Climate Change and Adaptation for Food Sustainability: Implications and Scenarios from Malaysia 3030853748, 9783030853747

Table of contents :
Preface
Contents
Abbreviations
Chapter 1: Introduction
1.1 Introduction
1.2 Problem Statement
1.3 Research Goals
1.4 Current Climate Change Scenario in Malaysia
1.5 Significance of Study
1.6 Limitations
1.7 Conclusion
1.8 Book Organization
References
Chapter 2: Recent Research on Climate Change and Food Security
2.1 Introduction
2.1.1 Climate Variability and Climate Change
2.1.2 Declining Food Sector
2.2 Asian Development Bank Observations of Climate Change in Agriculture in Southeast Asia
2.2.1 Dynamics of Food Security under a Changing Climate
2.2.2 Food Security and Climate Change: A Conceptual Framework
2.2.3 Contribution of Food Sector to Malaysian GDP
2.3 Potential Impacts of Climate Change on Food Security in Malaysia
2.4 Climate Change and Self-Sufficiency Level in Rice Production in Malaysia
2.5 Food Security Policy in Malaysia
2.6 Food Security and Responses to Climate Change
2.7 Exploring Development Paths: Institutions and Collective Behavior
2.8 Empirical Literature on the Impact of Climate Change
2.9 Relevant Literature Based on National and International Perspectives
2.10 Models to Assess Impact of Climate Change
2.10.1 Partial Equilibrium Models
2.10.2 Crop Simulation Models
2.10.3 Agro-Ecological Zone Models
2.10.4 Ricardian Models
2.11 Adaptation Policy for Food Security
2.11.1 Levels and Approaches of Adaptation for Malaysia
2.11.2 Government Policies, Challenges, and Actions for Food Security at National Level
2.11.3 Food Policy Measures and Challenges at International Level
2.12 Literature Gap to Study Impacts of Climate Change on Food Security
2.13 Contribution to Literature on Malaysian Perspectives
References
Chapter 3: Assessment of Climate Change and Adaptation Policies for Sustainable Food Security
3.1 Introduction
3.2 Hypothetical Construction of Study
3.3 General Equilibrium Theory
3.4 Conceptual Framework of Study
3.4.1 Data Sources
3.4.2 Study Area
3.4.3 Empirical Economizing Adoption
3.5 Study of Different Levels of Adaptation Options for Climate Change
3.6 Description of Simulations
3.7 Basics of CGE Model
3.8 Pros and Cons of Basic Model
3.9 Social Accounting Matrix
3.9.1 SAM Market Closure
3.9.2 Market Clearance Condition
3.9.3 Normal Profit Condition
3.9.4 Factor Market Balance
3.10 Balancing a SAM
3.10.1 CGE Model for Malaysian Economy
3.10.2 Basic Structure of Model
3.10.3 Prices
3.10.4 Production
3.10.5 Domestic Demand
3.11 Mathematical Statement and Specification of MICE Model
3.11.1 Price Block
3.11.2 Import Price
3.11.3 Export Price
3.11.4 Composite Goods Price
3.11.5 Domestic Output Price
3.11.6 Activity Price
3.11.7 Value-Added Price
3.11.8 Consumer Price Index
3.12 Producer Price Index for Nontraded Market Output
3.13 Production and Commodity Block Equations
3.14 Factor Income
3.14.1 Household Income
3.14.2 Household Consumption Demand
3.14.3 Investment Demand
3.14.4 Government Revenue
3.14.5 Government Expenditure
3.15 System Constraints Block
3.15.1 Factor Markets
3.15.2 Composite Commodity Markets
3.15.3 Current-Account Balance for ROW (in Foreign Currency)
3.15.4 Savings-Investment Balance
3.16 Price Normalization
3.16.1 Climate Change Block
3.17 Calibrating the CGE Model
3.17.1 Performing Scenario Simulations within CGE Model
3.18 Conclusion
References
Chapter 4: Food Security Challenges of Climate Change: An Analysis for Policy Selection in Malaysia
4.1 Introduction
4.1.1 Policy Scenarios
4.2 Baseline Scenario (BS)
4.3 Estimated Food Sustainability with No Adaption (EFSNA)
4.4 Estimated Food Sustainability with Adaption (EFSA)
4.4.1 Description of Simulations
4.5 Analysis of Different Scenarios
4.5.1 Different Levels of Damage from Climate Change
4.5.2 Costs of Different Adaptation Options
4.5.3 Effect of Climate Change in Government Spending
4.6 Impact of Climate Change on Food Sustainability over Time
4.6.1 Effects of Adaptation Strategies to RGDP
References
Chapter 5: Policy Implications for Climate Change Adaptation in Malaysia
5.1 Introduction
5.2 Suitable Adaptation Policy for Food Sustainability
5.3 Macroeconomic Effects of Climate Change
5.4 Predicted Implications of Adaptation Options for Food Sustainability
5.5 Adaptation Action and Policy Issues for Malaysia
5.6 Summary
References
Chapter 6: Climate Change Adaptation Policy Recommendation for Food Security in Malaysia
6.1 Introduction
6.2 Summary of Findings
6.2.1 Different Levels of Adaptation Action
6.2.2 Adaptation Policy Costs and Benefits
6.2.3 Impacts of Climate Change for Adaptation Option
6.3 Capacity-Building Options and Gaps in Local Policy Community
6.4 Policy Suggestions
6.5 Contribution
6.6 Suggestions for Future Research
6.7 Limitations
Appendix
Climatic Equations
Standard Model Equations That All Are Considered Over Time (t)
List of Parameters
Sets
List of Variables

Citation preview

Ferdous Ahmed Abul Quasem Al-Amin Zeeda Fatimah Mohamad

Climate Change and Adaptation for Food Sustainability Implications and Scenarios from Malaysia

Climate Change and Adaptation for Food Sustainability

Ferdous Ahmed • Abul Quasem Al-Amin  Zeeda Fatimah Mohamad

Climate Change and Adaptation for Food Sustainability Implications and Scenarios from Malaysia

Ferdous Ahmed IUBAT-Institute of SDG Studies (IISS) International University of Business Agriculture and Technology (IUBAT) Dhaka, Bangladesh

Abul Quasem Al-Amin Geography and Environmental Management University of Waterloo Waterloo, ON, Canada

Zeeda Fatimah Mohamad Department of Science & Technology Studies University of Malaya (UM) Kuala Lumpur, Selangor, Malaysia

ISBN 978-3-030-85374-7    ISBN 978-3-030-85375-4 (eBook) https://doi.org/10.1007/978-3-030-85375-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The main focus of this book is adaptation modeling of climate change with the aim of guaranteeing sustainable food security. Many concerns have been raised in connection with the gradual effects of climate change, and these directly impact the agricultural sector and result in yearly increases in global crop damage. As a consequence, many countries are losing their capacity for self-sufficiency and food security. In particular, this book highlights the Malaysian perspective and considers ways in which food sustainability could be secured for the next 50 years by applying CGE modeling. This model clearly indicates that adaptation modeling is applicable to combating climate change to reduce crop damage in Malaysia. Although the book concentrates on Malaysia, the applications discussed may be suitable for other developing countries facing the prospect of the same level of crop damage due to climate change or countries wishing to use the research for the aim of achieving improved food security. The book’s target audience is university students, academics, researchers, industry, nongovernmental organizations, national and international policy makers, and others, who, it is hoped, will regard the work as a reference and apply its contents, even if on a small scale, to reducing the negative impacts of climate change on the global food sector. Lastly, we will be happy if this book contributes, even in some small way, to combating climate change and improving future global food security. Dhaka, Bangladesh Waterloo, ON, Canada Kuala Lumpur, Malaysia

Ferdous Ahmed Abul Quasem Al-Amin Zeeda Fatimah Mohamad

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Contents

1 Introduction����������������������������������������������������������������������������������������������    1 1.1 Introduction��������������������������������������������������������������������������������������    2 1.2 Problem Statement����������������������������������������������������������������������������    3 1.3 Research Goals����������������������������������������������������������������������������������    7 1.4 Current Climate Change Scenario in Malaysia��������������������������������    7 1.5 Significance of Study������������������������������������������������������������������������    9 1.6 Limitations����������������������������������������������������������������������������������������    9 1.7 Conclusion����������������������������������������������������������������������������������������    9 1.8 Book Organization����������������������������������������������������������������������������   10 References��������������������������������������������������������������������������������������������������   10 2 Recent Research on Climate Change and Food Security ��������������������   13 2.1 Introduction��������������������������������������������������������������������������������������   14 2.1.1 Climate Variability and Climate Change������������������������������   14 2.1.2 Declining Food Sector����������������������������������������������������������   15 2.2 Asian Development Bank Observations of Climate Change in Agriculture in Southeast Asia ������������������������������������������������������   15 2.2.1 Dynamics of Food Security under a Changing Climate ������   16 2.2.2 Food Security and Climate Change: A Conceptual Framework����������������������������������������������������������������������������   19 2.2.3 Contribution of Food Sector to Malaysian GDP������������������   21 2.3 Potential Impacts of Climate Change on Food Security in Malaysia����������������������������������������������������������������������������������������   23 2.4 Climate Change and Self-Sufficiency Level in Rice Production in Malaysia ��������������������������������������������������������������������   27 2.5 Food Security Policy in Malaysia ����������������������������������������������������   28 2.6 Food Security and Responses to Climate Change����������������������������   29 2.7 Exploring Development Paths: Institutions and Collective Behavior��������������������������������������������������������������������������   31 2.8 Empirical Literature on the Impact of Climate Change��������������������   32

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2.9 Relevant Literature Based on National and International Perspectives��������������������������������������������������������������������������������������   36 2.10 Models to Assess Impact of Climate Change ����������������������������������   41 2.10.1 Partial Equilibrium Models��������������������������������������������������   42 2.10.2 Crop Simulation Models������������������������������������������������������   42 2.10.3 Agro-Ecological Zone Models����������������������������������������������   42 2.10.4 Ricardian Models������������������������������������������������������������������   43 2.11 Adaptation Policy for Food Security������������������������������������������������   44 2.11.1 Levels and Approaches of Adaptation for Malaysia ������������   44 2.11.2 Government Policies, Challenges, and Actions for Food Security at National Level��������������������������������������   47 2.11.3 Food Policy Measures and Challenges at International Level��������������������������������������������������������������������������������������   49 2.12 Literature Gap to Study Impacts of Climate Change on Food Security ������������������������������������������������������������������������������   51 2.13 Contribution to Literature on Malaysian Perspectives����������������������   52 References��������������������������������������������������������������������������������������������������   52 3 Assessment of Climate Change and Adaptation Policies for Sustainable Food Security ����������������������������������������������������������������   63 3.1 Introduction��������������������������������������������������������������������������������������   63 3.2 Hypothetical Construction of Study��������������������������������������������������   64 3.3 General Equilibrium Theory ������������������������������������������������������������   66 3.4 Conceptual Framework of Study������������������������������������������������������   67 3.4.1 Data Sources ������������������������������������������������������������������������   68 3.4.2 Study Area����������������������������������������������������������������������������   68 3.4.3 Empirical Economizing Adoption����������������������������������������   69 3.5 Study of Different Levels of Adaptation Options for Climate Change ��������������������������������������������������������������������������   72 3.6 Description of Simulations ��������������������������������������������������������������   74 3.7 Basics of CGE Model ����������������������������������������������������������������������   74 3.8 Pros and Cons of Basic Model����������������������������������������������������������   76 3.9 Social Accounting Matrix ����������������������������������������������������������������   76 3.9.1 SAM Market Closure������������������������������������������������������������   82 3.9.2 Market Clearance Condition ������������������������������������������������   82 3.9.3 Normal Profit Condition ������������������������������������������������������   83 3.9.4 Factor Market Balance����������������������������������������������������������   83 3.10 Balancing a SAM������������������������������������������������������������������������������   84 3.10.1 CGE Model for Malaysian Economy ����������������������������������   85 3.10.2 Basic Structure of Model������������������������������������������������������   86 3.10.3 Prices������������������������������������������������������������������������������������   86 3.10.4 Production ����������������������������������������������������������������������������   86 3.10.5 Domestic Demand����������������������������������������������������������������   87

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3.11 Mathematical Statement and Specification of MICE Model������������   89 3.11.1 Price Block����������������������������������������������������������������������������   90 3.11.2 Import Price��������������������������������������������������������������������������   90 3.11.3 Export Price��������������������������������������������������������������������������   91 3.11.4 Composite Goods Price��������������������������������������������������������   91 3.11.5 Domestic Output Price����������������������������������������������������������   92 3.11.6 Activity Price������������������������������������������������������������������������   92 3.11.7 Value-Added Price����������������������������������������������������������������   93 3.11.8 Consumer Price Index����������������������������������������������������������   93 3.12 Producer Price Index for Nontraded Market Output������������������������   93 3.13 Production and Commodity Block Equations����������������������������������   94 3.14 Factor Income ����������������������������������������������������������������������������������   94 3.14.1 Household Income����������������������������������������������������������������   94 3.14.2 Household Consumption Demand����������������������������������������   95 3.14.3 Investment Demand��������������������������������������������������������������   95 3.14.4 Government Revenue������������������������������������������������������������   95 3.14.5 Government Expenditure������������������������������������������������������   96 3.15 System Constraints Block ����������������������������������������������������������������   96 3.15.1 Factor Markets����������������������������������������������������������������������   96 3.15.2 Composite Commodity Markets ������������������������������������������   96 3.15.3 Current-Account Balance for ROW (in Foreign Currency)�����������������������������������������������������������   97 3.15.4 Savings-Investment Balance ������������������������������������������������   97 3.16 Price Normalization��������������������������������������������������������������������������   98 3.16.1 Climate Change Block����������������������������������������������������������   98 3.17 Calibrating the CGE Model��������������������������������������������������������������  100 3.17.1 Performing Scenario Simulations within CGE Model���������  101 3.18 Conclusion����������������������������������������������������������������������������������������  101 References��������������������������������������������������������������������������������������������������  102 4 Food Security Challenges of Climate Change: An Analysis for Policy Selection in Malaysia��������������������������������������������������������������  105 4.1 Introduction��������������������������������������������������������������������������������������  105 4.1.1 Policy Scenarios��������������������������������������������������������������������  106 4.2 Baseline Scenario (BS) ��������������������������������������������������������������������  107 4.3 Estimated Food Sustainability with No Adaption (EFSNA)������������  107 4.4 Estimated Food Sustainability with Adaption (EFSA) ��������������������  108 4.4.1 Description of Simulations ��������������������������������������������������  108 4.5 Analysis of Different Scenarios��������������������������������������������������������  108 4.5.1 Different Levels of Damage from Climate Change��������������  108 4.5.2 Costs of Different Adaptation Options ��������������������������������  110 4.5.3 Effect of Climate Change in Government Spending������������  112 4.6 Impact of Climate Change on Food Sustainability over Time����������  113 4.6.1 Effects of Adaptation Strategies to RGDP����������������������������  116 References��������������������������������������������������������������������������������������������������  118

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5 Policy Implications for Climate Change Adaptation in Malaysia ������  119 5.1 Introduction��������������������������������������������������������������������������������������  119 5.2 Suitable Adaptation Policy for Food Sustainability��������������������������  121 5.3 Macroeconomic Effects of Climate Change ������������������������������������  122 5.4 Predicted Implications of Adaptation Options for Food Sustainability������������������������������������������������������������������������������������  125 5.5 Adaptation Action and Policy Issues for Malaysia ��������������������������  129 5.6 Summary ������������������������������������������������������������������������������������������  130 References��������������������������������������������������������������������������������������������������  130 6 Climate Change Adaptation Policy Recommendation for Food Security in Malaysia����������������������������������������������������������������  133 6.1 Introduction��������������������������������������������������������������������������������������  134 6.2 Summary of Findings������������������������������������������������������������������������  134 6.2.1 Different Levels of Adaptation Action����������������������������������  134 6.2.2 Adaptation Policy Costs and Benefits����������������������������������  134 6.2.3 Impacts of Climate Change for Adaptation Option��������������  135 6.3 Capacity-Building Options and Gaps in Local Policy Community����������������������������������������������������������������������������  137 6.4 Policy Suggestions����������������������������������������������������������������������������  138 6.5 Contribution��������������������������������������������������������������������������������������  141 6.6 Suggestions for Future Research������������������������������������������������������  141 6.7 Limitations����������������������������������������������������������������������������������������  142 Appendix ����������������������������������������������������������������������������������������������������������  143 List of Parameters��������������������������������������������������������������������������������������������  149 List of Variables������������������������������������������������������������������������������������������������  151

Abbreviations

ADB ADPC ADDICE

Asian Development Bank Adaptation Policy Cost Adaptation Dynamic Integrated Model of Climate and the Economy (DICE) ADRICE Adaptation Regional Integrated Climate and Economy AD-WITCH Adaptation-World Induced Technical Change Hybrid Model AEZ Agro-ecological zone AL* Adaptation Level AOGCMs Atmosphere-Ocean General Circulation Models AR4 IPCC’s Fourth Assessment Report of Climate Change AR5 IPCC’s Fifth Assessment Report of Climate Change ASM Integrated Assessment of Climate Change Impact BS Baseline scenario BMRC The Centre for Australian Weather and Climate Research CCC Climate Change Capital CCM Capital Composition Matrix CCFS Climate Change and Food Security Framework CDM Clean Development Mechanism CES Constant Elasticity of Substitution CGE Computable General Equilibrium CGM2 Climate Change Model, version 2 CO2 Carbon Dioxide COP Conference of Parties CGE Computable General Equilibrium DART Dynamic Applied Regional Trade DCU Domestic Currency Unit DICE Dynamic Integrated Climate and Economy DOSM Department of Statistics, Malaysia DSSAT Decision Support System for Agro-technology Transfer EFSA Estimated Food Sustainability with Adaption EFSNA Estimated Food Sustainability with No Adaption xi

xii

Abbreviations

EPU Economic Planning Unit EXR Exchange Rate ESCAP Economic and Social Commission for Asia and the Pacific FAO Food and Agriculture Organization GAMS General Algebraic Modeling System GD Gross Damage GDP Gross Domestic Product GEDL Geophysical Fluid Dynamics Laboratory GCM Global Climate Model GEM Global Environmental Multi-scale Model GHG Greenhouse Gas GISS Goddard Institute for Space Studies GFDLC Geophysical Fluid Dynamics Laboratory Coupled Model GTAP Global Trade Analysis Project GVA Global Vulnerability Assessment HadCM3 Hadley Centre Coupled Model, version 3 HEIS Household Income and Expenditure Survey HTM Hamburg Tourism Model (HTM) IAMS Integrated Assessment Models IAASTD International Assessment of Agricultural Knowledge, Science and Technology for Development ICES Inter-temporal Computable Equilibrium System IFAD International Fund for Agricultural Research IFPRI International Food Policy Research Institute IGEM Inter-temporal General Equilibrium Model IIASA International Institute for Applied Systems Analysis ILO International Labor Organization IMPACT Integrated Impact Assessment Model of Climate Change IPCC Intergovernmental Panel on Climate Change IRRI International Rice Research Institute LDCs Least Developed Countries LFS Labor Force Survey MADA Muda Agricultural Development Authority MCE Malaysian Climate and Economy MCM Million Cubic Meter MINK Missouri-Iowa-Nebraska-Kansas MIT EPPA Emission Prediction and Policy Analysis MMD Malaysian Meteorological Department MARDI Malaysian Agricultural Research and Development Institute MOA Ministry of Agriculture and Agro-Based Industry Malaysia MoSTE Ministry of Science, Technology and the Environment MPCC Malaysian National Policy on Climate Change NAHRIM National Hydraulic Research Institute of Malaysia NAP Malaysia National Agro-food Policy NP3 Third National Agricultural Policy

Abbreviations

NC2 NKEAs NGOs ODA OECD PAGE PANE PCM PPM RAS REDD RD R&D RM RGDP RICE SM SRES TGR UKMO UNDP UNEP UNFCCC USA USD WGII WMO

xiii

Malaysia’s Second National Communication National Key economic Areas Non-government Organizations Agriculture’s Share in Official Development Assistance Organization for Economic Co-operation and Development Policy Analysis is for the Greenhouse Effect Poverty Action Network of Civil Society Organizations in Ethiopia Parallel Climate Model Parts Per Million Review of Agrarian Studies Reduction of Emissions from Deforestation and Forest Degradation Residual Damage Research and Development Malaysian Ringgit Real Gross Domestic Product Regional Integrated Climate and Economy Southwest Monsoon Special Report on Emission Scenarios The Green Revolution UK Dispersion Modeling Bureau United Nations Development Program United Nations Environment Program United Nations Framework Convention on Climate Change United States of America United States Dollar World Group II World Meteorological Organization

Chapter 1

Introduction

Abstract  Almost all countries of the world are experiencing the effects of climate change. Studies by the United Nations Framework Convention on Climate Change (UNFCCC) and the Intergovernmental Panel on Climate Change (IPCC) have established that climate change is no longer a regional problem but a global one. The enormous carbon footprint caused by burning large amounts of fossil fuels is mainly responsible for global warming and climate change. The unforeseen changes resulting from changing climatic patterns are severely impacting global food security. As a result of these changes, many parts of the world, like Asia, Africa, the Caribbean, and Latin America, are suffering from severe reductions in food production. In particular, in recent years, Southeast Asian or ASEAN countries have also experienced crop damage or loss of crop production due to climate change impacts. Some prominent studies have predicted that 10% to 30% of crops may suffer damage due to a 1 °C temperature increase by 2030. Malaysia also faces some common issues related to climate change, particularly extreme temperature and uneven flooding. Among the different scientific demands, because of the seriousness of climate change, it calls for an urgent response. Methodologically, it is established that climate change affects most countries in the world. There are two approaches to combating the effects of climate change: climate change adaptation and climate change mitigation. Therefore, the research goal of this chapter is to propose climate change adaptation policies applying Computable General Equilibrium (CGE) modeling for 50-year-scenario projections. This CGE model estimates scenario adaptation costs for the food sector based on economic trade-offs between climate change and its impacts. It also identifies suitable adaptation policy options to support a sustainable future for climate change adaptation strategies. However, these climate change adaptation scenarios will determine the capacity building options to support the overall adaptation policies in Malaysia. Although this CGE model has been calibrated specifically for the climate change adaptation scenarios of Malaysia, the scenario studies can serve as guidelines for other countries with similar levels of climate-­change-­related issues and socioeconomic conditions.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_1

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2

1 Introduction

1.1  Introduction The effects of climate change represent one of the most challenging issues facing all countries. The most common phenomenon of climate change patterns are uneven rainfall (flooding in some areas, elsewhere drought), rising temperatures, and irregular and extreme weather (e.g., cyclones, tornadoes, changing tides), which cause negatively affect the food sector1 (Porter et al., 2014). There is no doubt that climate change is a vital issue, but science can play an important role in determining various policy responses at government and international policymaker levels to reduce its effects. The climate change dilemma is now real, and most countries are vulnerable to its impacts, especially developing countries due to their limited adaptation capacity. Climate change is rapidly unfolding and becoming a very serious global issue (Godfray et al., 2010). Carbon emission augments the absorption of carbon dioxide and greenhouse gases, which increase the uneven temperature distribution what causes global warming. The global community is very preoccupied with the gradual, foreseen impacts of climate change and current trends in extreme weather that could affect global food security (Kurukulasuriya & Rosenthal, 2013). The developed world, like the USA, Europe, and Japan, is very concerned with climate change and is adopting measures to either mitigate or adapt to it. But countries of the developing world, like Malaysia, and their citizens still know very little about global public opinion or anthropogenic behavior and its relation to climate change because only a few national surveys have addressed the issue (Leiserowitz et  al., 2005; Brechin et al., 2003). The majority of people around the world believe anthropogenic activity is the single most important cause of climate change, but some still argue that global warming and ozone layer depletion are just as important (Cook et al., 2013). However, each Conference of the Parties (COP)2 of the UNFCCC has a special focus on agriculture and food security,3 which can be addressed through adaptation measures in most developing countries to address climate change 1  The food sector is almost entirely under private ownership. In this study there are 14 agricultural food sectors which are derived from the Input-output table-2005 of Malaysia. However paddy, food crops, vegetable, fruits, oil palm, flower plants, other agriculture, poultry farming, other livestock, fishing are the director food sector. But rubber and forestry are the indirect food sector. 2  The COP is the supreme decision-making body of the UNFCCC. All states that are parties to the convention are represented at the COP, where they review the implementation of the convention and any other legal instruments that the COP adopts and take decisions necessary to promote the effective implementation of the convention, including institutional and administrative arrangements. The COP21, the Conference of the Parties was held Nov 30, 2015 – Dec 12, 2015 in Paris. These COP conferences are organized by the UNFCCC every year. 3  Food security is a complex sustainable development issue linked to health through malnutrition, but also to sustainable economic development, the environment, and trade. It can also be defined as the “availability at all times of adequate world food supplies of basic foodstuffs to sustain a steady expansion of food consumption and to offset fluctuations in production and prices.” Because most of the food sector is derived from agriculture, there is a vital relationship among food security, the food sector, and agriculture. Moreover, Malaysia’s population is rising, which intensifies demand for food.

1.2  Problem Statement

3

impacts. Against this background, this study introduces some ideas and concepts regarding the challenges of using policies as tools for achieving long-term solutions to the problem of climate change and to examine some of the technical foundations for appropriate adaptation measures. The study outcomes are quite new in the development of the food sector and food sustainability4 with respect to the long-term vision of Malaysia. The findings from this study can be used by Malaysian policymakers to develop operational tools for dealing with climate change impacts and with similar economic and ecological conditions. Although this this study focused on Malaysian policy and perspectives, it can also be relevant and applicable to developing countries with similar levels of food security issue due to climate change impacts.

1.2  Problem Statement Climate change is globally revealed by rising temperature, uneven precipitation, and irregular wind patterns, which lead to extreme weather events and impacts. Most provinces in Malaysia are also facing the effects of climate change in extreme floods, rising temperatures, and changes in rainfall patterns. The scientific evidence on climate change being a significant problem is now overwhelming and demands an urgent response. Scientifically, it is clear that changing climate patterns often adversely affect many countries across the world. A large number of works have recently made reference to the subject, including well-known publications by Lobell et al. (2007, 2011), Rowhani (2011), Georgescu et al. (2011), Ahmed et al. (2011), Burke et al. (2009, 2010), Hertel et al. (2010), Bonfils et al. (2008), Cahill et al. (2007), and IPCC (2007a). Agriculture is the major concern since climatic effects are directly related to climate change. Almost double the level of crop production will be required to meet the projected growth of the human population and per capita food demand. Therefore, an efficient growth of food production must be continued further, but changes in climatic conditions are giving rise to unfavorable conditions for sustainable crop production (Easterling et al., 2007; Tubiello et al., 2007). Moreover, agriculture is a main economic and ecological factor that provides a wide range of food production. In fact, food production is extremely sensitive to variations in climate both in forms and locations based on ecosystem services (IPCC, 2007b). Due to the interruption of the El Nino Southern Oscillation phenomenon there is domination on the overall inter-annual inconsistency of production with its associated cycles of droughts and flooding events. Therefore, it causes between a 15% and 35% global yield variation in rice, wheat, oilseeds, and coarse grains, and this current sensitivity explains why climate change has consequences for agriculture (Lobell et al., 2014;

4  A truly sustainable food system is one that nurtures people, animals, land, communities, and the environment. In this study “food sustainability” is used to denote food production value.

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1 Introduction

Pooniya et al., 2015; Rowhani et al. 2011). Hence, it has become critical to identify and evaluate options for adapting to climate change in the coming decades, particularly in developing countries (Adger et  al., 2007).5 Moreover, because climate change has a direct impact on agriculture, the food sector is vulnerable to climate change. As a result, food security also becomes an issue. Therefore, from a national and international perspective, policymakers and environmentalists alike are looking for appropriate mechanisms to tackle these issues and operational tools for dealing with climate change impacts. Detailed analyses of long-term adaptation techniques, technical foundations, institutions, and operational barriers center on integrating the various climate change concerns. However, appropriate long-term adaptation modeling and frameworks aiming to resolve climate change disputes are fundamentally lacking, though evidence suggests the impact of climate change is increasing (Lobell & Gourdji, 2012). Therefore, the fundamental question is: What remains to be done? Are current adaptive policies sufficient? These fundamental questions are posed and addressed here from a Malaysian perspective, within the sustainable food sector in particular. It is already evidenced that most of the developing countries are turning into indefensible prototypic climate model due to the challenge of global climate change. However, both natural and human systems are affected by the impacts of climate change, which causes economic damage turning into a unstable foundations of policies for food sector. The extent and character of the climatic alteration that may be necessary enough to response for emerging knowledge practice. But climate change has necessitated a shift in policy agendas and constrained development at unprecedented rates (Lorenzoni & Pidgeon, 2006; Raddatz et al., 2007). The climate of Malaysia is characterized by uniform temperatures, high humidity, and copious rainfall (Toriman et al., 2014). Because Malaysia is located in the equatorial zone, it is extremely rare to see whole days of clear skies, even during periods of severe drought. In addition, it is rare to go several days without seeing the sun, except during the northeast monsoon season. A study of several regions’ annual mean temperature recorded in different parts of Malaysia indicated increasing warming trends (Paterson et al., 2013). A correlation analysis of annual mean temperatures makes it clear that the country’s lowland regions have the major trend over Southern and Central Peninsular Malaysia, whereas the lowest trend is found in the state of Sarawak. The rate of increase is about 1.5–2.7  °C in the last 100  years (Paterson, 2013). Though there is a lack of large-scale climate data, there are indications that the local warming trend may be due to the urbanization practices as in Southern and Central Peninsular Malaysia (Shaw et al., 2010). Southeast Asia shows a composite range of topographies and land–sea differences. The temperature has increased from around 0.14–0.20 °C per decade since the 1960s across the regions (Tangang et al., 2007). A trend toward warmer daytime 5  Here we use the term adaptation to include the actions of adjusting practices, processes, and capital in response to the actuality or threat of climate change, as well as responses in the decision environment, such as changes in social and institutional structures or altered technical options that can affect the potential or capacity for these actions to be carried out (Adger et al., 2007).

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1.2  Problem Statement

temperatures and cooler nighttime temperatures has also been observed (Manton et  al., 2001; Gosling et  al., 2011). However, different positive rainfall trends are observed, from heavy (top 10%) to light (bottom 5%) rainfall events, as well as a negative precipitation trend (moderate, 25–75%) (Lau & Wu, 2007). On the other hand, yearly total wet-day precipitation has increased by 22 mm per decade, whereas precipitation from extreme rainy days increased by 10 mm per decade (Alexander et al., 2006; Gosling et al., 2011). For a given region, strong seasonality changes have also been observed. In Peninsular Malaya during the southwest monsoon period, total precipitation and the occurrence of rainy days declined, but rainfall intensity increased in much of that region (Deni et  al., 2010). However, during northeast downpours, total precipitation, the occurrence of extreme rainfall, and precipitation intensity all rose in the peninsular regions (Suhaila et  al., 2010) (Table 1.1). Malaysia is among the countries experiencing a warming trend over the past few decades. According to the IPCC, in 2001, global land precipitation increased about 2% over levels in the early twentieth century. In addition, in 2007, extremely hot temperatures, heat waves, and heavy precipitation events became more frequent. In the past few years, the frequency of long dry periods showed a growing trend, with a significant increase in the mean and variance of the length of the dry spells. All wetness indices in these areas show a decreasing trend. Increasing temperature with long dry periods would give a variable result in terms of weather and climate (Deni et  al., 2010). According to the Malaysian Meteorological Department (MMD, 2009), Malaysia’s temperature and rainfall have been rapidly increasing between +0.6 and 3.4 °C and −1% to +32%, respectively, over the last 60 years and sea level has risen approximately 13–94 cm in the last 100 years, respectively. Thus, these changes will impact water resources, coastal zones, public health, food supplies, drainage, flooding, landslides, haze, typhoons, and other negative phenomena that will require national and international responses in the face of climate change. Realizing the importance of reducing and combating the impact of climate change, this study proposes an explanation of the fundamental climatic question in Malaysia in general and sustainable food issues in particular since climate change and agriculture and food productivity are interrelated (Al-Amin & Leal Filho, 2014). Lobell et al. (2008) asserted that due to climate change, southern Africa could lose more than 30% of its main crop, maize, by 2030. In Asia, especially South Asia Table 1.1  Projected monthly rainfall and temperature (NAHRIM, 2006) Projected changea monthly Temperature (°C) Regions/subregions/states Northeast Region: Terrengganu, Kelantan, Northeast +1.88 Coast Northwest Region: Perlis (west coast), Perak +1.80 Central Region: Klang, Selangor, Pahang +1.38 Southern Region: Johor, Southern Peninsula +1.74 Difference = Average 2025–2034 & 2041–2050; minus average 1984–1993

a

Maximum value Rainfall (%) +32.8 +6.2 +8.0 +2.9

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1 Introduction

and Southeast Asia, such as Malaysia, will lose many regional staples, such as rice, millet, and maize, whose production could drop by 10%. Assessment of the effects of global climate change on the food sector might help to properly anticipate changes and adapt farming to maximize food production (Rosamond et al., 2007). Malaysians understand the impacts of climate change issues, that requires more awareness for adaptive farming but specific operational guidance on how to take it into account is generally lacking. However, this study assumes that it will not be easy tominimize the gap among climate change concerns, adaptative measures and climate development activities. The two areas have different priorities and often operate on different time and spatial scales. Therfore specific information is required for the climate resilience of climate change for developmental activities along with operational guidance on how best to adapt to its impacts, within the context of other pressing social priorities proposed in the Malaysian National Policy on Climate Change (MNPCC, 2009).6 Consequently, to yield the expected benefits, this study needs to take into account how the mainstreaming of adaptation policy is developed and how it can be applied to the climate change concerns and development activities. As a way forward on this issue, long-term security options are being increasingly explored, along with adaptation mechanisms. However, the use of systems for enforcing the effects of adaptation remains a subject of debate, especially with regard to market mechanisms. Hence, overcoming the gap between adaptation options (i.e., in the food sector) and environmental conservation is among the most difficult elements of a modeling system. Therefore, the new challenge in addressing climate change issues in connection with adaptation options is integrating dimensions of physical and social sciences into a new approach. Such an approach must take into consideration, on the one hand, the need for environmental conservation and, on the other hand, requirements for effective climate change adaptation on the other. Nevertheless, the coordination of a multidisciplinary (i.e., dimensions of physical and social sciences together) adaptive modeling system is also important for structuring long-term climate change scenarios. This multidisciplinary adaptive approach must enable new effective adaptation techniques taking into account national agendas, current policy options, future national agricultural road maps, market preferences, green growth, and technological development, which is the initiative in this study to achieve sustainable food security. The rationale of the multidisciplinary adaptive approach is quite noble as it looks for long-term government policy planning for climate change issues. Here, it is also important to look at the issue, not only theoretically, but in realistic terms as well. We must also consider all societal subsystems related to national needs, such as a future option on green growth, green technology, market mechanisms and 6  The main objectives of the Malaysian National Policy on Climate Change (MNPCC) (2009) are wise management of resources, enhanced environmental conservation, and strengthening institutional and implementation capacity to reduce the negative impacts of climate change. The NPCC is based on the principles of sustainable development, coordinated implementation, effective participation, and common but differentiated responsibilities.

1.4  Current Climate Change Scenario in Malaysia

7

preferences, social utility, national growth plans and agendas, taxation policy, industrial development, and other social institutions contributing in one way or another, directly or indirectly. This study argues that scientists and social scientists may work together on developing adaptation modeling (i.e., agriculture), thus bringing together efficient technological innovation and long-term applicable adaptive frameworks. The implementation of the expected agreement should be answered on the basis of sound scientific knowledge. The specific budget line should therefore identify research needs and gaps that need to be addressed in view of establishing scenarios that are socially, economically, and environmentally suitable. Finally, there should be a justified combination of adaptation and development options to support long-run pathways.

1.3  Research Goals To develop a clear picture from the foregoing discussion and sound understanding of applicable adaptation option to Malaysia’s sustainable food policy, this study aimed to address the following research goals that emerged from the recent climate change and sustainable food policy issues. The overall goal of the research is to develop a mainstreaming adaptation structure for a sustainable food sector to explore the long-term national policy option, but the specific objectives of this book are to estimate scenario adaptation costs for the food sector based on economic trade-offs between climate change and its impacts, identify suitable adaptation policy options to support sustainable future climate change strategies, and identify the capacity-building options to support adaptation policies.

