exemplified by the estimated cost
of protecting against flood damage in Bangkok, reaching up to THB 56.9 billion (equivalent to 0.4
percent of GDP in 2020) according to a 2010 study. Despite being one-time investments, these
endeavors provide protection against events expected to become more frequent due to climate
change.
The easiest adaptation measures will be
Figure 3.6. Impact of a major flood in 2030
protecting new infrastructure. Insights from
on GDP (% from baseline) with and without
the World Bank’s Lifelines report suggest a
flood protection measures
compelling proposition that climate damages to
0 transport infrastructure could be significantly
-2 mitigated, achieving a 70 percent reduction
at a modest cost of only 1.2 percent of the
-4 total capital investment. However, the success
-6 of building resilience relies heavily on the
careful identification and focused targeting
-8
of infrastructure in need of protection. If not
-10 handled with precision, costs could quintuple.
In broader terms, top-down estimates project
-12
that the overall expenses associated with
-14 adapting to climate change in Thailand could be
RCP8.5 with RCP8.5 with
a major flood in 2030 a major flood in 2030,
at least 1.6 percent of GDP.
flood adaptation measures
Source: World Bank Staff estimates based on E3-Thailand
model
3.5. REDUCING EMISSIONS WITHIN THAILAND
Implementing carbon pricing mechanisms could stabilize emission levels in Thailand, but
achieving long-term emission reductions necessitates additional policy measures. Figure 3.7
illustrates two scenarios regarding carbon prices in Thailand, introduced in the form of a tax and
applied to CO2 emissions across all economic sectors with rates gradually increasing over time.
Both scenarios start with modest tax rates that increase to $20/tCO2 in the NDC scenario, and
$40/tCO2 in the Ambitious case. While both scenarios reduce emissions, their adequacy in meeting
Thailand’s current NDC emission reduction target depends on the post-COVID baseline trajectory
of emissions (including non-CO2 emissions), which remains uncertain. Notably, the carbon taxes
alone are insufficient for achieving sustained, long-term emission reductions.
Achieving deep emission reductions to meet Thailand’s carbon neutrality target will require a
combination of policies. While carbon pricing creates incentives to change energy user behavior,
its effectiveness depends on the availability of technology options. The possibilities of carbon prices
in the form of either carbon taxes or emission trading schemes has previously been discussed in
Thailand. Figure 3.8 presents a summary of compatibility between carbon taxes and key emitting
Chapter 3. Transitioning to a Bio-Circular-Green Economy 41
Figure 3.7. Potential decarbonization scenarios for Thailand
Figure A. Carbon price (USD/tCO2, 2023 price) Figure B. CO2 emissions (MtCO2)
160 350
140 300
120
250
100
200
80
150
60
40 100
20 50
0 0
2020 2025 2030 2035 2040 2020 2025 2030 2035 2040
NDC Ambitious Baseline NDC Ambitious
Source: World Bank Staff estimates based on E3-Thailand model
sectors in Thailand. Red boxes highlight potential barriers to behavior change, including the possibility
that energy users may not perceive the price increase from carbon taxes, technology options may
be insufficient, knowledge gaps may exist, or there could be regulatory or capability barriers to
switching. Additionally, the cost of behavioral change may be prohibitive, even with a carbon tax as
depicted in Figure 3.8. Notably, the power and transport sectors emerge as potentially amenable
to carbon taxes, but effective price incentives in the power sector would require market reform
and additional infrastructure is required in transport.
Figure 3.8. How the main sectors meet the criteria for effective carbon pricing
Power Industry Transport Buildings Agriculture
Price signal noticed
Tech option available
Alternative options known
Possible to switch
Desirable to switch
Note: Green cells indicate good compatibility and red cells potential impediments. Orange cells indicate either sectoral
heterogeneity or partial compatibility.
Source: World Bank Staff estimates
Carbon taxes have the potential to increase GDP and employment if the revenues are
utilized effectively. Figure 3.9 displays the results from model simulations for the same scenarios
as presented in Figure 3.7. In these simulations, the revenues generated from carbon taxes are
employed to reduce both income and employers’ labor tax rates. Model results suggest a slight
increase in the levels of both GDP and employment compared to the baseline scenario. The GDP
increase is attributed to two types of demand stimulus. First, there is additional investment in low-
42 Towards a Green and Resilient Thailand
carbon equipment, particularly in the power sector, despite the limited effectiveness of the carbon
tax. This is because the power sector becomes more capital-intensive and less energy intensive.
This effect is more noticeable in the short term, funded by higher debts that must be repaid
over the equipment’s lifetime. Second, there is a positive shift in Thailand’s trade balance. The
consumption of imported fossil fuel decreases, while domestic fossil fuel production may be sold
on global markets, thereby boosting exports. Importantly, Thailand’s other exports are generally
not carbon-intensive, limiting any loss of competitiveness from higher energy costs.
Figure 3.9. GDP and Employment impact of carbon taxes
Figure A. GDP impact, % from baseline Figure B. Employment impact, % from baseline
2.5 1.2
1.0
2.0
0.8
1.5
0.6
1.0
0.4
0.5 0.2
0.0 0.0
2020 2025 2030 2035 2040 2020 2025 2030 2035 2040
NDC Ambitious NDC Ambitious
Source: World Bank Staff estimates based on E3-Thailand model
To achieve Thailand’s ambitious goal of a swift transition to electric vehicles (EVs), a
comprehensive set of policies is essential. The adoption of EVs not only aligns with the country’s
commitment to sustainable development and climate change mitigation, but also presents an
opportunity to significantly transform the domestic car industry. While carbon taxes or higher fuel
taxes could contribute to supporting the shift to EVs, their overall impact on EV uptake is limited. A
more effective approach involves a combination of policies, including substantial public investments
in EV infrastructure, electrification of the public fleet, support for the electrification of taxis, and
incentives for EV purchases. Figure 3.10 illustrates the potential impact of this range of policies
on vehicle sales and fleet composition. Building on an existing trend toward electrification, these
policies could result in almost 60 percent of new cars in Thailand being electric by 2040. The early
scrapping of conventional vehicles could further accelerate this positive trend.
Transitioning to EVs offers substantial economic and environmental benefits (PER, 2022).
Initiating the shift involves introducing a broad range of policies, with climate benefits limited unless
there are parallel measures to decarbonize Thailand’s power sector. Collaborating with international
organizations and private sector partners is also recommended to expedite the transition to EVs
(Box 2). This holistic approach will ensure a smoother and more effective integration of EVs into
the transportation ecosystem.
Chapter 3. Transitioning to a Bio-Circular-Green Economy 43
Figure 3.10. EV market shares in new vehicle sales and in the vehicle fleet, %
EV share in sales EV share in fleet
60 45
40
50
35
40 30
25
30
20
20 15
10
10
5
0 0
2020 2025 2030 2035 2040 2020 2025 2030 2035 2040
Baseline All policies Baseline All policies
Source: World Bank Staff estimates based on E3-Thailand model
Box 2. The Bangkok E-Bus Program
The Bangkok E-Bus Program marks a milestone as the inaugural authorized climate protection initiative
under the bilateral cooperation agreement between Switzerland and Thailand, in alignment with
Article 6 of the Paris Agreement. This initiative empowers the private e-bus operator in the Bangkok
Metropolitan Area to transition its fleet from diesel to electric vehicles.
Simultaneously, the program lays the groundwork for an extensive city-wide charging infrastructure
network. To secure financing, the purchase agreement between Energy Absolute Public Company
Limited and the KliK Foundation for GHG emission reductions (International Transferred Mitigation
Outcomes, ITMOs) from this program was formalized on June 24, 2022. The reduction in GHG
emissions will count towards Switzerland’s NDC target rather than Thailand’s. However, this climate
protection endeavor is poised to enhance significantly air quality in Bangkok and, as a flagship initiative,
is expected to spearhead the electrification of Thailand’s mobility sector.
Addressing climate change in Thailand could have major fiscal implications, with net costs
projected to reach 1 percent of GDP by 2030. The overall impacts of the low-carbon transition
on fiscal balances will depend on the exact policy mix. However, without a broader application
of carbon pricing, the need for a net increase in public expenditure is expected. Analysis across
countries suggests that adaptation costs in Thailand could be at least 1.6 percent of GDP in the
2030s, with the government likely shouldering most of these costs, given the public goods nature
of many adaptation measures. The NDC carbon price modeled in the previous section4 could raise
enough revenues to cover this investment cost by 2040 (although not by 2030), but the benefits
from using the carbon tax revenues to reduce other tax rates would be lost. Power sector reform
to lower emissions would also reduce carbon tax revenues. Revenues from fuel excise duties
4 Here excluding road transport, which is covered separately under carbon-related fuel excise duties.
44 Towards a Green and Resilient Thailand
(currently around 1.2 percent of GDP) are expected to rise initially due to duties reflecting the
carbon content of fuels, but they will decrease with the transition to electric vehicles, in line with
government goals. Excise duties from car sales (currently at 0.8 percent of GDP) would also decline
as lower tax rates are applied to low-carbon vehicles. This figure assumes that other sectors, such
as transport and forestry, will require relatively small net public contributions.
Table 3.4. Indicative impact of climate-related policies on fiscal balances (% of GDP)
2025 2030 2035 2040
Adaptation costs -0.6 -1.6 -1.6 -1.6
Carbon tax revenues 0.4 0.7 1.0 1.6
Fuel excise duties 0.3 0.2 -0.1 -0.7
Vehicle excise duties -0.2 0.0 0.0 0.0
Other transport measures -0.4 -0.2 -0.2 -0.1
Forestry sector costs -0.1 -0.1 -0.1 -0.1
Total -0.6 -1.0 -1.0 -0.9
Source: World Bank staff estimates, 2024
3.6. MOVING TO A MORE CIRCULAR ECONOMY
The modeled scenario entails substantial reform to several key sectors of Thailand’s economy.
General principles include enhanced product design, extended product lifetimes, increased sharing
of goods, and efficient waste management (including increased recycling of steel, plastics, and
textiles). However, many of the measures included are specific to the sectors they cover (see Table
3.3). For example, reducing cement use will require new thinking in architecture and construction.
A shift to EVs (as described above) requires improvements to infrastructure.
If successful, the transition to a circular economy by 2030 could lead to additional GDP growth
and job creation. Meeting the outlined targets might result in an increase in the level of GDP by 1.0
percent and the generation of 160,000 jobs in Thailand by 2030, compared to the baseline scenario
(Figure 3.11). These results exclude short-term investment effects and show only the impacts of
changing production patterns. The economic benefits arise from improved waste management,
with a large share of the total benefits coming from the potential to increase agricultural and
food exports (for example due to lower wastage in food production). A focus on transforming
waste into new materials across advanced manufacturing and service sectors also increases value
added in these sectors and aggregate GDP. Although there is some lost production in domestic
extraction, circular economy measures in Thailand generally mean a shift toward local production
over imported virgin resources (including motor fuel). Jobs are created in the sectors that do the
extra processing. However, the employment gains depend on the availability of skilled workers,
requiring a sector-specific assessment.
Chapter 3. Transitioning to a Bio-Circular-Green Economy 45
Sectors with complex manufacturing processes stand to benefit the most from a shift to a
circular economy. The model results show that most of the additional production arises in advanced
manufacturing sectors. This group includes the repair and waste processing sectors, which will have
a much larger role in the circular economy. In contrast, sectors in the basic manufacturing sector,
including textiles, chemicals, and building materials, will see a fall in demand because of changes in
production methods. Reduced use of raw materials leads to lower output in the extraction sector,
while production in other sectors increases slightly, in line with the broader economic results.
