Indian Agriculture Under the Shadows of WTO and FTAs: Issues and Concerns 9789813368538, 9789813368545

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India Studies in Business and Economics

Rajan Sudesh Ratna Sachin Kumar Sharma Radika Kumar Adeet Dobhal   Editors

Indian Agriculture Under the Shadows of WTO and FTAs Issues and Concerns

India Studies in Business and Economics

The Indian economy is considered to be one of the fastest growing economies of the world with India amongst the most important G-20 economies. Ever since the Indian economy made its presence felt on the global platform, the research community is now even more interested in studying and analyzing what India has to offer. This series aims to bring forth the latest studies and research about India from the areas of economics, business, and management science. The titles featured in this series will present rigorous empirical research, often accompanied by policy recommendations, evoke and evaluate various aspects of the economy and the business and management landscape in India, with a special focus on India’s relationship with the world in terms of business and trade.

More information about this series at http://www.springer.com/series/11234

Rajan Sudesh Ratna · Sachin Kumar Sharma · Radika Kumar · Adeet Dobhal Editors

Indian Agriculture Under the Shadows of WTO and FTAs Issues and Concerns

Editors Rajan Sudesh Ratna South and South-West Asia Office UNESCAP United Nations Economic and Social Council New Delhi, India Radika Kumar Commonwealth Secretariat Trade Oceans and Natural Resources Directorate London, UK

Sachin Kumar Sharma Centre for WTO Studies Indian Institute of Foreign Trade New Delhi, India Adeet Dobhal Centre for WTO Studies Indian Institute of Foreign Trade New Delhi, India

ISSN 2198-0012 ISSN 2198-0020 (electronic) India Studies in Business and Economics ISBN 978-981-33-6853-8 ISBN 978-981-33-6854-5 (eBook) https://doi.org/10.1007/978-981-33-6854-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 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 Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

This book is dedicated to the millions of Indian farmers

Preface

Agriculture, for India, like many other developing countries in the world, is a vital sector given the pertinent role it plays in economic growth, food security, livelihood, rural development, employment and poverty alleviation. Despite the declining share of agriculture in India’s GDP, its share in total employment is more than 45 percent. Given its role in livelihood and food security, it is unsurprising that agriculture has always remained a sensitive sector for India at multilateral and regional trade deals. However, even today, the sector faces several challenges on both domestic and external fronts. Domestically, farming in India is characterised by small and fragmented landholdings, infrastructural inefficiencies, absence of marketing channels and farm distress. In addition, the Indian farmers face challenges due to the lack of adequate income safety nets, access to finance and technology, erratic rainfall, low productivity and other factors such as climate change and natural disasters. On the international front, the agriculture sector in India continues to face a multitude of challenges such as price volatility, increased use of non-tariff barriers on its exports, continued domestic support by developed countries and export subsidies leading to import surges, among others. Various distortions and market access barriers, including high non-tariff barriers (NTBs) imposed by its trading partners, have severely affected India’s agricultural competitiveness and export prospects. Since the 1990s, India saw a pan-sector liberalisation of its economy, including agriculture. These reforms were further advanced when India ratified the establishment of WTO and its agreements in 1995. Besides commitments in WTO, India also took an autonomous route of trade liberalisation, including in agriculture. Post 2003, India became an active participant in regional and free trade agreements, though the liberalisation of the agricultural sector under these agreements was limited. The opening of the agriculture sector was never without issues and, to date, remains contentious between all the stakeholders involved. While many favoured liberalisation of the sector, in view of the many opportunities that would open for the domestic players in the foreign markets, others remained sceptical of the unfair competition due to the import of subsidised products as well as NTBs on Indian export. Today, after almost 30 years since India first initiated the liberalisation process and 25 years of the establishment of WTO, this book comes as a timely endeavour to examine and evaluate issues pertaining to the Indian agricultural trade in the context vii

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of WTO and FTAs. There is no dearth of literature focusing on Indian agriculture, but there are a few that explicitly focus on the relationship between international trade under WTO and FTAs and Indian agriculture. This book, with a view to filling this gap in the literature, strives to provide a detailed and comprehensive analysis of the issues concerning India’s agricultural trade. With contributions from eminent trade experts from India and abroad, the book serves as a robust resource for researchers, policymakers, government officials, students and the private sector to acquaint themselves with trade and agriculture issues. The published resources in the book will act as a complementary aid for making evidence-based policies and better assist in future trade negotiations to achieve the developmental goals of the nation.1 The book is divided into three parts. Parts I and II comprise chapters that deal with Indian agriculture under WTO and RTAs, respectively. These chapters also provide valuable insights that may be applicable in other areas of current negotiations, in particular, the fisheries subsidies negotiations, by drawing from the Indian experience in agriculture subsidies negotiations. Part III deals with chapters on crosscutting issues pertaining to agriculture. Understanding domestic issues in agriculture will enable readers to understand how domestic issues influence India’s negotiating position in WTO and RTA negotiations. Furthermore, as the world grapples with the economic implications of the COVID-19 pandemic and charts plans for future recovery, understanding the issues in agriculture would enable policymakers in India as well as other like countries to develop policies targeting critical issues that ail this vital sector. Chapter 1 assesses the trade patterns of India’s total agriculture items under WTO and with the FTA partners. The chapter analyses the pertinent issues and challenges faced by India under the Agreement on Agriculture (AoA) and provides critical insights into current agricultural negotiations at WTO. It discusses the current impasse in WTO negotiations and the sensitivities of India on issues like domestic support, import surges, export subsidy and food security, among others. Further, it highlights the agriculture-related issues under various FTAs of India. Another important issue of concern for developing and island countries relates to negotiations on fisheries subsidies. This is discussed in Chap. 2, which examines the current proposals and discussions in WTO. Although fisheries is formally not covered by the AoA, the chapter finds a place in this book due to its importance for developing countries, including India, and the implications of the proposed disciplines on fisheries which mirror those in the AoA. The chapter provides a detailed analysis of the contentious issues and elements in the fisheries negotiations regarding which members of WTO, in particular, the developing and least developed countries, must be vigilant in order to avoid the asymmetries of the AoA from being replicated in the impending agreement. With the fisheries agreement due to be finalised in due course, the chapter will serve as an invaluable resource for both policymakers and

1 Disclaimer: The editors wish to state that the views and opinions expressed in the book are those of

the authors and do not reflect the official policy or position of any organisations or people affiliated to them.

Preface

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negotiators towards ensuring balanced outcomes in the fisheries subsidies agreement by MC12 in 2021. Chapter 3 undertakes the examination of income support and price support mechanisms, another important issue, both at WTO and for India. Under WTO, price support to agriculture, unlike income support, is considered to be trade-distorting and hence is subject to stringent disciplines. India’s minimum support price is classified as price support and hence is subject to the strict limits under the ‘Amber Box’ as prescribed under WTO rules. On the other hand, income support which is mainly provided by the developed members, is considered non- or minimal trade-distorting support under the exempt ‘Green Box’. This chapter theoretically demonstrates that income support measures, like price support measures, are also trade-distorting. Chapter 4 touches upon another area that is important for developing countries. It deals with the transparency aspects of the Sanitary and Phytosanitary (SPS) measures on agricultural products notified by India. This paper evaluates India’s SPS notifications to WTO over a period and tests them through the agreed guidelines of WTO. The chapter highlights that the quality of India’s SPS notification has improved significantly over the years. Further, the study indicates some of the areas where improvement is needed for transparency purposes. Although the study concerns India, its findings are also applicable for other like members in order to improve the quality of SPS notifications. Part II deals with some case studies of India’s FTAs and examines the impact on Indian agriculture. Chapter 5 examines the impact of the proposed India–UK FTA on the agriculture sector. With Brexit now in place, this chapter analyses the possible effects of tariff liberalisation on India’s exports of select agricultural products under the India–UK FTA. Using the partial equilibrium model for eliminating the tariffs, the chapter finds that India will see only a modest export growth post FTA which is due to the fact that India’s agricultural tariffs are higher compared to those of the UK and the EU. Chapter 6, by taking the case of the India–ASEAN FTA estimates India’s comparative advantage in the agriculture sector and the non-tariff measures (NTMs) faced by Indian agriculture exporter in ASEAN regions. This chapter explained the reasons behind the low export growth to ASEAN countries after the signing of the FTA in 2010. The findings indicate that among non-tariff measures (NTMs), Sanitary and Phytosanitary (SPS) measures hinder India’s agricultural exports the most, even on those items on which India has revealed comparative advantage. The study suggests that a dialogue on the standardisation of NTMs needs to be initiated between India and ASEAN for effective market access. Chapter 7 evaluates the economic impact of a potential India–European Union FTA on India’s marine sector. The study notes that the EU is the largest marine product importer in the world, and India has huge potential to increase marine output and thus likely India–EU FTA may enhance India’s marine products export to the EU. Given that the EU is a market for high-valued fishery products and India is a market for low-valued fishery products, possible India–EU FTA may not affect the domestic marine market. It also suggests that for sustained and long-term market

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access, the parties must negotiate mutual recognition agreements, etc., to address SPS- and TBT-related concerns in the fisheries sector. Part III deals with a cluster of chapters that focus on relevant cross-cutting issues for Indian agriculture. Recognising that agriculture is the key source of livelihood for rural India, sustainable production remains a significant concern, especially due to the overuse of subsidised inputs such as industrial agro-chemicals (fertilisers), diesel, etc. Chapter 8 examines the impact of these subsidised inputs on the environment. It finds that the gains in net returns from the use of subsidised inputs are more than offset by the adverse effects of emissions. Putting forth pertinent policy suggestions for sustainable agriculture, the chapter calls for the linking cash transfers to the use of organic fertilisers, among others, as an effective means of incentivising the farmers to switch to organic fertilisers. Chapter 9 empirically examines the role of sustainability and policy measures in influencing the export performance by using the ten leading exporters from the AsiaPacific Economic Cooperation (APEC) region and India for the analysis. The study points out that the export performance in the APEC has low mean efficiency scores and trade integration, though regional integration is an important characteristic in affecting the export performance. The study notes that the reduction in the absolute difference of real exchange rate and worldwide weighted applied tariff brings tradeenhancing effects and contributes to economic development by improving export performance. Next, Chap. 10 examines the dairy industry in India under the trade reforms. It underscores that small-scale farmers dominate the dairy sector in India; hence, government interventions are necessary to support the sector for ensuring food and livelihood security. The chapter also highlights the need to adopt measures to increase the productivity of the bovine stock by addressing both intrinsic and extrinsic variables to make the sector globally competitive. Finally, Chap. 11 investigates the issues related to the commercialisation of GM crops and examines the regulatory framework for GM crop development and commercialisation in India. It is to be noted that the issue of GM crops is highly sensitive in India due to the divergent views and positions of various stakeholders. This chapter tries to explain the reasons for the current deadlock between the regulators and the developers of GM technology. It also assesses the existing review system on this technology. Further, it explores a plausible way to utilise the best parts of GM technology still while keeping in sight the associated risks being pointed out continuously. New Delhi, India New Delhi, India London, UK New Delhi, India

Rajan Sudesh Ratna Sachin Kumar Sharma Radika Kumar Adeet Dobhal

Acknowledgements

This book finds its origins in a series of thought-provoking research papers presented in the Sixth International Conference on ‘WTO, Trade and Agriculture: Issues and Challenges for Developing and Least Developed Countries’ organised by the Centre for WTO Studies, New Delhi, during 11–12 October 2018. We, the Editors, take this as an opportunity to extend our sincere thanks and gratitude to the contributors, keynote speakers and other participants who have encouraged us to bring out the conference papers in an edited volume. Our sincere thanks to the Centre for WTO Studies, Indian Institute of Foreign Trade (IIFT) and Ministry of Commerce and Industry for providing financial support in organising this important conference. We would like to express our wholehearted gratitude to Mr. Anup Wadhawan (Commerce Secretary), Mr. Sudhanshu Pandey (Food Secretary), Mr. J. S. Deepak (Former Ambassador of India to WTO), Mr. Brajendra Navnit (Ambassador of India to the WTO), Mr. Amit Singla (Former Counsellor, Permanent Mission of India to WTO) and Mr. Anwar H. Shaik (Counsellor, Permanent Mission of India to WTO) for their support and encouragement. We are ever grateful to Mr. Rajeev Kher (Former Commerce Secretary) and Mr. Jayant Dasgupta (Former Ambassador of India to WTO) for all their support and encouragement. We will be failing in our duty if we do not acknowledge the help and assistance received from the Trade Policy Division, Ministry of Commerce, Government of India. We would like to express our gratitude to Mr. Praveen Mahto (Economic Advisor), Ms. Neetika Bansal (Director), Mr. Narayan Prasad (Former Under Secretary) and Ms. Prachi Singhal (Deputy Director) for their support. We place on record our thanks to Ms. Noncedo Vutula (Former Chair, SPS Committee and South African Permanent Mission to WTO) and Dr. Anne Marie Thow, (Senior Lecturer in Health Policy and Director of Academic Titles, School of Public Health, University of Sydney). We extend our heartiest thanks as well to Mr. Manoj Pant (Director, IIFT) and Prof. Abhijit Das (Head, CWS) for their continued support. Rajan Sudesh Ratna is grateful to Ms. Armida Salsiah Alisjahbana (UnderSecretary-General of the United Nations and the Executive Secretary of UN ESCAP) and Dr. Nagesh Kumar (Head, South and South-West Asia office of UN ESCAP) for their constant guidance and encouragement. xi

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Acknowledgements

Rajan is also grateful to his parents, wife Sonali, sister Rajshree, son Harshit, daughter Urvashi and other family members who not only stood by him during difficult times but also constantly supported him in this endeavour. Rajan is thankful to Geetu Joshi and Santha Thampi for their help and support. Reviewing the chapters and doing editorial changes would not have been possible if Sonali, Harshit and Urvashi would not have continued with the sustained and uninterrupted supply of coffee during the late hours of the night. We express our gratitude to Dr. James J. Nedumpara, Prof. Abhijit Das, Dr. Mohana Kumar, Prof. R. K. Sharma, Prof. Amresh Dubey, Prof. Vijaya Katti, Prof. Seema Bathla, Prof. Parmod Kumar, Dr. Elumalai Kannan and Dr. Rohit Mehtani for accepting our invitation for chairing or moderating different sessions. Professor Abhijit Das deserves a special mention for his guidance, encouragement and unflinching support to the conference and throughout the editing process. We are also grateful to our colleagues at the Centre, Prof. Mukesh Bhatnagar, Prof. Chandani, Prof. Murali Kallummal, Ms. Shailija Singh and Dr. Parlok Gupta, for their support and encouragement. We remain grateful to Mr. A. K. Lahiri, Mr. Sahil Sharma, Ms. Parkhi Vats, Mr. Mukesh Singh and others at the Centre and IIFT for their assistance in organising this conference. We are also grateful to our Research Fellows at the Centre, Mr. Suvayan Neogi, Mr. Raihan Akhter, Ms. Teesta Lahiri and Ms. Paavni Mathur for their support. We place on record our appreciation of the efforts and cooperation provided to us by the authors in revising and updating their respective papers, especially during this pandemic. Our profound thanks to Ms. Nupoor Singh, Ms. Sharmila Mary Panner Selvam and others at Springer for providing us with this opportunity. From expediting the proposal to their assistance throughout the publication process, their support has helped us finish the volume in a timely manner. Our sincere thanks to the anonymous reviewers as well for their comments and suggestions. We hope that this volume will benefit policymakers, civil society groups, farmers’ organisations, researchers and academicians interested in reading about agriculture trade under the multilateral and regional trade agreements.

Contents

Part I

WTO and Indian Agriculture

1

Indian Agriculture under WTO and FTAs: An Assessment . . . . . . . . Rajan Sudesh Ratna, Sachin Kumar Sharma, and Adeet Dobhal

3

2

Fisheries Negotiations at the WTO: Small Bait for Large Catch . . . . Radika D. Kumar

27

3

Revisiting the Question of Price and Income Support to Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Saratchand and Simin Akhter

55

Transparency and WTO SPS Notifications: A Case Study of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marcelo Alonso Valverde Arevalo and Walter Fernando Ibarra Davila

69

4

Part II

FTAs and Indian Agriculture

5

India–UK FTA: Export Prospects for Indian Agriculture . . . . . . . . . Bibek Ray Chaudhuri and Debashis Chakraborty

91

6

Non-tariff Measures and India’s Agricultural Exports: The Case of India-ASEAN Trade Agreement . . . . . . . . . . . . . . . . . . . . . . . . . 117 Abhishek Jha and Seema Bathla

7

India–EU FTA: Implications for India’s Marine Products . . . . . . . . . 139 B. H. Nagoor and Shankar Eiti

Part III Indian Agriculture: Cross-Cutting Issues 8

Evaluating the Role of Subsidies in Sustainable Agriculture: A Case Study of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Anjali Tandon and Roopali Aggarwal

xiii

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9

Contents

The Role of Sustainability and Policy Measures in Export Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Shubham Kumar and Tapas Kumar Giri

10 Dairy Industry in India Under Trade Liberalisation . . . . . . . . . . . . . . 193 S. Mohanakumar 11 Genetically Modified Crops and Indian Agriculture: Issues Relating to Governance and Regulation . . . . . . . . . . . . . . . . . . . . . . . . . 215 Anurag Kanaujia and Sujit Bhattacharya

Editors and Contributors

About the Editors Rajan Sudesh Ratna has been working in the United Nations Economic and Social Commission of Asia and the Pacific since July 2012 and is currently posted in South and Southeast Asia office in New Delhi. Dr. Ratna has previously worked in the Government of India for 25 years (as a civil servant from Indian Trade Service), initially in the Directorate General of Foreign Trade (DGFT) and later in the Ministry of Commerce handling the regional and multilateral trade policy issues. While working there, he formulated India’s Foreign Trade Policy, Duty Free Quota Free Scheme for LDCs and participated in several negotiations relating to WTO and Free Trade Agreements, including rules of origin. From June 2008 to December 2010, he worked as Professor, Centre for WTO Studies, Indian Institute of Foreign Trade, New Delhi, where he carried out research on issues relating to WTO (Agriculture, Environmental Goods and Services, TBT and NAMA) and India’s FTA/PTA negotiations. He has published several books and articles. Sachin Kumar Sharma is currently working at the Centre for WTO Studies as Associate Professor. He completed his Ph.D. in Economics from Jawaharlal Nehru University, New Delhi. He has undertaken research on various issues related to WTO, International trade and agriculture negotiations. He actively participated in various outreach activities conducted by CWS. He has authored many reports for the Ministry of Commerce on various issues related to Green box, India’s domestic support notifications, food security, Agreement on Agriculture, G-33 proposal on food security, etc. His research interests include WTO, subsidies, food security, free trade agreement, CGE modelling, agriculture negotiations and human development. Radika Kumar is currently working as Adviser, Infrastructure Policy, Trade Oceans and Natural Resources Directorate, Commonwealth Secretariat. Dr. Kumar holds a master’s degree in economics from the University of the South Pacific and Ph.D. in Economics from The University of the South Pacific. Her research areas include international trade and economics; WTO multilateral rules and SIDS; 4th xv

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Editors and Contributors

industrial revolution; agriculture and fisheries subsidies; trade negotiations (regional & multilateral); trade in services; trade policies. Adeet Dobhal is a Senior Research Fellow at the Centre for WTO Studies, Indian Institute of Foreign Trade, New Delhi. A law graduate from Amity Law School, Noida, India, he has been actively involved in providing strategic legal advice and inputs on international trade issues, WTO negotiations and disputes. At the Centre, Adeet has worked on several areas of critical importance for the Government of India including agricultural trade, food security and e-commerce, among others. His research interests include trade law, investment law and dispute resolution.

Contributors Roopali Aggarwal Jawaharlal Nehru University, New Delhi, India Simin Akhter Zakir Husain Delhi College, New Delhi, India Seema Bathla Centre for the Study of Regional Development (CSRD), School of Social Science (SS- III), Jawaharlal Nehru University, New Delhi, India Sujit Bhattacharya Academy of Scientific and Innovative Research (AcSIR), CSIR-National Institute of Science Technology and Development Studies (NISTADS), New Delhi, India Debashis Chakraborty Indian Institute of Foreign Trade, Kolkata Campus, West Bengal, India Bibek Ray Chaudhuri Indian Institute of Foreign Trade, Kolkata Campus, West Bengal, India Adeet Dobhal Centre for WTO Studies, Indian Institute of Foreign Trade, (IIFT), New Delhi, India Shankar Eiti Department Karnataka, India

of

Economics,

Karnatak

University,

Dharwad,

Tapas Kumar Giri Indian Institute of Management, Shillong, Meghalaya, India Walter Fernando Ibarra Davila Ministry of Foreign Trade and Tourism, Lima, Peru Abhishek Jha Centre for the Study of Regional Development (CSRD), School of Social Science (SS- III), Jawaharlal Nehru University, New Delhi, India Anurag Kanaujia Academy of Scientific and Innovative Research (AcSIR), CSIRNational Institute of Science Technology and Development Studies (NISTADS), New Delhi, India

Editors and Contributors

xvii

Radika D. Kumar Former Lecturer Economics, University of the South Pacific, Suva, Fiji Shubham Kumar Indian Institute of Management, Shillong, Meghalaya, India S. Mohanakumar Institute of Development Studies, Jaipur, Rajasthan, India B. H. Nagoor Department of Economics, Karnatak University, Dharwad, Karnataka, India Rajan Sudesh Ratna United Nations ESCAP, South and South-West Asia Office, New Delhi, India C. Saratchand Satyawati College, University of Delhi, New Delhi, India Sachin Kumar Sharma Centre for WTO Studies, Indian Institute of Foreign Trade, (IIFT), New Delhi, India Anjali Tandon Institute for Studies in Industrial Development (ISID), New Delhi, India Marcelo Alonso Valverde Arevalo Ministry of Foreign Trade and Tourism, Lima, Peru

Abbreviations

AAP ABAC ACTA AFTA AIFTA AMS AoA APEC APEDA APTA ARP ASCM ASEAN ATIGA ATMA BIMSTEC Bt CAGR CAP CCFTA CCI CECA CEPA CGE CIC CIF CMM CoA COMESA

Applied Administered Price APEC Business Advisory Council Anti-Counterfeiting Trade Agreement ASEAN Free Trade Agreement ASEAN–India free trade area Aggregate Measurement of Support Agreement on Agriculture Asia-Pacific Economic Cooperation Agricultural and Processed Food Products Export Development Authority Asia-Pacific Trade Agreement Alternative Reference Point Agreement on Subsidies and Countervailing Measures Association of Southeast Asian Nations ASEAN Trade in Goods Agreements Agriculture Technology Management Agency Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation Bacillus thuringiensis Compound Annual Growth Rate Common Agricultural Policy Canada–Chile Free Trade Agreement Competition Commission of India Comprehensive Economic Cooperation Agreement Comprehensive Economic Partnership Agreement Computable general equilibrium Central Information Commission Cost, Insurance and Freight Conservation and Management Measures Committee on Agriculture Common Market for Eastern and Southern Africa xix

xx

CPTPP CSIR CUTS CV DBT DBT DGFT DR-CAFTA DS EEZ EFTA EPWRF ERP ES EU FAO FFA FICCI FOB FRP FSSAI FTA FTAAP GATT GCC GDP GEAC GHG GM GoI GSP GSTP GTAP GVA HS ICAR ICCAT ICMR ICS ICT IOTC IPOA-IUU ITC

Abbreviations

Comprehensive and Progressive Agreement for Trans-Pacific Partnership Council of Scientific and Industrial Research Consumer Unity and Trust Society Coefficient of Variation Department of Biotechnology Direct Benefit Transfer Director General of Foreign Trade Dominican Republic–Central American Free Trade Agreement Domestic Support Exclusive Economic Zone European Free Trade Association Economic and Political Weekly Research Foundation External Reference Price Export Subsidy European Union Food and Agriculture Organization Forum Fisheries Agency Federation of Indian Chambers of Commerce & Industry Free on Board Fair and Remunerative Price Food Safety and Standards Authority of India Free Trade Agreement Free Trade Area of the Asia-Pacific General Agreement on Tariffs and Trade Gulf Cooperation Council Gross Domestic Product Genetic Engineering Appraisal Committee Greenhouse Gas Genetically Modified Government of India Generalised System of Preference Global System of Trade Preferences Global Trade Analysis Project Gross Value Added Harmonised System of Classification Indian Council of Agricultural Research International Commission for the Conservation of Atlantic Tunas Indian Council of Medical Research International Classification of Standards Information and Communications Technology Indian Ocean Tuna Commission International Plan of Action to Prevent, Deter and Eliminate Illegal, Unreported and Unregulated Fishing International Trade Centre

Abbreviations

I-TIP IUU LDCs LMT MC MEIS MERCOSUR MFN MNE MoEF&CC MPEDA MRA MRL MSME MSP MSY NAAS NAFTA NAMA NCRB NGO NITI Aayog NPC NSSO NTB NTC NTM OECD PIB PMFBY PM-KISAN PSCST PSH PTA R&D RCA RCEP REER RFMO RTA SAARC SACU SADC SAFTA

xxi

Integrated Trade Intelligence Portal Illegal, Unreported and Unregulated Fishing Least Developed Countries Lakh Metric Tonnes Ministerial Conference Merchandise Exports from India Scheme Southern Common Market Most Favoured Nation Multinational Enterprise Ministry of Environment, Forest, and Climate Change Marine Products Exports Development Authority Mutual Recognition Arrangement Maximum Residue Level Micro, Small and Medium Enterprises Minimum Support Price Maximum Sustainable Yield National Academy of Agricultural Sciences North American Free Trade Agreement Non-Agricultural Market Access National Crime Records Bureau Non-Government Organisation National Institution for Transforming India Nominal Protection Coefficient National Sample Survey Office Non-Tariff Barrier Non-Trade Concern Non-Tariff Measure Organisation for Economic Co-operation and Development Press Information Bureau Pradhan Mantri Fasal Bima Yojana PM-Kisan Samman Nidhi Parliamentary Standing Committee on Science and Technology, Environment and Forests Public Stockholding Preferential Trading Agreement Research and Development Revealed Comparative Advantage Regional Comprehensive Economic Partnership Real Effective Exchange Rate Regional Fisheries Management Organisation Regional Trade Agreement South Asian Association for Regional Cooperation Southern African Customs Union Southern African Development Community South Asian Free Trade Area

xxii

SAPTA SDG SDT SFA SPC SPS SSG SSM TBT TRAINS TRIPS TRQ UK UNCLOS UNCTAD UNESCAP UNFSA US USD VIF VoP VSS WCPFC WDI WITS WTO

Abbreviations

SAARC Preferential Trading Arrangement Sustainable Development Goal Special and Differential Treatment Stochastic Frontier Analysis South Pacific Community Sanitary and Phytosanitary Special Safeguard Measure Special Safeguard Mechanism Technical Barriers to Trade Trade Analysis and Information System Agreement on Trade-Related Aspects of Intellectual Property Rights Tariff-Rate Quota United Kingdom United Nations Convention on the Law of the Sea United Nations Conference on Trade and Development United Nations Economic and Social Commission for Asia and the Pacific United Nations Fish Stocks Agreement United States US Dollar Variance Inflation Factor Value of Production Voluntary Sustainability Standards Western and Central Pacific Fisheries Commission World Development Indicator World Integrated Trade Solution World Trade Organization

Part I

WTO and Indian Agriculture

Chapter 1

Indian Agriculture under WTO and FTAs: An Assessment Rajan Sudesh Ratna, Sachin Kumar Sharma, and Adeet Dobhal

Abstract Liberalisation of Indian agriculture under the World Trade Organisation (WTO) and free trade agreements (FTAs) has always been a sensitive issue due to the crucial role played by the sector in economic development, GDP growth and employment. This chapter provides an overview of the WTO’s Agreement on Agriculture and the issues faced by the Indian agriculture sector under its different pillars. In particular, it examines issues of critical importance for India, such as market price support, import surges, food security and special and differential treatment (S&DT) at the WTO, while also providing insights from negotiations. The chapter also deals with agriculture-specific issues in India’s FTAs, providing a broad view of its commitments and assessing trade performance of Indian agriculture over the years. It concludes by stressing the need to level the playing field in agricultural trade at the multilateral and regional level for Indian farmers. Keywords WTO · Agriculture · Food security · Import surges · Domestic support · Export subsidy · Market access · Developing countries · Free trade agreements

1.1 Introduction Liberalisation of Indian agriculture under WTO and FTAs has been a contentious issue for all the stakeholders involved. This is primarily because the sector contributes significantly to employment, GDP, poverty alleviation, rural and economic development. However, the inherent problems of this sector such as fragmented landholding, small farm size, inadequate irrigation facilities, marketing and other infrastructural deficiencies remain issues of significant concern. For instance, 99.43% of Indian R. S. Ratna United Nations ESCAP, South and South-West Asia Office, New Delhi, India S. K. Sharma (B) · A. Dobhal Centre for WTO Studies, Indian Institute of Foreign Trade, (IIFT), New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_1

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farmers are low income or resource-poor as their average landholding is less than 10 hectares (WTO 2020). Further, farmers’ income and livelihood continue to be adversely affected by cheap agricultural imports flowing in due to trade liberalisation (Roy 2006). Over and above, the stakeholders remain gravely concerned about the frequent attacks on India’s agricultural policies at the WTO (Sharma 2018). In fact, one of the primary reasons for India’s withdrawal from the Regional Comprehensive Economic Partnership (RCEP) negotiations in 2019 was the apprehensions of stakeholders, especially farmers, pertaining to the possible adverse impact of this mega-FTA on India’s agricultural sector (Dhar 2019). Issues regarding liberalisation are not new and were even raised when India was liberalising under the economic reforms of 1991 and during the Uruguay Round negotiations where agriculture as a sector was negotiated along with the establishment of WTO. Proponents of agricultural trade liberalisation believed that the process would be beneficial for developing countries’ farmers, including Indian farmers as it would open tremendous export opportunities for them. The Agreement on Agriculture (AoA) within the framework of the WTO was believed to benefit the farmers of developing countries, including India, which otherwise had a comparative advantage but were unable to get market access due to domestic support and export subsidies given by the developed countries. On the other hand, the opponents remained wary of import surge of subsidised goods and its negative impact on domestic farm prices which could prove detrimental for domestic producers (Chand and Bajar 2012). After liberalisation under the trade and economic reforms of 1991 and the establishment of the WTO in 1995, India witnessed an upward trend in both exports and imports of agricultural goods. The share of India’s exports in world agricultural exports increased from 0.85% in 1990 to 2.15% in 2018 (Table 1.1). A similar trend is also observed in India’s import share in world agricultural imports, which increased from 0.39% in 1990 to 1.54% in 2018. In absolute terms, the exports increased from US$3.5 billion in 1990 to US$38.92 billion in 2018. At the same time, imports of agricultural goods have also increased substantially from US$1.72 billion to US$28.24 billion (Fig. 1.1). Though the trade balance in agriculture remains positive, it shows a declining trend in recent years due to the narrowing gap between imports and exports. Additionally, given the diversification of the total trade basket of goods over the years, the share of agriculture in total merchandise imports and exports of India has shown a declining trend. Despite the increase in India’s agricultural trade, many concerns and issues related to the impact of trade liberalisation, under both multilateral and regional trade agreements, remain relevant. In recent times, these concerns have grown exponentially as agricultural policies of developing countries, including India, have been challenged through disputes and during the review process at the WTO (WTO 2019a, b). For instance, India is currently facing a challenge on its sugar and sugarcane policies in disputes brought against by Australia, Brazil and Guatemala in 2019. Further, the minimum support price policy (MSP) which functions as a safety net for Indian farmers was challenged by the United States, Australia and Canada during 2018–19

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Table 1.1 Share of export and import of Indian agriculture in total merchandise trade of India and the world (%) Year

Share of agriculture in India’s total

Share of Indian agriculture in world’s agriculture

Export

Import

Export

Import

1990

19.51

7.30

0.85

0.39

1995

20.64

8.65

1.07

0.48

2000

14.04

7.75

1.08

0.67

2005

10.31

5.26

1.21

0.84

2006

10.22

4.47

1.32

0.81

2007

10.86

4.65

1.44

0.90

2008

10.91

3.74

1.58

0.86

2015

12.93

7.03

2.22

1.74

2016

12.50

8.03

2.09

1.82

2017

12.98

7.33

2.24

1.89

2018

11.99

5.49

2.15

1.54

Source Authors’ compilation based on data from the WTO

2018

2015

2010

2005

1995

1990 0

5

10

15

20

25

30

35

40

45

Billion US$ Trade Balance

Import

Export

Fig. 1.1 Trend in India’s agriculture export and import (billion US$). Source Authors’ compilation based on data from the WTO

vide counter-notifications1 (WTO 2018a, b, c, 2019c). These challenges owing to the 1A

counter-notification is a part of the apparatus under the AoA to review notification and transparency obligations of WTO Members, whereby any Member may bring to the attention of the CoA, any measure by another Member which it considers to be required to be notified (Article 18.7).

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restrictive provisions of the AoA not only have the potential to dismantle agricultural support measures in developing countries but also derail the food security policies in many of these countries. This would negatively impact the livelihood of low-income and resource-poor farmers in India and several other developing countries. Unlike developed countries where farmers operate on large scales, have access to smart agriculture technologies and government-supported incentives, majority of the farmers in India practise subsistence farming with low income and returns. In addition, farmers are particularly challenged due to lack of adequate safety nets to shield them against income losses stemming from price fluctuations, poor farm mechanisation and other factors such as climate change and natural disasters. The low levels of income, along with crippling farm distress, have also resulted in farmers’ indebtedness and suicides in recent years. For instance, the latest survey on farm income reported that the average income per agricultural household was only around INR 6500 per month (NSSO 2013). The distress amongst the farm community can be gauged from the fact that more than 10,000 farmers committed suicide in India in 2018 (NCRB 2018). Absence of proper marketing channels, institutional credit systems, inadequate irrigation, farm mechanisation tools and infrastructural facilities compound the problems faced by farmers. Besides problems on the domestic front, high levels of support provided by developed members also adversely affected subsistence farmers in developing countries, with millions getting displaced. For illustration, the average annual per farmer support in India was US$ 282 for 2018–19 in contrast to US$61,000 in the USA for 2016 (Sharma et al. 2020a). This highlights the uneven and unfair playing field in international trade which permit developed countries to continue with such high levels of support at the detriment of the farmers in developing countries. Besides, these countries seek market access in developing countries for their products through negotiations under the WTO and regional trade agreements (RTAs). Recent challenges to agricultural policies of developing countries can be viewed in light of this commercial interest and a bid to gain market share in developing countries. On the other hand, developed countries themselves such as the United States have increasingly resorted to protectionist measures in the recent times to support their agriculture. The United States provided almost US$28 billion in payments to the producers affected by trade wars during 2018 and 2019 (Reuters 2019). Against this background, it is crucial to examine the various issues and challenges for Indian agriculture in light of the trade liberalisation process under WTO and RTAs. Specific issues of the Indian agriculture relating to WTO have been discussed in Sect. 2. Given that India is a party to many RTAs, Sect. 3 examines the pertinent agricultural issues under RTAs, and Sect. 4 concludes this chapter.

1.2 Indian Agriculture under WTO At the multilateral level, trade in agricultural goods is governed by the AoA. Prior to the WTO, agriculture was kept out of the General Agreement on Tariffs and

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Trade (GATT) negotiations. In the absence of concrete rules under GATT for the agriculture sector, the developed countries provided massive levels of support through various domestic and trade-related measures, and complex tariffs, thus developing their sectors through protectionist measures. Following the intense negotiations of the Uruguay Round from 1986 to 1994, members agreed to discipline tariffs, non-tariff barriers, subsidies etc. under the AoA. It was believed that the Agreement would correct the inequalities and distortions in global agricultural trade that benefitted producers of the developed world. To that end, the AoA aimed to “establish a fair and market-oriented trading system” and proposed commitments on its three main pillars: domestic support, market access and export subsidies. However, even after 25 years since the establishment of the WTO, several asymmetries and systemic issues remain unaddressed and a level playing field for majority of its members is yet to be achieved. The issues and challenges in the agriculture sector faced by India and other developing countries at the WTO are discussed in the following subsections.