1.4  Current Climate Change Scenario in Malaysia Malaysia has a diverse landscape ranging from coastal regions to hilly areas. The country has experienced abrupt changes in climate over the past few decades (Al-Amin & Leal Filho, 2014). Table 1.2 presents the observed and projected climate change scenario in Malaysia. The annual mean surface temperature for the entire country is about 26 to 28 °C (MMD, 2009). According to 50-year meteorological records, the mean surface temperature for Malaysia has increased from 0.6 to 1.2 °C (MMS, 2013). Moreover the highest recorded annual precipitation intensity for 1 hour periods (2000–2007) showed an increase rate of 17–112 mm/h, and for 3 h periods it increased by 29% to 133 mm/h compared to the 1970s (MMD, 2009). A sea level rise study was also conducted over a 20-year period (1986–2006) and showed an increase rate of 1.3 mm/year (MMD, 2009). Based on the average series of emissions, projections specify a 1.5–2.0 °C rise in surface air temperature by 2050 (MMD, 2009). Precipitation and river flows are projected to experience greater fluctuations. The occurrence of extreme weather is also projected to rise.

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1 Introduction

Table 1.2  Observed and projected climate change in Malaysia (UNFCCC, 2011) Climate variable Temperature

Observed 0.6–1.2 °C over 50 years (1969–2009)

Rainfall (amount)

No appreciable difference

Rainfall intensity

Increased by 17% for 1-h duration and 29% for 3-h duration (2000–2007 compared to 1971–1980) 1.3 mm/year (1986–2006,Tanjung Piai, Johor)

Sea level rise (SLR)

Projected (by 2050) 1.5–2 °C increase (−) 5% to (+) 9% change in regions within Peninsular Malaysia (−) 6% to (+) 11% change in regions within Sabah and Sarawak Increase in extremes within wet cycles, increase in frequency of extreme weather 0.5 m rise (global high worst case at 10 mm/year)

It has been established in the recent literature that climate patterns will change in the future. Malaysia likewise expects changes in its weather patterns and, due to the direct impact of weather patterns, in the food sector; food security is also under threat. Thus, addressing the issue and achieving self-sufficiency in food security is urgent, and there is a need to take proper measures to ensure food security in a sustainable way. I accept that the effects of climate change will continue in the future, but finding suitable options for mitigating the damage from climate change in the agricultural sectors remains an unresolved issue. This study represents a way forward based on climate, agro, and economic modeling approaches. As a research approach this study applied the Malaysian Integrated Climate and Economy (MICE)-based computable general equilibrium (CGE) modeling. Such a model usually provides an economywide perception and is very useful when considering the frequent and often complex exchanges that occur among the diverse parts of an economy, which are critically important (Abelson, 2011). However, for agriculture, these types of interactions can arise within the sector (competing for limited resources, including various types of land) and between agriculture and other sectors operating in the food and fiber chain system (White, 2013). In addition, this study also revealed a significant number of studies in the literature based on climate change in Malaysia and its impact on the country’s food sector. Some of these studies indicate crop production damage stemming from climate change, and others identified self-sufficiency targets in crop production. Moreover, there is a lack of studies focusing on farm-based adaptation options in the food sector which this study tried to minimize the lack of farm-based adaptation options for food sustainability. Although Malaysian policymakers are passing adaptation policies in some cases to reduce food damage from climate change, it is not obvious at what level they will adopt measures for ensuring the country’s resilience to climate change.

1.7 Conclusion

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1.5  Significance of Study The purpose of this study is to investigate the economywide effects of adaptation policies on the Malaysian economy. Specifically, this study makes the following contributions: 1. Help in setting up a long-term adaptation policy for food sustainability in response to the Malaysian National Policy on Climate Change (2009), 2. Fill a research gap in finding the distribution of impacts of the adaptation policies for the food sector, and 3. Provide guidelines for policymakers with respect to macroeconomic decision-­ making with precise knowledge of the overall impacts of adaptive measures. Although the ultimate target groups are principally Malaysian policymakers, a wide range of stakeholders and related organizations may benefit from the scientific findings of this research.

1.6  Limitations Although MICE-based CGE models offer innovative ways to identify quantitative estimates of important economywide effects associated with climate policy, there are a few weaknesses and limitations of the CGE modeling approach. The weakness of CGE models is that their results are implicitly linked to the assumptions made and the calibration mode. Another weakness of general equilibrium studies compared to sectoral models are that, following the top-down approach, CGE models typically lack a detailed bottom-up representation of the production and supply side. The other limitation relates to technology; as this study did not directly apply technology options to compare the crop damage for its further development to climate change.

1.7  Conclusion This study aims to evaluate the scenario framework for climate chnage adaptations options to lessen the impacts of climatic damage in food sectos and food sustainability. This research study will help to set up a long-term climate change adaptation mechanism for applicable policy programs and options, particularly on the issue of sustainable food security.7 Certainly the outcomes lead to designing a climate change adaptation model for the Malaysian food sector and sustainability issues in particular. 7  Sustainable food security (SFS) is a food system that delivers food security and nutrition for all in such a way that the economic, social, and environmental factors in establishing food security and nutrition for future generations are not compromised.

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1 Introduction

1.8  Book Organization This book is organized as follows. Chapter 2 discusses recent research on climate change and food security that highlights the literature on decision support models for policymaking in the sustainable food sector for a given level of food security, methods for studying policy implications under uncertainty, and how uncertainty methods have been applied to MICE-based CGE models. Chapter 3 highlights an assessment of climate change ipmacts on food sectos and identifies suitable adaptation policy options for sustainable food security as well as food sustainability. The chapter also presents the basic features of MICE-based CGE models. It also describes the numerical modeling framework that was developed and used to investigate suitable adaptation options to reduce threats to food production and to increase food sustainability. Chapter 4 investigates suitable food sustainability strategies under uncertainty (effects of climate change on the food sector) with respect to future climate policy using CGE modeling. Chapter 5 discusses policy implications for climate change adaptation in Malaysia. Chapter 6 investigates the importance of the food sector in connection with the Malaysian climate and economy (MCE) with a comparative discussion of the interpretation of the scenario-based long-term applicable adaptation modeling results. The chapter also summarizes the key insights, implications, and contributions of the book and includes discussions of the limitations of the presented research as well as future research opportunities.

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Burke, M. B., Miguel, E., Satyanath, S., Dykema, J. A., & Lobell, D. B. (2010). Climate robustly linked to African civil war. Proceedings of the National Academy of Sciences of the United States of America, 107(51), E185–E185. Cahill, K. N., Lobell, D. B., Field, C. B., Bonfils, C., & Hayhoe, K. (2007). Modeling climate and climate change impacts on wine-grape yields in California. American Journal of Enology and Viticulture, 58(3), 414A–414A. Cook, J., Nuccitelli, D., Green, S.  A., Richardson, M., Winkler, B., Painting, R., & Skuce, A. (2013). Quantifying the consensus on anthropogenic global warming in the scientific literature. Environmental Research Letters, 8(2), 024024. Deni, S.  M., Suhaila, J., Zin, W.  Z. W., & Jemain, A.  A. (2010). Spatial trends on dry spells over Peninsular Malaysia during monsoon seasons. Theoretical and Applied Climatology, 99, 357–371. Easterling, W. E., Aggarwal, P. K., Batima, P., Brander, K. M., Erda, L., Howden, S. M., Kirilenko, A., Morton, J., Soussana, J. F., Schmidhuber, J., & Tubiello, F. N. (2007). Food, fibre and forest products: Climate change 2007: Impacts, adaptation and vulnerability. In M. L. Parry, Canziani OF, J.  P. Palutikof, P.  J. Van der Linden, & C.  E. Hanson (Eds.), Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change (pp. 273–313). Cambridge University Press. Georgescu, M., Lobell, D. B., & Field, C. B. (2011). Direct climate effects of perennial bioenergy crops in the United States. Proceedings of the National Academy of Sciences of the United States of America, 108(11), 4307–4312. Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., & Toulmin, C. (2010). Food security: The challenge of feeding 9 billion people. Science, 327(5967), 812–818. Gosling, S. N., Warren, R., Arnell, N. W., Good, P., Caesar, J., Bernie, D., & Smith, S. M. (2011). A review of recent developments in climate change science. Part II: The global-scale impacts of climate change. Progress in Physical Geography, 35(4), 443–464. Hertel, T. W., Burke, M. B., & Lobell, D. B. (2010). The poverty implications of climate-induced crop yield changes by 2030. Global Environmental Change-Human and Policy Dimensions, 20(4), 577–585. IPCC. (2007a). Climate change 2007: Impacts, adaptation and vulnerability. Contribution of Working Group II to the fourth assessment report of the intergovernmental panel on climate change (M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, & C. E. Hanson, Eds.). Cambridge University Press. IPCC. (2007b). Climate change: Synthesis report. Contribution of Working Groups I, II and III to the fourth assessment report of the intergovernmental panel on climate change (Core writing team: R. K. Pachauri & A. Reisinger, Eds.). IPCC. Kurukulasuriya, P., & Rosenthal, S. (2013). Climate change and agriculture: A review of impacts and adaptations. World Bank. Lau, K. M., & Wu, H. T. (2007). Detecting trends in tropical rainfall characteristics, 1979–2003. International Journal of Climatology, 27(8), 979–988. 175. Leiserowitz, A. A., Kates, R. W., & Parris, T. M. (2005). Do global attitudes and behaviors support sustainable development? Environment: Science and Policy for Sustainable Development, 47(9), 22–38. Lobell, D. B., & Gourdji, S. M. (2012). The influence of climate change on global crop productivity. Plant Physiology, 160(4), 1686–1697. Lobell, D.  B., Bänziger, M., Magorokosho, C., & Vivek, B. (2007). Nonlinear heat effects on African maize as evidenced by historical yield trials. Nature Climate Change, 1, 42–45. Lobell, D. B., Burke, M. B., Tebaldi, C., Mastrandrea, M. D., Falcon, W. P., & Naylor, R. L. (2008). Prioritizing climate change adaptation needs for food security in 2030. Science, 319(5863), 607–610. Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333, 616–620.

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Lobell, D. B., Roberts, M. J., Schlenker, W., Braun, N., Little, B. B., Rejesus, R. M., & Hammer, G.  L. (2014). Greater sensitivity to drought accompanies maize yield increase in the US Midwest. Science, 344(6183), 516–519. Lorenzoni, I., & Pidgeon, N. F. (2006). Public views on climate change: European and USA perspectives. Climatic Change, 77(1-2), 73–95. Malaysian Meteorological Department Scientific Report (MMD). (2009). Climate change scenarios for Malaysia, 2001–2099. Malaysian Meteorological Service. (2013). Online: http://www.met.gov.my Manton, M. J., Della-Marta, P. M., Haylock, M. R., Hennessy, K. J., Nicholls, N., Chambers, L. E., & Yee, D. (2001). Trends in extreme daily rainfall and temperature in Southeast Asia and the South Pacific: 1961–1998. International Journal of Climatology, 21(3), 269–284. MMD. (2009). Climate change scenarios for Malaysia. Malaysian Meteorological Department, Ministry of Science Technology and Innovation. NAHRIM. (2006). Final report: Study of the impact of climate change on the hydrologic regime and water resources of Peninsular Malaysia. National Hydraulic Research Institute of Malaysia. Paterson, R. R. M., Sariah, M., & Lima, N. (2013). How will climate change affect oil palm fungal diseases? Protection, 46, 113–120. Pooniya, V., Choudhary, A. K., Dass, A., Bana, R. S., Rana, K. S., Rana, D. S., Tyagi, V. K., & Puniya, M. M. (2015). Improved crop management practices for sustainable pulse production: An Indian perspective. Indian Journal of Agricultural Sciences, 85(6), 747–758. Porter, J. R., Xie, L., Challinor, A. J., Cochrane, K., Howden, S. M., Iqbal, M. M., Lobell, D. B., Travasso, M. I., Chhetri, N., Garrett, K., Ingram, J., Lipper, L., McCarthy, N., McGrath, J., Smith, D., Thornton, P., Watson, J., & Ziska, L. (2014). Food security and food production systems. In Climate change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of Working Group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press. Raddatz, T. J., Reick, C. H., Knorr, W., Kattge, J., Roeckner, E., Schnur, R., & Jungclaus, J. (2007). Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-­ first century? Climate Dynamics, 29(6), 565–574. 150. Rosamond, L. N., David, S. B., Daniel, J. V., Walter, P. F., & Marshall, B. (2007). Assessing risks of climate variability and climate change for Indonesian rice agriculture. Proceedings of the National Academy of Sciences of the United States of America., 19, 7752–7757. Rowhani, P. (2011). Climate volatility and poverty vulnerability in Tanzania. Global Environmental Change-Human and Policy Dimensions, 21, 46–55. Rowhani, P., Lobell, D. B., Linderman, M., & Ramankutty, N. (2011). Climate variability and crop production in Tanzania. Agricultural and Forest Meteorology, 151(4), 449–460. Shaw, R., Pulhin, J. M., & Pereira, J. J. (Eds.). (2010). Climate change adaptation and disaster risk reduction: An Asian perspective: An Asian perspective (Vol. 5). Emerald Group Publishing. Suhaila, J., Deni, S. M., Zin, W. Z. W., & Jemain, A. A. (2010). Trends in Peninsular Malaysia rainfall data during the southwest monsoon and northeast monsoon seasons: 1975–2004. Sains Malaysiana, 39(4), 533–542. Tangang, F. T., Juneng, L., & Ahmad, S. (2007). Trend and interannual variability of temperature in Malaysia: 1961–2002. Theoretical and Applied Climatology, 89(3-4), 127–141. Toriman, M. E., Yun, L. Q., Kamarudin, M. K. A., Aziz, N. A. A., Mokhtar, M., Elfithri, R., & Bhaktikul, K. (2014). Applying seasonal climate trends to agricultural production in tanjungkarang, Malaysia. American Journal of Agricultural and Biological Sciences, 9(1), 119. Tubiello, F. N., Soussana, J. F., & Howden, S. M. (2007). Crop and pasture response to climate change. Proceedings of the National Academy of Sciences, 104(50), 19686–19690. UNFCCC, C. C. (2011). Agriculture and climate change in the UN climate negotiations. United States Environmental Protection Agency (EPA). (2010). Climate change indicators in the United States. White, T. (2013). Seeds of a new economy? A qualitative investigation of diverse economic practices within Community Supported Agriculture and Community Supported Enterprise. University of Massachusetts Amherst.

Chapter 2

Recent Research on Climate Change and Food Security

Abstract  The ability of food systems to respond to climate change is both exciting and underappreciated. This chapter examines potential producer and consumer responses to climate change, their ability to mitigate otherwise negative effects on food security, and the role of public and private organizations in investing in adaptation when individual responses are inadequate. This research, on the other hand, attempted to delve into the literature on climate change and adaptation policies by looking into the relationship between climate change and food security, adaptation, and agriculture in developing countries, specifically Malaysia. It is necessary to address some important issues concerning climate change and food security in this chapter in order to gain a better understanding of adaptation concepts and climate change as they relate to food security. Many studies have highlighted the negative net impact of climate change on agriculture. Most studies have shown that Sub-­ Saharan Africa is one of the most vulnerable regions to climate change, with the majority of people reliant on climate-sensitive agricultural systems. According to a review of the literature on food security issues, food production alone would not be able to contribute to overall food security because food production is dependent on a variety of climatic conditions and factors. Many reports in particular define the negative effects based on forecasts for various time segments and suggest that the amount of rainfall is decreasing in trend and will continue to decrease in the future with some uncertainty regarding its amount. Although a mild rise in temperature (between 1 and 3 °C) may support food production in temperate regions, it may have a negative effect in tropical and seasonally dry areas. Furthermore, this study discovered a scarcity of studies on adaptive capacities in developing countries that represent the introduction of a certain level of adaptation alternative that can be used as a benchmark for measuring food security or food sustainability. Therefore, the aim of this chapter is to discuss the different climate change adaptive capacities and concerns for food sustainability particularly in Malaysian context.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_2

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2  Recent Research on Climate Change and Food Security

2.1  Introduction The ability of food systems to respond to climate change is both exciting and underappreciated. This chapter examines potential producer and consumer responses to climate change, their ability to mitigate otherwise negative effects on food security, and the role of public and private organizations in investing in adaptation when individual responses are inadequate. According to the evidence, wealthier societies and households will be better able to adapt to a changing climate because they will have more options and will be able to take advantage of them. As a result, investments that increase poor people’s choices, such as enhanced food production technologies, financial instruments, and off-farm income opportunities, will likely be crucial in adapting food security to climate change. This research, on the other hand, attempted to delve into the literature on climate change and adaptation policies by looking into the relationship between climate change and food security (CCFS), adaptation, and agriculture in developing countries, specifically Malaysia. It is necessary to address some important issues concerning CCFS in this chapter in order to gain a better understanding of adaptation concepts and climate change as they relate to food security.

2.1.1  Climate Variability and Climate Change There is no universally agreed-upon concept of “climate change.” However, climate change can refer to: (i) long-term changes in average biogeophysical weather conditions (usage); (ii) alterations in climate patterns, including climatic drivers and their effects (usage); or (iii) anthropogenic anomalies in climate patterns (UNFCCC usage). There is still no consensus about how to explain “climate instability” in the context of climate change. Climate patterns have changed continuously over the course of Earth’s 4.5-billion-year history. However, the majority of such changes occurred on celestial or geological time scales, which are extremely hard to observe on a human scale. Normal climate disparity on these scales is often referred to as “climate variability,” which is distinct from human-caused climate change. Climate variability, on the other hand, has been described by meteorologists and climatologists as the variations in atmospheric conditions from year to year. That is why the UN’s Food and Agricultural Organization (FAO) prefers to use a comprehensive definition of climate change to assess food security and climate change, which takes into account long-term averages of key climate variables. In most cases, the observational record of these variables is very short, making it difficult to determine whether recent shifts characterize factual studies on a long-term basis (climate change) or are simply outliers around a stable mean (climate variability).

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2.1.2  Declining Food Sector The growth of the food sector has slowed over the last two decades, implying that security has deteriorated. The contribution of the food sector to gross domestic product (GDP) has drastically decreased as a result of low demand (ESCAP, 2008). For example, in East Asia and the Pacific, it was 3.0% in the 1980s and 0.1% higher in 2000–2003. This has been linked to a number of factors, including: (a) The agriculture food sector’s investments and dedication have decreased. (b) Low-efficiency and small-scale farming systems’ contributions (Devendra, 2010, 2012). The majority of small farms are located in Asia, accounting for 87% (470 million) of all occupied land area of less than 2  ha (Nagayets, 2005). (c) Small farmers’ food production potential is being marginalized. Globalization has had the following effects on market access and agricultural trade: 1. Food and nutritional insecurity 2. Poverty-hunger-vulnerability is a complex and serious problem. By 2020, 49 million people will be at risk as a result of climate change, with 132 million more at risk by 2050 (IFAD, 2009). From the recent analysis of Al-Amin and Leal Filho (2014) it has been demonstrated that, due to a temperature rise of 1  °C, output damage can be up to 6.1 (percent) in the region. On the other hand, population growth is a critical problem that necessitates ensuring food security in different regions. However, in the last two decades, carbon emissions have risen dramatically, by around 70%, due to industrialization, urbanization, deforestation, shifting landscapes, and other factors.

2.2  A  sian Development Bank Observations of Climate Change in Agriculture in Southeast Asia Southeast Asia is a major agricultural region with rice, maize, cassava, coconut oil palm, and natural rubber, as well as other crops (Fox & Castella, 2013). The majority of the raw grains used in the production of rubber and palm oil come from this area. In recent years, the growth of livestock has outpaced that of food crops. However, in the past the supply of animal protein was insufficient to meet estimated requirements, but animal protein supplies were inadequate to satisfy projected demands. The Asian Development Bank (ADB) (2009) has identified the following

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issues concerning agriculture in Southeast Asia in the context of climate change and the environment: (a) Methane (CH4) emissions from the majority of rice production can be minimized to ensure food security. (b) Unwanted carbon can be mixed in croplands as a means of sequestration by various farming practices. (c) Agriculture has the highest scientific mitigation potential of any area for reducing greenhouse gas (GHG) emissions from the food sector. (d) Limiting CH4 emissions from rice fields could boost food production while also lowering poverty and stabilizing GHG emissions (greenhouse gases). From the preceding discussion this study found that Malaysia also faced the same challenges in its food sector with respect to climate change and establishing the expected level of food security for human well-being.

2.2.1  Dynamics of Food Security under a Changing Climate Food protection is particularly vulnerable to climate change because the food sector is directly impacted by it (FAO, 2011). As a consequence, the national government places a high priority on ensuring food security. This is a particularly important concern because it provides a connection between output and availability on the one hand and potential use on the other. Farmers’ primary motivation for working on their farms is to have a better future for their families. The major components of food security, as shown in Table 2.1, are food supply, access, utilization, and stability. Food protection can be discussed at both a national and personal level. Food security, on the other hand, is usually achieved by balancing food demand and supply at the national level, where ample food is available at reasonable prices, and the majority of people have access to it (Hamilton et al., 2014). Food protection at the household level is critical because it is the basic financial unit that determines an individual’s consumption level. Obtaining a food protection solution necessitates the use of four mechanisms at the same time. Physical accessibility, on the other hand, may not be needed for the “availability” aspect, but it may increase the limited production volume (Wheeler & von Braun, 2013). It is not a critical question whether food is “available” or not in the current age of globalization, where trade is possible at a reasonable price. However, when it comes to the problem of economic and noneconomic capital, it is sufficient to ensure that everybody has access to adequate food. State self-­sufficiency, on the other hand, is neither required nor sufficient to ensure individual food security. Hong Kong and Singapore, for example, are not agriculturally self-sufficient. However, their people are well fed, while India is self-sufficient but has a large population that is food insecure (Thornton & Lipper, 2014). As a consequence, whether for its citizens or for trade reasons, “availability” is a priority of a country’s financial and nonfinancial resources.

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Table 2.1  Components of Food Security (FAO, 2008) Components Definition and Determinants AVAILABILITY Refers to physical availability of food; addresses the “supply side” of food security Determinants are:  (i) Economic level of production, stock level, and net trade  (ii) Socio-cultural-economic – factors that affect the producers’ response to market  (iii) Agro-climatic fundamentals of crop and pasture production, as well as sociocultural and economic factors that influence farmers’ market responses ACCESS Individuals’ access to sufficient services (entitlements) for obtaining suitable food for a healthy diet. Given the legal, political, economic, and social arrangements of the community in which individuals reside, entitlements are described as the collection of all commodity bundles over which an individual may establish command (including traditional rights such as access to common resources) Consumer buying power and the evolution of real wages and food prices are major determinants UTILIZATION To achieve a state of nutritional well-being in which all physiological requirements are fulfilled, food must be utilized through a sufficient diet, clean water, sanitation, and health care. This emphasizes the significance of nonfood inputs in ensuring food security Its subdimensions are related to sanitation, including sanitary conditions across the entire food chain, and it encompasses all food safety and quality aspects of nutrition STABILITY A community, family, or person must have access to sufficient food at all times to be food safe. They should not be at risk of losing food due to unexpected events (such as an economic or climate crisis) or cyclical events (e.g., seasonal food insecurity). As a result, the term “stability” may refer to both the availability and access aspects of food security

The literature reports many theoretical models on the existence and dynamics of the relationship between CCFS (Vervoort et al., 2014). These models include a linear relationship between CCFS in the future, based on the food production system, with marginal response in nature (Fig. 2.1). Additional comparable studies have been carried out, most notably by FAO (2008) and IFPRI (2012), but both looked at conceptual and empirical models in a linear dimension (Rosegrant & Cline, 2003). Food protection, on the other hand, cannot be interpreted in isolation, according to one universal viewpoint. This is a widespread issue because it is part of more complex interconnections involving oil, the atmosphere, climate change, food security, and financial security (Nelson & ven der Mensbrugghe, 2013). Capra (2013) also outlined the relationship between these issues and a biological framework. It does, however, outline the starting point as well as the connection between climate change and the related issues and their ultimate effects on food security (Hansen & Coffey, 2011). For example, the central issue is depicted in the fundamental concept that creation is limitless despite the Earth’s

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2  Recent Research on Climate Change and Food Security

Historical Factors

Social, political and economic factors

Agricultural and environmental factors

Food Networks

Imports & Exports

Agricultural production

No food uses

Post-harvesting handling

Processing

Loses

Storage & Packaging

Distribution & Retail

Family use

Household Food Security

Food availability Access to food Consumption Biological utilization State of health & nutrition Community & consumer level

Fig. 2.1  Relationship between climate change and food security (FAO, 2004)

tilt. The assumption is that growth or development is a linear function (Robinson et al., 2006). However, in conceptual paradigm systems, growth is nonlinear and constrained in all sectors, particularly natural resources. A vicious cycle, or self-reinforcing reaction loop, is formed by rapid population growth and poverty. Since current cropland and water sources are shrinking, this faster population growth creates hunger. Overgrazing, deforestation, and overfishing are examples of stressors on natural resources caused by excessive

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consumption and pollution in developed countries and rapid population growth in developing countries. Water tables are dropping, rivers are drying up, dams are dwindling, forests are shrinking, fisheries are collapsing, and soils are eroding, all of which pose a threat to food security. The world is facing extreme climate change as a result of the continued growth of fossil-fuel-based technology and resources (Challinor et  al., 2014). Deforestation is a major contributor to the huge release of carbon into the environment, and it is a critical concern. Uneven floods, hurricanes, and forest fires, as well as droughts, heat waves, increasing temperatures, and shifting rainfall patterns, all contribute to a decline in agricultural crop production. Increased global temperatures change many ecosystems, resulting in the extinction of many species present in the world (Chesterman & Ericksen, 2013).

2.2.2  F  ood Security and Climate Change: A Conceptual Framework Food processes, like all other manifestations of human activity, can be observed around the world (FAO, 2009a). Figure  2.2 depicts some of the major shifts in Earth’s structures that are expected to occur as a result of global warming, which would alter normal weather patterns. The most likely effects of climate change, as seen in Fig. 2.2, are increases in weather inconsistency. Extreme weather events are likely to become more common in the coming years. Continuous shifts would not reveal the predicted increases in mean temperatures and rainfall. However, it will see an increase in the frequency, length, and intensity of hot spells and rainfall events. However, the annual average warmer days and highest temperatures are projected to rise in most parts of the globe. Annual global rainfall is also increasing, but it is not predicted to be evenly distributed across the globe. Wet areas, on the other hand, are predicted to become wetter, while arid regions will become dryer (Jones & Thornton, 2009). Meanwhile, to illustrate the variables representing the food and climate systems, a theoretical overview of food security and climate change interfaces was developed. The CCFS structure (Fig. 2.1 and Table 2.1) shows how climate change has direct and indirect effects on major food security mechanisms such as food supply, food accessibility, food intake, and food system consistency (Füssel, 2007). Climate change variables affect the biophysical factors such as plant and animal progression, water successions, biodiversity, and nutrient rotation. Climate change affects agricultural management activities and land use for food production (UNDP-UNEP, 2011). Climate variables, on the other hand, have an effect on physical/human resources such as highways, storage and marketing infrastructure, homes, asset productivity, power grids, and human health. Finally, this may affect the monetary and sociopolitical problems that govern food access and use, posing a challenge to food system stability. Many of these factors manifest themselves in the ways in which the food system is funded. To cope with the

weather patterns -change in start and end of growing seasons

GREATER WEATHER VARIABILITY -greater instability in seasonal

of high winds, heavy rains, storm surges and flash floods associated with tropical storms and tornados

INCREASE IN FREQUENCY AND INTENSITY OF EXTREME WEATHER EVENTS -increase in annual occurrence

-increase in frequency, duration and intensity of dry spells and droughts -changes in timing, location and amounts of rain and snowfall

GRADUAL CHANGES IN PRECIPITATION

temperature on hot days -increase in minimum temperature on cold days -increase in annual occurrence of hot days -increase in frequency, duration and intensity of heat waves

Fig. 2.2  Climate change and food security (FAO, 2010)

Drivers of Global Warming • • Demographic • Economic • Socio-political • Technological • Cultural &religious

INCREASE IN GLOBAL MEAN TEMPERATURES -increase in maximum

-increase in availability of atmospheric carbon dioxide for plant growth

CO2 FERTILIZATION EFFECTS

Change in Food System Activities -Producing food -Storing andprocessing of food -Distributing food -Consuming food

Possibility of Migration and Conflict

Change in Food System Assets -Food productionassets -Storage, transport and marketinginfrastructur e -Agriculturally based Livelihood assets -Non-farm livelihoodassets -Food preparationassets

Adaptive Responses of Food Systems

Possible Changes in Human Health -Change in caloricsufficiency of diets -Change in nutritional value of diets -Increased incidence of water-borne diseases in flood-prone areas -Change in diseasevectors and habitatsfor existing diseases -Emergence of newdiseases

Nutritional change for climate change

Possible Changes in Food Consumption Patterns -Shift away fromgrainfed livestock products -Shift in proportion oflocally produced foodsin the diet -Increase in consumption of new food items -Reduction in consumption of wild foods -Reduction in quantities and/or variety of food consumed

Components of Food Security -Food availability -Food accessibility -Food utilization -Food system stability

20 2  Recent Research on Climate Change and Food Security

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effects of climate change, this framework shows how adaptive changes to food system output would be needed all along the food chain. These variables of climate change as presented in the CCFS framework are as follows: (a) CO2 emissions as a result of increased atmospheric GHG concentrations; (b) Increasing mean, maximum, and minimum temperatures; (c) Regular change in rainfall patterns; (d) Upsurge in frequency, duration, and strength of dry spells and droughts; (e) Changes in timing, duration, intensity, and geographic location of rainfall and snowfall; (f) Growth in frequency and intensity of storms and floods; and (g) Greater seasonal weather variability and changes in start/end of growing seasons. More frequent and punishing weather events, according to recent data, are already having direct effects on food production, food supply arrangements, food disasters, possessions, and human health in both rural and urban areas (Feder et al., 2010). Furthermore, ongoing deviations in mean temperatures and precipitation are expected to have less immediate consequences. However, these will reduce soil productivity for a variety of crops and grasslands; forest efficiency; aquatic assets; pathogen attack; biodiversity and ecosystem frequency; and irrigation water supply for crops, livestock, and fish farming (Sirohi & Michael, 2007). On the other hand, increasing salinity, depleting groundwater, and rising sea level may reduce fertility in arable soil (Gupta, 2007). Internal and global migration, resource disputes, and political instability caused by climate change will have an effect on the food system.

2.2.3  Contribution of Food Sector to Malaysian GDP Agriculture’s contribution to Malaysia’s GDP has recently decreased. Previously, in 1960, agriculture accounted for 37% of total GDP (Matahir, 2012). In 2013, however, it was just 11.2%. Furthermore, agricultural production growth during the Ninth Malaysia Plan (2006–2010) was 2.65% (Laurance et al., 2010), which was unpredictably lower. Agriculture is given priority in terms of food security as a result of these estimated scenarios. As a result, agriculture, palm oil, and other items have been designated as National Key Economic Areas (NKEAs) in the Tenth Malaysia Plan (2011–2015) (Nieves et al., 2011). In reality, in their first assessment report in 1990, the IPCC conducted an analysis of climate change and its effects on the food sector. Finally, the IPCC issued some global guidelines for climate change adaptation that are important for regional or country-specific economic growth in every field. As a result, it is critical to understand how IPCC research studies can be implemented in developing countries to ensure long-term food security in the face of climate change’s sudden impacts.

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Furthermore, as climatic conditions change, the problem only intensifies, necessitating a more immediate response. The main findings of the IPCC’s Fourth Assessment Report (AR4) (IPCC, 2007a) were as follows: (i) Unequivocal warming progress of climatic factors; (ii) Because of the timescales associated with climate systems and feedback, anthropogenic global warming could persist for centuries; and (iii) The surface air temperature in the twenty-first century is expected to rise from 1.1  to 2.9  °C for a “low scenario” and 2.4  to 6.2  °C for a “high scenario,” according to estimates. Indeed, according to IPPC (2007a) projections, the worst of climate change is yet to come. For example, based on the 1961–1990 baseline period, Southeast Asia is expected to have a 3.7 °C higher surface temperature by the end of the twenty-first century. Aside from weather patterns, we may have to experience very high emission scenarios for the next two to three decades. Climate change could cause 6.7% agricultural crop damage annually in Southeast Asia, according to a study by the Asian Development Bank (ADB, 2009). This includes Indonesia, the Philippines, Thailand, and Vietnam. However, if business effects are included, the economic cost will be 2.2% of GDP by 2010, 5.7% if health expenditures and biodiversity losses are included, and 6.7% if climatic catastrophes are also included, according to the statement (Smith & Olesen, 2010). As a result, by the end of the century, the global costs of climate change are estimated to be 2.6% of GDP annually. Furthermore, according to IFAD (2010), climate change is expected to put 49 million more people at risk of food shortage by 2020, and 132 million by 2050 (Fig. 2.3 and Table 2.2).