Figure 3.11. Potential economic impact of moving to a circular economy
GDP and employment impacts (% from baseline) Sectoral impacts in 2030 (% from baseline)
1.4
Services
1.2
Construction
1.0
0.8 Advanced
manufacturing
0.6
Basic
0.4 manufacturing
0.2 Extraction
and energy
0.0
2020 2025 2030 2035 2040 Agriculture
GDP Employment -3 -2 -1 0 1 2 3 4 5 6 7
Source: World Bank Staff estimates based on E3-Thailand model
46 Towards a Green and Resilient Thailand
4
BALANCING ACT:
ASSESSING THAILAND’S
ECOLOGICAL THRESHOLDS
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 47
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4. BALANCING ACT: ASSESSING THAILAND’S
ECOLOGICAL THRESHOLDS
4.1. TIPPING POINTS
This chapter examines the potential impacts of ecological thresholds (tipping points) in Thailand,
and the consequences of climate change and ineffective natural capital management. Tipping
points are complex, involving multiple variables interacting at different time scales. A tipping point is
interpreted as a non-marginal change or a sudden shift after which restoration of an ecosystem to
its previous state may no longer be possible. In some ecosystems, tipping points can occur rapidly,
such as the classic example of a small pond that becomes eutrophic and no longer able to support
some forms of life. In the case of forested ecosystems, tipping points occur over a much longer
horizon. To model a tipping point, we focus on climate change and continued deforestation and its
impacts on ecosystem service flows.
4.2. AN INTEGRATED ECONOMIC-ENVIRONMENTAL MODEL FOR
THAILAND
The chapter uses an IEEM model, which is a data-driven decision-making framework linked to
spatial LULC and ESM. It is widely utilized by multilateral institutions and government bodies for
cross-sectoral public policy and investment analysis, addressing concerns like climate change, the
Sustainable Development Goals, and Green Growth Strategies. IEEM integrates comprehensive
environmental data that is available through the United Nations System of Environmental-Economic
Accounting (SEEA) and generates key indicators such as GDP, employment,
poverty, wealth, sustainability, natural capital stocks, and ecosystem services (ES)
supply.
The unique value of IEEM lies in its incorporation of detailed environmental
information aligned with the SEEA and the System of National Accounts.
IEEM provides policymakers with essential indicators for sustainable economic
development, adjusting net national savings for changes in natural capital stocks
and environmental damage, rather than prioritizing short-term economic growth
at the expense of natural capital assets (Banerjee et al., 2021a).
IEEM’s modules capture the dynamics of natural capital-based sectors and,
through integration with spatial ESM, estimate impacts on both market and
non-market ES. As a single-country recursive dynamic Computable General
Equilibrium (CGE) model, IEEM considers all sectors simultaneously, accounting
for resource constraints, inter-sectoral linkages, and market interactions. It
assesses impacts on material and provisioning ES with market prices, as well as
cultural and recreational ES. For non-material or regulating ES without market
prices, IEEM is linked with spatial ES modeling, allowing evaluation of impacts on
48 Towards a Green and Resilient Thailand
regulating services like erosion mitigation, crop pollination, water regulation, and water purification
due to localized LULC changes. The spatial allocation of IEEM-projected land demand is determined
through an LULC change model. In its unique application to Thailand, the database underpinning
IEEM, the Social Accounting Matrix, is constructed based on the country’s latest Supply and Use
Tables from 2012, and macro-economic data, government budget data, and balance of payment data
from 2019. The Social Accounting Matrix distinguishes 26 production activities, 26 commodities,
eight primary production factors, and one household category (see Supplementary Information
section 1 for a detailed presentation of IEEM and IEEM+ESM methods).
To assess the impacts and costs of inaction, the Integrated Economic-Environmental Model
(IEEM) linked with high-resolution spatial Land Use Land Cover (LULC) change and ecosystem
services models (IEEM+ESM; Banerjee et al., 2020a, 2020b) is applied to contrast the “business-
as-usual” baseline case with scenarios that represent a portfolio of policies and investments
designed to counteract climate change and the associated anthropogenic drivers of degradation.
4.3. LULC CHANGE MODELING
LULC change modeling serves as the crucial link between IEEM and spatial ES modeling. To
allocate spatially LULC changes, the analysis employs the CLUE (Conversion of Land Use and its
Effects; Verburg et al., 2008a, 1999a) modeling framework. This framework integrates empirically
quantified relationships between land use and location factors, incorporating dynamic modeling
of competition between land use types. Specifically, the Dynamic CLUE (Dyna-CLUE) model is
utilized as a tool well-suited for smaller regional extents (Veldkamp and Verburg, 2004a; Verburg
et al., 2021a). The Dyna-CLUE model consists of two modules: a non-spatial demand module,
populated with IEEM-derived land demand, and a spatially explicit allocation procedure determining
the probability of each LULC class occurrence for each pixel through a suitability analysis. Within
the Dyna-CLUE model, the demand module generates annual demands for various land use types
based on IEEM. These demands, along with suitability maps calculated for each land-use type,
function as inputs for the allocation module. The suitability maps indicate the likelihood of each
land use class occurring for each pixel and are developed through binomial logit stepwise regression
using explanatory variables (Verburg et al., 2021).
4.4. ESM
The IEEM+ESM workflow employs the Integrated Valuation of Ecosystem Services and
Tradeoffs (InVEST) suite of models (Natural Capital Project, 2023a) to compute spatially
explicit changes in ES supply across various scenarios. InVEST models integrate LULC maps with
biophysical information to estimate ES. Six ES models were parameterized using both global and
national data sources: the sediment delivery ratio model, the carbon storage model, the annual
water yield model, the nutrient delivery ratio model, the crop pollination model, and the coastal
vulnerability model.
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 49
The primary variable influencing changes in the InVEST ES modeling is the scenario-driven
LULC projections generated using the Dyna-CLUE model. New LULC maps for each scenario
and period are incorporated into each of the five ES models (the coastal vulnerability model does
not use LULC as an input). Scenario-driven changes in ES supply for any given year, t, are computed
as differences between ES in the scenario for year t and the baseline scenario for that same year.
Results are presented as a percentage difference from the baseline for each of Thailand’s six regions
(North, Northeast, Central, West, East and South).
4.5. MODEL INTEGRATION AND INTERACTION: THE DYNAMIC
IEEM+ESM APPROACH
In the basic IEEM+ESM workflow, scenarios are applied in IEEM to assess their impacts on
economic indicators. IEEM generates a land demand projection, spatially allocated using the
LULC change model. The five ES models (excluding coastal vulnerability) analyze LULC change
maps for the initial year, final year, and each scenario. The difference between ES supply in each
scenario and the baseline in the final period indicates scenario-based impacts on the ES. When
compared with other IEEM+ESM outputs, this approach offers insights into trade-offs between
economic, environmental, and social outcomes. ES supply changes have varied economic effects.
IEEM addresses impacts for provisioning ES with market values, like food, water, fiber, and minerals.
Some cultural ES values related to tourism and recreation are estimated through standard IEEM
implementation (Banerjee et al., 2019b). However, the basic workflow lacks economic values for
regulating ES without market prices.
The analysis employs the dynamic IEEM+ESM approach, capturing policy impacts on regulating
ES by integrating dynamic feedback between natural capital, ES, and the economic system.
This enables the estimation of the contribution of regulating ES to economic indicators, in this
application, with a focus on changes in soil erosion mitigation ES and crop pollination ES. The demand
for land is taken as exogenous and determined by the scenarios. Dyna-CLUE is implemented to
allocate spatially land demand, as shown in Figure 4.1. Using LULC maps from LULC modeling, the
sediment delivery ratio model (for soil erosion mitigation ES) and the crop pollination model are
run in periodic time steps (5-year periods) throughout the analytical period.5
5 Note that when demand for land is exogenously determined, as is the case in this study where the scenarios define
the demand for land, the LULC change model and the ES models are run iteratively to calculate changes in ES and
the economic shocks described below. Iteration between all three models (IEEM, the LULC change model and the
ES models) is required where there is endogeneity in demand for land (for example, see: Banerjee, Cicowiez, et al.
(2020b) and Banerjee, Cicowiez, Malek, et al. (2022)).
50 Towards a Green and Resilient Thailand
Figure 4.1. Overview of the dynamic IEEM+ESM workflow applied to Thailand
1 2 3 4 5 6 7
Calculate
DYNACLUE Invest
Economic shocks: for Implement
LULC models:
results + each 5-year erosion IEEM
Policy modeling; erosion,
projection period, and resuls, ES
scenarios new LULC pollination
of demand calculate pollination results
IEEM maps 5-year water yield,
for land di erence shocks in reporting
timestep water quality,
2020-50 with respect IEEM
carbon
to base
Source: Authors’ own elaboration.
4.6. SCENARIO OVERVIEW
The model simulations assess the consequences of approaching ecological thresholds (tipping
points) and strategies to avert it, utilizing a baseline and two primary scenarios in IEEM+ESM.
The baseline scenario projects Thailand’s economy until 2050 without significant new policies,
investments, or accelerated degradation of natural capital.
The first scenario, DEGRADE, simulates climate change-accelerated ecological degradation,
highlighting the costs of policy inaction compared to the baseline scenario. DEGRADE includes
sub-scenarios with more rapid and destructive deforestation, increased flooding, catastrophic
floods, reduced agricultural productivity, stagnating tourism, sea-level rise, increased erosion, and
decreased crop pollination. Some DEGRADE sub-scenarios use Relative Concentration Pathway
(RCP) projections, specifically RCP8.5 and RCP4.5 (see Supplementary Information Section 2 for
a detailed presentation of the sub-scenario components).
The second scenario, POLICY, represents policies and investments aimed at preventing a
tipping point and adapting to climate change. Contrasting the portfolio of policies with the
baseline underscores the economic benefits of investing in natural capital enhancement, resilience,
and recovery, while revealing potential trade-offs between economic, social, and environmental
outcomes. POLICY includes sub-scenarios countering the effects of DEGRADE, as well as
initiatives aligning with Thailand’s National Strategy, such as the elimination of deforestation by
2037 and afforestation (1,806,400 ha equivalent to 22 percent of current forest cover) and forest
restoration (2,558,400 ha equivalent to 31 percent of current forest cover).
4.7. RESULTS
The baseline projection indicates continuous forest loss throughout the analytical period while
the DEGRADE scenario depicts an accelerated deforestation rate, potentially eliminating most
of Thailand’s non-protected forests. The POLICY scenario, conversely, incorporates afforestation
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 51
measures (1,806,400 ha) and forest restoration (2,558,400 ha), alongside the elimination of
deforestation, starting in 2024 and linearly reaching zero new deforestation by 2037. The results
that follow focus on the difference between the DEGRADE and POLICY scenarios relative to the
baseline in the final year of the analytical period (2050) for each of Thailand’s six regions.
The impact on carbon storage ES in the DEGRADE scenario (Figure 4.2, left) reveals that
the greatest decreases would occur in the north, south, and west (-16%, -11%, and -5%,
respectively). In the POLICY scenario (Figure 4.2, right), carbon storage would notably increase,
particularly in the south, north, and west (19.8%, 19.2%, and 8.6%, respectively).
Figure 4.2. DEGRADE PES+ and POLICY PES+ carbon storage climate mitigation ecosystem
services in 2050 as a difference from the baseline in percent
Source: IEEM+ESM results. Note: scenario names that terminate in PES+ use the RCP8.5 pathway projection.
For erosion mitigation ES (Figure 4.3, left), a considerable decline is anticipated across most
of Thailand as the ecological tipping point approaches, with reductions of 16.3 percent in the
east, 11.4 percent in the west, and 5.2 percent in the south. Introducing policy interventions
would markedly improve erosion mitigation ES, with increases of 24.4 percent in the north, 10.9
percent in the west, and 7.5 percent in central Thailand (Figure 4.3, right).
52 Towards a Green and Resilient Thailand
Figure 4.3. DEGRADE PES+ and POLICY PES+ erosion mitigation ecosystem services in 2050
as a difference from the baseline in percent
Source: IEEM+ESM results. Note: scenario names that terminate in PES+ use the RCP8.5 pathway projection.