1.2.1 Domestic Support All WTO members implement various domestic support measures in order to achieve agricultural growth and development. The AoA classifies these measures under different heads or ‘boxes’ in WTO parlance based on their potential distorting effect on production, prices and trade. Some domestic support measures such as those for general services, crop insurance, food aid, public stockholding for food security purposes etc. are considered either non-trade-distorting or at most causing minimal trade distortion or effect on production. These measures under Annex 2 of the AoA are termed as “Green Box”, and all members can provide support without any financial limit under them. Besides the Green Box, there are other provisions under which support can be provided by members such as “Blue Box”, “Development Box” and “Amber Box”. Blue Box measures are enshrined under Article 6.5, and these include direct payments made under production-limiting programmes. Like the Green Box, all members can provide support without financial limits under it. Article 6.2, also known as the Development Box, is a S&DT provision under which developing countries can provide support without prescribed limits for certain measures such as investment subsidies generally available to agriculture, input subsidies to low income or resource producers and subsidies provided to encourage diversification from illicit narcotic crops. Over the years, India has provided support, not only under Green Box and Article 6.2 but also under Amber Box, as mentioned in Table 1.2. Amber Box, being trade-distorting support under the AoA, is subject to strict financial limits. It is divided into product-specific and non-product-specific support; the former covering support provided on individual product basis, while the latter covers support available for agricultural products in general. For a majority of developing countries, trade-distorting support is capped at the de minimis limit, which

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Table 1.2 Trend in domestic support to agriculture in India (million US$) Years

Green box support

Article 6.2

Product-specific support

Non-product-specific support

Total support

2012–13

18,741

24,173

2,367

423

45,704

2013–14

18,362

22,828

1,212

379

42,780

2014–15

25,875

24,836

1,919

366

52,995

2015–16

18,391

23,553

1,171

334

43,450

2016–17

19,693

21,514

2,104

2,653

45,963

2017–18

31,443

22,574

4,919

1,541

60,476

2018–19

22,482

24,184

6,473

3,317

56,457

Source Authors’ compliation based on Domestic Support Notifications of India to the WTO

is the minimum level of support allowed under the Amber Box. Both productspecific and non-product-specific de minimis is set at 10% of the value of production (VoP) for a concerned agricultural product and total agricultural VoP, respectively, for developing members. This limit for developed countries is set at 5%. As a result of the constraining limit under the Amber Box, Indian domestic support measures, especially in the form of the MSP, have come under severe attack in recent times. MSP is a form of market intervention under which the government procures agriculture products at target prices in order to protect farmers from price fluctuations and to ensure remunerative prices. Besides the constraining limit, the outdated methodology used to calculate product-specific support is threatening the continuation of this support policy. The AoA provisions provide that market price support (MPS) shall be calculated by multiplying the quantity of production eligible to receive the administered price with the gap between the fixed external reference price (ERP) and the applied administered price (AAP). The ERP is based on the years 1986–88, termed as the “base period”, and reflects the import or export price of an agricultural product during the base period, depending on whether a country was a net importer or exporter of the agricultural product concerned. As the MSP increases over the years, its comparison with the fixed ERP is bound to result in a breach of the 10% limit due to cumulative inflation. Based on this methodology, some WTO members have alleged that India has breached the applicable limit in the case of wheat, rice, pulses and cotton. These members ignore the impact of inflation on market price support which results in an inflated product-specific support. Further, by utilising this methodology, Australia in its counter-notification on India’s support to sugar and sugarcane claimed that India provided support exceeding its limits, almost equalling the value of sugarcane production in 2015. The same has been escalated into a WTO dispute, with Brazil and Guatemala also joining suit. The MSP policy serves an important safety for farmers and has played a vital role in attaining self-sufficiency in many agricultural products. Currently, 23 agricultural products are covered by this policy. India, with its vast market, is considered as a potential export destination by many WTO members for their products, and this

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commercial interest is also viewed as the reason for many of India’s policies, such as the MSP, being challenged at the WTO. In this context, it is also important to mention the additional aggregate measurement of support (AMS) entitlements of developed countries. During the Uruguay Round of negotiations, those members with high trade-distorting support got the additional flexibility to provide support beyond their de minimis limit. On the other hand, Amber Box flexibilities of most developing members has been restricted to the de minimis limit because of low levels of trade-distorting support during the base period. The limited flexibility under Amber Box, coupled with the MPS methodology, has considerably restricted the policy space of many developing countries (Sharma 2016). It is pertinent to note that it was mostly the developed nations providing high levels of trade-distorting support during the base period, and hence they secured this additional flexibility. Due to these entitlements, members such as the United States and the European Union have provided support for many products much above their de minimis limits. In addition to these inequitable provisions, recently there have been demands at the WTO seeking further disciplines to curtail the existing policy space available to developing countries, particularly under the de minimis and Article 6.2. These will invariably have detrimental effects on the limited and already-shrinking policy space available, increasing the development divide between developed and developing countries. Several developing countries have consistently raised concerns regarding the shrinking policy space under the AoA and the attack on S&DT principles in agriculture negotiations, which is a founding principle of the multilateral trading system.

1.2.2 Market Access Under the market access pillar, the AoA mandated conversion of all non-tariff barriers such as quantitative import restrictions, variable import levies, discretionary import licensing etc. to import tariffs that provided an equivalent level of protection. This process was called “tariffication”, and the limits were reflected in the Schedules of the members and then subsequently subjected to reduction commitments. In addition, members could not maintain or revert to non-tariff barriers that were required to be converted to tariff barriers. By adopting the ceiling-binding method under the tariffication process, India bound its tariffs on all agricultural lines. The average bound tariff on agricultural goods is 113%. However, India liberalised several lines autonomously and its applied average tariff was 39% in 2018–19. Tariff profile on agricultural products (Fig. 1.2) shows that for some of the products bound tariffs are much higher than applied tariffs, such as oilseeds. Under the AoA, some selected members secured the flexibility in the form of special safeguard measures (SSG) to deal with the adverse impact of import surges on agricultural products. The SSG allows for the imposition of additional duty on a product, over and above the bound rate, in case of an import surge or price

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180

165

160 140 120

126 114

113

100 80

64

40

54

52

60 39

50 50

37

35

20 0 Agriculture

Sugar

Dairy Bound Tariff

Cereals

Oilseed

Apple

Applied Tariff

Fig. 1.2 Tariff profile of agriculture in India. Source Authors’ compilation based on data from the WTO

falls compared to the 1986–88 base levels. It, therefore, serves as an effective tool to protect the domestic producers against high import volumes and price falls by allowing members to levy higher safeguard duties. However, this flexibility is not available to most developing countries, including India, leaving the producers in these countries vulnerable to import surges and declining prices (Sharma and Dobhal 2020). Indian farmers remain extremely susceptible to subsidised imports and volatility in prices, which adversely affects their income. Without the SSG, India can raise its applied customs duties only to the bound limit under the AoA in case of an import surge. An SSG type of instrument therefore becomes much needed for products with no or little gap between the bound and applied tariff. In 2018, India had experienced import surges in more than 200 tariff lines at six-digit HS level out of a total of 700 agriculture lines (Das et al. 2020). To deal with this situation India, along with other developing countries, have been pushing for a special safeguard mechanism (SSM) under the Doha Development Agenda. This will enable them to raise tariffs above the bound levels similar to safeguards in case of import surges and hence protect farmers’ income and livelihood. While ignoring the concerns of developing members, especially on SSM, the developed members are now calling for steep cuts in tariff on agricultural products in negotiations. In the absence of any mechanism to protect farmers from surges, cuts in tariffs will make them even more vulnerable to imports and price fluctuations.

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1.2.3 Export Subsidies Among the three pillars of the AoA, members have reached a consensus to address the negative effects of export subsidies on international trade. In the Nairobi Ministerial Conference (2015), members agreed to eliminate all forms of export subsidies on agricultural products. As per this decision, developed and developing members are not permitted to provide any export subsidies after 2015 and 2018, respectively. However, the developing countries have the flexibility to provide export subsidies under Article 9.1 (d–e) of the AoA till the end of 2023. Under this provision, India can provide subsidies to reduce the costs of marketing exports of agricultural products, including handling, upgrading, international transport and freight and other processing costs and internal transport and freight charges on export shipments. This decision was crucial because it allowed the developing countries to provide export subsidies, although limited, that are much needed to offset the infrastructural and marketing deficiencies. Notably, as part of the India-Sugar and Sugarcane disputes Australia, Brazil and Guatemala have also challenged certain export subsidy measures for sugar, besides the alleged domestic support measures for sugarcane. In another dispute, the United States had challenged India’s export-related measures alleging that these were inconsistent with the Agreement on Subsidies and Countervailing Measures (ASCM). Among the measures, the Merchandise Exports from India Scheme (MEIS), which covered agricultural products as well, was also challenged at the WTO and India lost this dispute in 2019, though certain panel findings have been appealed by India. In addition to these disputes, India’s export subsidy measures such as those related to transport and marketing assistance, are regularly questioned at the Committee on Agriculture (CoA). In this regard, the main challenge for Indian policymakers is to ensure the compatibility of its measures with the provisions of the AoA as well as the Nairobi Ministerial Decision. Pertinent to note is also the fact that since the window for providing export subsidies under Article 9.1 (d–e) will close in 2023, the policy orientation must be towards developing better infrastructure facilities and providing support in a manner compatible with WTO rules.

1.2.4 Food Security and other Non-Trade Concerns In today’s time, the non-trade concerns (NTC) have become almost as important as the trade concerns themselves. This is mainly because of the multifunctional impact and contribution that agriculture has on food security, environment, land conservation and plant, animal and public health. Recognising these, the AoA also gives due importance to NTCs by making them an integral part of the reform and negotiation process. The NTCs form an essential aspect of agricultural trade policy, more so for developing countries. Especially in light of the inching Sustainable Development

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Goals’ (SDGs) deadline, harnessing the agriculture sector also becomes vital for developing countries to achieve the eradication of poverty (Goal 1), zero hunger and doubling agricultural productivity and income (Goal 2). Food security, however, remains the most important NTC for most developing countries. In many countries, including India, food security programmes are intertwined and function in tandem with other integral components such as procurement, stockholding and distribution. Under the AoA as mentioned above, public stockholding and distribution are classified as Green Box measures under Annex 2 and hence are exempt from current AMS calculation. However, the procurement of food grains at administered prices attracts the provisions market price support under Para 8 of Annex 3. This support is covered by the Amber Box and is subject to strict de minimis limits. Given the 10% cap of de minimis, it is feared that many developing countries will breach, or are likely to breach, this limit on account of the food security policy itself. The limited amplitude under the Amber Box makes it extremely difficult for governments to procure food grains from farmers at administered prices breaching their applicable limits, seriously jeopardising these food security programmes. As an interim solution to this problem, members at the Bali Ministerial Conference in 2013 agreed that they “shall refrain from going through the WTO Dispute Settlement Mechanism to challenge the compliance of a developing member with its obligation related to domestic support” in relation to support provided for traditional staple food crops in pursuance of public stockholding programmes for food security purposes. This gave developing countries the much-needed flexibility to implement price-support policies for food security purposes, even if they resulted in a breach of the de minimis limit. However, for recourse to the Bali Decision to be available, members must ensure compliance with notifications, transparency, anticircumvention and safeguard provisions as laid down therein. Although the decision was a step in the right direction, it received criticism for its limited scope, coverage and the burdensome requirements that it placed on countries taking recourse to it. The decision covered only “traditional staple food crops” and was applicable only on the programmes that were in existence on the date of the decision, excluding coverage of any future food security programmes. The Bali Decision was initially supposed to be in force for four years as an interim solution. However, despite ministerial mandates requiring a permanent solution to the issue of food security, countries have been unable to reach a consensus. A complementary decision taken by the WTO members in 2014 permits this peace clause to be available until a permanent solution to the issue of food security is negotiated. This will continue to benefit developing countries that are likely to breach their commitments. India has become the first WTO member to take recourse to the Bali Decision for protecting its public stockholding programme for food security purposes for rice. In 2018–19, India’s product-specific support to rice was 11.46%, exceeding its 10% de minimis limit. However, by invoking the Bali peace clause, India is unlikely to face a legal challenge from other members arising from this breach of commitments. Given the many glaring lacunas in the interim Bali Decision, countries must engage in fruitful negotiations to reach a permanent solution addressing this issue. Food security is an evolving and multifaceted issue. Restricting its scope and coverage

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as under the Bali Decision will not be beneficial in the battle against global food insecurity. Consideration must be given to the issues and demands raised by developing countries, only then can this issue be successfully resolved. As is evident from above, the AoA although seemingly provides flexibilities to developing countries, but in reality, is skewed in favour of the developed countries. With these rules tilted against them, the developing countries continue to face challenges on multiple fronts. India has been under pressure to reduce its tariff on agricultural products and enhance market access for other countries, even though it has autonomously liberalised agriculture tariffs. Further, proposals have also been tabled at the WTO seeking disciplines on de minimis limits. Notwithstanding the fact that de minimis is the only flexibility that most developing countries have under the Amber Box, as opposed to the additional AMS entitlements of developed countries, any further commitments will invariably reduce the limited flexibility available to developing countries. Additionally, support under Article 6.2, which is an S&DT provision, has been sought to be disciplined in the negotiations and despite its undeniable importance, proposals seeking its reduction and capping have been tabled at the WTO. Not only do these strike at the very foundation of the S&DT principles, but also contrast with the mandate under the Doha Development Round and will negatively impact agriculture in developing countries, especially India. The coming times at the WTO will be extremely difficult for India as it wages an uphill battle on many fronts. Developing countries must rally together and negotiate effectively to produce outcomes ensuring that global agricultural trade becomes fairer, inclusive and more equitable.

1.3 Indian Agriculture under FTAs While the earlier section discussed the implications of WTO obligations on Indian agriculture, this section examines the implications of India’s commitments in FTAs/RTAs. Unlike WTO, the implications of RTAs in goods vary since they have different forms and scopes. This section is divided into three sub-sections as follows:

1.3.1 General Characteristics of RTAs The simplest form of RTAs is preferential trading agreements (PTAs). In PTAs tariff concessions over MFN applied rates are offered on limited products. The other form is an FTA, which has a higher level of commitment. In FTAs tariffs on goods are required to be eliminated gradually, meaning that after an agreed timeframe, the FTA duties should be “zero”. Unlike PTAs, FTAs are required to cover substantial trade liberalisation. The highest level of RTAs is in the form of Comprehensive Economic Cooperation Agreements (CECA) or Comprehensive Economic Partnership Agreements (CEPA). These cover issues, which go beyond conventional goods

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only agreements of PTAs and FTAs. CECAs/CEPAs not only cover FTAs in goods but also include binding commitments or cooperation frameworks for trade in services, investments, intellectual property, standards and non-tariff barriers, trade facilitation, competition etc. All these RTAs have the objectives of liberalising trade and economy, which are broader and deeper than WTO obligations or are beyond the scope of WTO. It may also be important to note that in PTAs since the degree of tariff liberalisation is lesser than FTAs, generally agricultural products are kept out of tariff concessions. However, in FTAs and CECAs, since the tariffs have to be eliminated on substantial trade coverage, liberalisation of agriculture sector often becomes a compulsion for the participating countries. The agreements, nonetheless, provide certain flexibilities allowing countries to keep certain sensitive products out of tariff liberalisation commitments, and these products are listed separately in the agreement as Exclusion/Negative/Sensitive List. Another important element of RTAs is rules of origin. A product exported under RTA, and on which a tariff concession is sought, must comply with the rules of origin prescribed under that RTA. In simple terms, the rules of origin specify the conditions for a product to be eligible for preferential treatment upon imports. For primary products like agriculture items, they prescribe that the products must have been grown in the exporting country (i.e. wholly obtained), however, for manufactured items, the conditions become complex as there are conditionalities relating to the production processes and/or use of imported inputs. The objective of rules of origin is to ensure that tariff concessions on imports are availed only by the parties to the RTAs and circumvention of third country goods do not happen. As different forms of RTAs have different coverage and commitments, they also differ from the WTO obligations. Some of the main differences between an RTA and WTO agreement are as follows: (i)

The negotiations at the WTO are to bind tariffs at new levels which are lesser than the base level of bindings negotiated in the previous round. For example, India’s average agriculture bound tariff is 113% due to commitments taken under the Uruguay Round which were completed in 1994. The proposal in the Doha round was to achieve a new bound rate through a formula approach so that these new bindings are less than 113% (but not zero duty). India took autonomous liberalisation after implementing Uruguay Round commitments, and the average applied import tariff on agriculture items is 39% in 2018, which is commonly called at MFN tariff or applied rate of tariff. The new binding rates, as per Doha round modalities, must be lesser than 113% but depending on the formula it can be higher or lesser than 39%. In case of FTAs however, the negotiations are held to bring the tariffs to zero in a fixed timeframe, and the actual reduction in tariff in FTA starts from the MFN applied duty, i.e. 39% and not the WTO binding rates which in this example was 113%. Thus, while WTO provides for greater flexibility and policy space to the domestic producers, in FTAs the flexibility is only for items kept in the Exclusion/Negative/Sensitive list. Therefore, the agricultural items which are included in the FTA tariff liberalisation list will face greater competition

1 Indian Agriculture under WTO and FTAs: An Assessment

(ii)

(iii)

(iv)

(v)

15

from FTA partners than the rest of the world. As explained earlier, PTAs are more liberal than WTO but less liberal than FTAs, as substantial coverage of products is not required, and thus tariffs on most of the sensitive agriculture items are not liberalised. In WTO, the modalities for tariff liberalisation are different for the agricultural sector and non-agricultural sector. Generally, the binding level in agriculture is higher than in the non-agriculture sector. However, in FTAs a single modality for tariff liberalisation (bringing duties to zero) is agreed for both agriculture and non-agriculture products. Though both WTO and FTAs aim to reduce the non-tariff barriers, it has been observed that the process in WTO is much slower than the FTAs. Since the number of parties in FTAs is lesser, it is easy to reach an agreement for seeking harmonisation of standards bilaterally or regionally and equivalence of mutual recognition arrangements (MRAs) (Sithamaparam 2011; Ratna 2016) In terms of safeguard actions, the WTO agreement provides a mechanism for protection of the domestic industry, including agriculture items as per the Agreement on Safeguards. In case of a surge in imports causing a serious injury to the domestic industry, a safeguard measure is allowed to be taken by the importing country, subject to compliance with other provisions in the Agreement on Safeguards. However, in the RTAs, since the surge in imports may happen due to preferential tariffs from RTA parties themselves, taking WTO safeguard action may restrict imports from non-RTA parties, which cannot be penalised for preferential imports. Thus, in many of the RTAs, special provisions are made through a preferential safeguard mechanism. This mechanism is different from the WTO and safeguard action is taken only when there is a surge in imports causing serious injury to the domestic industry, including primary agriculture and processed food sector on account of preferential tariff given to RTA partners. As a safeguard mechanism, tariff concessions that are allowed under RTAs can be withdrawn partially or fully. Also, while there are discussions of a Special Safeguard Mechanism for the agriculture sector at the WTO, so far, no such discussions have been observed in FTAs. Certain issues covered in WTO but are generally not covered in RTAs relate to domestic support and export subsidies. The disciplines on these are negotiated in WTO and not in RTAs. In case a country agrees in RTA not to provide domestic support or export subsidy on agricultural products, this will automatically be extended unconditionally to the rest of the WTO members.

1.3.2 An Overview of India’s FTAs in the Context of Agriculture India had initially adopted a very cautious and guarded approach to RTAs (Chaisse et al. 2011) and was engaged in bilateral/regional initiatives, mainly through PTAs

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like the Bangkok Agreement signed in 1975 to exchange tariff concessions in the ESCAP region, and SAARC Preferential Trading Arrangement (SAPTA signed in 1993), which had the objectives of promoting South–South trade. However, since they were PTAs with partial tariff reduction on a limited number of items under tariff concessions, the intra-regional trade was not significant in these agreements (Mohanty 2003; Ratna 2008). India had signed bilateral FTAs with Bhutan and Nepal, which are non-reciprocal due to the sizes of economies and also to maintain social, economic and political stability with neighbouring nations. India’s FTA with Sri Lanka was signed in 1998 but was operated from March 2000 (Table 1.3). This FTA too had a favourable treatment for Sri Lanka since it allowed having a bigger negative list for Sri Lanka and while India brought the tariffs to zero in 3 years, Sri Lanka was given 8 years. The asymmetry in this FTA was also due to the differences in the levels of economic development of the nations and good political relationship between the two (HCI 2013). In India’s FTAs with Bhutan and Nepal, the parties liberalised the entire agriculture sector, thereby making all agricultural items imported under FTA on zero duty. In the FTA negotiations with Sri Lanka, India agreed to eliminate tariffs on most agricultural products, only desiccated coconut and alcoholic beverages were kept in the negative list. In addition, a tariff-rate quota (TRQ) on tea was provided. TRQ is a mechanism where an annual agreed quantity of a product, called a quota, may be imported under tariff concession. Once the quota is fully used in a given year, MFN duty is charged on subsequent imports in excess of the quota amount. India’s liberalisation of agriculture for Sri Lanka was also on account of the fact that many of the agricultural items were not produced in Sri Lanka and hence they could not pose a threat to domestic producers for they would not qualify the rules of origin and thus could not be imported duty-free. As the implementation of FTA progressed, a surge in imports on certain high MFN duty agricultural products (in the range of 60–70%) was witnessed. In certain cases, even circumventions in rules of origin were noticed, where imports of cloves, pepper and vanaspati created a lot of problems for Indian producers (Economic Times, 2005 and 2019). Import of vanaspati from Nepal also became a problem for India’s domestic producers (Economic Times, 2007). This led to India imposing quantitative restrictions on imports of vanaspati from Sri Lanka (DGFT 2008). The liberalisation of items in FTAs with high MFN duties can always create problems as the chances of circumvention are high, while on the other hand if the MFN duties are less, then chances of circumvention are less. This was noted when India brought the MFN duty on crude palm oil (CPO) from 45% to 0, and the duty-free vanaspati import from Sri Lanka and Nepal under FTA stopped (Business Standard 2013). There have been several studies and lessons on the impact of India’s FTAs on the agriculture sector. These are ex-ante studies which were useful in negotiations. Many other studies were carried out, which were ex-post facto analysis. These studies observed that if India liberalises its agriculture sector in FTAs, it will be detrimental to the farmers as well as the domestic producers. Studies have also pointed out the problems that the agriculture sector faces along with the plantation crops, dairy and spices (Bhutani 2014; Ghosh 2009; GRAIN 2019; Mohanakumar 2012; Sharma

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Table 1.3 Illustrative list of agriculture items on which India has given tariff concession Countries/Region

Members

Items description

Afghanistan

–

Raisins, dry fruits, fresh fruits and spices

Asia Pacific Trade Agreement (APTA)

Bangladesh, China, India, Lao PDR, Republic of Korea, Sri Lanka

Live animals, meat and meat products, fisheries, yogurt, butter milk, seeds and tubers, molasses and sugar, processed food and drinks etc

Chile

–

Meat and fish products and rock salt

Global System of Trade Preferences (GSTP)

G 77

Only 5 items relating to copra, lac, gum and molasses covered

MERCOSUR

Argentina, Brazil, Paraguay and Uruguay

Around 10 items—meat and meat products are covered

ASEAN

10 ASEAN members

Many of the agriculture items are covered like meat, certain plants, spinach, olives, vegetables like gherkins, mushrooms, some beans, sweet potato, cashew, Brazilian nuts, hazel nuts, dates, peach, kiwi fruit, cinnamon, buck wheat, vegetable seeds, pasta, corn flakes, biscuits, fruit juices etc. Partial tariff concession on certain agriculture items under the Special Products category which cover crude and refined palm oil (CPO and RPO, respectively), coffee, black tea and pepper

Bhutan

–

All agriculture items covered for duty-free imports

Nepal

–

All items, except Vanaspati which is in TRQ

SAFTA

SAARC members

Except for frozen meat, fish, milk and milk products, vegetables, dry fruits, tea, spices, wheat, maize, rice, edible oils, sugar, juices etc. all other agriculture items are covered

PTA

FTA

(continued)

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Table 1.3 (continued) Countries/Region

Members

Items description

Sri Lanka

–

Except for desiccated coconut and alcoholic beverages, all other agriculture items are covered under tariff concessions. TRQ on Vanaspati and tea

Republic of Korea

–

Live animals, meat, cheese, bulbs and roots, spinach, green pepper, mushroom, cucumber and gherkins, beans, hazel nut, pistachio, banana, dates, pineapple, mango, guava, berries, chili powder, oil seeds, vegetable saps and extracts, sugar confectioneries, cocoa powder, certain breads, pastries, certain jams, jellies, fruit juices, preserved fruit, nuts, soup, ketchup, sauce, mineral water etc

Japan

–

Live animals, meat, cheese, bulbs and roots, spinach, green pepper, mushroom, cucumber and gherkins, beans, hazel nut, pistachio, banana, dates, pineapple, mango, guava, berries, black tea, chili powder, oil seeds, vegetable saps and extracts, betel leaves, animal fats, glucose, sugar confectioneries, cocoa powder, certain breads, pastries, certain jams, jellies, fruit juices preserved fruit, nuts etc

Malaysia

–

India has offered ASEAN-plus tariff concessions to Malaysia on 76 extra items such as fruits, cocoa, and palm oil products. Special products on which tariff reduction is applied are CPO, RPO, Coffee, Black tea, Pepper, palm kernel oil, margarine of edible vegetable origin

CECA

(continued)

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Table 1.3 (continued) Countries/Region

Members

Items description

Singapore

–

On products cocoa butter, pasta, dried soup powder, certain breads—duty is eliminated. On meat and meat products, baking powder, soya sauce, mayonnaise, soft drinks, pan masala, custard powder etc.—preferential duty is 50% of MFN duty

Source Authors’ compilation based on information available at the Department of Commerce, Government of India

2007; Wouters 2014). Some studies also pointed out that for certain markets, India’s agriculture exports may benefit from FTAs (Chand 2014; Jagdambe 2016; Renjini 2016). It has also been argued that the much needed domestic reforms in India have not taken place, and thus FTAs can be used as a tool to facilitate these reforms (Economic Times 2019a; Ratna 2013). Drawing from these experiences, India in subsequent FTAs exercised more caution in liberalising agriculture; thus, most of the agriculture items were kept in the Sensitive/Negative list, which was illustrated in South Asian Free Trade Area (SAFTA), Singapore, ASEAN, Japan and the Republic of Korea FTAs.

1.3.3 Trade Performance of Indian Agriculture in FTAs This section analyses whether the Indian agricultural sector has benefited from these FTAs/CECAs. We examine how agriculture trade is taking place with the FTA partners vis-à-vis its global trade for the entire period of 1996 to 2019, irrespective of the fact that most FTAs were signed after 2000. This analysis is done only for the countries with whom India has an FTA or CECA. The data covers total agriculture sector trade as classified under WTO HS nomenclature and has not been taken as per the year of the signing of FTA/CECA, but for the entire period from 1996 till 2019. Since the data on preferential trade is not available, this analysis was done with respect to the total agriculture trade. Figure 1.3 demonstrates the share of FTA partner2 in India’s global export of total goods and agriculture during 1996–2019. It shows that the share of the FTAs partners in global export of India’s agricultural goods is higher than the total goods comprising both agricultural and non-agricultural goods. However, the share of the FTA partners in India’s agricultural export has shown a declining trend over the years. In the case of imports, a significant share of India’s agricultural import is sourced 2 The

analysis is with reference to trade with ASEAN, SAARC, Japan, Malaysia and Republic of Korea with whom India has FTA.

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40% 35% 30% 25% 20% 15% 10% 5% 2017

2018

2019

2017

2018

2016

2016

2014

2015

2013

2012

2010

2011

2009

2008

2007

2005

2006

2004

2003

2001

2002

1999

2000

1998

1997

1996

0%

Export share of FTA partners on India's global exports Agriculture export share of FTA partners on India's global agriculture exports

Fig. 1.3 Share of FTA partners in India’s global total and agricultural exports. Source Authors’ calculation based on WITS

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2003

2004

2002

2001

2000

1999

1998

1997

1996

70% 60% 50% 40% 30% 20% 10% 0%

Import share of FTA partners on India's global imports Agriculture import share of FTA partners on India's global agriculture imports

Fig. 1.4 Share of FTA partners in India’s global imports. Source Authors’ calculation based on WITS

through its FTAs partners. For instance, more than 42% of India’s agricultural import came from FTAs members in 2018 (Fig. 1.4). Given that the shares may only reflect the relative importance of export versus imports, it is also important to investigate the actual value of trade, at least in terms of the balance of trade (export value—import value). While India has a favourable balance of trade in its global trade of agriculture sector (Fig. 1.1); when it comes to trade with the FTA partners the situation is reversed from 2014, which is also the year when the full implementation of FTA with ASEAN began. In 2018, India’s imports from FTA partners was worth US$7.67 billion against its exports of US$4.97 billion with a negative balance of trade of US$2.7 billion (Fig. 1.5). This gap is mostly due to imports from Indonesia and Malaysia which collectively account for US$5.92 billion. Given that India has kept most of the agriculture items in its Negative or Sensitive List, majority of the agriculture imports are either under partial tariff concessions (case of palm oil from Indonesia and Malaysia), or TRQs or under full payment of duties. From the above analysis, it becomes clear that the total agriculture sector

1 Indian Agriculture under WTO and FTAs: An Assessment

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12 10 8 6 4 2 0 -2 -4 Exports

Imports

Balance of trade (FTA)

Fig. 1.5 India’s agriculture trade with FTA partners (in US$ billion). Source Authors’ calculation based on WITS

liberalisation in FTAs by India and its trade partner may bring more advantage to the FTA partner rather than India. India has been in the process of negotiating RTAs with some of its important trading partners. Some of these agreements have been at an advanced stage. These include Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC), Gulf Cooperation Council (GCC), SACU, EU, EFTA, New Zealand, Canada, Australia, Indonesia, Israel etc. (Department of Commerce, India 2020). Since 2012, India had been actively involved in the RCEP negotiations as well. With the ASEAN and six of its free trade partners—Australia, China, India, Japan, New Zealand and South Korea, the RCEP sought to achieve a close regional integration amongst its members. However, in November 2019, India announced its withdrawal from the RCEP in light of the potential adverse impact the agreement would have had on its economy, especially on sectors such as agriculture, dairy and micro, small and medium enterprises (MSMEs). It was expected that agriculture and dairy that have been traditionally protected with tariffs would have been negatively impacted by this agreement (Dhar 2019; Das 2019; Jafri 2018). Owing to the fact that India’s dairy sector is dominated by small-scale dairy farmers, it would have been unable to compete with the large-scale and technology-intensive dairy industries of Australia and New Zealand after joining the RCEP (Verma 2020; GRAIN 2019). India’s trade balance in agricultural goods with the RCEP countries stood at USD ()1387 million in 2018 (Sharma et al. 2020b). Given that under the RCEP, India would have been required to lower its tariffs substantially, this negative trade balance would have only increased further. In addition, the lowered tariffs could have increased the occurrences of the already high number of import surges on agricultural goods, negatively impacting the livelihood of Indian farmers. Further, the likely adverse impact of RCEP on non-agricultural market access (“NAMA”) products, especially those produced by MSMEs, was another crucial factor for India’s withdrawal from the RCEP.

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1.4 Conclusion The above discussion highlights some of India’s concerns and sensitivities regarding agriculture under the WTO and FTAs negotiations. Agricultural policies of India have been frequently challenged at the multilateral level by other WTO members. Due to restrictive provisions of the AoA, India’s price support programmes, such as the MSP, have been severely questioned at various instances during the review process. Additionally, several proposals have been tabled at the WTO that seek to curtail the policy space available to developing members in providing domestic support to farmers. Through various proposals, many developed members have also sought the dilution of the S&DT provisions in the AoA, which may have adverse implications for input subsidies to low-income or resource-poor farmers in India and other developing countries. Besides, Indian farmers face unfair competition on account of the high level of domestic support provided by the developed members, which often displaces poor farmers in international as well as domestic markets due to import surges of subsidised goods. Given the fact that most of the farmers in India practise subsistence farming, which is labour-intensive as opposed to technology-intensive, they face multiple challenges. Without adequate safety-nets and dilution of S&DT principles in the pretext of trade liberalisation will negatively affect the welfare of these farmers. India, along with other developing countries, needs to be cautious in the negotiations and must strive to correct the imbalances in the AoA and demand per farmer support as an essential element in future negotiations. Further, the welfare of Indian farmers continues to be undermined due to import surges stemming under multiple FTAs. When India started its RTA negotiations, it was mostly to show the solidarity towards South– South trade. However, even on this end, the results for India have not been very favourable. In fact, one of the major reasons for India’s withdrawal from the RCEP negotiations was the likely adverse impact on its agriculture sector. To effectively utilise the opportunities under the WTO and the various FTAs, there is a need for domestic reforms in the agricultural sector. Recent policy changes such as PM-Kisan Samman Nidhi (PM-KISAN), Pradhan Mantri Fasal Bima Yojna (PMFBY) and the direct benefit transfers (DBT) for fertiliser subsidies, among others, are all steps taken towards transforming Indian agriculture. However, further reforms need to be undertaken, especially on issues related to non-tariff barriers such as sanitary and phytosanitary measures for ensuring export competitiveness. Finally, trade liberalisation under FTAs and WTO must not be compartmentalised and viewed in isolation, rather there is a need for coherence and consistency in both the approaches.

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WTO. (2018a). Communication from the United States of America- Certain Measures of India Providing Market Price Support to Rice and Wheat. Document Number G/AG/W/174. WTO. (2018b). Communication from the United States of America- Certain Measures of India Providing Market Price Support to Cotton. Document Number G/AG/W/188. WTO. (2018c). Communication from Australia—India’s Measures to Provide Market Price Support to Sugarcane. Document Number G/AG/W/189. WTO. (2019a). China—Domestic Support for Agricultural Producers, Report of the Panel, Document Number WT/DS511/R. WTO. (2019b). India- Measures Concerning Sugar and Sugarcane. DS 579, DS 580 and DS 581. WTO. (2019c). Communication from Canada and the United States of America - Certain Measures of India Providing Market Price Support to Pulses, Including Chickpeas, Pigeon Peas, Black Matpe, Mung Beans and Lentils. Document Number G/AG/W/193. WTO. (2020). Notification by India, DS 1, Document Number G/AG/N/IND/18.

Chapter 2

Fisheries Negotiations at the WTO: Small Bait for Large Catch Radika D. Kumar

Abstract Fisheries subsidies negotiations have been a protracted issue ever since the launch of the Doha Development Agenda in 2001. Members of the World Trade Organization (WTO) have intensified their efforts to conclude the negotiations by the 12th WTO Ministerial Conference to be held in 2021. At present, significant divergences exist between developed and developing countries in the WTO on the formulation of disciplines on fisheries subsidies. This chapter will discuss the key contentious issues of the various fisheries subsidies proposals, including the recent Chair’s text of July 2020. The chapter discusses the major imbalances, including the lack of policy space for development, the imposition of stringent management measures, compromising the rights of developing countries in UNCLOS and the low ambition of special and differential treatment. The chapter further discusses how the existing proposals benefit the market access agenda of the developed economies. It also cautions that a similar scenario of the imbalance experienced by developing countries in the Agreement on Agriculture will be repeated in the existing fisheries subsidies negotiations if the contentious issues remain unresolved in the final agreement. The paper also provides a strategic way forward in relation to a balanced special and differential treatment for member’s consideration. Keywords Fisheries · Subsidies · Negotiations · Developing countries · Policy space · Management

This chapter draws in certain sections from the author’s working paper titled “Fisheries Subsidies Negotiations at the WTO: The Real Catch” published with the Centre for WTO Studies, IIFT, India dated 17 November 2017. Disclaimer: The views expressed in the paper is that of the authors and not of any persons or organzation which the author is affiliated with. R. D. Kumar (B) Former Lecturer Economics, University of the South Pacific, Suva, Fiji e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_2

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2.1 Introduction In recent times, members of the WTO have intensified their efforts to reach a consensus on the long overdue fisheries subsidies’ negotiation. The discussions on fisheries subsidies have been an outstanding agenda for the WTO since the launch of the Doha Development Agenda in 2001. The mandate of the Doha round in this regard was to clarify and improve the existing WTO fisheries disciplines, on which a consensus still eludes the membership. To further add clarity to the 2001 mandate on fisheries subsidies, at the Hong Kong Ministerial Conference in 2005, the agenda was extended to include the prohibition of fisheries subsidies that contribute to overfishing and overcapacity.1 While members of the WTO have underscored the importance of a balanced outcome of the fisheries subsidy negotiations, there has been a longstanding issue concerning the market access and socio-economic implications for different countries. For the developing countries, fisheries is a crucial sector for their socioeconomic development, including livelihood issues for small fishermen. Most of the small states and least developed countries are major holders of fish resources being coastal states, while the developing countries are major fish processors. According to the 2016 FAO Report on the State of the World of Fisheries and Aquaculture, both “fisheries and aquaculture remain an important source of food, nutrition, income and livelihoods for hundreds of millions around the world”. The report also shows that in 2016 the developing countries accounted for more than half of the fish exports. In other words, the developing countries hold a more significant share of the fisheries market as compared to the developed economies. As a result, for developing and least developed countries, fish is not just used for human consumption but also adds to the upstream and downstream values (Kumar 2017). At the 11th Ministerial Conference2 of the WTO in 2017, the members agreed to continue to work constructively on fisheries subsidies negotiation with a view of adopting an agreement on comprehensive and effective disciplines that prohibit certain forms of fisheries subsidies that contribute to overcapacity and overfishing and eliminate subsidies that contribute to illegal, unreported, and unregulated (IUU) fishing. In doing so, members also recognized that appropriate and effective special and differential treatment for developing country and least developed countries should be integral to this negotiation. Members of the WTO expressed their commitment in intensifying their efforts to reach a consensus on fisheries subsidies negotiations in 2020. However, there are several proposals that have been tabled at the WTO since 2017, and the divergence between members is massive. With the outbreak of Coronavirus (COVID-19) and the postponement of the 12th Ministerial Conference, members of the WTO are continuing discussions to resolve this divergence. There are several issues that merit further examination in various proposals. These issues include the scope of the disciplines on fisheries subsidies, among others. Most developed countries that have undertaken subsidies reforms and have shifted to the 1 See 2 See

https://www.wto.org/english/tratop_e/rulesneg_e/fish_e/fish_e.htm. https://www.wto.org/english/news_e/news17_e/mc11_13dec17_e.htm.

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provision of non-specific subsidies are only aiming at disciplining the specific subsidies. Constraining the scope to only specific subsidies would affect the developing countries adversely, which might create a similar situation of the imbalance that the WTO Agreement on Agriculture has created for the developing countries. Secondly, some of the proposals entail burdensome requirements on special and differential treatment (SDT) for developing and least developed countries. The implementation of the SDT is conditional on stringent management measures. For example, in some of the proposals from the developed countries, developing countries are required to develop a management plan and also provide fish stock assessment before it can benefit from the provision of subsidies to its small-scale sector. Such stringent management requirements impose additional burden and costs on developing countries. Furthermore, this creates an automatic link between fisheries subsidies disciplines and management. Fisheries management is not in the mandate of the WTO but falls under regional fisheries management organizations. There are unilateral disciplines imposed by the European Union and the United States on fisheries management violation. If these requirements are multilateralized in the WTO, they will create an additional burden on trade cost for the developing and least developed countries’ fisheries exports acting as non-tariff barriers. Some countries are aiming at a cap-based approach to the disciplines which has resemblance to the contentions and imbalances in the agriculture subsidies which members are grappling with for over a decade. The developing and least developed countries are still experiencing the detrimental economic consequence of the outcomes of the agriculture subsidies negotiations. Transparency issues are also expanded to include management measures with burdensome requirements conditioned for availing special and differential treatment. Another element which members are still aiming to resolve is the structure of the dispute settlement system in view of the fisheries subsidies negotiation and the broader discussions on the WTO reforms. This paper examines the implication of the current fisheries proposals that are under negotiations at the WTO. As it stands, the rules-based negotiations on fisheries subsidies are ongoing, and members are required to conclude the negotiations by the 12th Ministerial Conference (MC12). Several proposals have emerged between 2017 and 2020. The paper is critical and timely as it provides a consolidated analysis of these new proposals. The paper will also enable trade negotiators and policymakers to understand better the existing fisheries instruments and synergies to major imbalances that are created in the various proposals and areas where countries need to exercise caution to retain policy space for development. The research from this paper will benefit WTO member countries, in particular, developing and least-developed country negotiators. The paper will be an additional resource in the fisheries subsidies negotiations to enable negotiators to reach a balanced multilateral outcome for disciplines on fisheries subsidies. The rest of the paper is as follows: Sect. 2.2 of the paper will briefly discuss the existing international agreements and instruments in relation to fisheries management and trade. Fisheries management measures is a topical issue in many of the proposals, and it is imperative to understand its synergy with the subsidies negotiations. Section 2.3 will provide a brief on the state of play in the fisheries sector

30

R. D. Kumar

globally in relation to the resource owners, the vessel holders, the subsidy providers and the marine capture producers. It will also show the interplay between fisheries economics and fisheries management. Section 2.4 will analyze the various fisheries subsidies proposals over the past three years (2017–2020), and Sect. 2.5 will conclude with policy insights and recommendations in the negotiation.