Fig. 2.3  Contribution (%) of agriculture to GDP in Malaysia (DOSM, 2013)

2.3 Potential Impacts of Climate Change on Food Security in Malaysia

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Table 2.2  Summary of possible effects of climate change on Malaysia’s major agricultural crops (UNFCCC, 2011) Crop Oil palm

Potential impacts The ideal annual temperature for oil palm production is 22–32 °C, with a mean annual evenly distributed rainfall of 2000–3500 mm. If the temperature rises 2 °C above optimum levels and rainfall falls 10%, oil palm yields could drop by around 30% Rice The ideal daily temperature for rice cultivation is between 24 and 34 °C, with more than 2000 mm of rainfall per year. A temperature rises of 2 °C above the threshold temperature reduces rice yield by up to 13%. Floods (15% increase in seasonal rainfall) and droughts (15% decrease in seasonal rainfall) early in the growing season, on the other hand, could reduce yields by up to 80% Rubber The ideal daily temperature for rice cultivation is between 24  and 34 °C, with more than 2000 mm of rainfall per year. A temperature rise of 2 °C above the threshold temperature reduces rice yield by up to 13%. Floods (15% increase in seasonal rainfall) and droughts (15% decrease in seasonal rainfall) early in the growing season, on the other hand, could reduce yields by up to 80% Cocoa The ideal annual temperature for cocoa production is between 25 and 32 °C, with a mean annual rainfall of 1500 and 2000 mm. Cocoa production will be significantly reduced in drought conditions with annual rainfall below 1500 mm. Due to a higher fungus occurrence, yields will be reduced if annual rainfall exceeds 2500 mm

2.3  P  otential Impacts of Climate Change on Food Security in Malaysia Climate change may pose a threat to a country’s food security. More than 860 million people around the world suffer from food insecurity, with the majority (95%) belonging to developing countries (Tiong et al., 2009). According to a study conducted by Parry et al. in 2004, approximately 1300 million people worldwide will face food insecurity by 2080. As a result, climate change is likely the most serious threat to global food security, especially in emerging economies such as Malaysia (ADB, 2009). However, for the development of food crops, the availability of land and water supplies is critical. Changes in climate variables such as temperature, precipitation, and relative humidity are making these vital sources of food production increasingly vulnerable (Devendra & Leng, 2011). Furthermore, a scarcity of water supplies would almost certainly result in serious drought (Khor, 2008). Changes in climatic factors can result in soil degradation and water scarcity, both of which have a negative impact on food production and supply. Climate change’s negative impact on food production will potentially stymie efforts to achieve food self-sufficiency. Table  2.3, on the other hand, depicts Malaysia’s food self-sufficiency rate from 1995 to 2010. We discovered that milk, mutton, and beef have lower self-sufficiency rates, while fruit, poultry, eggs, and pork have higher rates (Othman et al., 2013). Consequently, due to limited domestic supply, Malaysia is far more reliant on the importation of food products such as rice, wheat, beef, sheep meat, and dairy products to meet increasing domestic demand (Zahari & Alimon,

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Table 2.3  Recent IAM studies of economic consequences of climate impacts Regional Study scope Sectoral focus Global intertemporal economic modeling studies de Bruin et al. Global Aggregate (2009) Bosello et al. Global (12 Aggregate with energy (2010b) regions) system detail Nordhaus Global (12 Aggregate (2011) regions) CGE economic modeling studies Deke et al. Global (11 Agriculture, sea level (2001) regions) rise Darwin (1999) Global (8 Agriculture regions) Darwin and Sea level rise Tol (2001) U.S. Agriculture, forestry, Jorgenson et al. (2004) energy, water, coastal protection, air quality, heat stress Bosello et al. Global (8 Health (2006) regions) Bosello et al. Agriculture (2007b) Energy demand Bosello et al. (2007a) Bosello et al. Sea level rise (2007b) Global (8 Tourism, sea level rise Berrittella regions) et al. (2006) and Bigano et al. (2008) Eboli et al. Global (14 Agriculture, tourism, (2010) regions) energy demand, sea level rise, health Bosello et al. Global (14 (2010a) regions) Bosello et al. Europe (3 Ecosystem services, (2011) regions) linkages to 5 impact sectors in Eboli et al. (2010) Bosello et al. Global (14 Agriculture, forestry, (2012a, b) regions) tourism, energy demand, sea level rise, health, flooding

Remarks Uses AD-DICE/AD-RICE model (global damage function) Uses AD-WITCH model (global damage function) Uses RICE-2010 model (regional damage functions) Uses DART model (Klepper et al., 2003) Uses FARM model (Darwin 1995)

Uses IGEM model (Jorgenson & Wilcoxen, 1993)

Uses GTAP-EF model

Couples HTM and GTAP-EF models

Uses ICES model

Couples AD-WITCH and ICES models to investigate adaptation Uses ICES model

Uses ICES model

(continued)

2.3 Potential Impacts of Climate Change on Food Security in Malaysia

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Table 2.3 (continued) Regional Study scope Europe (5 Ciscar et al. regions) (2009, 2011, 2012) Calzadilla Global (16 et al. (2010) regions) Reilly et al. Global (16 (2012) regions) Literature surveys Agrawala and Multiple regions Fankhauser (2008)

World Bank Publications (2013)

6 developing regions

UNFCCC (2007)

Asia, Latin America, Africa, Small island states

Remarks Uses GEM-E3 model (Capros et al., 1997)

Water resources, agriculture Agriculture, health, ecosystems

Uses GTAP-W model (Berrittella et al., 2006) Uses MIT EPPA model (Paltsev et al., 2005)

Continue previous table coastal zone, agriculture, water resources, energy demand, infrastructure, tourism, health Infrastructure, coastal zones, water supply and flood protection, agriculture, fisheries, health, extreme weather events Agriculture, water resources, health, terrestrial ecosystems, coastal zones

Survey of studies providing sector-specific estimates of adaptation costs generated by sectoral economic simulations

Coastal zone, agriculture, water resources, energy demand, infrastructure, tourism, health World Bank 6 developing Infrastructure, coastal (2010) regions zones, water supply and flood protection, agriculture, fisheries, health, extreme weather events Sectoral partial equilibrium studies Block et al. Ethiopia Water, agriculture (2008) Nelson et al. Mali Agriculture (2010) Atwood et al. U.S. regional Agriculture (2006, 2008) McCarl et al. U.S. Forestry (2000)

Agrawala and Fankhauser (2008)

Multiple regions

Sectoral focus Agriculture, sea level rise, flooding, tourism

Sector-specific estimates of adaptation costs, generated by combining dose-response functions with engineering analyses and sectoral economic simulations Summarizes vulnerability, current and future adaptation plans/strategies, drawing on UNFCCC national communications, regional workshops, and expert meetings Survey of studies providing sector-specific estimates of adaptation costs generated by sectoral economic simulations Sector-specific estimates of adaptation costs, generated by combining dose-response functions with engineering analyses and sectoral economic simulations

Uses IMPACT model (Rosegrant et al., 2008) Uses MASM model Uses ASM model (McCarl et al., 1998) Uses FASOM model (Adams et al., 1998) (continued)

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2  Recent Research on Climate Change and Food Security

Table 2.3 (continued) Regional Study scope Sohngen and Global (9 regions) Mendelsohn (2003) Other simulation studies Tol (2008) Global (16 regions)

Nicholls et al. (2008) Narita et al. (2010) O’Brienet al. (2004) Hope (2006)

Sectoral focus Forestry

Remarks Uses an optimal control model (Adams et al., 1998)

Health

Uses FUND model (Tol, 2005; Anthoff & Tol, 2009) which has regional damage functions for impact endpoints (species loss, agriculture, coastal protection, disease morbidity/ mortality, cyclones, migration, ecosystems, sea level rise)

Sea level rise Cyclones Multisector Global (8 regions)

Aggregate

Uses PAGE model (Plambeck & Hope, 1996)

2005). Malaysia, for example, imported the vast majority of its beef and dairy products (77% and 98%, respectively) in 2005. (Ahmed & Siwar, 2013). The Tenth Malaysian Plan (2010–2015) aimed to increase food production, such as rice, beef, sheep meat, milk, fruit, and vegetables, in order to increase self-­ sufficiency (Arshad et  al., 2011). Nonetheless, achieving significant self-sufficiency in the near future seems unlikely since, on the one hand, there are resource constraints in the food sector and, on the other hand, climate change has a negative impact on crop production. According to a recent study by Al-Amin and Leal Filho (2014), food production will decrease by 4.6–6.1% for every 1 °C increase in temperature. Furthermore, the country’s population is projected to grow in the coming decades, necessitating a substantial increase in food production. In 1995, the country’s population was just 21 million, but by 2014, it had risen to 30 million (Basri et al., 2015). As a result, the country is expected to remain heavily reliant on imports of a variety of food products to meet rising domestic demand. Put another way, the deficit in meeting increased domestic food demand will lead to increased food imports at a high cost of over RM 14 billion and rising (Masud et al., 2014).

2.4 Climate Change and Self-Sufficiency Level in Rice Production in Malaysia

27

2.4  C  limate Change and Self-Sufficiency Level in Rice Production in Malaysia From the Malaysian perspective, there are three main factors of food security. There are as follows: (a) Food availability in terms of stability of food resources and sufficiency, (b) Accessibility of sufficient and healthy food, (c) Nutrients obtained through the supply of nutritious food. In reality, the definition of food security emphasizes a country’s ability to supply enough food to satisfy domestic demand on a national level. However, at the household or personal level, food security is defined as the ability of each household to obtain adequate healthy food in a timely manner. On the other hand, each household’s willingness and ability to pay for food are significant factors determining its degree of food security (Bala et al., 2014). Similarly, the government’s role in food security is to ensure that citizens have unrestricted access to sufficient food supplies. Nonetheless, this effort will be difficult because it necessitates thorough and precise planning as well as a clear understanding of both parties’ responsibilities. However, more than 100,000 farmers in Malaysia depend on rice production for a living, and many of them also work in the rice-based industry (Akinbile et  al., 2011). Furthermore, unsustainable rice production is a major concern for ensuring food security and alleviating poverty. Aside from development, food safety is a concern on both a national and international level. As a result, Malaysia’s National Agro-­ Food Policy (NAP) is intended to replace the country’s Third National Agricultural Policy (NAP3) (Alam et al., 2012). As a result, NAP intends to increase the country’s food production in order to meet rising domestic demand and advance agricultural growth, which will boost rice production’s contribution to national revenue and agricultural entrepreneurship (Murdiyarso, 2000). The main goal of this strategy is to increase production and productivity in order to ensure food security, as well as to discover high-value agriculture, increase supply chain escalation, implement sustainable agricultural practices, and improve human capital, with more participation from the private sector and efficient government support. However, since only 7% of total global rice production is traded, it is critical to increase local rice production to ensure rice supply self-sufficiency. Rice prices are prone to volatility due to supply stability, rising demand, and the limited amount of rice traded on the international market. As a result, contributions from rice bowls in the East Coast Economic Region (ECER) are needed to achieve the country’s rice production selfsufficiency level. Furthermore, government support for the national paddy and rice industries is essential for strengthening relevant agencies, increasing development, and ensuring efficient supply management. Furthermore, the government intends to achieve long-term food security by increasing rice production, which is the primary food source for the majority of the country’s population (Arshad & Hameed, 2010). Table 2.3 demonstrates this product’s role in meeting self-sufficiency goals. However, since the cost of rice

1996-2000

2001-5

2006-10

1976-80

1971-75

1966-70

1961-65

FMyaP1SMyaP2 5MP1 5MP2 5MP3 5MP4 5MP5 5MP6 5MP7 5MP8 5MP9 5MP10 5MP11

Targeted SSL (%)

66

66

2011-20

1991-95

72

71

72

1986-90

70

2011-20

71

65

71

71

65

2016-20

76.3

65

71

75

65

2011-15

76.5

65

1981-85

85

92

87

65

60

90 54

100 90 80 70 60 50 40 30 20 10 0

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2  Recent Research on Climate Change and Food Security

1956-60

Self-sufficiency Level (%)

28

ETP

AFP

Achieved SSL (%)

Fig. 2.4  Self-sufficient level of rice in Malaysia (Arshad, 2017)

production in Malaysia is relatively high, the National Agricultural Policy (1992–2010) will not be able to achieve the country’s self-sufficiency target (Najim et al., 2007). On the other hand, it demonstrates the effectiveness of government assistance and agricultural transformation in rural areas, especially in rice-bowl regions for achieving the desired food productivity levels. If we accept that climate change is real and imminent, how can Malaysia offset the effects of climate change on crop production? What steps should Malaysian policymakers take to ensure that potential rice development improvements are feasible due to climate instability and vulnerability? The issue is that the national policy alternative still has a knowledge gap. Climate change and public understanding remain a mission for politicians and stakeholders (Karahan & Roehrig, 2015) (Fig. 2.4).

2.5  Food Security Policy in Malaysia The Food Security Policy (FSP 2008–2010) was first implemented in Malaysia in 2007 in response to the global food crisis, but it is expired in 2015 (Pingali, 2007). The FSP will most likely be expanded this year as part of the 11th Malaysia Program, which will also include the implementation of the National Agricultural Policy. Because climate change is unfolding badly at the moment, extending related food policies is a critical issue. The FSP is primarily focused on rice production, which requires increasing productivity in order to ensure long-term food security. As a result, government support is needed to achieve food security, which includes fertilizer subsidies, paddy seed prices, paddy production, paddy yield, and rice prices (Baharuddin et al., 2013). The main approaches of the FSP are as follows: (i) Growth of rice production (ii) Rising production and yield

2.6 Food Security and Responses to Climate Change

29

( iii) Strengthen marketing and distribution network (iv) Bumi Hijau program; and (v) Development of discarded areas. Reviewing climate change strategies for major components of food production including rice, animals, and aquaculture, as well as developing implementation processes and methods that can increase food production from each of the subsectors, is critical. Without a clear strategy for implementing climate change policies, there would be a constant risk of food shortages and social unrest. More importantly, a poor or ineffective FSP will result in increased food imports at very high cost, requiring Malaysia to incur additional costs of RM14 billion (Bell et  al., 2009). Despite the fact that Malaysia’s economy is growing thanks to the service, manufacturing, and mining sectors, the country’s food security is still in jeopardy. It was unable to achieve self-sufficiency in most food production due to a lack of agricultural sustainability (Chandra & Lontoh, 2010). Climate change is becoming a critical problem in Malaysia’s desire to achieve long-term food sustainability. Malaysia is vulnerable to the effects of climate change, according to both national and international research (Murad et al., 2008), as revealed by a comparison of meteorological databases from the last two to three decades, which showed that temperature had already risen from 0.7 to 2.6 °C. Furthermore, annual rainfall has decreased by up to 30%, and sea level has risen by 15–95 cm. Climate change has a direct effect on food security, according to some reports (Raza et.al., 2019), which is why the topic of climate change has already piqued the interest of politicians due to its long-term consequences. While the Malaysian government launched the Malaysian Plan on Climate Change (MPCC) in 2009, it has yet to be fully implemented. This may be due to inflexible issues or to a lack of demand for change on the part of the general public. However, since the effects of climate change are having a significant impact on food security, the Malaysian government should strategize the MPCC and Malaysian policy on food security (MPFS) to increase food production (Schmidhuber & Tubiello, 2007). As a strategy, this research proposes a climate adaptation alternative for the country’s desired long-term food security. Although the government has begun to introduce climate change adaptation policies, they have yet to determine which adaptation option or level of adaptation it will implement in the agricultural sector to achieve the highest level of food security in Malaysia. Given the likelihood that the effects of climate change will worsen in the future, certain adaptation options for Malaysia’s targeted food security policy must be identified.

2.6  Food Security and Responses to Climate Change Climate policy responses must prioritize strategies that help to mitigate the possible negative effects of climate change on food production systems, with an emphasis on rural livelihoods in poor developed countries, in order to sustain global and regional food security. A strong emphasis of adaptation or mitigation planning should be on

30

2  Recent Research on Climate Change and Food Security

feeding the hungry and lifting growing numbers of rural farmers in developing countries out of poverty for current and future generations. Since the agricultural sector is completely reliant on biophysical influences, climate change has a direct effect on food security. As a result, it is critical to consider adaptation options that will be successful in combating climate change and minimizing agricultural crop damage. Despite decades of research, much remains unclear about many of climate change’s food security impacts (Wheeler & Von Braun, 2013). To some degree, more evidence will help. For example, as the evidence base grows with further study, gaps in understanding the underlying science, social science, and economics of climate change impacts will diminish. Other uncertainties, however, will remain as a result of climate change predictions, natural climate fluctuations, and future pathways. As a result, this analysis should yield four broad research goals for the future: (i) gathering evidence on the effects of climate change on food access, utilization, and stability dimensions in order to achieve a more holistic understanding of food security; (ii) understanding the indirect impacts of climate change on food security, which will require more comprehensive analytical approaches and sophisticated modeling, including links to the political economy; (iii) improving food security by improving food access, utilization, and stability; and (iv) improving food security by improving food access, utilization, and stability. Since food systems are fundamentally influenced by people and their behavioral responses to real and perceived changes in their local environment, better incorporating human aspects of climate change impacts into food security planning will be critical to adapting to climate change and hunger-fighting efforts. Avoiding deforestation, preserving and managing forests, developing agroforestry for food and energy, regenerating land, recovering biogas and waste, and a wide range of strategies that lead to the conservation of soil and water resources by enhancing their quality, availability, and efficiency of use are just a few examples of desirable policy aims. These strategies are often deeply embedded in local cultures and expertise and are in addition the subject of study, funding, and implementation by major international agencies and nongovernmental organizations (NGOs) (Bruinsma, 2003). They all aim to make production systems more resilient in the face of rising climatic pressures while also providing substantial carbon sequestration or lowering land-­ based GHG emissions. Many of these synergies, however, are also essential for long-term social, economic, and environmental sustainability, though it is important to remember that these synergies are often area and system specific and must be assessed on a case-by-case basis. Under certain conditions, a number of adaptation practices can help to strengthen land mitigation capacity (FAO, 2012). Increased irrigation and fertilization, for example, which are needed to sustain productivity in marginal semiarid regions as a result of climate change, can also significantly improve the ability of soils in those areas to sequester carbon (Beckman, 2011). This is particularly true in Sub-Saharan Africa, where small gains in resource efficiency can have a big impact on crop biomass production while also restoring carbon pools and soil quality. A change from fallow systems to continuous cultivation (including cover crops) would maximize

2.7 Exploring Development Paths: Institutions and Collective Behavior

31

production under the new precipitation conditions while also increasing soil carbon sequestration capacity in scenarios with increased precipitation, particularly at midlatitudes. Some mitigation strategies, on the other hand, may not be conducive to adaptation. Bioenergy and some land conservation programs, for example, will entail activities that create new competition for land and water resources that are otherwise needed for enhancing system resilience and ensuring food production in the face of climate change. Climate change has the potential to stymie progress toward a world free of hunger. Climate change effects on crop production have been shown to have a strong and consistent global trend, which may have implications for food supply. Because of short-term supply fluctuations, the reliability of whole food systems could be jeopardized as a result of climate change. At regional scales, however, the potential effect is less obvious, but climate instability and transition are likely to intensify food insecurity in areas that are already vulnerable to hunger and malnutrition. Similarly, food access and use will likely be influenced indirectly by collateral effects on household and individual incomes, as well as food consumption. The evidence points to the need for significant investment in adaptation and mitigation measures in developing countries in order to create a “climate-smart food system” that is more resilient to the effects of climate change on food security (Vermeulen et al., 2012).

2.7  E  xploring Development Paths: Institutions and Collective Behavior Explorations of social behavior and values are crucial to gaining a better understanding of the human universe in which climate change policies are developed. New institutional theory is particularly important in discussions of institutional genesis and reform because it incorporates a thorough understanding of the normative elements that pervade collective action. This field marks a significant departure from highly logical and structuralist explanations of human actions, acknowledging that, in the collective sense, humans often act on the basis of routines and standard operating procedures, driven by a “logic of appropriateness” (March & Olsen, 2004). This is in stark contrast to a cost-benefit analysis or a “logic of consequentiality” (March & Olsen, 2004). This finding forces a shift in focus away from making a logical, scientific case for the avoided costs yielded by climate change action and toward the need for embedding new norms and values associated with climate change action throughout familiar and established practices and institutional and social habits (as explored through Bourdieu’s concept of enculturation). Indeed, since convictions are more often motivating than traditional rules or rational judgments, affective and cognitive aspects of actions are intricately interwoven (Slovic et al., 2007; Peters & Slovic, 1996; Powell & DiMaggio, 2012; Slovic et al., 2007; Epstein, 1994). In other words, affective reactions may act as inhibitors or enablers

32

2  Recent Research on Climate Change and Food Security

of action, but they also have an effect on decisions that are considered to be based solely on a rational analysis of available evidence. Values, attitudes, and social context are also important antecedents or determinants of actions at the personal level (Kollmuss & Agyeman, 2002; Stern, 2002; Kaiser et al., 1999) and thus can promote or hinder climate change responses.

2.8  Empirical Literature on the Impact of Climate Change Zhai and Zhuang (2012) looked at the long-term agricultural effects of climate change around the world, with an emphasis on Southeast Asia (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) (China). Both studies found that global grain, livestock, and processed food production will shrink by 7.4%, 5.9%, and 4.6% in 2080, respectively, based on a complex CGE model of the global economy and Cline’s business as usual crop productivity projections (Cline, 1996). Climate change would have an effect on all four dimensions of food security: food availability (production and trade), food access, food supply stability, and food utilization (FAO, 2004; Rosenzweig et al., 2002). The relative importance of the different dimensions and the overall influence of climate change on food security will vary across regions and over time and will, above all, be dependent on a country’s overall socioeconomic profile as the effects of climate change take hold. Almost all objective analyses suggest that climate change will have a negative impact on food security (Berg et al. 2013). Climate change will increase developing countries’ reliance on imports, concentrating food insecurity in Sub-Saharan Africa and, to a lesser degree, South Asia (Holt-Gimenez & Patel, 2012). Climate change’s negative effects will particularly affect the poor in developing countries. Many quantitative analyses also suggest that the socioeconomic context in which climate change is likely to develop is more significant than the impacts predicted from climate change’s biophysical changes. Climate change has a variety of effects on agriculture and food production. It has a direct impact on food production through changes in agro-ecological conditions, as well as an indirect impact on income growth and distribution and, thus, demand for agricultural production. Numerous experiments have been conducted with different hypotheses with the aim of quantifying the effects (IPCC, 2007a). “Quantifying the long term Impacts on Food Security” it indicates a set of finndings (Shindell et al., 2012). Higher temperatures in temperate latitudes are expected to favor agriculture primarily: the region theoretically suitable for cropping will expand, the duration of the growing season will lengthen, and crop yields will increase (Shindell et al., 2012). In some humid and temperate grasslands, moderate gradual warming could boost pasture productivity while reducing the need for housing and compound feed. These gains must be balanced against increased frequency of extreme events, such as heat waves and droughts in the Mediterranean, or increased heavy precipitation events and flooding in temperate regions, including the possibility of increased coastal storms (Rosenzweig et  al., 2002); they must also be balanced

2.8 Empirical Literature on the Impact of Climate Change

33

against the fact that semiarid and arid pastures are likely to be reduced (IPCC, 2007a). Climate models predict increased evapotranspiration and lower soil moisture levels in drier regions (IPCC, 2007b). As a result, some cultivated fields may become unfit for cropping, and some tropical grassland may become more arid. Many agricultural pests’ ranges will grow as temperatures rise, and pest populations will be better able to survive the winter and target spring crops. Finally, a number of recent studies have predicted improvements in land suitability, potential yields, and food production based on the current crop and cultivar suite (Oerke et al., 2012). As a result, these forecasts indirectly include adaptation using existing management techniques and crops but do not include new cultivars or biotechnology (Paudel, 2013). These studies are focused on the agro-ecological zone (AEZ) methodology developed by the FAO and the International Institute for Applied Systems Analysis (IIASA) (Fischer, 2005; Parry et  al., 2004; Tubiello et al., 2007).1 However, the same study revealed more pronounced regional changes, with a significant increase in suitable cropland at higher latitudes (developed countries 160 million ha) and a corresponding decrease in possible cropland at lower latitudes (developing countries110 million ha). In developing countries, an even more pronounced change in cropland quality is expected (Schmidhuber & Tubiello, 2007). A major decline in agricultural prime land of 135 million ha is compensated by a rise in moderately suitable land of 20 million ha, resulting in a net decline of 110 million ha (Schmidhuber & Tubiello, 2007). This shift in land appropriate for multiple cropping reflects a shift in quality. Land suitable for double cropping would decline by 10 million to 20 million ha in Sub-Saharan Africa alone, and land suitable for triple cropping would decline by 5 million to 10 million ha. Similar approaches suggest that, as a result of climate change, the greatest declines in suitable cropland are likely to occur in Africa, while the greatest expansion of suitable cropland is likely to occur in the Russian Federation and Central Asia (Fischer et al., 2005). Climate change will have the greatest negative effect on crop production in Sub-­ Saharan Africa, Latin America, and South Asia, with reductions of 30%, 24%, and 20%, respectively (Hertel et al., 2010). Southeast Asia’s effect will be less serious, but still important, at a 17% loss by 2080 (Dai, 2013). Crop production will increase in areas where the impacts on agricultural productivity are minor or favorable. New Zealand has the highest rate, at about 141% (Wardle et al., 2011). This is due to its higher agricultural production as a result of climate change and its economy’s limited crop share. Furthermore, analysis shows that the same cross-region difference exists for livestock and processed food production. In addition, Zhai and Zhuang (2009) demonstrated that all Southeast Asian countries will experience production losses in all crop sectors, with the exception of rice output in Malaysia. Singapore would lose the most aggregate crop yield, while Viet Nam would lose the least, by around 48% and 11%, respectively. With the exception 1  For instance, pioneering work of Fischer et al. (2002) suggested that total land and total prime land would remain virtually unchanged at the current levels of 2,600 million and 2,000 million hectares (ha), respectively.

34

2  Recent Research on Climate Change and Food Security

of Singapore and Thailand, livestock production in the rest of the world will decline. The study also revealed that the expected slowdown in agricultural productivity will have an effect on the countries’ macroeconomic results. True GDP contractions will be seen in all six countries, ranging from 0.3% in Singapore to 2.4% in Thailand. Furthermore, there will be a slight decrease in expenditure and consumption levels. According to the literature, China’s crop production is expected to drop by 0.1%. Wheat production will increase (by 4.2%), while other industries’ output will decrease. Zhang and Verikios (2006) also predicted that China’s crop sector will see higher exports and fewer imports, owing to the country’s relatively lower climate change risk to crop agriculture than the global average. The increase in exports will range from 46.8% for paddy rice to 126.7% for wheat, while imports will decrease by 14.9–34.1%. Crop productivity losses are projected to result in a 1–2% decline in noncrop agriculture, mining, manufacturing, and service outputs, owing to rising input costs and resource diversion to crop agriculture. Mendelsohn et al. (1996) and Seo and Mendelsohn (2008) assessed the effect of climate change on US and South American agriculture, respectively, using the Ricardian model and cross-sectional evidence. Climate has a complicated impact on agriculture, according to Mendelsohn et al. (1994), which is highly nonlinear and varies by season. Higher temperatures are likely to diminish average farm values, whereas higher precipitation is likely to stimulate average farm values, according to projected marginal impacts (except in autumn, which will be the reverse). Mano and Nhemachena (2007) on Zimbabwean agriculture, Kabubo-Mariara and Karanja (2007) on crop and agriculture in Kenya, and Malua and Lambi (2007) on crop farming in Cameroon all support this conclusion. Despite the fact that climate sensitivity differs across farm types, Seo and Mendelsohn (2008) found that both rising temperature and precipitation will be detrimental to South American agriculture (i.e., crop-only, mixed, and livestock-­ only farms). The effect of standardized climate scenarios on agriculture was examined in some studies. Mano and Nhemachena (2007), for example, found that the standardized scenarios of rising temperature by 2.50 and 50 °C and decreasing precipitation by 7% and 14% result in a decrease in net farm revenues across all farms in Zimbabwe. In Cameroon, Molua and Lambi (2007) found that the uniform scenarios of rising temperature of 2.5 and 5 °C will result in $0.65 billion and $1.82 billion in crop net revenues, respectively. Furthermore, they stated that the standardized scenarios of declining precipitation by 7% and 14% would result in a $2.95 billion and $4.96 billion decrease in crop net revenues, respectively. Using the crop land model, Mendelsohn et al. (1994) estimated annual agricultural harm in the US to be in the neighborhood of 4–5% based on the CO2 doubling scenario, which predicts a 50  °F and 8% rise in temperature and precipitation, respectively. However, using a crop-revenue strategy would be marginally advantageous (by around 1% annually). Seo and Mendelsohn (2008) looked at the effect of predicted climate from the Climate Change Capital (CCC) and Parallel Climate Model (PCM) models on South American agriculture. In doing so, PCM scenarios projected that crop-only and mixed farms will lose 23% and 13% of their land value by 2100, respectively. Livestock-only farms, on the other hand, will see a 38%

2.8 Empirical Literature on the Impact of Climate Change

35

increase in production. Using the CCC model’s forecast environment, they projected a far larger drop in farm income across the board. Mano and Nhemachena (2007) also looked at the effect of three Special Report on Emission Scenarios (SRES) climate change scenarios on agriculture in Zimbabwe, namely, Climate Change Model, version 2 (CGM2), Hadley Centre Coupled Model, version 3 (HadCM3), and PCM. As of 2100, they predicted that farm net sales will fall by US$0.8 billion, US$1.3 billion, and US$1.4 billion across all farms. Climate scenarios from CCC and GFDL (Geophysical Fluid Dynamics Laboratory) were used in the analysis by Kabubo-Mariara and Karanja (2007), which predicts a 3.5 and 4 °C rise in temperature, respectively, and a 20% increase in precipitation by 2030 over Kenya. For simulations based on the CCC model, the results projected a 1% (US$3.54/ha) gain in high potential zones but a 21.5% (US$54/ha) loss in medium and low potential zones. Using the GFDL model, the results projected a loss of US$32/ha in high potential zones by 2030, while losses in medium and low potential zones will be US$178/ha. Deressa et  al. (2011) evaluated the effect of climate change on South African sugarcane production under irrigation and dry land conditions using the Ricardian model. They showed that climate change was having a substantial impact on net revenue per hectare in sugarcane farming, with a higher vulnerability to potential temperature rises than precipitation, using time series data from 1977 to 1998. The findings of Kabubo-Mariara and Karanja (2007) on Kenyan crop agriculture are close. Furthermore, Deressa et al. (2011) found that a 20 °C rise in temperature and a 7% increase in precipitation (doubling of CO2) has negative effects on sugarcane yield, similar to the findings of Mendelsohn et al. (1994). This result is also shown to be unequally distributed across the farming types listed. However, the difference is insignificant since dry land farming reduces net revenue per hectare by about 1% more than irrigated farming. As a result, they came to the conclusion that irrigation is not a very successful adaptation measure for reducing the effects of climate change on sugarcane farming. Other research, by Gbetibouo and Hassan (2005), looked at the economic effects of climate change on major South African field crops using the same method. Their study concluded that, similar to Deressa et al.’s (2011) findings on sugarcane farming, field crop production in South Africa would be very sensitive to marginal changes in temperature as opposed to changes in precipitation. Unlike Deressa et al. (2011), however, they argued that switching from rain-fed to irrigated agriculture might be an important adaptation choice for reducing climate-­ change-­related damage to field crops. Kurukulasuriya and Mendelsohn (2008) used a Ricardian model, cross-sectional data from 11 countries in the region, and potential climate scenarios from three Atmosphere-Ocean General Circulation Models (AOGCMs) to validate this finding on African cropland. Furthermore, Kurukulasuriya and Mendelsohn’s (2008) marginal impacts indicate that higher temperatures will increase net revenues from irrigated farms while decreasing net revenues from dry land farms. Higher precipitation, on the other hand, will boost net revenue in both types of farms. In Ethiopia, three separate studies used the same methodology, namely, the Ricardian model. Deressa (2007), on the other hand, looked at the effect of climate change on total agricultural

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2  Recent Research on Climate Change and Food Security

production, while Deressa et al. (2009) and Molla et al. (2008) looked at crop agriculture. According to both teams of researchers, climate variables have a huge effect on net sales per hectare. According to Deressa (2007), a rise in temperature by only a few degrees during the winter and summer seasons reduces net revenue per hectare by US$997.7 and US$177.6, respectively. In the spring and fall seasons, however, it raises net revenue per hectare by US$337.8 and US$1879.7, respectively. According to Deressa et al. (2011), rising annual temperature decreases net revenue per hectare by US$21.61 (though by an insignificant amount). According to Molla (2008), a small rise in annual temperature for the model without adaptation would result in a shift in crop net revenue of −3358.41 birr for Ethiopia’s Nile basin, 3483.25 birr for irrigated farms (though negligibly even at the 10% level of significance), and −5904.97 birr for dry land farms. The shift in crop net revenues for the Nile basin of Ethiopia, irrigated and dry land farms, respectively, is −3127.95, 2275.41 (not significant), and −4485.46 birr for the model with adaptation. Furthermore, Deressa et al. (2009) found that rising precipitation raises net revenue per hectare slightly in the spring season by US$225.1, while decreasing net revenue per hectare by US$464.7, US$18.9, and US$64.2 in the winter, summer, and fall seasons, respectively, although the last two are negligible. However, according to Deressa et al. (2011), increasing annual precipitation has a marginal effect on net revenue per hectare of US$322.75. Molla (2008), on the other hand, showed that it will increase crop net revenues by 322.89 birr, 309.54 birr and 352.68 birr for the model without adaptation while for the model with adaptation the gain amounts 147.45 birr, 147.46 birr and 267.66 birr for Nile basin of Ethiopia, irrigated and dry land farms, respectively. Deressa et al. (2009) and Molla et al. (2008) further revealed that the uniform scenarios of temperature increasing by 2.5 and 5 °C and decreasing precipitation by 7% and 14% are all damaging to agriculture in the country, except that Molla et al. (2008) indicated that a 2.5 °C increase in temperature results in a net gain for the irrigated farms. Furthermore, Deressa et al. (2009) projected that net revenue per hectare would increase by 2050 but decline by 2100, based on forecasted temperature and precipitation values from three climate change models (i.e., CGM2, HaDCM3, and PCM), while Deressa et al. (2011) predicted lower crop net revenue per hectare in both 2050 and 2100. The effect of climate change will intensify over time unless it is mitigated by prudent adaptation measures, according to this report.

2.9  R  elevant Literature Based on National and International Perspectives According to Siwar and Hossain (2009), the effects of both climate change and agricultural practices in Malaysia are commonly seen as being related in a fascinating and circular way. The magnitude of both impacts is difficult to assess because it might necessitate a comparative benefit-cost review, which is beyond the scope of

2.9 Relevant Literature Based on National and International Perspectives

37

this report. The primary goal of this research is to examine the effects of climate change on Malaysian agricultural sustainability and poverty. As a result, the study’s analysis has been established with a focus on appraisals related to climate change and current agricultural practice and policy. Climate change, according to the report, poses a major challenge to agricultural sustainability in Malaysia because it is constantly changing and affecting agriculture in a variety of ways. As a result, accurate measurement of its effects on sustainable agriculture is needed to ensure Malaysia’s long-term agricultural viability. According to Siwar and Hossain (2009), the problems of climate change, agricultural sustainability, and poverty in Malaysia are interconnected. Quantitative analysis of the relationships between these three variables is a complex job that is beyond the scope of this study. As a result, the primary goal of this research is to examine the connections between climate change, agricultural sustainability, and poverty in Malaysia. Questions have been raised that need to be investigated further in order to fully comprehend these connections. The questions were formulated with a focus on appraisals involving the creation and implementation of social policies and activities that are applicable to these three issues. According to the regional Climate Change Adaptation Knowledge Platform, Malaysia is currently able to handle climate change impacts due to its strong environmental protection systems, economic policies, and successful programs such as food production and poverty eradication. However, it is important to note that these initiatives only counter the danger of environmental change, not the threat of climate change, which has a different stage of long-term effects for Malaysia. Climate change may also trigger national and international distribution disputes in Malaysia, such as in fisheries, exacerbating the region’s already difficult problems. Given the foregoing considerations, for some areas of interest: Climate change is caused by deforestion, as well as the destruction of marine and freshwater ecosystems. Increases in many hydrometeorological and geomorphologic events as a result of climate change: Reduced capacity for food production and other economic structures caused by climate change; ethics and climate change: questions of justice, such as displacements caused by environmental degradation and migration, deprivation and livelihood of some subsistence activities, and the protection and security of vulnerable sectors of society. Adger (2007) discussed the history of vulnerability to environmental change as well as the difficulties that current vulnerability research faces in combining resilience and adaptation. Vulnerability refers to a person’s vulnerability to harm as a result of exposure to pressures associated with environmental and social change, as well as a lack of adaptability. Theories of risk such as entitlement loss and theories of danger are examples of antecedent traditions. Each of these fields has led to current formulations of environmental change vulnerability as a function of social-­ ecological structures linked to resilience. Vulnerability to the effects of climate change has been studied throughout history, in both antecedent and successor cultures. Vulnerability research faces many challenges, including developing rigorous and reliable interventions, incorporating diverse approaches that include risk and vulnerability expectations, and

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incorporating governance research on processes that mediate vulnerability and foster adaptive action and resilience. These difficulties are shared by the realms of vulnerability, adaptation, and resilience, and they serve as common ground for coherence and integration. The need to explain food insecurity, civil war, and social upheaval prompted research on entitlements in livelihoods. Explaining commonalities between seemingly different forms of natural disasters and their effects on society led to research on the social impacts of natural hazards. However, it is clear that these phenomena (entitlement loss leading to famine and natural disasters) are not mutually exclusive. While severe climate events such as drought or flood can cause famines, vulnerability researchers have increasingly shown that disease, conflict, and other factors are much more likely to cause famines and food insecurity (Sen, 1981; Swift et  al., 1997; Bohle et al., 1994). Vulnerability explanations based on entitlements focus almost exclusively on the social realm of institutions, well-being, and important variables such as class, social status, and gender, while vulnerability research on natural hazards developed an integrated knowledge of environmental risks with human response, drawing on geographical and psychological perspectives in addition to social parameters of vulnerability. Food insecurity is explained as a series of interconnected economic and institutional variables by so-called entitlement theory. Individuals’ entitlements are the real or future resources they have based on their own production, properties, or mutual agreements. Food insecurity is therefore a product of human action that can be avoided by changes in behavior and political interventions. Vulnerability arises from systems that humans actively participate in and can almost always avoid. The theory of entitlements as a cause of famine was established in the early 1980s (Sen, 1981), and it displaced previous beliefs that famine was caused by a lack of food supply due to drought, flood, or pest. Instead, it concentrated on the actual demand for food, as well as the social and economic means of consuming it. Climate change is a transnational problem, according to Koh and Bhullar (2010), but adaptation steps are typically developed at the international, national, and local levels. This pattern is more common in developing countries, such as those in the Association of Southeast Asian Nations (ASEAN), which are the most vulnerable to climate change’s effects. The developments in the ASEAN region, at both the regional and national levels, are examined and analyzed in this paper. It focuses on (i) the various types of adaptation interventions and the value of mainstreaming; (ii) forecast scenarios and their related impacts; (iii) adaptation within the international climate policy framework; (iv) the institutional and policy framework’s key features, highlighting potential adaptation needs and options for the region; and (v) policy implications. Adaptation has been described in several different ways. Adaptation, in essence, refers to the actions taken in response to climate change, either to mitigate the negative effects or to take advantage of the opportunities presented by such changes. Adaptation strategies may be reactive or proactive. In response to existing climate variability and observed impacts, reactive adaptation steps are introduced. Anticipatory adaptation steps, on the other hand, are implemented prior to the