The impacts of approaching a tipping point on water regulation ES Impacts would be negative,
particularly for the north, south and west of Thailand (-12.7%, -6.8% and -3.3%, respectively)
(Figure 4.4, left). With policy intervention, water regulation ES would be markedly improved,
especially in the north, south and west of the country (Figure 4.4, right). With regards to water
quality, the DEGRADE scenario would have severe impacts, particularly in the north, south and
west of the country (-36%, -26% and -9%, respectively; Figure 4.5, left). With policy intervention,
impacts would be strongly mitigated with the greatest effects in the north, south and west (9%, 3%
and 2%, respectively; Figure 4.5, right).
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 53
Figure 4.4. DEGRADE PES+ and POLICY PES+ water regulation ecosystem services as a
difference from the baseline in percent
Source: IEEM+ESM results. Note: scenario names that terminate in PES+ use the RCP8.5 pathway projection.
Figure 4.5. DEGRADE PES+ and POLICY PES+ water purification ecosystem services
(nutrient retention) as a difference from the baseline in percent
Source: IEEM+ESM results. Note: scenario names that terminate in PES+ use the RCP8.5 pathway projection.
54 Towards a Green and Resilient Thailand
Impacts of approaching an ecological tipping point on crop pollination under DEGRADE would
be negative across the country, with the greatest impacts experienced in the north, south
and west of Thailand (-8.2%, -5.5% and -2.6%, respectively). The impacts of approaching an
ecological tipping point on crop pollination ES are presented (Figure 4.6, left). Again, with policy
intervention, these negative impacts would be largely offset with the greatest impacts in the north,
south and west of the country (27.7%, 27.6% and 11.6%, respectively; Figure 4.6, right).
Figure 4.6. DEGRADE PES+ and POLICY PES+ crop pollination ecosystem services as a
difference from the baseline in percent
Source: IEEM+ESM results. Note: scenario names that terminate in PES+ use the RCP8.5 pathway projection.
Thailand’s eastern coastline and gulf region east of Bangkok are the areas exhibiting the highest
levels of exposure to coastal vulnerability. Figure 4.7 presents results from the coastal vulnerability
modeling. In this application, policy scenarios that affect specific coastal vulnerability variables were
not considered. At this stage, Figure 4.7 presents baseline coastal vulnerability.
The contribution of ES to the economy is shown in Table 4.1. In the results that follow, scenario
names that terminate in OPT consider the RCP4.5 pathway while those that terminate in PES
use the RCP8.5 pathway projection. The RCP8.5 pathway is the highest emissions scenario, and
therefore climate change under RCP8.5 is expected to be more severe (scenario name terminating
in PES to abbreviate ‘pessimistic’) compared with RCP4.5 (scenario name terminating in OPT to
abbreviate ‘optimistic’).
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 55
Figure 4.7. Baseline coastal vulnerability, Cultural and recreational ES would
index value between 1 (very low exposure) experience the greatest decline in approaching
to 5 (very high exposure) an ecological tipping point. As would be
expected, impacts of scenarios that use RCP4.5
projections versus RCP8.5 projections would
be milder, though still negative. Energy ES would
be next in terms of negative impacts followed
by food provisioning ES. Crop pollination and
erosion mitigation ES would also decline.
ES losses as an ecological tipping point
approached would result in an overall net loss
of $177.6 billion in ES values (DEGRADE_
PES+). Policy intervention would mitigate some
of this loss. Regulating ES would make positive
contributions, but some losses would still be
incurred through the loss of provisioning and
cultural and recreational ES, resulting in a net
impact of $39 billion in ES losses with policy
implementation (POLICY_PES+).
Source: IEEM+ESM results.
Table 4.1. Contribution of Ecosystem Services (ES) to the economy as a cumulative difference
from the baseline in 2050 in USD million
ES Section ES Class Scenario
DEGRADE_OPT DEGRADE_PES+ POLICY_OPT POLICY_PES+
Provision ecosystem services
Food (plant-based) -6,834 -79,786 -7,074 -22,477
Meat (excluding fish) -1,335 -7,672 -1,895 -3,159
Fish -1,845 -2,996 -4,786 -1,138
Timber and non-timber 499 3,224 -4,786 -3,631
Abiotic subsurface
-15,257 -10,361 -11,402 -9,525
minerals
Abiotic subsuface non-
-1,641 -1,454 541 814
mineral energy
Cultural and recreational ecosystem services
Culture, recreation and
-26,256 -61,156 -5,103 -17,930
tourism
56 Towards a Green and Resilient Thailand
ES Section ES Class Scenario
DEGRADE_OPT DEGRADE_PES+ POLICY_OPT POLICY_PES+
Regulating ecosystem services
Crop pollination -7,508 17,749
Erosion mitigation -9,871 285
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
The POLICY scenario would result in an increase in CO2 storage equivalent to 2,103 million
tons compared to the baseline. The elimination of deforestation would result in a net 189-million-
ton increase in CO2 storage. Afforestation and forest restoration activities that are components of
the POLICY scenario, would result in the storage of an additional 1,913 million tons of CO2.
The cumulative GDP impact from loss of ES could be a negative $553.7 billion by 2050 (Table
4.2). Policy intervention would reduce these losses significantly, though the impact would still
be negative ($174.9 billion). With the elimination of deforestation as well as afforestation and
forest restoration activities, the policy interventions to avert an ecological tipping point would
enhance cumulative wealth by $54 billion. Detailed results for each sub-scenario are presented in
Supplementary Information Section 3, including macro-economic results expressed in percentage
change.
Table 4.2. Impacts on macro-economic indicators as a difference from the baseline in 2050 or
cumulative impact as indicated in USD million
DEGRADE_OPT DEGRADE_PES+ POLICY_OPT POLICY_PES+
GDP -36,442 -46,878 -7,658 -14,548
Cumulative GDP -423,101 -553,708 -80,056 -174,902
Wealth -6,564 -6,888 -1,649 2,669
Cumulative wealth -75,420 -80,530 -18,238 54,490
Private consumption -27,392 -39,652 -5,515 -11,143
Private investment -11,999 -11,287 -2,674 -4,217
Exports -34,314 -37,279 -25,383 -24,324
Imports -32,551 -35,136 -3,721 -5,129
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
Figure 4.8 presents the GDP trajectory of each scenario while Figure 4.9 presents the wealth
trajectory, both as a difference from the baseline. The “steps” visually evident in both these
figures are the result of the impacts of catastrophic floods occurring in the years 2029 and 2047.
These specific years were chosen through a random number draw.
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 57
Figure 4.8. GDP trajectory as a difference from the baseline in USD million
10,000
0
Millions of USD
-10,000
-20,000
-30,000
-40,000
-50,000
20
22
24
24
28
30
32
34
36
38
40
42
44
46
48
50
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
DEGRADE_OPT DEGRADE_PES+
POLICY_OPT POLICY_PES+
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
Figure 4.9. Wealth trajectory as a difference from the baseline in USD million
4,000
2,000
Millions of USD
0
-2,000
-4,000
-6,000
-8,000
24
26
28
30
32
34
36
38
40
42
44
46
48
50
20
20
20
20
20
20
20
20
20
20
20
20
20
20
DEGRADE_OPT DEGRADE_PES+
POLICY_OPT POLICY_PES+
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
Employment would fall cumulatively by more than 4.3 million jobs (Figure 4.10). Policy
intervention would mitigate much of this impact, though the result would still be a loss of 931,000
jobs. The DEGRADE_PES+ scenario would result in 46,510 more poor while policy intervention
would reduce the impact but still result in 11,283 more poor (Figure 4.11).
58 Towards a Green and Resilient Thailand
Figure 4.10. Scenario impacts on employment as a difference from the baseline in 2050
0
-500,000
-1,000,000
Number of jobs
-1,500,000
-2,000,000
-2,500,000
-3,000,000
-3,500,000
-4,000,000
-4,500,000
-5,000,000
DEGRADE_OPT DEGRADE_PES+ POLICY_OPT POLICY_PES+
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
Figure 4.11. Change in number of individuals in poverty as a difference from the baseline in 2050
50,000
45,000
Number of individuals below
40,000
poverty line in 2050
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
DEGRADE_OPT DEGRADE_PES+ POLICY_OPT POLICY_PES+
Source: IEEM+ESM results. Note: scenario names that terminate in OPT consider the RCP4.5 pathway while those that
terminate in PES use the RCP8.5 pathway projection.
Examining the household welfare impacts of the scenarios in a benefit-cost framework, the
POLICY_OPT scenario would result in a negative return of $32.3 million with a 2.5 percent
opportunity cost of capital and a negative $8.4 million return with a 10 percent opportunity
cost of capital. With a discount rate of 2.5 percent and 10 percent, the POLICY_PES+ scenario
would result in a return of negative $78.4 million and negative $23,9 million, respectively.
Chapter 4. Balancing Act: Assessing Thailand’s Ecological Thresholds 59
60 Towards a Green and Resilient Thailand
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5
OVERALL CONCLUSION AND
RECOMMENDATIONS
Chapter 5. Overall Conclusion and Recommendations 61
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5. OVERALL CONCLUSION
AND RECOMMENDATIONS
5.1. A WAY FORWARD
Thailand launched its Bio-Circular-Green (BCG) economic model in 2021 with the goal of
combining the country’s biological and cultural diversity with technological innovation to
ensure sustainable future growth. The BCG model focuses on four sectors: food and agriculture;
human health; bio-based material and energy; and tourism and the creative economy.
As one of the world’s most vulnerable countries to climate change, Thailand faces severe
sustainability challenges due to rising sea levels, extreme weather events, and changing
precipitation patterns. Addressing issues such as deforestation, coastal degradation, and
implementing climate adaptation measures is paramount, requiring a combination of policies and
strategies that cut across all levels of society — government, business, political, and social — to
promote resiliency to climate impacts and economic sustainability.
Thailand also faces a challenge in reducing its own GHG emissions. To date, Thailand’s CO2
emissions in the energy sector have grown almost proportionately with GDP (although other
emissions have grown more slowly). While the use of renewable electricity generation may slow
CO2 emission growth, the general trend in emissions after the COVID pandemic is not yet clear.
The pandemic means that Thailand may meet its current NDC target of slower absolute emission
growth relatively easily, but it will increasingly come under pressure to reduce its level of GHG
emissions.
This report focuses on BCG+, which is a combination of the previous BCG vision and the
current climate reality. The move towards a BCG and climate-resilient economy is a critical shift
for Thailand, offering protection against environmental and economic risks that threaten growth. A
BCG+ economy could mitigate these exposures by reducing reliance on global commodity prices
and enhancing economic resilience.
The uneven distribution of climate impacts across the country highlights the need for
targeted interventions to address specific vulnerabilities. Thailand’s population is predominantly
concentrated in urban areas, with rapid urbanization increasing the vulnerability of densely
populated concentrations to climate-related risks, particularly floods. Lower-income households,
often residing in hazard-prone areas, face greater challenges due to limited access to essential
services. The country’s vital agricultural sector is also significantly threatened by altered rainfall
patterns and temperature extremes, jeopardizing crop production.
5.2. MULTI-SECTOR PARTICIPATION
Achieving the transition to a BCG+ economy requires contributions from all sectors, with a
focus on sector-specific characteristics. While some sectors such as forestry stand out as being
62 Towards a Green and Resilient Thailand
critical to a BCG+ economy, the transition will need contributions from all sectors. For example,
the challenge of reducing GHG emissions will likely require a restructuring of the power sector,
electrification of vehicle transport, and changes to industrial production processes. The circular
economy modeling in this report identified multiple policies that were specific to the sectors
covered. Electrification of transport likewise requires a range of policies specific to the sector.
When considering climate adaptation, location is likely to be a critical factor but several sectors (e.g.
transport, tourism, fishing) require potentially vulnerable coastal locations.
Macro-level policies, including carbon taxes, are important but must consider technological
nuances for effectiveness. The carbon taxes tested in this report were sufficient to prevent
emissions from growing but, in isolation, could not drive major reductions in emissions. Promoting
circular production methods poses additional challenges because of the multiple inputs and outputs
in the business model. Coordination between the public and private sectors will be imperative to
realizing the BCG+ vision. The public sector must initiate change, finding financing solutions for
actions like climate adaptation. Simultaneously, private companies bear responsibility for improving
efficiency, fostering innovation, and aligning product designs with bio-circular goals. For carbon
taxes to be effective, power sector reforms are essential in Thailand to ensure a reliable and
equitable transition to low-carbon energy sources. These reforms can help align pricing signals
with carbon reduction goals, driving investments in cleaner technologies and enhancing overall
efficiency within the sector.