2.2 International Agreements Related to the Fisheries Sector In the current fisheries subsidies negotiations, one of the major contentious issues has been the linkage of the disciplines on fisheries subsidies negotiations to the disciplines on fisheries management measures. It is therefore imperative to understand how various international agreements related to fisheries are addressing management issues and ways in which the WTO negotiations of the disciplines in relation to subsidies would impinge on the rights of member countries, in particular, the developing countries on fisheries resource management. In relation to the ownership and management of fisheries resources, one of the important multilateral decision relates to the United Nations Convention on the Law of the Seas (UNCLOS)3 which grants autonomous rights to Member States to explore, exploit, conserve, and manage the fisheries in their exclusive economic zones (EEZ). Article 61 of the UNCLOS provides coastal states with the rights over its EEZ. In doing so, the coastal states should take into consideration the best scientific evidence available to them, and where appropriate, cooperate at sub-regional, regional, and global levels. In managing the resources within their EEZs, appropriate measures are designed considering the relevant environmental and economic factors which include the needs of the coastal communities and the special requirements of developing countries. In practice, the management of resources within the EEZ is conducted through the formulation and development of national fisheries legislation and policies. In doing so, various economic, social, and environmental factors are taken into consideration by each nation while formulating the policies. Member States cooperate with the regional or sub-regional agencies that assist them through the training of observers and provision of scientific advice. Based on the said scientific advice, States develop national regulations for issuing licenses or permits to the local and foreign vessels for fishing in their EEZ. Sub-regional systems of collaboration are present in different regions. For example, in the Pacific region, the regulation of fisheries in the EEZ is achieved through the assistance of sub-regional organizations such as the Forum Fisheries Agency (FFA), the South Pacific Community (SPC), and the Parties to the Nauru Agreement (PNA for per seine fisheries). The coastal states within a certain region 3 Refer

to United Nations Convention on the Law of the Sea. https://www.un.org/depts/los/conven tion_agreements/texts/unclos/unclos_e.pdf.

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch

31

are members of these sub-regional organizations. These organizations have the skills and expertise to provide management advice to the coastal states. The UNCLOS is complemented by the UN Fish Stocks Agreement4 (UNFSA). The UNFSA’s objective is to ensure the long-term conservation and sustainable use of straddling fish stocks and highly migratory stocks through effective implementation. Artice 5 of the UNFSA states that in order to conserve and manage straddling fish stocks and highly migratory fish stocks, coastal states and states that are fishing on the high seas shall, in giving effect to their duty must cooperate in accordance with the convention. Part VII on the UN Fish Stock Agreement recognizes the special requirements of developing countries. It stipulates that states shall give full recognition to the special requirements of developing states in relation to conservation and management of straddling fish stocks. The special requirements of developing countries include factors such as (a) the vulnerability of the developing countries’ dependence on the exploitation of the living marine resources, (b) the avoidance of the adverse impact and ensuring that access to fisheries resources are available to subsistence, small scale, and artisanal fisheries, and (d) that such conservation and management measures do not disproportionately burden the developing countries. In the context of the WTO fisheries subsidies negotiations, members of the WTO need to exercise caution to ensure that both the UNCLOS and the UNFSA rights of developing countries are not diluted or revoked in the negotiations in the fisheries subsidies. Members need to ensure that in relation to the rights of developing countries over their exclusive economic zones and the special requirements of developing countries, enshrined in the UNCLOS and UNFSA are not superseded by the legally binding provisions of the fisheries subsidies disciplines. Some of the major proposals for discussions include aspects requiring members to commit to stringent management measures as a condition for special and differential treatment, including compromising the rights of developing countries over their EEZ. Such proposals will only limit the developing countries policy space and ability to manage its fisheries resources and sectoral expansion, however, at the same time they provide the dominant developed countries fisheries players’ greater market access. The discussions of management of fisheries resources must, therefore, be kept out of the WTO fisheries subsidies negotiations. At the regional level, members have various fisheries management organizations (RFMOs) that work with member countries in the conservation and management of fisheries resources as well. The participants of the RFMOs comprise the members and cooperating nonmembers. However, it is imperative to note that the conservation and management measures (CMM) adopted must not impose a “disproportionate burden” on developing states. In other words, there are already existing institutions with the expertise to deal with the CMMs. As a result, the WTO which does not have the mandate nor the technical expertise should not be discussing these complex issues and bringing

4 Refer

to United Nations Division of Ocean Affairs and the Law of the Sea: https://www.un.org/Depts/los/convention_agreements/convention_overview_fish_stocks.htm.

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R. D. Kumar

it into its forum. Developed countries through proposals must not dictate unilateral CMMs into the WTO fisheries subsidies disciplines. To effectively implement these legal instruments on CMMs and to ensure that the fisheries resources are managed efficiently in each of the different regional waters of the world, countries including the coastal states, the cooperating non-members, including distant water fishing nations form part of the membership of the various regional fisheries management organizations (RFMOs). The RFMO members are responsible for negotiating and developing CMMs. The agreed CMMs are negotiated among member countries taking into account the special circumstances of developing countries. By agreeing to a set of CMMs in the context of the disciplines on fisheries subsidies negotiations, the developing countries will compromise their rights to negotiate CMMs in RFMOs and undermine the fisheries management organizations. There are different RFMOs in operation in different regions. In the Pacific region, the Western Central Pacific Fisheries Commission (WCPFC)5 is an established RFMO. The WCPFC was established by the Convention on the Management of Highly Migratory Fish Stock in the Western Central Pacific Ocean. Another major RFMO is the International Commission for the Conservation of Atlantic Tunas (ICCAT)6 formed in 1969. The Commission may be joined by any government that is a member of the United Nations, any specialized UN agency, or any inter-governmental economic integration organization constituted by States that have transferred to it competence over the matters governed by the ICCAT Convention. There are 51 contracting parties to ICCAT. Some of which are the USA, Japan, South Africa, Ghana, Canada, France, Brazil, Korea, Cote D Ivoire, Angola, Russia, Gabon, Venezuela, Panama, China, United Kingdom, Namibia, Vanuatu, Guatemala, El Salvador and Honduras. The Indian Ocean Tuna Commission (IOTC) was established in 1993 through the Agreement Establishing the IOTC. There are 31 members of the IOTC. Some of the members are Australia, China, Comoros, EU, France, India, Indonesia, Japan, Kenya, Korea, Malaysia, the Philippines, South Africa, United Kingdom, Mauritius, Thailand, Seychelles, Pakistan and Tanzania. The cooperating non-contracting parties are Senegal and Liberia. In addition to the legally binding fisheries agreements and regional fisheries management measures, there are also non-binding voluntary instruments. However, these guidelines are for member countries to adopt based on their specific needs and capacities. These include the following: 1. 2.

FAO Code of Conduct for Responsible Fishing International Plan of Action (IPOA-IUU) • International Plan of Action for Reducing Incidental Catch of Seabirds in Longline fishing • International Plan of Action for Conservation and Management Measures (CMMs) of Sharks

5 Refer 6 Refer

to www.wcpfc.int. to https://www.iccat.es/Documents/SCRS/Manual/CH1/CH1-ENG.pdf#page=3.

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch

33

• International Plan of Action for Fishing Capacity. 3. 4.

FAO Voluntary Guidelines for Securing Small Scale Fisheries FAO Agreement on Port State Measures.

2.3 Overview of the State of Play of Fisheries Sector and Role of Subsidies In relation to fisheries subsidies and multilateral trade agreements of the WTO, the Agreement on Subsidies and Countervailing Measures (ASCM) provides some directions on disciplines in relation to fisheries subsidies. The agreement provides set criteria for the determination of subsidies and measures that the WTO members can take in the event of damage or injury incurred to its domestic industries due to subsidization. The agreement focuses on disciplines in relation to specific subsidies. The ASCM is not all-encompassing as other international multilateral agreements, and non-binding agreements also need to be considered in conjunction with the ASCM. However, the discussions on the disciplines on fisheries subsidies in all the proposals refer to the ASCM and target disciplines in relation to specific subsidies within the fisheries negotiations. The ASCM does not account for non-specific or horizontal subsidies which have the potential to distort the global market on fisheries access and prices. A similar analogy is observed in the current discussions on the agriculture subsidies which developing countries are still debating in terms of Green Box subsidies and trade-distorting effects (Sharma 2016). The fisheries sector operates through the interaction of different players, including fishing activity at sea, resource management, processing, production, and exports. As a result, it is imperative to understand how these stakeholders act in the fisheries market and the extent to which subsidies play a role in the social, economic, and environmental dimensions. An understanding of the interplay between the various players in the market is vital to understand the different positions which countries at the WTO are undertaking in the fisheries subsidies negotiations. To begin with, countries that own a large share of the exclusive economic zones (EEZ) where fishing activities take place are also considered to be holders or owners of the fisheries resources. These comprise coastal states which include small island states that are ocean-based economies and owners of EEZs.7 The EEZs are major fishing areas with fisheries resources that countries either use their vessels to fish or sell access rights through access agreements to distant water fishing nations. The Pacific Ocean comprises the largest portion of the fishing area (46.8%). This is followed by the Atlantic Ocean (21.8%), the Indian Ocean (16.7%), and the Southern Ocean (9.5%). Each of these fishing areas also has different types of fish species (Kumar et al.

7 The

exclusive economic zone (EEZ) comprises 200 nautical miles of water from coastal lines owned by countries.

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R. D. Kumar

2019). The Pacific Ocean comprises tuna and tuna-like species, while others such as the Indian Ocean consists of multispecies of fisheries resources (Table 2.1). The second group of players in the fisheries sector are those countries which are the owners of fishing vessels. These countries may not have their own fisheries resources, and thus they use these vessels for fishing in other’s territories (mostly EEZs) through fisheries access agreements. The fisheries access agreement provides access to fisheries resources from a coastal state (owner of the EEZ) to the partner countries (Refer to Annex 2.1). The European Union, including its individual member Table 2.1 Major fishing areas by region

Region

Major fishing area (sq. km)

Indian Ocean, Western 29,300,000 Indian Ocean, Eastern 31,100,000

Percentage 8.1 8.6

Total Indian Ocean

34,100,000

16.7

Pacific, Northwest

21,500,000

6.0

Pacific, Northeast

7,600,000

2.1

Pacific, Western Central

33,300,000

9.2

Pacific, Eastern Central

48,100,000

13.3

Pacific, Southwest

27,700,000

7.7

Pacific, Southeast

30,800,000

8.5

Total Pacific Ocean

169,000,000

46.8

Atlantic, Antarctic

11,800,000

3.3

Indian Ocean, Antarctic

12,700,000

3.5

Pacific, Antarctic

9,600,000

2.7

Total Southern Ocean

34,100,000

9.5

Arctic Sea

9,300,000

2.6

Atlantic, Northwest

6,300,000

1.7

Atlantic, Northeast

14,400,000

4.0

Atlantic, Western Central

14,500,000

4.0

Atlantic, Eastern Central

14,100,000

3.9

Mediterranean and Black Sea

3,000,000

0.8

Atlantic, Southwest

17,500,000

4.8

Atlantic, Southeast

18,300,000

5.1

Total Atlantic Ocean and adjacent seas

79,100,000

21.8

Source FAO database

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch Table 2.2 Fishing vessel capacity in gross tonnage

Country

Gross tonnage (metric tonnes)

European Union

1,549,742

Norway

393,785

Spain

331,778

United Kingdom

191,439

France

177,126

Iceland

154,079

Italy

146,260

Netherlands

120,509

Portugal

84,416

Denmark

74,426

Greece

71,104

35

Source Eurostats

states are among the largest owners of fishing vessel capacity in the world. In 2018, the total vessel capacity of the European Union in terms of gross tonnage was 15,497,42 metric tonnes. Norway, Spain, United Kingdom, France, Iceland, Italy, Netherlands, Portugal, Denmark, and Greece are among the highest holders of vessel capacity (Table 2.2). The producers of marine fish capture are the third major group of players in the fisheries sector. These are countries that have fish processing capacity and are major competitors in the fisheries global value chain. Table 2.3 shows the marine capture production in metric tonnes in 2018. The OECD member countries are major fish processors, followed by China, the least developed countries, Sub-Saharan Africa, European Union, India, Malaysia, and Canada. As such, it is evident that there is massive competition for fish and fish products (refer to Table 2.3). The current fisheries subsidies negotiation at the WTO aims to eliminate fisheries subsidies in relation to illegal, unreported, and unregulated fisheries (IUU), overfishing and overcapacity as per SDG 14.6. However, most of the developed member countries are focusing on the retention of the so-called “good subsidies” as exclusions by way of defining them as non-specific subsidies. For example, according to the OECD, the fisheries support includes direct revenue-enhancing subsidies and transfers that reduce operating costs and cost of general services provided to fishing services. These general services comprise fishing protection and fishing management services. It also includes other general services such as cost of local weather forecasting, cost of navigation, and satellite surveillance system designed to assist fishing fleet. The EU countries and those with large holders of vessel capacity by providing such subsidies to its fishing fleet provide an added advantage of cost reduction, gaining a further competitive edge. On the contrary, developing countries, constrained with financial resources and a small fisheries sector, would not be able to provide such subsidies and thus these carve-outs would only mean greater flexibility for the developed countries.

36 Table 2.3 Major fish capture producers (metric tonnes)

R. D. Kumar Countries

Capture fish production (Metric tonnes)

OECD members

23,224,057

China

17,800,000

Least developed countries: UN classification

9,196,983

Sub-Saharan Africa

7,225,986

Indonesia

6,584,419

European Union

5,264,083

India

5,082,332

Malaysia

1,584,371

Canada

874,727

Sri Lanka

521,637

Pacific island small states

500,654

New Zealand

424,791

Papua New Guinea

309,245

Cameroon

233,190

Australia

174,629

Fiji

44,663

Source World Bank Database

These general subsidies are not specific to the fisheries sector alone. In other words, this is similar to the Green Box subsidies in agriculture that have enabled the developed economies to boost the sector. A similar scenario is also being enacted in the fisheries subsidies negotiations. Table 2.4 shows the good subsidies defined by OECD, which includes fisheries subsidies consisting of general services such as fisheries protection services and fisheries management, local area weather forecasting, the cost of navigation and satellite surveillance systems designed to assist the fishing fleets. Fuel subsidies, which is one of the most controversial, are classified as general subsidies by the European Union as opposed to specific subsidies in developing countries. Table 2.4 clearly illustrates the differences in the value of fisheries support that are classified as horizontal subsidies or “good subsidies”. Countries such as China, Japan, USA, Canada, Norway, Australia, Korea, and New Zealand are the largest providers of these forms of subsidies, as opposed to developing countries and least developed economies. The least developed countries provide subsidies to sustain the food security and livelihood of low-income and resource-poor fishermen rather than for any commercial interests. In any case, should the WTO disciplines focus on eliminating specific subsidies, the developed countries will already have a considerable advantage in so far as competition is concerned.

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch Table 2.4 Good subsidies: horizontal subsidies excluded from fisheries subsidies disciplines

Countries

Fisheries support value (USD)

China

1,374,816,000

Japan

1,223,639,649

United States of America

803,372,987

Canada

675,526,486

Norway

214,533,338

Australia

109,265,821

Korea

90,849,833

New Zealand

37,358,961

Colombia

37,189,522

Argentina

35,497,291

OECD

17,866,180

Chile

17,410,102

India

10,411,000

United Kingdom

10,082,060

Cameroon

5,767,000

Fiji

4,258,000

Senegal

3,180,000

37

Source OECD Database and Sea Around us. Data for India, China, Papua New Guinea, Fiji, South Africa, Senegal and Cameroon sourced from the sea around for 2009. The data for the rest of the countries are for 2016–2017 sourced from the OECD database

2.3.1 Fisheries Subsidies in Developed Countries Most of the developed countries had been providers of fisheries subsidies which were specific in nature. For example for New Zealand, in the initial stages of its fisheries sector development, two policy instruments that were used by New Zealand to encourage the expansion of their domestic fleets into the EEZ included (1) package of financial incentives to the domestic industry including duty-free vessel importation, concessionary interest and suspensory loans, investment allowances and tax incentives and (2) joint ventures which enabled domestic fishing companies to acquire technology and expertise, gaining access to international markets and supplying on-shore processing facilities. The foreign partners contributed equity to the joint venture, provided capital for plant and equipment and assisted with access to international markets. The companies in New Zealand could charter foreign vessels, and these vessels were used to provide raw materials necessary to establish on-shore processing and distribution facilities. It was also recognized that the industry’s rapid expansion was largely attributable to joint ventures (Sharp 1997).

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R. D. Kumar

The USA in the 1960s8 had also provided substantial specific subsidies to the fisheries sector. The US government has transferred fishing equipment to the private sector, presumably at no cost. In addition, the USA implemented the Fishing Vessel Construction Differential Subsidy, and other subsidy programs were instituted to promote the expansion and modernization of the American fishing fleet. Starting in 1957, the Fisheries Loan Fund was used to encourage the expansion of the fishing fleet, through the refinancing of old debt or the creation of new debt for vessel construction. These programs evolved into the Fishing Vessel Obligation Guarantee and then the Fisheries Finance. The Vessel Mortgage Insurance program was established in 1960 to provide insurance for mortgages taken to finance fishing vessel construction. The recent data from 2019 shows that the European Union has a total number of 81,253 vessels, of which 69,480 are less than 12 meters in length with total gross tonnage of 174,778 and total engine power of 2,484,888 kW. The other 11,733 vessels have capacity of 1,376,141 gross tonnage and engine power of 3,589,310 kW.9 Furthermore in relation to subsidies, the European Union support included the five European Structural and Investment Funds that support the economic development of the EU till 2020. In that it has a total of 6.4 billion euros in allocation, with 5.7 billion being managed by the individual member states.10

2.4 Implications of WTO Fisheries Negotiations: Unbalanced Outcomes This section analyses some of the proposals which have been tabled at the WTO (details are given as Annex 2.2) and the pros and cons of the texts in the context of developmental agenda and the related policy implications for developing and least developed countries.

2.4.1 Scope of the Disciplines on Fisheries Subsidies Negotiations In relation to the scope of the fisheries subsidies negotiations, most of the proposals focus on Article 1 of the Agreement on Subsidies and Countervailing Measures (ASCM). In other words, the focus of the disciplines is on specific subsidies. The disciplines on specific subsidies for fisheries are mentioned in the proposals of 8 See

https://www.fao.org/docrep/006/Y4647E/y4647e06.htm.

9 https://ec.europa.eu/oceans-and-fisheries/facts-and-figures/facts-and-figures-common-fisheries-

policy/fishing-fleet_en# 10 https://ec.europa.eu/oceans-and-fisheries/facts-and-figures/facts-and-figures-common-fisheries-

policy/european-union-support_en

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39

Indonesia, the EU, the ACP, the LDC, Argentina, Columbia, Costa Rica, Panama, Peru, and Uruguay, including the new Chair’s text of fisheries subsidies of 2020. Aside from this, the scope of the fisheries subsidies disciplines is linked to certain applications of the ocean space, i.e., waters. The initial EU proposal is more stringent covering all waters, while the other proposals provide for some carve-outs. The EU proposal aims to prohibit subsidies which it has already phased out, such as subsidies that increase the marine fishing capacity, subsidies that support the construction of fishing vessels or the importation of fishing vessels, and subsidies for the creation of transfer of fishing vessels for joint venture and partnerships. The EU, through the reforms, has a well-maintained vessel capacity and has a domestic fishing sector which does not require the formation of joint ventures. As opposed to this, many developing countries have low vessel capacity and as highlighted earlier, they are small-scale producers but have the capacity to develop its fishing sector as most of these small states have major fishing areas, i.e., EEZ. As a result, through the EU proposal, greater flexibility will be granted to developed economies as opposed to the developing countries that are yet to develop their fisheries sector. On the other hand, the EU further included an illustrative list of subsidies which members can grant as an example of positive list. These are subsidies in the fisheries sector which EU is currently providing to its fishing industry. These include subsidies to improve fisheries management systems and thus promote sustainable fisheries for research and development activities, subsidies to improve health and safety of fishers, subsidies to improve/enhance the capacity to fight against IUU, and subsidies for the permanent cessation of fishing activities. For the EU, it has the financial capacity to provide such subsidies. However, the developing and LDCs, with small-scale fisheries sector and sustainable fish stocks, need to provide specific subsidies and also form joint venture and partnerships in order to develop their fisheries sector and also expand its fisheries value chain and processing. In other words, the EU proposal is largely aiming to impose its common fisheries policies on the developing countries without taking into account the extant situations and development needs. The ACP and LDC proposals carve-out inland fisheries, aquaculture, and fisheries in disputed waters. The LDC proposal, however, is more stringent in relation to the definitions of aquaculture and inland fisheries. The Indonesia proposal limits the scope of the disciplines to capture fisheries only. Members of the WTO have to negotiate the categories of subsidies that fall within the scope. However, despite the carve-outs, one of the major elements that the proposals are silent on is the nonspecific or horizontal subsidies. As illustrated in Table 2.4, most of the subsidies provided by the developed economies, including China, are horizontal subsidies which are classified as good subsidies (refer to Sakai et al. 2019). In other words, if the focus of the disciplines on fisheries subsidies are concentrated on specific subsidies, then the developed countries will gain by taking less or no commitments at all, given that they have undertaken the required fisheries subsidies reforms. On the contrary, developing countries such as India, which is one of the global players of fisheries production, will be compelled into reducing further the specific subsidies that are for food security and livelihood for the fisher folks. With the unprecedented

40

R. D. Kumar

economic shocks of COVID-19 pandemic, undertaking such rigorous disciplines will add to the existing economic downturn of developing countries.

2.4.2 Linking Fisheries Management and WTO Negotiations Another major debacle in the negotiations is the linkage of the disciplines on fisheries subsidies to stringent management measures. These stringent measures, as identified in the EU proposal in 2017, and also implicitly following into the new Chair’s text of 2020, would not only demise the developing countries’ fisheries sector but also some of the major developed economies such as the United Kingdom. For the United Kingdom, negotiations under the current ongoing Brexit deal aims to ensure that it takes control over its waters. However, in relation to management issues, it does not have the capacity to undertake management, i.e., patrolling for waters. (Economist, 2020). On the contrary, the European Union and other developed countries have huge vessel capacity and established management plans (both in terms of the number of vessels and the capacity to catch fish) and thus have the early first-mover advantage in relation to venturing into distant water fishing, i.e., into the EEZs of other countries. On the other hand, developing countries do not have the vessel capacity but have fisheries resources. The EU proposal states that developing and least developed countries may grant or maintain subsidies in relation to specific subsidies such as subsidies for marine fishing capacity, vessel construction, and joint venture formations if it meets the specific conditions in the proposal. These conditions include that vessel benefitting from the subsidy should not target fish stocks in overfished conditions. Furthermore, the targeted stock has to be managed on the basis of the best available science at the disposal of the concerned party. These findings have to be consistent with the conservation and cooperation obligations under the relevant international laws, as reflected in UNCLOS, conservation and management measures of competent RFMO(s)/(A)s, and generally accepted standards of conservation and management of fisheries resources. In addition, the subsiding member has to present a management plan for the fleet segment it intends to subsidize. The proposal further states that the management plan must contain information that ensures sustainable exploitation of the fish stock. As a result, it shall contain/include information on the stock, fishery, and the area to which it applies quantified projected fishing mortality rates indicate provisions on fishing vessel monitoring and systems for reporting data and catch in sufficient detail. In order for developing and least developed countries to meet these conditions, it will require the capacity to undertake scientific assessments first and foremost to show that the fish resources are managed at a sustainable level. The developing countries do not have the capacity to undertake such a stringent management assessment, and as a result, unable to apply the flexibility to develop its sector. The developing and LDC members will not be able to enhance their vessel capacities and form joint ventures if they do not meet the required conditions. The

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch

41

proposals relating to management measures are both binding and non-binding in nature in WTO, and the binding commitments must be complied. Many of the developing and LDCs will face more significant challenges in implementing the decisions at WTO. The countries will also face another challenge of discussing the same issues at two different multilateral forums. These stringent management measures are disguised restrictions to development of developing countries’ fisheries sector. In other words, it is similar to non-tariff measures. Furthermore, the EU proposal also aims to legally bind members into accepting voluntary fisheries conservation and management measures (Kumar et al. 2019). Another proposal that aims to open discussions beyond the WTO mandate into management measures is the Indonesian proposal. Despite the proposal focusing on special and differential treatment, it is conditioned on fish stock assessment and management measures. In order to manage fisheries resources sustainably, usually at the regional level institutions are set up to provide scientific advice through stock assessments for members to make decisions on either issuing of fisheries license to vessels or providing allocated days called vessel day scheme to fish in their exclusive economic zones. Most developing countries do not have the capacity to undertake such stock assessments. The Argentina, Columbia, Costa Rica, Panama, Peru, and Uruguay proposal defines overfishing subsidies as those that negatively affect the fish stock in overfished conditions. It defines a fish stock as overfished if the stock is at such low level that the mortality from fishing needs to be restricted to allow the stock to rebuild to a level that produces maximum sustainable yield (MSY) or alternative reference points (ARP). This should be based on the best scientific evidence available to the member within its jurisdiction or to the relevant RFMO. The definition of fish stock in overfished condition bases the proposal on cause and effect, with the determination of MSY or ARP are highly technical issues that are discussed and negotiated by members of the fisheries management organizations. The determinations of MSY and ARPs are used to develop CMMs. As such, members linking management to the fisheries disciplines are using the WTO as a forum to impose the management measures under a legally binding framework on all the members. Furthermore, in the context of the WTO, these measures do not take into account the full extent of the disproportionate burden on developing countries, in particular the least developed countries. Secondly, some of the management measures imposed in the RFMOs are for the high-seas jurisdiction. However, in the context of the WTO, some proponents have extended these to territorial waters and EEZ. The WTO also does not have the mandate on fisheries management or development of conservation and management measures.

2.4.3 Special and Differential Treatment Provisions The special and differential treatment provisions are integral in the fisheries subsidies negotiations. The proposals in the fisheries negotiations focus mainly on the

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R. D. Kumar

transition period for the implementation of the subsidies reform by members. Some proposals have also adopted a format similar to that of the trade facilitation agreement on declaring the capacity constraints and assistance needed to implement the fisheries disciplines. However, it should be noted that fisheries subsidies disciplines differ from trade facilitation, and thus the latter approach may not be practical for countries to follow. According to WT/COMTD/W/196, there is a six-fold typology to the special and differential treatment. These include (i) provisions aimed at increasing trade opportunities to developing country members, (ii) provisions under which WTO members should safeguard the interests of developing country members, (iii) flexibility of commitments of action, (iv) the use of policy instruments, (v) transitional time-period, and (vi) technical assistance and provisions in relation to LDC members. The fisheries proposal has limited the scope of the special and differential treatment to the transition period for implementation. On the other hand, the ACP proposal of 2017 had listed additional types of assistance, including assistance in relation to monitoring control and surveillance, research and development and technology transfer, among others. The initial LDC proposal of 2017 had carved out obligations for the LDCs in relation to the stringent fisheries subsidies disciplines. However, the proposal is detrimental as the stringent obligations apply to developing countries except for the LDCs. The LDC proposal further includes disciplines on small-scale fisheries which will affect many low-income and poor-resourced fisherman in developing countries. The LDCs need to reflect on the fact that most of the countries in the LDC category will be transitioning into developing countries in the next six years. It is therefore imperative for the LDC group to ensure that it is cognizant of their LDC transition and support disciplines which provide flexibility and policy space for the developing countries too. In the near future, as these LDCs will graduate into developing countries, they will have to take obligations they design in the agreement at present. The LDC proposal has linked the disciplines on fisheries subsidies to Article 61 and Article 62 commitments of the UNCLOS but has not balanced these with Article 202 on technical assistance to developing countries. As such, developing countries, including small island states, would be disadvantaged from the proposal of the LDCs. Similarly, the proposal from China (TN/RL/GEN/195), in relation to IUU has a special and differential treatment element. The provision, however, is not well placed for developing countries. The IUU measures cover all the fisheries, including small scale, artisanal, and subsistence fishing. Members are only provided a transitional period to adhere to the measures. This may be difficult for developing countries with small-scale fisheries that would require further assistance in implementing the provisions rather than transition periods. Through the WTO process of fisheries negotiations, the developed countries further aim to reduce the special and differential aspect of fisheries and at the same time expand on other commitments. The principle of special and differential treatment is embedded in other internationally legally binding instruments in relation to fisheries such as the UNCLOS and UN Fish Stock Agreement. The UN Fish Stocks Agreement, for instance, recognizes (i) the vulnerability of developing states which are dependent on the exploitation of living

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch

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marine resources, (ii) the need to avoid adverse impact and ensure access to fisheries by subsistent, small-scale, and artisanal fisheries, and (iii) the need to ensure that such measures do not result in transferring directly or indirectly, a disproportionate burden of conservation action upon developing states. Other non-legally binding agreements also have the recognized special and differential treatment (known as special requirements of developing countries). India has also submitted a recent proposal (TN/RL/GEN/200/Rev.1) in March 2020. In relation to IUU, on the issue of unregulated and unreported, the Indian proposal carves out coastal waters which include small-scale fisheries, and within the EEZ it excludes small-scale commercial fisheries in order to secure the livelihood of small-scale fishermen to an extent. On the issue of overfished stock, the subsidies are carved out for territorial waters. However, caution must be exercised on the compromise of the UNCLOS rights of member states to their EEZ in this situation. The Indian proposal has provided for a two-year period which may be feasible for India to undertake the stock assessment, but for small states it would be difficult given the capacity constraints of national authorities to undertake stock assessments. The Technical Assistance and Capacity Building Provision of the Indian proposal could be further expanded by integrating some of the specific areas of technical assistance from the ACP proposal (TN/RL/GEN/192). These include addressing institutional and financial difficulties as well as assistance to establish a reporting mechanism and regulation as well as assistance to conduct stock assessments, monitoring control and surveillance of fish stock, and research and development.

2.4.4 Cap-Based Approach: Replication of Agriculture Negotiations Imbalance Argentina, Australia, USA, and Uruguay, in their latest 2019 proposal TN/RL/GEN/197/Rev.2, have submitted a proposition for a cap-based approach to certain fisheries subsidies negotiations. A tiered approach on the amount/quantum of subsidies to be given is linked with the marine capture production. This is similar to the subsidies reduction commitments on the aggregate measurement of support (AMS) which developed countries have scheduled in the Agreement on Agriculture. Similarly, in fisheries, most developed countries already have vessel capacity and have shifted their subsidies to non-specific. As such, providing a cap of 50 million dollars will only benefit these developed countries. The marine capture production is not a good indicator alone to determine the subsidies cap. In approaching such measures, the developed countries are provided more flexibility than developing and least developed economies. As previously discussed, the developed countries are already providing non-specific subsidies, whereas developing countries do not have the capacity to provide fisheries subsidies. The developed countries under the

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cap-based approach will take minimum to no commitments at all, whereas the developing countries will commit to deeper cuts and will be challenged more on the socio-economics. Furthermore, looking into the modalities, members would only be required to provide up-to-date information on subsidies cap excluding the government expenditure on fisheries management and enforcement. The developed countries are already providing huge amounts of such subsidies. As such, the developed countries will gain further flexibility by continuing to provide such subsidies. On the other hand, the developing countries, including the LDCs even though they have major fisheries resources in their territories, need to develop vessels and equipment to tap into these resources. Without adequate financial resources to provide such subsidies, the developing countries, including the LDCs, will not be able to develop its fisheries sector. In other words, an imbalance in the market is created, providing an advantage to developed countries. The proposal provides further division of countries into different tiers for the reduction of specific subsidies. There are 26 WTO members in tier 1, which include China, Indonesia, EU, USA, Russia, Peru, India, Japan, Vietnam, Norway, Philippines, Chile, Malaysia, Korea, Morocco, Mexico, Thailand, Canada, Bangladesh, and South Africa. The tier 2 countries for subsidies reduction contain a total of 64 countries which include a mix of developed, developing, and least developed countries. These include Namibia, Brazil, Angola, Sri Lanka, Senegal, New Zealand, Nigeria, Pakistan, Papua New Guinea, Ghana, Cameroon, Australia, Fiji, and Kenya, among others. It again provides greater flexibility to developed countries. For New Zealand, as discussed earlier, it has already eliminated its fisheries subsidies and has undertaken the domestic sector reforms. Historically, New Zealand had provided specific subsidies. Reductions under tier 2 would again burden the developing countries to undertake deeper cuts. On the other hand, subsidies in the interest of developed countries are already carved out, and these countries can take a subsidies cap of 50 million dollars annually. On the other hand, developing and LDCs, due to resource capacity constraints, would not be investing such huge amounts per year in the fisheries sector.

2.4.5 Transparency and Notification Requirements Some of the proposals submitted by members in relation to fisheries subsidies relate to additional commitments to notify subsidies (refer to the European Union in document TN/RL/GEN/181/Rev.1, Argentina, Columbia, Costa Rica, Panama, Peru, and Uruguay in document TN/RL/GEN/187/Rev.2 and the LDC proposal in document TN/RL/GEN/193). The LDC proposal has taken carve out from notification for LDCs only, which means all other countries must notify their subsidies. As per the existing proposals, the following information will have to be provided by the WTO members including inter alia: (a) fleet capacity in the fishery for which the subsidy is provided; (b) vessels and operators fishing in areas beyond national jurisdiction, for which the subsidy is provided; (c) kind of subsidies provided and amounts granted; (d) program

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name; (e) legal authority for the program; (f) catch data, to the extent possible by species, in the fishery for which the subsidy is provided; (g) status of the fishery for which the subsidy is provided (e.g., overexploited, depleted, fully exploited, recovering, or underexploited); (h) conservation and management measures in place for the relevant fish stock; (i) total imports/export, to the extent possible per species. Information on fish stock, conservation, and management measures catch data are examples of fisheries management measures which is beyond WTO mandate and also places an additional burden on developing countries. It is worth noting that many of the developing countries, including small island countries, do not have resources or manpower to comply with such burdensome requirements. The notification requirements in the fisheries subsidies negotiations expand beyond Article 25.3 of the ASCM.

2.4.6 Dispute Settlement Measures and Fisheries Subsidies Negotiation One of the issues which members are yet to clarify how the agreements arrived under fisheries subsidies will be treated in the WTO dispute settlement mechanism. There are divergent views by members and clarity on this would depend on the scope and the obligations of the fisheries subsidies negotiations. In 2019, in document TN/RL/GEN/198, Canada had submitted a discussion paper for reflection on whether the DSU would need to be reviewed or not. This issue is yet to be settled. Given the wider/broader implications of the DSU, developing countries in the WTO negotiations need to be more vigilant on the scope and obligation and ensure that management measures are not legally binding on members which may be difficult/challenging to comply with in future and be subject to dispute settlement.

2.5 Conclusion The negotiation on fisheries subsidies disciplines at the WTO has been arduous given that a consensus of 164 members of WTO needs to be reached. Despite the momentum by negotiators to reach an agreement, many issues need to be successfully resolved. The proponents have projected the disciplines on fisheries subsidies as a sustainability concern, however, closer scrutiny reveals that this is majorly a market access issue. The proposals seem to be unbalanced and in favor of developed countries, like past cases negotiated in Uruguay round. The new Chair’s text of July 2020 is a consolidation of most of the contentious issues that prevailed since 2017. Binding rules on fisheries management have been enunciated under the UNCLOS, and the UN Fish Stocks Agreement but these rights are being compromised in the current negotiations. Members also need to exercise caution in ensuring that unilateral fisheries

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management disciplines are not inadvertently multilateralized imposing greater nontariff barriers on developing and least developed countries fisheries export. These are, in fact, complex issues; therefore, at the regional, sub-regional, and national levels the relevant management organizations collaborate in ensuring that fish resources are managed sustainably. Given that fish, unlike land resource, involves the issuance of fisheries access rights, as such, there is a sea of competition to access the resources at a reasonable price. The countries with a large fleet capacity would eventually be the ones bidding for the access rights to fish in the EEZ of developing countries. Given that this is the first time that fisheries subsidies would be disciplined, the aim should be to have a practical outcome rather than looking for an all-out result with inflexible conditions. The outcome must consider the aspirations of many of the smaller developing to enter the market and expand the sector for food security and livelihood. There needs to be some playing field with greater flexibility to address the challenges. Historically, countries such as the EU and New Zealand have been providing specific subsidies to develop their fleets and over time have shifted the specific subsidies into non-specific budgetary support. Should there be disciplines on specific subsidies alone, there would be an imbalance in the outcome. Secondly, entangling issues of management at the WTO are complicated, and countries need to be vigilant as IUU measures should not be a disguised restriction to international trade. Fisheries mechanisms are in place at the regional and national level in order to enable countries to address IUU fishing in a concerted manner. If States wish to strengthen the regime on fisheries management, they must negotiate the same in a forum outside the purview of the WTO. For example, in the WCPFC tuna commission, members negotiate the terms and conditions of various conservation and management measures taking into account the special requirements of developing countries. In the WTO fisheries subsidies negotiations, developing and least developed countries must ensure that these rights of RFMO members are not curtailed with uniform legally binding commitments, constraining the bargaining power of developing and least developed countries on management issues in RFMOs. In order to achieve an outcome on fisheries subsidies at the WTO, the focus must remain on the trade element, considering that countries are at different levels of development and subsidization, and there can be no one-size-fits-all approach to disciplining fisheries subsidies. Those countries that are yet to develop their fisheries sector need to be provided with an effective and implementable SDT provision. Transition period alone is insufficient for these economies to develop the sector. The special and differential treatment proposal can be enhanced by combining the recent 2020 proposal tabled by India and the 2017 ACP proposal. Another critical factor that the negotiators need to be vigilant about is to ensure that their rights and obligations under international fisheries treaties (UNCLOS and UN fish stock agreement) are retained. The rights under UNCLOS over the exclusive economic zones of developing countries were negotiated in order to ensure that a balance of power, fairness, and equity are provided to members at the global level. Compromising or giving up these rights or even renegotiating it under the special and differential treatment in the fisheries subsidies disciplines is step backwards in terms of developing countries giving up its already existing rights on marine resources.