2.9 Relevant Literature Based on National and International Perspectives

39

occurrence of impacts in order to minimize potential risk exposure. The introduction of anticipatory steps is difficult given the uncertainties surrounding climate change, since they necessitate in-depth information and awareness about climate change. Brunei, Cambodia, Indonesia, Laos, Myanmar, Malaysia, the Philippines, Singapore, Thailand, and Vietnam are members of ASEAN, which was established in 1967 (AMCs (ASEAN Media Cooperation)). Climate change has different impacts, adaptive capabilities, and vulnerabilities in different areas. Several factors have contributed to the magnitude of climate change impacts in this area. For starters, a dense concentration of people and economic activity along long coastlines is vulnerable to sea level rise. Second, climate change’s physical effects are likely to be unevenly distributed. Third, in terms of national income and jobs, the population is heavily dependent on climate-­sensitive sectors such as agriculture, fisheries, forestry, and natural resources. Fourth, the high rate of poverty in the area makes people more vulnerable. Fifth, the countries’ financial, technical, and institutional capacities are small. In Austria, Bednar-Friedl (2013) created an integrated modeling system to explain the need for adaptation and its economic consequences. They concentrated on the two climate-vulnerable industries of agriculture and tourism. High-resolution climate change simulations derived from four regional climate models are coupled with comprehensive sectoral models for agriculture and tourism in the integrated modeling system. The results of the tourism and agriculture models were combined into a computable general equilibrium (CGE) model of the Austrian economy to account for the feedback effects on the rest of the economy. The options for adaptation are the subject of a second emphasis. Although agriculture has long been prepared to respond to climatic change and is thus an example of largely autonomous adaptation, winter tourism is dependent on snow availability, necessitating not only larger-scale adaptation but also targeted policy responses, such as increasing artificial snow making capacities. A third emphasis is on model validation and reliability, as both climate scenarios and economic growth over time scales applicable to climate change research are fraught with uncertainty. This research, on the other hand, examines the uncertainties that are present in the overall modeling method, ranging from climate scenarios to economic modeling. According to Ho and Ching (2008), the Green Revolution resulted in a transition from diversity to monocultures. Many traditional, local varieties were discarded and became extinct when farmers chose to plant Green Revolution crop varieties and raise new breeds of livestock. Agricultural biodiversity, on the other hand, is critical for long-term food protection since it provides insurance against crop and livestock disease outbreaks and increases rural livelihoods’ long-term resilience to adverse patterns or shocks (Pimbert, 1999). In recent years, the Green Revolution model’s most important claims of achievement, its efficiency gains, have proven difficult to maintain and, in some cases, have become exhausted. The yield patterns from long-­ term trials performed on experiment stations, such as the International Rice Research Institute’s (IRRI) long-term continuous cropping experiment, are the best example of this. The aim is to monitor maximum yields over time while maintaining constant input levels and crop management practices. Even with the best available cultivars

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and scientific management, rice yields are declining over time, even though input levels remain constant (Pingali, 2007). Since input levels do not remain constant over time, decreasing yield patterns are seldom seen at the farm level. However, in areas where intensive rice monoculture has been practiced for the past two to three decades, stagnant yields and/or declining partial factor productivities, particularly for fertilizers, have been observed, as have declining total factor productivities. Furthermore, countries with higher cropping intensities have a faster rate of yield deceleration (Pingali, 2007). Intensive rice monoculture systems, according to farm-level evidence from Asia’s rice bowls, lead to declining input productivities over time (Pingali, 2007). Farmers have been discovered to use rising quantities of inputs over time in order to maintain the yield gains achieved during the Green Revolution years. The following changes occur as a result of intensive rice monoculture in the lowlands: (i) rice paddies flooded for the majority of the year without a sufficient drying period; (ii) increased dependence on inorganic fertilizers; (iii) asymmetry of planting schedules; and (iv) greater uniformity of cultivars. The aforementioned modifications have considerable ecological costs in the long run due to negative biophysical impacts (Pingali, 2007). The buildup of salinity and water logging, decreasing soil nutrient status, increased occurrence of soil toxicities, and pest buildup and decreased ecosystem resistance to pest attacks are all negative biophysical effects that have reduced productivity. According to Pingali (2007), intensive rice monoculture leads to the deterioration of the paddy resource base and, as a result, decreasing productivities. According to Alam et al. (2011), Malaysia is one of the most vulnerable countries to climate change. Climate change has a negative effect on agricultural sustainability and relevant livelihood sustainability in the region. A cautious adaptation approach is critical for adapting to climate change. Several countries have adopted various adaptation policies based on their socioeconomic and geographical circumstances. Malaysia must weigh many important factors when determining its adaptation strategy. This study examines issues concerning Malaysian farmers’ adaptation to climate change and makes a few recommendations that will aid policymakers in developing agricultural adaptation policies for climate change. Since adaptation must be done at several levels, including at the household and community level, and many of these projects are self-funded, it is impossible to assign precise costs to it (Stern, 2007). Technological advancements, government initiatives, farm production methods, and farm financial management are all examples of agricultural adaptation options (Smit & Skinner, 2002). As a result, it has been proposed that a planned and constructive adaptation alternative be prepared to ensure that the economic, social, and environmental systems continue to work properly (Sarker et al., 2012). Following that, concrete policy guidelines for various stakeholders are suggested to better deal with the issue. Al-Amin et al. (2010) discussed policy options for reducing climate-related vulnerability in Malaysian rice farming. Based on observational records of interannual variability in precipitation and worming climatic influences, a study of impacts on climate change and vulnerabilities was conducted. Global circulation models (GCMs) were used in conjunction with crop modeling software like Decision

2.10 Models to Assess Impact of Climate Change

41

Support System for Agro-technology Transfer (DSSAT) to represent a variety of possible climate scenarios. The method used is a bottom-up policy approach, concentrating on the vulnerability of Malaysian rice agriculture in economic conditions and considering a wide range of possible climate outcomes. The study examines the Malaysian rice agriculture sector from both a climate and economic standpoint, quantifying the merits of the predicted simulation and providing insight into the essence of the tradeoff between climate fluctuations and the probability of a decline in rice cultivation earnings over the next 40 years, from 2020 to 2060. The forecasts show the possible future changes and uncertainties in rice production, as well as a potential direction for developing investment strategies to minimize vulnerabilities and uncover priorities for Malaysia’s future agriculture. This study’s findings can be applied to climate-related agriculture policies in Malaysia and elsewhere. Agricultural practices and environment are inextricably linked, with mutually reinforcing effects. Climate change and agricultural practices are commonly seen as being linked one to another in a circular manner in Malaysia. Because of its global distribution and the clear linkages and dependencies of the climate and environmental factors, climate change has the greatest impact on agriculture compared to other economic sectors. At both the macro and micro scales, the effects of climate change on agricultural development have a bearing on the socioeconomic dimension. The most common processes directly influencing the relationship between agriculture and climate change are floods and droughts.

2.10  Models to Assess Impact of Climate Change Climate change’s economic effects are becoming increasingly quantifiable. Until 1999, however, no research had been done explicitly on developing countries (Mendelsohn & Dinar, 1999). While more studies dedicated to developing countries have emerged since then, Ethiopia has only had a few national-level studies. As a result, little is understood about how climate change would impact the country’s agriculture and, as a result, its economy. Researchers have used partial equilibrium or general equilibrium methods to determine the possible economic impacts of climate change2 (Deressa et al., 2011; Zhai & Zhuang, 2009; Deressa et al. 2009).

2  Partial equilibrium models are based on the analysis of part of the overall economy such as a single market or subsets of markets or sectors, assuming no interrelationship among sectors. However, general equilibrium models are analytical models, which look at the economy as a complete, interdependent system, thereby providing an economywide prospective analysis capturing links between all sectors of the economy (Zhaiand Zjuang, 2012).

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2.10.1  Partial Equilibrium Models To assess the effects of climate change on agriculture, three basic partial equilibrium approaches have been established, including crop simulation models, AEZ models, and Ricardian models (Mendelsohn & Dinar, 1999; Kurukulasuriya & Mendelsohn, 2008).

2.10.2  Crop Simulation Models Crop simulation models, also known as agro-economic models, depend on controlled experiments in which crops are grown in a field or laboratory setting and crop yield responses are estimated for various potential climate and CO2 levels (Zhai & Zhuang, 2009). Since other improvements in farming methods are not permitted across experimental settings, the variations in results are attributed to differences in the variables of interest, such as temperature, precipitation, and CO2 levels. The yields are then fed into economic models that forecast total crop production, costs, and net revenue (Mendelsohn & Dinar, 1999). Since each crop necessitates rigorous testing, almost all crop simulation studies to date have concentrated on the most important crops (mostly grains). Furthermore, the forecasts in these models do not take into account farmers’ adaptation to changing climate conditions. As a result, they appear to exaggerate the effects of climate change on agriculture (Mendelsohn & Dinar, 1999; Seo & Mendelsohn, 2008). Furthermore, such tests are expensive, so only a few places can be checked. As a consequence, in developing countries with few testing sites, the findings of these models may not be generalizable (Molla et al. 2008).

2.10.3  Agro-Ecological Zone Models The crop suitability method (also known as an AEZ model) is used to assess the suitability of different land and biophysical attributes for crop production. The model’s first task is to divide existing land into smaller units based on the duration of the growing season (determined by temperature, precipitation, soil characteristics, and topography differences) and climate. This method considers crop characteristics, current technology, and soil and climate factors when assessing land suitability for crop production (FAO, 1996). The incorporation of the aforementioned variables made it possible to identify and distribute potential crop-producing lands. This model can be used to forecast the effect of changing climatic conditions on potential agricultural productivity and cropping patterns since climate is included as one of the determinants of land suitability for crop production (Molla et al., 2008).

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Researchers must specifically account for farmers’ adaptation to changing climate conditions in these models, just as they must in crop simulation models (Mendelsohn & Dinar, 1999). They also use crop yield simulation (rather than actual crop yields) to determine the potential production ability of various AEZs. Furthermore, the model’s additional issue remains the inability to predict final outcomes without specifically modeling all related components. As a result, ignoring a single major factor will have a significant impact on the model’s predictions (Mendelsohn & Tiwari, 2000).

2.10.4  Ricardian Models Mendelsohn et al. (1994) created the Ricardian model to investigate the effect of climate change on agriculture in the United States (Mendelsohn et  al., 1994; Mendelsohn et al., 1996; Deressa et al., 2007). Because of his original observation that the value of land would represent its net productivity under perfect competition, it is named after David Ricardo (1772–1823). (Deressa et al., 2007; Kabubo-Mariara & Karanja, 2007; Molua & Lambi, 2007; Kurukulasuriya & Mendelsohn, 2008). By regressing farm output (land values or net revenue) on environmental and other socioeconomic factors, this model has been widely used to calculate the marginal contribution of environmental (and other) factors to farm income (land values) (Mendelsohn et al., 1994; Mendelsohn & Dinar, 1999; Deressa et al., 2007). It is widely adopted and used in countries such as Brazil, India, the United States (Mendelsohn & Dinar, 1999; Deressa et al., 2007), and some African countries such as Burkina Faso, Cameroon, Egypt, Ethiopia, Kenya, Senegal, South Africa, Zambia, and Zimbabwe (Mendelsohn & Dinar, 1999; Deressa et al., 2007). The Ricardian model, unlike the other two approaches, takes into account farmers’ adaptation to changing local climate conditions. Farmers are mitigating risks, and it is reasonable to believe that they can respond to climate change by changing their crop mix, planting and harvesting dates, and a variety of other agro-economic activities, among other things (Mendelsohn & Dinar, 1999; Deressa et al. 2009). Furthermore, the model allows for a comparison of with and without adaptation scenarios (Mano & Nhemachena, 2006). Another benefit of the model is that it can be used at a lower cost than other models because secondary data on climatic production and socioeconomic factors can be collected more easily on cross-sectional sites (Deressa et al. 2009). However, there are several criticisms of the Ricardian model. For starters, it is not based on a well-controlled experiment conducted across farms. Farms can vary across space for a variety of reasons that are not included in any model. As a result, no guarantee can be provided that all variables have been included in the analysis; some might not even be measured (Cline, 1996; Mendelsohn & Dinar, 1999). Second, since it is a partial equilibrium analysis, it does not account for price variations; all farms face the same costs, resulting in a bias in welfare estimates (Mendelsohn et al., 1996; Cline, 1996). Finally, it is flawed because it ignores the

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effects of carbon fertilization, instead relying solely on precipitation and temperature (Cline, 1996; Mendelsohn & Tiwari, 2000). CGE simulations combine the abstract Walrasian general equilibrium structure formalized by Arrow and Debreu with practical economic data to solve numerically for the levels of supply, demand, and price that sustain equilibrium across a range of markets (Peterson, 2003; Wing et al., 2005). It is “computable” in the sense that, based on equations describing the economy and numerical values for the parameters and exogenous variables, an explicit numerical solution for all endogenous variables in the model can be computed (Peterson, 2003). Despite their widespread economic applications, some economists regard them as a so-called black box whose results cannot be linked to any specific features of their database or input parameters, algebraic structure, or solution form (Wing et al., 2005). However, since climate change affects various sectors of the economy directly or indirectly, the dynamic interactions between them must be examined in order to determine its effect on agriculture and, by extension, the entire economy. It is a CGE model capable of elucidating certain interactions between agriculture and other sectors of an economy, which is the model’s strongest feature (Zhai & Zjuang, 2009). A CGE model also has the benefits of theoretical continuity and a large amount of flexibility in terms of aggregation changes (Peterson, 2003). This study used a CGE model to create a more accurate, practical, and consistent image of the economic system (Böhringer et al., 2012).

2.11  Adaptation Policy for Food Security Since adaptation must be done at several levels, including at the household and community levels, and many of these projects are self-funded, it is impossible to assign precise costs to adaptation (Stern, 2007). Technological advancements, government initiatives, farm production methods, and farm financial management are all examples of agricultural adaptation options (Smit & Skinner, 2002). As a result, it has been proposed that a planned and constructive adaptation alternative be prepared to ensure that the economic, social, and environmental systems continue to work properly (Alam et  al., 2012). Following that, detailed policy proposals for various stakeholders are suggested in order to better cope with the situation (Sage, 2013; Griggs et al., 2013; Winn et al., 2011).

2.11.1  Levels and Approaches of Adaptation for Malaysia While adaptation is not a replacement for mitigation, there are reasons to treat it as a response step. Because of past pollution and the climate system’s persistence, mitigation efforts would never be able to prevent a certain degree of climate change (IPCC 2007a; Vermeulen et al., 2013; Pittock, 2013). Furthermore, although most

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adaptation practices have an immediate impact, mitigation effects can take decades to manifest. Adaptation eliminates the risks associated with current climate instability as well as future climate change risks, while mitigation only addresses future risks. Adaptation strategies may be implemented on a local or root level with the participation of a significant number of stakeholders, while mitigation takes place at the decision-making level. Climate conditions are exogenous variables that are immitigable in a timely manner in today’s environment, so adaptation is the most suitable way to cope with the system properly. Different nations have taken various approaches to dealing with climate change. Nepal uses a community-based adaptation approach to weather-related disasters, a microfinance system through a special insurance scheme to deal with rising flash floods, and structural adaptation to deal with flash floods. Mongolia adopts a policy structure for climate change adaptation strategies for Mongolian rangelands at multiple scales, as well as risk communication at multiple levels to raise public awareness. By efficiently communicating climate threats and adaptation initiatives, India promotes the incorporation of adaptation strategies into developmental policies. Climate change adaptation is being mainstreamed in watershed management and upland cultivation in the Philippines. Bangladesh adopts a participatory approach to climate risk assessment and the implementation of local adaptation action plans, as well as community-based practices to respond to changing ecosystem conditions (Table 2.4). Malaysia is working on a strategy to address looming negative climate effects. It acknowledges adaptation as a critical component of policy responses to climate change, as expressed in the basic principles of Malaysia’s Second National Communication to the UNFCCC Project (NC2): integration with country’s development priorities (poverty alleviation, food security enhancement, action plans under MEAs (Multilateral Environmental Agreements)); reversing patterns that increase maladaptation and risk to human populations and natural systems; ongoing reevaluation of existing strategies to improve the robustness of infrastructure designs and long-term investments; societal understanding and preparedness for future climate change (from policymakers to local communities); increased knowledge of factors that help or hinder the adaptability of vulnerable populations and natural systems; focus on assessing the flexibility and durability of social and natural systems; instead of a reliance on the availability of high-quality data, rely on a thoughtful evaluation involving a comprehensive stakeholder process (Glick et  al. 2011; Adger et al., 2013). Malaysia should concentrate on a few issues while designing an adaptation strategy. IPCC (2007b) mentions a few issues when discussing adaptation assessment, which is described as “the process of identifying and evaluating options for adapting to climate change based on criteria such as availability, benefits, costs, effectiveness, performance, and feasibility.” Yohe and Tol (2002) suggests that policymakers should pay attention to the following determinants of adaptation capacity: the spectrum of available technical options for adaptation; the availability of resources and their distribution among the population; the structure of critical institutions, the derivative allocation of decision-making authority, and the decision criteria that

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Table 2.4  Selected crop studies for South and Southeast Asia

Study Rosenweig et al. (2004)

Scenario GCM’s

Qureshi and Hobbie (1994)

Average of 5 GCMs

Parry et al. (2004)

GISS

3 GCMs Matthews et al. (1995a, b)

Geographic scope Pakistan India Bangladesh Thailand Philippines

Yield impact (%) −61 to +67 −50 to +30 −6 to +8 −17 to +6 −21 to +12

Other comments UKMO, GFDL, GISS and + 2 °C, +4C and ±20 °C precipitation, range is over sites and GCM scenarios with direct CO2 effect scenarios W/O CO2 and w/ adaptation also were considered; CO2 effect important in offsetting loses of climate-only effects; adaptation unable to mitigate all losses GCM’s included UKMO, +10 Bangladesh Rice Decrease GFDLC, CSIR09, CCC and Wheat India BMRC; GCM results sealed to −3 Rice Indonesia represent 2010; included CO2 Soybean −20 Pakistan −40 Philippines Maize effect −60 to Wheat Sri Lanka −10 Rice Decrease Rice Soybean −6 Coarse −3 to +1 Decrease grain Coconut Decrease approx. 4 Low estimates consider Indonesia Rice adaptation; also estimated overall Soybean −10 to increase loss of farmers’ income ranging Maize from US $10 to US $150 annually −65 to −25 Maize yield affected by reduced −22 to Rice Malaysia radiation (increased clouds); −12 Maize Thailand variation in yield increases; range −22 to Oil-­ sites across scenarios −10 Palm Rubber Increase −15 Rice −5 to +8 −5 to +8 Range across GISS, GFDL and Rice −3 to India UKMO, GCM scenarios and crop +28 Bangladesh models; included direct CO2 −9 to Indonesia effect; varietal adaptation was +14 Malaysia +6 to +23 shown to be capable of Myanmar +2 to +27 ameliorating detrimental effects of Philippines temperature increase in currently −14 to Thailand high-temperature environments +22 −14 to −14 −12 to +9 Crops Wheat Wheat Rice Rice Rice

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would be used; the stock of human capital, which includes education and personal security; the stock of social capital, which includes the definition of property rights; the system’s access to risk spreading processes, such as insurance; decision makers’ ability to manage information, as well as the processes through which they determine which information is credible and their own credibility (Below et al. 2012; Fankhauser, 2013) (Table 2.5).

2.11.2  G  overnment Policies, Challenges, and Actions for Food Security at National Level To ensure adaptation at all levels, the government, as the policy- and law-making authority, must play the most influential role. The government’s primary duty is to provide adequate resources for farmers to adapt to climate change and to try to make them self-sufficient rather than reliant on subsidies. To control farm-level production practices and financial management, government bodies must carefully identify their subsidy supports and incentive programs. Agricultural policies and investments must be more strategic in this regard (Alam et al., 2012). Furthermore, these programs must be established to ensure that the affected groups – individual farmers or farms – receive compensation, minimum income security, and insurance coverage. Even though Malay farmers’ productivity is lower than that of other ethnic groups, the government has set aside a certain amount of land for them (Alam et al., 2012). It also poses a challenge to the country’s ability to achieve self-sufficiency in paddy production. At the same time, because of Chinese farmers’ high productivity, if the government allots more land to them, it would create a social imbalance. As a result, the government should implement policies aimed at assisting Malay farmers

Table 2.5  Cases of adaptation according to response time and main sector in charge (Gagnon-­ Lebrun & Agrawala, 2006)

Main sector in charge of response

Private sector

Public sector

Response time Preadaptation Use of private insurance market Private R&D investment

Use of early warning system Construction of public infrastructure (irrigation system) Communication of risks Use of subsidies Publicly available R&D

Postadaptation Change of crop cultivation and applicable agricultural techniques Regulation of insurance market Verification of adaptation options of the minimum expense Recovery from aftermath of disasters Compensation for consequences of impacts Insurance contract Compensation system Subsidies and support

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in increasing their productivity through unique training or education initiatives, public awareness campaigns, or additional incentive programs. In light of current government policy, production practices are crucial. The region (Kedah State) has been designated solely for paddy production by the government. However 85.5% of Malaysia’s total paddy production is planted in Peninsular Malaysia (Firdaus et al. 2013). This has many ramifications. Farmers are not permitted to choose their own crops, despite their proclivity to grow their preferred crops (Alam et al., 2011). Furthermore, land loss is widespread in this region due to monocropping. Crop rotation and crop variety are needed here, based on soil suitability, to preserve land fertility and reduce the impacts of climate change. The government must ensure appropriate resource distribution and adequate infrastructural and informational support. It must also establish programs to manage the effects of the use of all forms of fresh water supplies, as well as their conservation. Other important considerations to consider include agricultural wages, land-lease system and cost, maximum farm size, and so on (Alam et al., 2011). These factors are critical for small farmers’ long-term viability, poverty reduction, and income inequality reduction (Alam et al., 2011). The government’s focus on these factors would help boost overall efficiency, allowing for self-­sufficiency or near self-sufficiency, as well as food security (Alam et al., 2011). Chemical fertilizers are currently provided by the government to farmers in order to boost productivity. Government policy should be environmentally friendly, with more subsidies going to organic fertilizers than chemical fertilizers. Furthermore, technical advancement should be prioritized because technology has been shown to improve paddy yields (Alam et al., 2012). To reap more benefits in the future, the government must invest more in and subsidize more technology. Barriers to adaptation, such as ecological, financial, structural, and technical barriers, as well as knowledge and cognitive hurdles, must be considered by policymakers during the planning process. Other critical concerns that must be addressed include stakeholders who might be underinformed about climate change needs and potential solutions (Eisenack et al., 2006, 2007). Farm-level growth is hampered by an unpredictable future, which obstructs the adoption of adaptation policies (Behringer et al., 2000; Brown et al., 2007), and the policy deals with various overlapping interest groups. Climate change’s effect on changing social conditions must also be understood by policymakers. Different countries take different approaches to climate change adaptation based on their socioeconomic trends. Malaysia is currently deciding on its adaptation strategy. It should carefully consider its adaptation strategy in light of climate change and potential socioeconomic vulnerability among various stakeholders at various levels. Farmers, for example, need more comprehensive government health-care assistance in the face of climate-related illness, as well as preparation, guidance, and recommendations in the face of climate change adaptation (Alam et al., 2011). It must also understand climate change adaptation as a risk management strategy rather than attempting to maintain or restore current conditions. Climate change issues, as well as their adaptation and mitigation, must be addressed as part of Malaysia’s overall growth strategy. Furthermore, the government must play a leading role in terms of coordination and cooperation among

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various government agencies as well as external parties. To incorporate climate change problems into current agricultural policies and development projects, environmentalists, lawmakers, economists, and agricultural policymakers must work together. Finally, Malaysia desperately needs a proper mitigation strategy to prevent future climate change and to regulate pollution and emissions. Present climate change predictions are riddled with uncertainty. Furthermore, these forecasts do not take into account the model’s dynamic socioeconomic relationships. Furthermore, due to the emissions from industrial farming, the agricultural sector will need to include mitigation policies in the future. In the future, many projects, such as the Clean Development Mechanism (CDM) to offset carbon emissions, will be needed for both agriculture and wider development activities. As a result, policymakers must adopt a versatile approach.

2.11.3  F  ood Policy Measures and Challenges at International Level Modifying a number of main market distortions and market structures at the international level, which serve as a disincentive to the transition to sustainable agricultural practices at the national level in developing countries, is a major challenge. This is about agricultural production in developed countries and their exports to developing countries being heavily subsidized. For the years 2003–2005, the average support to agricultural producers in the major developed countries as a percentage of gross farm receipts was 30%, amounting to nearly $1 billion per day (Gagnon-Lebrun & Agrawala, 2006; Ignaciuk & Mason-D’Croz, 2014). These agricultural policies in developed countries cost developing countries about US$17 billion per year, which is five times the current amount of Official Development Assistance (ODA) to agriculture (Anderson et al. 2006). It is difficult to imagine how developing country producers will adopt a paradigm shift toward sustainable agricultural production at the necessary massive scale, both in depth and width, as long as these conditions persist and are not substantially altered by the current Doha Round of World Trade Organization (WTO) negotiations. The removal of “perverse” subsidies should be followed by the implementation of appropriate carbon pricing tools and policies. Carbon or energy taxes, as well as other fiscal instruments, should be investigated for agriculture, which has a large number of relatively small producers, to create the right incentives for innovation and desired improvements in production and consumption patterns and methods. This must be complemented by foreign trade policy reforms that are truly supportive of ecological agriculture. According to Chang and Jung (2010), this should include improved market access for developing world produce, policy room to help the agricultural sector, enable expansion of local food production, and the use of effective instruments to promote food security, farmers’ livelihoods, and rural growth, in addition

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to real reductions in domestic support in developed countries (Hoffmann, 2011). The global market domination of a few firms that control the world’s crop, agrochemical, and biotechnology markets is, however, extremely problematic. In 2004, the top four agrochemical and seed firms (the concentration ratio of the top four, or CR4) had a market share of 60% for agrochemicals and 33% for seeds, respectively, up from 47% and 23% in 1997 (World Bank, 2008). These corporations have a vested interest in keeping agriculture dependent on external inputs, monoculture focused, and carbon-intensive. Furthermore, international supply chains, which are often led by major food processors or retailers, must rethink their sourcing from scale-focused monocrop production in favor of complex multicropping and integrated livestock and crop farming systems (Ferede et  al., 2013). It remains to be seen whether these issues can be successfully resolved. Agriculture needs a refocus in international development cooperation, as well as a U-turn in assistance to the industry. Agriculture’s share of ODA has dropped dramatically over the last two decades, from about 18% in 1979 to 3.5% in 2004. In absolute terms, it fell from about US$8 billion in 1984 to US$3.4 billion in 2004. Multilateral financial institutions, especially the World Bank, saw the biggest drop (World Bank, 2008). Much more funding should be directed toward improving the agricultural innovation and extension system for environmentally friendly farming practices and infrastructure. Furthermore, smallholders must once again be a priority for development assistance. In this context, there is a need to democratize agricultural assistance and research at both the national and international levels. Food and agriculture research often ignores the beliefs, desires, expertise, and concerns of those who supply the food, instead serving powerful commercial interests, such as multinational seed and food retailing corporations. Agricultural research and assistance must refocus on what farmers and food consumers want and need. Farmers and other citizens must play a critical role in identifying agricultural research and food policy strategic goals. The process of methodological production of effective mitigation and adaptation techniques and steps, according to Stolze (2012) and Herrero et al. (2010), is expensive and needs multifaceted experts. As a result, they see the need for an international instrument that offers a global platform for agricultural action and support, such as renaming the IAASTD the IPCC for Agriculture. The international community can look into the benefits and drawbacks of including land-use changes and terrestrial carbon opportunities in the Kyoto Protocol’s flexibility mechanisms. Recent discussions under the CDM on better utilizing the capacity of soil carbon sequestration and above-ground carbon in agriculture run the risk of bringing carbon trading to new levels of absurdity by extending no-till monocultures, tree plantations, and minor technical changes in the livestock industry. Better management of synergies, tradeoffs, and leakage involved in GHG mitigation from land-based sources and sinks could be achieved by transitioning to a holistic approach of all land uses. This will necessitate the development of terrestrial carbon baselines, a thorough land-use GHG accounting system, and adequate calculation, monitoring, and verification tools over time (FAO, 2009a). Since these are difficult,

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expensive, and time-consuming challenges, it is unclear whether an international agreement on these issues will be reached in the near future. New financing systems, according to FAO (2011), should be developed with wider, more versatile approaches, incorporating various funding sources and innovative payment/incentive/delivery schemes to meet producers, including smallholders. A staggered approach with aggregating modalities for greater cost-effectiveness, front-loaded payments secured by insurance or performance bonds, simpler laws, and acknowledgement of community/individual, formal/informal property rights, according to FAO, are some design elements that appear to hold promise in this regard (FAO, 2009b). In this context, it may be worthwhile to expand the current financing reach or create an agricultural counterpart to the enhanced Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD+) program. Because agriculture and bioenergy have an effect on forests, this program already exists. A REDD+ choice can include market- or non-market-­ based instruments and can be based on results against predetermined criteria or GHG quantification. Finally, agricultural product markets, such as the implementation of agricultural product requirements and labeling related to GHG mitigation benefits, may be a possible means of reaching agricultural producers with some additional carbon funds (e.g., product carbon footprint standards). The introduction of such approaches can be greatly aided by building on the institutions and lessons learned from the creation of organic and sustainable agricultural-products marketing platforms for smallholders. However, whether product carbon footprint labeling is a blessing or a bane for farmers in developing countries will be determined by the methodologies used in measuring GHG emissions. Furthermore, it is unclear whether or not product carbon footprint labeling or regulations would be able to move beyond a niche market.

2.12  L  iterature Gap to Study Impacts of Climate Change on Food Security The numerous negative effects of climate change on food security are summarized in this section. Many studies have highlighted the negative net impact of climate change on agriculture. Most studies have shown that Sub-Saharan Africa is one of the most vulnerable regions to climate change, with the majority of people reliant on climate-sensitive agricultural systems. In terms of negative results, the other regions are more or less the same. Thus, it is clear that climate change has the potential to affect the three components of food security (food supply, food access, and food use), but only the food production (availability) component has been thoroughly researched, whereas the other two lag behind. A review of the literature on food security issues revealed that food production alone would not be able to contribute to overall food security because food production is dependent on a variety of

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climatic conditions and factors. Many reports in particular define negative effects based on forecasts for various time segments and suggest that the amount of rainfall is decreasing in trend and will continue to decrease in the future, with some uncertainty in its amount. While a mild rise in temperature (between 1 and 3 °C) may benefit food production in temperate areas, it may have a negative effect in tropical and seasonally dry areas. As a result, once the temperature rises above 3 °C, it has a negative impact on food production (availability) in all regions, particularly in areas where well-established adaptation strategies are lacking. Furthermore, due to Malaysia’s complex relationship with climatic influences, climate change adaptation issues on food accessibility are understudied in comparison to mitigation in many developed countries, including Malaysia. Finally, this research revealed a scarcity of studies on adaptive capacities in developing countries that represent the introduction of a certain degree of adaptation alternative that can be used as a benchmark for measuring food security or food sustainability. As a result, this research focused entirely on adaptive capacities and adaptation issues. While this study is primarily focused on Malaysia, it can be applied to other developing countries with similar ecological conditions in order to achieve effective CCFS adaptation options.

2.13  Contribution to Literature on Malaysian Perspectives There is currently enough literature available that reflects the harm and cost of climate change adaptation, especially in the developing world’s food sector. This research also discovered several studies on climate change adaptation costs and damage based on CGE modeling. However, there has never been a study in Malaysia that looks at the cost and harm of scenario adaptation based on the current food market. While some studies in the literature suggest that a 10% adaptation option is the best option based on a county’s national budget, which has a significant effect on national GDP, this study is the first to look at a 50-year scenario adaptation cost that considers 5–20% adaptation options to reduce the harm and adaptation costs of certain food sectors related to climate change.

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Khor, M. (2008). The impact of trade liberalization on agriculture in developing countries: The experience of Ghana. Third World Network. Klepper, G., Peterson, S., & Springer, K. (2003). DART97: A description of the multi-regional, multi-sectoral trade model for the analysis of climate policies (No. 1149). Kiel Working Paper. Koh, K. L., & Bhullar, L. (2010). Adaptation to climate change in the ASEAN region. Draft. Centre for Law and the Environment, University College London. www.ucl.ac.uk/laws/environment/ docs/hong-­kong/Adaptation%20to%20CC,20 Kollmuss, A., & Agyeman, J. (2002). Mind the gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research, 8(3), 239–260. Kurukulasuriya, P., & Mendelsohn, R. (2008). How will climate change shift agro-ecological zones and impact African agriculture? The World Bank. Laurance, W. F., Koh, L. P., Butler, R., Sodhi, N. S., Bradshaw, C. J., Neidel, J. D., & Mateo Vega, J. (2010). Improving the performance of the roundtable on sustainable palm oil for nature conservation. Conservation Biology, 24(2), 377–381. Malua, E., & Lambi, C. (2007). The economic impact of climate change on agriculture in Cameroon. Policy Research Working Paper 4364, World Bank. Mano, R., & Nhemachena, C. (2006). Assessment of the economic impacts of climate change on agriculture in Zimbabwe: A Ricardian approach CEEPA DP11. University of Pretoria. Mano, R., & Nhemachena, C. (2007). Assessment of the economic impacts of climate change on agriculture in Zimbabwe: A Ricardian approach. World Bank Policy Research Working Paper (4292). March, J. G., & Olsen, J. P. (2004). The logic of appropriateness (pp. 690–708). Arena. Masud, M.  M., Rahman, M.  S., Al-Amin, A.  Q., Kari, F., & Leal Filho, W. (2014). Impact of climate change: An empirical investigation of Malaysian rice production. Mitigation and Adaptation Strategies for Global Change, 19(4), 431–444. 176. Matthews, R. B., Kropff, M. J., & Bachelet, D. (Eds.). (1995a). Modeling the impact of climate change on rice production in Asia. International Rice Research Institute. Matthews, R.  B., Horie, T., Kropff, M.  J., Bachelet, D., Centeno, H.  G., Shin, J.  C., … Lee, M. H. (1995b). A regional evaluation of the effect of future climate change on rice production in Asia. In R. B. Matthews, M. J. Kropff, D. Bachelet, & H. H. van Laar (Eds.), Modeling the impact of climate change on rice production in Asia (pp. 95–139). CAB International. Matahir, H. (2012). The empirical investigation of the nexus between agricultural and industrial sectors in Malaysia. International Journal of Business and Social Science, 3(8), 225–231. McCarl, B. A., Chang, C. C, Atwood, J. D., Nayda, W. I. (1998). Documentation of ASM: The U.S.  Agricultural Sector Model (Technical Paper). Texas A&M University, Department of Agricultural Economics, TX. McCarl, B. A., Adams, D. M., Alig, R. J., Burton, D., & Chen, C. C. (2000). Effects of global climate change on the US forest sector: Response functions derived from a dynamic resource and market simulator. Climate Research, 15(3), 195–205. Mendelsohn, R., & Dinar, A. (1999). Climate change, agriculture, and developing countries: Does adaptation matter? The World Bank Research Observer, 14(2), 277–293. Mendelsohn, R., & Tiwari, D. (2000). Two essays on climate change and agriculture: A developing country perspective (FAO Economic and Social Development Paper 145). FAO. Mendelsohn, R., Nordhaus, W., & Shaw, D. (1994). The impact of global warming on agriculture: A Ricardian analysis. II. American Economic Review, 84, 753–771. Mendelsohn, R., Nordhaus, W., & Shaw, D. (1996). Climate impacts on aggregate farm value: Accounting for adaptation. Agricultural and Forest Meteorology, 80(1), 55–66. Molla, A., Cooper, V., Corbitt, B., Deng, H., Peszynski, K., Pittayachawan, S., & Teoh, S. Y. (2008). E-readiness to G-readiness: Developing a green information technology readiness framework. ACIS 2008 Proceedings, 35. Molua, E. L., & Lambi, C. M. (2007). The economic impact of climate change on agriculture in Cameroon, volume 1of 1. The World Bank.

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Chapter 3

Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

Abstract To formulate sustainable adaptation policies for food security in Malaysia, it is essential to generate a specific model to identify possible outcomes and results. Therefore, this research study systematized a dynamic Malaysian Integrated Climate and Economy (MICE) model based on computable general equilibrium (CGE) methods to find optimized results for climate-related issues that incorporates aggregated agricultural sectors for food security and sustainability issues. First, it developed a social accounting matrix (SAM) based on a Malaysian input-output (IO) table of 2005 (latest), which was updated for 2010 from the national account. Then the MICE model determined how climate change impacts will be translated into monetary damage and how this damage can be reduced via different levels of adaptation strategies and choices over long time periods. This methodology and framework, applied to quantify the economic impacts of climate change and adaptation It establishes an integrated approach incorporating general equilibrium models based on an IO model, SAM model, and MICE-CGE model that is more robust and comprehensive for food sustainability. Therefore, this climate model successfully integrated in the different climate change adaptation scenarios from 2015 to 2065 to determine and diminish the policy shocks.