If these policy challenges can be met, the transition could offer macro-level opportunities,
showcasing potential benefits like increased economic welfare, higher incomes, and enhanced
employment levels. These positive impacts could offset many of the damages of climate
change, especially if there is a strong role for flood prevention and climate adaptation measures.
Technological advancements and undiscovered productivity avenues underpin these opportunities,
positioning the Bio-Circular Green economy as a driver for economic development. As a country
that imports many of its material inputs, Thailand could boost domestic production. Crucially, the
shift to a BCG+ growth model could safeguard Thailand from future climate and economic risks
while preserving natural capital for sustainable growth.
5.3. ECOLOGICAL THRESHOLDS
Thailand must act urgently to prevent ecological tipping points regarding deforestation and
flooding that threaten billions of dollars in economic losses. The report analyzes the severe
impacts of Thailand approaching an ecological tipping point and proposes preventive strategies. It
compares two scenarios: DEGRADE, leading to increased deforestation and flooding, and POLICY,
involving interventions to mitigate these effects. Thailand’s forest cover has declined by 12% since
2000, risking further reductions if deforestation continues. Eliminating deforestation and promoting
reforestation are highlighted as effective and low-cost measures to enhance ecosystem services
(ES) like water regulation, crucial for flood management. Without action, Thailand could face
$553 billion in GDP losses by 2050. Policy measures could reduce these losses by 68 percent and
increase wealth. However, these policies alone are insufficient to counteract fully environmental
Chapter 5. Overall Conclusion and Recommendations 63
degradation. The report underscores the need for detailed climate adaptation and mitigation plans,
emphasizing that preserving natural capital is vital for resilience against climate change, especially in
mitigating flood impacts. Comprehensive economic frameworks that include the value of ES are
essential for sustainable policy and investment decisions.
Addressing the multifaceted consequences of economic growth constraints, climate
vulnerability, and environmental degradation requires a holistic and integrated approach. By
integrating measures on climate resilience, sustainable resource management, and inclusivity in its
development strategy, Thailand can work towards achieving its vision of a BCG+ economy.
5.4. ACTION PRIORITIES
While all actions discussed in this report are valuable, some are more urgent than others.
Table 5.1 provides a guide for defining priority actions based on three criteria: urgency, co-
benefits, and feasibility. Certain actions are particularly urgent because they generate or facilitate
subsequent opportunities and benefits, such as governance enhancements that enable larger
adaptation investments. The report classifies the urgency of each action into short-term priorities
(by 2030), medium-term priorities (by 2040), and long-term priorities (beyond 2040-50). Some
measures are expected to advance both climate and development goals by improving economic
opportunities regardless of climate impacts. These include measures that enhance economic and
fiscal management, governance, and implementation capacity, as well as those that create new jobs
and income opportunities.
Table 5.1. Prioritization Approach for Policy Actions
Co-benefits (Development co- Feasibility (Financing needs and
Urgency (When to act)
benefits from climate actions) enabling conditions)
Short-term (S) 3 Highly Likely (HL)
Medium-term (M) 2 Likely (L)
Long-term (L) 1 Less Likely (LL)
5.4.1. Adaptation
Adaptation Strategies for Climate Resilience
To mitigate the impacts of river floods on communities and infrastructure, it is essential to
implement early warning systems and disaster preparedness measures in flood-prone areas.
Improving access to essential services like healthcare, education, and early warning systems for
lower-income households will enhance their resilience to climate-related impacts. Infrastructure
investments should consider increased climate risks, while land use policies must be developed
and enforced to prevent urban expansion in hazard-prone areas and protect natural buffers
such as forests and wetlands. Sustainable land use practices and reforestation efforts should be
promoted to reduce the risk of landslides and erosion in mountainous regions. Additionally, green
64 Towards a Green and Resilient Thailand
infrastructure and sustainable urban planning should be implemented to minimize the impact of
extreme weather events and flooding in urban areas.
The roles of the public and private sectors in addressing river floods and other climate challenges
are distinct but complementary. The public sector is crucial in establishing early warning systems,
developing disaster preparedness measures, and creating policies that enhance resilience, especially
for lower-income households. Government actions such as enforcing land use policies to prevent
urban sprawl in hazard-prone areas and protecting natural buffers are vital for mitigating climate
change impacts. Public investment in infrastructure must consider increased climate risks to better
protect communities from extreme weather events.
The private sector can integrate sustainable practices and innovative solutions into its operations.
Businesses can invest in green infrastructure and sustainable urban planning, which are essential for
minimizing the impact of extreme weather events and flooding in urban areas. The private sector’s
role in financing and implementing these measures, in collaboration with public sector policies and
support, is critical for achieving effective and comprehensive adaptation strategies. Collaboration
between the public and private sectors, supported by public-private partnerships, is key to building
resilient communities and reducing vulnerabilities to climate-related impacts.
The modeling conducted in this study provides valuable insights that inform key policy
recommendations for Thailand’s climate change adaptation efforts. These recommendations
are crucial for enhancing resilience and mitigating the impacts of climate-related events. Table 5.2
elaborates on the key recommendations.
Table 5.2. Priority Adaptation Actions
Action Description Urgency Co-benefits Feasibility
Implement Given the significant projected impact of S 3 L
flood floods, Thailand must prioritize comprehensive
management flood management strategies to reduce the
strategies vulnerability of communities and infrastructure.
Key measures include investing in flood control
infrastructure like levees and flood barriers,
implementing nature-based solutions such as
wetland restoration and floodplain zoning, and
strategically locating new infrastructure away
from flood-prone areas. Enhancing resilience
through improved drainage systems and
promoting green infrastructure can further
mitigate the adverse impacts of floods. (Ministry
of Natural Resources and Environment,
Ministry of Interior, Urban Local Bodies and
Communities)
Chapter 5. Overall Conclusion and Recommendations 65
Action Description Urgency Co-benefits Feasibility
Develop Early warning systems are vital for preparedness S 3 L
early warning and reducing the risk of loss during extreme
systems weather events. Thailand should invest in advanced
and enforce technologies and community engagement for
building these systems. Enforcing building regulations to
regulations ensure structures can withstand and are elevated
above flood levels is essential. Strategic planning
and zoning in flood-prone areas, guided by risk
assessments, can minimize exposure, and promote
sustainable development. (Ministry of Natural
Resources and Environment, Ministry of Interior,
Ministry of Agriculture, Local Government Units
and Community Organizations)
Enhance With the increasing threat of sea-level rise M 2 HL
coastal and coastal erosion, Thailand should enhance
resilience coastal resilience. This includes implementing
nature-based solutions like mangrove restoration
and beach nourishment and investing in hard
infrastructure like seawalls and breakwaters.
Developing coastal zone management plans
that integrate climate considerations and involve
local communities is crucial for sustainable
coastal adaptation. (Department of Marine and
Coastal Resources, Department of National
Parks, Wildlife and Plant Conservation. Local
Community Groups)
Promote Climate change poses significant risks to M 1 L
climate-smart Thailand's agriculture, crucial for food security
agriculture and livelihoods. To build resilience, Thailand
should promote climate-smart practices like
crop diversification, water-efficient irrigation,
and soil conservation. Providing farmers with
access to climate information and extension
services will help them to adapt and minimize
crop losses. (Ministry of Agriculture and
Cooperatives, Ministry of Natural Resources
and Environment, Local Government Units and
Community Organizations, Research Institutions
and Academia)
Strengthen As urbanization accelerates, cities in Thailand L 2 LL
urban face increased climate-related risks like
resilience heatwaves, urban flooding, and infrastructure
damage. Investing in green infrastructure, such
as parks and green roofs, can mitigate the urban
heat island effect and reduce flood risk.
66 Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Integrating climate considerations into urban
planning and design, including climate-responsive
building codes and sustainable transport
systems, will enhance urban resilience and
promote sustainable development. (Ministry
of Interior, Ministry of Natural Resources and
Environment, Ministry of Digital Economy
and Society, Local Government Units and
City Planning Authorities, Private Sector and
Industry)
Enhance Recognizing the importance of local L 2 L
community- knowledge and community participation,
based Thailand should prioritize community-based
adaptation adaptation approaches. Empowering local
communities to implement tailored adaptation
measures will enhance grassroots resilience.
Supporting community-led initiatives, such as
climate-resilient agriculture and disaster risk
reduction activities, can build social cohesion
and strengthen adaptive capacity. (Ministry
of Agriculture and Cooperatives, Ministry
of Natural Resources and Environment,
Local Government Units and Community
Organizations)
Invest in Climate-proofing infrastructure investments is M 2 L
climate- essential for reducing vulnerability to climate
resilient change impacts. Thailand should integrate
infrastructure climate considerations into infrastructure
planning, design, and maintenance across
sectors like transportation, energy, and water
management. This includes incorporating climate
risk assessments, designing infrastructure to
withstand extreme weather, and ensuring robust
maintenance and monitoring systems. (Ministry
of Transport, Ministry of Energy, Ministry of
Interior. Local Government Units and Municipal
Authorities, Private Sector and Industry)
Overall, the integration of these recommendations into Thailand’s climate adaptation strategies
is paramount for fostering a resilient economy, enhancing quality of life, and safeguarding the
planet for future generations. Investing in adaptation measures protects vulnerable communities
and infrastructure from the impacts of climate change and strengthens the economy by reducing
disaster-related losses and enhancing productivity in sectors such as agriculture and tourism.
Moreover, building resilience to climate change fosters social cohesion and inclusivity, ensuring that
no one is left behind in the face of environmental challenges.
Chapter 5. Overall Conclusion and Recommendations 67
5.4.2. Mitigation
Thailand faces significant challenges in mitigating its carbon footprint and achieving carbon
neutrality by 2050, grappling with rapid urbanization, industrial growth, and reliance on
fossil fuels. To succeed, Thailand must enact comprehensive policies, invest in renewable energy
infrastructure, and promote clean technologies. Table 5.3 elaborates on the key mitigation
recommendations.
In Thailand’s quest for carbon neutrality by 2050, the roles of the public and private sectors in
mitigation are distinct yet interconnected. The public sector is crucial in crafting and enforcing
policies, such as carbon pricing and renewable energy incentives, that establish a framework for
reducing emissions. Government investment in renewable infrastructure and public awareness
campaigns is essential to create a supportive environment for sustainable development. Meanwhile,
the private sector must implement these policies through innovation and investment in clean
technologies. Businesses drive the transition to renewable energy and enhance energy efficiency
across industries. The adoption of electric vehicles and other low-carbon technologies by private
enterprises can significantly reduce the carbon footprint of transportation and other sectors.
Effective collaboration between government and industry is essential, with public policies and
incentives aligning with private sector initiatives to ensure a unified approach to carbon mitigation.
Table 5.3. Priority Mitigation Actions
Action Description Urgency Co-benefits Feasibility
Implement Introducing carbon pricing mechanisms, such S 2 HL
carbon pricing as a carbon tax or emissions trading scheme,
mechanisms in Thailand can incentivize businesses to
reduce carbon emissions. These mechanisms
encourage cleaner technologies and practices,
leading to reduced emissions. Revenue from
carbon pricing can be reinvested in climate
mitigation and adaptation efforts, enhancing
Thailand's resilience to climate change.