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In addition, though the FAO guidelines on fisheries management are an important benchmark, they are nonetheless not a legally binding text. As a result, countries must ensure that such guidelines are used as a reference but not incorporated into the fisheries disciplines as a legal text. The decision to grant a legally binding status to the guidelines on fisheries management would require negotiation in the relevant forums outside of the WTO, with skills and expertise. Secondly, developing countries have a certain degree of flexibility in implementing these guidelines based on their level of development and their domestic policy objective choices. Imposing these guidelines in a legally binding form at the WTO would have repercussions for the development of the domestic fisheries sector of developing countries. For any successful outcomes in fisheries negotiations, the focus should be on special and differential treatment, which needs to be delinked from the complex issue of fisheries management, giving up of UNCLOS rights of coastal states, and adherence of stringent transparency measures. Given the global imbalance in the fisheries sector between the developed and developing nations, special and differential treatment is the key. The importance of special and differential treatment in the fisheries sector is even more paramount now given the economic losses which many developing and least developed countries are encountering as a result of the COVID-19 pandemic. In future proposals on fisheries subsidies negotiations, the effect of outbreaks and pandemics of such gravity should be accounted for in design and effect of fisheries provisions. The disciplines on fisheries subsidies have a market access agenda and a clear commercial interest of selected developed countries. Therefore, developing countries need to ensure that the history of the imbalance suffered from the disciplines on agriculture subsidies during the Uruguay round is not repeated in fisheries subsidies.

Annex 2.1 List of Fisheries Access Agreement for the European Union with Coastal States

Country

Expiry date

Type

Total EU Sectorial support per contribution per year year

Cabo Verde

Protocol provisionally entered into force on 20 May 2019

Comoros

Protocol expired on 31.12.2016. Agreement denounced

Cook Islands

13.10.2020

Tuna

385 000/350 000 e

350 000 e

Côte d’Ivoire

31.7.2024

Tuna

682 000 e

352 000 e (2yrs) 407 000 e

Gabon

Protocol expired on 23.07.2016 16 099 978 e

2 931 000 e

Greenland

31.12.2020

Guinea- Bissau

New protocol being negotiated, legislative procedures underway

Mixed

Kiribati

Protocol expired on 15.09.2015 (continued)

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R. D. Kumar

(continued) Country

Expiry date

Type

Total EU Sectorial support per contribution per year year

Liberia

8.12.2020

Tuna

715 000 e/ 650 000 e/ 585 000

357 500/ 325 000/ 292 500

Madagascar

Protocol expired on 31.12.2018

Mauritania

15.11.2019

Mixed

61 625 000 e

4 125 000 e

Mauritius

07.12.2021

Tuna

575 000 e

220 000 e

Micronesia

Protocol expired on 24.02.2010

Morocco

New Agreement and its implementing Protocol entered into force on 18 July 2019

Mozambique

Protocol expired on 31.01.2015

São Tomé and Principe

18.12.2024

Tuna

840 000 e

Senegal

19.11.2019

Tuna (+ hake component)

1 808 000/1 668 000 750 000 e e

Seychelles

17.1.2020

Tuna

5 350 000 e in 2 600 000 e 2014To 5 000 000 in 2019

440 000 e

Solomon Islands Protocol expired on 8.10.2012 The Gambia

30.7.2025

Tuna (+ hake component)

Equatorial Guinea

Protocol expired on 30.06.2001

550 000 e

Country

Period

Faeroe Islands

2006–2012

Norway

2009–2015

Source European Commission

Northern agreements

Annex 2.2 Summary of WTO Fisheries Subsidies Negotiation Proposals

275 000 e

Document

TN/RL/GEN/181/Rev.1 European Union

TN/RL/GEN/187/Rev.2 Argentina, Columbia, Costa Rica, Panama, Peru, and Uruguay

TN/RL/GEN/189/Rev.1 Indonesia

TN/RL/GEN/191 Norway

TN/RL/GEN/192 Africa, Caribbean, and Pacific (ACP)

Year

2017

2017

2017

2017

2017

Context

(continued)

The ACP proposal focuses on article 1 of the ASCM on specific subsidies. It, however, excludes inland fisheries, aquaculture and recreational fishing and claims for disputed waters. Additional exclusions include subsidies for disaster relief or safety, research and development, the sustainability of fish stocks, the acquisition and installation of equipment for vessels and crew safety, adoption of technology and improving compliance with fisheries management and climate change. The ACP proposal considers prohibited subsidies for IUU fishing. For overfishing and overcapacity, the prohibition is applied to large scale industrial fishing and fishing activity outside the EEZ. Thus, retaining members right under UNCLOS. For developing countries that hold fisheries resources, this is useful for it to develop its fisheries sector. On the other hand, for the developed countries that have maintained vessel capacity, such subsidies are to be prohibited. As such, the proposal aims to create a balance On the SDT for the ACP proposal, the disciplines on overfishing and overcapacity do not apply to LDCs. There is also a transitional period granted for small scale fisheries of developing countries to improve its reporting and regulation requirements. Moreover, the SDT proposal also provides for targeted technical assistance and capacity building to developing countries including LDCs and SVEs in addressing institutional and financial difficulties as well as assistance to establish a reporting mechanism and regulation as well assistance to conduct stock assessments, monitoring control and surveillance of fish stock and research and development On Transparency provisions, the ACP proposal on the notification is in accordance with GATT Article XVI of GATT 1994 and Article 25 of the ASCM. Additionally, the notification provision is specific to mentioning that confidential information, including confidential business information, should not be required for notification

Provision on the prohibition of subsidies for vessels engaged in IUU

Disciplines on Prohibitions and SDT Focuses on specific subsidies in the scope of disciplines however application limited to capture fisheries and excludes artisanal fisheries. However, has stringent conditions for developing countries to meet the special and differential treatment provisions by linking these to management measures of fish stock assessment and management plans

Provision on IUU, overfishing, overcapacity, transparency, and technical cooperation. Similar to the EU proposal the provision on overcapacity provides flexibility to already existing capacity holders. Mention of overfishing raising issues of fish stock assessment and linkages to fisheries management. The Transparency mechanism is beyond the existing requirements of the ASCM agreement, however, the focus on subsidies disciplines are only confined to specific subsidies

WTO disciplines on fisheries subsidies linked to SDG 14.4, disciplines on overcapacity and conditioning special and differential treatment on stringent management measures

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch 49

Document

TN/RL/GEN/193 LDC

TN/RL/GEN/195 China

TN/RL/GEN/196 Philippines

Year

2017

2017

2017

(continued) Context

(continued)

The proposals call for prohibition of subsidies in disputed waters. This is an issue that should be solved outside the WTO

China’s proposal focused on the prohibition of IUU fishing In the Preamble China has made a note of SDG 17.10, 14.6, the Doha and Hong Kong Ministerial Declaration and the IPOA-IUU The subsidies disciplines apply to the member country granting it and not necessarily the flag of the vessel The determination of IUU by flag member to be made in accordance with its domestic laws and regulations. In the event the flag state and the subsidizing states being different, countries would need to cooperate The determination of the IUU can be made by members through due procedure or by RFMO lists The investigation for IUU fishing activities to be undertaken jointly by the flag member with the relevant RFMO The procedure for the determination of IUU is clear and something which is applied in practice. The element of cooperation between the RFMOs is, however, vital for it to work The SDT provision for the China proposal is not strong. The IUU measures cover all the fisheries, including small scale, artisanal and subsistence farming. Members are only provided a transitional period to adhere to the measures. This may be difficult for developing countries with small scale fisheries that would require further targeted assistance aside from transition periods alone

The scope of the LDC proposal is similar to the ACP. It has excluded inland fisheries and aquaculture but provided for specific definitions for both inland fisheries and aquaculture which are limiting. The LDC proposal includes prohibition for capacity enhancing subsidies for vessel or operators engaged in illegal fish transhipment at sea; capacity enhancing subsidies supporting large scale fishing activities outside of the subsidizing member’s maritime jurisdiction. Subsidies for acquisition, construction, repair, renewal, renovation, modernization of fishing vessels, or any equipment that increases the ability of fishing vessels to fish and find fish. Subsidies for operating costs including licence fees or similar charges, fuel, ice, bait, personnel, social charges, insurance and at sea support, or operating losses of such vessels or activities The LDC proposal is imposing on developing countries and includes disciplines on small scale fisheries which will affect a large number of low income and poor resourced fisherman. However, the LDC proposal has carved LDCs from undertaking such commitments. On developing countries, the LDC proposal has linked it to article 61 and article 62 commitments of the UNCLOS as a condition for granting of subsidies but has not balanced these with Article 202 on technical assistance to developing countries On notification and transparency requirements the LDC proposal has carved obligation out for LDCS but is imposing notification requirements for article 25.3 of the ASCM which includes management measures on developing and developing countries alike and imposing limited flexibility to developing countries

50 R. D. Kumar

Document

TN/RL/GEN/197/Rev.2 Argentina, Australia, USA and Uruguay Argentina, Australia, USA, and Uruguay

Year

2019

(continued) Context

(continued)

These countries have submitted a proposal on a cap-based approach to certain fisheries subsidies negotiations. This is similar to the subsidies reduction commitments of the Agreement on Agriculture. A default cap of 50 million dollars would work in favour of developed countries. This is similar to the scenario of the Aggregate Measurement of Support which developed countries have scheduled in the agriculture subsidies. Similarly, in fisheries, most developed countries already have vessel capacity and have shifted their subsidies to non-specific. As such, providing a cap of 50 million will only benefit these developed countries further. Furthermore, looking into the modalities, members would only be required to provide up to date information on subsidies cap excluding the government expenditure on fisheries management and enforcement. The developed countries are already providing huge amounts of such subsidies gaining further flexibility by continuing to provide such subsidies. On the other hand, the developing countries including the LDCs though own major fisheries resources are yet to develop their sector and most do not have the capacity to provide such subsidies. In other words, an imbalance in the market is created, providing an advantage to developed countries. The proposal provides further division of countries into different tier for reduction of specific subsidies. There are 26 WTO members in tier 1 which include China, Indonesia, EU, USA, Russia, Peru, India, Japan, Vietnam, Norway, Philippines, Chile, Malaysia, Korea, Morocco, Mexico, Thailand, Canada, Bangladesh, and South Africa The marine capture production is not a good indicator alone to determine the subsidies cap. In approaching such measures, the developed countries are provided more flexibility then developing and least developed economies. As previously discussed, the developed countries are already providing non-specific subsidies, whereas developing countries do not have the capacity to provide fisheries subsidies. The developed countries under the cap-based approach will take minimum to no commitments at all, whereas the developing countries will commit to deeper cuts and be challenged more on socio-economics The Tier 2 countries for subsidies reduction contain a total of 64 countries which include a mix of developed, developing and least developed countries. These include Namibia, Brazil, Angola, Sri Lanka, Senegal, New Zealand, Nigeria, Pakistan, Papua New Guinea, Ghana, Cameroon, Australia, Fiji, and Kenya among others It again provides flexibility to developed countries. For New Zealand, as discussed earlier, it has already eliminated its fisheries subsidies and has undertaken the domestic sector reforms. Historically, New Zealand had provided specific subsidies. Reductions under tier 2 would again burden the developing countries to undertake deeper cuts. On the one hand, subsidies in the interest of developed countries are already carved out, and these countries can take a subsidies cap of 50million annually. On the other hand, developing and LDCs, due to resource capacities, would not be investing such huge amounts per year in the fisheries sector The technical assistance in this proposal is also conditional on the reduction of subsidies by tier 2 countries. The developed countries have already phased out specific subsidies and should it take a 50 million cap on subsidies then it would benefit them further. On the contrary, developing and LDCs may not be in a position to reduce subsidies and thus would not be able to benefit from technical assistance

2 Fisheries Negotiations at the WTO: Small Bait for Large Catch 51

TN/RL/GEN/198 Canada

TN/RL/GEN/200/Rev.1 India

2019

2020

Source Based on various proposals submitted by the members

Document

Year

(continued) Context

India has submitted an SDT proposal In relation to IUU, for unreported and unregulated fishing India has carved out coastal waters which includes small scale fisheries and also for EEZ it as excluded small scale commercial fisheries which is important for food security and livelihood for low income and poor resourced fishermen. There is alignment to the ACP proposal of 2017 to some extent In relation to overfished stock, it has carved out territorial waters. However, the proposal has compromised the UNCLOS rights of countries in their EEZ. The phasing out of subsidies with a transition period for 2 years may seem feasible for India, but for the rest of the small economies, it may not be feasible. Furthermore, the small economies would require capacity building to be able to undertake stock assessment On overfishing and overcapacity, LDCs are exempted from prohibiting subsidies. The subsidies prohibition in relation to overfishing and overcapacity also does not apply to fishing and fishing-related activities at sea and in their territorial waters. There are four criteria which a developing country must meet in order to prohibit subsidies in relation to overfishing and overcapacity. These include: (i) their GNI per capita crosses US$ 50003 (based on constant $2010) for three consecutive years; (ii) their individual share exceeds 2% of the annual global marine capture fish production as per most recent published FAO data; (iii) they engage in distant water fishing; (iv) the contribution from Agriculture, Forestry and Fishing in their national GDP5 is less than 10%for three consecutive years

This is a discussion paper on whether DSCU would need to be reviewed or not and how environmental recourse would be treated given the scope of the WTO agreement. Given that the WTO has a mandate on trade issues. The DSU also does not have the capacity to undertaken scientific evidence and management measures. For small economies, it will be even more challenging to invoke a claim given their capacity constraints

On notification, the burden of members notification is conditional to members who may want to benefit from the subsidies cap. These include all countries. However, the developed countries have the capacity to notify and benefit as opposed to developing countries

52 R. D. Kumar

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References Kumar, R. (2017). Fisheries subsidies negotiations at the WTO. Center for WTO Studies, New Delhi, India: The Real Catch. Kumar, R., Kumar, R. R., Stauvermann, P. J., & Chakradhar, J. (2019). The effectiveness of fisheries subsidies as a trade policy tool to achieving sustainable development goals at the WTO. Marine Policy, 100, 132–140. Sakai, Y., Yagi, N., & Sumaila, U. R. (2019). Fishery subsidies: The interaction between science and policy. Fisheries Science, 85, 439–447. https://doi.org/10.1007/s12562-019-01306-2. Sharma, S. K. (2016). The WTO and food security: Implications for developing countries. Singapore: Springer. Sharp, B. M. H. (1997). From regulated access to transferable harvesting rights: Policy insights from New Zealand. Marine Policy, 21(6), 501–517.

Chapter 3

Revisiting the Question of Price and Income Support to Agriculture C. Saratchand and Simin Akhter

Abstract A key issue in the foundation and subsequent evolution of the decisions on agricultural trade under the World Trade Organization (WTO) was the question of price and income support to agriculture. It is generally believed that income support, as opposed to price support, is less trade-distorting, which is also reflected in their classification under the Agreement on Agriculture (AoA). Price support is classified under the trade-distorting Amber box, whereas income support is covered by the provisions of the Green box that are considered as minimally trade-distorting. Most developing countries, however, tend to resort to price-support policies due to budgetary constraints and fiscal concerns. Any redistributive policies like the National Rural Employment Guarantee Program though found to be highly effective in bringing up wages and rural income are often critiqued domestically by neoliberals for the financial burden they allegedly place on the exchequer. This study seeks to engage with a particular aspect of critique of price-support policies that claim that income-support policies extended to farmers in developed countries do not distort prices and output. Though this proposition may be valid in a partial equilibrium perfectly competitive model, it is not necessarily valid in an oligopoly or a general equilibrium framework or a Keynesian/Kaleckian macroeconomic setting. Thus, this study makes a modest attempt to demonstrate that income-support measures, like price-support measures are also trade-distorting. Keywords Income support · Price support · Developing country · WTO

C. Saratchand (B) Satyawati College, University of Delhi, New Delhi, India e-mail: [email protected] S. Akhter Zakir Husain Delhi College, New Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_3

55

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C. Saratchand and S. Akhter

3.1 The Impact of Subsidies on Agricultural Incomes There are some key differences between small-scale, labour-intensive, capital-scarce, and technologically traditional peasant agriculture, as practiced in developing countries, and large-scale, capital-intensive corporate farming that needs to be kept in mind when analysing the impact of subsidies on agricultural prices. The impact of price and income support to agriculture has been a major foundational issue and an evolutionary edifice for the World Trade Organization (WTO). The ‘type’ of agricultural practice—commercial or subsistence—also has implications for the choice of technique, the scale of production, market bargaining power of the participants besides ecological and welfare-participation outcomes. As opposed to the developed countries where the agricultural sector is dominated by a few large corporations, agricultural-support policies in developing countries such as India also serve as anti-poverty programmes and thus need to be analysed with greater flexibility of consideration.1 The fact that in developing countries, a large number of small landholdings are under cultivation despite a large proportion of land being owned by a few big farmers, and also has implications for how both direct and indirect subsidies will impact prices in these countries vis-à-vis their corporate-dominated developed country counterparts. Legislations such as the Fiscal Responsibility and Budget Management Act (enacted in 2003) also make it more viable for governments in India to adopt pricesupport measures instead of income subsidies, as this act imposes limitations on the implementation of price-support measures.2 Since the agricultural population is itself differentiated, whatever price-support measures are implemented tend to have a differential impact on the two broad groups comprising of peasants and agricultural workers on one hand and big farmers and landlords on the other hand. Besides this, one also needs to investigate whether price and income support when taken separately have the same impact on fixed rent and share-cropping agriculture and seek to assess whether and how direct income support and price subsidies impact the market. Several studies have shown that under perfectly competitive market conditions, income support does not change market prices in partial equilibrium. However, Stiglitz et al. (2007) has demonstrated that income support raises the floor level of income for farmers, thus making them less risk-averse, thereby impacting their choice of technique and quantity produced which in turn impacts prices. Stiglitz et al. (2007) also argue that income support also tends to influence the choice of inputs, prodding farmers to choose inputs with lesser price volatility, which in fact acts to increase price volatility for other inputs, the use of which would have contained volatility in their respective prices. Since income support impacts both choice of inputs and quantity produced, it acts to increase output volatility, also causing greater price volatility. It is also demonstrated by Stiglitz et al. (2007) and 1 Patnaik

(2004) discusses at length the impact of procurement and price-support policies on rural incomes and relative poverty. 2 Singh et al. (2017) look at the various provisions of the act and critically evaluate the impact of each one of these on the relative income of different participants in each sector of the economy.

3 Revisiting the Question of Price and Income Support to Agriculture

57

Gupta (1980) that if output is constrained by the availability of funds, income support in enhancing quantity produced will also decrease the average cost under increasing returns to scale, thereby reducing prices. This paper argues that both income- and price-support measures distort markets. Section 3.1 presents a general context and Sect. 3.2 discusses simple microeconomic models to analyse how an income subsidy will impact equilibrium prices in the case of perfect competition and Cournot oligopoly in the agricultural sector. It is also shown by means of a simple discussion, how there is no difference between priceand income-support measures under general equilibrium in terms of their impact on prices and composition of the output vector. Section 3.3 demonstrates within the framework of a Keynesian/Kaleckian macroeconomic framework that an incomesupport measure is likely to change prices and output.3 In Sect. 3.4, an empirical exercise is undertaken to examine the temporal trend of agricultural prices in selected developed and developing countries to analyse trends in price volatility. The findings elucidate how the internal structure of agriculture has an impact on the effect of any agricultural-support measure on price and other variables, and the need for the Indian government to lead an effort to renegotiate the WTO classification of different support measures for agriculture including price and income support, public distribution system, public investment in agriculture and subsidized credit for farmers. Why an appropriate set of support measures must be devised for Indian farmers, most of whom are peasants as well as agricultural workers, is discussed subsequently. Section 3.5 concludes the paper.

3.2 A Perfectly Competitive Microeconomic Analysis of Price Versus Income Support Neoclassical theoretical assumptions4 imply that the impact of administered price changes, including price-support measures, extended to agriculture do not change the equilibrium price of the agricultural commodity if the relevant market is perfectly competitive. There could be three possible types of land: ‘cultivated land’, ‘cultivable land which is fallow’ and ‘other land’ which could be transformed into cultivable at some non-zero cost which need not be the same for all other lands. If the government now announces a fixed-income subsidy of F then all those other lands where the cost of making the land cultivable is less than or equal to F will now be made cultivable. If the fixed-income subsidy increases, then some more ‘other land’ will be made cultivable. However, the decision to actually cultivate the agricultural land will depend on the relation between market demand and the market supply of the agricultural land. 3 For

many primary commodities including many agricultural crops speculation often results in price volatility that is somewhat unrelated to changes in demand of actual users and supply of actual producers. 4 For a detailed discussion, refer to Varian (2004).

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For simplicity, it is assumed that the cost of actual cultivation is the same for all agricultural producers. Now the fixed-income subsidy does not influence the decision on whether to cultivate a plot of cultivable land since F by definition is paid irrespective of whether actual cultivation is undertaken. Let q denote agricultural output. The cost function of all agricultural producers, who are assumed to be identical, in a state of perfect competition is described as a cubic polynomial in output: C = aq 3 − bq 2 + cq

(3.1)

The marginal cost (MC) and average cost (AC) functions that correspond to this cost function are MC = 3aq 2 − 2bq + c

(3.2)

AC = aq 2 − bq + c

(3.3)

The profit of the agricultural producer may be expressed as follows: π = pq − aq 3 + bq 2 − cq

(3.4)

In a perfectly competitive equilibrium, the following conditions are satisfied: 1. The marginal cost of the agricultural producer must equal its price ( p), this being the condition for profit maximization of the individual agricultural producer: p − 3aq 2 + 2bq − c = 0

(3.5)

2. The average cost of the agricultural producer must equal its price ( p), this being the condition for no entry and no exit: p − aq 2 + bq − c = 0

(3.6)

3. Market demand (Q D ) must equal market supply (Q S ) for the agricultural commodity. Market demand is a decreasing function of price: Q D = e − gp

(3.7)

Market supply equals the product of the number of firms (n) and the per firm output: (3.8) Q S = nq Market equilibrium requires the equality of market demand and market supply: e − gp − nq = 0

(3.9)

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At the market equilibrium, output, price and the number of firms will be constant and their values will be b (3.10) q∗ = 2a 4ac − b2 4a   4ae − g 4ac − b2 ∗ n = 2b p∗ =

(3.11)

(3.12)

It is evident that the introduction of a fixed-income subsidy will not change equilibrium price, output or the number of firms since F conditions for an equilibrium of a perfectly competitive agriculture sector. Equilibrium profits remain zero before and after the introduction of the fixed-income subsidy. The actual number of plots of land which are cultivable may be greater than or equal to n ∗ . In a perfectly competitive agricultural sector, the relation between cultivable and cultivated land has no significance for equilibrium price and output. However, the assumption of perfect competition is not only empirically invalid but also logically questionable since there is no (imaginary Walrasian) auctioneer who changes prices in real economies while all agents remain price takers. Let it be assumed that the agricultural sector is characterized by Cournot oligopoly which is not far-fetched assumption to make when agribusiness has become significant.5 In the absence of the fixed-income subsidy, suppose two agricultural producers cultivate land whose output levels are x and y. In a Cournot oligopoly, in equilibrium, each agricultural producer will earn supernormal profits and hence none of them will leave their land fallow. The inverse market demand curve is p = g − hx − hy

(3.13)

For simplicity, it is assumed that the cost of production of both agricultural producers is the same and denoted by j. The expressions of profit of both agricultural producers are as follows: (3.14) πx = (g − hx − hy)x − j x π y = (g − hx − hy)y − j y

(3.15)

The first-order conditions for profit maximization of both agricultural producers are, respectively, dπx = −hy − 2hx − j + g = 0 (3.16) dx

5 Simple

(1983).

models of oligopoly such as those considered in this paper are discussed in Friedman

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dπ y = −2hy − hx − j + g = 0 dy

(3.17)

At the market equilibrium, output of both agricultural producers, market output (Q ∗∗ ) and price are as follows: g− j x ∗∗ = (3.18) 3h g− j 3h

(3.19)

2 (g − j) 3h

(3.20)

2j + g 3

(3.21)

y ∗∗ = Q ∗∗ = p ∗∗ =

The equilibrium profit of both agricultural producers which is the same is π ∗∗ =

2( j − g)2 9h

(3.22)

Now the government introduces a fixed-income subsidy of magnitude F for all cultivable land. As a result, let it be assumed that one more agricultural producer makes its land cultivable by incurring a cost N . Let the output produced by the third agricultural producer be denoted as z. The market inverse demand function would now become p = g − hx − hy − hz

(3.23)

The profit functions of all three agricultural producers are as follows: πx = (g − hx − hy − hz)x − j x

(3.24)

π y = (g − hx − hy − hz)y − j y

(3.25)

πz = (g − hx − hy − hz)y − j z

(3.26)

The first-order conditions for profit maximization of all three agricultural producers are, respectively, dπx = −hz − hy − 2hx − j + g = 0 (3.27) dx dπ y = −hz − 2hy − hx − j + g = 0 dy

(3.28)

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dπz = −2hz − hy − hx − j + g = 0 dz

(3.29)

At the market equilibrium, output of all three agricultural producers, market output and price are as follows: g− j x∗ = (3.30) 4h y∗ =

g− j 4h

(3.31)

z∗ =

g− j 4h

(3.32)

3 (g − j) 4h

(3.33)

3j + g 4

(3.34)

Q∗ = p∗ =

The equilibrium profit of all three agricultural producers which is the same is π∗ =

( j − g)2 16h

(3.35)

After the fixed-income subsidy, it is readily established that when compared to the pre-fixed income subsidy situation that 1. Equilibrium price is lower: p ∗ − p ∗∗ =

j −g 0 12h

(3.37)

2. Equilibrium market output is higher: Q ∗ − Q ∗∗ =

3. Equilibrium profit of each agricultural producer is lower if the fixed-income subsidy is excluded: 23( j − g)2 π ∗ − π ∗∗ = − 0 144h

(3.39)

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The third agricultural producer whose land became cultivable after the fixed-income subsidy will do so if ( j − g)2 F−N+ >0 (3.40) 16h If this condition is not satisfied then the third agricultural producer will not make its land cultivable. As previously mentioned in a Cournot oligopoly as long as supernormal profit can be made, no agricultural producer will leave its cultivable land fallow. Thus, in a Cournot oligopoly setting, a fixed-income subsidy to agricultural producers will have an impact on equilibrium output and price. Therefore, it not tenable to argue that a fixed-income subsidy does not change equilibrium prices and output.

3.3 A General Equilibrium Analysis of Price Versus Income Support In a general equilibrium setup, if a fixed-income subsidy in terms of some price numeraire is provided to all farmers based on landholding then this could change prices and output.6 To begin with, the fixed-income subsidy to farmers has to be financed by taxing others (non-farmers) in the economy. It is assumed for simplicity that there are two commodities which are consumed, namely, the agricultural and the industrial. However, the share of consumption expenditure on each of these two commodities need not be the same for farmers and non-farmers. If an amount H in terms of some price numeraire is transferred to farmers from non-farmers by the government then the market demand for both commodities will change. Let it be assumed for the sake of illustration that farmers spend a greater share of their consumption expenditure on the industrial commodity as compared to nonfarmers. Then a transfer to farmers from non-farmers that is effected by the government will increase the market demand for the industrial commodity and reduce the market demand for the industrial commodity. This will bring about changes in the prices and outputs of both commodities. Further the techniques of production need not be the same for both commodities. For instance, if the industrial commodity requires more labour and less land as compared to the agricultural commodity then an increase in market demand and output for the industrial commodity as a result of the government-induced transfer from non-farmers to farmers will result in changes in the wage rate and the rental rate of land. The scenario such as the one set out in the previous paragraphs will not change prices and the composition of the output vector if all individuals have the same consumer preferences and all commodities have the same technique of production. But this need not be the case in principle and certainly is not the case empirically. 6 Rude (2001)

has provided a detailed evaluation of green box subsidies in the framework of the WTO wherein a discussion of income-support measures is provided.

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In any simple general equilibrium model, there will be full employment of all resources before and after any parametric change. But it is possible that a parametric change could bring about changes in the composition of the output vector, changes in product prices and changes in factor prices. Changes in prices referred to here involve not only market prices but also equilibrium prices. It is therefore logically untenable to argue that a fixed-income subsidy to farmers will never change agricultural output and prices.

3.4 A Macroeconomic Examination of Price Versus Income Support A fundamental difference between a (Keynesian/Kaleckian) macroeconomic setup and a general equilibrium setup7 is that in the former there is no guarantee that there will be full employment of all resources even along a steady state (or equilibrium). Consider a two sector macroeconomic model with an agricultural and an industrial sector. The real wage rate is fixed at a magnitude that corresponds to subsistence with some positive level of unemployment in the economy. If a fixed-income subsidy is provided to farmers then they could either spend it or save it. In case they spend it, then the demand for either of the commodities or both will increase. An increase in the output of the industrial commodity will increase the degree of capacity utilization which may increase investment in the industrial sector. If the output of the agricultural commodity increases then new agricultural land may be brought under cultivation or the technique of production on some of the existing land may be altered. Both these factors will alter the share of rent in the value of agricultural output. These income distribution changes in the agricultural sector may have an additional impact on demand for and therefore output of both commodities. In case multiple techniques of production coexist in the production of both commodities, then changes in demand for either commodity will change the average cost of production of either commodity and therefore their prices. If the profit margin in the industrial sector depends on the degree of capacity utilization then an increase in output of that sector would lead to income distribution changes in that sector which may have an additional impact on demand for both commodities. In case the fixed-income subsidy provided to farmers is saved, this could take a number of forms. A part of that amount may be lent either for production or consumption to borrowers which will have an impact on the demand for both commodities. Alternatively, farmers could save a part of the fixed-income subsidy in institutions such as banks. Depending on the degree of capacity utilization and its expected trajectory in the future, banks may make their lending decisions. If there are some producers in either sector (but more likely in the industrial sector) who are credit constrained and credit worthy according to banks then such producers could increase 7 For

a detailed understanding of this issue, please refer to Blecker and Setterfield (2019).

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their investment on the basis of borrowing from banks. As discussed above, this in turn could alter prices and income distribution in certain circumstances. In other words, in a Keynesian/Kaleckian macroeconomic setup, where there is some unemployment of resources, a fixed-income subsidy to farmers may cause some changes in output and prices.

3.5 Empirical Trends in Price and Income This section briefly discusses empirical evidence on price and income support to farmers in both developed and developing countries. Data indicates that subsidy per hectare is not only much higher among developed countries, as opposed to developing countries but is so despite a much larger share of the total population being dependent on agriculture in the latter. For instance, according to Rude (2001), overall government support to agricultural producers was 17.6% of gross farm receipts per year in 2017–19 in the Organisation for Economic Co-operation and Development (OECD) countries. Rude (2001) goes on to point out that in the same period, overall government support to agricultural producers in the emerging economies was 8.5% of gross farm receipts per year. Not just this, developed nations, according to Schmitz et al. (2006), also hand out a disproportionately large share of total subsidy to large producers. The USA, for instance, hands out over 70% of all agricultural subsidies to large farmers of three crops—corn, soybeans and wheat; aggravating relative income inequality within agriculture, not just at the inter-country level, but also internally.

Table 3.1 Total producer support estimate for agriculture in the US $ million (developed and developing countries) 2000–2018 Regions 2000 2005 2010 2015 2018 OECD (34 countries) EU (28 countries) US Japan Korea Turkey Canada China Russia Brazil India

244950

269126

251889

222650

246687

87632

126375

104315

94928

110314

50881 52683 19402 9036 4352 9286 370 2728 −256

40772 43036 21971 14449 6358 33152 6409 5156 −24671

29269 52599 19545 24383 7148 115494 16209 9550 −57294

37386 32968 23253 15315 3971 228605 9042 3802 −7688

44308 41819 25418 8030 4199 206474 10005 2292 −28330

Source OECD (2019)

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Table 3.1 shows a much higher estimate of total support for agriculture in developed countries as compared to developing countries. The aggregate support to agriculture in Brazil, for instance, was as low as USD 2728 million while in the OECD (34 countries) and the US it was as high as USD 244950 million and 87632 million, respectively, in the year 2000. One can see that the difference persists, and even though OECD countries have not increased their aggregate support to agriculture significantly over the years, rising only to USD 246687 million in 2018, it continues to be as low as USD 2292 million for Brazil, indicating the extent to which the proverbial playing field is skewed. China too can be seen to have a high total agricultural-support estimate at USD 9286 million in 2000, which rose sharply to USD 206474 million in 2018. This is a critical contributing factor to any explanation of how China has managed to protect its agriculture despite mounting producer support pressure from the first world. A full evaluation of the impact of subsidies to agriculture, however, needs to consider a whole host of factors that encompass different aspects of the political economy of the contemporary world, including that of countries like China that have a more diffused distribution of both spatial and geographic ownership of agricultural assets. India can be seen to have a persistently negative gross transfer from consumers and taxpayers to producers8 within agriculture. This is explained by low overall incomes and policy-restricted support. This is despite a total budgetary package of Rs. 57,600 crores (USD 71.912 billion) for agriculture in 2018. This not only shows how inadequate the existing policy support is vis-à-vis developed nations but also why a high volume of both price- and income-support measures may be needed to boost income and consumption in agriculture. Developing countries, in general, tend to resort to price-support measures like the Minimum Support Price in India due to both budgetary constraints and domestic political considerations. Though found to be highly effective in raising rural wages, direct income transfer programmes like the National Rural Employment Guarantee programme are often critiqued by the neoliberals for allegedly putting a significant burden on the exchequer. The WTO itself, since it classifies price support as more distortionary, encourages income-support measures (usually preferred and found more viable by the developed nations). From a Keynesian/Kaleckian macroeconomic framework, it may be argued that an income subsidy to farmers (mainly agribusiness) in developed countries would allow them to undersell farmers in developing countries such as India. Arguably, agrarian distress that is manifested as protests, farmers’ suicides, inability to repay loans, etc. is at least partly connected to the adverse outcome of agricultural subsidies to farmers in developed countries on farmers in developing countries such as India. 8 Producer

support estimate by definition is gross transfer from direct and indirect tax revenue to producer subsidy within a sector. Since tax revenue is much lesser than producer subsidy transfers in the sector the sign carried by the variable is negative. It needs to be noted that the variable itself does not speak about who receives this subsidy within the sector and is thus silent about the income redistributive aspect of the tax/subsidy. There is thus a need for a ratio that looks at the share of the subsidy going to small/marginal versus large producers.

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3.6 Conclusion The paper has sought to demonstrate that no plausible and logical formulation of economic theory be it oligopoly, general equilibrium or Keynesian/Kaleckian macroeconomics allows one to advance the proposition that unlike price-support measures, income-support measures do not impact prices and output. The argument that pricesupport measures usually adopted by developing countries like India are more distortionary as opposed to income-support and risk-cover policies implemented by the developed nations thus stands challenged. Policy measures that seek to support agriculture in India must take into account that most Indian farmers are low income or resource poor and working as small peasants or agricultural workers. A minimum support price to crops thus needs to be supplemented by a public distribution system that is not based on targeting since a large part of the rural population are likely to be net buyers of food grains. Leaving aside all other advantages of the latter it is the case that such a measure would reduce the costs of storage and wastage due to poor storage facilities that afflict the current system of government support to agriculture. Besides, it would also enhance food security. However, the provision of agricultural price support and other related measures also needs to consider the ecological consequences of the cultivation of waterintensive crops such as rice, sugarcane, etc. on the one hand and conventional farming methods which employ high volumes of pesticides, fertilizers, etc. on the other hand. The highlighting of this problem is not an argument for cutting government support to agriculture (involving rice, wheat, etc.) since that would immediately impoverish peasants. What is being advocated here is a balanced transition to agro-ecological cultivation of crops such as millets apart from alternative agro-ecological methods of cultivating rice, wheat, etc. This would require not only public investment in agriculture and redistributive land reform but also the extension of price support to crops such as millets, incorporation of millets into the public distribution system, etc. The historical experience of most developing countries and communities seems to indicate that as their incomes rise, they seek to shift to a diet based on animal protein in analogy with lifestyles in the developed countries. This would require a rise in the output of food grains and fodder crops. This would require the Indian government to lead an effort to renegotiate the WTO classification of different support measures for agriculture including price and income support along with other measures that enhance the sector’s overall capacity to employ skilled labour, allow the adoption of appropriate technology, etc.

References Blecker, R. A., Setterfield, M. (2019). Heterodox macroeconomics: Models of demand, distribution and growth. Edward Elgar Publishing. Friedman, J. (1983). Oligopoly theory. Cambridge University Press.

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Gupta, G. S. (1980). Agricultural prices policy and farm incomes. Economic and Political Weekly, 15(39), A123–A131. OECD. (2019). Agricultural support estimates (Edition 2019). Organisation for Economic Cooperation and Development (OECD). https://www.oecd-ilibrary.org/content/data/dfc70665-en. OECD. (2020). Agricultural policy monitoring and evaluation 2020. Organisation for Economic Cooperation and Development (OECD), p. 200. https://www.oecd-ilibrary.org/content/publication/ 928181a8-en. Patnaik, U. (2004). The republic of hunger. In Social scientist, pp. 9–35. Rude, James. (2001). Under the green box: The WTO and farm subsidies. Journal of World Trade, 35, 1015–1033. Schmitz, A., Schmitz, T. G., & Rossi, F. (2006). Agricultural subsidies in developed countries: Impact on global welfare. Review of Agricultural Economics, 28(3), 416–425. Singh, C., Prasad, P. R., Sharma, K. K., et al. (2017). A review of the FRBM act. In IIM Bangalore Research Paper 550. Stiglitz, J., et al. (2007). Green box subsidies: A theoretical and empirical assessment. In United Nations Conference on Trade and Development, India. Varian, H. R. (2004). Microeconomic analysis. New York, London: WW Norton & Company.