3.1  Introduction To recommend a suitable adaptation preference for sustainable food security from the short to the long run in Malaysia, it is essential to build a specific model to find likely outcomes and results. This model must correspond to the economic structure and to the impact of future changes in the socioeconomic variables. Thus, this research study deployed a dynamic Malaysian Integrated Climate and Economy (MICE) model based on computable general equilibrium (CGE) techniques to find likely outcomes and results for climatic matters that incorporates aggregated agricultural sectors for food security and sustainability issues. The model is designed to be useful as a development tool for determining the effects of investments intended to reduce food sustainability issues and to explore policy options to deal with a © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_3

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number of macro matters. The model extends previous modeling work on Malaysia in several ways. First, it develops a social accounting matrix (SAM)1 based on a Malaysian input-output (IO) table2 from 2005 (latest), which was updated for 2010 from the national account. Then the updated food sustainability variables were incorporated into the MICE model. Second, the MICE model is a dynamic model that incorporates food sustainability with different levels of adaptation preferences for expected food security to answer for the short- to long-run adjustment process that occurs as the economy responds to the shocks of climate change. Third, the MICE model is able to address a number of growth-related questions by looking at sustainable development overall and climate change in particular. Fourth, the MICE model is a country-specific model that permits examination of the impact of sectoral development policies, particularly focused on agriculture for food security in line with the research scope. Finally, the MICE model is focused on how impacts are translated into monetary damage and how this damage can be reduced via different levels of adaptation strategies and choices over time.

3.2  Hypothetical Construction of Study Based on reports in the literature, this study has identified indispensable theories for constructing a concrete conceptual framework that makes it possible to meet the main objectives. For example, the theory of transitions was developed for this study and applied to the concept of different paths to adapt to climate change to achieve national sustainable food security or food sustainability over time. In this section, theories are highlighted that are applied to the study of adaptation costs and damage related to climate change in connection with food security. Figure 3.1 is deliberately simple and follows the straightforward causal chain from greenhouse gases (GHGs) to climate damage. Working downward from the top of the diagram, changes in atmospheric GHG concentrations as a result of human activities (i) drive changes in climate variables such as temperature and precipitation at the regional scale (ii). In turn, climatic changes give rise to impacts (iii) that influence the productivity of various sectors of the regional economies where the impacts occur (iv), giving rise to climate-related damage to the economy (v). Less straightforward is adaptation induced by the threat, or the onset, of economic damage. The response of sectoral productivities to the character and

1  SAM: A social accounting matrix represents the flows of all economic transactions that take place within an economy (regional or national). It is, at its core, a matrix representation of the national accounts for a given country but can be extended to include nonnational accounting flows and created for whole regions or area. SAMs refer to a single year, providing a static picture of the economy. 2  Input-output table: In economics, an input–output model is a quantitative economic technique that represents the interdependencies between different branches of a national economy or different regional economies.

3.2 Hypothetical Construction of Study

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(i) Change in Global Atmospheric GHG Connections

A (ii)Changes in Climate Variables (by Region)

B

(iii) Response of Physical Impacts Endpoints to Climate Variables (by Region)

C

Protective/Defensive Expenditures

(iv)Response of Sectoral Productivity to Physical Impact Endpoints (by Region and Sector)

Protective/Coping Expenditures

D

General Equilibrium Effects

(v) Economic Losses (by Region & Sector) Type III

Type I

Type II

Fig. 3.1  Canonical integrated assessment model (IAM) incorporating climate impacts and adaptation (Fisher-Vanden et al., 2011)

magnitude of the initiating impacts is moderated by specific protective or defensive measures, which henceforth will be referred to as Type II adaptations. A qualitatively different type of adaptation reduces the extent to which the productivity effects of impacts that do manifest themselves end up causing economic damage. However, this study also refers to specific investments of this kind as Type III adaptations. Lastly, for given levels of these specific adaptations (or no adaptation), the magnitude of the damage that does ultimately befall the economy also depends upon price changes and substitution responses across many markets. These passive general equilibrium adjustments may be thought of as a sort of adaptation in their own right, labeled Type I.  The dashed lines in the figure are meant to emphasize that all three kinds of adaptation are themselves endogenous responses to expectations of economic damage shaped by climate impacts. The fundamental insight of the diagram is that adaptation cannot be considered in isolation: it is inseparable from the overarching context of magnitude and, crucially, the character of the climate impacts that generate the demand for adaptation responses in the first place. This suggests that quantification of the economic consequences of climate impacts rests critically on estimates of the responses of both key impact endpoints with respect to changes in climate variables at the regional scale

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(B) and sectoral productivity shocks with respect to these endpoints (C). Without these two key pieces of information, estimating the potential for adaptation to mitigate the economic damages from climate change will continue to be a matter of guesswork.

3.3  General Equilibrium Theory This study developed a country-specific dynamic MICE model based on computable general equilibrium model to examine the impacts of climate change on the Malaysian economy (with and without adaptation policy). The MICE model that rests on the ideas of CGE model is based on general equilibrium theory developed by Walras in 1954. The theory was established in connection with competitive market exchange, which explains a state in which all markets will be in equilibrium simultaneously. Therefore, each individual sector will be in equilibrium at the same time. The total market demand for every commodity output and every factor in total is equivalent to the total market supply. The price of each commodity is fixed in such a way that an equilibrium profit for any firm is zero after all payments are made to the various factors of production. Household expenditures must be equivalent to household income. The value of transfer payments from government to consumers is equal to the government’s revenue from taxes. Therefore, Walrasian equilibrium for this model is a set of prices such that the supply side of an economy is in equilibrium by ensuring all firms maximize their own profits. Similarly, the demand side is in equilibrium by ensuring all households maximize their utility conditional upon a budget constraint given by the value of their endowments, and excess demand for every commodity is zero. This general equilibrium model assumes that all markets are perfectly competitive in terms of both consumption of goods and factors of production. In this study the basic CGE framework of the MICE model is originally static in nature and expanded into a dynamic model for the period of 2015–2065 applying a recursive structure. This means that the model is solved for an individual year, savings and investment rates are then used to update the capital stock in various sectors, and the new values for the capital stock are then used in the solution for the subsequent year. In addition to this, numerous other values are updated from 1 year to the next. To model the impact of climate change in the CGE model, this study uses a productivity of l and for various types of agriculture decline or increase, based on estimates from Al-Amin et  al. (2015), Lobell et  al. (2008), and Cline (2007). However, for the 2015–2030 period, this study assumes land productivity for different crops changes each year by a twentieth of the overall change estimated for the overall period. For the scenario of 2030–2065, this study assumes land productivity changes by the amount needed to bring the 2065 value to that predicted in Cline (2007). Since Cline’s long-term projections are considerably more pessimistic for the short term, this meant that productivity declines for most crops after 2030. Moreover, this study assumed a steady decline in crop productivity from 2015 to

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3.4 Conceptual Framework of Study

2065, bearing in mind that the impact of climate change is modeled as declining land productivity rather than as declining agricultural yields; this provided scope for agents to adjust by applying more labor and capital. As a fictitious “no climate change” baseline, it also ran the same simulations for the period 2015–2065 under the same assumption that none of these climate-change-induced productivity changes took place.

3.4  Conceptual Framework of Study From the adaptation-related literature, this study devises the conceptual framework for this study as shown in Fig. 3.2. The conceptual framework shows that the capacity to adapt depends on natural resources and factors, particularly climate variability, and on economic resources, for example, capital, labor, investments, institution, and trade. This framework also highlights the capacity of the national priorities for climate change adaptation and food sustainability to strategize the national agendas that supposed to be implemented for the future economic growth for food sustainability. These national priorities are accomplished with science and social science based modeling options. However, science modeling can identify the applicable optimization options for the climate change adaptation and food sustainability. On the other hand, nonscience (social-science) modeling is suitable for both micro- and macroeconomic simulations. Both science and nonscience modeling are interrelated, which is applied by dynamic modeling. However, adaptation options have been included as policy variables in an IAM, namely, the Dynamic Integrated model of Climate and the Economy (DICE), which was originally developed by Nordhaus (1994) and elaborated in Nordhaus and Boyer (2000). The DICE model is a global model and includes economic growth functions as well as geophysical functions. Global Model AD-DICE AD-RICE

National priorities

-Growth strategies -National agenda -Future plans & actions

Non-science Modeling -CGE model -Macro simulations

Science Modeling -Optimization

Other Priorities

MICE Modeling

Fig. 3.2  Conceptual framework of study. (Source: Author)

Economic structure

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The use of adaptation is assumed to be optimal and is already included in the damage function. This study develops what has been called the Adaptation in DICE (AD-DICE) model, which includes adaptation as a decision variable. Estimates from the empirical literature on the costs and benefits of adaptation are used to calibrate the model and derive the adaptation cost curve that is implicit in the DICE model. However, new policy scenarios were then constructed with no adaptation to understand the effects of adaptation. The model also takes a closer look at the effects of adaptation both in AD-DICE3 and AD-RICE4 orientations. Finally, the AD-DICE model was constructed to derive adaptation cost functions implicit in the DICE and AD-RICE models to estimate the damage and adaptation costs resulting from the damage done by climate change. Total damage costs are the sum of adaptation costs and residual damage costs (unavoidable damage).

3.4.1  Data Sources Two sets of data are used in this study. The first set is from macroeconomic variables, such as from the Department of Statistics (DOS), the Economic Planning Unit (EPU), HIES (Household Income and Expenditure survey), Labor Force Survey (LFS), and national accounts (DOS, 2010).

3.4.2  Study Area The areas where this study took place are located in East and West Malaysia. Specifically, climate data are used from four regions: Kuching (1.5° N, 110.3° E) and Kota Kinabalu (5.9° N, 116.0° E) in East Malaysia and Kuantan (3.8° N, 103.3° E) and Petaling Jaya (3.0° N, 101.6° E) in West Malaysia.

3  The DICE, as well as AD-Dice, model is a computer-based integrated assessment model developed by William Nordhaus that “integrates in an end-to-end fashion the economics, carbon cycle, climate science, and impacts in a highly aggregated model that allows a weighing of the costs and benefits of taking steps to slow greenhouse warming.” 4  Nordhaus also developed the Regional Integrated Climate-Economy (RICE) model, a variant of the DICE model updated and developed alongside the DICE model. The AD-RICE model estimates damage and adaptation costs resulting from the damage of climate change. Total damage costs are the sum of adaptation costs and residual damage costs (unavoidable damage).

3.4 Conceptual Framework of Study

69

3.4.3  Empirical Economizing Adoption Adaptation scenarios and assessments are incorporated into this study by the use of the MICE model with empirical economizing to observe the complex interaction between global warming and climate variability with capital stock, carbon concentrations, carbon emissions, temperature and rainfall fluctuations, and agriculture productivity. The economizing measures are signified in a range of reasonable climatic outcomes for 50-year long-term adaptation scenario projection. However, the baseline is 2015 until 2065 (cf. Table  3.1). The adopted modeling is a top-down approach,5 focusing on the impacts in Malaysia given a wide range of likely climate outcomes by a specific climate prediction on a global level to a country-specific level. The MICE model is constructed by applying a national observational large-­ scale database to (a) the predicted annual cycle of observed regional temperature and rainfall and (b) the predicted annual cycle observed in large-scale circulation fields (West and East Malaysia) (Fig. 3.3). However, the MICE model then includes the yearly average circulation parameters as predictor variables, like yearly average temperatures and rainfall, that fluctuate with carbon concentrations to show the changes in large-scale exchange over time (cf. Fig. 3.4). All the large-scale predicted data used in this study are taken from the climate change scenarios for Malaysia for the period 2001–2090, as projected by the Malaysian Meteorological Department (MMD) (2009). The national temperature variations are derived from historical records6 applied in the MICE model for the projection of large-scale variations by the concentration of GHGs (280 parts per million (ppm) in preindustrial times to 650 ppm in 2065). This study takes a quantitative approach to analysis, with some steps and procedures as shown in Fig. 3.4. However, some modifications7 have been made to the data, which were derived from the SAM and MMD to align with the scope of study. The annual cycle of local temperature is adopted for MICE based on 1.5° N, 110.3° E;5.9° N, 116.0° Table 3.1  Time segments for scenario studies Time segment 1 2 3 4 5 6

Year 2015 2025 2035 2045 2055 2065

5  The top-down approach indicates global change and then individual countries tackling climatic initiatives to disaggregate them for measurement. 6  The temperature data recorded by the MMD. 7  Modification means that an adjustment has been made to the national climatic and microeconomic data, particularly from the SAM and genotype data from the MMD.

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

Precipitation change

Temperature change

Climate change Sea-level rise

Extreme events

Earth system Ecosyste

Climate process drivers Greenhouse gases

Concentration Emissions

Water resources Equity

Impacts & vulnerability Aerosol

Human health Food

Settlement & society

Human system Population

MARKET Literacy

Health

Trade Socio-economic development Technolo Mitigation

Goveman

Production & consumption

Socio-cultural preferenoes

Adaptation

Fig. 3.3  Schematic framework representing anthropogenic drivers, impacts of and responses to climate change, and their linkages (IPCC, 2007)

E; 3.8° N, 103.3° E; 3.0° N, 101.6° E latitude and longitude to isolate the long-term temperature effects with a standard elevation setup between 2015 and 2065. This study constructed SAM using different data sources for different time periods. Then SAM was updated and balanced by a cross-entropy process. The second set of data is from the MMD on climate change and meteorological parameters (MMD, 2009; NAHRIM, 2006). The data on climate change, particularly meteorological (i.e., climatic) parameters, are used for the scenario exercise based on two monsoons and four seasons from 1969 to 2007 for the application of the baseline year in 2015. The summer monsoon data are categorized as the southwest monsoon (SM), which affects the climate of Malaysia from May to September. The winter monsoon is categorized as the northeast monsoon (NM), which affects the climate from November to February (Al-Amin and Leal, 2014). Modeling on the basis of MICE helps to quantify the likelihood of exceeding thresholds as core data for impacts and vulnerability up to the year 20658 (Fig. 3.4). The threshold variable data 8  The threshold here indicates a point beyond which the institutional and socioeconomic system would be affected or fundamentally changed by climate change issues. Without knowing the socioeconomic system and institutions affected or fundamentally changed by climate change and global

71

3.4 Conceptual Framework of Study

Study Approach (Quantitative)

Secondary Sources  The Department of Statistics (DOS)  The Economic Planning Unit (EPU)

Data Sources

 Household Income and Expenditure survey  Labor Force Survey; and  Other supplementary data

Social Accounting Matrix (SAM)

Balancing method

IAMs

(RAS/Cross entropy) DICE

Calibration of the CGE Model

RICE

AD-DICE

AD-RICE

MICE

Fig. 3.4  Process of Malaysian model for climate and the economy (MICE)

are (i) the probability of unforeseen climatic shocks in the present and likely future (i.e., 2065) climate situations and (ii) climate vulnerabilities with their likely impacts.9 This study selected several diverse scenario data on temperature between 0.8 and 3.1 °C and 280–650 ppm carbon concentration (CO2) with certain levels of fluctuation with several climatic damage intercepts.

warming, it may not be possible to determine how alternative options would be affected by climate change issues (Al-Amin & Leal, 2014). 9  The selection of threshold level and climate variables was facilitated by the MMD (2009).

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

3.5  S  tudy of Different Levels of Adaptation Options for Climate Change This study has taken advantage of the extensions of AD-DICE and AD-RICE modeling based on William Nordhaus (1994). To compare the different levels of adaptation options, this study also followed the AD-RICE model (de Bruin et al. 2009a), which defined the 10% adaptation option as the optimum level of adaptation based on national accounts using the following equation:

 j ,t

AL

  j  Mt      2, j 1, j

1

  2 , j 1  

(3.1)

where (𝜔𝑗∙𝑀𝑡) is the value of the gross damage found from the Malaysian model, and the remaining parameters are adaptation coefficients. The value of these coefficients was estimated from the AD-RICE model, which is adapted for a middleincome country (such as Malaysia). However, this study also considered the values of these coefficients exogenously from the AD-RICE model in MICE to achieve the optimum level of adaptation and to support sustainable future strategies (Fig. 3.5). Although de Bruin et al. (2009b) indicated a 10% adaptation option as the optimal level, in this study there are four different adaptation options (5–20%) with scenarios of 50  years from the model simulation that have been integrated for the best selection of the Malaysian adaptation option based on both the IO table of Malaysia 2005 and its national accounts. However, the study does not necessarily look for optimal or minimal adaptation options but long-term adaptation cost scenarios based on 5–20% adaptation options for climate change and its implications for the food sector in Malaysia. The climate change adaptation options can be adopted and implemented in the following ways: This study also takes advantage of the extensions of AD-DICE and AD-RICE modeling and uses a basket of adaptation options in Eq. (3.9) under three broad categories of adaptation with subinstruments as follows: 1. Management-related instruments

(a) Irrigation scheduling (b) Integrated pest management (IPM) (c) Weather and climate information systems (d) Higher cropping intensity (e) Diversification of cropping production on irrigated areas (f) Protected cultivation (g) Postharvesting technology (h) Income stabilization programs due to farmers’ income losses

2. Infrastructure-related instruments

1. Issue

3.5 Study of Different Levels of Adaptation Options for Climate Change

5. Interpretations

4. Computer simulation

3. Model formulation

2. Theory

Policy background

Theoretical foundation of key mechanisms (e.g. analytical “maquette” of numerical model)

Construction of consistent Benchmark equilibrium Data Set

Date: input output tables, national accounts, tax data, income and expenditure data

Formulation and implementation of numerical model (Incl. choice of functional forms); scenario definition

Choice of exogenous elasticities (literature survey)

Calibration: Calculation of parameter values from benchmark data

Simulations: Calculation of new policy equilibrium (counterfactual)

Reporting and economic interpretation of results

Replicatio n check successful

No

Yes Sensitivity analysis

Robust results

No Yes

Conclusions and policy recommendations

Fig. 3.5  Steps in CGE analysis (Böhringer et al., 2012)

73

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

(a) Irrigation facilities (b) Storage and milling facilities (c) Other forms of mechanization

3. Community (CBOs and NGOs) initiated instruments

(a) Small-scale capacity building (b) Credit facilities (c) Marketing support

Based on current population growth rates and targeted food security options, simple statistical calculations10 were made outside of the main modeling works and keyed into the outcomes to ALt and to our EDCGECE (Empirical Dynamic Commutable General Equilibrium Model for Climate and the Economy) model.

3.6  Description of Simulations This study estimated climate change impacts over a period of 50 years. It divided these 50 years into 6 different time segments, each of 10 years’ duration, and those time segments are independent of each other. However, the study considers 2015 as the benchmark year (base year) for this study to simulate the scenario outcomes. Therefore, all the simulations start from this benchmark year and end in 2065. Table 3.1 shows time segments 1–6, starting in 2015 and ending in 2065.

3.7  Basics of CGE Model The basic idea of CGE is to implement theoretical economic models empirically. To simulate the welfare effects of different policies, a general equilibrium approach is combined with empirical data. The CGE model is based on the Walrasian (1954) general equilibrium theory. An equation system representing the demand for goods by consumers, the supply of goods by producers, and the equilibrium condition where supply equals demand in every market is solved simultaneously (Arrow & Debreu, 1954). However, the CGE model allows for some modifications like imperfect markets and externalities. To explain the term CGE it is useful to proceed by defining it word by word. Computable means numerical calculations by a computer. The term equilibrium refers to the concept of market equilibrium. This concept includes the microfoundation of profit-maximizing firms and utility-maximizing households. Hence, agents have no incentive to revise their decisions. Finally, the  To maintain the targeted food-security option; this study‘s core objective is to advance y (by offsetting leveling position) under there broad categories of basket of adaptation option as by ΔYield = constant + y. ΔC Change (improved management options) + statistical error.

10

3.7 Basics of CGE Model

75

approach is general since all markets are interconnected and not considered separately in a partial equilibrium. The Walrasian equation system represents the interdependencies between markets via commodity and corresponding payment flows between market agents. These circular flows represent a closed system. Closed means that there cannot be a payment or commodity flow from one agent that has no recipient. The budgets of all agents must be balanced. Agents obtain a certain income that can be spent on goods. For further details on the concept of circular flows of commodities and payments, see Wing (2004). For more information about the basics of CGE a classical introduction can be found in Shoven and Whalley (1984). The general procedure of a CGE can be explained in the following nine steps (Bröcker 2004) (the procedure uses the formalized equation system of Walrasian [1954] general equilibrium theory): 1. Delineate the agents (producers, consumers, state) and markets (e.g., food, cars). 2. Organize the data for a computer program. In a so-called SAM agents appear twice, once in the row with their payments and once in the columns with their receipts. In Table 3.2, a SAM is set up for a static economy with two industries (I1 and I2), two factors of production (labor L and capital K), and two households (H1 and H2). There is no public sector and neither taxes nor savings and investments. I2 pays four units for inputs that are produced by it, six units for inputs from I1, four units for labor, and seven units for capital (similarly for I1). Three units of labor income go to H1, respectively seven units to H2. Capital income (11 units) goes to H1 (5 units) and H2 (6 units). H1 (H2) spends one unit (8 units) of its income for goods from I1 and 7 units (5 units) for goods from I2. Gross production is 37 units (sum of I1and I2), of which 16 are intermediate goods (flows from I1 to itself, to I2 and vice versa). The gross domestic product (GDP) is 21 units; this can be either considered as the units produced by the two industries using labor and capital inputs or as the expenditure of the two households for the produced units. 3. Assume a market form (usually perfect competition). 4. Choose an arbitrary benchmark price. 5. Specify the functional forms of supply and demand to set up the model. 6. Calibrate the model. This is a crucial point. Only one time period is included in the SAM, and parameters are chosen to reproduce the benchmark data. There is Table 3.2  SAM for a static economy (Bröcker, 2004) I1 I2 L K H1 H2 Sum

I1 1 5 6 4

16

I2 6 4 4 7

21

L

K

3 7 10

5 6 11

H1 1 7

H2 8 5

8

13

Sum 16 21 10 11 8 13 79

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

no information on reactions of the agents, which is needed to specify the slope parameters (elasticities). Estimation of these slope parameters is only possible with longer time periods. Since this is not the case within the CGE analysis, this information must come from econometric analysis outside the CGE. 7. Compute the policy effects. 8. Continue with the analysis of welfare effects using methods like Hicksian equivalent variation. 9. Perform sensitivity analysis. To reduce the arbitrariness of the chosen elasticities from other research results, sensitivity analysis with varying elasticities is implemented in a CGE procedure.

3.8  Pros and Cons of Basic Model In CGE models, as in all general equilibrium models, price changes cause simultaneous reactions in all other markets. This property is important for the two main advantages, the microfoundation and the inclusion of economic feedback processes. The microfoundation consists of three conditions, market clearance, zero profit of firms, and income balance of households. These principles are considered in the formulation of a CGE. Because of the inclusion of economic feedback processes (due to price changes that lead to quantity changes), CGE can be used for long-term perspective analysis (Walz & Schleich, 2008). A significant weakness of CGE was already mentioned  – the poor empirical foundation of calibration. Only observations from 1 year are used to calibrate shift parameters. The production and utility functions are constrained to a constant elasticity of substitution (CES). The parameters for these functional forms come exogenously from empirical estimation of elasticities, not from the calibration process. These “best guess” values add a large uncertainty to the model. The chosen elasticity has an especially significant effect on the results (West et al. 1995).

3.9  Social Accounting Matrix A SAM is a matrix-form representation of the microeconomic and macroeconomic transaction records of a socioeconomic system that captures the transfers and transactions among all agents in the economic system (Pyatt & Round, 1985; Reinert & Roland-Holst, 1997). It is an exemplification of the national accounts for a specific country, though it can be extended to include multinational accounting flows, so it can be constructed for whole regions or a global context. A SAM recognizes all monetary flows from sources to recipients, within a disaggregated national account. However, a circular flow diagram of an economy is shown in Fig. 3.6 that captures all real transactions, including all transfers among institutions and sectors. The production procedure involves buying factors of production such as capital, land,

77

3.9 Social Accounting Matrix

and labor inputs (with the rental/wages) from the factor markets, and from the commodity markets it requires intermediate inputs to produce final goods and services. These domestically produced commodities are supplemented by imports of commodities. Figures 3.6 and 3.7 explain the circular flow of the economic activities, which shows that each institution’s income becomes another institution’s expenditures. For instance, government and households transfer income to producers by purchasing commodities. Yet again, producers use this income to carry on further production activities. Also, further interinstitutional transactions, such as savings and taxes, ensure that the circular flow of incomes is a closed system. More specifically, all expenditure and income flows are carried out, whether domestic or international transactions, and there are no overflows from the system. In Fig. 3.7, the dotted arrow indicates government transfers to households. The dashed arrow indicates a firm’s income from selling commodities. The dotted-­ dashed arrow shows intermediate demands. The double-dot and dashed arrow shows government fiscal surplus. For all solid arrows, the indicators are stated inside the diagram. Likewise, a SAM is also a framework that assigns numerical values to expenditures and incomes in the circular flow of the economy. It is a matrix representation of a circular flow diagram with real monetary figures. A SAM is a square matrix, meaning the number of rows must equal the number of columns in which each column and row is labeled as an “account.” Table 3.3 shows a SAM of an economy that relates to the circular flow diagram in Fig. 3.7. Every single box in the diagram is

E1. Product Markets Government Expenditures Markets Government Good & Services

A. Households

F.

Good &Services

C. Government

Taxes

E.G over Taxes

B. Firms

E2. Intermediate Goods Mkts.

Profits/ Factor Income Markets Government D. Factor Markets

H1. Externalities

H1. Externalities

G. Environment H2. Externalities

Goods & Factors

H2. Externalities

Payments

/

Fig. 3.6  Circular flow of economy with environmental interactions (Wing, 2004)

Non-market Effects

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

PRODUCT MARKETS

Composite goods (Q)

Armington CES tariffs REST OF WORLD

Imports (M) Domestic goods (D)

Exports (E) exptax

Armington CET Domestic Output (X)

indtax

Leontief

FACTOR MARKETS

Value added Cobb Douglas

Labor

Land

Capital

Intermediates

REPAT

CORTAX

HHOLDS

CORTRN

HHTAX

FACTIN

CORP

GOVT INTER

GOVTRN

Savings HHSAV

Real flows

INTER

FORSAV

Investments

Transfers

Fig. 3.7  Schematic representation of CGE model of Malaysia (Kim & Summer, 2005)

6. Government

5. Enterprises

4. Households

3. Factors

2. Activities

Receipts 1. Commodities

Sales tax, tariffs, export taxes

Domestic Production MAKE matrix

1. Commodities

Expenditures

Indirect taxes, factor use taxes

Value added

2. Activities Intermediate Inputs USE matrix

4. Households Private consumption

Factor income to government, factor taxes

Transfers to government, direct household taxes

Factor income Inter-­ to households household transfers Factor income to enterprises

3. Factors

Table 3.3  A Macroeconomic SAM (Lofgren et al., 2001)

Transfers to government, enterprise direct taxes

Transfers to household

5. Enterprises

Transfers to enterprises

Transfers to household

6. Government Government consumption

(continued)

Activity income (gross output) Factor Factor income from income ROW Transfers to Household income household from ROW Transfers to Enterprise income enterprise from ROW Transfers to Government government income from ROW

7. Savings-­ 8. Rest of the investment world Total Investment Exports Demand

3.9 Social Accounting Matrix 79

Total

Supply

Receipts 7. Savings-­ investment 8. Rest of the Imports world

1. Commodities

Expenditures

Table 3.3 (continued)

Activity expenditures

2. Activities

Factor expenditures

Factor income to ROW

3. Factors

Household expenditure

4. Households Household savings

Enterprise expenditure

Transfers to ROW

5. Enterprises Enterprise savings Government transfers to ROW Government expenditure

6. Government Government savings

Foreign exchange outflow

8. Rest of the world Total Balance of Savings payments

Investment Foreign exchange inflow

7. Savings-­ investment

80 3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

3.9 Social Accounting Matrix

81

considered an account in the SAM. Each cell in the matrix signifies a monetary flow from a column account to a row account. For instance, the private consumption spending of the circular flow diagram indicates a flow of funds to the commodity markets from households. In the SAM, this value is represented by the commodity row and the household column. The total expenditure must equal the total revenue for each and every account in the SAM (to satisfy the principle of double-entry bookkeeping systems). Thus, for every account, the column and row totals must be the same. Table 3.4 shows the general components of a SAM.  The SAM differentiates between commodities and the activities. Activities are entities that produce goods and services for an economy while commodities are those goods and services produced by activities. They are differentiated by the fact that activities can produce more than one type of commodity (byproducts). Likewise, a commodities can be produced by more than one type of activity. For instance, rice can be produced by large-scale or small-scale farms. The monetary values in the activity accounts are typically calculated in producer prices, which implies factory gate or farm gate prices. Activities produce commodities (goods and services) using the factors of production along with intermediate inputs. This fact is displayed in the activity column of the SAM, where each activity pays for the factors of production, i.e., the rents, wages, and profits they generate during the production process (that is, value-­ added). Since this represents a payment transferred from activities to factors, in the SAM, the value-added entry appears in the factor row and the activity column (Row 3, Column 1). In the same way, payment for intermediate demand is transferred from activities to commodities (Row 2, Column 1). The accumulation of value-added and intermediate demand is needed for gross output. The data on production mechanism included in the activity column are the input part of a common IO table, which implies the required factor and the required intermediate inputs per unit of output. Goods and services are either produced domestically and supplied domestically (Row 1, Column 2) or imported from other countries (Row 7, Column 2). For domestically produced commodities, indirect sales taxes are paid to the government, whereas for imported commodities, import tariffs are paid to the government (Row 5, Column 2). As mentioned earlier, activities purchase commodities for use as intermediate inputs in the production process (Row 2, Column 1). However, final demand for each commodity consists of household consumption expenditures for that commodity (Row 2, Column 4), government expenditures (recurrent) (Row 2, Column 5), investment or gross capital formation (Row 2, Column 6), and export demand of that commodity (Row 2, Column 7). The SAM in Table 3.3 shows only a single commodity and activity rows and columns. However, a SAM is usually composed of a number of commodities and activities. For example, this study has 15 different activities and commodities based on the study focus. Because this study’s main focus is on the food sector of Malaysia, the SAM was disaggregated into 10 different agricultural sectors and 5 other sectors (Table 3.4).

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

Households are usually the ultimate owners of the factors of production, and therefore, they receive the incomes earned by the factors during the production process (Row 4, Column 3). They also receive transfer payments (TP) from the government (Row 4, Column 5) (for instance, pensions and social security), and from the rest of the world (ROW) they receive remittances from foreign workers (Row 4, Column 7). On the other hand, households pay direct and indirect taxes to the government (Row 5, Column 4) and purchase commodities to consume (Row 2, Column 4). The surplus income (if positive) will be saved or disservice (if expenditures exceed income), for example, when comparing a new practice to business as usual for climate change adaptation and food sustainability (Robertson et al., 2014). Data for household accounts are typically taken from national accounts and household income and expenditure surveys from the country’s bureau of statistics. From the ROW government receives TPs in the form of foreign grants and development assistance (Row 5, Column 7). Total government revenues thus consist of income from taxes of all types and TPs from the ROW. On the expenditure side, the government pays for recurrent consumption expenditures (Row 2, Column 5) and TPs to households (Row 4, Column 5). The gap between total revenues (TR) and total expenditures (TE) is the fiscal surplus (or fiscal deficit, if expenditures exceed revenue) (Row 6, Column 5). Information about government accounts is normally available from public-sector budgets published by a country’s ministry of finance. In keeping with the concepts of ex-post accounting identity, the total investment or gross capital formation (including changes in inventories or stocks) must be equal to the total savings. The total capital inflows (from abroad) is the difference between the total investment demand and the total domestic savings and is referred to as the current account balance (Row 6, Column 7). Information on the current account (or rest of world) is drawn from the balance of payments, which is generally published by a country’s central bank.

3.9.1  SAM Market Closure There are three conditions of market closure that the standard SAM must satisfy for the CGE model, discussed in what follows.

3.9.2  Market Clearance Condition The market clearance condition involves commodity market balance and factor market balance: (a) Commodity market balance implies that the quantity of each commodity, Xi, produced by producer I will equal the commodity demanded by producer j in n industries as their intermediate inputs (Zij) to production and by the representa-

3.9 Social Accounting Matrix

83

tives’ agents in the economy as their final demand, Fj, that absorb those commodities: n



n

n

Xi    Fj i 1 j 1

j 1

(3.2)

(b) Factor market balance implies that all industries in the economy are fully employed by the factor endowments available in the market, in other words, the quantities demanded by primary factor inputs used by all producers are equal to the supply of factor endowments by the representatives agent’s, 𝑉𝑗: n

Vi  Vi j 1



(3.3)

3.9.3  Normal Profit Condition The second condition is normal profit, which implies that all industries are assumed to receive a zero profit where the values of the output generated by producers, Xi, must equal the values of the inputs of the intermediate goods, Zij, and primary factors, Vj, employed in production. In other words, total revenue (price times quantity of output produced) generated by producers is equal to total costs derived from the utilization of intermediate inputs and the value added or primary factors in production. Since profit is calculated on monetary terms, hence this equation must be timed with the price for cost of intermediate inputs, Pi, and the cost of value added, Wf. Here, it assumes that the average cost for the value added, i.e., rent and profit, is equal to the average wages of the labor employed, and the total revenue is equal to the price, Pi, times output, Xi: Total Revenue  Total Cost Total Revenue  Cost Intermediate Inputs  Value Added Cost Total Revenue  Pi X i  

n

n

 P  Z  W i

j 1,i 1

ij

j 1

f

(3.4)

 Vj

3.9.4  Factor Market Balance Factor income (m) received by the representative’s agents of factor endowments must equal the value of producer payments, 𝑉𝑗 (the total value added payments), that utilize the primary factor endowments and must equal the factor’s gross expenditure

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

on goods and services, which is the total final demand, Fj. This condition implies that income must balance the sum of the elements of V, which in turn must equal the sum of the elements of total final demand, F: n

n

j 1

j 1

m  V j  Fj



(3.5)

These are the three basic macro balances used to achieve general equilibrium.

3.10  Balancing a SAM The SAM accounts are represented as a square matrix where the inflows (receipts) and outflows (expenditures) for each account are shown as a corresponding row and column of the matrix. Because it is an accounting framework, the total receipts by rows and total expenditures by columns for each account must balance following the principles of double-entry accounting systems. However, as the required information to construct a SAM comes from different sources, for example, government budgets, household surveys, national accounts, and balance of payments, placing all these data within the SAM framework often generates inconsistencies between the expenditures and incomes of the corresponding accounts. For instance, the value of government expenditures in national accounts might diverge from the value given in the government budget. Therefore, the SAM needs to be balanced so that total receipts equal total expenditures. A number of statistical estimation techniques exist for balancing SAMs. This study presents a balancing technique that makes it possible to reconcile this information in order to balance a micro-SAM. The technique minimizes the changes to the base data using a RAS (Review of agrarian studies) method, a widely used optimization technique for balancing SAMs. It is an iterative method of biproportional adjustments to rows and columns that is independently developed when new information on the matrix row and column sums are accessible and need to be adjusted to the existing matrix. The RAS technique illustrated by Schmidhuber and Tubiello (2007) is as follows. Consider a matrix Mij, where Mj is the vector of column totals. From this matrix a coefficient matrix Aij0 can be obtained as follows:

Aij0 = Mij / M j



Pre- and postmultiplication of this matrix by vectors rj and sj leads to the creation of another matrix Aij1 . Aij and Aij1 are the vectors of the target row and column total. This coefficient matrix is now ready to undergo a sequence of iterative multiplications, shown in Eqs. (3.6a), (3.6b), (3.6c), (3.6d), (3.6e) and (3.6f). Pre- and

3.10 Balancing a SAM

85

postmultiplication of the initial coefficient matrix by the corresponding row and column produces the next iteration coefficient matrix as follows.