(Ministry of Finance, Ministry of Environment
and Natural Resources, Ministry of Industry,
Ministry of Energy, Ministry of Agriculture and
Cooperatives, Private Sector and Industry)
Power sector The Government of Thailand should prioritize S 3 L
reforms power sector reforms to enhance the
effectiveness of carbon taxes. By aligning energy
pricing with carbon reduction goals, these
reforms would encourage investment in cleaner
technologies and support a smoother transition
to a low-carbon economy. (Ministry of Energy,
Electricity Generating Authority of Thailand,
Ministry of Finance, Energy Regulatory
68 Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Commission, Department of Alternative Energy,
Development and Efficiency, Private Sector
and Industry, International Organizations and
Development Partners)
Utilize carbon The revenue generated from carbon taxes S 3 HL
tax revenues could be channeled into a dedicated climate
to support fund, supporting other critical climate policies
other climate and initiatives, further accelerating the country's
policy transition to a low-carbon climate resilient
economy. (Ministry of Finance, Ministry of
Energy, Office of the National Economic
and Social Development Council. Climate
Change Department, Ministry of Environment
and Natural Resources, Energy Regulatory
Commission)
Collaborate for Collaborating with international organizations M 2 L
electric vehicle and private sector partners can accelerate
transition Thailand’s transition to electric vehicles
(EVs). By sharing knowledge, expertise, and
resources, Thailand can address barriers to EV
adoption, such as high upfront costs and limited
charging infrastructure. These partnerships
can also foster domestic EV manufacturing
capabilities, creating new opportunities for
economic growth and innovation. (Automobile
Manufacturers, Charging Infrastructure
Providers, Energy Companies, Ministry of
Energy, Ministry of Transport, Thailand Board
of Investment)
Implement a Thailand can promote widespread EV adoption M 2 L
comprehensive through a comprehensive policy package. This
EV policy could include incentives for EV purchases,
package subsidies for charging infrastructure, and tax
breaks for manufacturers. By addressing both
supply and demand-side barriers, Thailand can
create a supportive environment for EV uptake,
reduce GHG emissions from transportation,
and improve urban air quality. (Ministry of
Energy, Ministry of Transport, Department of
Land Transport Electricity Generating Authority
of Thailand, Thailand Board of Investment,
Ministry of Finance, National Science and
Technology Development Agency. Office of the
National Economic and Social Development
Council)
Chapter 5. Overall Conclusion and Recommendations 69
Action Description Urgency Co-benefits Feasibility
Implement Thailand can mitigate climate change and L 2 L
afforestation protect ecosystems by implementing
and forest afforestation and forest restoration measures.
restoration Restoring degraded forests and expanding
measures green cover will sequester carbon dioxide,
enhance biodiversity, and provide economic
benefits such as job creation in forestry and
opportunities for ecotourism. These measures
are essential for Thailand’s long-term climate
resilience and sustainability. (Ministry of Natural
Resources and Environment, Department of
National Parks, Wildlife and Plant Conservation,
Royal Forest Department, Department of
Land Development, Ministry of Agriculture and
Cooperatives, Office of the National Economic
and Social Development Council, Local
Government Units and Municipal Authorities,
Private Sector and Non-Governmental
Organizations)
Enhancing Improving energy efficiency in Thailand is M 2 L
Energy essential for reducing consumption and
Efficiency greenhouse gas emissions. Measures include
adopting strict efficiency standards, promoting
energy-efficient building designs, and using
smart grid technologies. Incentives for energy
audits and savings technologies, along with
public awareness campaigns and training, will
support a transition to a greener economy
and lower overall energy demand. (Ministry
of Energy, Department of Alternative Energy
Development and Efficiency, Energy Regulatory
Commission Ministry of Interior, Office of the
National Economic and Social Development
Council, Thai Green Building Institute, Local
Government Units and Municipal Authorities,
Private Sector and Industry Associations)
By adopting these tailored policies and measures, Thailand can effectively mitigate climate
change, promote sustainable development, and build a more resilient and prosperous future
for its citizens. Collaboration, innovation, and strong policy frameworks will be key to achieving
Thailand’s climate goals and ensuring a livable planet for future generations.
70 Towards a Green and Resilient Thailand
5.4.3. Circular economy
Adopting a circular economy is crucial for Thailand, especially to address the plastic waste crisis
affecting the Chao Phraya River. This development model provides a comprehensive solution by
reducing plastic use, enhancing recycling and reuse, and minimizing waste. Table 5.4 details key
recommendations for transitioning to a circular economy.
To tackle plastic pollution and move towards a circular economy, the public and private sectors
must collaborate. The public sector should establish regulatory frameworks, implement policies
like extended producer responsibility (EPR), and invest in waste management infrastructure. It
should also promote eco-design standards and run awareness campaigns to encourage sustainable
consumer behavior. The private sector’s role involves applying these policies through innovation,
redesigning products to reduce plastic use, and investing in advanced recycling technologies. Efficient
value chains for material reuse and repurposing are essential. By aligning public policy with private
sector practices, Thailand can effectively address plastic waste and advance towards a sustainable
circular economy.
Table 5.4. Priority Circular Economy Actions
Action Description Urgency Co-benefits Feasibility
Policy The Thai government should create a M 2 HL
Framework comprehensive policy framework for a circular
for Circular economy, including regulations, incentives,
Economy and guidelines to promote sustainable design,
resource efficiency, and waste reduction.
Setting clear targets and timelines will guide
and hold stakeholders accountable across
sectors. (Ministry of Natural Resources and
Environment, Department of Environmental
Quality Promotion, Ministry of Industry,
Office of the National Economic and Social
Development Council, Department of Industrial
Works, Thailand Board of Investment, Local
Government Units and Municipal Authorities)
Support Thailand should leverage innovation and M 3 L
Innovation and technology to advance the circular economy.
Technology Investing in research and development will
help scale up technologies for recycling,
remanufacturing, and resource recovery.
Embracing digital technologies and data analytics
can optimize resource use and support circular
business models. By fostering a culture of
innovation, Thailand can lead in sustainable
resource management and circular solutions.
(Ministry of Science and Technology, National
Chapter 5. Overall Conclusion and Recommendations 71
Action Description Urgency Co-benefits Feasibility
Science and Technology Development Agency,
Ministry of Industry, Department of Industrial
Works Office of the National Economic and
Social Development Council, Thailand Board
of Investment, Private Sector and Industry
Associations, Universities and Research
Institutions)
Circular Promoting circular procurement practices is M 2 HL
Procurement essential for driving demand for sustainable
products and services in Thailand. The
government can lead by incorporating
circularity criteria into public procurement.
Clear guidelines for evaluating product and
service circularity will encourage businesses to
adopt circular practices. By boosting market
demand for circular products, Thailand can
foster innovation, investment, and progress
toward sustainability goals. (Ministry of Finance,
Office of the Public Procurement, Ministry
of Commerce, Department of Internal
Trade, Ministry of Industry, Thailand Board of
Investment, Office of the National Economic
and Social Development Council, Private Sector
and Industry Associations, Environmental Non-
Governmental Organizations)
Product Design Thailand can encourage businesses to focus M 2 L
Improvements on eco-design principles, such as durability,
repairability, and recyclability, in product
development. Offering incentives and support
for sustainable design will help reduce waste and
improve resource efficiency. Designing products
for easy disassembly and component reuse can
extend their lifespan, minimize new resource
extraction, and reduce environmental impact.
(Ministry of Industry, Department of Industrial
Works, National Science and Technology
Development Agency, Thailand Board of
Investment, Office of the National Economic
and Social Development Council, Private Sector
and Industry Associations, Environmental Non-
Governmental Organizations, Universities and
Research Institutions)
72 Towards a Green and Resilient Thailand
Action Description Urgency Co-benefits Feasibility
Enhanced Thailand should develop and invest in robust M 2 M
Material recycling infrastructure and technologies
Recycling to facilitate efficient collection, sorting,
and processing of recyclable materials. By
establishing comprehensive recycling programs
and promoting consumer awareness and
participation, Thailand can increase recycling
rates and divert more waste from landfills.
Partnering with the private sector and
incentivizing investment in recycling facilities
can accelerate the transition to a circular
economy. (Ministry of Natural Resources and
Environment, Department of Environmental
Quality Promotion, Department of Local
Administration, Ministry of Industry, National
Science and Technology Development
Agency, Thailand Board of Investment, Local
Government Units and Municipal Authorities,
Private Sector and Industry Associations)
Chapter 5. Overall Conclusion and Recommendations 73
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80 Towards a Green and Resilient Thailand
SUPPLEMENTARY INFORMATION SECTION 1
Detailed Methods
The dynamic Integrated Economic-Environmental Model (IEEM) linked with spatial Land Use Land
Cover (LULC) change and Ecosystem Services Modeling (IEEM+ESM) approach was applied in this
study, which is a cutting-edge analytical framework that incorporates feedback between changes in
Ecosystem Services (ES) and the economy while maintaining consistency with a country’s System
of National Accounts. The three main models comprising IEEM+ESM — namely IEEM, the LULC
change model, and the ES models— and how they interact are discussed in turn.
An Integrated Economic-Environmental Model (IEEM) for Thailand
IEEM+ESM is an economy-wide, decision-making framework for evidence-based public policy and
investment design. The framework is being applied by multilateral institutions and government
institutions including Ministries of Finance and Central Banks in future-looking analysis of public
policy and investment. IEEM+ESM models have been developed and applied in over 30 countries
to answer hundreds of questions of public policy and investment, including analysis of the complex
challenges associated with climate change, the Sustainable Development Goals and Green Growth
Strategies, and across economic sectors including energy, infrastructure, agriculture and tourism.
Figure SI 1 presents the latest IEEM model coverage across the globe.
Figure SI1. IEEM+ESM countries indicated in green
Source: Authors’ own elaboration based on above cited data.
The value-added of IEEM includes: (i) the model’s integration of detailed environmental information
through the United Nations System of Environmental-Economic Accounting (SEEA; United
Nations et al., 2014) to represent the economy and the environment in a comprehensive and
inter-connected way, all consistent with the System of National Accounts (European Commission
Supplementary Information Section 1 81
et al., 2009); (ii) the model’s generation of indicators demanded by policy makers including Gross
Domestic Product (GDP), employment, and poverty, as well as metrics of wealth, sustainability,
natural capital stocks, and ES supply. The metric of wealth used is a variation of adjusted net savings
or genuine savings (Hamilton, 1999; Hamilton and Clemens, 1999) in which net national savings is
adjusted for changes in natural capital stocks and environmental damage. GDP, on the other hand,
lacks the value of changes in natural capital stocks and environmental damage. Wealth metrics are
necessary to inform policies aimed at sustainable economic development rather than once-off,
short-run economic growth at the expense of a country’s natural capital asset base (Banerjee et
al., 2021b; Dasgupta, 2021; Lange et al., 2018; Polasky et al., 2015; Stiglitz et al., 2010, 2009; UNEP,
2018); (iii) IEEM’s environmental modeling modules that capture the specific dynamics of natural
capital-based sectors while IEEM’s linkage with spatial ES modeling enables estimation of impacts
on the future flow of market and non-market ES.
At its core, IEEM is a single-country recursive dynamic Computable General Equilibrium (CGE)
model (Burfisher, 2021; Dervis et al., 1982; Dixon and Jorgenson, 2012; Kehoe, 2005; Shoven
and Whalley, 1992). CGE models are among the most well-documented class of models in the
literature over the last four decades, outlining the theory, methods, strengths, and limitations of
the approach (Burfisher, 2021, 2017; Cicowiez and Lofgren, 2017; Dervis et al., 1982; Dixon and
Jorgenson, 2012; Kehoe, 2005; Shoven and Whalley, 1992).
Three key documents provide detailed technical information for IEEM: (i) IEEM’s mathematical
structure is documented in Banerjee and Cicowiez (2020); (ii) IEEM’s database is an environmentally
extended Social Accounting Matrix (SAM) described in Banerjee et al. (2019b), and, (iii) a user
guide for IEEM, applicable to any country with the corresponding database, is available in Banerjee
and Cicowiez (2019). With the IEEM model’s theory maintained separately from a country
application’s data and database, these three documents provide the relevant technical detail for
any IEEM country application.
The results from simulations with IEEM provide a comprehensive and consistent view of the
economy and its evolution over time, including linkages between primary factors; production and
the income it generates; households; the government (its policies and budget), and the balance of
payments. In terms of theoretical pedigree, IEEM for Thailand can be characterized as a dynamic
extension of standard comparative-static single-country CGE models for developing countries in
the tradition of Dervis et al. (1982), Lofgren et al. (2002) and Robinson et al. (1999). In recent
years, models belonging to this class have been widely used in applied development policy research.