Chapter 4

Transparency and WTO SPS Notifications: A Case Study of India Marcelo Alonso Valverde Arevalo and Walter Fernando Ibarra Davila

Abstract WTO members over the years have adopted various sanitary and phytosanitary (SPS) measures in order to protect the human, animal, and plant life. As tariff measures at the border have reduced, the trend for non-tariff measures (NTMs), including SPS and technical barriers to trade (TBT), has significantly increased. These NTMs are important as they also affect trade in agricultural goods. With respect to agriculture, the SPS measures applied need to be transparent and complete in order to assist exporters and importers with information. As a result, there is the need for enhanced transparency provisions to ensure more detailed and complete SPS notifications. Members of the WTO, therefore, will benefit from the examination of the completeness and quality-related test for SPS notifications to ensure smooth trade flow of agricultural products among countries. It is in this context that this study will examine the quality and related issues for SPS notifications for India. The findings of the study show that there have been considerable improvements in India’s quality of SPS notifications over the years, however, some areas need addressing to enhance quality even further. Keywords SPS measures · Non-tariff barriers · Transparency · Notifications

4.1 Introduction The WTO agreements cover a wide range of issues related to trade, such as agriculture, textiles, services, standards, food sanitation regulations, among others. These are governed by several key principles to make trade non-discriminatory, transparent, and predictable. In this regard, one way for the multilateral system to improve predictability is through transparency provisions, which stipulates that a country’s Disclaimer The views and opinions expressed in this article are those of the authors and do not necessarily reflect any official policy or position. M. A. Valverde Arevalo (B) · W. F. Ibarra Davila Ministry of Foreign Trade and Tourism, Lima, Peru e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_4

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policies and regulations affecting foreign trade should be clearly communicated to its trading partners. Transparency is a key provision in the WTO agreements which provides clarity and predictability on trade policies, and regulations of member countries. Given the steep increase in the incidence of non-tariff measures (NTM), the transparency provisions have assumed significant importance over the years. The NTMs are policy measures other than custom tariffs which comprise sanitary and phytosanitary (SPS) and technical barriers to trade (TBT) measures, among others. SPS measures are imposed by countries to protect human, animal, and plant life or health from additives, contaminants, toxins, or disease-causing organisms and pests rising from in foods, or feedstuffs (Annex A Para 1 of SPS agreement). On the other hand, TBT measures are related to technical regulations, standards, and conformity assessment procedures, such as labelling, marking, and packaging requirements. The SPS agreement has significant implications for trade in agricultural products as it balances international trade with the right of a member to protect human, animal, or plant life or health. Non-transparent and discriminatory SPS measures can adversely affect the export of agricultural goods. The transparency in the form of timely and detailed notifications of SPS measures has a significant and pivotal role in agricultural trade and for investors in the sector. WTO members are obligated to notify new or changed regulations at an early stage, providing members with the opportunity to discuss and comment, at least 60 days before a measure or regulation is finalized. The transparency provisions allow the stakeholders to prepare themselves in the light of proposed changes related to the SPS measures. The importance, relevance, and necessity of transparency provisions can also be understood from the rising numbers of SPS measures that were notified to the WTO by the members (Fig. 4.1). There are 16,489 SPS measures that have been initiated since 1995, and 3494 measures are in force in August 2020. The six WTO members who have submitted the most notifications since 1995 are the United States, Brazil, Canada, China, Japan, and the European Union, covering around 40% of total SPS measures notified to WTO.

Number of noƟficaƟons

1800 1600 1400 1200 1000 800 600 400 200 0

1995

2000

2005

2010

2015

2017

Years Corrigendum

Addendum

TranslaƟon supplement

Emergency noƟficaƟon

Regular noƟficaƟon

Fig. 4.1 Notifications submitted per year by WTO members (1995–2017). Source Compilation based on WTO SPS notifications

4 Transparency and WTO SPS Notifications: A Case Study of India

71

A detailed examination of SPS notifications over time reflects that the quality, details, and frequency of SPS notifications have improved. However, it is observed that many members are lagging in submitting complete and timely notifications. Downes (2012) stated that SPS notifications ‘provide little indication as to the extent of member’s commitment to transparency’. It was observed that the NTMs are considered diverse and less transparent, and thus create unnecessary obstacles for exporters (Josling and Robert 2011). From the private sector perspective, it is highlighted that the SPS measures are the most frequently used to obstruct or block trade. Ambiguity, inconsistency, and discriminatory behaviour in both information and enforcement of SPS regulations were the problems highlighted by businesses (ABAC 2016). In that study, 80% of business respondents considered that regulations were difficult, complex, and opaque to understand and implement. A study by Kallummal (2012) also highlights various problems associated with the SPS notifications such as (1) language barriers, (2) absence of harmonised system (HS) code in the notifications, (3) vagueness in the description of the objective of the notification, and (4) short time for comments. Similarly, UNESCAP1 (2015) recognized that the two main problems relating to the SPS notifications were information on the date of entry into force and the correct HS classification of products that will be affected by the notified measures. Information on the effective date of implementation is essential for businesses and traders to take actions that could allow them to be prepared for compliance. Similarly, having precise information on the product(s), on which the SPS measure is applied, is important to not only the exporters but also the importers and importing country’s customs and other agencies that regulate imports. Any ambiguity may lead to delay in clearance of consignments and thus will increase the cost. Therefore, a notification giving exact and precise details of measures can only ensure the quality of transparency and smooth flow of trade. There have been many discussions in the WTO on the quality of notifications submitted by WTO members. It has been frequently pointed out that the SPS measures were implemented without notifying to the WTO. Given that notifications are critical for regulatory governance and trade decisions, the non-notification or late notification of SPS measures has negatively impacted trade and created an environment of uncertainty. With the increasing importance of SPS measures in agricultural trade, it is important to examine the SPS notifications for transparency purposes. In this context, the study examines the quality of SPS notifications submitted by India over the years. India is a significant player in the agricultural trade with positive trade balance, and therefore, the quality of SPS notifications assumes significance for all the stakeholders. More precisely, this study examines how India has performed in its transparency obligations under the SPS agreement, measured through the SPS notifications.

1 United

Nations Economic and Social Commission for Asia and the Pacific.

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4.2 Methodology This study examines India’s regular SPS notifications to the WTO from the guiding document on G/SPS/7/Rev.3 from 2009 to 2017.2 These guidelines were developed in order to ‘assist members fulfil their transparency obligations under Article 7 and Annex B of the SPS Agreement regarding the notification of SPS regulations’. The guideline prescribes a format which consists of 13 elements in which detailed information relating to the SPS measure has to be notified. The study evaluates the completeness of India’s SPS notifications with reference to the 13 elements as prescribed under the WTO guidelines. Further, the quality of notification is measured by examining the depth of information provided for each of the elements. It is to be noted that India submitted a total of 141 regular notifications during 2009–2017. For this evaluation, two indices were developed in accordance with the WTO recommended procedures for implementing the transparency obligations of the SPS agreement (G/SPS/7/Rev.3) (WTO 2008): (i)

(ii)

Completeness of information: This index is evaluated if all the 13 elements as given in the WTO guidelines have been filled. A 100% completeness meant that all 13 elements were filled. Quality of information: This index examines if the information provided in a particular element provided in-depth description of the measure in terms of HS codes, date of entry into force, or other information prescribed by the guidelines for that element.

The details of how these above indices were developed and quantified in the analysis are given in Table 4.1. The quality and completeness index is calculated based on the simple average of the scores of the concern’s items in the SPS notifications. For the completeness index, the score of items 1 to 13 except for item 9 is considered. On the other hand, for the quality index, items 3, 5, 6, 8, and 11 to 13 have been considered. This is a qualitative analysis where each item has been given a score of 0 or 1. The methodology has certain limitations. For instance, this study assumes that each item has equal significance in the SPS notifications, which may differ for practical purposes.

4.3 Disaggregate Analysis of the SPS Notification In recent times especially since 2014, India has been actively notifying its SPS measures (Fig. 4.2). The number of SPS notifications by India has increased substantially, which reflect the importance given by the Indian government to disseminate the information about SPS measures. However, the question arises about the completeness and quality of India’s SPS notifications. As mentioned in the earlier section, 2 All notifications are public and could be found on the WTO SPS Information Management System

website (https://spsims.wto.org/).

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73

Table 4.1 Elements evaluated for the completeness and quality of India’s SPS notifications S. no

Item from the SPS notification

Element

Alternatives

1

1

Notifying member

India

2

2

Agency responsible for elaborating the notification

Not included

Included

3

3

Tariff item number(s) (HS)

Not included

Included

4

3

International Classification of Standards (ICS)

Not included

Included

5

3

Description of the products covered

Not included

Included

6

3

Inclusion of any abbreviation

Not included

Included

7

3

Clearness of the description of the products

Not clear

Clear

8

4

Inclusion of the geographical regions or countries likely to be affected by the notified regulation

Not included

Included

9

5

Title of the sanitary or phytosanitary regulation

Not included

Included

10

5

Page numbers of the notified Not included document

Included

11

5

Identification of language of Not included the sanitary or phytosanitary regulation

Included

12

5

Inclusion of a link to the sanitary or phytosanitary regulation draft document attached in PDF format

Not included

Included

13

5

Availability of the website link

No

Yes

14

6

The objective of the regulation is indicated

No

Yes

15

6

The probable effects on trade are described

No

Yes

16

6

There is an outline of the specific SPS measures that the regulation will apply

No

Yes

17

6

The impacts on exports can be clearly identified

No

Yes

0

1

(continued)

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M. A. Valverde Arevalo and W. F. Ibarra Davila

Table 4.1 (continued) S. no

Item from the SPS notification

Element

18

6

19

Alternatives 0

1

In general, the description allows the full understanding of the proposed regulation

No

Yes

6

Inclusion of any abbreviation

Not included

Included

20

7

Inclusion of the objective and rationale of the SPS measure

Not included

Included

21

8

Existence of a relevant international standard

Answer given

No answer

22

8

Conformance of the Answer given proposed regulation with the relevant international standard

No answer

23

8

The existing standard, guideline or recommendation is appropriate referred

No

Yes

24

10

The date, when the regulation is expected to be adopted, is presented

No

Yes

25

10

Date of adoption

dd/mm/year

dd/mm/year

26

10

The proposed date of publication of the definitive measure is presented

No

Yes

27

10

Date of publication

dd/mm/year

dd/mm/year

28

11

The proposed date of entry into force is presented

No

Yes

29

11

Date of entry into force

dd/mm/year

dd/mm/year

30

12

The final date for comments No is specified

Yes

31

12

Final date for comments

dd/mm/year

dd/mm/year

32

12

The agency or authority designated to handle comments is identified

No

Yes

33

12

There is specific information No of contact point in charge of handling comments

Yes

34

13

The agency or authority No where the texts are available is identified

Yes

(continued)

4 Transparency and WTO SPS Notifications: A Case Study of India

75

Table 4.1 (continued) S. no 35

Item from the SPS notification

Element

Alternatives

13

There is specific information No of contact point in charge of handling comments

0

1 Yes

Number of noƟficaƟons

Source Authors’ compilation based on the SPS notification format 40 35 30 25 20 15 10 5 0 1996

2000

2005

2010

2015

2017

Years Addenda emergency

Addenda regular

Emergency noƟficaƟon

Regular noƟficaƟon

Corrigenda regular

Fig. 4.2 Notifications submitted by India per year (1995–2017). Source Compilation based on WTO SPS notifications

these issues have been evaluated based on the guidelines given in WTO document number G/SPS/7/Rev.3. This document states that information contained in the notifications should be as complete as possible, and no section should be left blank. The following analysis is based on the examination of the notifications and analysis of the contents of 13 elements as given in Table 4.2.

4.3.1 Items 1 and 2: Member Notifying and Agency Responsible WTO members need to provide the information about the name of the government as well as the agency responsible for notifying the SPS measures under the items 1 and 2 of SPS notification format. India has been consistently providing information in these two areas. Different agencies such as the Food Safety and Standards Authority of India (FSSAI), Department of Agriculture Cooperation and Farmers Welfare, Ministry of Agriculture and Farmers Welfare and Department of Animal Husbandry, Dairy and Fisheries, Ministry of Agriculture are responsible for formulating India’s SPS regulations, which are notified by the Trade Policy Division, Department of

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Table 4.2 Item 3: Products covered Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009–2017

Completeness

Tariff item number(s) (HS) mentioned

0

2009–2017

Completeness

Description of the products

100.00

2009

Completeness

Inclusion of abbreviations

75.00

2010

Completeness

Inclusion of abbreviations

37.50

2011

Completeness

Inclusion of abbreviations

50.00

2012

Completeness

Inclusion of abbreviations

20.00

2013

Completeness

Inclusion of abbreviations

50.00

2014

Completeness

Inclusion of abbreviations

69.23

2015

Completeness

Inclusion of abbreviations

88.46

2016

Completeness

Inclusion of abbreviations

86.36

2017

Completeness

Inclusion of abbreviations

100.00

2009–2013

Quality

Clearness of description

0.00

2014

Quality

Clearness of description

53.85

2015

Quality

Clearness of description

46.15

2016

Quality

Clearness of description

47.73

2017

Quality

Clearness of description

51.35

Source Authors’ compilation

Commerce to the WTO. Looking at the SPS notifications made by the Government of India to WTO, it was observed that the compliance with these conditions was 100%.

4.3.2 Item 3: Products Covered The information given under this item has prime importance for the stakeholders as it deals with the products covered by the SPS measures and imperative for trading partners to understand the scope of the measure. The guidelines prescribe that members should provide information about the coverage of products in the form of HS chapter or heading or tariff number. In addition, ICS numbers should be provided, where applicable. Further, abbreviations should be avoided. A clear description is important for an understanding of the notification by delegations and translators. An examination of SPS notifications revealed that India neither included the tariff item numbers as per HS nomenclature nor the ICS numbers. However, so far as giving a description of products is concerned, India’s SPS notifications between 2009 and 2017 included the description of the products that are likely to be affected by the SPS measures. Through the years, more specific details of products were given in India’s

4 Transparency and WTO SPS Notifications: A Case Study of India

77

notifications, thus giving a better clarity on the product coverage. It may also be worth noting that between 2009 and 2013, notifications included broader descriptions such as ‘food in general’ or ‘plants’ etc. lacking specificity. As per the guidelines, the use of abbreviations in the notifications was observed to be declining over the years. It might also be recognised that in cases of SPS measures which apply across the board basis on agricultural products, processed food or plants, it may be difficult to give specific HS codes for all items covered. Thus, having HS codes in all notifications may be often difficult, but even an indication of the chapter under which the products are covered may be useful for the exporters as well as importing regulators. Products without HS codes and exact description of products also create room for discourse, which could increase the probability of trade disputes. It was seen that over the years, India’s notifications became more clearer in terms of description of the product, but HS codes were missing. For a country such as India, capacity development of the agencies involved in formulating SPS measures, including the customs officials, would be necessary to rectify this issue. However, these issues are not specific to India’s SPS notification, but the majority of WTO members do not provide the exact HS classification of the products covered by the measures (Kallummal 2012).

4.3.3 Item 4: Regions or Countries Likely to Be Affected The guidelines suggest that ‘the geographical regions or countries likely to be affected by the notified regulation should be identified to the extent relevant or practicable. Members are encouraged to be as specific as possible in identifying regions or countries likely to be affected’. The Indian SPS notifications compliance with this provision was 100%. This information enables transparency in understanding the countries/regions that may likely be affected, enabling exporters from such countries/regions to understand the conditions for exports to India.

4.3.4 Item 5: Title of SPS Regulation, Language, and Number of Pages of the Notified Document The guidelines suggest that a member should provide the (1) title of notified proposed or adopted SPS regulation, (2) number of pages in the notified document, (3) languages in which the notified document is available. Further, it is also suggested that if a translation of the whole document or its summary exists, it should be indicated in the notifications. In case, a member submits the text of the draft regulation or a summary or translation thereof in a portable document format (PDF) along with the notification, the WTO Secretariat will facilitate access to this text through a hyperlink in the notification format.

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Table 4.3 Item 5: Title, language, and number of pages of the notified document Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009–2017

Completeness

Tittle

100.00

2009–2017

Completeness

Number of pages

100.00

2009–2017

Completeness

Language

100.00

2009–2014

Completeness

Inclusion of a link

0.00

2015

Completeness

Inclusion of a link

3.85

2016

Completeness

Inclusion of a link

9.09

2017

Completeness

Inclusion of a link

0.00

2009–2014

Quality

Link performance

0.00

2015

Quality

Link performance

3.85

2016

Quality

Link performance

4.55

2017

Quality

Link performance

0.00

Source Authors’ compilation

During the entire period of examination, India complied with the guidelines by giving correct information about the title, number of pages, and the language in which the notified document is available (Table 4.3). However, regarding the source of the information, i.e., weblink address, it is found that the same is not provided. Only in some of the notifications from 2015 to 2017, the weblink was provided. A low level of compliance on the source of information, i.e., weblink is also from the fact that during earlier periods Indian system of notifications was not fully electronically automated, and thus the weblinks did not exist. Over the years, there have been some improvements in electronic reporting.

4.3.5 Item 6: Description of Content The description of the content is one of the most important aspects of transparency in the SPS notifications. It allows commercial partners to understand the scope of the notified measures. If the information provided by the member is too narrow or too general, it is unlikely that stakeholders will be able to identify the impact of the measure on trade. In almost all the notifications, the objective is easy to identify. It is worth mentioning that India has not included abbreviations in most of its notifications (Table 4.4). However, the information about the outline of regulation, description of the effect on trade, and the impact on trade is not satisfactorily. For instance, in less than 20% of the notifications, it is possible to understand its effects on trade. Moreover, only in 2014, in almost 30% of notifications, an outline of the specific measure was presented. In the rest of the years, the average is less than 15%. Additionally, in the notifications of 2015 and 2016, it was possible to identify probable impacts on

4 Transparency and WTO SPS Notifications: A Case Study of India

79

Table 4.4 Item 6: Description of content Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009–2013

Completeness

Inclusion of abbreviations

100.00

2014

Completeness

Inclusion of abbreviations

76.92

2015

Completeness

Inclusion of abbreviations

92.31

2016

Completeness

Inclusion of abbreviations

86.36

2017

Completeness

Inclusion of abbreviations

97.30

2009–2015

Quality

Objective of the regulation

100.00

2016

Quality

Objective of the regulation

95.45

2017

Quality

Objective of the regulation

94.59

2009–2013

Quality

Description of effects on trade

0.00

2014

Quality

Description of effects on trade

7.69

2015

Quality

Description of effects on trade

11.54

2016

Quality

Description of effects on trade

11.36

2017

Quality

Description of effects on trade

16.22

2009–2013

Quality

Outline of the SPS measure

0.00

2014

Quality

Outline of the SPS measure

30.77

2015

Quality

Outline of the SPS measure

3.85

2016

Quality

Outline of the SPS measure

13.64

2017

Quality

Outline of the SPS measure

5.41

2009–2014

Quality

Impact on exports

0.00

2015

Quality

Impact on exports

11.54

2016

Quality

Impact on exports

11.36

2017

Quality

Impact on exports

0.00 (continued)

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M. A. Valverde Arevalo and W. F. Ibarra Davila

Table 4.4 (continued) Year

Completeness/Quality

Elements required within the item

2009–2017

Quality

Understanding of the proposed measure

Level of accomplishment (%) 0.00

Source Authors’ compilation

exports for Indian trade partners. There is a need for improvement in this item for enhancing the completeness and quality of SPS notifications.

4.3.6 Item 7: Objective and Rationale The guideline prescribes that the objective of SPS measures should be clearly specified in relation to the protection of human health from food-borne risks; or protection of human health from plant- or animal-carried diseases; or protection of animal health from pests or diseases; or protection of animal health from contaminated feed; or protection of plant health from pests or diseases; or prevention of other damage from entry, establishment, or spread of pests. It was found that in all SPS notifications by India, the objectives and rationale were clearly mentioned, and thus the level of accomplishment was 100%. India had clearly specified the prescribed SPS measures in relation to the objectives.

4.3.7 Item 8: Existence of International Standard, Guidelines, or Recommendation In the notifications, it is also important to identify whether there is a relevant international standard applicable for such a measure or not. From Table 4.5, it is observed that this information was provided in the notifications of India. However, given the varying degree of conformance with international standards (indicated in percentages below), one can find that up to 2013, most of Indian SPS measures were based on national regulations. However, with the passage of time, India started adopting international standards for its SPS measures. It may also be noted that the WTO rules prescribe that if the SPS measures are based on international standards, they are not required to be notified to the WTO. Later, realising that it is important to make other members aware of adopting to international standards, WTO members were encouraged to notify even the international standards to WTO, which explains India’s higher level of notifications complying to this requirement.

4 Transparency and WTO SPS Notifications: A Case Study of India

81

Table 4.5 Item 8: Existence of international standard, guideline, or recommendation Year

Completeness/Quality

Elements required within the Level of accomplishment item (%)

2009–2017

Completeness

Existence of international standards

2009

Completeness

Conformance with international standards

25.00

2010–2013

Completeness

Conformance with international standards

14.29

2014

Completeness

Conformance with international standards

90.00

2015–2017

Completeness

Conformance with international standards

100.00

2009

Quality

Appropriate reference of the international standards

0.00

2010

Quality

Appropriate reference of the international standards

85.71

2011

Quality

Appropriate reference of the international standards

50.00

2012

Quality

Appropriate reference of the international standards

80.00

2013

Quality

Appropriate reference of the international standards

100.00

2014

Quality

Appropriate reference of the international standards

70.00

2015–2017

Quality

Appropriate reference of the international standards

100.00

100.00

Source Authors’ compilation

4.3.8 Item 9: Other Relevant Documents and Language(s) in Which These Are Available To improve the quality and effectiveness of the SPS notification, the guidelines recommend that following information and documents should be included in the reference: (a) publication where notice of the proposed regulation appears, including date and reference numbers; (b) proposal and basic document to which proposal refers, and the language(s) in which the notified documents and any summary of these are available; (c) publication in which proposal will appear when adopted, including websites. In 2010 and 2011, no information was provided in this section. In the rest of the years, India included information related to the official gazette and links to external webpages. Considering that the information presented in this item is diverse, it was not included for the indexes.

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Table 4.6 Item 10: Proposed date of adoption and of publication Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009

Completeness

Date of adoption or publication

75.00

2010

Completeness

Date of adoption or publication

62.50

2011

Completeness

Date of adoption or publication

100.00

2012

Completeness

Date of adoption or publication

60.00

2013

Completeness

Date of adoption or publication

50.00

2014

Completeness

Date of adoption or publication

15.38

2015

Completeness

Date of adoption or publication

7.69

2016

Completeness

Date of adoption or publication

18.18

2017

Completeness

Date of adoption or publication

8.11

Source Authors’ compilation

4.3.9 Item 10: Proposed Date of Adoption and of Publication This item specifies that the WTO member notifying the SPS measure must indicate the date for the adoption of the measure notified. The information provided by India on this issue has varied over the years. In the initial period, it showed a higher level of percentage on indicating the date of adoption or publication, with the year 2011 seeing 100% compliance (Table 4.6). However, over the years, the provision of information on this item has declined. A possible explanation for this could be the fact that from 2009 to 2012, the notifications may have included existing or advanced SPS measures which India was notifying. With the passage of time, these notifications may be about the proposed draft regulations, where the dates could not be indicated. Non-indication of dates brings tentativeness and thus may create a challenge for the importers, who are at the risk of paying the penalty or higher charges upon imports.

4.3.10 Item 11: Proposed Date of Entry into Force This information required under this item is similar to the item discussed above. The level of accomplishment, regarding the inclusion of a specific date of entry into force, has been decreasing since 2012 (Table 4.7). From 2015, more than 80% of

4 Transparency and WTO SPS Notifications: A Case Study of India

83

Table 4.7 Item 11: Proposed date of entry into force Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009

Completeness

Date of entry into force

2010

Completeness

Date of entry into force

62.50

2011

Completeness

Date of entry into force

100.00

2012

Completeness

Date of entry into force

60.00

2013

Completeness

Date of entry into force

50.00

2014

Completeness

Date of entry into force

46.15

2015

Completeness

Date of entry into force

11.54

2016

Completeness

Date of entry into force

13.64

2017

Completeness

Date of entry into force

13.51

2009–2013

Quality

Six months period

0.00

2014

Quality

Six months period

15.38

2015

Quality

Six months period

0.00

2016

Quality

Six months period

2.27

2017

Quality

Six months period

0.00

50.00

Source Authors’ compilation

notifications do not specify any information related to it. In many of the notifications, the six-month period for compliance was not given.

4.3.11 Item 12: Final Date for Comments and Agency or Authority Handling Comments The level of compliance in relation to the final date for comments by authorities is high. India has, in general, allowed 60 days for members to provide comments to the notifying measure and as allowed, in cases of trade facilitating SPS measures or if these measures were based on international standards the 60-day period was not given (Table 4.8). In the notifications, India has identified the FSSAI as national notification authority or National Enquiry Point for handling comments and provided details of additional contact points. With this information, it would be possible for interested stakeholders to easily communicate and transmit their comments or observations.

4.3.12 Item 13: Texts Available from Relevant Authorities For allowing a wider understanding of the notification, the WTO recommends providing the details of the authority with whom the SPS regulation is available. India

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Table 4.8 Item 12: Final date for comments and agency or authority handling comments Year

Completeness/Quality

Elements required within the item

Level of accomplishment (%)

2009–2017

Completeness

Identification of authority for handling comments

100.00

2009

Quality

Time for comments

25.00

2010

Quality

Time for comments

62.50

2011–2013

Quality

Time for comments

100.00

2014

Quality

Time for comments

92.31

2015

Quality

Time for comments

96.15

2016

Quality

Time for comments

100.00

2017

Quality

Time for comments

97.30

2009–2017

Quality

Additional contact information

100.00

Source Authors’ compilation

has always identified the National Notification Authority or the National Enquiry Point and the additional contact information to facilitate the communication with trade partners.

4.4 Trend in Quality and Completeness Indexes of India’s SPS Notifications After evaluating all the notification of India to the WTO during 2009–2017 based on guidelines prescribed by the WTO, quality and completeness indexes have been developed by taking the simple average of individual scores in each item. Figure 4.3 depicts the levels of completeness and quality of the Indian SPS notifications. It was found that with the passage of time, the quality of SPS notifications by India has improved. It seems that in the period analysed, the expertise and capacity of the Indian authority in charge of submitting these notifications have been enhanced. The quality index has reached almost 50% over the years. This number might not seem very high; however, it is indicative of the considerable improvement made in SPS notifications since 2009. The deeper analysis of quality index provides useful insights about the notifications. It is noted that item 6 has the least score followed by item 5 in terms of quality of notification. For this item, the guideline stipulates clearly stating the objective of the proposed measure, the description of the impacts that this measure might cause, the outline of the SPS measure, its impact on exports, and the incorporation of details that would allow stakeholders to understand the measure better. There is also lack of detail regarding the item 3 (clearness of description), which may pose challenges to the traders as well as various agencies that regulate imports as a lack of

4 Transparency and WTO SPS Notifications: A Case Study of India

85

100.00% 90.00%

86.11%

Percentage

80.56%

66.67%

64.00%

65.00%

37.35%

37.50%

40.00%

41.67%

2010

2011

2012

2013

76.49%

58.33%

60.83%

80.00% 70.00%

80.00%

79.17%

60.00% 50.00% 40.00% 30.00%

77.65%

77.90%

78.54%

78.83%

65.59%

65.90%

66.67%

66.13%

47.50%

47.76%

48.86%

47.07%

2014

2015

2016

2017

27.08%

20.00% 10.00% 0.00% 2009

Years Completeness

Quality

General evaluaƟon (All the factors)

Fig. 4.3 Notifications completeness and quality summary (in percentage). Source Compilation based on the study results

clarity in the description will always bring discretion and tentativeness. It would also be observed from low quality of item 11 (six-month period) that the lack of adequate time creates problems to not only exporters but also the domestic players as they will also have to comply with these regulations under the national treatment provision of WTO. However, in many items especially related to the objective of the regulation, appropriate reference to international standards, time for comments, among others, India’s performance is impressive. In terms of completeness, the value of the index is significantly higher than the quality index. The completeness index from 2009 to 2017 remains more or less stable with minor fluctuations. In many of items which have a significant impact on the completeness index, India’s notifications seem to comply with the guidelines. However, items related to giving HS codes, inclusions of weblink, among others, have a low rate of compliance. In general, though the quality of SPS notification has witnessed a considerable improvement, there is a scope to improve the information in some of the items to make these notifications effective and transparent.

4.5 Conclusion The quality and completeness of SPS notifications have an important bearing on the smooth functioning of international trade in agricultural goods. The notification of SPS measures is important for ensuring transparency and accountability and avoiding asymmetric information in the global trading markets. As the role of tariffs has considerably declined over the years, the use of NTMs, including SPS, has significantly increased. All the WTO members have adopted various SPS regulations to

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protect the life and health of human, animal, and plant. There is a need to balance the objective of SPS regulations with the free flow of agricultural trade. Therefore, the importance of transparency provisions in the form of detailed and complete SPS notifications play an important role. It is highlighted many times that members do not notify SPS measures to the WTO, which creates obstacles in predictable trade. Further, even if a member notifies SPS notification in a timely manner, the quality of information is not satisfactory. The absence or lack of credibility of information in the market also adds to additional cost at the firm level to exporters. In this context, there is a need to examine the SPS notifications for completeness and quality-related issue. Many developing, and the least developing countries are not able to provide timely and complete information due to various constraints. The challenge is also faced by many developed as well, who have failed to provide complete information about the product coverage and HS code. In this context, this study examines the SPS notifications of India for quality-related issues. For this purpose, item-wise analysis has been done as per the WTO guidelines. The issue highlighted in this study is not specific to India, but applicable for almost all the members of the WTO. Results show considerable improvement in the quality of India’s SPS notifications. However, there is still scope for increasing the quality and completeness of notifications for smooth international trade without compromising the health and life of humans, animals, and plants. As such, there is a need for technical assistance and capacity building for members to comply with the guidelines on SPS notifications. The Committee on SPS at the WTO needs to re-examine the needs of developing countries, including small vulnerable economies and least developed countries, and consolidate resources as well as build partnerships to provide such assistance. The WTO can only achieve enhanced transparency in SPS measures and avoid market failures in relation to information asymmetries if appropriate training and capacity building assistance are provided to the member countries.

References APEC Business Advisory Council (ABAC). (2016). Non-tariff barriers in agriculture and food trade in APEC. California: Marshall School of Business. Downes, C. (2012). The impact of WTO transparency rules: Is the 10,000th SPS notification a cause for celebration?-A case study of EU practice. Journal of International Economic Law, 15(2), 503–524. https://commerce.gov.in/InnerContent.aspx?Id=63. Accessed 10 Sept 2018. https://spsims.wto.org/. Accessed 5 Sept 2018. https://www.wto.org/. Accessed 18 Sept 2018. Josling, T., & Robert, D. (2011). Measuring the impact of SPS standards on market access. https:// www.oecd.org/tad/ntm/48632882.pdf. Accessed 15 Aug 2018. Kallummal, M. (2012). SPS measures and possible market access implications for agricultural trade in the doha round: An analysis of systemic issues. Asia-Pacific Research and Training Network on Trade (ARTNeT). No 11612.

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The United Nations Economic and Social Commission for Asia and the Pacific’s (UNESCAP). (2015). Trade and non-tariff measures: Impacts in the Asia-Pacific Region. Emerging Issues in Trade and Investment: Volume No. 1. https://www.unescap.org/sites/default/files/NTM%20Flag ship%20-%2025%20May.pdf. Accessed 15 Aug 2018. WTO Committee on Sanitary and, Phytosanitary, & Measures. (2008). Recommended procedures for implementing the transparency obligations of the SPS agreement (Article 7). Geneva: WTO.

Part II

FTAs and Indian Agriculture

Chapter 5

India–UK FTA: Export Prospects for Indian Agriculture Bibek Ray Chaudhuri and Debashis Chakraborty

Abstract In order to evaluate the impact of a likely India–UK FTA post-BREXIT on select Indian agricultural product exports, the current analysis has adopted a partial equilibrium approach. Since the average tariffs on agricultural products are quite low on an average, we have estimated the impact only for a zero-tariff scenario for all the agricultural items. As a departure from existing work, we have used the recently estimated import demand elasticities at six-digit HS level by Ghodsi et al. (Import Demand Elasticities Revisited. Vienna Institute for International Economic Studies, Vienna, 2016) in our user-defined SMART simulation analysis. In line with evidence from the literature involving north–south agri-trade reform in the presence of NTBs, not much changes are observed even at zero tariffs, and hence other scenarios of partial liberalisation were not attempted. Next, we tried to find out the reasons for low gains from full-tariff liberalisation. Five products were identified where a possible restriction due to NTBs might impact India’s export prospects to the UK. Applying the methodology outlined in Bradford (Rev Econ Stat 85:24–37, 2003), an estimate of NTB restrictiveness was obtained for the identified agricultural products. It corroborated with our initial apprehensions that not only were NTBs high but restrictiveness also went up over time. Hence if the proposed FTA does not address the issue of NTBs, even a full liberalisation in terms of tariffs will not lead to any substantial benefits for Indian agri-exports. Keywords India · EU · UK · FTA · Agricultural trade · Partial equilibrium · SMART · Tariff cut simulations · Non-tariff barriers

B. R. Chaudhuri (B) · D. Chakraborty Indian Institute of Foreign Trade, Kolkata Campus, West Bengal, India e-mail: [email protected] D. Chakraborty e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_5

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5.1 Introduction In light of the modest outcome of the WTO Doha Round negotiations, a number of member countries are increasingly focusing on regional trade agreements (RTAs) for promoting their exports. Several recent RTAs, having members both from developed and developing countries, are currently promoting intra-bloc trade by going beyond tariff reforms, e.g., through technical barriers to trade (TBT) harmonisation (McDaniels et al. 2018), introduction of trade facilitation measures (Neufeld 2014) and so on. While the positive influence of the RTAs on trade is generally reported in the literature, their repercussions on development are, however, still ambiguous (DiCaprio et al. 2018). India, a developing country, is no exception to this recent regionalisation drive. After the inception of WTO, India initially relied more on multilateral route for export promotion. However, the modest pace of reforms at the WTO forum caused the country to opt for RTA route since completion of the Cancun Ministerial (2003). Initially, India partnered the developing countries in the neighbourhood, namely through India-Sri Lanka Free Trade Agreement (2001) and South Asia Free Trade Area (SAFTA) (2006). The geographical coverage of India’s preferential trade partnership increased subsequently with the formation of India-Singapore Comprehensive Economic Cooperation Agreement (CECA) (2005), India-ASEAN FTA (2009), India-South Korea Comprehensive Economic Partnership Agreement (CEPA) (2010), India-Japan CEPA (2011) and India-Malaysia CECA (2011). India is presently engaged in a number of ongoing RTA negotiations both in Asia and beyond (e.g., India-GCC FTA, India-Peru FTA, India-Israel FTA, India-South African Customs Union PTA etc.). India’s penetration into ‘Eastern’ RTAs, however, has so far been modest owing to three reasons. First, a number of ASEAN countries retained some form of tariff protection against Indian exports, and effective market access enhancement has been limited (Prasad 2017). Second, China entered into FTAs with other East and Southeast Asian countries before India, thereby enjoying the early mover’s advantage (Chakraborty 2018). Third, the export basket of India and several ‘Eastern’ partners consists of labour-intensive low-tech products, making them competitors rather than natural partners (Chakraborty and Chakraborty 2017). All these underline the possible need to enter into RTAs with developed countries in Europe and America, where economic complementarities can be observed. The country’s participation in the ongoing negotiations for India-European Union FTA (starting in 2007), IndiaEuropean Free Trade Association FTA (2008), India-Canada Economic Partnership Agreement (2010), India-Eurasian Economic Union (2015) is an acknowledgement of this economic compulsion. Negotiations for the India–EU FTA, which is largest in scope among the ‘West’ RTAs, started a decade back. During the 1990s, the growing economic relations between EU and India was cemented through the EU–India Cooperation Agreement (1994), and subsequently through the periodic annual EU–India summits. The India–European Union FTA negotiations were launched in 2007. However, the

5 India–UK FTA: Export Prospects for Indian Agriculture

93

negotiations got delayed due to difference in perspective over multiple areas, e.g., addressing TRIPS-Plus provisions, application of Anti-Counterfeiting Trade Agreement (ACTA) provisions on India’s generic pharmaceutical products, the extent of bilateral tariff reforms (e.g., wine and spirits) and inclusion of products in the negative list, the stringency of technical standards (e.g., automobiles), handling agricultural subsidies and so on (Chaisse and Chakraborty 2014). A practical problem in reaching a common ground on India–EU FTA negotiations has been the involvement of 28 EU members, thereby making the process of incorporating the preferences of each negotiating partner a long and tedious one. Therefore, the Brexit referendum in 2016 provided India with a possible opportunity to enter into a bilateral RTA with United Kingdom (UK), subsequent to its departure from the bloc at a future date. The proposed FTA with the UK has generally been welcomed by business communities (FICCI 2016; McCole and Panjwani 2018). However, GTAP results indicate that India’s expected gains from the bilateral FTA with the UK might be modest, given the smaller size of the bloc as compared to EU (Roy and Mathur 2016). The SMART simulation results of Banga (2017) reported higher export growth for the UK, given the lower tariff level imposed by the country (as part of the EU customs union) vis-à-vis India on imports. It is expected that in the aftermath of Brexit, India can conclude the FTA negotiations with the UK with relative ease, given the involvement of only two countries. Now, the crucial question is whether the resulting tariff reform only through FTA would enhance India’s market access in agricultural products in the UK market considerably. India has already witnessed a modest rise in its market access in ASEAN, despite the tariff reforms as per reform schedule under the trade agreement, given the possible presence of non-tariff barriers (NTBs) (Chakraborty et al. 2019). The current analysis, therefore, intends to closely look into the possible impacts of future tariff liberalisation on India’s exports of select agricultural products through the proposed India–UK FTA. The paper is arranged along the following lines. The introduction is followed by a brief literature survey on the impacts of tariff reform on bilateral trade flows. The emerging pattern of India–UK bilateral trade in agricultural products is analysed next. Then through a simulation exercise, the impact of tariff reforms on select India’s agricultural exports to the UK is determined. In light of the obtained results, the NTBs in the UK on Indian exports are identified next. Finally, based on the findings, certain policy conclusions are drawn.