Fij  Aij0 M j



The original coefficient matrix is now multiplied by the row of a target column total, M ∗j , to obtain the matrix Fij. The row totals of this matrix are represented by the vector ui. The ratio of ui∗ to ui is the multiplier ri. Multiplying rj by Fij then leads to a new Fij. The row vector vj of column totals is obtained and used to calculate the multiplier Sj. Fij and Sj are then multiplied. The entire sequence of operation is represented by Eqs. (3.6a), (3.6b), (3.6c), (3.6d), (3.6e) and (3.6f):



ui  Fij j

(3.6a)

 i



ri  u / ui

(3.6b)



Fij = ri Fij

(3.6c)



V j  Fij i



(3.6d)



S j  V j / V j





Fij  Sij  Fij



(3.6e) (3.6f)

The iterative process in Eqs. (3.6a), (3.6b), (3.6c), (3.6d), (3.6e) and (3.6f) continues until the conditions 𝑢𝑖 = ui∗ and 𝑣𝑗 = V j∗ are met. At that point, the matrix 𝐹𝑖𝑗 is assumed to be the best estimate of the true posterior matrix M ∗j .

3.10.1  CGE Model for Malaysian Economy This section presents a CGE model that was developed as an appropriate method for assessing the economic-environmental effects of adaptation policies in the Malaysian economy. This model is the MICE model. The study divides the Malaysian economy into 15 sectors. However, two factors of production are considered, labor and capital. The institutions in the model represent government, firms, households, rest of the world, and capital account. The next subsection discusses the basic structure of the model.

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

3.10.2  Basic Structure of Model The model and equation are written in general algebraic modeling system (GAMS) language to estimate the solving parameters with nonlinear programming. Five economic blocks are considered (e.g., economically essential components/parts): price, production and commodities, institutions, system constraints, and climate change. The measurements with all the economic interactions are as follows.

3.10.3  Prices This study reasonably assumed that, as a small country, Malaysia is a price taker, which means it has no power to change world import prices. Thus, import price is considered as being exogenously determined in the model. The country’s export demand function is downward sloping. Figure 3.7 shows the price structure of the economy. Domestic import and export prices are determined by world prices (pwm and pwe, respectively), exchange rate (EXR), and import tariff (tm) or export subsidy (te). The price system of the model is rich, mainly due to the assumed quality differences among commodities of different origins and destinations (imports, exports, and domestic outputs that are used domestically) (Fig. 3.8).

3.10.4  Production The IO tables (for Malaysia) for the year 2005 consist of a different number of sectors. Specifically, they have 120 groups of sectors. However, to meet the research objectives, sectors were re-grouped into different groups of sectors. This model consists of 15 sectors, 4 institutional agents, 2 primary factors of production, and the rest of the world (ROW). The 15 sectors were aggregated from the 2005 Malaysian IO table that was initially composed of 120 sectors, with details on agricultural sectors. The agricultural sectors were disaggregated into 10 sectors. The following Table 3.4 shows the regrouped sectors for this study (Fig. 3.9). Figure 3.8 shows the nested structure of production activities, which captures the income generation by activities in the production of commodities and net supply of different types of commodities by various kinds of domestic production activities. The circular economy receives income from the supply of various goods as a source of income from industrial activities through domestic and foreign resources/intermediate inputs (imports) and through the supply of intermediate commodities to other production activities. Income is also generated from the consumption of goods and services by other domestic and foreign (exports) agents in the economy. All producers are assumed to maximize profits and each faces a two-level nested Leontief/CES production function. This flow represents the total GDP that is produced locally from each production activity as part of purchasing raw materials

87

3.10 Balancing a SAM

Activity 1 Price (PXAC)

Activity n Price (PXAC)

+ activity and factor

Commodity Price (PX)

Export Price (PE)

+ export tax

Domestic Supply Price (PDS)

Domestic Demand Price (PDD)

Import Price (PM)

+import tax

Composite Commodity Price (PQ) + sales tax

Fig. 3.8  Prices in standard model (Lofgren et al., 2001)

either as domestic products or as imports (foreign). However, the remaining production costs (value-­added factor payments) indicates values paid out to the factors of production in the form of wages (labor), rents (land or natural resources), and profits (capital) to resource markets (through enterprises) as well as tax payments to the government.

3.10.5  Domestic Demand Figure 3.10 shows the demand structure of the economy. Total composite demand consists of household consumption, government spending, investment demand, and intermediate demand. All four of these components have a fixed share, the demand for government spending, for example, is exogenously fixed since the government selects how much they should spend. Consumption demand implies a household’s consumption expenditures to maximize utility. Intermediate demand is subject to

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Table 3.4  Sectors in model Sector SEC1-A Paddy SEC2-A Food Crops SEC3-A Vegetables SEC4-A Fruits SEC5-A Rubber SEC6-A Palm Oil SEC7-A Livestock SEC8-A Forestry and Logging SEC9-A Fishing SEC10-A Other Agriculture SEC11-A Crude Oil and Natural Gas and Mining and Quarrying SEC12-A Industrials SEC13-A Transportation and Communication SEC14-A Financial Services SEC15-A Services

Sectors from 2005 IO table 1 2 3 4 5 6 9, 10 11 12 7, 8 13–16 17–94 95–101 102–107 108–120

Commodity Output

Commodity Output

Commodity 1

Commodity n Leontief

Activity Output Leontief

Intermediates

Value added

Leontief

CES

Primary Factor 1

Intermediate Input n

Intermediate Input 1

Primary Factor n

Imported

Domestic

Fig. 3.9  Production technology (‘CES’ is constant elasticity of submission aggression function. ‘Leontief’ is fixed shares) (James Thurlow, 2004)

3.11 Mathematical Statement and Specification of MICE Model

Government spending

Household consumption

Investment demand

89

Intermediate demand Level 1 Substitution among categories and commodities

Fixed share

Total demand m composite

Level 2

Figure 4-10: The Structure of demand for the MICE Substitution between Source:Yeah, Kim Leng (1992) CES Cost- minimizing

Level 3 Substitution among imports from different sources

Domestic

CES

Imports from region 1

Imports from region 2

domestic and import composite

Imported demand

Imports from region 3

Imports from regionn

Fig. 3.10  Structure of demand for MICE model. (Source: Yeah, 1992)

fixed IO coefficients. The demand for investment is derived from a capital composition matrix (CCM). The total composite demand is broadly grouped into total domestic commodity demand and total import demand from the rest of the world.

3.11  M  athematical Statement and Specification of MICE Model This section presents mathematical modeling of the MICE model. In its mathematical form, the CGE model consists of a set of nonlinear simultaneous equations where the number of equations is equal to the number of endogenous variables. The model equations are divided into “blocks” for prices, production and commodities, institutions, climate change, and system constraints. Explanatory boxes are added for each block of equations. In accordance with its objectives, this study considered five different blocks of equations. A brief overview of each equation block is given in Fig. 3.11.

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security Price Block

Production & Commodity Block

Import price Export price Composite price Activity price Composite intermediate input price Value added price Consumer price index

Production function Value added function Armington function Import demand function Output transformation function Export supply function

Institution Block Household income function Households’ sectoral consumption function Household saving investment equation Government income equation Government expenditure equation

Climate Change Block Gross demand function Climate impact function Monetary demand function Residual damage function Adaptation cost function

System Constraint Block Factor market equilibrium Production market equilibrium Foreign exchange market equilibrium Saving investment closure

Fig. 3.11  Block of equations

3.11.1  Price Block As mentioned earlier, Malaysia is a developing country; therefore, it acts as a price taker for imports and exports. The small country model is assumed in the MICE model, which means that the prices of imports and exports are exogenously driven. The price block contains equations in which endogenous model prices are associated with other prices (exogenous or endogenous) and to nonprice model variables. The corresponding equations are given as follows.

3.11.2  Import Price The import price (PMc) in domestic currency units (DCUs) is the price paid by domestic users for imported commodities (excluding sales taxes). Equation (3.7) states that it is a transformation of the world price of these imports (pwmc), considering the exchange rate (EXR) and import tariffs (tmc) plus transaction costs per unit of the import (icm). For all commodities, the market price paid by domestic commodity consumers is the composite price, PQ (in this equation, PQ applies only to

3.11 Mathematical Statement and Specification of MICE Model

91

payments for trade inputs). The exchange rate and domestic import price are flexible, whereas the tariff rate and the world import price are fixed, following the small-­ country assumption:

PM c  1  tmc   EXR  pwmc



(3.7)

where 𝑃𝑀𝑐 = import price in DCUs including transaction costs 𝑝𝑤𝑚𝑐 = c.i.f. import price in foreign currency units (FCUs) 𝑡𝑚𝑐 = import tariff rate 𝐸𝑋𝑅 = exchange rate (DCUs per FCU)

3.11.3  Export Price The export price (PEc) in DCUs is the price received by domestic producers when they sell their output in export markets. This equation is structurally similar to the import price definition. The main difference is that the tax and the cost of trade inputs reduce the price received by domestic producers of exports. This study assumes that the set of exported commodities are all produced domestically:

PEc  1  tec   EXR. pwec



(3.8)

where 𝑃𝐸𝑐 = export price in DCUs 𝑝𝑤e𝑐 = FOB (Freight on Board) export price in FCUs 𝑡𝑒𝑐 = export tax rate 𝐸𝑋𝑅 = exchange rate (DCUs per FCU)

3.11.4  Composite Goods Price One assumption of MICE modeling is that goods are perfect substitutes for domestically produced and imported goods, known as the Armington assumption. Under this assumption, a CES function is derived (also known as an Armington function). The composite commodity price is the total domestic spending on a commodity at domestic consumer prices. Equation (3.9) defines it excluding sales taxes. Absorption is expressed as the total spending on domestic outputs and imports at domestic sales prices, PDc and PMc. The PDc and PMc prices include the cost of trade inputs but exclude the commodity sales taxes:

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PQc  QQc   PDc  QDc   PM c c CM   1  tqc 

(3.9)

where 𝑄𝑄𝑐 = quantity of goods supplied to domestic market (composite supply) 𝑄𝐷𝑐 = domestic sales quantity 𝑃𝐷𝑐 = domestic sales price 𝑃𝑀𝑐 = import price 𝑡𝑞𝑐 = sales tax rate (as share of composite price inclusive of sales tax)

3.11.5  Domestic Output Price For every domestically produced commodity (QXc), the marketed output value at producer prices (PXc) is stated as the sum of domestic sales and export values. Domestic sales (QDc) and exports (QEc) are valued at the prices received by the suppliers, PDc and PMc, both of which have been adjusted to account for the cost of trade inputs:

PX c  QX c  PDc  QDc   PEc  QEc 



(3.10)

where 𝑃𝑋𝑐 = aggregate producer price for commodity 𝑃𝐷𝑐 = domestic sales price 𝑄𝐷𝑐 = aggregate quantity of domestic output 𝑃𝐸𝑐 = export price 𝑄𝐸𝑐 = quantity of exports

3.11.6  Activity Price The activity price (PAa) is the gross revenue for each activity (i.e., the unit return from the sale of an output). It can also be expressed as the sum of the amount of production per activity unit multiplied by the activity-specific commodity prices for all commodities. This allows for the fact that activities may produce multiple commodities: where 𝑃𝐴𝛼 = activity price

PAa   PX   ac

(3.11)

3.12 Producer Price Index for Nontraded Market Output

93

𝑃𝑋𝑐 = aggregate producer price for commodity 𝜃𝑎𝑐 = quantity of commodity c′ as trade per exported unit of C produced and sold domestically

3.11.7  Value-Added Price PVa  PAa   PQc  icaca



(3.12)

where 𝑃𝑉𝑎 𝑃𝐴𝑎 𝑃𝑄𝑐 𝑖𝑐𝑎𝑐𝑎

= = = =

value-added price activity price composite commodity price nonexported commodities

3.11.8  Consumer Price Index

CPI   PQc  cwtsc



(3.13)

where CPI = consumer price index (exogenous variable) 𝑐𝑤𝑡𝑠𝑐 = weight of commodity c in consumer price index

3.12  Producer Price Index for Nontraded Market Output

PPI   PDSc  dwtsc

(3.14)

where 𝑃𝑃𝐼 = producer price index (exogenous variable) 𝑑𝑤𝑡𝑠𝑐 = weight of commodity c in producer price index Equations (3.13) and (3.14) define the CPI and the PPI for domestic market outputs. The CPI is the weighted sum of composite goods prices, whereas the PPI is the weighted sum of domestic goods prices. Either index can be used as the numeraire price so that all other prices are measured relative to it.

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3.13  Production and Commodity Block Equations As stated in the model assumptions, each sector produces a gross output (Xi) with constant returns to scale and minimize costs subject to a production function. The technology of production is usually represented by a series of CES of functions that can be organized by a nested structure reflecting the production hierarchy (Shoven & Whalley, 1992). This means that the elasticities of substitution may vary at different levels of the nesting hierarchy and independent of each other.

3.14  Factor Income Equation (3.15) defines the total income for each factor (YFf). Here, this income is split into domestic institutions in fixed shares after payment of direct factor taxes (1−tf) ∙ YFf and transfers (trnsfr) to the ROW. The latter are fixed in foreign currency and transformed into domestic currency by multiplying by the exchange rate (EXR). This equation becomes a reference for the set of domestic institutions (household, enterprises, and the government, a subset of the set of institutions, which also includes the ROW):

YFf  shryhf  WFf  WFDIST fa  QFfa



(3.15)

where 𝑌𝐹𝑓 = income of factor 𝑓

3.14.1  Household Income

YH h   YFhf  trh, gov  EXR  trh, gov

where 𝑌𝐻ℎ = income to domestic institution i from factor 𝑓 Σ𝑌𝐹ℎ𝑓 = total of factor incomes 𝑡𝑟ℎ,gov = transfer from factors, government, and ROW EXR = exchange rate



(3.16)

3.14 Factor Income

95

3.14.2  Household Consumption Demand QH ch 

 ch  1  mpsh   1  tyh   YH h PQc



(3.17)

3.14.3  Investment Demand Fixed investment demand (QUNV) is defined as the base-year quantity ( qinvc ) multiplied by an adjustment factor (𝐼𝐴𝐷𝐽). For the basic version of the model, the adjustment factor is exogenously determined, and therefore the quantity of the investment turns out to be exogenous: QINVc  qinvc  IADJ



(3.18)

where 𝑄𝐼𝑁𝑉𝑐 = quantity of fixed investment demand for commodity 𝑞𝑖𝑛v𝑐 = base-year quantity of fixed investment demand 𝐼𝐴𝐷𝐽 = investment adjustment factor (exogenous variable)

3.14.4  Government Revenue Total government revenue (YG) is the sum of revenues from taxes (𝑇𝐼𝑁𝑆), factors (  ), and transfers from the ROW (𝑡𝑟𝑛𝑠𝑓𝑟𝑔𝑜𝑣):



YG   TINSi  YI i   tf f  YFf   tvaa  PVAa  QVAa   taa  PAa  QAa   tmc  pwmc  QM c  EXR   tec  pwec  QEc  EXR   tqc  PQc  QQc   YIFgov , f  trnsfrgov ,row  EXR

where 𝑌𝐺 = government revenue



(3.19)

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3  Assessment of Climate Change and Adaptation Policies for Sustainable Food Security

3.14.5  Government Expenditure Total government spending (EG) is the sum of government spending on consumption and transfers:

EG   trh, gov   PQc  qgc

(3.20)



where EG = government expenditures

3.15  System Constraints Block 3.15.1  Factor Markets Factor market equilibrium requires that for each factor, total demand (QF) for that factor must be equal to the supply of that particular factor (QFS). In the basic version of the model, at a given time, the supply of factors is fixed while demand is flexible/variable. The model uses WFf (the wage factor paid by each activity) as an equilibrating variable to satisfy factor market equilibrium. An increase in WFf the wage paid by every single activity, 𝑊𝐹𝑓. 𝑊𝐹𝐷𝐼𝑆T, which is inversely, related to the quantity demanded for factors, 𝑄𝐹𝑓𝑎. All factors are movable among the demanding activities:

QF

fa

 QFS f

a A



demand for  supply of   factor f    factor f     

f F

(3.21)

where 𝑄𝐹S𝑓 = quantity supplied of factor (exogenous variable)

3.15.2  Composite Commodity Markets Composite commodity market equilibrium requires that demand for composite commodities be equal to the quantity supplied. The demand for composite commodities consists of endogenous terms and changes in inventories, which is exogenous. In the basic version of the model, QG and QINV are fixed. The supply of composite commodities, QQc, drives quantity demanded for domestic commodities,

3.15 System Constraints Block

97

QD, and imports, QM. The domestic prices PDD and PDS act as market-clearing variables, along with quantities of imports supplied, for the output of the domestic market: QQc  QINTc a  QH c h  QGc  QINVc  qdstcc  QTc a A



hH

composite  composite   intermediate   supplyy    supply     use        household   government     consumption   consumption  c C  fixed   stock   trade       investment  change   input use 



(3.22)

where 𝑞𝑑𝑠𝑡𝑐 = quantity of stock exchange

3.15.3  C  urrent-Account Balance for ROW (in Foreign Currency) The current-account balance (expressed in terms of foreign currency) usually indicates a country’s spending to the ROW and must be equal to the country’s income in foreign currency. That means spending on imports and factor income outflows must equal income from exports and factor income inflows (foreign saving, FSAV). In the basic version of the model, FSAV is fixed and the real exchange rate (EXR) plays the role of a balancing variable in the current account:

 pwmc  QEc   tri ,row  FSAV   pwmc  QM c



(3.23)

where 𝐹𝑆𝐴𝑉 = foreign savings (FCU) (exogenous variable)

3.15.4  Savings-Investment Balance Equation (3.24) states that total investment must be equal to total savings. The total savings is the sum of savings of national nongovernmental institutions, government savings, and savings from the ROW, with the last element being converted to local currency. Total investment is the sum of the values of the changes in stocks and fixed investments (gross fixed capital):

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 mpsi  1  tyh   YH h  YG  EG   EXR  FSAV  PQc  QINVc  WALRAS c C

(3.24)

where YHh = household income

3.16  Price Normalization

 PQc  cwtsc  CPI

(3.25)

3.16.1  Climate Change Block CGE models are commonly used to quantify the costs and benefits of an environmental policy. The aim is to simulate how economic activity affects the environment and vice versa. Furthermore, CGE models deal with the question of how technological advances and production are influenced by environmental policies (Dellink et al., 2004). The impacts of global warming are usually entered into a CGE model as monetized damages. Aggregate monetized gross damage (GD) is modeled as a function of the climate variable. Then gross damage is a function of the climate variable:

GDt   i  Tt 2

(3.26)

where the change in global mean temperature compared to a base year is used. Mostly, the functional form is assumed to be quadratic (or at least the power is greater than 1). This allows for increasing impact costs when temperature rises. Again, the climate impact function is

Tt   j Tt 1   k EM t

(3.27)



where, as the exogenous shock, an increase in carbon dioxide emissions (EMt) by a certain amount leads to an increase in the global mean temperature (Tt) compared to the level of the preceding period. Damage grows linearly with GDP as a constant fraction of GDP.  This linear trend can be influenced by other factors, shifting the amount of damage up or down. For example, population growth results in increased numbers of consumers. Then income growth affects people’s valuation of impact, and this results in a change of tastes affecting valuation:

EM t    Yt 1  t  ALt 



(3.28)

3.16 Price Normalization

99

where cumulative emission depends on output and adaptation and mitigation policies. For this study it considered no mitigation policy, so emission depends on the output and adaptation level. Here, the mitigation cost is zero because there is no mitigating policy, and the adaptation cost depends on the output and adaptation level:



ACt   1  ALt 2 Yt

(3.29)

Gross damage depends on output and emission values:



GDt    Mt Yt

(3.30)

Again, gross damage from climate change can be expressed as a function of climate variables:



GDt  1  Tt   2  Tt 3 Yt

(3.31)

The monetary value of gross damage as a percentage of GDP/output can be expressed as the sum of RDt (residual damage) and ACt (adaptation costs):



GDt RDt  GDt ,ALt ,ABt  ACt  ALt ,ABt    Yt Yt Yt

(3.32)

Gross damage as a percentage of output depends on the residual damage and adaptation costs for a certain level of adaptation. The value of residual damage depends on gross damage GDt and adaptation level ALt. Consumption is given as output minus all climate change costs:

RDt  1  ALt   GDt

(3.33)



The value of residual damage depends on gross damage GDt and adaptation level ALt. Consumption is given as output minus all climate change costs:

Ct  Yt  RDt  ACt  MCt



(3.34)

Net consumption is the value of the output minus the cost of climate change policies. In the Malaysian model, this study considers 𝑀𝐶𝑡, mitigation cost, to be zero (if no climatic mitigation action is taken place). Thus, it depends only on adaptation cost, residual damage, and output.

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Finally, social welfare can be maximized through utility maximization: Z



U t  t   Ct  t 1

(3.35)

where 𝜌𝑡 is the discounting factor and 𝐶𝑡 consumption after adaptation policy. The mathematical statement starts with alphabetical lists of sets, parameters, and variables, as shown in the appendix.

3.17  Calibrating the CGE Model Standard SAM procedures require additional parameter values to carry out estimation and simulation using MICE-based CGE modeling. Once the operators are identified and their optimization behavior is determined by algebraic equations, the parameters in the equations should be evaluated. Data on exogenous and endogenous variables at a given time are usually used for this purpose. This process is known as calibration. Calibration is performed to estimate the related coefficient parameters (if data are sufficient and available) or benchmark data from the existing literature are used (if there is a lack of data) in order to standardize the parameters used in the calibration technique. The parameter and elasticity values (i.e., CES, constant-elasticity-of-transformation (CET)) that are employed in the modeling equations for MICE-based CGE are vital to assess the impact of various policy effects or external shocks. The accurate estimation of the model parameters is crucial for obtaining consistent results. Generally, two types of parameter estimates are widely used by researchers to develop CGE models: the econometric approach and the calibration method that enables the static module equations to generate a baseyear equilibrium observation or short-run solution (Sánchez-Chóliz et al., 2007). The calibration approach was introduced by Jorgenson in 1960 and the econometric approach was first used by Jorgenson and Wilcoxen (1993). The econometric approach uses statistical tools to estimate parameters. Generally, elasticities and parameters of productions and consumption functions are determined econometrically using time series data. Each parameter is associated with a standard error (SE) and correlation factor (R), which define the accuracy of the estimation. However, the econometric estimation consumes time and resources. In most cases, econometric estimation of the calibration procedure assumes that the economy is in equilibrium. This is established by a benchmark data set that represents equilibrium for an economy so that the model is actually solved from equilibrium data for its parameter values (Shoven & Whalley, 1984). Specifically, the benchmark data set is systematically represented in the compiled SAM. Equilibrium exists because the SAM is square, and row-column sums for a given account are equal because all income must be accounted for by an outlay of another type (Pyatt & Round, 1985). When these parameters are correctly estimated, the result using the initial data must match

3.18 Conclusion

101

the base year equilibrium data. When results are not identical, it is necessary to modify the model until it can replicate the base-year observation. Nevertheless, the calibration approach has been criticized for the following reasons: the parameters estimated are deterministic in nature, and therefore, there is little scope to support the reality of the coefficients; the estimation of the parameters is a function of the selected benchmark year. The calibration method, however, remains widely used for various reasons. Accounting for the model sector-factor-institution breakdown implies that many of the parameter values (sometimes thousands) are needed to solve the model. The simultaneous stochastic estimation of all these parameters is unrealistic due to the scarcity of data, especially for developing countries, the required sophistication of techniques, and the need for severe identification restrictions (Gunning & Keyzer, 1995). Despite these criticisms, the major advantage of the calibration method is that only a few data are needed because the parameter estimation only one observation, which may, however, involve gathering a great deal of data when a SAM is estimated (Sánchez-Chóliz et al. 2007). Furthermore, in most CGE applications for LDCs (Least Developing Countries), the calibration approach is widely used because of the infeasibility of full-fledged econometric estimations. Hence, the SAM has been widely used as base data for calibration. Hence, in this study, the same calibration approach is used to determine the model parameters. To solve the parameters, the MICE-based CGE model and equations are written in the GAMS. The GAMS was developed to solve these types of models and makes the process of programming and running CGE models even simpler.

3.17.1  Performing Scenario Simulations within CGE Model Simulations based on different scenarios are performed using the developed MICE-­ based CGE model. Scenarios include cases of different degrees of temperature change combined with the imposition of an optimum adaptation policy versus no adaptation policies. Special focus is given to the impact on the agricultural sector, the impact on production, and the effects on important economic variables (i.e., real income, inflation, unemployment, and social welfare). Lastly, the estimated findings from the MICE-based CGE simulation results are interpreted to rationalize the research objectives.

3.18  Conclusion From the foregoing discussion on methodology and frameworks, it is clear that to quantify the economywide impacts of adaptation, an integrated approach using general equilibrium models based on an IO model, SAM model, and MICE-based CGE

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model is more robust and comprehensive. This is mainly due to the fact that integrated approaches are applied and policy shocks from price reforms are best captured within the general equilibrium modeling approach.

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Lofgren, H., Chulu, O., Sichinga, O., Simtowe, F., Tchale, H., Teska, R., & Wobst, P. (2001). External shocks and domestic poverty alleviation: Simulations with a CGE model of Malawi. IFPRI. MMD. (2009). Climate change scenarios for Malaysia. Malaysian Meteorological Department, Ministry of Science Technology and Innovation, Kuala Lumpur, Malaysia. NAHRIM. (2006). Final report: Study of the impact of climate change on the hydrologic regime and water resources of Peninsular Malaysia. National Hydraulic Research Institute of Malaysia. Nordhaus, W. D. (1994). Managing the global commons: The economics of climate change (Vol. 31). MIT press. Nordhaus, W. D., & Boyer, J. (2000). Warming the world: Economic models of global warming. MIT pPess. Pyatt, G., & Round, J. I. (1985). Social accounting matrices: A basis for planning. The World Bank. Reinert, K. A., & Roland-Holst, D. W. (1997). Social accounting matrices. In Applied methods for trade policy analysis: A handbook (pp. 94–121). Cambridge University Press. Robertson, G. P., Gross, K. L., Hamilton, S. K., Landis, D. A., Schmidt, T. M., Snapp, S. S., & Swinton, S. M. (2014). Farming for ecosystem services: An ecological approach to production agriculture. BioScience, 64(5), 404–415. Sánchez-Chóliz, J., Duarte, R., & Mainar, A. (2007). Environmental impact of household activity in Spain. Ecological Economics, 62(2), 308–318. Schmidhuber, J., & Tubiello, F. N. (2007). Global food security under climate change. Proceedings of the National Academy of Sciences, 104(50), 19703–19708. Shoven, J. B., & Whalley, J. (1984). Applied general-equilibrium models of taxation and international trade: An introduction and survey. Journal of Economic Literature, 22(3), 1007–1051. Shoven, J.  B., & Whalley, J. (1992). Applying general equilibrium. Cambridge surveys of economic literature. Cambridge University Press. Simonovits, A. (1975). A note on the underestimation and overestimation of the Leontief inverse. Econometrica, 43, 493–498. Thurlow, J. (2004). A dynamic computable general equilibrium (CGE) model for South Africa: Extending the static IFPRI model. Trade and Industrial Policy Strategies. Walras, L. (1954). Elements of pure economics. Allen and Unwin. English translation by William Jaffe, originally published in 1874. Walz, R., & Schleich, J. (2008). The economics of climate change policies: Macroeconomic effects, structural adjustments and technological change (No. 1030). Springer. West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with normal variables. Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Wing, I. S. (2004). Computable general equilibrium models and their use in economy-wide policy analysis. Joint Program on the Science and Policy of the Global Change, Technical paper, (6). Yeah, K. L. (1992). Computable general equilibrium analysis of external and policy shocks on the Malaysian agricultural sector (Doctoral dissertation).

Chapter 4

Food Security Challenges of Climate Change: An Analysis for Policy Selection in Malaysia

Abstract  The key goal of this chapter is to examine and assess the effect of various adaptation strategies and their related costs on macroeconomic variables such as real gross domestic product (RGDP), government spending, exports, net consumption and net production, and food sustainability over time as a means of addressing Malaysia’s climate change and food security issues. Our research focuses on the agriculture sector since Malaysia is becoming increasingly reliant on imported food, which could increase as a result of climate change. The results from the proposed Malaysian Integrated Climate and Economy (MICE) model are presented in this chapter in order to determine which adaptation policy alternative would be most successful in addressing long-term food security issues caused by climate change impacts. The comparative results of likely adaptation policies with various levels of adaptation are also simulated in this chapter. The chapter focuses on food security challenges and how climate change effects transform into agro-economic damage, as well as how the damage can be mitigated by effective response measures and interventions. Finally, the chapter calculates the economic risks of climate change with and without adaptive policies, as well as their economic effects, in order to determine which adaptation measures would be most successful in mitigating climate-­change-related costs and impacts on agro-food security problems.

4.1  Introduction The main objective of this chapter is to analyze and evaluate the impact of several adaptation policies and their associated costs on macroeconomic variables such as real gross domestic product (RGDP), government expenditures, exports, net consumption and net output, and food sustainability over time as an option to address the issue of climate change and the food security of Malaysia. The agricultural sector is the main focus of this research because Malaysia finds itself increasingly dependent on exported food products, which may rise due to the impact of climate change. This chapter reports the thesis findings based on the proposed Malaysian Integrated Climate and Economy (MICE) model to ascertain which adaptation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_4

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policy option would be most effective in dealing with long-term food security issues caused by the impacts of climate change. This study also simulated the comparative effects on the overall economy of likely adaptation policies with different levels of adaptation options.

4.1.1  Policy Scenarios This study focuses on food security issues and how climate change impacts translate into agro-monetary damage and how this damage can be reduced by appropriate adaptation strategies and actions.1 Under the environmental CGE framework, several types of integrated assessment models (IAMs) can be utilized. Among the climate-­change-related regional and global impact models, well-recognized models are the Dynamic Integrated Climate and Economy (DICE) model introduced by Mendelsohn and Nordhaus (1999) and its extended AD-DICE model that considered adaptation as a decision variable. Moreover, the regional version of this model is called Regional Integrated Climate and Economy (RICE), model and its extension for adaptation is the AD-RICE model.2 This study introduces MICE, which considered Malaysia as a case study with its own economic data and tried to determine the locally appropriate/suitable policy without considering any externalities and spillover effects of global activities and policies.3In the MICE model, every economic activity causes environmental degradation (e.g., ultimately climate change) with no undertaking of prevention measures. Therefore, environmental degradation is a linear function of economic output. This environmental degradation can be reduced only by mitigation efforts, but for a single country like Malaysia, it will be mostly unsuccessful without coordination with neighboring countries. Therefore, environmental degradation in this model is considered a linear function of economic output disregarding any mitigation effort; the study assumes that adaptation (with the support of the related literature) is the only viable option for a country’s climate change policy. Accordingly, the emission level/environmental degradation for a country will change with ongoing economic activity. Thus, in our model, the net emissions/environmental degradation value is dependent on a country’s output or total production value. Disregarding any mitigation effort implies that the costs of mitigation will be zero. It is known that net damage depends not only on a country’s own emissions but also on cumulative global emissions; however, for simplicity’s sake, this study assumes no spillover  This study focused only on Malaysia, though analogies can be easily applied to other countries.  Referring to de Bruin et al. (2009a, b). 3  This study assumed populations are constant over time, and all price-related parameters are nonzero. In this model, the values of the elasticity of substitution were exogenously taken from the GTAP database (Zhang &Verikios, 2006). For consistent growth rate, the RGDP growth rate data were collected from the national statistics department and World Bank, which estimates the data for Malaysia. 1 2

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effect or no externalities and, hence, that the net damage to a country will depend only on its own emissions. This study treated temperature change (e.g., from 1900s levels) as an exogenous shock and simulated the effects of adaptation policies in a 50-year period based on the 2015 base year by the social accounting matrix (SAM) for the Malaysian economy. The study examined the policy effectiveness with respect to food sustainability and security issues by simulating scenarios with and without adaptation options. To achieve this, it first makes a business-as-usual assumption, referred to here as the Base Case or Base Case Scenario (BCS) simulation when no adaptation policies are engaged. Also, this situation does not consider the monetary value of climate change damage in economic figures in the base year. Thus, this study determines the economic costs of climate change without any adaptive policy and compares its impacts on the economy. Therefore, several adaptation actions are introduced (5%, 10%, 15% and 20%) into the simulations based on the national accounts to see what types of adaptation strategies are effective in terms of reducing climate-change-related costs and impacts on agro-food security issues.4 The following three scenarios are considered in this study.

4.2  Baseline Scenario (BS) This scenario posits that the country’s economic development will not be affected by the climatic change and will continue following the existing trends.

4.3  E  stimated Food Sustainability with No Adaption (EFSNA) This scenario considers what will be the worst-case economic situation when the projected climatic parameters change with the associated impacts, but policymakers, economic agents, and stakeholders do not respond and so implement no adaptation policies; hence, there is no investment in adaptation.

4  de Bruin (2009a) of Wageningen University in the Netherlands first introduced the concept of different levels of adaptation options for climate change. According to his recommendation, the starting level of adaptation should be no less than 5 (%). He also indicated a 10 (%) level of adaptation as optimal for developed countries like the Netherlands. However, he did not mention any particular adaptation level for developing countries in connection with climate change. Thus, this study introduced four different types of adaptation options based on the economic status of Malaysia to see what types of adaptation strategies are effective and best in terms of policy selection.

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4.4  Estimated Food Sustainability with Adaption (EFSA) In this scenario, policymakers take several adaptation actions and bear the associated costs. Thus, this case highlights the economic impacts of adaptation. Also, the comparative analysis of EFSA fulfills the objective of measuring the effectiveness of adaptation policy in terms of its economic impacts.

4.4.1  Description of Simulations This study estimated climate change impacts over a period of 50  years. For this purpose, the study divided those 50 years into 6 different time segments, each of 10 years’ duration and each being independent of the others. However, 2015 is considered the benchmark year or base year for this study. Therefore, all the simulations start from this benchmark year and end in 2065. Table 3.1 shows time segments 1–6, starting in 2015 and ending in 2065 (Table 3.1).

4.5  Analysis of Different Scenarios According to the first objective, this study developed a scenario-based long-term applicable adaptation model for a sustainable food sector. The model was used to simulate adaptation costs, gross damage, residual damage, net damage, net consumption, net output total with climate change, food sustainability over time, percentage of sectoral food sustainability over time, and, finally, RGDP. The study also compared the entire simulated objective between baseline scenarios to obtain a real scenario on the effects of climate change adaptation policy on food sectors.

4.5.1  Different Levels of Damage from Climate Change This study tried to focus on different levels of damage, for example, gross damage, residual damage, and net damage. For all these kinds of damage it discusses different adaptation scenarios with different adaptation actions and, finally, compares these calibrated adaptation scenarios with the baseline year 2015. In the case of residual damage, the study presents residual damage without adaptation action, residual damage scenarios with different adaptation actions (Fig. 4.1), and net residual damage (Fig.  4.2) and compares different scenarios with the baseline. If no adaptation action is taken, then the residual damage according to this optimized

4.5  Analysis of Different Scenarios

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Fig. 4.1 Residual damage with and without adaptation actions under different scenarios (million RM)

model shows it will rise gradually. The residual damage is RM1746.865 million in the baseline 2015, but in 2065 it shows rapid damage increasing up to RM2017.94 million without any adaptation action (Fig. 4.1). However, this study also focuses on different scenarios of residual damage applying different levels of adaptation, such as 5–20%. The study finds that the residual damage decreases by RM87.08 million, which is 4.9 (%) less than the baseline case after implementing 5% adaptation policies (Fig.  4.2). In the same way, the trend of residual damage for other scenarios taking 10%, 15%, and 20% adaptation policies is to gradually decline from the baseline. On the other hand, this study compares all scenarios of residual damage with the baseline and finds that all values are negative (Fig. 4.2). Thus, the adaptation options in the projections show a net positive for Malaysian agro sectors.

 US$ 1 = 3.5 RM (Malaysian ringgit).

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Fig. 4.2  Net residual damage in different adaptation scenarios with baseline (absolute value in million RM)

4.5.2  Costs of Different Adaptation Options To determine a suitable level of adaptation policy and food security, this study considers the AD-RICE approach to MICE modeling. However, the study also estimates the value of all coefficients from the AD-RICE model adapted for a middle-income country (Malaysia). Moreover, it considers the values of all coefficients exogenously using time segments 1–6 from the AD-RICE model to achieve the optimum level of food security. These values are tabulated in the appendix. Although 10% adaptation policies are considered the optimum for most developed countries, in the case of Malaysia, this study does not recommend any fixed adaptation policy in the initial simulations and scenarios but rather leaves it as an open question. Thus, it considers several levels of adaptation options, from 5 (%) to 20 (%).6 Therefore, it shows four different adaptation options to observe the overall macroeconomic sectors by focusing on food security matters. However, the study

6  We assumed that the percentage of adaptation policy that could be applied mostly depended on policymakers based on budgetary obligations in connection with climate change.