CGE models, in contrast to partial equilibrium approaches, consider all sectors in an economy
simultaneously and take consistent account of economy-wide resource constraints, inter-sectoral
intermediate input-output linkages, and interactions between markets for goods and services on
the one hand, and primary factor markets including labor markets on the other. CGE models such
as IEEM simulate the full circular flow of income in an economy, from income generation from
production to the primary distribution of that income to workers, owners of productive capital,
and recipients of the proceeds from natural capital endowments. Income is used for consumption
and investment and its redistribution may be achieved through taxes and transfers.
82 Towards a Green and Resilient Thailand
In the current application to Thailand, the starting point for the construction of the IEEM database,
a Social Accounting Matrix (SAM) is Thailand’s most recent (2012) Supply and Use Tables6 and
2019 macro-economic data from the Office of the National Economic and Social Development
Council, government budget data from the Bureau of the Budget, and balance of payment data
from the International Monetary Fund. Thailand’s SAM distinguishes 26 production activities and
26 commodities or products; eight primary production factors including labor factors, private
capital, government capital; five natural resources (agricultural land and mineral stocks); and one
household category (Table SI.1.).
Table SI1. Accounts in the 2019 Social Accounting Matrix for Thailand
Category Item
Sectors (activities [26] and Agriculture: crops; livestock
commodities [26]) Other primary: forestry; fishing; mining
Manufacturing: food industry; textiles and wearing apparel; wood and
paper; chemicals; rubber and plastic; non-metallic mineral prod; metals
and metal prod; machinery and equipment; vehicles; other manufacturing
Other industry: electricity, gas and water; construction
Services: trade; hotels and restaurants; transport; business services;
public administration; education; education and health; recreation; other
services
Factors (8) Labor
Capital, private
Capitall, goverment
Land: crops, livestock, forestry
Fishing
Mining
Institutions (4)* Households
Government
Rest of the World
International Tourists
Taxes (2) Tax, indirect
Tax, direct
Distribution margins (3) Trade and transport margins, domestic
Trade and transport margins, imports
Trade and transport margins, exports
Investment (3) Investment, private
Investment, government
Investment, change in inventories
*The institutional capital accounts are for domestic non-government (aggregate of households and enterprises),
government and rest of the world.
Source: Authors’ elaboration.
6 Published in the Asian Development Bank Data Library: https://data.adb.org/dataset/supply-and-use-tables-Thailand
Supplementary Information Section 1 83
The numerical calibration process for IEEM involves the determination of the initial model
parameters in such a way that the equilibrium solution for the 2019 benchmark year exactly
replicates the 2019 benchmark SAM. The values for the sectoral elasticities of factor substitution,
the Armington elasticities (i.e., the elasticities of substitution between imports and domestically
produced output by commodity), the Constant Elasticity of Transformation (CET) elasticities (i.e.,
the elasticities of transformation between exports and domestic sales), and the income elasticities
of household demand are informed by available econometric evidence from secondary sources
presented in Aguiar et al. (2019), Muhammad et al. (2011) and Sadoulet & de Janvry (1995). In
summary, the elasticities of factor substitution are in the range of 0.20-0.95, the Armington and
CET elasticities are both in the range of 0.9-2.0, and the income elasticities of household demand
are in the range 0.72-1.52.
IEEM may be used directly to estimate public policy and investment impacts on material ES (IPBES,
2019), also referred to as provisioning ES (European Environment Agency, 2018; Haines-Young
and Potschin, 2012), most of which have a market price. With some database customization, IEEM
may also be used to directly estimate impacts on cultural and recreational ES including tourism and
recreation. To enable estimation of impacts on non-material ES, also known as regulating ES, which
generally do not have a market price, we link IEEM with spatial LULC change and ES modeling.
In linking IEEM with spatial modeling, we can estimate impacts on regulating services that are
driven by localized (national level) LULC change such as erosion mitigation, crop pollination, water
regulation, and water purification services. The bridge between IEEM and the spatial ES modeling
is made through the spatial allocation of IEEM-projected demand for land using a LULC change
model as described in the section that follows.
Land Use Land Cover Change Modeling
LULC change modeling is the necessary bridge between IEEM and spatial ES modeling. We use the
CLUE (Conversion of Land Use and its Effects; Verburg et al., 2008, 1999; Verburg and Overmars,
2009a) modeling framework to spatially allocate LULC change using empirically quantified
relationships between land use and location factors, in combination with the dynamic modeling of
competition between land use types. CLUE is among the most widely used spatial LULC change
models and has been applied at different scales across the globe (Rakotoarinia et al., 2023).
The version of the CLUE model family used is the Dynamic CLUE (Dyna-CLUE) model, which is
appropriate for smaller regional extents compared with global LULC change modeling (Veldkamp
and Verburg, 2004; Verburg et al., 2021, 2002; Verburg and Overmars, 2009b). IEEM demand
for land is spatially allocated across a grid with the LULC change model to generate baseline and
scenario-based mapped projections of LULC. The maps are the main variable of change used in
the ES modeling, with most other parameters held constant.
The Dyna-CLUE model is sub-divided into two distinct modules: a non-spatial demand module
populated with IEEM-derived demand for land, and a spatially explicit allocation procedure. The
allocation procedure determines the probability of occurrence of each LULC class for each pixel
as described below (suitability analysis). The results from the demand module specify, on an annual
84 Towards a Green and Resilient Thailand
basis, the area covered by the different land use types, which is a direct input to the allocation
module. Annual demands for forest, rain-fed crops, and grazing areas (and/or other LULC classes,
depending on the specific application) are generated by IEEM. In an intermediate step to the
allocation of demand for land, Dyna-CLUE calculates suitability maps for each land use type that
reflect the probability of each land-use class occurring for each pixel. This suitability analysis is
performed as a binomial logit stepwise regression for each land use and set of explanatory variables
(Verburg et al., 2021).
The IEEM-Enhanced Dyna-CLUE LULC change model was calibrated for this application. The 2020
LULC map developed through the European Space Agency’s Climate Change Initiative (Defourny
et al., 2019) was used as the base map. This base map was selected based on the relevance of the
LULC classes that it presents (27 classes), its long-time series (1992 to present with a few year
delay), its recent base year (2020), and its spatial resolution (300 meters). We reclassified the base
map to nine LULC classes to meet the needs of this application. The reclassified map is shown in
SI 2 and the initial area in each LULC class is shown in SI 2.
Figure SI2. Reclassified base Land Use Land Table SI2. Reclassified Land Use Land Cover
Cover (LULC) Map for 2020 (LULC) classes and areas
Land Use Land Cover Class Hectares
Irrigated crops 2,967,525
Rainfed crops 27,688,075
Grassland 183,700
Forest and natural vegetation 8,250,500
Mosaic vegetation 8,594,400
Shrubland 2,156,225
Mangrove and flooded forest 378,775
Urban and bare areas 436,875
Water 958,350
Total 51,614,425
Source: Calculations made based on European Space
Agency (ESA) Climate Change Initiative (CCI) 2020
Land Use Land Cover (LULC) Map.
Source: Reclassified based on European Space Agency
(ESA) Climate Change Initiative (CCI) 2020 Land Use
Land Cover (LULC) Map.
Supplementary Information Section 1 85
Ecosystem Services Modeling
The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) suite of models (Natural
Capital Project, 2023b) was used in the IEEM+ESM workflow to calculate scenario-based, spatially-
explicit changes in ES supply. The InVEST models are open source, well documented, and the most
widely used set of tools for ES modeling globally. InVEST combines LULC maps and biophysical
information to calculate ES. In this study, six ES models were parameterized based on both
global and national data sources, namely: the sediment delivery ratio model used to calculate the
Revised Universal Soil Loss Equation; the carbon storage model used to calculate carbon storage
and carbon sequestration potential; the annual water yield model to calculate water supply; the
nutrient delivery ratio model to calculate the amount of nutrients transported to streams; the
crop pollination model to calculate an index of pollinator abundance; and, the coastal vulnerability
model to calculate an index of exposure to erosion and inundation during storm events.7
The main variable of change in the ES modeling is the scenario-driven LULC projections generated
with the Dyna-CLUE model. New LULC maps for each scenario and time period are used in each
InVEST model run for each of the five InVEST models. Note the coastal vulnerability model does
not require LULC as an input and thus is not discussed in the section that follows. Scenario-driven
changes in ES supply in any given year are calculated as differences between ES in the scenario
for year t and for the baseline scenario for that same year. For ease of interpretation and analysis,
results were summarized as a percent difference from baseline for each of Thailand’s six regions.
Model Integration and Interaction: The Dynamic IEEM+ESM Approach
In the basic IEEM+ESM workflow, scenarios are implemented in IEEM and impacts on economic
indicators are reported. As described above, IEEM generates a projection of demand for land
that is spatially allocated with the LULC change model. The five ES models are run with the LULC
change maps generated for the baseline initial year and final year as well as for each scenario.
The difference between ES supply in each scenario and the baseline case in the final time period
provides the scenario-based impact on the five ES. This information alone, reported in biophysical
units, is valuable for shedding light on trade-offs between economic, environmental, and social
outcomes.
Changes in ES supply affect the economy through various mechanisms. Some ES impacts are
determined in IEEM without any additional spatial or ES modeling. This pertains specifically to
provisioning ES that have existing markets. Following the Common International Classification of
Ecosystem Services (European Environment Agency, 2018; Haines-Young and Potschin, 2012),
these ES include: food, potable water supplied by a utility company, fiber/biomass, and mineral and
non-mineral subsoil extracts. With additional SAM database customization, cultural and recreational
ES values are also estimated through IEEM implementation (Banerjee et al., 2018).
7 Note that the implementation of the coastal vulnerability model is preliminary since there is a lack of data related to
wave heights and wind speed and direction in proximity to Thailand’s mainland.
86 Towards a Green and Resilient Thailand
The basic workflow does not, however, generate economic values for those ES, mostly regulating
ES, that do not have a market price. The InVEST models on their own also do not generate these
values. While it is possible to estimate the economic value of changes in ES flows using ES values
obtained from stated preference, benefits transfer, and other environmental economic methods,
in this study we implemented the dynamic IEEM+ESM approach that captures the impacts of
policies on regulating ES that do not have a market price. IEEM+ESM incorporates dynamic
feedbacks between natural capital, ES, and the economic system (Banerjee et al., 2020; Banerjee
et al., 2019a; Banerjee et al., 2020b) enabling estimation of the contribution of regulating ES to
economic indicators.
These regulating ES include both abiotic and biotic services such as: hydrological regulation including
flood control and coastal protection, regulation of soil processes, wind and fire protection, climate
and air quality regulation, pest and disease control, and pollinator activity. To integrate these ES in
the dynamic IEEM+ESM framework, the ES of interest is identified and a transmission pathway to
the economy then is established in quantitative terms. In this study, we focus on integration of soil
erosion mitigation and crop pollination ES in the dynamic framework, though we also estimate
impacts on the economic value of cultural and recreational and provisioning ES and impacts on
the remaining four regulating ES (water regulation, water purification, carbon storage, and coastal
vulnerability) in biophysical units.
Specifically, we related changes in soil erosion mitigation ES (Borrelli et al., 2017; Panagos et
al., 2018, 2015; Pimentel, 2006; Pimentel et al., 1995) and crop pollination ES (Bauer and Sue
Wing, 2016; Garibaldi et al., 2016; Johnson et al., 2021; Kennedy et al., 2013; Klein et al., 2007) to
agricultural productivity. Additional transmission pathways (though not considered here) could be
specified; for example, increased soil erosion and nutrient run-off affect water quality, which can
have implications for water treatment costs, human health, and tourism values (Aguilera et al.,
2018; O Banerjee et al., 2019; Keeler et al., 2012; O’Neil et al., 2012; Paerl and Huisman, 2008;
STAC, 2013).