5.2 Impact of RTA Reforms on Agricultural Trade: Literature Survey A rich literature exists on the assessment of the impact of tariff reforms/preferences granted to the current and potential RTA partners on intra-bloc agricultural and primary trade flows. A section of the existing literature has analysed the intra-bloc agricultural trade growth through case studies. Covering select products traded within

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B. R. Chaudhuri and D. Chakraborty

the North American Free Trade Agreement (NAFTA) and Dominican RepublicCentral American Free Trade Agreement (DR-CAFTA), Shearer et al. (2009) noted the increase in market access after the bloc formation and the consequent agricultural trade growth. Several studies have analysed the agricultural trade reform question under the RTA route in a partial equilibrium framework, mostly through gravity modelling. The gravity analysis evidence in the Asian context usually has shown a positive effect of RTA reforms on agri-trade. Through a logit analysis conducted for estimating the propensity score matching, Lee and Lim (2015) have shown that the agricultural exports of South Korea in its RTAs generally demonstrate a positive effect. Ji and Yoo (2018) observed a significant change in agricultural import structure as a direct result of the preferences granted in South Korean FTAs. The positive effect of RTAs on agricultural trade in the Americas has been reported in several studies. Malhotra and Stoyanov (2008) have shown that Canada-Chile FTA (CCFTA) considerably enhances Chilean agricultural exports to Canada, though any significant change in its imports has not been observed. Analysing the effect of NAFTA on Mexican agricultural exports, Grassnick (2017) notes a positive effect. Through an analysis on NAFTA from US perspective, Johnson (2017) arrived at a similar conclusion for a wider range of agricultural products, namely meat and dairy products, grains, fruits, tree nuts, vegetables, oilseeds etc. In the European context, analysing Albania’s agricultural trade data with Central and East European countries, Hodo (2014) reported a positive influence of the FTAs on trade facilitation in general and agricultural trade flows in particular. EC (2017) noted that 72.7% of agricultural exports of the EU are delivered to other member states. A number of studies have attempted to analyse the effects of agricultural tariff reduction through RTAs in a cross-region framework. The gravity analysis of Korinek and Melatos (2009) has shown that intra-bloc agricultural trade has significantly increased under ASEAN Free Trade Agreement (AFTA), Common Market for Eastern and Southern Africa (COMESA) and the Southern Cone Common Market (MERCOSUR). The PPML estimation by Sun and Reed (2010) witnessed a similar result involving intra-bloc agricultural trade for ASEAN-China FTA, EU-15 and EU-25 member states, and Southern African Development Community (SADC). Through an intensive margin and triple-difference model involving multiple trade partners, EC (2016) demonstrates that EU’s exports to Mexico and Switzerland have increased primarily in processed food and beverages category, whereas its export growth to South Korea is explained by primary agricultural products. Another section of the literature has analysed the intra-bloc agricultural trade growth through general equilibrium models. The static and dynamic model simulation results of Kazutomo (2007) involving Japan’s existing and upcoming FTAs in a CGE framework report sizeable potential welfare gains in the agricultural sector. The CGE analysis of Jean and Bureau (2015), covering a multiple RTAs over 1998–2009, noted that the resulting trade preferences had enhanced intra-bloc agricultural and food exports by around 30–40%, apart from increasing the probability to intra-bloc trade as well. However, in the aftermath of the sub-prime crisis and global recession, the intra-bloc trade growth has declined. The CGE analysis of Bureau et al.

5 India–UK FTA: Export Prospects for Indian Agriculture

95

(2017) observed that while during 2001–2013 tariffs in agricultural and food products declined by 27.4%, the subsequent trade wars reduced agricultural trade growth to a modest level. The GTAP analysis by Songfeng et al. (undated) focused on the possible trade effects of an FTA between China and the USA and reported trade growth in several categories including soybeans, corn, food, alcohol and tobacco. While a significant part of the existing studies observes an increase in intra-bloc agricultural trade in the post-bloc period, the evidence to the contrary is not entirely scarce. Pasadilla (2006) noted the limited effect of the AFTA in promoting intraASEAN agriculture trade. The gravity analysis of Jongwattanakul (2014) involving Thailand indicates that signing an FTA is not a sufficient condition for opening up of a market. It depends crucially on the nature and structure of the bilateral trade between the partners. Bureau et al. (2017) have noted limited reforms in applied agricultural tariffs, despite the rise in the number of RTAs. Skewed benefits, given the difference in tariff bases across partners, have also been noted. The SMART simulation results by Renjini (2016) observed higher gains for ASEAN agricultural exports in the Indian market, owing to deeper tariff cuts on Indian imports. On the other hand, given pre-bloc lower tariffs imposed by ASEAN countries on India, the latter’s gain from the RTA has been limited. The modest intra-bloc agricultural trade performance, even after tariff reforms, can be partly explained by the existing non-tariff barriers (NTBs) on agricultural trade flows. Such NTBs can be classified under both sanitary and phytosanitary measures (SPS) and technical barriers to trade (TBT), which are generally more restrictive in the developed country markets. Beghin and Bureau (2001) underlined the significance of these SPS-TBT compliance requirements in lowering the competitiveness of agricultural exports. OECD (2017) noted the significant rise in trade costs owing to regulatory divergence. Kallummal and Gurung (2017) stressed the possible trade impacts of EU SPS-TBT restrictions under different scenarios. The possible distortions in north–south agricultural trade due to SPS-TBT and other barriers have been noted extensively in the literature. The analysis of Disdier et al. (2007) underlined that while SPS-TBT measures lower OECD imports, the effect is not significant for intra-OECD trade. Only imports from developing countries and least developed countries (LDCs) get negatively influenced by these measures. Deb (2006) observed that the agricultural exports of Bangladesh and Cambodia (both LDCs) face NTBs in both developed and developing countries in the form of stringent rules of origin (ROO) compliance requirements. The analysis recommended a reduction in ROO stringency level for ensuring smoother export flows. Several agricultural products exported by India have also been subjected to NTBs (APEDA 2008; GoI undated; Mehta 2005). Apart from standard-related barriers, agricultural trade in general and intra-bloc trade, in particular, is often restricted due to imposition of contingency measures, namely anti-dumping, subsidies and countervailing duties and safeguard measures. Fulponi et al. (2011) observed the imposition of safeguard and countervailing duties in intra-bloc trade flows. Analysing 26 RTAs spread across the globe, Viljoen (2016) observed that many of them contain specific provisions on bilateral or regional

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B. R. Chaudhuri and D. Chakraborty

safeguards on agricultural exports, with the coverage, scope, structure, and utilisation of such measures deepening over time. The paper recommended greater transparency and predictability, lowering product coverage for effective promotion of intra-bloc agricultural exports. Grassnicka (2017) indicated the protective effect of trade defence instruments on agricultural imports. As the paper primarily looks into India’s export opportunities in the UK after FTA formation and associated tariff reforms, the rise in the country’s agricultural imports in the post-reform period is not the focus area. A brief note on the same, however, would provide an interesting insight. After WTO’s inception, India removed the quantitative restrictions on imports, thereby canalising a number of items in the list. This led to a rise in imports of several primary products (Goldar 2005). It may be noted that while India has entered into a number of RTAs, the agricultural tariff preferences granted by the country to partners (e.g., ASEAN, SAFTA-LDC, SAFTA-Non-LDC, Unilateral Tariff Preference for LDCs, Korea, Japan) retain the flexibility to impose a relatively higher tariff for several categories. The applied rate with respect to the aforesaid partners is fairly high for a number of agricultural products (GoI 2017). The competitiveness concerns, particularly for certain sectors, however, remain relevant. For instance, the SMART analysis of Mondal et al. (2012) on dairy products indicates that India’s tariff preferences to ASEAN may result in modest threat for local players. On the other hand, analysing the reform initiatives and import trends in India, Chand and Bajar (2012) raised concerns over the inherent lack of competitiveness in certain sectors. The current analysis contributes to the existing literature in the following manner. First, the SMART simulations are run in the current context by utilising the userdefined module. Second, latest estimates of import demand elasticities at six-digit HS level have been used to analyse the impact of tariff liberalisation under the proposed India–UK FTA, following Ghodsi et al. (2016). Further, we have only concentrated on the prospects of Indian agricultural exports to the UK market. Finally, the paper also undertakes a deeper analysis by focusing into the possible causes of the observed meagre benefits from the anticipated tariff liberalisation, namely the presence of NTBs.

5.3 India–UK Bilateral Trade Flows in Agricultural Products Figure 5.1 depicts the Indo-UK bilateral trade scenario in agricultural products. It is observed that India’s exports to the UK over 2003–2017 have increased from US$ 0.34 to US$ 0.85 billion, while the corresponding figures for imports have been US$ 0.03 and US$ 0.24 billion in that order. The linear trend of trade growth underlines the gradually deepening trade relations between the partners. Table 5.1 shows the importance of the UK in India’s both-way overall trade in agricultural products over 2003–2017. For understanding the evolving trade pattern,

5 India–UK FTA: Export Prospects for Indian Agriculture

97

0.90 0.80

X

M

0.70 0.60 0.50 0.40 0.30 0.20 0.10 2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

0.00

Fig. 5.1 India–UK bilateral trade flows in agricultural products (in USD billions). Source Constructed by authors from WITS data

the period is divided into three sub-periods, namely 2003–2007, 2008–2012 and 2013–2017. Fluctuating or declining trend is observed for several categories in both exports and imports. Major Indian export items to the UK include product groups like: live tree and plants (HS 6), edible vegetables (HS 7), edible fruit and nuts (HS 8), coffee, tea, spices (HS 9), preparations of cereal, flour etc. (HS 19) and preparations of vegetable, fruit, nuts (HS 20). The imports from the UK, on the other hand, are concentrated in the following categories: live animals (HS 1), meat products (HS 2), marine and fish products (HS 3), dairy products (HS 4), products of milling industry, malt etc. (HS 11), preparations of cereal, flour etc. (HS 19) and beverages, spirits and vinegar (HS 22). Table 5.2 shows the importance of India in UK’s both-way overall trade in agricultural products over 2003–2017. Interestingly, India is presently not a major market in UK’s export basket (judged by market share above 1% in global trade), barring the exception of beverages, spirits and vinegar (HS 22). On the other hand, India’s presence in UK imports is significant for product groups like marine and fish products (HS 3), coffee, tea, spices (HS 9), cereals (HS 10), Lac, gums, resins etc. (HS 13), vegetable plaiting materials (HS 14) and cotton (HS 52). Tables 5.3 and 5.4 show the average applied tariff (AHS) imposed by India on the UK and EU on India, respectively. The comparison of the two tables reiterates the conclusion drawn by Banga (2017) that EU (and in turn UK, part of the EU customs union) impose a lower tariff on agricultural products vis-à-vis India. It is observed from Table 5.3 that only for edible fruit and nuts (HS 8), cereals (HS 10) and cotton (HS 52) significant imports from the UK enter India through the duty-free channel. Table 5.4 shows that the EU currently imposes a relatively higher tariff on Indian exports in case of meat products (HS 2), marine and fish products (HS 3), dairy

Oil seeds

Lac, gums, resins etc

Vegetable plaiting materials

Animal of vegetable fats and oils

Preparations of meat, fish or crustaceans

Sugars and sugar confectionery

Cocoa and cocoa preparations

Preparations of cereal, flour etc

Preparations of vegetable, fruit, nuts

14

15

16

17

18

19

20

Edible fruit and nuts

8

13

Edible vegetables

7

12

Live tree and plants

6

Products of milling industry, malt etc

Animal products

5

11

Dairy products

4

Coffee, tea, spices

Marine and fish Products

3

Cereals

Meat products

2

10

Live animals

1

9

Product description

HS code

7.822

16.633

7.373

1.156

3.770

2.621

1.424

2.573

2.904

5.142

3.006

7.463

6.443

3.435

9.582

5.858

0.301

5.397

0.036

8.536

10.948

2.330

0.469

2.908

2.722

1.126

1.121

2.000

4.290

2.132

6.164

4.744

3.041

11.802

3.498

0.466

3.642

0.024

0.034

9.394

6.637

0.246

0.615

3.666

2.238

2.254

1.382

1.339

3.283

2.029

4.547

4.322

4.374

11.887

1.111

0.063

2.756

0.000

0.046

1.224

2.527

3.677

0.850

1.806

0.036

0.131

0.630

0.370

4.979

0.029

0.759

0.041

0.011

0.108

0.882

5.817

2.696

2.212

10.935

2003–2007

0.390

Share in imports 2013–2017

2003–2007

2008–2012

Share in exports

Table 5.1 Importance of the United Kingdom in India’s agricultural trade flows (in %)

1.299

3.928

2.619

0.414

0.496

0.106

0.095

0.760

0.306

3.910

0.178

0.339

0.045

0.077

1.224

0.507

1.327

1.300

1.272

8.851

2008–2012

(continued)

0.924

3.910

0.888

0.109

1.977

0.009

0.058

0.278

0.048

3.013

0.039

0.038

0.003

0.001

2.091

0.373

4.932

3.046

3.834

18.862

2013–2017

98 B. R. Chaudhuri and D. Chakraborty

Miscellaneous edible preparations

Beverages, spirits and vinegar

Food residues and waste

Tobacco products

Cotton

21

22

23

24

52

Source Constructed by authors from WITS data

WTO Agriculture

Product description

HS code

Table 5.1 (continued)

0.540 2.207

3.346

2.882

0.111

0.503

1.457

4.720

0.118

1.380

3.214

2.010

0.369

1.065

0.455

0.497

2.692

0.893

0.282

16.755

3.109

25.163

3.677

2003–2007

4.487

Share in imports 2013–2017

2003–2007

2008–2012

Share in exports

1.021

0.204

4.314

2.721

35.083

2.705

2008–2012

1.088

0.082

1.115

0.982

37.529

2.622

2013–2017

5 India–UK FTA: Export Prospects for Indian Agriculture 99

Oil seeds

Lac, gums, resins etc

Vegetable plaiting materials

Animal of vegetable fats and oils

Preparations of meat, fish or crustaceans

Sugars and sugar confectionery

Cocoa and cocoa preparations

Preparations of cereal, flour etc

Preparations of vegetable, fruit, nuts

14

15

16

17

18

19

20

Edible fruit and nuts

8

13

Edible vegetables

7

12

Live tree and plants

6

Products of milling industry, malt etc

Animal products

5

11

Dairy Products

4

Coffee, tea, spices

Marine and fish Products

3

Cereals

Meat products

2

10

Live animals

1

9

Product description

HS Code

0.187

0.039

0.083

0.121

0.099

0.182

3.589

0.529

0.256

0.297

0.003

0.223

0.031

0.086

0.013

0.465

0.074

0.044

0.009

0.513

0.115

0.076

0.234

0.042

0.218

3.810

0.561

0.080

0.260

0.026

0.356

0.072

0.049

0.237

0.169

0.118

0.070

0.002

0.494

0.317

0.126

0.041

0.141

0.017

0.160

0.302

0.405

0.105

0.430

0.002

0.191

0.025

0.016

0.411

0.174

0.107

0.213

0.005

0.299

1.339

0.291

0.060

0.424

0.094

0.653

9.781

4.594

2.649

0.817

12.975

10.052

1.319

0.469

0.194

2.446

0.025

4.062

0.000

0.000

2003–2007

0.145

Share in Imports 2013–2017

2003–2007

2008–2012

Share in exports

Table 5.2 Importance of India in United Kingdom’s agricultural trade flows (in %)

1.627

0.513

0.076

0.977

0.105

1.106

2.689

7.329

2.794

1.153

12.135

9.286

1.140

0.883

0.322

2.471

0.075

3.894

0.000

0.001

2008–2012

(continued)

2.021

0.353

0.014

0.833

0.295

1.114

7.117

7.500

2.347

2.055

10.406

8.352

1.137

1.105

0.308

1.018

0.001

5.039

0.000

0.001

2013–2017

100 B. R. Chaudhuri and D. Chakraborty

Miscellaneous edible preparations

Beverages, spirits and vinegar

Food residues and waste

Tobacco products

Cotton

21

22

23

24

52

Source Constructed by authors from WITS data

WTO Agriculture

Product description

HS Code

Table 5.2 (continued)

0.377 0.404

0.349

0.076

0.608

0.762

0.289

0.096

0.594

0.637

0.124

0.608

0.462

0.075

0.549

1.325

0.154

0.939

8.946

3.717

0.113

0.014

0.390

2003–2007

0.106

Share in Imports 2013–2017

2003–2007

2008–2012

Share in exports

1.149

10.187

3.348

0.132

0.009

0.710

2008–2012

1.119

8.297

2.215

0.291

0.021

0.650

2013–2017

5 India–UK FTA: Export Prospects for Indian Agriculture 101

Oil seeds

Lac, gums, resins etc

Vegetable plaiting materials

Animal of vegetable fats and oils

Preparations of meat, fish or crustaceans

Sugars and sugar confectionery

13

14

15

16

17

Edible fruit and nuts

8

12

Edible vegetables

7

Products of milling industry, malt etc

Live tree and plants

6

11

Animal products

5

Coffee, tea, spices

Dairy products

4

Cereals

Marine and fish Products

3

10

Meat products

2

9

Live animals

1

HS code Product description

Weighted average

Free import as % of Total import

44.20

30.00

51.14

30.00

29.57

25.80

30.44

0.00

72.45

34.30

30.00

31.67

30.00

35.79

30.00

38.75

30.00

36.61

30.00

24.98

30.00

26.56

19.84

29.33

14.00

70.72

29.44

30.30

24.42

27.94

35.82

28.89

24.00

28.50

36.75

37.00

29.42

30.00

28.61

18.63

31.83

23.33

66.53

40.17

30.00

5.00

29.58

38.72

30.00

30.00

30.00

42.00

30.00

33.78

30.00

29.77

27.01

30.03

0.00

97.80

33.18

30.00

41.17

30.00

39.99

30.00

31.64

30.00

40.71

30.00

22.16

30.00

28.63

16.11

29.07

14.00

94.99

27.31

30.92

35.11

28.38

35.91

28.40

24.00

29.75

49.74

33.64

19.37

30.00

29.37

18.59

30.01

23.33

78.69

38.23

30.00

5.00

29.74

32.49

30

30.00

30.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

100.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.74

0.00

0.00

0.00

3.04

69.04

0.00

36.70

0.00

0.00

0.00

0.00

0.00

0.53

1.38

(continued)

0.00

0.00

0.00

0.00

0.00

0.00

0.00

41.64

0.00

29.54

0.00

0.00

0.00

0.00

0.00

0.00

0.00

2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017

Simple average

Table 5.3 India’s average tariff on imports from the United Kingdom

102 B. R. Chaudhuri and D. Chakraborty

Preparations of cereal, flour etc

Preparations of vegetable, fruit, nuts

Miscellaneous edible preparations

Beverages, spirits and vinegar

Food residues and waste

Tobacco products

Cotton

19

20

21

22

23

24

52

Weighted average

Free import as % of Total import

29.57 9.53

19.62

25.42

112.20

35.47

30.00

30.00

29.74

30.00

30.00

106.64

38.02

30.43

32.71

29.85

10.35

29.20

25.42

111.31

39.37

29.84

30.33

30.00

18.21

30.00

30.00

169.55

70.88

30.82

37.37

29.36

6.89

29.39

29.90

149.15

53.82

30.00

30.00

28.76

8.69

29.33

29.45

149.46

59.28

29.83

30.00

30.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

16.83

0.00

0.00

0.00

0.00

0.00

0.00

0.00

14.85

0.00

0.00

0.00

0.00

0.00

0.00

0.00

2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017

Simple average

Source Constructed by authors from WITS data

Cocoa and cocoa preparations

18

HS code Product description

Table 5.3 (continued)

5 India–UK FTA: Export Prospects for Indian Agriculture 103

104

B. R. Chaudhuri and D. Chakraborty

Table 5.4 EU’s average tariff on imports from India HS Product code description

Simple average

Weighted average

2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017

1

Live animals

1.108

0.600

0.358

2.226

0.664

0.590

2

Meat products

5.528

5.130

8.453

4.908

5.130

8.457

3

Marine and fish products

9.248

9.996

9.824

9.386

10.692

10.514

4

Dairy products

5.194

5.838

5.306

7.752

8.670

3.516

5

Animal products

0.050

0.106

0.060

0.020

0.142

0.126

6

Live tree and plants

5.480

6.820

6.016

7.020

6.596

5.134

7

Edible vegetables

7.958

8.984

8.168

9.132

10.332

9.912

8

Edible fruit and nuts

5.168

5.790

5.108

2.388

3.724

4.838

9

Coffee, tea, spices

1.984

2.184

1.980

0.312

0.434

0.378

10

Cereals

6.746

2.018

1.742

6.970

0.030

0.012

11

Products of milling industry, malt etc

9.646

11.052

9.880

7.644

8.196

7.492

12

Oil seeds

0.790

0.930

0.740

0.328

0.424

0.350

13

Lac, gums, resins etc

1.822

2.440

2.080

0.136

0.168

0.170

14

Vegetable plaiting materials

0.000

0.000

0.000

0.000

0.000

0.000

15

Animal of vegetable fats and oils

4.924

5.638

5.126

2.764

3.428

2.970

16

Preparations 15.882 of meat, fish or crustaceans

17.044

16.428

17.150

18.880

17.386

17

Sugars and sugar confectionery

12.226

12.420

9.442

12.444

13.238

10.240

18

Cocoa and cocoa preparations

5.640

5.360

5.736

5.932

5.534

7.074

19

Preparations of cereal, flour etc

8.666

10.650

8.810

10.286

12.780

10.206

(continued)

5 India–UK FTA: Export Prospects for Indian Agriculture

105

Table 5.4 (continued) HS Product code description

Simple average

Weighted average

20

Preparations of vegetable, fruit, nuts

16.318

17.196

16.544

15.442

16.130

15.900

21

Miscellaneous edible preparations

8.762

9.580

8.796

9.138

11.014

9.128

22

Beverages, spirits and vinegar

1.694

1.630

1.578

1.760

0.546

1.334

23

Food residues and waste

0.854

1.152

1.042

1.596

0.500

0.200

24

Tobacco products

39.402

40.676

42.352

55.858

36.322

52

Cotton

6.230

6.204

5.934

5.028

4.504

2003–2007 2008–2012 2013–2017 2003–2007 2008–2012 2013–2017

33.57 5.516

Source Constructed by authors from WITS data

products (HS 4), live tree and plants (HS 6), edible vegetables (HS 7), edible fruit and nuts (HS 8), products of milling industry, malt etc. (HS 11), animal of vegetable fats and oils (HS 15), preparations of meat, fish, or crustaceans (HS 16), sugars and sugar confectionery (HS 17), cocoa and cocoa preparations (HS 18), preparations of cereal, flour etc. (HS 19) and preparations of vegetable, fruit, nuts (HS 20), miscellaneous edible preparations (HS 21) and tobacco products (HS 24). It may be noted that for several product categories, simple weighted average tariff in the EU is higher than the trade weighted average tariff. This may indicate two possibilities. First, despite a lower tariff, India cannot export certain categories to the UK, perhaps owing to the absence of demand for them. Second, lower tariff in the EU does not necessarily translate into actual exports, given the presence of some standard-related or other form of NTBs. This might be an area of concern for Indian exports. To understand the importance of the standard related NTBs on global imports in general and bilateral trade in particular, a brief analysis has been performed with WTO ITIP database (WTO ITIP, undated). It is observed that during January 1, 2010, to December 31, 2019, the EU has initiated 260 SPS-related measures on agricultural products at two-digit level (i.e., HS 1–23) against all partners, while 89 measures were in force on the end date. The corresponding numbers involving India were 13 and 7, respectively. In addition, four India-specific trade concerns were in force on December 31, 2019. On the other hand, over the same period, India has initiated 114 measures on agricultural products against the rest of the world, while 25 measures were in force on the end date. No EU-specific standards have, however, been imposed by India during this period.

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5.4 Methodology and Data The current analysis is carried out at three levels. The data for the analysis has been drawn from the WITS database. First, we have used the SMART user-defined module1 to run simulations to estimate the impact on India’s agricultural export to the UK due to the reduction in tariff. Since the average tariffs on agricultural products imposed by the EU are quite low on an average, we have estimated the impact only for a zero-tariff scenario. In line with the evidence gathered from literature involving north–south agri-trade reforms in the presence of NTBs, not much changes are observed even at zero-tariff, and hence other scenarios of partial liberalisation were not attempted. In a departure from existing work, we have used recently estimated import demand elasticities at six-digit HS level by Ghodsi et al. (2016) in the current analysis. Next, we tried to find out the possible reasons for low gains from full liberalisation by looking at the NTBs at the HS six-digit levels. For the simulation exercise, first, we have identified agricultural products from India which have an RCA greater than one, when considering exports to the World. Next, we matched these products with top exports from India to the world. This gives us a set of agricultural products in which India has an advantage and also a large market. Similarly, for the UK, we look at their top agricultural imports from the rest of the world, including imports from intra-EU partners. The matched set of India is then compared with the list from the UK. The common set of products is those in which India has an advantage and has a large export market, and these are also imported by the UK from the rest of the world. This matched set at HS sixdigit level forms the basis for further analysis. We found 21 products at HS six-digit level, which satisfies our initial criteria. Three products had to be dropped from the analysis as they were not found in the UK’s import from India though they featured in India’s exports to the UK. Further, we looked at the top five exporters to the UK for each of these products and the corresponding average unit value. Additionally, the top export markets for India and the unit value for product exported to any EU countries were considered for products in this list which India does not export to the UK. Finally, we look at the tariff difference. The average tariff rate applied by EU on India (at HS six-digit level) is compared with the average tariff rate applied for all countries. We also look at the ratio of the average unit value of the top five exporters to the UK to that of India’s export to the UK. This is done to get an idea about quality or variety of product being an important factor impeding India’s exports. If it is found that India does not feature in the top five exporters to the UK even when the unit value is substantially lower than the competitors, the underlying reason may be twofold (Table 5.8). First, it may be a quality or variety issue which is reflected in the unit value difference. Second, added to that or separately, it may be due to higher non-tariff barriers. In the third step, we look at the non-tariff barriers in general imposed by EU to this set of products to get an idea about it. Given the modest trade gains experienced by India in UK agri-imports, even in the zero-tariff scenario, the current analysis 1 The

module can be accessed from https://wits.worldbank.org/simulationtool.html.

5 India–UK FTA: Export Prospects for Indian Agriculture

107

attempted to identify the possible presence of NTBs in the UK market on import. From Table 5.8, five products where India is not among the top five import sources for the UK are selected for this analysis. The products are dried fish other than cod (HS 030559), onions and shallots fresh and chilled (HS 070310), rice in husk (paddy rough) (HS 100610), flour, meal and powder of the product (HS 110630) and preparations of (excluding citrus) (HS 200799). Data is obtained from trade map and WTO I-TIP databases for the NTB analysis. There exists a rich literature for computing impact of NTBs on international trade. The current analysis draws from the framework developed by Bradford (2003), which computes the ratio of an importing country’s producer price to the world price to quantify the prevailing extent of protection. The theoretical undercurrent behind this formulation is that the higher technical standard introduced in the importing country (say, pesticide residue limit in EU countries for an agricultural product) results in higher compliance cost by their domestic firms. If exporters from a foreign country (say, India) intend to export to the UK market, they have to comply with these standards. Hence the average world price, which consists of the non-complying countries (say, India), will be lower than the domestic price level in the UK. The ad valorem tariff equivalent for the NTBs can be considered at HS six-digit level of aggregation. The formulation used by the analysis is the following: p

ppr i j =

pi j piw

(5.1)

where ppr i j represents the preliminary measure of protection of good i in country p j, pi j represents the producer price of good i in the importer country j (UK in the current context) and piw represents the world price of good i. One limitation of this approach is that the producer or domestic price of a particular product at HS six-digit level in the importing country may not be readily available. Under those circumstances, following Ardakani et al. (2009) the FOB price, obtained from trade data, may replace the domestic price. The world price, on the other hand, may be obtained through the addition of international transport cost to the lowest export price observed among major exporting countries (Bradford 2003), in the following manner: piw = pi M (1 + tm i )

(5.2)

where piw represents the world price of good i, pi M represents the minimum of the export price from the list of major import sources (e.g., top ten import sources) and tm i represents the international transport margin for good i. Bradford (2003) further notes that the constructed measure of NTBs will, however, not reflect the actual protection scenario if the countries selected for analysis are characterised by high import barriers. Under those circumstances, the world price ( piw ) as calculated by (5.2) will be higher than the actual price, as the tariff-laden

108

B. R. Chaudhuri and D. Chakraborty

import price enhances the export price in a country. As piw appears in the denominator of Eq. (5.1), this will consequently lead to a downward bias towards the measurement of protection coefficient, i.e., ppr i j . To correct the possible resulting downward bias, Bradford (2003) calculates the final measure of protection in the following manner: pr i j = max( ppr i j , 1 + tar i j )

(5.3)

where ppr i j represents the preliminary measure of protection of good i in country j, pr i j represents the final measure of protection of good i in country j and tar i j represents the tariff rate for good i in country j. While certain limitations of this approach have been noted (Dean et al. 2006), the coefficient obtained by adopting Bradford (2003) method can be considered as a proxy of policy-induced or implicit NTBs.

5.4.1 Simulation Results The SMART simulation results, sorted on the percentage change in post-reform import figures, are reported in Table 5.5. The point to note in Table 5.5 is that the gains from full-fledged reform (i.e., zero tariff) is quite low for products with a higher percentage change in imports. So, we have reported the results for the top five products with the highest absolute change in the next table. Only two products from Table 5.5 feature in Table 5.6, which observes the higher per cent changes in imports. The results in Table 5.6 indicate that given the higher base import values, the percentage gains are quite muted. In other words, the higher absolute changes in imports have happened for existing opportunity products. To gauge the situation more clearly, we also present the total change for all agricultural products in Table 5.7. It is observed that the expected change in Indian agricultural exports in the post-tariff reform period is relatively modest, as compared to the existing value. Table 5.5 Result of SMART simulations (top five agri-products in terms of % change) S. No.

Product code

1

071220

2

030339

3

200559

4

110610

5

200899

Source Authors’ calculations

Base imports 2016 (in ‘000 USD) 33747.26 239.616 27202.67 5509.209 145537.5

Import change (in ‘000 USD)

Percentage change in imports

1401

4.15

9

3.75

912

3.35

120

2.17

2070

1.42

5 India–UK FTA: Export Prospects for Indian Agriculture

109

Table 5.6 Result of SMART simulations (top five agri-products in terms of absolute change) S. No.

Product code

Base imports 2016 (in ‘000 USD)

Import change (in ‘000 USD)

Percentage change in imports

1

080610

672259.8

4131

0.61

2

200899

145537.5

2070

1.42

3

200599

108878

1437

1.31

4

071220

33747.26

1401

4.15

5

200190

120485.6

1208

1.00

Source Authors’ calculations

Table 5.7 SMART results for all agricultural products

Product

Base imports 2016 (in ‘000 USD)

Import change (in ‘000 USD)

Percentage change

All agriculture

61,295,100

14,860

0.02

Source Authors’ calculations

Thus, our results corroborate the findings of Banga (2017), even in the case of agricultural products. Using a more flexible modelling than the in-built SMART and considering the latest estimates of import demand elasticities also did not give any different result. The prospects of gain in agricultural exports through tariff liberalisation under India–UK FTA, therefore, do not seem to be bright from India’s perspective. Hence a more in-depth analysis into the other factors, namely NTBs, is called for to which we turn next. Table 5.8 amply shows that in all the identified prospective agricultural products, the major competitors have been EU countries. This may be an advantage for India in a post-BREXIT situation if otherwise India is competitive and there are no quality or variety issues. It is expected that non-tariff barriers are and will play an important role, at least for agricultural products. Out of the selected 18 products, in ten cases, India does not feature in the top five exporter’s list to the UK. Out of these ten products India does not export two products to the UK at all but exports it to other EU countries, namely mushrooms of genus Agaricus (HS 071231) and rock lobsters and other sea crawfish (HS 030611). For both these products, the major exporters to the UK are other EU countries. Out of the remaining eight products in five, the unit value of competitors of India are substantially higher (marked in bold italics in column (9). In all these products, the major exporters to the UK are from other EU countries (Column (4)). So for these set of products, the reason for lower exports by India may be due to quality or variety issue and/or presence of non-tariff barriers. Since it is difficult to analyse quality or variety issues at HS six-digit level, in the next step we look at the possibility of non-tariff barriers being imposed by the UK on non-EU countries for this set of products.

Preparations of (excluding Citrus)

Cucumbers and gherkins prepared/processed

Flour, Meal and Powder of the product

Flour, meal and powder of the dried

Rice in Husk (Paddy No Rough)

Spices nes

Mixtures of two or more products

Citrus Fruit

Mushrooms of genus agaricus

200799

200100

110630

110610

100610

091099

091091

080590

071231

No

No

Yes

Yes

Yes

No

Yes

No

Roasted chicory and No other roasted

210130

EU, China

EU, Bangladesh

EU, Pakistan

EU, Thailand, Turkey

EU

EU, USA

EU, Peru, Turkey

EU

EU

EU

Is India among Competitors top five (4) exporters to the UK (3)

Product name (2)

Product code (1)

Table 5.8 Analysis of trade prospects product-wise

0.012

0.002

0.0046

0.003

0.0011

0.0017

0.0108

0.0009

0.0026

0.003

Avg. unit value of top five exporters to UK (CIF) (5)

–

0.0041

0.0031

0.0016

0.0007

0.0018

0.0016

0.0009

0.0013

0.004

India’s unit value to UK(CIF) (6)

0.033–0.153

–

–

–

–

–

–

–

–

–

1.5

3.63

0.08

0.08

2.94

0.58

2.17

5.71

11.22

2.65

India’s unit value to Tariff an EU country if it is difference not exporting to UK (8) (FOB) (7)

(continued)

0.49

1.48

1.88

1.57

0.94

6.75

1.00

2.00

0.75

Ratio of unit value (9)

110 B. R. Chaudhuri and D. Chakraborty

Onions and shallots fresh and chilled

Cuttle fish

Fish life/fresh/chilled

Rock lobster and other sea crawfish

Dried fish other than No cod

Fish fillets and other No fish meat

070310

030749

030741

030611

030559

030499

Source Authors’ calculations

Cucumbers and Gherkins

071140

No

Yes

Yes

No

Yes

Yes

Onions dried whole/cut/sliced

071220

EU, Turkey, Canada, Iceland, USA

EU, Thailand, Myanmar

EU

EU, China

EU, Thailand, Indonesia, USA

EU, Egypt, Mexico

EU, Turkey

EU, China, USA

Is India among Competitors top five (4) exporters to the UK (3)

Product name (2)

Product code (1)

Table 5.8 (continued)

0.0044

0.0064

0.0112

0.0058

0.0053

0.0011

0.001

0.0022

Avg. unit value of top five exporters to UK (CIF) (5)

0.0039

0.0042

–

0.0058

0.0045

0.0003

0.0008

0.0019

India’s unit value to UK(CIF) (6)

–

–

0.0112–0.0200

–

–

–

–

–

1.99

3.52

0.97

0.22

0.73

2.65

4.11

2.32

India’s unit value to Tariff an EU country if it is difference not exporting to UK (8) (FOB) (7)

1.13

1.52

1.00

1.18

3.67

1.25

1.16

Ratio of unit value (9)

5 India–UK FTA: Export Prospects for Indian Agriculture 111

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B. R. Chaudhuri and D. Chakraborty

5.5 Non-tariff Barrier Analysis While computing the tariff equivalent of the NTBs, it is observed that for some products in certain years (e.g., HS 030559 for 2017), the minimum CIF price prevailing among the top ten importer countries for the UK is an outlier, and the next country in the list has been considered. This correction has been done primarily for LDCs, where price fluctuation has been noticed. On the other hand, for the UK the FOB export price for 030559 in 2017 has been unusually high, perhaps reflecting changes in local market conditions. The preliminary results are summarised in Table 5.9. The tariff equivalent of the NTBs are reported in the left panel of the table, and India’s share in UK’s import of these categories are noted in the right panel. Two observations particularly emerge from the table. First, for most of the commodities, the year-wise world price (minimum price) is noted from within European countries, often an EU member state. The result can be explained through the fact that the EU countries are recipients of farm subsidies through Common Agricultural Policy (CAP) (WTO 2017), and the transportation cost of these commodities reaching the UK market is relatively lower vis-à-vis other developing country partners. This devolution of subsidies, coupled with the EU intra-bloc tariff preferences adds further to the possible trade diversions. The NTBs on the selected products are found to be quite high, with no declining trend. However, these computed NTB equivalents are valid for UK’s global imports and not India-specific. Hence their possible effects on India’s exports need to be considered. Second, barring the exception of dried fish other than cod (030559) and flour, meal and powder of the product (110630), India’s share in UK import for all the products is quite modest and not showing any significant increasing trend. The modest presence of Indian exports in the UK market can be partly explained by the NTBs prevailing therein, identifying the detailed effect of which can be an area of future research.