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also represents different costs of adaptation from the scenario studies of the model in Fig. 4.3. The overall summary of results shows that the impact of adaptation policies for Malaysia is positive in favor of reducing climate change effects on food sustainability7 and future food security. Importantly, the costs will be below RM 1 million in the application of a 5% adaptation policy from baseline 2015 until 2065 (Fig. 4.3). However, the costs of adaptation will rise steadily if a higher adaptation policy percentage is used. Different levels of adaptation trends are required to maintain food sustainability over time, and a higher level of adaptation is important because continued economic activities are mainly responsible for the effects of climate change. Because of this rising impact of climate change, gross damage also increases drastically in the food sector. That is why if this study applies the 10% adaptation option, the cost will be about RM 15 million in 2065, and if the 15% adaptation policy is applied, the adaptation costs will be RM 53 million in 2015 and RM 60

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Fig. 4.3  Comparison of adaptation costs considering different levels with baseline in different scenarios (million RM)  In this study, food sustainability is used to denote the food production value.

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million in 2065. Finally, if a 20% adaptation policy is applied, then the cost will be about RM 167 million in 2015 and RM 193 million in 2065.

4.5.3  Effect of Climate Change in Government Spending This study considers various adaptation costs in agriculture as government spending and their percentage of the existing economy. However, it tries to compare this spending with a comparative dimension to see the impacts on the related macroeconomic variables. Therefore, it finds that an adaptation level over 10% shows higher benefits than other adaptation options. Thus, this study tries to increase this based on country-specific macroeconomic conditions that can be related to an agriculture agenda in Malaysia, such as food sustainability and food security issues over time. Figure 4.4 shows the estimated values of government expenditures before an adaptation policy. This study’s findings show that the general trend with continued economic activities is for government expenditures to increase linearly over time after the application of different adaptation scenarios (Fig. 4.5). Government spending is an inevitable aspect of public policy. Thus, to enforce adaptive actions, government must bear the costs of adaptation. The costs in terms of the percentages of GDP and government expenditures must be identified; it is

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Fig. 4.5  Government expenditures with different adaptation actions (million RM)

also important to set resource allocations for different levels of adaptation for food security. Specifically, this study evaluates the different adaptation costs in terms of percentage of GDP and government expenditures with adaptation and without adaptation to contrast the different scenario results. It is straightforward and logical that government expenditures will be higher with adaptation actions, but the additional costs found here are marginal in terms of monetary value and percentage change (Fig. 4.5). The contrasted findings can be seen in the scenario outcomes with adaptation and no adaptation (Figs. 4.8 and 4.9). The findings of different levels of adaptation actions show that even for the year 2065, the additional adaptation costs are marginal for each time segment to support sustainable future strategies.

4.6  I mpact of Climate Change on Food Sustainability over Time In accordance with the study’s main objective, food sustainability over time is prioritized to determine the long-term scenarios of food security and food sustainability of Malaysia’s food sector. However, the study contrasts food sustainability over time with and without adaptation actions in the baseline year (Fig. 4.6), with adaption actions over time in different adaptation scenarios (Fig. 4.7), and finally differentiates different scenarios with the baseline over time from the MICE model.

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Fig. 4.6  Food sustainability over time without adaptation actions (million RM)

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Fig. 4.8  RGDP without adaptation policy (million RM)

The findings indicate that after applying different levels of adaptation over time, food sustainability rises considerably (Fig. 4.7). However, this finding projects food sustainability values of RM3566.24 million in the baseline year 2015 and RM4097.42 million in 2065 without adaptation, but in comparison it shows progress with at least a 10% adaptation level in different adaptation scenarios. Thus, food sustainability in the baseline year 2015 is RM3576.82 million for a 10% adaptation level, RM3619.48 million for a 15% adaptation level, and higher adaptation levels show greater progress over time. Similarly, food sustainability in 2065 is RM4109.64 million for a 10% adaptation level, RM4158.91 million for a 15% adaptation level, and higher adaptation levels likewise show greater progress. The contrasted scenarios with the baseline and over time are found to be progressive, and food sustainability rises proportionately as the percentage of adaptation policy is increased with a given level of action. Because the growth values are positive and show a rising trend, as seen from the study findings, clearly projected adaptation actions can favor food sustainability in Malaysia (Fig. 4.7).

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4.6.1  Effects of Adaptation Strategies to RGDP Figure 4.8 shows RGDP without an adaptation policy (million RM). However, Fig. 4.9 indicates the RGDP benefit in the different adaptation scenarios as a result of the different actions with comparative dimensions. The figures and findings from the MICE indicate which policy actions (among 5%, 10%, 15%, and 20%, based on the state of the economy) should be suitable and appropriate for further consideration as far as food sustainability is concerned. According to the study’s projections, RGDP is RM464,793.1 million in 2015, RM478,465.7 million in 2025, RM492,510.3 million in 2035, RM506,918.0 million in 2045, RM521,727.4 million in 2055, and RM536,921.8 million in 2065 without adaptation actions (Fig. 4.9). In contrast, with a 5% adaptation level, the RGDP increase from baseline in 2015 is RM73.85 million, RM76.25 million in 2025, RM73.14 million in 2035, RM81.35

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million in 2045, RM76.67 million in 2055, and RM86.48 million in 2065, and the trend is progressive over time with a higher level of adaptation action, except at 20% (Fig. 4.9). For the10% adaptation option in 2055, the benefit to RGDP appears to be surprisingly higher than in the other scenarios. Because this study follows Nordhaus’ model where it can be optimized, changes in RGDP are positive if the economy becomes green or adopts green technology by changing human behavior. However, this study also applies that idea in the particular MICE model used to see the RGDP impacts as benefits in 2055 for the Malaysian economy in terms of climate change policy options. This study ultimately attempts to determine the cost-benefit trends with respect to climate change in a way that challenges food security and supports sustainable future strategies. However, economic theory suggests that for any kind of policy action, if the benefit exceeds the costs, then obviously that policy option can be considered as applicable. Just to compare the adaptation costs and benefits in terms of GDP, this study chose 10 (%) adaptation options. Thus, according to the study’s findings, the adaptation costs in 2015 are 0.00229(%) and the benefits are 0.0301(%). On the other hand, the study also finds that the adaptation costs in 2065 are 0.0024 (%) and the benefits are 0.0305 (%) (Fig. 4.10) of GDP. This result also indicates that a 15 (%) adaptation policy is also effective in the Malaysian economy where adaptation costs do not exceed 1 (%) of GDP, but adaptation benefits will rise gradually.

0.14 0.12

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Fig. 4.10  Compare adaptation benefit and cost of GDP (%)

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It is evident from the study’s findings that the benefits of adaptation exceed the costs of adaptation for each time segment in terms of monetary value or percentage change (Fig. 4.10). This implies that the benefit-to-cost cost ratio will continue to rise over time. Thus, from the foregoing results this study found that the residual damage and net damage decline in different scenarios after applying different adaptation strategies, which indicates a positive impact on the national economy. Moreover, food sustainability also increases after different adaptation options are taken. RGDP likewise shows a positive trend under different adaptation scenarios, which means the national economy can benefit from adaptation actions. In summary, these results demonstrate that adaptation costs and government expenditures rise if different adaptation strategies for food sustainability are adopted. But in terms of comparing adaptation costs and benefits (as a percentage of GDP), this study found that adaptation benefits exceed the costs and expenditures that will have to be made in the near future to pay for the adaptation policy.

References de Bruin, K., Dellink, R.  B., Ruijs, A., Bolwidt, L., van Buuren, A., Graveland, J., de Groot, R. S., Kuikman, P. J., Reinhard, S., Roetter, R. P., Tassone, V. C., Verhagen, A., & van Ierland, E. C. (2009a). Adapting to climate change in The Netherlands: An inventory of climate adaptation options and ranking of alternatives. Climatic Change, 95(1–2), 23–45. de Bruin, K., Dellink, R., & Agrawala, S. (2009b). Economic aspects of adaptation to climate change. Mendelsohn, R., & Nordhaus, W. (1999). The impact of global warming on agriculture: A Ricardian analysis: Reply. The American Economic Review, 89, 1053–1055. Zhang, X. G., & Verikios, G. (2006). Armington parameter estimation for a computable general equilibrium model: A database consistent approach. Discussion Paper-University of Western Australia Department Of Economics, 10.

Chapter 5

Policy Implications for Climate Change Adaptation in Malaysia

Abstract  This chapter addresses the study findings in contrast to other literature; the findings specifically show that climate change will have detrimental consequences for Malaysia that may be mitigated by adaptation policies. This chapter demonstrates that the gains outweigh the associated costs for each time segment considered in the research simulation. Given the relevance of the food sector to the Malaysian economy, this chapter assesses the effects of climate change and attempts to identify the best response strategy to support the country’s agro-food sustainability. The following main research questions are addressed: (i) determine appropriate adaptation options with estimated costs for a sustainable food sector based on climate change and its impacts, (ii) assess appropriate adaptation policies based on estimated costs of adaptation with correct tools to support a sustainable future policies, and (iii) minimize the gap between climate change and targeted food sustainability. The majority of climate change impacts on the food market, as well as its climate-related policy choices, are either global or international, according to the published literature. As a result, when deciding on suitable adaptation actions to take for Malaysia’s long-term food security policies, it is important to determine the viability of a given adaptation strategy on a country-by-country basis. This study shows that through continuing economic practices (e.g., triggering climate change) with elevated gross risk values, varying levels of adaptation choices (5–20%) will keep the food security problem alive over time. Given the value of the food sector to the Malaysian economy, this chapter assesses the effects of climate change and attempts to identify the best response strategy to promote long-term food sustainability.

5.1  Introduction Considering the importance of the food sector for the Malaysian economy, this study evaluates the impact of climate change and attempts to determine the best adaptation option to support its agro-food sustainability options. The key research questions evaluated here are as follows: (i) determine the appropriate adaptation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_5

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option with estimated costs for sustainable food production based on climate change and its impacts, (ii) assess suitable adaptation policies based on the estimated costs of adaptation using suitable tools to support sustainable policies in the future, and (iii) minimize the gap between climate change and a food sustainability vision, with applicable policy supports. This study reveals, from a review of previous literature, that most climate change impacts on the food sector and its climate-related policy options are either global or regional. It is thus necessary to assess the feasibility of an adaptation plan on a country-by-country basis when choosing appropriate adaptation actions to support sustainable future strategies related to food security challenges. This study indicates that, despite ongoing economic activities (e.g., causing climate change) with increased gross damage values, the different levels of adaptation options (5–20%) can support food sustainability over time (Al-Amin & Ahmed, 2016). With reference to the related literature, most climate change impacts on the food sector and climate policy related to it are either global or regional. However, the impacts and costs of climate change cannot be optimally determined on a global basis because climatic impacts differ from region to region, among countries, or even within the same country. It is thus necessary to assess the feasibility of future adaptation plans on a country basis to choose the appropriate adaptation actions to support sustainable future strategies with respect to food security challenges. Considering the importance of the food sector for the Malaysian economy, this study evaluates the impact of climate change and tries to determine the optimal adaptation options to support sustainable future agro-food sustainability options. However, two components need to be clear for the adaptation framework and policy action: (i) specific evaluation of climate variability over time and (ii) correct possible adaptation options focusing on projected scenario issues. Consequently, the key questions to answer are the level of adaptation that is optimal for a tropical country like Malaysia, the estimated costs of adaptation, and how adaptation will affect the food sector in trying to attain the target food sustainability vision in Malaysia. This study shows that with continued economic activities (e.g., causing climate change) along with increased gross damage values, the optimum level of adaptation policies (5–20%) increase over time to maintain food sustainability. This chapter focuses on the interpretation of key findings. Here, the results of this research are compared with past studies to obtain a clearer understanding and validate the effectiveness of the adaptation policy that has been suggested for Malaysia. The discussion is divided into five sections according to the study’s main objectives. Section 5.2 discusses scenario-based long-term applicable adaptation modeling for sustainable food sector based on the MICE approach. Section 5.3 deals with adaptation strategies and their likely effects in supporting sustainable future policy options. Section 5.4 explains the capacity-building options and gaps in the local policy community/network to support adaptation policies, i.e., whether adaptation policies are effective in terms of the associated costs and benefits. Finally, Sect. 5.5 describes the adaptation action and strategy issues facing Malaysia.

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5.2  Suitable Adaptation Policy for Food Sustainability According to the results and findings, this study found the optimum level of adaptation option depending on continuing changes in temperature, emissions, economic growth, population growth, and changes in other related climatic variables for each time segment. The study suggests that a different level of adaptation option over time will be effective in terms of decreasing climate change’s negative impacts. The growing economic activities that are causing climate change and damage reduction options would cause the optimum level of adaptation to increase over time. This study focuses on reactive adaptation actions and the benefits and costs of adaptation. In the case of the food sector, reactive adaptation is particularly important rather versus a proactive response, especially in developing countries since this sector is a substantial source of national income for developing countries and would be effective within a very short gestation gap. The findings are similar to those of related studies, particularly those addressed by the Stern Reports (Stern et al., 2006) and UNFCCC estimates (UNFCCC, 2007a, b). According to the findings, this study found a suitable level of adaptation depending on continued temperature change, emissions, economic growth, population growth, and changes in other related climatic variables for each time segment. The study suggests that different levels (5–15%) of adaptation are applicable over time in combating the negative impacts of climate change. In addition, this study also shows an increasing trend in the costs of adaptation over 50 years. However, the study focuses on responsive adaptation actions and compares the benefits and costs of adaptation. The findings are similar to those of related studies, especially those addressed by Stern Reports (Agarwal et  al, 2014; Stern et  al., 2006) and UNFCCC estimates (UNFCCC, 2007a, b). Stern et al. (2006) estimated the adaptation costs at US$4–37 billion. This particular investigation also applied the World Bank’s methods but reduced the mark-up by 5–20% and a certain percentage of climate-sensitive official development assistance (ODA) to 20%. The benefits of robust and initial actions far outweigh the economic costs of not taking any action. If no action is taken, the overall costs and risks of climate change will be equivalent to losing at least 5–20% of global gross domestic product (GDP) each year, now and in the future. In contrast, the costs of measures taken to decrease greenhouse gas emissions to avoid the worst effects of climate change can be restricted to around 1% of global GDP each year. Food sustainability is a vital issue for Malaysia because it is directly related to food security. As this study found from the previous chapter, it is clear that the adoption of different levels of adaptation represents different levels of food sustainability over time. Unless proven adaptive initiatives are taken to lessen the impacts of climate change on agricultural sectors, food production will diminish over time, along with food sustainability; this would make Malaysia more dependent on food imports. Therefore, this study shows how adaptation action with respect to climate change can help improve food sustainability in the future. Although a 5–20%

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adaptation option is applied to compare the different adaptation actions, this study found from the results that 5–15% adaptation action is more suitable for Malaysia.

5.3  Macroeconomic Effects of Climate Change Our study considers an EDCGECE (Empirical Dynamic Commutable General Equilibrium Model for Climate and the Economy) model as a way forward, in which impacts of climate change are affected by relevant climatic changes, as addressed in the introduction, and investigates the impacts of climate change adaptation policy with its associated costs on agricultural food security issues. In addition, this study evaluates the costs of adaptation to the percentage of GDP, in terms of macroeconomic costs. The results from the simulations show that the benefit of adaptation is huge (e.g., RM4.1 billion) compared to the costs (e.g., RM195 million) and is a small percentage of the estimated GDP. Interestingly, the results show that the costs, as a percentage of GDP, of taking action early on are minor compared to taking action late. These estimations are found to be similar to some earlier global estimates, for example, subject tothe aggregation criteria, funding adaptation would be spending as indicated by 0.1% of the industrialized regions’ as percentage of the national GDP (Stephan & Schenker, 2012). Importantly, following our prioritizing arguments and modeling results, it is obvious that adaptation options (e.g., a basket of approaches) such as management-­ related instruments, infrastructure-related tools, and community-initiated mechanisms, can be improved by 10–15% easily by each broad instrument. Presented here, based on management-related instruments, is a basket of adaptation options related to management tools, which refers to overall efforts from implementing proper irrigation scheduling, timing on operations, development programs on risk management to address moisture deficiencies and effects of droughts and develop early warning systems for seasonal weather predictions and forecasts, integrated pest management (IPM) for crop loss, higher production by greater cropping intensity, modified seeds, diversification of cropping production in irrigated areas, diversification of cropping production in nonirrigated areas, protected cultivation, efficient fertilization, flood- and drought-related advance measuring in coordination with early warning systems, and improved postharvesting technology. Within the improvement by 10–15% of each broad instrument, our EDCGECE results indicate that under climate change, the agricultural yield losses can be offset by 20–25% up to the year 2065, making it possible to maintain food security and food sustainability over time at modest cost now as opposed to later. In addition, based on infrastructure-related instruments, a basket of adaptation options relates to infrastructure-related tools that can be improved by 5–15% such as for irrigation facilities, storage and milling facilities, and other forms of mechanization. Importantly, infrastructure-related instruments include efforts to maintain rice production with proper irrigation facilities, which can be sustained by federal and local government, ad hoc compensation and assistance programs for the risk of

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farm-level income loss associated with disasters and extreme events, suitable storage and milling facilities run by local government, plowing and harvesting facilities administered by local communities, postharvesting technologies developed by government, and farm-level land and management practices in light of changing climate conditions. Within the improvement by 5% of each broad instrument, our EDCGECE results indicate that clime-change-related negative impacts on food sustainability can be fully offset by adaptations that would cost 15–20% of GDP up to the year 2065. Finally, community (CBOs (Community-based organizations) and NGOs)initiated instruments include a basket of adaptation policies related to small-scale capacity building, credit facilities, and marketing support for community-initiated tools. The community initiated tools (CBOs and NGOs) refer to efforts to maintain rice and other grain production based on small-scale capacity building by farmers, more microcredit facilities by small NGOs, and marketing support by local groups. However, the federal and provincial governments must maintain some provisions for the acceptable and accurate information and training programs for climatic damage in food production. It will enhance more applicable policy options of climate change adaptation measures for food sustainability. Our EDCGECE results indicate it can be improved by 15–20% easily by each broad instrument with the help of CBOs and NGOs, and the study findings reveal that food sustainability can be offset by 10–20% up to the year 2065 (Al-Amin & Ahmed, 2016). Climate costs appear to be relatively moderate, representing only a fraction of overall real GDP (RGDP). It should be emphasized, however, that offsetting structural and resource shifts at the macro level may conceal serious adjustment costs for some stakeholder groups within economies. Impacts are quite heterogeneous across countries, with lower-income countries being more adversely impacted by agriculture-­related constraints (crops, water, and land). Because these countries have higher shares of GDP in agriculture and much higher expenditure shares on agro-food products, agriculture-related climate impacts hit low-income economies harder (Metelerkamp, 2011). This fact, coupled with their more limited financial, institutional, and other means for adaptation, indicates that lower-income Asia generally and South Asia and Southeast Asia in particular will face higher-than-average climate adaptation challenges. As a way forward to address food sustainability issues, this study considers a MICE model, in which impacts of climate change are affected by relevant climatic factors. Thus, it has been investigated the different adaptation policy options to determine the climate change impacts that are associated with the food sustainability issues. In addition, this study evaluates the costs of adaptation compared to the percentage of real GDP to determine the macroeconomic costs. The results from the simulations show that the costs of adaptation represent a small percentage of estimated GDP.  Interestingly, the results demonstrate that early action costs can be reduced, whereas if adaptation measures are taken too late, the costs will increase as a percentage of GDP. Furthermore, the results establish that, for the food sector, the costs of adaptation continue to be a small percentage of GDP.

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These estimates are similar to previously reported global estimates and are subject to aggregation criteria and funding for adaptation options. For example, for industrialized regions, this spending amounts to 0.1% of GDP (Stephan & Schenker, 2012). Many estimates have been made of the net economic cost of damage (also called the social cost of carbon) and adaptation orientation resulting from climate change. Citing the results of the Global Vulnerability Assessment (GVA) of coastal communities in several countries in the 1993 IPCC report, Frankhauser (2006) pointed out that coastal adaptation could reduce the number of people at risk from flooding by almost 90%, at an annual cost of around 0.06% of GDP, while in agriculture, adaptation could result in avoided yield losses of as much as 30%. Indeed, adaptation costs are already a significant part of the impacts of climate change, and the results cited earlier show that adaptation investments could have high, positive net benefits. Tol et al. (1998) estimated adaptation costs at 7–25% of total damage for a doubling of atmospheric concentrations of carbon dioxide. If total damage were 1–2% of world income, then adaptation costs would range from 0.1–0.5% of GDP. The Stern Report cited a much higher cost of adaptation of US$15–150 billion each year (0.05–0.5% of GDP) for OECD countries alone and only for making new infrastructures and buildings climate-resilient (Francisco, 2008). Adaptation costs could be much higher in those areas that are most vulnerable to climate change. For small-island developing states (SIDS) like Jamaica, the cost of protecting the country’s coastline from a 1-m sea level rise could account for 19% of the country’s GDP, or US$462 million per year (UNFCCC, 2005). Similar studies, for example by Stern (2006), found that the costs of adaptation measures for the whole world would be a minimum of US$4 billion to a maximum of US$37 billion per year, whereas the World Bank estimates (2007) that the annual costs of adaptation may vary from US$10 to 40 billion. In contrast, UNFCCC (2007a, b) estimates show different results. According to those projections, the annual costs of adaptation to climate change by 2030 will be in the range of US$46–171 billion, and about US$28–67 billion will be needed for developing countries. The UNFCCC estimated that additional investment of US$28 –67 billion per year will be needed by 2030 for adaptation in developing countries (Smith et al., 2016). The World Bank also estimated that the adaptation costs for developing countries will be approximately US$80 –90 billion annually by 2030 (UNFCCC, 2007a, b; Smith et al., 2016). Ahmed and Suphachalasai (2014) showed that South Asia on average could lose nearly 2% of its GDP by 2050, rising to a loss of nearly 9% by 2100. However, that study found adaptation costs be around RM0.0022 million to RM 0.0023 as a percentage of GDP from the baseline year 2015 until the scenario year of 2065. But the adaptation benefit is almost RM0.030 million as a percentage of GDP for the year 2065. Therefore, it may be asserted that the adaptation benefit exceeds adaptation costs for Malaysia from 2015 to 2065. If this study considers the national GDP of Malaysia, in that sense the adaptation costs are negligible as a percentage as GDP. Thus, Malaysia can set fairly ambitious targets for certain adaptation options in the food sector.

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5.4  P  redicted Implications of Adaptation Options for Food Sustainability The general goal of this study is to evaluate the applicable adaptation options for a sustainable food sector following climate change impacts on the Malaysian economy with and without adaptation measures and options. To determine the outcomes in terms of food security or food sustainability based on the food sector in Malaysia, the 2005 input-output table of the national accounts is considered. It can be seen that the benefit of adaptation tends to increase at a higher rate than the rate of associated costs over time. This implies that the benefit-cost ratio will continue to increase over the given time period. The positive values for food sustainability indicate adaptation is effective in terms of agricultural food production because production without an adaptation policy in place is less than production with an adaptation policy in place for the next 50  years compared with the baseline scenario (Al-Amin & Ahmed, 2016). The trend in climate change in the region establishes the fact that the adaptation policy would be beneficial for Malaysia in terms of food sustainability or food security as far as climatic issues are concerned. Thus, based on the findings of this study, it may be suggested that the optimum adaptation policy should be implemented by the Malaysian policymakers. However, farmers in Malaysia in practice are paying little attention to planning for potential climate change impacts at both the individual and community levels. Generally, farmers cope with weather patterns on a short-term basis and can sometimes adjust to potential risks and weather variability through best management practices, but climate change may pose new, unpredictable risks to Malaysia, like the rest of the world (Al-Amin & Ahmed, 2016). This proposition (5–20% adaptation option) is valid, because our research findings indicate that the impacts of climate change are projected to increase over time, which could ultimately reduce outputs of all economic sectors. Hence it is the government’s responsibility to formulate optimum adaptation policies with the help of the basket of adaptation options because the benefits of adaptation can be achieved collectively (Al-Amin & Ahmed, 2016). However, in Malaysia at present, no separate, specific policy exists for every economic sector that would address the impacts of climate change on individual sectors and their productivity. Unfortunately in Malaysia there exists a serious lack of information in this regard. Hence, it is apparent that for Malaysia the main obstacles include a lack of knowledge of climate change impacts, limited conservation facilities, and political will, for example (Al-Amin & Ahmed, 2016). Moreover, Malaysia faces a distinct and important challenge, which is the continued uncertainty about the extent of the climate change effects it will face. It is also unsure as to what extent adaptation will reduce vulnerability to climate change in the Malaysian context. Thus, despite the uncertainties, rigorous effort is evaluated by our EDCGECE to facilitate decision-making based on projections. Subsequently, for a range of climate change scenarios, a range of adaptation options and costs is estimated (Al-Amin & Ahmed, 2016).

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Piao et al. (2010) highlighted that one can appreciate that reconciling observed temperature and precipitation trends with future projections for China remains a major scientific challenge. This can be addressed using regional models fitted with aerosol and chemistry effects on climate and improved descriptions of land–atmosphere feedback processes, to enable improved impact studies and to design cost-­ effective adaptation measures. In some previous impact studies, human behavior is presumed to remain virtually unchanged in response to climate change. Thus, the recent literature suggests that human behavior would not change much as expected by neither the anticipatory nor autonomous adaptation literature (Hanf & Soetendrop, 2014). Because climatic issues are evident and factual from the recent scientific findings of the IPCC, the motivation of adaptation to anticipatory adaptation must be changed (Al-Amin & Filho, 2014). An effective adaptation policy would be effective in terms of food sustainability particularly in agro-based sectors (Al-Amin & Filho, 2014). Some recent studies suggested that without an adaptation policy, the impacts of the climate change on a society will possibly be tightly connected to the so-called dumb farmer hypothesis.1 In particular, some studies estimated climate change damage based on extreme weather events, morbidity, hunger, health, and other related issues. Ignoring adaptation is undoubtedly insufficient and may lead to an overestimation for the probable impact of climate change vulnerabilities. To investigate the adaptation policy in reducing impacts, the value of the damage with and without adaptation policies can be compared (Al-Amin & Filho, 2014). O’Brien et al. (2006) estimated the impacts of climate change with an adaptation policy on the food sector using an arbitrary set of low-cost adaptation measures; for example, they considered an adaptation action such as increased irrigation or a change in planting date. That study was conducted when adaptation issues were initially raised in the scientific literature, and the results showed that adaptation could reduce damage to the Missouri-Iowa-Nebraska-Kansas region by 30–60% for the food sector. The trend is found similar in our current study conducted. Many other studies also showed similar results (Al-Amin & Filho, 2014). Kurukulasuriya and Rosenthal (2013) classified adaptation into three arbitrary levels, and the results from the global study showed that a change of 1.2–7.6% in cereal grain output/ production (worldwide) without adaptation was related to 0–5% damage with an adaptation policy. The current study also obtained similar findings and showed that adaptation policy was favorable. Reilly et al. (1994) estimated the similar study utilizing Rosenzweig and Parry’s (1994) data in the 1990s. However, the present study found that loss of GDP is less than that found by Reilly (1994) and the damage is less than that shown by them because this study only considered agro-based sectors. These results are similar to the recent studies of Francisco (2008) that implemented adaptation strategies for Southeast Asian regions, Piao et al. (2010) in China, and Beintema et al. (2012) in India.

 Nevertheless, this dumb farmer hypothesis of no adaptation has been used in some impact studies.

1

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The aforementioned linear trend can be influenced by other factors shifting the amount of damage up or down, for example, population growth, which affects the number of people involved. In addition, income growth affects people’s valuation of impacts, and this results in a change of preferences affecting valuation (de Bruin et al., 2009b). However, in order to achieve different damage values for each time segment, the current study included Malaysian agro-based income and agro-population data in the model. Provided that adaptation is applied as optimally, de Bruin et al. (2009b) argue that the benefits of the adaptation policy will always outweigh the costs. This kind of modeling belongs to the category of reactive adaptation. This result also revealed the same proposition as shown in Fig. 4.10. According to Tol et al. (1998), during the early period 2025–2034, the savings from an optimal adaptation and mitigation option compared to no action (with cost reduction of 3%) is very small, whereas the benefits of action increase dramatically over time. The maximum benefits are possible in the period 2045–2055. This finding is in line with this study’s results, which showed the benefits of adaptation to be 0.04% of RGDP in 2015 and tending to increase to 1.7% of RGDP by 2055. Practically speaking, wide-ranging modifications in management could offset all losses. However, the gains would more likely come from developed countries. Since developing countries have more resource limitation, therefore adaptation policy is assumed to be fairly less effective and these will continue to suffer from significant losses. On the other hand, damage from climate impacts could be reduced moderately when developing countries will have enough adaptation funding and technology transfer assistance from the developed countries (de Bruin et  al., 2009a). However, similar trends are found in this study as well compared to other related and similar regions.2 For the case of Malaysia, this study found that without investing in adaptation measures, climate change will cause significant losses in RGDP (almost 5.7% of RGDP). But the application of different adaptation policies can significantly reduce losses, which constitutes the benefit of adaptation. This study shows that the benefit of adaptation exceeds the costs of adaptation for each time segment considered. This implies that the policy is beneficial in terms of costs and benefits for Malaysia’s food sector. Hope et  al. (1993) developed a similar model, called the Policy Analysis for the Greenhouse Effect (PAGE) model. The model compares the cases of no adaptation and aggressive adaptation. For the no-adaptation case, impacts are accepted as they occur and when they occur. The effect of aggressive adaptation is that the food sector face no damage from a 2 °C rise in temperature by 2100. If the temperature rise is more than 2 °C, further implemented measures reduce the impacts of climate change by up to 90% compared to that of the no-adaptation scenario. But adaptation should only be implemented if benefits exceed the costs of adaptation. The estimated results show that the adaptation costs of 0.5 trillion euros will avoid damage from climate change impacts by 17.5 trillion euros. Therefore, adaptation should be implemented to a large extent.

2  For example, Africa can reduce its gross damages by 35% with adaptation in the amount of 7% of gross damages.

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However, this study established that even a small temperature change (e.g., 0.73 °C by 2005) would contribute to accelerated damage due to climate change. Some studies specifically focus on impacts on the food sector and only assess the benefits of adaptation rather than costs and benefits (Beintema et  al., 2012). Nevertheless, considering a society that is fully adapted, the impacts of climate change will be reduced, but progress in this direction could be costly and achieved only with sufficient planning and appropriate policy measures. Thus, as a way forward, this study devotes more attention to distribution issues. However, it is predicted that the costs and benefits of adaptation will be distributed unevenly among different sectors of the economy. In the case of government finances in connection with adaptation, the distribution aspects require more consideration through adequate funding of measures. Such distribution measures can be translated into action by looking at the costs and benefits for the scenario trends estimated in the current study. For adaptation in conjunction with other measures, the choice of policy response is expected to be dependent on the distribution considerations in other cases in Malaysia. The results show that for the entire food sector the benefit tends to exceed the associated costs. Another similar study, namely FUND (Narita et al., 2010), simulated damage due to climate change in key areas such as forestry, agriculture, energy, water resources, ecosystems, sea level rise, mortality, and human health. Adaptation occurs in that model via the agriculture food sector in connection with food sustainability. A parameter denoted by the speed of adaptation lowers the impact of climate change on this sector. The adaptation costs are only modeled implicitly while explicit adjustment costs are lacking (Warren et al., 2006). Thus, the present study represents one step forward compared to that one because it considers adaptive measures by looking at the adjustment costs over time for each time segment. Based on FUND,3 the results of 2000–2100 show for the business-as-usual scenario at a global level a small benefit from climate change for a very moderate increase of about 0.5 °C above 1990 levels. But for greater temperature increases, damage rises as global warming increases. For a 3 °C rise in temperature, damage will amount to between 1.2% and 2.7% of global GDP per year. For a 2 °C rise the damage is still between 0.5% and 1.0%. Compared to the results of the DICE model (0.5% loss for a 2 °C rise in temperature), the damage estimates are very similar (Warren et al., 2006). However, the present study’s model shows that with a 2 °C rise of temperature would bring a damage of 2.4% of Malaysian RGDP (Al-Amin & Ahmed, 2016). Thus, this study is justified by recent global studies carried out on food sustainability issues in the face of climate change.

3  The FUND (Climate Framework for Uncertainty, Negotiation and Distribution) model, developed by Tol (1997), is based on the DICE model but it contains a regional specification like AD-RICE and MERGE. FUND also includes interregional capital flows and a detailed specification of the functions to assess the damage costs of climate change.

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5.5  Adaptation Action and Policy Issues for Malaysia Based on the findings of the study, an evaluation is made as to what adaptation actions should be taken in Malaysia based on national GDP. According to a literature review and field visits, it is found that farmers in practice are paying little attention to planning for potential climate change impacts at both the individual and community levels. Generally, farmers can cope with weather patterns on a short-­ term basis and sometimes adjust to potential risks and weather variability through best management practices. This proposition is valid because the present research found that the impacts of climate change are projected to increase over time, which will ultimately reduce outputs from all sectors of the economy. Hence, it is government’s responsibility to implement the best adaptation actions to achieve the maximum benefits collectively (Al-Amin & Ahmed, 2016). However, presently in Malaysia, no specific policy exists for the agro-economic sector that would address the impacts of climate change and address food sustainability issues. Thus, there exists a huge lack of information in this regard with respect to Malaysia. Moreover, it is apparent that the knowledge gap is one of the greatest obstacles to an effective adaptation policy in agro-based sectors that would address the impacts of climate change. There is also a lack of suitable restoration facilities and geopolitical willingness (Dubash et al., 2013). In addition, there is a distinct and main challenge for Malaysia in the face of continued uncertainty with respect to the consequences of climate change and the proper guidelines for a suitable adaptation policy in the food sector in terms of food security and sustainability. Also uncertain is the extent to which adaptation would reduce climate change vulnerability concerns in the Malaysian context. Therefore, despite these uncertainties, rigorous effort is being made to facilitate decision-making for adaptation policy based on climate change projections. Thus, for a range of climate change scenarios, a range of adaptation options and costs are estimated. Taking all these into consideration, this study has taken the initiative in formulating guidelines for maintaining food security and sustainability over time (Al-Amin & Ahmed, 2016). Adaptation to climate change as presented in this study is not a new concept in some developed countries, but it is quite new for developing and advanced developing countries. This study also finds different optimum levels of adaptation under different climate conditions over different time periods. Our suggestion to policymakers is to implement a policy with sufficient funding to improve awareness and change the attitudes of Malaysians toward such a policy (Al-Amin & Ahmed, 2016). Some critical issues have been explicitly considered in developing countries like Malaysia to address climate change impacts in food sustainability. Thus, there may be advantages and disadvantages to solving the issues raised in this study as presented. Though, there are some uncertainties still retained to estimate the real economic damage of climate change but an equal distribution of resources could help to find a suitable adaptation policy in the developing countries (Al-Amin & Ahmed, 2016). This study focuses on certain issues, as follows:

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1. he impacts and costs of climate change measures cannot be optimally determined on a global basis because impacts can vary from region to region, between countries, or even within the same country. Hence, it is necessary to assess the feasibility of adaptation plans so that appropriate adaptation actions can be taken for a specific country, as has been done in the case of Malaysia. 2. Impacts of climate changes can affect all sectors of the economy differently. The food sector is one of the most vulnerable sectors because it depends directly on weather conditions. It is also the most important sector because it is directly related to food security and economic development, which has been addressed in this study. 3. Appropriate adaptations can greatly reduce the magnitude of the impacts of climate change. Existing knowledge regarding adaptive capabilities and adaptation options is not sufficient in Malaysia. Future projections of adaptation options and policies and their associated costs are unreliable in terms of monetary value, as highlighted in this research.

5.6  Summary This chapter discussed the research findings in relation to insights from other research findings in the literature. The results clearly indicate that for Malaysia, climate change would bring negative impacts that can be reduced through adaptation policy. This study’s findings reveal that the benefits of adaptation policy are higher than the associated costs for every time segment considered in the study’s simulation. The next chapter concludes this study with some adaptation policy recommendations for Malaysia.