The dynamic IEEM+ESM approach has three important features that advance integrated economic-
environmental methods published elsewhere: (i) by accounting for changes in ES flows throughout
the analytical period, agents in IEEM adjust their behavior according to these changes in ES flows; (ii)
the approach maintains consistency with a country’s National Accounting System, which enhances
its credibility with country institutions including Ministries of Finance and Central Banks that are
often responsible for developing and maintaining their country’s System of National Accounts; and,
(iii) the economic value of regulating ES is calculated endogenously in the IEEM+ESM framework.
In this study, demand for land is exogenous and defined entirely by the scenarios themselves. Where
demand for land is endogenous, price in IEEM is the equilibrating mechanism that brings supply
and demand into balance. In this workflow presented in Figure SI 3, Dyna-CLUE is implemented
to spatially allocate demand for land. Using the LULC maps produced through the LULC modeling,
the ES models of interest (the sediment delivery ratio model and crop pollination model in this
Supplementary Information Section 1 87
case that are used to calculate soil erosion mitigation ES and pollinator abundance, respectively) are
run in periodic time steps (five-year periods in this study) for the entire analytical period.8
Figure SI3. Overview of the dynamic IEEM+ESM workflow applied to Thailand
1 2 3 4 5 6 7
Calculate
DYNACLUE Invest
Economic shocks: for Implement
LULC models:
results + each 5-year erosion IEEM
Policy modeling; erosion,
projection period, and resuls, ES
scenarios new LULC pollination
of demand calculate pollination results
IEEM maps 5-year water yield,
for land di erence shocks in reporting
timestep water quality,
2020-50 with respect IEEM
carbon
to base
Source: Authors’ own elaboration.
In the case of the sediment delivery ratio model, this model calculates the soil loss per pixel
across the country (tons/pixel). In the case of the crop pollination model, pollinator abundance is
calculated as an index of pollinator abundance for each pixel. The scenario impact on ES supply is
calculated as the difference between the scenario ES map in year t+5 and the baseline ES map in
the year t+5 using a raster calculator in a Geographic Information Systems (GIS) software package.
Since ES impacts are calculated on a five-year basis, the change in ES between five-year time steps
is calculated by simple linear interpolation. To link the change in soil erosion mitigation and crop
pollination ES back to the economy, economic shocks for each ES are calculated to account for the
change in future ES supply.
We estimated the impact of changes in erosion on agricultural productivity based on a survey of
the literature. We establish a threshold after which erosion is considered to have a measurable
effect on agricultural productivity. Following Panagos et al. (2018) and our survey of the literature,
this threshold is set to a level of erosion greater than 11 tons per hectare per year. In this approach,
first we identify the area by Thai region exhibiting erosion of greater than 11 tons/ha, using zonal
statistics and the raster calculator in a GIS software package, for both the baseline and each
scenario. If the area of erosion greater than 11 tons/ha is larger in the policy scenario compared
with the baseline, this indicates that erosion has increased as a result of the policies implemented
in the scenario. If the area of erosion greater than 11 tons/ha is smaller in the scenario compared
with the baseline, this indicates that erosion has decreased as a result of the policies implemented
in the scenario.
8 Note that when demand for land is exogenously determined, as is the case in this study where the scenarios define
the demand for land, the LULC change model and the ES models are run iteratively to calculate changes in ES and
the economic shocks described below. Iteration between all three models (IEEM, the LULC change model and the
ES models) is required where there is endogeneity in demand for land (for example, see: Banerjee, Cicowiez, et al.
(2020b) and Banerjee, Cicowiez, Malek, et al. (2022)).
88 Towards a Green and Resilient Thailand
Based on Panagos et al. (2018) and our survey of the literature, we relate the presence of erosion
greater than 11 tons/ha to a reduction in agricultural productivity of 8 percent. This 8 percent is
applied from the base year to 2050. In a more pessimistic scenario, we use a value of 16 percent.
To create feedback between changes in ES and IEEM, we apply equation 1 to each scenario:
SERr
LPLr = · 0.08 equation 1
TAAr
Where:
• LPLr is the land productivity loss by subscript region r of Thailand;
• SERr is the agricultural land area (hectares) subject to erosion >11t/ha/year in each region;
• TAAr is the total agricultural area, both crop and livestock, by region and;
• 0.08 is the agricultural productivity shock.
In the case of crop pollination ES, the dependence of specific agricultural crops and the crop yield
impacts related to the presence or absence of pollinators was based on a seminal paper by Klein
et al. (2007). This paper provides the most comprehensive review of studies that associate crop
dependence on pollinators and yield. Due to the high level of disaggregation in crop types required
for this exercise, data from FAOSTAT — the UN Food and Agriculture Organization’s statistics
division — on specific crops for Thailand were used in conjunction with the IEEM database.
With crop output value as the variable of interest, Thailand’s crop output in the base year was
mapped to the crops presented in Klein et al. (2007). Note that some of the crops present in Klein
et al. (2007) were not produced in Thailand and some crops produced in Thailand including staple
crops such as wheat, rice, and corn are not pollinator dependent. Pollinator dependent crops are,
however, important for human nutrition, and deficiencies in nutrition have been directly associated
with pollinator decline (Chaplin-Kramer et al., 2019; Ellis et al., 2015; Smith et al., 2022). Analysis
of this data shows that 23 percent of the crop output in Thailand is to some degree pollinator
dependent. An economic shock to describe the relationship between crop pollinator abundance
and crop yield was calculated as described in equation 2.
CPCr = Dr · (Ar · Y(r,vh) · V(r,vh) · W(r,vh) + Ar · Y(r,h) · V(r,h) · W(r,h) + Ar · Y(r,m) · V(r,m) ·W(r,m) +Ar · Y(r,l) · Vrl · W(r,l) )
equation 2
Where:
• Dr is a pollinator adjustment factor representing current pollinator abundance relative to full
potential abundance.
• CPCr is the crop productivity impact for subscript region r of Thailand;
• Ar is pollinator abundance in subscript region r of Thailand;
• Y(r,vh) is the yield impact in region r for very highly pollinator dependent crops (subscript vh);
• V(r,vh) is the value of crop output in region r for very highly pollinator dependent crops
Supplementary Information Section 1 89
(subscript vh);
• W(r,vh) is the weight of the value of very highly pollinator dependent crops (subscript vh) in
Thailand’s total crop output value and;
• Subscripts h, m and l refer to high, medium and low dependent pollinator crops.
Pollinator abundance is calculated based on the baseline and scenario-based LULC maps generated
with Dyna-CLUE. The pollinator adjustment factor in the case of Thailand is based on Chaudhary
and Chand (2017). Yield impacts are derived from Klein et al. (2007) and mapped to Thailand’s
crop output from FAOSTAT and the IEEM database. The crop output value and weights are
calculated from FAOSTAT data. We implement LPLr and CPCr shocks in IEEM individually and
simultaneously, which enables analysis of the individual contribution of erosion mitigation and crop
pollination ES to economic outcomes. The IEEM+ESM approach enables estimation of the marginal
value of regulating ES that generally do not have a market price. At the time of publication, the
dynamic IEEM+ESM workflow is the only modeling framework in the peer-reviewed literature that
integrates dynamic feedback between changes in ES and the economy in this way.
90 Towards a Green and Resilient Thailand
SUPPLEMENTARY INFORMATION SECTION 2
Full Scenario Description
What follows is a complete description of the scenarios implemented in IEEM.
Baseline: This is the business-as-usual scenario that is used as the counterfactual reference scenario
to which all other scenarios are compared. It presents the future trajectory of Thailand’s economy,
projected until 2050, in the absence of any new large public policies and investments and without
further acceleration in the degradation of the natural capital base. The rate of deforestation is
based on (TEIF, 2021) and is calculated as 0.37 percent annually. It is assumed that 50 percent of the
area deforested is converted to productive cropland and the remaining 50 percent is assumed to
be degraded, unproductive, and unused. The baseline scenario includes climate change impacts for
current policies, estimated through a damage function approach. These impacts include damages
and losses related to floods and cyclones, reduced labor and land productivity for agriculture,
reduced construction sector labor productivity, tourism demand, and sea level rise as estimated in
Markandya (2023).
DEGRADE: Upon the baseline counterfactual, the first set of scenarios (DEGRADE) will represent
some of the main drivers of degradation discussed in the introduction. The comparison between
the baseline and DEGRADE reveals the economic, wealth, natural capital, and ES costs of policy
inaction. DEGRADE is comprised of the following sub-scenarios:
DEFOR: This sub-scenario represents an accelerated rate of deforestation with respect to
the baseline rate of deforestation. The projected rate of deforestation follows that of Global
Forest Watch data that is calculated as 0.5804 percent per year (Hansen et al., 2013; Harris et
al., 2021). Fifty percent of deforested land is assumed to be converted to productive cropland
and the other 50 percent is assumed to be degraded, unproductive, and unused.
DEFOR2: This sub-scenario represents an accelerated rate of deforestation with respect to
the DEFOR rate of deforestation. In this sub-scenario, an exponential decay function is applied
to the rate of deforestation in which the standing stock of forest left in 2050 is approximately
5.425 million ha, which approximates the size of Thailand’s protected forest area. All new
deforested areas are assumed to be degraded, unproductive, and unused in this sub-scenario.
FLOOD: This sub-scenario simulates coastal and inland flooding due to storms and cyclones
and its damage to infrastructure. A damage function approach was used that projects damage
from these phenomena for Relative Concentration Pathways (RCP) 4.5 and RCP8.5 projections.
The 90th percentile of damages arising from flooding was used in this scenario (Markandya,
2023). The distribution of economic impacts across Thailand’s economy followed that of the
2011 flood (World Bank, 2012).
CATFLOOD: This sub-scenario represents increasing intensity and frequency of storms
leading to extreme coastal and inland flooding. Thailand’s 2011 flood was considered a one in
50-year event. In this sub-scenario, we simulate two of these storm events occurring within
Supplementary Information Section 2 91
the modeling horizon to 2050. The year in which these storms occur was chosen as a random
number draw, resulting in these catastrophic floods occurring in years 2029 and 2047. The
severity of the economic impact of the flood in this sub-scenario was assumed to be double
that of the 2011 flood. The distribution of economic impacts across Thailand’s economy
followed that of the 2011 flood (World Bank, 2012).
CLIMATE_AGRI: This sub-scenario simulates the impact of projected climate change on:
(i) agricultural land productivity. We apply a damage function approach in which damages
from climate change impacts on land productivity for RCP4.5 and RCP8.5 were estimated in
Markandya (2023) and applied in this sub-scenario; and,
(ii) agricultural labor productivity. We apply a damage function approach in which damages
from climate change impacts on agricultural labor for RCP4.5 and RCP8.5 were estimated in
Markandya (2023) and applied in this sub-scenario.
LABPROD: This sub-scenario simulates the impact of projected climate change on construction
sector labor productivity. We apply a damage function approach in which damages from
climate change impacts on construction sector labor productivity for RCP4.5 and RCP8.5
were estimated in Markandya (2023) and applied in this sub-scenario.
TOUR: This sub-scenario simulates the impact of projected climate change — specifically,
temperature rise — on foreign tourism demand in terms of a reduction in the number of
tourist arrivals and their average expenditure. We apply a damage function approach in which
damages from climate change impacts on tourism demand for RCP4.5 and RCP8.5 were
estimated in Markandya (2023) and applied in this sub-scenario.
SEALEVEL: This sub-scenario simulates the impact of sea level rise on coastal infrastructure.
We apply a damage function approach in which damages from climate change impacts on sea
level rise for RCP4.5 and RCP8.5 were estimated in Markandya (2023) and applied in this sub-
scenario.
ERODE: This sub-scenario models the effect of LULC change and deforestation on soil
erosion and its resulting impact on agricultural productivity following Banerjee et al. (2023)
and Banerjee & Cicowiez (2022).
POLLEN: This sub-scenario models the effect of LULC and deforestation on crop pollination
and its resulting impact on agricultural productivity following Banerjee et al. (2023) and Banerjee
& Cicowiez (2022).