5.6 Conclusion Since 2005, India has participated in several Asia-centric RTAs. However, it has been noticed that the country’s export gains in ASEAN and other markets have remained modest so far, with a greater rise in imports and the consequent widening of trade deficit. The modest success of India’s existing trade blocs has so far been attributed to various factors, namely safeguard provisions in the RTAs, lower absolute tariff reform by India’s partner countries, incomplete trade facilitation reforms, presence of NTBs and so on. Considering the past experience, the current analysis attempts to understand the possible implications of an FTA with the UK in the post-Brexit period on India’s agricultural exports. In this paper, we attempted to apply a partial equilibrium analysis of tariff liberalisation to find out the prospects for agricultural products from India to the UK. Initial descriptive trade flows and tariff analysis showed that India is not a major

118.20 (Spain)

225.77 (Germany)

259.37 (USA)

116.09 (Denmark)

070310

100610

110630

200799

116.42 (Denmark)

202.38 (USA)

177.17 (Greece)

103.00 (Spain)

369.82 (India)

129.01 (Netherlands)

160.03 (USA)

121.97 (Greece)

27.59 (Spain)

174.72 (Vietnam)

103.99 (Poland)

197.68 (USA)

286.15 (Greece)

31.63 (Spain)

199.55 (India)

124.43 (Netherlands)

217.06 (India)

233.93 (Greece)

160.78 (Spain)

756.84 (Lithuania)

0.3

3.8

0.1

0.6

0.0

0.2

3.1

0.3

0.8

0.2

2014

0.2

2.8

0.1

0.9

0.2

2015

0.4

5.8

0.2

0.8

0.4

2016

Source Computed by authors from Trade Map and WTO I-TIP data Note The exporting country to the UK, whose CIF price has been considered as a proxy of the world price, has been reported in the parenthesis

93.41 (China)

2017

2013

2016

Share of India in UK import (Per Cent) 2015

2013

2014

NTB estimate (Per Cent)

030559

HS codes

Table 5.9 Non-tariff barrier estimate for the United Kingdom: select agricultural products

0.6

3.5

0.0

0.9

1.6

2017

5 India–UK FTA: Export Prospects for Indian Agriculture 113

114

B. R. Chaudhuri and D. Chakraborty

source for agricultural products for the UK. Further, tariffs on Indian products are on average much lower in the UK than for UK products in India. This indicates that the gains from tariff liberalisation may be low for Indian agricultural products in the UK market. Literature is also replete with work which shows that NTBs may be higher in products where actually tariff is lower. In general, NTBs are quite restrictive in developed markets than in developing countries. The empirical analysis confirms only a modest export growth post-FTA even under full-tariff reform, given the fact that EU’s agricultural tariffs are lower as compared to India. Overall percentage gain from full-tariff liberalisation is not even 1%. A detailed analysis of India’s competitiveness vis-à-vis other exporting countries revealed that at least with respect to other EU countries exporting to the UK, India might be at a disadvantage due to higher NTBs. Thus, even after the Brexit if the UK continues with significant NTBs on its primary product imports, India’s benefit from an FTA with this country may not be substantial. A lot would, therefore, depend on how the negotiations take care of NTBs if such an FTA were to have some success.

References Agricultural and Processed Food Products Export Development Authority. (undated). Non-Tariff Barriers faced by Indian Agricultural Products. Retrieved September 20, 2018, from https://apeda. in/apedahindi/Databank/NTBs_March_08.pdf. Ardakani, Z., Yazdani, S., & Gilanpour, O. (2009). Studying the effects of non-tariff barriers on the export of the main agricultural products of Iran. American Journal of Applied Sciences, 6(7), 1321–1326. Banga, R. (2017). Brexit: Opportunities for India. Trade Competitiveness Briefing Paper 2017/01. London: Commonwealth Secretariat. Beghin, J. C., & Bureau, J. C. (2001). Quantitative policy analysis of sanitary, phytosanitary and technical barriers to trade. Economie Internationale, 87(3), 107–130. Bradford, S. (2003). Paying the Price: Final Goods Protection in OECD Countries. The Review of Economics and Statistics, 85(1), 24–37. Bureau, J., Guimbard, H., & Jean, S. (2017). Agricultural trade liberalization in the 21st century: Has it done the business? Working Paper No. 2017–11. Paris: Centre d’Études Prospectives et d’Informations Internationales (CEPII). Chaisse, J., & Chakraborty, D. (2014). The evolving and multilayered EU-India investment relations: Policy conjectures and regulatory issues. European Law Journal, 20(3), 385–422. Chakraborty, D., Chaisse, J., & Qian, X. (2019). Is it finally time for India’s free trade agreements? The ASEAN “Present” and the RCEP “Future.” Asian Journal of International Law, 9(2), 359– 391. Chakraborty, D. (2018). Picking the right alternative: Should India participate in TPP instead of RCEP? In J. Chaisse, H. Gao & C. Lo (Eds.), The transpacific partnership: A paradigm shift in international trade regulation. Singapore: Springer. Chakraborty, D., & Chakraborty, A. (2017). Economic and political cooperation between India and East Asia: The emerging perspective. Journal of Economics and Political Economy, 4(2), 144–158. Chand, R., & Bajar, S. (2012). Agricultural trade liberalization policies in India: Balancing producer and consumer interests. In R. Banga & A. Das (Eds.), Twenty years of India’s liberalization: Experiences and lessons (pp. 28–42). Centre for WTO Studies and United Nations.

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Lee, G.,& Lim, S. S. (2015). FTA effects on agricultural trade with matching approaches. Discussion Paper No. 2015–25. Retrieved September 20, 2018, from https://www.economics-ejournal.org/ economics/discussionpapers/2015-25. Malhotra, N., & Stoyanov, A. (2008). Analyzing the agricultural trade impacts of the Canada-Chile free trade agreement. CATPRN Working Paper 2008–08. Canada: Canadian Agricultural Trade Policy Research Network (CATPRN). McCole, K., & Panjwani, T. (2018). The UK and India: The bilateral trade relationship. London: UK India Business Council. McDaniels, D., Molina, A. C., & Wijkström, E. (2018). How does the regular work of WTO influence regional trade agreements? WTO Staff Working Paper ERSD-2018-06. Geneva: World Trade Organisation. Mehta, R. (2005). Non-tariff barriers Affecting India’s exports. RIS Discussion Paper No. 97. New Delhi: Research and Information System for the Non-Aligned and Other Developing Countries. Mondal, B., Sirohi, S., & Thorat, V. (2012). Impact of ASEAN-India free trade agreement on Indian dairy trade: A quantitative approach. Retrieved May 23, 2020, from https://mpra.ub.unimuenchen.de/40790/1/MPRA_paper_40790.pdf. Neufeld, N. (2014). Trade facilitation provisions in regional trade agreements: Traits and trends. WTO Staff Working Paper ERSD-2014-01. Geneva: World Trade Organisation. OECD. (2017). International regulatory co-operation and trade: Understanding the trade costs of regulatory divergence and the remedies. Paris: OECD. Pasadilla, G. O. (2006). Preferential trading agreements and agricultural liberalization in East and Southeast Asia. Asia-Pacific Research and Training Network on Trade (ARTNeT) Working Paper No. 11, Bangkok: United Nations Economic and Social Commission for Asia and the Pacific. Prasad, H. A. C. (2017). Reviving and accelerating India’s exports: Policy issues and suggestions. Working Paper No. 1/2017-DEA, Department of Economic Affairs, Ministry of Finance. New Delhi: Government of India. Renjini, V. R. (2016). Impact of ASEAN-India free trade agreement on Indian agricultural trade. Ph.D. thesis. New Delhi: Division of Agricultural Economics, Indian Agricultural Research Institute. Roy, A., & Mathur, S. K. (2016). BREXIT and India-EU free trade agreement. Journal of Economic Integration, 31(4), 740–773. Shearer, M., Almeida, J. S., & Gutierrez, C. M. Jr. (2009). The treatment of agriculture in regional trade agreements in the Americas. IDB Working Paper Series No. 145. Washington DC: InterAmerican Development Bank. Ji, S., & Yoo, J. (2018). A study on the changes of agricultural import structure according to implementation of FTAs in South Korea. Journal of Korea Trade, 22(1), 2–16. Songfeng, C., Yaxiong, Z., & Jianqin, Y. (undated). The effects of China US FTA (CHUSFTA). Retrieved September 20, 2018, from https://www.gtap.agecon.purdue.edu/resources/download/ 7437.pdf. Sun, L., & Reed, M. R. (2010). Impacts of free trade agreements on agricultural trade creation and trade diversion. American Journal of Agricultural Economics, 92(5), 1351–1363. Viljoen, W. (2016). Comparing Safeguard Measures in Recent Regional and Bilateral Trade Agreements. Geneva: International Centre for Trade and Sustainable Development. World Bank. (undated). World Integrated Trade Solution (WITS). Retrieved August 8, 2018, from https://wits.worldbank.org/. World Trade Organization. (2017). European Commission—Trade policy review. Geneva: WTO. World Trade Organization. (undated). Integrated Trade Intelligence Portal (I-TIP). Retrieved May 26, 2020, from https://www.wto.org/english/res_e/statis_e/itip_e.htm.

Chapter 6

Non-tariff Measures and India’s Agricultural Exports: The Case of India-ASEAN Trade Agreement Abhishek Jha and Seema Bathla

Abstract The protection accorded to agricultural trade continues to be a contentious issue in the multilateral trade negotiations across the globe. The developed and industrialized countries extend support to their agricultural sector through tariffs, non-tariff barriers, subsidies on inputs and output. These may discourage exports of agricultural products from the developing countries, despite being competitive. The Regional Trade Agreements (RTAs), which proliferated amongst the developing countries, have also done little to reduce the protectionism accorded to agriculture. Taking the case of the Association of Southeast Asian Nations (ASEAN), this chapter examines the degree of protection accorded to agricultural commodities, which among other factors could explain India’s low share in total exports. The findings indicate that among various non-tariff measures (NTMs), measures such as the sanitary and phytosanitary (SPS) may impact agricultural exports the most. The way forward for India is to adopt measures to improve the quality of primary and processed agricultural products, while also upgrading their standards. Exchange of dialogue regarding the transparency and good quality NTMs that perform as a tool to regulate quality of goods is a must. Keywords Export competitiveness · Non-tariff measures · Coverage ratio · Frequency index · Revealed comparative advantage

6.1 Introduction The protection accorded to agricultural trade continues to be a contentious issue in the multilateral trade negotiations across the globe. Countries resort to protective measures either through tariffs, that is the levy of customs, seconded by Article II of the General Agreement on Tariffs and Trade (GATT) and/or through non-tariff barriers, that are any form of trade barriers other than the tariff. Most of the developed A. Jha (B) · S. Bathla Centre for the Study of Regional Development (CSRD), School of Social Science (SS- III), Jawaharlal Nehru University, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_6

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countries also extend price or income support to their agricultural sector through the provision of subsidies on inputs and output (Clark 1992), which suppresses domestic prices and thus does not allow imports or it allows the domestic players to export at a cheaper price. These measures bring distortions in the market and discourage exports of agriculture products from the developing countries, despite being competitive. The multilateral trade negotiations have helped countries to reduce tariffs on several importable commodities and hence increase the market access and trade. However, the number of non-tariff measures (NTMs)1 has intensified, which seems to be critical in a lesser integration across the global markets (Cadot et al. 2015; Grant et al. 2017). The Regional Trade Agreements (RTAs), which proliferated amongst the developing countries during the 2000s, have also done little to reduce the protectionism being accorded to agriculture, especially in addressing the nontariff measures. However, little understanding and information exists regarding the prevailing NTMs and their impact on external trade. WTO agreements on technical barriers to trade (TBT) and application of sanitary and phytosanitary (SPS) measures are frequently used NTMs in the international trade, adversely affecting the exports of developing countries (Chaudhari et al. 2012). A quantitative analysis by Otsuki et al. (2001) suggests the impact of aflatoxin, a specific SPS standard applied by the EU has negatively affected the African exports by 64% (USD 670 million). Bosworth (1999) argued that non-tariff measures (NTMs) seem to be more harmful economically, both to the world trading system and for the individual countries than tariffs. Zarrilli and Musselli (2004) found that NTMs are costly and burdensome for developing countries. This chapter quantifies the important NTMs that may act as major impediments to agriculture exports from India to Association of South-East Asian Nations (ASEAN) and proposes some feasible ways to address these. India signed a free trade agreement (FTA) with 10 countries, group of ASEAN, in August 2009 with an intent to facilitate the bilateral trade. Keeping in view India’s ‘Act East Policy’, we find that exports have turned up, but the share of agriculture exports in total exports remains low (Ratna and Kallummal 2013), necessitating a detailed investigation on the tariff reduction schedule and NTMs imposed on agriculture products by the ASEAN. Section 2 provides an overview of the schedule of tariff reduction as per the AIFTA (ASEAN-India free trade area) and the incidence of NTMs in agriculture commodities relative to non-agriculture (manufactured) commodities. This is followed by an analysis on the magnitude of inter-country trade in important agriculture commodities, India’s revealed competitiveness (RC) in primary and processed agri-products and their juxtaposition with the NTMs on products that are competitive during 2004 to 2018 in Sect. 3. Section 4 draws conclusions and suggests a way forward. Data for the study is sourced from the ITC trade map, COMTRADE and TRAINS (UNCTAD) from 2003 to 2020. The categorization of agricultural products into primary and processed under HS Chapters 1–24 is done as per UNCTAD. 1 Non-tariff barriers (NTBs) emphasize protectionist scopes through imposition of quotas, and export

restraints. These have been replaced by non-tariff measures (NTMs) that lay stress on their potential role in hampering or facilitating trade (Grant and Arita, 2017).

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Category I. Live Animals; Animal Products (Chapters 1–5) Category II. Vegetable Products (Chapters 6–14) Category III. Animal or Vegetable Fats and Oils and their Cleavage Products; Prepared Edible Fats; Animal or Vegetable Waxes (Chap. 15) Category IV. Prepared Foodstuffs; Beverages, Spirits and Vinegar; Tobacco and Manufactured Tobacco Substitutes (Chaps. 16–24).

6.2 AIFTA’s Tariff Reduction Schedules and Incidence of NTMs The ASEAN India Free Trade Area (AIFTA) holds significance as it is one of the few multi-country FTAs that India signed. Ultimately, it took six years for the agreement to arrive at a bounteous conclusion as each country belonging to the regional bloc had to agree to India’s schedule of tariff concessions individually. Disagreements surfaced over the sensitive issue of opening of the markets for agricultural products. India’s primitive proposal of a negative list of 1,400 agricultural items was ultimately reduced to 489 in the final agreement (CUTS, 2009). To understand whether AIFTA can boost India’s trade, it is useful to analyse the tariff profile of ASEAN members. The broader aim of the said agreement is to arrive at a zero-customs duty regime for ‘substantially all merchandise trade’ between India and the ASEAN. The timespan for eliminating tariffs varies by country and product grouping. Once the agreement comes into full execution, tariffs would be scrapped on 80% of tariff lines. The tariff liberalization schedule for ASEAN Trade in Goods Agreements (ATIGA) has five components: (i) normal track; (ii) sensitive track; (iii) special products; (iv) highly sensitive list; and (v) exclusion list. Under normal track, tariff rates for products are expected to be reduced to zero. Normal track 1 and 2 refer to different time periods wherein the tariffs are expected to reduce to zero. For the sensitive track, the import tariff rates are to be reduced to 5% and further to 4.5 and 4%. Special products category is specific to India and it includes agricultural items whose imports are allowed at agreed reduced tariff. Under highly sensitive list, products are classified into three categories: one category is where applied MFN tariff rates are to be brought down to 50% and the other two categories are where applied MFN tariff rates are to be reduced by either 50 or 25%. For the products listed in the exclusion list, no tariff alleviation commitments have been made. However, it has been notified in the agreement that yearly review of tariff will be done to burgeon the market access for the exclusion list. AIFTA envisages that India and ASEAN-5 would bring down their tariff rates to zero in a phased manner during 1 January 2010 to 31 December 2013 for items in normal track. For other items the reduction in duties is to be done by 2019. It proposes to gradually slash tariffs for over 4,000 product lines at six-digit classification over a staggered period by 2019. India has two tariff reduction schedules for the AIFTA.

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Table 6.1 Proposals under India–ASEAN FTA (at HS 2007) Country

HS Code level

NT-1

NT-2

NT

ST

HST

EL

Total

Brunei

8 Digit

5628

928

6556

673

0

1071

8300

Cambodia

8 Digit

6644

336

6980

1134

19

166

8299

Indonesia

10 Digit

3657

409

4066

3486

552

633

8737

Laos

8 Digit

5711

719

6430

1640

0

230

8300

Malaysia

9 Digit

7461

1536

8997

1551

127

1030

11,705

Myanmar

8 Digit

5533

588

6121

1255

0

1250

8626

Philippines

8/9 Digit

5226

1479

6705

600

393

1174

8872

Singapore

8 Digit

–

–

–

–

–

–

–

Thailand

8 Digit

5540

138

6278

958

26

1045

8307

Vietnam

10 Digit

5580

188

6368

661

607

1549

9185

India

8 Digit

7775

1252

9027

1805

40

1297

12,169

Source AIFTA Text Note NT-1 is normal track 1, NT-2 is normal track 2 (represents different years for liberalization phase), NT is normal track comprising NT 1 and 2, ST is sensitive track, HST is highly sensitive track, EL is exclusion list.

There is a separate tariff reduction schedule for the Philippines and the remaining nine ASEAN members. Focusing on the general tariff reduction schedule of India, which is relevant for the nine ASEAN, we find that about 15% tariff lines are scheduled under the ‘Sensitive Track’ where tariffs are to be reduced to 5% or less by a certain date. The ‘Special Products’, where India has committed to truncate tariff rates at a much slower pace than both the normal track and the sensitive track include plantation—coffee, tea, pepper, and crude and refined palm oil (CPO and RPO, respectively). At HS 8-digit level, 40 tariff lines are listed under the ‘Special Products’ for which tariffs under AIFTA are reasonably high. Table 6.1 presents a comparative statement on the tariff liberalization program for India and ASEAN. India has put 1,297 tariff lines at the HS 8-digit level in the exclusion list (EL), which amounts to about 10.6% of tariff lines. As per the estimates, these tariff lines correspond to 496 tariff lines at HS 6-digit level out of which 302 items pertain to agriculture, 81 to textiles, 52 to machinery and automobiles, and 17 to chemicals and plastics. Classification of the tariff lines according to broad HS groups shows that a large number of products in agriculture, fish and marine, textiles, and garments have been put under the EL. On an average, India’s most favoured nation (MFN) tariff rate in agriculture products is about 34% against 13% preferential tariffs for ASEAN. Currently, around three-fourths of products have already entered the ASEAN markets at duty-free tariff rates. As of now, tariffs have been eliminated or reduced for more than 80% of tariff lines by both the regional partners (India and SEAN). But instead of realizing balanced gain for both the partners, India seems to import more than export indicating that the utilization rate of this FTA is low (Francis 2009; Harilal 2010; Yean et al. 2014).

6 Non-tariff Measures and India’s Agricultural Exports …

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About the NTMs applied by the ASEAN on India’s agriculture exports, we find that most of these stem from non-trade policy objectives such as food safety or environmental protection. However, they are also used as instruments of commercial policy, which have restrictive or distortionary effects on international trade (Cadot, 2015a). It seems that the NTMs act as the primary hindrance to increased market access, especially for developing economies (UNCTAD 2010; UN ESCAP 2015). The studies further state that NTMs are more complex than tariffs not just because of multiple objectives, but because their compliance is often difficult. Moreover, unlike tariffs that have majorly rent-shifting effects, the NTMs have the potential to affect the market structure in various intricate ways. Frequent and increasing usage of NTMs explains sluggishness in the intra-ASEAN trade and a static share of India–ASEAN agricultural trade. In what follows, we estimate the incidence of NTMs based on two indices. The first is the conventional method based on the frequency index. It shows the number of tariff lines covered by an eclectic group of NTMs. The crucial element of the index is a dummy variable that considers the unit value if one or more NTMs are applied to them. The second one is the extension of the index, which is known as the import coverage ratio. It weights the existing NTMs structure on home country imports or world imports (Bathla 2006). The frequency index is computed as follows: Fj = (



Di Ni /Ni ) ∗ 100

where D is a dummy variable reflecting the presence of one or more NTMs and N indicates number of products which are imported by the country. For example, if there are 100 products at HS 6-digit whose imports are non-zero by an economy, and out of which 10 products have one or more than one NTMs applied by the importing nation, then frequency index will be calculated as 10 (10 divided by 100). It should be noted that frequency index is unable to reflect the relative value of the affected products and thus does not give any indication of the overall impact of the NTMs on imports. A measure on overall imports of the NTMs is given by the coverage ratio which measures the percentage of imports subject to NTMs for the importing country. In formal terms the coverage ratio is evaluated as: Cj = (



Di Vi /Vi ) ∗ 100

where Vi represents the value of imports in tariff line item ‘i’ in the year under consideration, and Di is a dummy variable that takes a value of unity if NTM is applied in that year, and zero otherwise. For example, if an economy imports US$ 100 worth of products which are subject to one or more NTMs, and the total imports of that economy is US$ 500, then the coverage ratio of that economy will be 20 (when we divide 100 by 500). Two data sets are used to compute the frequency

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index and coverage ratio (C j ) which are TRAINS (UNCTAD) and ITC trade map. To enable comparisons of the incidence of NTMs over time, computations are done for two time periods 2009 and 2016 based on TRAINS (UNCTAD) and the export data provided by the DGCI&S, Government of India. As shown in Table 6.2, ASEAN’s frequency index and coverage ratio reflects that the agriculture sector is highly protected compared to their manufacturing sector. In the majority of the ASEAN, both the indices cover more than 90% of agricultural imports with some kind of NTMs. On comparing these indices in 2020 that with 2003 figures (Table 6.3), we can observe eloquently that there has been a spectacular rise in the implementation of NTMs applied by ASEAN on agriculture products. This rise is essentially due to SPS and TBT measures. Only Thailand and Philippines have less than 90% of the coverage ratio for agriculture in 2020. We also found that the degree of protection in agriculture, reflected through NTMs, has proliferated since 2003 (Table 6.3). We can infer that on the one hand import tariffs applied by ASEAN on Indian agriculture products declined with respect to time, while on the another hand, there is a continuous burgeoning of NTMs by ASEAN. Henceforth, a scissor and blade graph can be thought (where import tariff axis depicts a decline with respect to time and NTMs axis portrays a rise with respect to time) while discussing tariffs and non-tariffs imposed by the ASEAN on India’s agricultural exports (included all and bilateral members) (Cadot et al. 2015b). The challenge is dichotomous as on the one hand, the NTMs have been surging on agriculture products, and on the other hand, India’s competitiveness in value-added processed agricultural products has not been robust. Table 6.3 suggests that the intensity of NTMs applied by ASEAN on Indian agriculture products in 2003 was low. For instance, only US$ 105.5 million worth of Indian agriculture exports were subject to NTMs applied by Singapore, out of US$ Table 6.2 NTMs across ASEAN (2020) Country

Frequency index (%)

Coverage ratio (%)

For agriculture

For manufacturing

For agriculture

For manufacturing

Vietnam

97

46

96

57

Indonesia

96

39

91

42

Thailand

92

13

77

24

Philippines

90

74

86

66

Singapore

93

11

96

11

Malaysia

99

25

99

41

Myanmar

100

21

100

44

Cambodia

00

00

00

00

Brunei

99

10

100

26

Lao

99

98

100

99

Source Compiled from https://unctad.org/en/Pages/DITC/Trade-Analysis/Non-Tariff-Measures. aspxas on 2 August, 2020.

6 Non-tariff Measures and India’s Agricultural Exports …

123

Table 6.3 Coverage ratio (%) and frequency index evaluated for Indian agricultural exports to ASEAN in 2003 ASEAN

Indian agricultural products imported by ASEAN subject to any NTMs at HS 6-digit (a)

Total Frequency Indian ASEAN’s Indian Index agricultural total products (a/b) *100 products imports imported imported from by by ASEAN India, in ASEAN subject to US$ at HS any NTMs, millions 6-digit in US$ (d) (b) million (c)

Coverage ratio (c/d) *100

Singapore

219

2385

9.2

105.2

1701.9

6.2

Indonesia

147

1625

9.0

83.7

1039.6

8.0 30.5

Philippines 109

1170

9.3

98.9

324.3

Malaysia

161

2263

7.1

224.3

793.2

28.2

Thailand

142

1800

7.9

74.7

731.7

10.2

Vietnam

27

979

2.7

37.2

378.8

9.8

Sectors/Items of India’s exports covered

Major products covered with high frequency includes vegetables products, meat, fish, cereals, coffee, tea, preserved and tinned marine products, fresh and dried fruits

Source Author’s calculation using TRAINS (UNCTAD) and ITC trade map data sets

1701.9 total Indian exports to Singapore. Shakib and Taneja (2005) also evaluated the frequency index and coverage ratio for 2003. Since they considered all types of products (agriculture and non-agriculture) instead of agriculture, their coverage ratios are higher than ours except for Vietnam. This clearly indicates that, during 2003, more NTBs were applied on non-agriculture goods like leather, textiles, chemicals, iron and steel, pharmaceuticals, and electronics than on agriculture goods, by ASEAN. Now, agricultural products are not at all isolated by the ASEAN’s NTMs. We observed that ASEAN has significantly increased SPS measures on agriculture products in the last decade, especially on vegetables, animals, vegetable oils, and prepared food (Table 6.4). The TBT imposed on animal products too burgeoned during the last decade. Price control and quality control measures remained moderately static from 2003 to 2018. HS 01 to 24 cover more than 75% of all NTMs applied across tariff lines. Contingent trade protective measures too increased from 89 to 114. A continuous increase in the number of NTMs applied by the ASEAN is graphically presented in Fig. 6.1. Table 6.5 depicts that SPS and TBT together constitute the majority of NTMs applied to India’s agricultural exports. Under category IV of Table 4.4, major agriculture products facing high NTMs by ASEAN includes preserved and tinned marine

Animal and vegetable fats, oils and waxes

Prepared foodstuff; beverages, spirits, vinegar; tobacco

Category IV

Source TRAINS Database, 2018

Vegetable products

Category III

Total

Category II

Product description

2011–2018

Live animals and products

659

Prepared foodstuff; beverages, spirits, vinegar; tobacco

Category IV

Category I

TBT

Animal and vegetable fats, oils and waxes

Category III

100

37

97

70

123

37

110

Vegetable products

Category II

664 59

Total

Live animals and products

TBT

Product description

Category I

2003–2010

219

126

403

285

742

SPS

144

71

161

191

361

SPS

15

7

37

13

92

INSP

4

1

13

10

43

INSP

1

114

CTPM

9

89

CTPM

10

1

7

4

50

QC

6

3

9

3

34

QC

Table 6.4 Non-tariff measures applied by ASEAN on India (all members and bilateral) (2003 to 2010) and (2011 to 2018 May)

21

8

17

21

86

PC

24

8

14

12

48

PC

71

50

80

89

248

EXP

60

51

83

69

223

EXP

6

3

8

3

14

OTH

2

2

1

1

8

OTH

124 A. Jha and S. Bathla

6 Non-tariff Measures and India’s Agricultural Exports …

125

Fig. 6.1 NTMs applied on all products by the ASEAN on India (approximately 75% is applied to agricultural products). Source ASEAN-ERIA-UNCTAD NTM database

Table 6.5 Number of NTMs applied by ASEAN between 2003 and 2010 on agricultural products NTMs classification as per UNCTAD2

NTMs

2003–2010

2011–2018 (till May)

A

Sanitary and Phytosanitary

361

726

B

Technical Barriers to Trade

664

648

C

Pre-shipment inspection

43

90

D

Contingent trade-protective measures

89

114

E

Quantity control measures

34

50 86

F

Price-control measures

48

G, H, I, J, K, L, M, N, O

Others

8

14

P

Export-related measures

223

248

Source Author’s compilation

2 The classification of non-tariff measures encompasses 16 chapters (A to P) as per UNCTAD 2012

version.

products, extracts, and juices of fish and meat, prepared foods of flours, ready to eat products, soups, prepared foods, sauces, ketchup and seasonings, biscuits and bakery products, protein concentrates and chocolates. Even if India starts manufacturing these commodities and becomes cost-competitive, gaining market access will remain a herculean task in the existing scenario.

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Table 6.6 Agricultural trade between India and ASEAN (2004–2016) Trade (US Billion $)

2004

2009

2016

Total exports from India to ASEAN (A)

10.28

22.95

26.42

Total imports from ASEAN to India (B)

10.63

29.64

41.51

Total Trade (C)

20.91

52.59

67.94

Agricultural Exports from India to ASEAN (D)

1.44

2.7

7.42

Agricultural Imports of India from ASEAN (E)

2.02

5.01

7.86

Total Agricultural Trade (F)

3.46

7.71

15.28

19.06

14.65

22.5

Share of Agricultural Trade in total Trade ((F/C) * 100) Source UN COMTRADE

6.3 India’s Agricultural Trade with ASEAN Data on India’s exports to ASEAN is sourced from the ITC trade map database 2018 and COMTRADE from 2004 to 2016. As shown in Table 6.6, India’s agricultural trade with ASEAN burgeoned from USD 3.46 billion in 2004 to USD 7.7 billion in 2009 and then to USD 15.1 billion in 2016. A surge in agricultural trade was stimulated because of the rise in exports from USD 2.7 billion in 2009 to USD 7.4 billion in 2016, mainly due to a phase-wise reduction in the tariff rate by the ASEAN. During 2009 to 2016, a proliferation in India’s agricultural exports (considering in absolute terms) to ASEAN can be explained by a reduction in the tariff rate by the said regional block under the FTA. As per the frequency index, till 2009, a large proportion of agricultural products belonged to the category of zero NTMs. However, between 2009 and 2016, we observed a surge in the overall NTMs applied to agricultural products. A large proportion of agricultural exports to Malaysia and Vietnam are subject to NTMs. For many of India’s products exported to Malaysia, Vietnam, Singapore, Philippines, Thailand, and Indonesia, the NTMs coverage ratio has burgeoned, signalling more agricultural products facing these barriers. Following the free trade agreement, the duties reduced overall cost of trade and thus benefitted exports. However, from the trends in NTMs applied by the ASEAN, India’s agricultural exports seem to enervate the degree of benefit. Thus, the heat of NTMs may create a daunting platform for India’s agriculture exporters as they tend to be heterogeneous. A graphical representation shows that from 2007 to 2019, India’s agricultural exports escalated more for Vietnam and relatively lesser for Malaysia, Thailand, and other countries (Fig. 6.2). This hike could be due to a reduction in the tariff schedule. Meat (HS 02) is the top ranked with more than 30% share in total agricultural exports and around 10% share to total products. Other important agricultural export items to ASEAN having a high share in agricultural exports are fish and fish products3 (15%), oilseeds (8.4%), cotton (8.2%), and coffee (6.4%). The composition of key sectors 3 As

per the WTO definition, fish and fish products do not fall under agriculture, but in this study, we have included it in agriculture sector.

6 Non-tariff Measures and India’s Agricultural Exports …

127

9000 8000 7000 6000 5000 4000 3000 2000 1000 0 2001

Viet Nam

2005

Malaysia

2010

Indonesia

2015

Thailand

2016

Singapore

2017

Rest of ASEAN

Fig. 6.2 India’s agri-exports to ASEAN (US$ million). Source Compiled from ITC trade map

has changed between 2009, i.e. at the time of implementation of AIFTA and 2019. There is an addition of two new sectors: fish and fish products (HS 03) and coffee, tea, and spices (HS 09). Among the 10 ASEAN, India’s agri-exports are mainly concentrated on Vietnam, Indonesia, Singapore, Malaysia, and Thailand. Together they consist of 90% of India’s agriculture exports to ASEAN, Vietnam being the largest destination. India exports almost 10% of its global exports to ASEAN and buys around 10.6% of its global imports. Figure 6.3 portrays economies from where India imports agricultural products, i.e. Indonesia, Malaysia, and Myanmar. Major products whose imports surged post-FTA are crude palm oil, refined palm oil, animal feed, cinnamon, oil cakes, coffee, turmeric, and pepper. 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 2001

2005 Indonesia

Malaysia

2010 Myanmar

2015 Viet Nam

2016 Thailand

2017

Rest of ASEAN

Fig. 6.3 India’s agri-imports from ASEAN (US$ million).n Source Author’s calculation from ITC trade map

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From 2010 to 2017, the annual rate of growth of India’s agricultural exports is positive, close to 9% but is lower than that from 2001 to 2009 at 16.30% (Table 6.7). Except for Myanmar, the annual growth rate of exports to all economies is lower in the latter period. This might be explained due to a continuous rise in the NTMs by ASEAN on India’s agricultural products. Even after the reduction of tariff rates following the India–ASEAN trade agreement, proliferation in agricultural exports to ASEAN was not reflected. Within the ASEAN, India’s agricultural export share to Vietnam surged from 6.27% share in 2001 to 62.83% in 2017. For Thailand, Indonesia, Singapore, and the Philippines, the respective share plummeted. This reflects that post-India–ASEAN FTA, India’s agricultural exports remained concentrated towards Vietnam only. Table 6.8 presents India’s agricultural imports from ASEAN. Approximately 80% of imports are from Indonesia and Malaysia. From other nations, imports were moderate during 2017. As we have seen that the growth rate of Indian agriculture exports to ASEAN from 2001 to 2009 remained significantly higher than that Table 6.7 India’s agri-exports to ASEAN (in US$ million) and % share (in parentheses) Importers

2001

2007

2010

2014

2017

Annual rate of growth 2001–2009 (%)

Annual rate of growth 2010–2017 (%)

World

8370

18,563

26,085

47,832

42,508

13.5

3.2

2402

3666

ASEAN total 950

8712

8822

16.3

9

Vietnam

59 (6.2) 648 (27) 1216 (33.1)

4824 (55.3)

5543 (62.8)

45.1

18.9

Malaysia

245 (25.8)

608 (25.3)

876 (23.9)

1103 (12.6)

924 (10.4)

14.1

-2.1

Thailand

119 (12.6)

247 (10.3)

382 (10.4)

868 (9.9)

697 (7.9)

19.5

3.8

Indonesia

237 (24.9)

482 (20.1)

588 (16.0)

983 (11.2)

695 (7.8)

9.0

-4.7

Myanmar

3 (0.3)

9 (0.4)

102 (2.7)

153 (1.7)

359 (4.0)

14.9

31.3

Philippines

122 (12.8)

209 (8.7)

268 (7.3)

358 (4.1)

283 (3.2)

4.9

-1.0

Singapore

158 (16.7)

170 (7.0)

201 (5.5)

331 (3.8)

277 (3.1)

4.1

2.3

Cambodia

1 (0.1)

19 (0.8)

20 (0.5)

39 (0.4)

20 (0.2)

29.4

-4.5

Brunei Darussalam

0.83 (0.09)

5 (0.2)

8 (0.2)

19 (0.2)

19 (0.2)

35.7

8.4

Lao People’s Democratic Republic

1 (0.1)

0.08 (0)

0.1 (0)

29 (0.3)

1.9 (0.02)

–

63.4

Source Author’s calculation using ITC trade map data

6 Non-tariff Measures and India’s Agricultural Exports …

129

Table 6.8 India’s agricultural imports from ASEAN in US$ million and percentage share (in parentheses) Exporters

2001

2007

2010

2014

2017

Annual rate of growth from 2001–2009 (%)

Annual growth rate from 2010–2017 (%)

World

3103

7421

12,908

20,157

26,364

15.5

9.2

ASEAN

1119

2248

5866

8354

8354

15.2

2.0

Indonesia

405 (36.2)

1455 (64.7)

4008 (68.3)

4289 (51.3)

5474 (65.5)

22.6

-0.6

Malaysia

432 (38.6)

190 (8.4)

810 (13.8)

2621 (31.3)

1584 (18.9)

-2.7

7.5

Myanmar

225 (20.1)

479 (21.3)

683 (11.6)

823 (9.8)

553 (6.6)

17.6

2.1

Vietnam

11 (1.0)

29 (1.3)

95 (1.6)

295 (3.5)

354 (4.2)

20.5

19.1

Thailand

21 (1.8)

65 (2.9)

204 (3.4)

197 (2.3)

250 (3)

29.9

-0.3

Singapore

19 (1.7)

24 (1.08

47 (0.8)

83 (1)

75 (0.9)

9.7

3.6

Philippines

3 (0.2)

1 (0.06)

10 (0.1)

44 (0.5)

49 (0.6)

12.7

31.3

Cambodia

0(0)

1(0.05)

6 (0.1)

0.4 (0)

10 (0.1)

–

-1.9

Lao People’s 0(0) Democratic Republic

0.07(0)

0.15(0)

0.03(0)

2(0.03)

–

31.40

Brunei Darussalam

–

–

–

–

–

–

–

Source Author’s calculation from ITC trade map. Note ‘–’ not estimated as figures are either not available or value is negligible

from 2010 to 2017. Similarly, imports’ growth rate from 2001 to 2009 also remained higher than that from 2010 to 2017s figure of imports growth. Point to be noted here is that from 2010 to 2017 Indian agriculture exports to ASEAN grew by 9% while our agricultural imports from ASEAN for the same period surged only by 2%, implying that India realized higher agricultural exports post AIFTA (ASEAN–India free trade area) than imports. This can be an outcome of lowered import tariff rates of ASEAN’s agricultural products. The composition of agriculture exports has also undergone significant changes due to a sizeable diversification. During 2007, meat and edible meat products accounted for almost 13% share in total agriculture exports. Nearly one-fourth (27%) exports consisted of residues and waste from food industries. These two groups accounted for almost 40% of ASEAN’s agriculture imports from India. Cotton was the third important import item having a 9% share in India’s imports to ASEAN. Further,

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oilseeds accounted for 7.83%; fish 6%; coffee, tea, cereals, vegetables, roots, and tubers 3% share in the export basket. If we compare India’s agriculture imports share in total imports from the ASEAN region between 2010 and 2017, the figures are almost static. As discussed above, the agriculture imports from Indonesia, Malaysia, and Myanmar constitute over 85% share in total imports. Reduction in tariffs did not change the proportion of India’s import basket in terms of agricultural products.