References Ahmed, M., & Suphachalasai, S. (2014). Assessing the costs of climate change and adaptation in South Asia. Asian Development Bank. Al-Amin, A. Q., & Ahmed, F. (2016). Food security challenge of climate change: An analysis for policy selection. Futures, 83, 50–63. Elsevier. Al-Amin, A. Q., & Leal Filho, W. (2014). A return to prioritizing needs: Adaptation or mitigation alternatives? Progress in Development Studies, 14(4), 359–371. Agrawal, A., Wollenberg, E., & Persha, L. (2014). Governing agriculture-forest landscapes to achieve climate change mitigation. Global Environmental Change, 29, 270–280. Beintema, N., Stads, G.-J., Fuglie, K., & Heisey, P. (2012). ASTI global assessment of agricultural R&D spending: Developing countries accelerate investment. International Food Policy Research Institute (IFPRI). de Bruin, K., Dellink, R.  B., Ruijs, A., Bolwidt, L., van Buuren, A., Graveland, J., de Groot, R. S., Kuikman, P. J., Reinhard, S., Roetter, R. P., Tassone, V. C., Verhagen, A., & van Ierland, E. C. (2009a). Adapting to climate change in The Netherlands: An inventory of climate adaptation options and ranking of alternatives. Climatic Change, 95(1), 23–45.

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de Bruin, K. C., Dellink, R. B., & Tol, R. S. (2009b). AD-DICE: An implementation of adaptation in the DICE model. Climatic Change, 95(1), 63–81. Dubash, N. K., Hagemann, M., Höhne, N., & Upadhyaya, P. (2013). Developments in national climate change mitigation legislation and strategy. Climate Policy, 13(6), 649–664. Francisco, H. A. (2008). Adaptation to climate change: Needs and opportunities in Southeast Asia. ASEAN Economic Bulletin, 7–19. Frankhauser S. (2006). The economics of adaptation. Hanf, K., & Soetendorp, B. (Eds.). (2014). Adapting to European integration: Small states and the European Union. Routledge. Hope, C., Anderson, J., & Wenman, P. (1993). Policy analysis of the greenhouse effect – An application of the PAGE model. Energy Policy, 21, 327–338. Kurukulasuriya, P., & Rosenthal, S. (2013). Climate change and agriculture: A review of impacts and adaptations. Metelerkamp, L. (2011). Commercial agriculture in the Swartland: Investigating emerging trends towards more sustainable food production. Doctoral dissertation, University of Stellenbosch. Narita, D., Tol, R. S., & Anthoff, D. (2010). Economic costs of extratropical storms under climate change: An application of FUND. Journal of Environmental Planning and Management, 53(3), 371–384. O’Brien, K., Eriksen, S., Sygna, L., & Naess, L. O. (2006). Questioning complacency: Climate change impacts, vulnerability, and adaptation in Norway. Ambio: A Journal of the Human Environment, 35(2), 50–56. Piao, S., Ciais, P., Huang, Y., Shen, Z., Peng, S., Li, J., & Fang, J. (2010). The impacts of climate change on water resources and agriculture in China. Nature, 467(7311), 43–51. Reilly, J., Hohmann, N., & Kane, S. (1994). Climate change and agricultural trade: Who benefits, who loses? Global Environmental Change, 4(1), 24–36. Rosenzweig, C., & Parry, M. L. (1994). Potential impact of climate change on world food supply. Nature, 367(6459), 133–138. Smith, J.  B., Dickinson, T., & Donahue, J.  D. (2016). Development and climate change adaptation funding: Coordination and integration. In International Climate Finance (pp. 72–89). Routledge. Stephan, G., & Schenker, O. (2012). International trade and the adaptation to climate change and variability. ZEW-Centre for European Economic Research Discussion Paper, (12-008). Stern, N. H., Peters, S., Bakhshi, V., Bowen, A., Cameron, C., Catovsky, S., & Zenghelis, D. (2006). Stern review: The economics of climate change (Vol. 30, p. 2006). Cambridge University Press. Tol, R.  S. J. (1997). On the optimal control ofcarbon dioxide emissions: An application of FUND. Environmental Modeling and Assessment, 2, 151–163. Tol, R. S., Fankhauser, S., & Smith, J. B. (1998). The scope for adaptation to climate change: What can we learn from the impact literature? Global Environmental Change, 8(2), 109–123. United Nations Framework Convention on Climate Change (UNFCCC). (2005). Climate change: Small island developing states. Bonn. United Nations Framework Convention on Climate Change (UNFCCC). (2007a). Climate change: Impacts, vulnerabilities and adaptation in developing countries. Bonn. United Nations Framework Convention on Climate Change (UNFCCC). (2007b). Climate change: Impacts, vulnerabilities and adaptation in developing countries. Bonn. Warren, R., Arnell, N., Nicholls, R., Levy, P., & Price, J. (2006). Understanding the regional impacts of climate change. Tyndall Centre for Climate Change Research Working Paper, 90.

Chapter 6

Climate Change Adaptation Policy Recommendation for Food Security in Malaysia

Abstract  This chapter ends with policy proposals focused on the study’s conclusions and clarifies the study’s strengths and shortcomings, as well as its realistic contribution, before pointing out potential research opportunities. According to the Malaysian Integrated Climate and Economy (MICE) model, different approximate values for different levels of adaptation, i.e., 5–20%, were found promising in this study. Following a 5–20% adaptation intervention, both residual and net damage are minimized. Residual loss, on the other hand, decreased from 4.98% to 23.07%, amounting to RM403 million. On the other hand, in terms of net damage, it showed a downward trend of 5–20%, or RM209 million. However, if the adaptation of 5–20% is used instead, these results for residual damage and net harm show a promising pattern. As a result, if the appropriate adaptation option (5–20%) is implemented, it is clear that such policies would have a positive effect on the national economy in terms of climate change mitigation, food security, and long-term sustainability. Recall bias and willful misreporting may affect longer time frames, differences in social discount variables, imperfect competitiveness, numeraire price, and short-run to long-run time choice. Despite the fact that extreme vigilance is exercised during modeling, the findings could have under- or overreported on specific actions discussed in this section. While several variables were examined to fulfill the study’s goal, the omission of other variables may restrict the applicability of the conclusions, and some of the usual criticisms may appear in the analyses. Qualitative research in the future will be beneficial in gaining a deeper understanding of the problems discussed here. While this research is specifically important for climate policy shocks to food sustainability in Malaysia, it can serve as a guideline or foundation for other developing countries fighting climate change for long-term food security.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4_6

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6.1  Introduction The chapter concludes with some policy recommendations based on the findings of this study. Also, it clarifies the strengths and weaknesses and practical contributions of the study before highlighting further opportunities for future research.

6.2  Summary of Findings 6.2.1  Different Levels of Adaptation Action This study found different estimated values for different levels of adaptation, i.e., 5–20%, based on the Malaysian Integrated Climate and Economy (MICE) model. Both residual damage and net damage are reduced after taking 5–20% adaptation actions. However, residual damage declined from 4.98% to 23.07%, which amounts to RM403 million. On the other hand, with respect to net damage, a 5–20% decreasing trend was shown, which indicates RM209 million. However, these results for residual damage and net damage indicate a positive trend if the 5–20% adaptation option is implemented in Malaysia. Therefore, if the proper adaptation policy of 5–20% is adopted, then it is clear that such measures will bring a positive outcome to the national economy against the impact of climate change in terms of suitable food security and greater sustainability.

6.2.2  Adaptation Policy Costs and Benefits The results from the simulations showed the costs of adaptation to be a small percentage of estimated real gross domestic product (RGDP). Interestingly, the results show that early action costs are as little as 0.0022–0.0023% for a 5–20% adaptation option, as a percentage of GDP, whereas if adaptation measures are taken later, the costs increase more than expected because of the longer period during which damage, as a percentage of GDP, from climatic change can accrue. Furthermore, the results showed that the adaptation benefit was 0.030% of GDP for the baseline year 2015 with 5% adaptation action, but it increases by the 2065 scenario, at 0.031% of GDP under a 20% adaptation plan. These values increase in a consistent manner, i.e., linearly over the entire simulation period of 50 years from 2015 to 2065. But the rate of change of adaptation costs for each time segment are not the same throughout the simulation period. For example, for 2015, government expenditures for a 5% adaptation option are RM89,689.301 million, but in 2065 government expenditures increase up to RM99,188.938 million. The patterns for other simulations, like 10%, 15%, and 20% adaptation plans, are similar throughout the adaptation scenarios and outcomes.

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6.2.3  Impacts of Climate Change for Adaptation Option Climate change has real impacts on the production side of the economy because it has a direct impact on physical output. Temperature increases will directly affect crop production. Thus, production is negatively affected by the impact of climate change. This study simulated three scenarios to evaluate the impacts of adaptation options with the associated costs on the economy: (i) a baseline scenario (BS), (ii) estimated food sustainability with no adaption (EFSNA), and (iii) estimated food sustainability with adaption (EFSWA). The study investigated the impact of adaptation policies on real GDP, the production of commodities, government expenditures, and other related macroeconomic and climatic variables. It is obvious from these findings within the three scenarios that if no adaptation action is taken, then residual damage, according to the optimized model of this study, will increase gradually. Though the residual damage is RM1746.86 million in the baseline year 2015, in 2065 the model shows a rapid increase in residual damage, as high as RM2017.94 million without any adaptation measures. The findings show an increase in damage trends in all segments of the study periods, 2015–2025, 2025–2035, 2035–2045, 2045–2055, and 2055–2065. However, the study also focused on different scenarios of residual damage applying different levels of adaptation, such as 5–20%. Specifically, these findings show that the residual damage decreases significantly with reference to the 2015 baseline year after adopting 5% adaptation policies. Similarly, the trend of residual damage for other scenarios involving 10%, 15%, and 20% adaptation policies is one of gradually declining damage over the baseline values of each segment. Thus the findings justify the rationale of taking adaptation action in different scenarios from 2015 to 2065. On the other hand, this study compares all scenarios of net residual damage with the baseline and found all values to be negative. These findings represent one step further in the clarification of projections and scenarios and help to justify the rationale of adaptation in this study. The results thus show that the cost will be below RM1 million in the application of the 5% adaptation policy based on the 2015 baseline year until 2065. The findings show the cost of adaptation will rise over time. The cause is straightforward since the level of adaptation must increase over time to allow for food sustainability, and a higher level of adaptation will be required as continued economic activity will cause climate change and gross damage to rise as well over the indicated time periods. For example, if the 10% adaptation policy is applied from the baseline (2015), then the cost will be about RM15 million, and if the 15% adaptation policy is applied, then the cost will be about RM53 million and just over RM60 million in 2065; a 20% adaptation policy based on the baseline (2015) will entail costs of around RM167 million in 2015 and RM193 million in 2065. This study also identified other adaptation costs in connection with government expenditures and as a percentage of GDP and compares their dimensions based on impacts on other related macroeconomic variables. However, the study’s findings show that adaptation would incur costs in addition to government expenditures over time after applying different adaptation actions. Thus, it is clear that government

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expenditures will be higher than if no adaptation policy were adopted by the amount of adaptation costs, but the additional costs of adaptation compared to damage are found to be marginal in terms of monetary value and percentage change. The findings relating to the different levels of adaptation actions show that even for the year 2065, additional adaptation costs are marginal for each time segment to support sustainable future strategies. The findings indicate that after applying different levels of adaptation over time, food sustainability rises considerably, and food sustainability in the baseline year 2015 is projected to be RM3566.24 million and in 2065 RM4097.42 million, without adaptation, but comparatively it shows a gain of 10% or more in different adaptation scenarios. Thus, food sustainability in the baseline year 2015 is RM3576.82 million with a 10% adaptation level and RM3619.48 million with a 15% adaptation level; higher adaptation levels show greater gains over time. Similarly, food sustainability in 2065 will cost RM4109.64 million at a 10% adaptation level and RM 4158.92 million at a 15% adaptation level; higher adaptation levels also show greater progress. The contrasted scenarios with the baseline and over time are found to advance and food sustainability to rise proportionately as the percentage of adaptation policy rises. Further, related to RGDP, the findings of this study indicate different RGDP scenarios after taking into consideration different adaptation actions over time (e.g., 2015–2065) to justify and to know the importance of adaptive actions to consider from an economic viewpoint. On the other hand, according to the study’s findings, the RGDP figures as projected progress in line with the different levels of adaptation actions. Adaptation actions between 5% and 15% reflect a rising RGDP, but 20% adaptation actions abruptly result in a decline in RGDP.  This shows that a 20% adaptation action level is not appropriate for the current national agenda in maintaining food security. Some critical factors need to be considered before applying that level of adaptation action to overcome the decline in RGDP. According to the study’s projections, RGDP will be RM464,793.1 million in 2015, RM478,465.7 million in 2025, RM492,510.3 million in 2035, RM506,918.0 million in 2045, RM521,727.4 million in 2055, and RM536,921.8 million in 2065, without adaptation action. In contrast, with a 5% adaptation action, RGDP “increases from baseline” in 2015 at RM73.85 million, RM76.25 million in 2025, RM73.14 million in 2035, RM81.35 million in 2045, RM76.67 million in 2055, and in 2065, it will be RM86.48 million, and the trend advances over time with a higher level of adaptation action, except 20%. Thus, according to the present research findings, the percentage of GDP of adaptation costs in 2015 is 0.00229% and the benefit is 0.0301%, the percentage of GDP of adaptation costs in 2025 is 0.00229% and the benefit is 0.0302%, the percentage of GDP of adaptation costs in 2035 is 0.00229% and the benefit is 0.0324%, the percentage of GDP of adaptation cost in 2045 is 0.00229% and the benefit is 0.0303%, the percentage of GDP of adaptation costs in 2055 is 0.00229% and the benefit is 0.1280%, and, finally, the percentage of GDP of adaptation costs in 2065 is 0.0024% and the benefit is 0.0305%. This implies that the benefit-to-cost ratio would continue to increase over the period of time except for a 20% adaptation action.

6.3  Capacity-Building Options and Gaps in Local Policy Community

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6.3  C  apacity-Building Options and Gaps in Local Policy Community Climate change is happening and bringing with it changes in climatic risk patterns. The impacts of climate change have the potential to undermine development achievements and threaten the food security of tens of millions of people, especially those living in the least developed countries (LDCs). The IPCC’s Fourth Assessment Report recognized a trend toward increasing climate variability associated with more extreme weather events that are likely to have a direct impact on rural livelihoods, particularly in LDCs. Although Malaysia is the top developing country, its food sectors are still severely vulnerable to climate change. Because agriculture is one of the most climate-sensitive sectors, food security is under stress due to greenhouse gas emissions and so-called climatic factors, so sustainable adaptation strategies need to be developed to counterbalance the future effects of climate change. It is imperative to identify and institutionalize mechanisms that enable the most vulnerable farmers and local communities to cope with climate change impacts. This means that farmers and local communities must be supported in preparing themselves for the changing situations and taking the steps that will improve their ability to protect their livelihoods. However, there is no one-­ size-­fits-all solution. Awareness must be increased and capacity-building processes are urgently needed at all levels that will support long-term learning processes and, at the same time, take into consideration a broad range of ecosystems and socioeconomic conditions. Decentralized programs seem most appropriate to promote local adaptation, within the framework of coherent national policies. With this in mind, specific attention should be given to the development of location-specific adaptation options that can manage future anticipated risks and take biophysical, socioeconomic, and sociocultural factors into consideration, such as those carried out in this study. A more systematic and consistent application – sustainable agricultural, forestry, and fisheries practices – is already known that may serve as a suitable entry point to adapt to and mitigate the impacts of changing climates and environmental conditions. Knowledge gaps remain as to how long these practices would be able to counteract the impacts of climate change and how best to design and promote adaptation processes, in view of uncertainty in climate change scenarios and location-specific impacts. However, immediate action is needed to manage the existing and future risks within the framework of broader understanding on the most likely impacts of climate change. Case studies of adaptation processes are needed that will add to gathering, disseminating, and replicating good practices, especially for the most vulnerable. The following capacity-building programs can be initiated in Malaysia along with any given country to increase community engagement for climate change adaptation: 1. Technical capacity: Particularly in the areas of meteorology, hydrology, and preparation of national communications (NC), emissions inventories, and vulnerability and adaptation assessments;

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2. Institutional capacity: Enabling local, regional, and national authorities and civil society to respond to disasters, adapt to climate change, and plan and adopt mitigation measures; strengthening the capacity of national focal points, e.g., in negotiating skills; 3. Research and systematic observation: Involvement of all sectors of society in recording information on climate and natural resources (e.g., rainfall, fish landings, soil quality, crop yields, and vegetation cover); strengthening research capabilities in academic institutions; development of new and appropriate technologies (e.g., renewable energy, flood control measures); 4. Vulnerability and adaptation assessment: Use of community-based techniques to measure and record information and assess vulnerability to climate change; training of technicians to better assess risks due to climate change; 5. Integration of adaptation responses into national development strategies: Building capacity to respond to climate change events; reducing risk of climate impacts on infrastructure investments (climate proofing), e.g., disaster preparedness, use of traditional knowledge and new technologies, and coordinated regional response; 6. Enabling environments and technology transfer: Introduction of appropriate technologies to aid adaptation (e.g., flood control systems, emergency shelters) and mitigation (e.g., energy efficiency, reforestation); strengthening capacity to adopt and maintain new technologies; 7. Clean Development Mechanism (CDM): Capacity development to enable developing countries to engage in CDM projects; support for establishment of designated national authorities; 8. Probabilistic climate forecasting: Introducing concept of probabilistic climate forecasting; 9. “No-regret” technologies: Initiating field testing of adaptation options with “no-regret” technologies; 10. Launching local interactions: Launching local interactions on the basis of traditional knowledge and existing local adaptation practices to climate risk; 11. Adaptation promotion: Promoting adaptation to current climate variability and extreme events; 12. Increased awareness: Addressing longer-term issues of climate change through awareness building.

6.4  Policy Suggestions Policy suggestions are always a crucial issue for any research because inappropriate policy recommendations would result in wrong policy action. Thus, this study maintains a cautious stance on the application of action and national issues as a reference concept with respect to most climate change impacts on the food sector and climate policies, which are either global or regional. However, the impacts and costs of climate change cannot be optimally determined on a global basis because

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climate change impacts differ from region to region, from country to country, or even within the same country. It is thus necessary to assess the feasibility of future adaptation plans on country-to-country basis to choose the appropriate adaptation actions to support sustainable future strategies in connection with food security challenges. Considering the importance of the food sector for the Malaysian economy, this study evaluated the impact of climate change and tried to find the optimal adaptation option to support sustainable agro-food strategies. The key questions to answer have to do with which level of adaptation is optimal for a tropical country like Malaysia, the estimated costs of adaptation, and how adaptation will affect the food sector in terms of maintaining Malaysia’s target food sustainability vision. This study shows that with continued economic activities (e.g., causing climate change) along with increased gross damage values, the optimum level of adaptation (5–20%) points to an increase over time to maintain food sustainability. However, what degree of adaptive actions are applicable to Malaysian agro sectors estimated using the optimum level of adaptation with the values of gross damage to adaptation actions? The residual damage reduction and minimum adaptation costs with comparative cost-benefit outcomes of adopting adaptation actions by 5–20% over time support food sustainability strategies. This study finds a suitable adaptation option where food sustainability shortage over time is minimized and estimates adaptation costs to be less for different time segments from 2015 to 2065. This study’s results suggest that up to 15% adaptation actions should be suitable for Malaysia in terms of the current national agenda in addressing the food security issues. Thus, according to the study’s results and findings, the optimum level of adaptation depends on continuing change in temperature, emissions, economic growth, population growth, and changes in other related climatic variables for each time segment. The study suggests that a different level of adaptation over time would be effective in terms of a decrease in the negative impacts of climate change. This study showed an increasing trend in the cost of adaptation over the 50 years from 2015 to 2065. The growing economic activities that cause climate change and damage reduction options would cause the optimum level of adaptation to increase over time. This study focused on reactive adaptation actions and studied the benefits and costs of adaptation. In the case of the food sector, reactive adaptation is particularly important as opposed to proactive responses, especially in developing countries where this sector is a substantial source of national income, and it is to be effective within a very short gestation period. Furthermore, the study’s results established that, for the food sector, the cost of adaptation is very small as a percentage of GDP. Based on the findings of the study, it may be suggested that the optimum adaptation policy should be implemented by Malaysian policymakers. However, farmers in Malaysia in practice pay little attention to planning for potential climate change impacts at both the individual and community levels. Generally, farmers cope with weather patterns on a short-term basis and can sometimes adjust to potential risks and weather variability through best management practices, but climate change may pose new, unpredictable risks for the future of Malaysia similar to the rest of the world. This proposition is valid because this study found that impacts of climate

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change are projected to increase over time, which ultimately will reduce outputs of all economic sectors. Hence, it is the government’s responsibility to formulate optimum adaptation policies so that the benefits of adaptation are enjoyed collectively. However, in Malaysia at present, no separate, specific policy exists for every economic sector that would address the impacts of global warming and climate change on individual sectors and their productivity. Unfortunately, in Malaysia, there exists a serious lack of information in this regard. Hence, it is apparent that for Malaysia the main obstacles are a lack of knowledge of climate change impacts, limited shortage of conservation facilities, and political will, for example. Moreover, Malaysia confronts a distinct and important challenge – the continued uncertainty about how much climate change it will face. In addition, the extent to which adaptation will reduce vulnerability in the Malaysian context is also uncertain. Thus, despite the uncertainties, rigorous effort is needed to facilitate decision-making based on climate projections. Subsequently, for a range of climate change scenarios, a range of adaptation options and costs is estimated. Taking into account these facts, this study has proposed initiatives to maintain food security and sustainability over time. However, this study has found a different optimum level of adaptation with different climate conditions over different time segments. This research study suggests that policymakers should implement this policy with the necessary funding to improve awareness and change attitudes among Malaysians toward adopting new policies. The issues highlighted in this study are not new in some developed countries, but they are quite new for developing and advanced developing countries. Thus, some critical issues need to be considered in developing countries as there may be advantages and disadvantages in solving the new research problems raised in this study. Though there are some complications in estimating the economic impacts of climate change for an optimum adaptation policy due to allocations of resources for the appropriate option, the study has the following strengths: (a) The impacts and costs of climate change measures cannot be optimally determined on a global basis because impacts can vary from region to region, among countries, or even within the same country. Therefore, it is necessary to assess the feasibility of adaptation plans so that appropriate adaptation actions can be taken for a specific country, as has been done in the case of Malaysia. (b) The impacts of climate change can affect different sectors of an economy differently. Agriculture is one of the most vulnerable sectors because it directly depends on weather conditions. It is also the most important sector because it is directly related to food security and economic development, which prompted this study. (c) Appropriate adaptations can greatly reduce the magnitude of the impacts of climate change. Existing knowledge regarding adaptive capacities and adaptation options is not sufficient in Malaysia. Therefore, there exists a lack of reliability of future projections of adaptation options and policies and their associated costs in monetary terms, as highlighted in this research. This study represents a way forward toward find a suitable adaptation option to justify applicable policy recommendations. The issues addressed in this study may

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serve as an appropriate guideline for macroeconomic decision-making with precise knowledge of the overall impacts of long-term adaptive measures. Thus, the suggested guidelines would contribute further to the current state of knowledge in setting up a long-term national adaptation plan.

6.5  Contribution This study has revealed the macroeconomic effects of adaptation policies in the Malaysian economy, particularly addressing food security and sustainability issues over the short and long run. Specifically, this study enhances current knowledge for setting up a long-term national climate change adaptation policy framework for Malaysia in response to Malaysian National Policy on Climate Change (2009). The study will contribute to fill a research gap in determining the distribution of impacts on the costs and benefits of adaptation for the food sector to achieve an expected level of food security and sustainability. The study proposed guidelines for policymakers with respect to macroeconomic decision-making with precise knowledge of the overall impacts of adaptation measures in agriculture. Although the ultimate target groups are principally Malaysian policymakers, a wide range of farming organizations and stakeholders may benefit from the scientific findings of the research presented herein. The ultimate contribution of this study was to reveal the macroeconomic effects of climate change adaptation policies on the Malaysian economy. Specifically, the study enhances current knowledge for (a) setting up a long-term national climate change adaptation policy framework for Malaysia in response to the Malaysian National Policy on Climate Change, (b) filling a research gap by outlining the distribution of impacts of the costs of adaptation for the sustainability of the food sector, and (c) creating guidelines for policymakers in the macroeconomic area with precise knowledge of the overall impacts of those adaptive measures that support sustainable future strategies. Although the ultimate target group is Malaysian policymakers, a wide range of people and organizations may benefit from the general nature of the scientific findings of this study. In essence, it is evident that the benefits of adaptation are higher than the costs of adaptation for all time segments. Furthermore, the benefits of adaptation should increase at a higher rate than the rate of increase of costs over time, which confirms that the adaptation policy would be effective for Malaysia.

6.6  Suggestions for Future Research Climate change is one of the most challenging issues facing Malaysia in the coming decades. Therefore, it will require additional interventions to address the new conditions, stresses, and natural hazards that will result from climate change. Although

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farming communities have their own means of dealing with extreme climatic events based on endogenous experience, their knowledge will not be that effective in dealing with the expected impacts of climate change, which, it is assumed, will change drastically in the future. Thus, it is crucial to make explicit plans for adjusting to these impacts. However, adaptation planning also requires an assessment of current and future impacts and vulnerability to climate change. But the lack of reliable data sources creates some uncertainty with respect to this assessment, which does not reflect real scenarios of climate change in a country or region. The processes between baseline scenario studies and identifying feasible adaptation measures, on the other hand, are composite since these approaches are not often supported by an effective planning process.

6.7  Limitations A longer time frame, differences in social discount factors, imperfect competition, numeraire price, and short-run to long-run time preferences can suffer from recall bias and deliberate misreporting. Even though heightened caution is exercised during modeling, the results might have underreported or overreported regarding particular actions. This misreporting could influence the findings. Although many variables were analyzed to meet the objectives of the study, the exclusion of other variables might limit the study’s findings and some of the usual criticisms may arise in the analyses. Future qualitative studies would also be useful in developing a better understanding of the issues explored here.

Appendix

Climatic Equations Gross damage is defined as:

GDt =∝i ∆Tt 2

(1)

The climate impact function is defined as:

Tt =∝ j Tt −1 + ∝ k EM t

(2)



Growth impact function is defined as:

EM t = Ω.Yt ( 1 − µt − ALt

)

(3)

The adaptation cost is defined as:



ACt = γ 1 . ALγt 2 Qxt



GDt = ω. M t Qxt

(4a) (4b)



The gross damage and residual damage are defined as:



GDt = α1 ∆Tt + α 2 ∆Ttα 3 Qxt

(5)

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4

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Appendix

GDt RDt ( GDt ,ALt ,ABt ) ACt ( ALt ,ABt ) = + Qxt Qxt Qxt

(6)

 tandard Model Equations That All Are Considered Over S Time (t) The import price is defined as: PM c = . (1 + tmc ) .EXR. pwmc  import price   tariff   exchange rate   import price  = . .  ( DCU )  adjustmeent  ( LCU per FCU ) ( foreign currency ) 

c ∈ CM (7)

The export price is defined as: PEc = . (1 − tec ) .EXR. pwec export price   tariff   exchange rate   export price  .  DCU  = .  +  ment  ( LCU per FCU )  ( foreign currency )  ( )  adjustm 

c ∈ CE (8)

The absorption price is defined as:



PQc .QQc =  PDc .QDc + ( PM c )c∈CM  .((1 + tqc )  domesticc sales price   import price  c ∈ CE +  .  salestax  times times [absorption ] =     adjustment   domestic sales quantity   import quantity  

(9)

The domestic output value is defined as: QX c = PDc .QDc + ( PEc .QEc ) producer prices    domestic sales price   export price  +   = times times times       domestic output quuantity   domestic sales quantity  export quantity 

c ∈C

(10)

Appendix

145

The activity price is defined as: Aa = ∑PX c .θ ac c∈C



activity   producer prices   prices  =  times yieelds     

α∈A

(11)

The value-added price is defined as: PVAa = PAa − ∑PQc .icaca c∈C

 intermdediate input cost  α∈A value − added   =  per unit of agregate  − [ input cost per activity unit ]   price    intermediate input    (12)

The consumer price index is defined as: CPI = ∑PQc .cwtsc c∈C



 consumer   prices times   price index  =  weig ght    

α∈A

(13)

The producer price index for non-traded market output is defined as: PPI = ∑PDSc .dwtsc c∈C



 producer price index   prices times  for non − traded outputts  =  weight     

α∈A

(14)

The factor income is defined as: YFf = shryhf



∑WF .WFDIST

α ∈A

f

fa

.QFfa

h ∈ H, f ∈ F  household factor   income share to  = . [ factor income ]    income    household h 

(15)

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Appendix

The household income is defined as: YH h = ∑YFhf + trh, gov + EXR.trh, gov f ∈F



 transfer from government  h ∈ H (16)  household income   factor    and rest of world  from factorr f  =  incomes  .          The household consumption demand is defined as:

β ch . (1 − mpsh ) . (1 − tyh ) .YH h

QH ch =

PQc

 household demand for   household income, = f    commodiity c    composite price 



(17)

c ∈C

The investment demand is defined as: QINVc = qinv c .IADJ fixed investment   based year investment    demand for  =  times      commodity c   adjustment factor 



c ∈C (18)

The government revenue is defined as: YG =

∑ TINS .YI + ∑tf .YF + ∑tva .PVA .QVA + ∑ta .PA .QA + ∑ tm . pwm .QM .EXR + ∑ te . pwe .QE .EXR + ∑tq .PQ .QQ + ∑YIF + trnsfr .EXR i

i

i∈INSDNG a

a

a

a∈ A

f

a

c

c

c

a

a

a∈ A c

c

c∈CM

c

c∈C

f

f ∈F

c

c

c

c∈CE

gov f

gov row

f ∈F

direct taxes  direct taxes  government       revenu  =  from  +  from  u e    institutions   factors       value   activity   import   export  + added  +  + + tax   tariffs   taxes    tax   sales   factor   transfer from  + + +  RoW  tax   income   



(19)

Appendix

147

The government expenditure is defined as: EG = ∑ trh, gov + h∈H

∑

PQc .qgc

i∈INSDNG

(20)

government   houusehold   government   spending  =  transfers  + consumption       



The factor market is defined as:

∑QF

= QFS f

fa

a∈ A

demand for   supply   factor f  = factor f     



f ∈F

(21)

The composite commodity market is defined as: QQc = ∑QINTca + ∑QH c h + qgc . + QINVc a∈ A

h∈H

mposite demand;   com  sum of intermediate,  composite      supply  =  household, government,      and investment demand 



c ∈C (22)



The current-account balance is defined as:

∑pwm .QE + ∑tr c

c∈C

i ,row

c

+ FSAV =

f ∈F

∑ pwm .QM c

c

c∈CM

 transfer from   export    foreign   import   revenue  +  RoW to households  +  saving  = spending          and government 



(23)

The savings-investment balance is defined as:

∑mps . (1 − ty ) + YH + (YG − EG ) + EXR.FSAV = ∑PQ .QINV i

h∈H

h

h

c

c

+ WALRAS

c C

 household  government   foreign   fixed   WALRAS dummy   savings  +  savings  + savings  =  investment  +   variable           (24)

148

Appendix

The price normalization is defined as:

∑PQ .cwts c

c

= cpi

c∈C



 price times   weighs  = [CPI ]  

(25)

List of Parameters

Sets t time periods ada activities aqc commodities atc imported commodities cpi non-imported commodities cwtsc exported commodities icaa non-exported commodities mpsh factors pwec households pwmc institutions (households, government, and rest of the world) qgc government commodity demand qinvc base-year investment demand shryhf share of the income from factor f in household h tec export tax rate tmc import tariff rate tqc sales tax rate trii transfer from institution i’ to institution i tyh rate of household income tax αfa value-added share for factor f in activity a βch share of commodity c in the consumption of household h δqc share parameter for composite supply (Armington) function δtc share parameter for output transformation (CET) function αac yield of commodity c per unit of activity a exponent (-1< pcq < ∞) for composite supply (Armington) function pcq pct exponent (-1< pct < ∞) for output transformation (CET) function q σc elasticity of substitution for composite supply (Armington) function σtc elasticity of substitution for output transformation (CET) function © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4

149

List of Variables

EG EXR FSAV IADJ PAa PDc PEc PMc PQc PVAc PXc QAa QDc QEc QFfa QFSf QHch QINTc QINVc QMc QQc QXc WALRAS WFf WFDISTfa YFhf YG YHh

government expenditure foreign exchange rate (domestic currency per unit of foreign currency) foreign savings investment adjustment factor activity price domestic price of domestic output export price (domestic currency) import price (domestic currency) composite commodity price value-added price producer price activity level quantity of domestic output sold domestically quantity of exports quantity demanded of factor f by activity a supply of factor f quantity of consumption of commodity c by household h quantity of intermediate use of commodity c by activity a quantity of investment demand quantity of imports quantity of goods supplied to domestic market (composite supply) quantity of domestic output dummy variable (zero at equilibrium) average wage (rental rate) of factor f wage distortion factor for factor f in activity a transfer of income to household h from factor f government revenue household income

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 F. Ahmed et al., Climate Change and Adaptation for Food Sustainability, https://doi.org/10.1007/978-3-030-85375-4

151

List of Variables

152 Table 5-1  Residual damage without adaptation action Year Residual damage

2015 1746.859

2025 1798.245

2035 1851.029

2045 1905.179

2055 1960.838

2065 2017.944

Table 5-2  Residual damage with adaptation action in different scenarios Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 1659.779 1572.646 1485.398 1397.954

2025 1708.605 1618.909 1529.095 1439.078

2035 1758.735 1666.442 1574.002 1481.308

2045 1810.21 1715.181 1620.027 1524.657

2055 1863.07 1766.119 1667.707 1569.178

2065 1917.355 1816.703 1715.918 1614.901

2055 1863.07 1766.119 1667.707 1569.178

2065 1917.355 1816.703 1715.918 1614.901

Table 5-3  Net residual damage in different scenarios with baseline Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 1659.779 1572.646 1485.398 1397.954

2025 1708.605 1618.909 1529.095 1439.078

2035 1758.735 1666.442 1574.002 1481.308

2045 1810.21 1715.181 1620.027 1524.657

Table 5-4  Compare adaptation cost in different level with baseline in different scenarios (million RM) Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 0.676376 10.63761 53.31414 167.2833

2025 0.696273 10.95054 54.88251 172.2044

2035 0.716702 11.27206 56.49434 177.2578

2045 0.737678 11.60174 58.14627 182.445

2055 0.759219 11.94629 59.85758 187.7726

2065 0.781341 12.28845 61.58798 193.244

Table 5-5  Government expenditure without adaptation action (million RM) 2015 89681.14

2025 91457.23

2035 93290.3

2045 95192.79

2055 97150.41

2065 99180.32

Table 5-6  Government expenditure with different adaptation action (million RM) Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 89689.3 89705.96 89752.96 89864.17

2025 91465.47 91482.4 91530.3 91645.3

2035 93302.42 93314.1 93361.25 93485.97

2045 95201.21 95218.93 95269.44 95391.38

2055 97162.98 97038.17 97166.9 97358.59

2065 99188.94 99207.44 99260.79 99390.04

Table 5-7  Food sustainability over time without adaptation action (million RM) Year Food sustainability over time

2015 2025 2035 2045 2055 2065 3566.247 3666.68 3769.949 3876.088 3985.24 4097.422

List of Variables

153

Table 5-8  Food sustainability over time with different adaptation action (million RM) Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 3566.890929 3576.82308 3619.482815 3733.462014

2025 3667.342 3677.567 3721.481 3838.813

2035 3770.615 3781.163 3826.375 3947.124

2045 3876.789 3887.621 3934.147 4058.456

2055 3985.944 3997.727 4045.28 4172.917

2065 4098.164919 4109.637356 4158.916865 4290.584787

Table 5-9  RGDP without adaptation policy (million RM) Year RGDP

2015 464793.134

2025 478465.673

2035 492510.26

2045 506918.03

2055 521727.363

2065 536921.765

Table 5-10  RGDP benefit from adaptation in different scenarios (million RM) Year With 5% adaptation With 10% adaptation With 15% adaptation With 20% adaptation

2015 73.846 139.798 177.99 155.22

2025 76.249 144.347 183.675 160.271

2035 73.139 159.455 196.405 161.232

2045 81.235 153.787 195.688 170.752

2055 76.673 669.026 311.317 169.043

2065 86.476 163.711 208.315 181.77

Table 5-11  Compare adaptation benefit and cost in % of GDP Year % in GDP for adaptation benefit % in GDP for adaptation cost

2015 0.03 0.0022

2025 0.0301 0.0022

2035 0.0323 0.0022

2045 0.0303 0.0022

2055 0.128 0.0022

2065 0.0304 0.0023