Note that RCP4.5 and RCP8.5 pathways were used in the estimation of the damage functions for
the following scenarios: FLOOD, CLIMATE_AGRI, LABPROD, SEALEVEL, TOUR and DEGRADE.
The names of the scenarios that use the RCP4.5 projections terminate with _OPT, and the names
of the scenarios that use the RCP8.5 projections terminate with _PES+.
POLICY: Contrasting with the DEGRADE scenarios, the policy and investment (POLICY)
scenario simulates the implementation of climate change mitigation and adaptation strategies. The
92 Towards a Green and Resilient Thailand
comparison of POLICY and DEGRADE shows the economic benefits of investing in enhancing
natural capital and resilience and contributing to economic recovery, as well as trade-offs that may
exist between economic, social, and environmental outcomes. The POLICY scenario is comprised
of the following sub-scenarios:
NODEFOR: This sub-scenario represents the elimination of deforestation with respect to
the DEFOR scenario’s rate of deforestation. Deforestation is reduced linearly beginning in
2024 until reaching zero new deforestation in 2037. The cost of avoiding deforestation was
estimated as an annual reoccurring cost equivalent to US$5.82/ha/yr.9
REDFLOOD: This sub-scenario simulates measures to reduce the damages caused by coastal
and inland flooding and cyclones through the implementation of early warning and monitoring
systems as well as physical infrastructure to mitigate damage. This sub-scenario also assumes
global cooperation, that all countries implement their NDCs, and that these NDCs are
effective in mitigating climate change impacts related to increasing frequency and intensity of
storms. These measures are assumed to be effective in offsetting 70 percent of the climate
change impacts on agriculture as captured by the FLOOD and CATFLOOD sub-scenarios.
The investment costs for transportation infrastructure were supplied by the World Bank.
For RCP4.5, we use 75 percent of these investments in transportation infrastructure, and
for RCP8.5, we use 100 percent of these costs. Investment costs for coastal protection, river
protection, and Water, Sanitation and Hygiene (WASH) were supplied by the World Bank.
For this sub-scenario, we use 100 percent of river protection costs and WASH costs and 25
percent of coastal protection costs. For RCP4.5 the “best” investment scenario was used,
while for RCP8.5, the “max’”investment scenario was used.
REDCLIMATE_AGRI: This sub-scenario simulates measures to adapt to projected climate
change and its impact on agricultural land and agricultural labor productivity. These measures
are assumed to be effective in offsetting 70 percent of the climate change impacts on
agriculture as captured by the CLIMATE_AGRI sub-scenario. Investments in adapting to climate
change include investment in irrigation and climate-smart agriculture. Investments in irrigation
infrastructure were supplied by the World Bank. For RCP4.5, the “best” investment scenario
was used, while for RCP8.5, the “max” scenario was used. Investments in climate adapted
agriculture follow the estimates presented in Khatri-Chhetri et al. (2021).
REDSEALEVEL: This sub-scenario assumes global cooperation, that all countries implement
their NDCs, and that these NDCs are effective in mitigating and adapting to sea-level rise.
Investments in adapting to sea level rise were supplied by the World Bank. We used 75 percent
of the coastal protection investments presented in the data and the “best” investment scenario
for RCP4.5 and “max” investment scenario for RCP8.5. These measures are assumed to be
9 This cost is based on the Cambodia CCDR and specifically on the (REDD+ Task Force Secretariat, 2020). For
reference, the cost of fire protection in Cambodia between 2013 and 2022 was on average US$8.6 million/year
which equates to US$1.89/ha/yr, considering a standing forest stock of 16,255,595 (see email of September 27 and 29,
2023). This value is low; as a point of comparison, in Brazil’s CCDR, we used a value of US$538.70/yr/ha (Consultant
for the World Bank, 2022).
Supplementary Information Section 2 93
effective in offsetting 70 percent of the sea level rise impacts as captured by the SEALEVEL
sub-scenario.
INCTOUR: This sub-scenario assumes global cooperation, that all countries implement their
NDCs, and that these NDCs are effective in mitigating and adapting to climate change impacts
on temperature and its effect on foreign tourism demand. Measures implemented in this sub-
scenario were assumed to be effective in offsetting climate change impacts on tourism by 70
percent. Data was not available to support the investments required to adapt to climate change
impacts on tourism , so the impacts of this scenario should not be considered in isolation.
Instead, its relevance is its contribution to the overall POLICY scenario.
AFFOR: This sub-scenario simulates the provisions in the National Development Strategy for
planting of 1,806,400 ha of forest plantations (Kingdom of Thailand, 2019; Ministry of Natural
Resources and Environment, 2019). To meet the target area by 2037, 129,029 ha per year are
planted, with all of these newly planted forests (100 percent) used for commercial forestry
purposes. The cost of afforestation, including establishment and early maintenance costs, was
estimated as $200/ha and was based on the Thai government budget for similar activities in
the past. It is assumed that the trees planted are harvestable by year 10 and reach maximum
carbon storage at 18 years of age.
RESTORE: This sub-scenario simulates the provisions in the National Development Strategy
for restoring and increasing the area of natural forests by 2,558,400 ha (Kingdom of Thailand,
2019; Ministry of Natural Resources and Environment, 2019). To meet the target area by 2037,
182,743 ha per year would be planted. Twenty percent of these newly planted forests will be
used for commercial forestry purposes. The cost of restoration is assumed to be half that of
afforestation and thus equal to $100/ha. It is assumed that the trees planted are harvestable by
year 10 and reach maximum carbon storage at 15 years of age.
REDERODE: This sub-scenario simulates the impact of forest restoration and eliminating
deforestation and afforestation (RESTORE, REDEFOR, and AFFOR, respectively) on erosion
mitigation ES.
REDPOLLEN: This sub-scenario simulates the impact of forest restoration and eliminating
deforestation and afforestation (RESTORE, REDEFOR, and AFFOR, respectively) on crop
pollination ES.
Note that RCP4.5 and RCP 8.5 pathways were used in the estimation of the damage functions for
the following sub-scenarios: REDFLOOD, REDCLIMATE_AGRI, RELABPROD, REDSEALEVEL,
INCTOUR, and POLICY. The names of the scenarios that use the RCP4.5 projections terminate
with _OPT and the names of the scenarios that use the RCP8.5 projections terminate with _PES+.
94 Towards a Green and Resilient Thailand
SUPPLEMENTARY INFORMATION SECTION 3
Detailed IEEM+ESM Results
Table SI3. Macroeconomic results in millions of USD
DEFOR
DEFOR2
FLOOD_OPT
FLOOD_PES
CATFLOOD
CLIMATE_AGRI_OPT
CLIMATE_AGRI_PES
CLIMATE_AGRI_PES+
LABPROD_OPT
LABPROD_PES
LABPROD_PES+
GDP -209 428 102 -525 -34,901 -1,382 -4,123 -7,872 37 -572 -1,152
Cumulative GDP -952 2,027 1,444 -5,654 -412,791 -15,352 -49,121 -90,807 1,272 -6,506 -13,096
Wealth -396 -946 19 -92 -6,085 994 1,588 1,305 6 -126 -254
Cumulative wealth -5,647 -19,317 247 -958 -70,407 16,708 26,886 22,893 264 -1,505 -3,029
Private consumption 3 -11 75 -387 -25,914 -1,407 -4,381 -8,933 34 -352 -709
Private investment -221 453 33 -171 -11,368 91 322 955 5 -254 -511
Exports -447 913 95 -493 -32,682 -1,808 -3,631 -4,218 32 -483 -973
Imports -412 843 89 -463 -30,749 922 1,330 1,043 29 -447 -900
Source: IEEM+ESM results.
Table SI4. Macroeconomic results in millions of USD, continued
SEALEVEL_OPT
SEALEVEL_PES
SEALEVEL_PES+
TOUR_OPT
TOUR_PES
TOUR_PES+
ERODE_PES
ERODE_PES+
POLLEN_PES
POLLEN_PES+
DEGRADE_OPT
DEGRADE_PES
DEGRADE_PES+
GDP 0 -613 -1,225 -280 -463 -900 -46 -759 -102 -551 -36,442 -41,864 -46,878
Cumulative GDP 0 -9,818 -19,657 -588 -1,911 -3,783 -712 -9,871 -906 -7,508 -423,101 -483,895 -553,708
Wealth 0 -38 -73 2 -31 -72 -3 -52 -8 -37 -6,564 -8,414 -6,888
Cumulative wealth 0 -808 -1,598 1,140 1,220 2,166 -58 -822 -77 -627 -75,420 -102,743 -80,530
Private consumption 0 -762 -1,533 -300 -460 -845 -57 -920 -119 -671 -27,392 -32,177 -39,652
Private investment 0 141 288 -648 -829 -1,634 11 149 15 111 -11,999 -12,907 -11,287
Exports 0 -17 -27 -1,041 -1,389 -2,797 -1 -61 -15 -40 -34,314 -37,822 -37,279
Imports 0 27 61 -1,426 -1,833 -3,596 2 -9 -9 -1 -32,551 -35,670 -35,136
Source: IEEM+ESM results.
Supplementary Information Section 3 95
Table SI5. Macroeconomic results in millions of USD, continued
NODEFOR
REDFLOOD_OPT
REDFLOOD_PES
REDCLIMATE_
AGRI_OPT
REDCLIMATE_
AGRI_PES
REDCLIMATE_
AGRI_PES+
REDSEALEVEL_OPT
REDSEALEVEL_PES
REDSEALEVEL_PES+
GDP 44 -7,464 -10,655 -341 -1,101 -2,208 195 -39 -223
Cumulative GDP -292 -80,425 -131,328 -3,239 -12,249 -24,557 2,678 -1,179 -4,123
Wealth 677 -1,991 2,602 -26 -101 -199 348 533 522
Cumulative wealth 7,770 -24,680 50,434 -243 -1,277 -2,535 5,640 8,591 8,347
Private consumption -113 -5,263 -7,349 -403 -1,260 -2,543 219 -24 -252
Private investment 156 -2,580 -3,594 56 138 286 38 60 102
Exports 277 -23,013 -19,710 -43 -216 -422 -2,053 -2,330 -2,336
Imports 253 -4,149 -3,837 -20 -136 -262 844 1,020 1,028
Source: IEEM+ESM results.
Table SI6. Macroeconomic results in millions of USD, continued
INCTOUR_OPT
INCTOUR_PES
INCTOUR_PES+
AFFOR
RESTORE
REDERODE_PES
REDPOLLEN_PES
POLICY_OPT
POLICY_PES
POLICY_PES+
GDP -85 -142 -281 223 58 29 1,011 -7,658 -11,486 -14,548
Cumulative GDP -176 -579 -1,153 12,111 3,757 285 17,749 -80,056 -134,175 -174,902
Wealth 1 -8 -17 106 42 2 64 -1,649 2,977 2,669
Cumulative wealth 357 395 765 4,711 1,667 24 1,507 -18,238 58,666 54,490
Private consumption -95 -146 -285 -374 -131 34 1,251 -5,515 -7,857 -11,143
Private investment -196 -251 -500 410 138 -4 -235 -2,674 -4,155 -4,217
Exports -311 -415 -831 -433 -151 4 20 -25,383 -23,140 -24,324
Imports -432 -558 -1,109 -364 -126 2 -54 -3,721 -4,024 -5,129
Source: IEEM+ESM results.
96 Towards a Green and Resilient Thailand
Table SI7. Macroeconomic results expressed as average growth rates over simulation period as
percentage point difference from the baseline
INCTOUR_OPT INCTOUR_PES INCTOUR_PES+ AFFOR
GDP -85 -142 -281 223
GDP in 2050 with respect to BASE -176 -579 -1,153 12,111
Wealth 1 -8 -17 106
Wealth in 2050 with respect to BASE 357 395 765 4,711
Private consumption -95 -146 -285 -374
Private investment -196 -251 -500 410
Exports -311 -415 -831 -433
Imports -432 -558 -1,109 -364
Source: IEEM+ESM results.
Supplementary Information Section 3 97
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