6.3.1 Competitiveness of India’s Agricultural Products The export competitiveness of agricultural products is estimated separately for each of the four agricultural product categories mentioned above and within each for some of the important commodities from 2000 to 2017. The agriculture products in categories I and II are broadly primary (raw) in nature with some value addition. Products considered under categories III and IV are value-added products, i.e. they undergo a high level of processing. India’s agriculture exports consist of 75% primary products since the last two decades, and the remaining comprise value-added products. We follow revealed competitiveness (RC) method suggested by Vollrath (1991). First, the Conventional Revealed Comparative Advantage (RCA) Index is evaluated as per Balassa (1977): RCAAi = (XAi /  j∈P XAj ) / (XWi /  j∈P XWj ) where P is the set of all products (with i ∈ P), XAi is the exports of product i, from country A exports, XWi is the worlds’ exports of product i,  j∈P XAj is the country A’s total exports (of all products j in P), and  j∈P XWj is the world’s total exports (of all products j in P). For a country to possess revealed comparative advantage for a given product, the value of RCA has to be more than 1. With value being more than 1, it is inferred to be a competitive exporter of that product relative to a country producing and exporting that good at or below the world average. With higher value of a country’s RCA for product i, the higher export strength is reflected. Second, import competitiveness is estimated in a similar way. The only difference is that the import flows are considered in this index instead of export flows. This is named as Revealed Comparative Advantage of Imports (RMA). Subsequently, the logarithmic form of RMA is subtracted from the logarithmic form of RCA (which is export competitiveness) to get the revealed competitiveness (RC), i.e. the difference between the logarithm of the relative export advantage and the logarithm of the relative import advantage: RC = ln (RCAAi ) – ln (RMAAi ). A positive value of each index indicates revealed comparative advantage, whereas a negative value indicates revealed comparative disadvantage. Since RCA is not symmetric (Balance et al. 1987), we proceeded our estimations using RC. The estimates on RC reveal that only 17 agriculture product categories at 4-digit HS classification have export competitiveness after adjusting for imports. In category I, crustaceans have the highest export competitiveness, followed by bovine meat and

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131

molluscs. In category II, coconuts and cashew nuts, tea, black pepper, fenugreek, rice, cardamoms, copra, and groundnuts are competitive. In category III, fixed oils and fats extracted from vegetables, vegetable saps, groundnut oil, and oleaginous fruits are competitive. Category IV represents food products with maximum value addition in the industrial units, where export competitiveness is considerably low. Only four products under HS 16 to HS 24 are found to have RC positive, means competitive, which are essence and extracts of coffee, pellets of oilcake, raw and manufactured tobacco. The products in which India has remained competitive include meat products, frozen fish, crustaceans, onions and shallots, tea, rice, groundnuts, oilseeds, cane and beet sugar, the essence of coffee and oil cakes. Table 6.9 presents a category-wise RC in major agriculture exports from India based on average triennium ending (TE). The following are the key observations. 1.

2.

3.

4.

High competitiveness is found in category I in meat of bovine animals, meat of sheep and goats either fresh or chilled, frozen fish, crustaceans, molluscs, bird eggs and egg yolks, natural honey, ivory, and tortoiseshells Among vegetable products and cereals (category II), onions, shallots, dried vegetables, preserved vegetables, spices like cardamoms, tea, coffee (prepared), cashew nuts, coconuts, gherkins, cucumbers, mango and mangosteens, rice, wheat, wheat flours, soybeans, meslin flours, and millets possess competitiveness. For remaining products, i.e. pulses, lentils, grams, potato, and tomato, indices don’t reflect competitiveness. From category III animal or vegetable fats and oils and their cleavage products, prepared edible fats; animal or vegetable waxes category only a few have trade competitiveness including groundnuts and groundnut oil, jojoba oil, oleaginous fruits. Category IV comprising prepared foodstuffs; beverages, spirits, and vinegar; tobacco and manufactured tobacco substitutes have medium and high valueadded products. With a few exceptions, India lacks competitiveness in these, including ready to eat food products.

It is further observed that since 2000 India had little structural change in gaining export competitiveness, implying not much change in the agricultural export basket. The possible explanations can be, first, India is not cost competitiveness in producing value-added agricultural products and may find hard to compete with other comparable developing countries—Vietnam, Thailand, and Indonesia. Second, inadequate public infrastructure may hinder farmers’ incentives to make investments in technology and other assets (Bathla 2017). Third, the value-added exportables have more scope to generate value, but in the long run and not in short run. Therefore, it is important for the food industry to make investments in technology to reap benefits from exports of value-added products. To what extent does India’s agriculture products that are competitive are affected by NTMs? This question is addressed by taking data on the number of NTMs imposed by ASEAN in primary and processed food products given in UNCTAD TRAINS Database. The NTMs can be applied to all goods, however, nearly 75% of NTMs are applied to agricultural products. Broadly, NTMs constitute quality certifications, lab

132

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Table 6.9 India’s revealed competitiveness in primary and value-added agriculture products HS Codes

Category I

0202

Meat of bovine animals, frozen

0204

TE 2003

TE 2007

TE 2010

TE 2013

TE 2017

0.77

0.82

0.84

1.05

1.07

Meat of sheep or goats, fresh, chilled or frozen

−0.21

−0.33

0.16

0.05

0.02

0206

Edible offal of bovine animals,

−1.37

−1.36

−1.03

0.01

0.07

0302

Fish, fresh or chilled

−1.00

−1.09

−1.49

−0.89

−0.61

0303

Frozen fish

0.52

0.22

0.20

0.24

0.32

0304

Fish fillets and other fish meat,

−0.56

−0.65

−0.48

−0.42

−0.31

0305

Fish, fit for human consumption, dried, salted

−0.41

−0.52

−0.63

−0.44

−0.40

0306

Crustaceans

0.86

0.75

0.59

0.83

0.89

0307

Molluscs

0.50

0.50

0.41

0.46

0.55

0409

Natural honey

−0.52

0.18

−0.03

0.32

0.34

2.96

3.02

2.55

2.57

2.54

0.43

0.78

0.86

0.61

0.77

Category I: All Category II 0703

Onions, shallots, garlic, leeks and other alliaceous vegetables, fresh or chilled

0713

Dried leguminous vegetables, shelled, whether or not skinned or split

−58.52

−31.71

−44.05

−34.71

−31.59

0801

Coconuts, Brazil nuts and −33.99 cashew nuts, fresh or dried, whether or not shelled or peeled

−31.55

−16.68

−14.19

−10.92

0804

Dates, figs, pineapples, avocados, guavas, mangoes and mangosteens, fresh or dried

−0.38

0.00

−0.01

−0.15

−0.18

0806

Grapes, fresh or dried

−0.32

−0.24

−0.09

−0.09

−0.02

0901

Coffee

−9.53

−50.12

−56.95

−60.58

−29.53

0902

Tea

0.96

0.87

0.81

0.78

0.81

0904

Pepper of the genus Piper; dried or crushed or ground

−25.14

−32.40

−29.91

−24.40

−22.12

0909

Seeds of anis, badian, fennel, coriander, cumin or caraway; juniper berries

−2.43

−2.91

−1.66

0.01

−1.61

(continued)

6 Non-tariff Measures and India’s Agricultural Exports …

133

Table 6.9 (continued) HS Codes

Category I

0910

Ginger, saffron, turmeric “curcuma”, thyme, bay leaves

TE 2003

TE 2007

TE 2010

TE 2013

TE 2017

−0.95

−3.24

−1.91

−1.30

−1.50

1006

Rice

1.23

1.19

1.09

1.05

1.03

1202

Groundnuts, whether or not shelled or broken (excluding roasted or otherwise cooked)

0.98

1.15

1.18

1.30

1.36

1207

Other oilseeds and oleaginous fruits, whether or not broken (excluding edible nuts, olives)

0.50

0.10

−0.30

0.25

0.46

1211

Plants and parts of plants used primarily in perfumery

−4.19

−5.42

−2.66

−4.21

−4.03

1302

Vegetable saps and extracts; pectic substances, pectinates and pectates; agar−agar and other…

−3.14

−1.15

−1.36

−0.67

−0.52

HS

Category II: All

2.96

2.10

2.19

2.80

1.64

Category III 1504

Fats and oils and their fractions of fish or marine mammals, whether or not refined

−3.63

−2.58

−2.25

−1.10

−1.08

1513

Coconut “copra”, palm kernel or babassu oil and fractions thereof, whether or not refined

−2.12

−2.36

−2.01

−1.81

−1.52

1515

Fixed vegetable fats and oils, incl. jojoba oil, and their fractions, whether or not refined

0.85

0.90

0.96

1.01

1.12

1516

Animal or vegetable fats and oils and their fractions, partly or wholly hydrogenated

−2.80

−4.19

−1.78

−0.21

−0.14

1518

Animal or vegetable fats and oils and their fractions, boiled, oxidised, dehydrated

−1.96

0.26

0.24

−0.56

−1.08

HS

Category III: All

−2.18

−1.58

−1.58

−1.86

−2.02

Category IV (continued)

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Table 6.9 (continued) HS Codes

Category I

TE 2013

TE 2017

1605

Crustaceans, molluscs and other aquatic invertebrates, prepared or preserved (excluding smoked)

TE 2003 −0.16

TE 2007 0.31

TE 2010 0.24

−0.16

−0.11

1701

Cane or beet sugar and chemically pure sucrose, in solid form

0.46

−1.84

−1.61

−2.20

−1.29

1905

Bread, pastry, cakes, biscuits and other bakers wares, whether or not containing cocoa

−0.80

−0.49

−0.46

−0.43

−0.40

2101

Extracts, essences and concentrates, of coffee, tea

0.67

0.52

0.41

0.35

0.39

2106

Food preparations, n.e.s

−1.09

−1.09

−1.18

−1.49

−1.02

2304

Oilcake and other solid residues, whether or not ground or in the form of pellets

0.61

0.82

0.87

0.70

0.71

2306

Oilcake and other solid residues

−14.00

−16.81

−14.52

−16.55

−14.04

2309

Preparations of a kind used in animal feeding

−9.75

−8.66

−7.93

−9.59

−9.38

2401

Unmanufactured tobacco; tobacco refuse

0.49

0.50

0.61

0.54

0.58

2403

Manufactured tobacco and manufactured tobacco substitutes

0.16

0.28

0.39

0.27

0.26

Category IV: All

1.88

2.08

2.02

2.08

1.84

Source Based on data from COMTRADE

tests, and risk certifications. One example implemented by the ASEAN is PSAT (fresh food of plant origin) which considers lab testing procedures, and safety certification procedures. Table 6.10 shows that the ASEAN together imposed a maximum number of NTMs on value-added agriculture products, belonging to category III (animal and vegetable fats, oils and waxes HS Chap. 15) and category IV (prepared foodstuff; beverages, spirits, vinegar; tobacco, from HS Chaps. 16 to 24) compared to those under categories I and II, respectively. The SPS and TBT measures comprise more than 80% of the NTMs in this category. We find no relaxation or liberalization provided by ASEAN on India’s exports, even on those that have revealed competitiveness (Table 6.11). This carries a serious risk for exports to ASEAN in due course as the cost may hurt its competitiveness. The situation seems to aggravate as hardly any aggressive and pragmatic approach has been discussed to facilitate traders on NTMs in AIFTA text.

Prepared foodstuff; beverages, spirits, vinegar; tobacco Categories I and II Categories III and IV

Category II

Category III

Category IV

Primary Agriculture Products

Value Added Agriculture Products

01 - 05

06–14

15

16–24

TBT

823

655

661

162

383

272

SPS

1120

1089

821

299

427

662

INSP

34

46

24

10

20

26

CTPM

0

0

0

0

0

0

QC

44

57

32

12

36

21

PC

101

104

72

29

53

51

EXP

325

476

191

134

242

234

OTH

15

19

10

5

12

7

2462

2446

1811

651

1173

1273

Total

Source https://asean.i-tip.org/. Note: INSP is pre-shipment inspection, CTPM is contingent trade protective measure, QC is quality control measure, PC is price control measure, EXP is export-related measure and OTH is other measures

Animal and vegetable fats, oils and waxes

Vegetable products

Product description Live animals and products

Category I

HS Code

Table 6.10 NTMs applied by ASEAN on India’s agriculture products

6 Non-tariff Measures and India’s Agricultural Exports … 135

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A. Jha and S. Bathla

Table 6.11 NTMs applied by ASEAN on India’s agri-products that are competitive HS Code

Product description

TBT

SPS

INSP

QC

PC

EXP

OTH

0201

Fresh meat

66

199

4

4

17

64

1

0202

Frozen meat

65

201

4

5

17

64

1

0303

Fish, frozen

54

161

5

5

16

81

1

0304

Fish fillets

53

163

4

5

16

80

1

0305

Fish, dried

48

157

4

4

14

76

1

0306

Crustaceans

41

183

8

7

13

74

0902

Tea

25

136

2

1

11

15

1

1006

Rice

75

172

9

13

22

51

4

1701

Cane or beet sugar and chemically pure sucrose, in solid form

61

119

5

6

12

36

3

Source UNCTAD TRAINS Database. Note: TBT is technical barriers to trade, SPS is sanitary and phytosanitary measures, INSP is pre-shipment inspection, QC is quality control measures, PC is price control measure, EXP is export-related measures, OTH is others

6.4 Conclusions and Way Forward This chapter examined the degree of protection accorded to India’s primary and processed agriculture product exports by the ASEAN. Broad findings indicate that since the mid-2000s, tariff rates have reduced on agriculture trade but the incidence of non-tariff measures on several agricultural products has been on the increase, even in those commodities in which India has revealed competitiveness. This may be an important factor behind a low share of agricultural exports in total exports to ASEAN. The important NTMs are found to be food quality, sanitary and phytosanitary and health-related restrictions with little understanding and transparency about each of these. Furthermore, various eclectic regulations are poorly constructed, failing to safeguard the public while needlessly complicating the business. This may be explained by the fact that regulations are mostly enforced in punitive ways, signalling an anti-business culture of many administrations. Besides, the NTMs typically span the competencies of several ministries, with miniscule harmonization mechanisms to make the necessary trade-offs. Such protectionism by ASEAN on India’s agriculture exports may act as an impediment due to added cost, risk, and time. A dialogue regarding the standardization of NTMs needs to be initiated at the multilateral and regional level. India and ASEAN’s concerned regulatory authorities should cooperate and introduce transparent and good quality NTMs that could serve as a tool of check and balance for quality of goods, and also for health, safety, and environmental protection. The way forward may also require India to formulate and execute several domestic measures to escalate the quality of her fresh and processed agricultural products and modernize food standards. Yet, in case of any discrepancy and unreasonably high standards set by the importing countries, the exporters and export promotion agencies can raise concerns

6 Non-tariff Measures and India’s Agricultural Exports …

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at both bilateral and multilateral forums. For this, it is essential to have scientific research and adequate data to establish a case. India should also specify the modus operandi for an institutional mechanism to follow and lay hold of market access, tackle barriers, and handle with sanitary and phytosanitary issues. Another approach which seems pragmatic for India and ASEAN is to follow the NTMs specifications given by the Codex Alimentarius in a harmonised manner for agricultural products. Food safety standards formulated by Codex Alimentarius are referred under the SPS agreement for executing and designing trade polices as these are scientifically justified. Ironically, even today, economies digress from the Codex standards. Harmonization of NTMs can only be attained when all countries adopt similar standards. The General Principles of the Codex Alimentarius specify the ways in which member countries may ‘accept’ Codex standards. It is also imperative for agriculture exporters to equip themselves with the requisite regulations implemented by the ASEAN, keeping in view that the WTO members adopted a Trade Facilitation Agreement in 2017.

References Balassa, B. (1977). Revealed comparative advantage revisited: An analysis of relative exports shares of the industrial countries 1953–1971. Manchester School of Economic and Social Studies, 45, 327–344. Ballance, R. H., Forstner, H., & Murray, T. (1987). Consistency tests of alternative measures of comparative advantage. Review of Economics and Statistics, 69, 157–161. Bathla, S. (2006). Trade policy reforms and openness of Indian agriculture: Analysis at the commodity level. South Asia Economic Journal, 7(1), 19–53. https://doi.org/10.1177/139156 140500700102. Bathla, S. (2017). Public investment in agriculture and growth: An analysis of relationship in the Indian context. In Bathla, S. & Dubey, A. (Eds.), Changing Contours of Indian Agriculture: Investment, Income and Non-Farm Employment (pp. 13–28). Singapore: Springer Nature. Bosworth, M. (1999). Non-tariff measures as trade barriers—Yesterday ‘s problem or what? Paper presented at the OECD workshop with non-member economies on barriers to trade in goods and services in the post-Uruguay round context, Paris, pp. 27–28 September 1999. Cadot, O., Ing, L. Y. (2015a). Non-tariff measures harmonization: Issues for the RCEP. Economic Research Institute for ASEAN and East Asia (ERIA) discussion paper series no.61, Jakarta, September 2015. Cadot, O., Munadi, E., Ing, L. Y. (2015b). Non-tariff measures in ASEAN: The way forward. Asian Economic Papers, 14(1), 35–70. Chaudhari, M. B., Giedraitis, V., & Kapse, P. (2012). Barriers to export from India to the European Union. Ekonomika, 91(2), 38–48. Clark, D. (1992). Non-tariff measures and industrial nation imports of agricultural products. Southern Journal of Agricultural Economics, 24, 225–232. Consumer Unity & Trust Society. (2009). India-ASEAN FTA: A move towards multilateral free trade agreements? CUTS Centre for International Trade, Economics & Environment (CUTS CITEE), Briefing paper number 1/2010. Francis, S. (2011). A sectoral impact analysis of the ASEAN-India free trade agreement. Economy and Political Weekly, 46(2), 46–55.

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Grant, J. H., & Arita, S. (2017). Sanitary and phyto-sanitary measures: Assessment, measurement, and impact. International Agricultural Trade Research Consortium (IATRC) commissioned paper number 21, 1–56. Harilal, K. N. (2010). ASEAN-India free trade area: Noises of dissent from deep south. Occasional paper number 2010:01. Kerala State Planning Board, Government of Kerala, Thiruvananthapuram. Otsuki, T., Wilson, J. S., & Sewadeh, M. (2001). What price precaution? European harmonization of aflatoxin regulations and African groundnut exports. European Review of Agricultural Economics, 28, 263–283. Ratna, R. S., & Kallummal, M. (2013). ASEAN-India free trade agreement (FTA) and its impact on India: A case study of fisheries and selected agricultural products. Foreign Trade Review, 48(4), 481–497. Yean, S. T., & Yi, A. (2014). Reassessing the impact of the ASEAN-India free trade agreement. Jurnal Ekonomi Malaysia, 48(2), 99–110. Taneja, N., & Saqib, M. (2005). Non-tariff barriers & India’s exports: The case of ASEAN and Sri Lanka. Indian Council for Research on International Economic Relations (ICRIER). Working paper no.165, pp. 1–49. United Nations Conference on Trade and Development (UNCTAD). (2010). Non-tariff measures: Evidence from selected developing countries and future research agenda (New York and Geneva: United Nations, 2009).Retrieved from https://unctad.org/en/Docs/ditctab20093_en.pdf. United Nations Conference on Trade and Development (UNCTAD). (2015). International classification of non-tariff measures 2012 version. (Geneva: United Nations, 2015). Retrieved from https://unctad.org/en/PublicationsLibrary/ditctab20122_en.pdf. United Nations Economic and Social Commission for Asia and the Pacific. (2015). Emerging issues in trade and investment, volume 1 trade and non-tariff measures: Impacts in the Asiapacific region, United Nation Publication. Retrieved from https://www.unescap.org/sites/default/ files/NTM%20Flagship%20-%2016June.pdf. Vollrath, T. L. (1991). A theoretical evaluation of alternative trade intensity measures of revealed comparative advantage. Weltwirtschaftliches Archiv, 127, 265–79; Review of World Economics, 127, 265–280. Zarrilli, S., I. Musselli. (2004). The sanitary and phytosanitary agreement, food safety policies, and product attributes. In D. Merlinda & J. Nash (Eds.), Agriculture in the WTO: Creating a trading system for development, World Bank and Oxford University Press, Washington, DC.

Chapter 7

India–EU FTA: Implications for India’s Marine Products B. H. Nagoor and Shankar Eiti

Abstract With the growing trade integration of India with the world, trade in marine products, like any other sector of the Indian economy, has become exposed to heightened international competition. After being stalled for several years, recent calls were made to resume the India–EU FTA negotiations. In India, marine products trade is significant in terms of providing employment to the millions of poor people, and the EU is one of the largest trading partners of India in this sector. In this backdrop, the paper aims to assess the impact of India–EU FTA through trade and economic linkages. The paper seeks to examine the problems faced by Indian exporters of marine product, and the strategies to enhance the marine exports of India under the Indo-EU FTA. The study indicates that though the EU is a major marine export destination of India even today, but its share has been continuously declining over time. Even though the EU imposes relatively lower tariffs on India’s marine products, India faces many constraints in exporting marine products to the EU. Under the proposed India–EU FTA, the present non-tariff barriers, particularly the stringent regulations and standards, need to be addressed so as to reach a mutually beneficial solution. Keywords Marine products exports · FTA · Tariffs · Regulations and standard

7.1 Introduction Marine products exports have consistently played an important role in the Indian economy. India is one of the major producers of marine products in the world. Exports of these products form around 17% of India’s total agricultural export and around 2% of its total export. In India, the trade in marine products is significant in terms of providing employment to millions of poor fishermen and is a net foreign exchange earner to the country. These fishermen are able to generate income from the sector because several varieties of marine fish have been exported from the country, including in various forms such as chilled and dried items, fish oil, shrimp B. H. Nagoor (B) · S. Eiti Department of Economics, Karnatak University, Dharwad, Karnataka, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_7

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and prawns. Thus, from the point of view of employment and income generation, fisheries trade is significant for India (Meenakshi 2008). Fisheries and aquaculture remain an important source of food, nutrition, income and livelihoods for millions of population (Kumar et al. 2019). India’s marine export performance has been affected by the trade liberalization measures since 1991, the establishment of WTO in 1995 and India’s engagement with free trade agreements (FTAs) (Anjani 2004). The global trade environment has also undergone a drastic change after the entry of WTO as an international regulatory body for international trade of goods and services (Shinoj et al. 2009). The ongoing crisis at the World Trade Organization (WTO), the impasse in the Doha round of trade talks and limited market access opportunities have necessitated a shift to bilateral and regional free trade agreements. In relation to fisheries, discussions were held at the WTO pertaining to disciplines on fisheries subsidies, whereby member countries have aimed at defining and granting subsidies based on prohibition and elimination (Kumar et al. 2019). The FTA between India and EU is in the 16th round of negotiations and covers agriculture, marine products and investment. It is India’s most ambitious and challenging FTA to date. With 281 countries, the EU is one of the largest trading blocks and controls one-third of global trade. The minimum agreed coverage of the FTA would be 90% of all trade. Indian negotiators expect that India–EU FTA will provide Indian exporters access to EU markets. While tariffs are low in the EU market there exist several other import restrictions such as non-tariff barriers (NTBs), tariff rate quotas (TRQs), sanitary and phytosanitary (SPS) measures and tariff peaks, and domestic subsidies to protect and support their markets. Given their significance, it is important to assess the possible impact of the proposed India–EU FTA on marine products production and trade of India. The paper aims to (i) evaluate the possible impact of India–EU FTA through India and EU Trade and Economic Linkages; (ii) assess the potential impact of India– EU FTA on India’s marine trade; (iii) understand the problems the Indian marine product exporters encounter in the EU market and how these could be addressed under India–EU FTA; and (iv) the strategies to enhance the marine exports of India under the Indo-EU FTAs.

7.2 Research Methodology 7.2.1 Coverage The study is based on primary and secondary data. Interviews of the Indian exporters of marine products were conducted to find the problems that were faced in relation to SPS and technical barriers to trade (TBT), market access and domestic

1 For

analysis in this paper, the UK has been considered as part of the EU.

7 India–EU FTA: Implications for India’s Marine Products

141

subsidy-related measures. The interviews are expected to provide critical grassrootslevel inputs for Indo-EU negotiations. The major exporters from the coastal belt of Karnataka and Kerala of India were included in the survey. On the basis of the volume and value of marine products and exports by the major producers and exporters of this coastal belt, the number of sampling for the interview has been decided. Regarding the product coverage, marine products exports include fish and crustaceans, aquatic invertebrates, molluscs and others. Classification is as per the harmonized system (HS), and the data is collected from UN COMTRADE.

7.2.2 Data Collection The primary data are collected through interviews and schedule questionnaires to find the existing market access problems faced in relation to SPS and TBT measures. Secondary data pertaining to marine product exports, imports and tariffs for both India and EU were collated from the United Nations COMTRADE database, United Nations Conference on Trade and Development (UNCTAD), World Trade Organization (WTO) and European Union Commission (ECM).

7.2.3 Data Analysis In order to evaluate the economic impact of a bilateral agreement between India and the EU, and to measure the competitiveness of India’s marine exports, revealed comparative advantage (RCA), dynamic revealed comparative advantage (DRCA) and the price competitiveness measures are used for this study. For the trend analysis, compound annual growth rate (CAGR), export unit value, import unit value, export and import in quantity, value and stability of trade over a period of time are considered. For this paper, the data from 28 members of the EU have been used, including the United Kingdom (UK). Although the UK will not be part of the India–EU FTA, as and when it is signed, there might be a possibility of a separate India–UK bilateral FTA post-Brexit.

7.3 Literature Review A good volume of literature has developed in recent years, assessing the bilateral trade gains between economies. Ten Raa and Chakraborty (1991) tried to locate the comparative advantage of India vis-à-vis Europe. Sikdar (2008), in her study on free trade between India and EU, has concluded that bilateral trade has been the bedrock of the India–EU relationship right from the days of the latter’s inception. This trade has shown impressive growth over the years and at present India shares a healthy

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trade relationship with the EU. The extent of gains in this trading arrangement is as high as 78.1% for India, while for its stronger trading partner EU, it is only 3.3%. Therefore, the immediate and direct impact of Indo-EU will result in an expansion of trade between the parties. To date, there have been no particular studies assessing the possible economic impact of an India–EU FTA on the marine sector of India. Only a few studies at the macro level, i.e., assessing the impact on overall the India–EU economies in terms of costs and benefits to both the parties have been undertaken. This study contributes to the existing literature by way of bringing to fore the problems faced in exporting India’s marine products to the EU, and by assessing the possible economic impact of India–EU FTA on marine products exports from India.

7.4 India and EU Trade and Economic Linkages EU is a longstanding and a major trading partner of India. However, in recent years, the EU’s share in India’s trade has decreased, implying a decline in economic ties between India and the EU. A summary of India’s trade with the EU is given in Tables 7.1 and 7.2. The five yearly average of India’s export to the world, EU and major EU countries have been estimated in Table 7.1. The analysis of India’s export to the EU shows that in terms of absolute value, except for the year 2016, India’s total export to the EU has increased. It has increased from USD 5.97 billion during 1991–1995 to USD 51.19 billion during 2011–2015. In the year 2016, it has declined to USD 45.75 billion. It is to be noted that the year 2016 witnessed a decline in India’s total export to the world as well. India’s compound annual growth rate (CAGR) of exports (from 1991 to 2019) to the world and the EU shows that export to the world (12.54%) is much higher than export to EU (10.61%). In terms of EU percentage share in India’s total export, it is declining. The five yearly average share has come down from 25.11% during 1991–1995 to 16.95% during the years 2011–2015. However, compared to 2011–2015 (Table 7.1), during the year 2016, EU’s percentage share in India’s total export increased to 17.57%. The year 2016 witnessed a large decline in India’s export to the world. The UK, Germany, France, Belgium, Netherlands, Italy and Spain are the major trading partners of India. Together these countries account for 85–90% of India’s export to the EU. Though in terms of value, there is an increase in India’s export to these countries, but in terms of percentage share in India’s total export to the world, it has declined from 22.13% during 1991–1995 to 14.61% during 2011–2015. Among the EU members, the decline in share in India’s total export is large for Germany, UK and Italy. During 1991–1995, Germany, UK and Italy together imported 16.35% of India’s total exports to the world, however, it has decreased to 7.21% during 2011–2015 and 6.98% in 2019. The analysis of India’s export to the EU indicates that though the EU is a major export destination for India, its share in India’s total export has been continuously

65.92

169.23

301.92

260.33

294.36

322.49

323.25

Avg 2001–2005

Avg 2006–2010

Avg 2011–2015

2016

2017

2018

2019

10.61

56.00 (17.33)

57.35 (17.78)

51.17 (17.38)

45.75 (17.57)

51.19 (16.95)

34.99 (20.68)

14.92 (22.64)

8.77 (24.27)

5.97 (25.11)

India total export to EU

9.11

6.18 (1.91)

6.81 (2.11)

6.22 (2.11)

5.36 (2.06)

6.14 (2.03)

4.13 (2.44)

1.96 (2.97)

1.39 (3.84)

Belgium

Source Estimated from UN COMTRADE

12.54

36.15

Avg 1996–2000

CAGR 1991–2019

23.78

India total export to world

Avg 1991–1995

Year

10.87

5.43 (1.68)

5.28 (1.64)

5.04 (1.71)

4.87 (1.87)

5.12 (1.69)

3.18 (1.88)

1.36 (2.06)

0.84 (2.33)

0.56 (2.34)

France

7.99

8.57 (2.65)

8.95 (2.78)

8.23 (2.80)

7.18 (2.76)

7.65 (2.53)

5.27 (3.11)

2.47 (3.74)

1.85 (5.11)

1.62 (6.83)

Germany

9.27

5.19 (1.61)

5.52 (1.71)

5.66 (1.92)

4.46 (1.71)

4.93 (1.63)

3.73 (2.20)

1.74 (2.64)

1.10 (3.04)

0.75 (3.15)

Italy

13.09

8.91 (2.76)

8.66 (2.69)

5.43 (1.84)

4.87 (1.87)

7.99 (2.65)

5.28 (3.12)

1.38 (2.10)

0.83 (2.30)

0.54 (2.27)

Netherlands

12.10

4.25 (1.31)

4.10 (1.27)

3.77 (1.28)

3.36 (1.29)

3.05 (1.01)

2.18 (1.29)

1.04 (1.58)

0.52 (1.43)

0.27 (1.16)

Spain

8.75

8.80 (2.72)

9.75 (3.02)

8.95 (3.04)

8.57 (3.29)

9.22 (3.05)

6.25 (3.69)

3.15 (4.78)

2.05 (5.67)

1.51 (6.37)

UK

10.43

47.33 (14.64)

49.07 (15.22)

43.30 (14.71)

38.66 (14.85)

44.10 (14.61)

30.01 (17.74)

13.10 (19.88)

7.74 (21.42)

5.26 (22.13)

Main EU countries

11.82

8.67 (2.68)

8.28 (2.57)

7.88 (2.68)

7.09 (2.72)

7.09 (2.35)

4.97 (2.94)

1.82 (2.76)

1.03 (2.85)

0.71 (2.98)

Other EU countries

Table 7.1 India’s total export to the world and the EU countries in USD billion (figures in brackets show percentage share in proportionate to India’s total export to the world)

7 India–EU FTA: Implications for India’s Marine Products 143

45.18

84.08

265.80

453.51

356.70

444.05

507.62

478.88

14.06

Avg 1996–2000

Avg 2001–2005

Avg 2006–2010

Avg 2011–2015

2016

2017

2018

2019

CAGR 1991–2019

Source Estimated from UN COMTRADE

11.20

47.69 (9.96)

52.85 (10.41)

46.15 (10.39)

41.10 (11.52)

48.68 (10.73)

40.36 (15.18)

17.73 (21.09)

11.90 (26.34)

6.22

7.48 (1.56)

9.34 (1.84)

9.01 (2.03)

9.00 (2.52)

10.59 (2.33)

7.17 (2.70)

4.54 (5.40)

3.23 (7.15)

–

26.50

Avg 1991–1995

6.93 (26.15)

India total import India total import Belgium from the world from EU

Year

9.58

5.99 (1.25)

6.53 (1.29)

6.04 (1.36)

4.33 (1.21)

3.75 (0.83)

3.99 (1.50)

1.38 (1.64)

0.90 (2.00)

0.93 (3.52)

France

9.61

13.45 (2.81)

14.88 (2.93)

12.11 (2.73)

10.91 (3.06)

12.73 (2.81)

10.72 (4.03)

3.26 (3.88)

2.32 (5.13)

2.07 (7.82)

Germany

8.58

4.48 (0.94)

4.68 (0.92)

4.03 (0.91)

3.62 (1.02)

4.18 (0.92)

3.84 (1.44)

1.32 (1.57)

1.01 (2.24)

0.90 (3.40)

Italy

5.41

5.88 (1.23)

6.61 (1.30)

5.25 (1.18)

4.43 (1.24)

7.29 (1.61)

5.91 (2.22)

3.88 (4.61)

2.63 (5.83)

1.95 (7.37)

UK

11.19

37.28 (7.78)

42.04 (8.28)

36.45 (8.21)

32.28 (9.05)

38.54 (8.50)

31.63 (11.90)

14.38 (17.11)

10.10 (22.36)

5.86 (22.10)

Major EU countries

11.41

10.41 (2.17)

10.81 (2.13)

9.70 (2.18)

8.82 (2.47)

10.14 (2.24)

8.73 (3.28)

3.35 (3.98)

1.80 (3.98)

1.07 (4.05)

Other EU countries

Table 7.2 India’s import from world and EU countries in USD billion (figures in brackets show percentage share in proportionate to India’s total import from the world)

144 B. H. Nagoor and S. Eiti

7 India–EU FTA: Implications for India’s Marine Products

145

declining over time. In this context, the issue of how the FTA between India and the EU can enhance India’s export to the EU has been examined. The scenario of India’s import from the EU since 1991, as shown in Table 7.2, shows a similar trend. India’s import from the EU, in terms of value, increased from USD 6.93 billion during 1991–1995 to USD 48.68 billion in 2011–2015. However, in 2016, it has declined to USD 41.10 billion. In terms of EU’s percentage share in India’s total import, it is declining. The five yearly average share of India’s import from the EU has shown a downward shift from 26.15% during 1991–1995 to 10.73% during the years 2011–2015 and 9.96% in 2019. However, during the year 2016, the percentage share of the EU in India’s total import is increased to 11.52%. The year 2016 witnessed a huge decline in India’s total import from the world. India’s bilateral trade with the EU is shown in Fig. 7.1. It is seen that the balance of trade (BoT), which was unfavourable for India until 2012, has become favourable after 2012. In addition, the BoT gap is widening in favour of India since 2016. The decline of the EU’s share in India’s total import can be attributed to the rise in India’s import of petroleum products, gems and jewellery from countries other than the EU. EU is not a major exporter of petroleum products and gems and jewellery. While assessing the importance of the EU’s trade with India, it is observed that India’s share in the EU’s total trade is low. The five yearly average share has been estimated in Table 7.3. During 1991–1995, India’s share in the EU’s total export was 1.67%, and it increased to 2.30% during 2006–2010 and 2.18 during 2018. It has declined to 2.08% during 2019. Similarly, India’s share in the EU’s total import also increased from 1.45% during 1991–1995 to 1.89% during 2006–2010, to 2.35% during 2019. It shows the importance of India’s trade with the EU. 70.00

India total export to EU India's total import from EU BoT

60.00

56.15

50.00

46.53 38.29

40.00

44.71 41.10

39.29

30.00

56.00

56.28

47.69

20.00 10.00

12.62

10.13

7.81 0.00 -2.33 1996 -10.00

7.39

10.34

8.32

-1.06 1998

2000

2002

2004

2006

2008 -8.72

2010

2012

2014

2016

2018

-20.00

Fig. 7.1 India’s balance of trade with EU countries (in USD billion). Source Estimated from UN COMTRADE

146 Table 7.3 EU’s trade with India (percentage share)

B. H. Nagoor and S. Eiti Year

India’s share in EU total export

India’s share in EU total import

Avg 2001–2005

1.67

1.45

Avg 2006–2010

2.30

1.89

2011

2.54

2.30

2012

2.23

2.07

2013

2.03

2.17

2014

2.05

2.19

2015

2.09

2.28

2016

2.12

2.29

2017

2.18

2.37

2018

2.28

2.31

2019

2.08

2.35

Source Estimated from UN COMTRADE

7.5 Analysis of India–EU Marine Products Trade 7.5.1 India: Marine Products Trade Since the economic reforms of 1991, India has been reducing its external trade restrictions as a result of its large increase in its export and import share in global trade. Similarly, there has been a large increase in India’s marine trade to the world. India is one of the major marine exporting countries in the world, after China and Vietnam. India’s share in the world marine trade since 2001 has been presented in Table 7.4. This trend shows that its exports has been increasing; India’s export share in the world marine export has increased from 2.75% during 2001–2005 to 4.98% in 2014 and further increased to 5.78% in 2017. In 2018, this share decreased to 5.36, and it saw a marginal increase to 6.55% in 2019. India’s marine export share in its total merchandise exports shows that from 2001 to 2005 it hovered around 2%, thereafter and until the year 2010 it was on a decline. Since 2011, this share has been progressively increasing from less than 1% in 2008– 2010, to 2% during 2016, and 2.26% in 2017, with a marginal decline thereafter in 2018 and 2019. On India’s marine import, it can be observed from Table 7.4 that the percentage share of India in world import is minuscule. The three yearly average of India’s total and marine trade in value terms has been estimated in Table 7.5. It can be observed from Table 7.5 that India’s import has been increasing from an average USD 0.49 million during 1991–1993 to an average USD 53.36 million during 2012–2014. It has further increased to USD 98.16 million and 111.30 million during 2018 and 2019, respectively.

7 India–EU FTA: Implications for India’s Marine Products

147

Table 7.4 India’s marine trade share in the world marine trade (figures are in percentage) Year

India’s marine export share in the world marine export

India’s marine import share in the world marine import

India’s marine export share in its total merchandise export

India’s marine import share in its total merchandise import

Avg 2001–2005 2.75

0.02

2.13

0.01

Avg 2006–2010 2.28

0.05

0.96

0.01

2011

3.43

0.11

1.07

0.02

2012

3.57

0.07

1.13

0.01

2013

5.07

0.03

1.50

0.01

2014

4.98

0.05

1.69

0.01

2015

4.71

0.07

1.73

0.02

2016

4.91

0.06

2.00

0.02

2017

5.78

0.07

2.26

0.02

2018

5.36

0.08

1.98

0.02

2019

6.55

0.11

1.95

0.02

Source Estimated from UN COMTRADE

The estimated compound annual growth rate for Indian marine trade during the period 1991–2019 is given in Table 7.5. India’s marine imports registered a higher growth rate of 22.58% per annum compared to its marine export of 8.31% and merchandise imports of 14.06% during this period. This shows that India’s marine import dependency is progressively increasing. The export competitiveness of India’s marine export measured through revealed comparative advantage (RCA) has been estimated in Table 7.5. It shows that India’s marine export has international competitiveness, as RCA index value is greater than one from the year 1991 to 2015. However, when compared to the 1990s, the RCA index value is on a decline in recent years.

7.5.2 EU Marine Products Trade EU is one of the major trading group in the world. Its share in the world trade has been around 13% in the last 18 years. However, except for 2019, this share is on a decline in recent years (Table 7.6). EU’s marine trade in the world marine trade has been estimated in Table 7.6. EU’s marine trade analysis shows that the EU is the largest marine importer in the world. EU’s marine import share in the world marine import has been around 20–22% for the last 19 years. The EU is also one of the major marine exporting groups in the world and its share in the world marine export is around 4–5%.

148

B. H. Nagoor and S. Eiti

Table 7.5 India’s merchandise and marine trade (in USD million) Year

India total marine export

India total marine import

India’s merchandise export

India’s merchandise import

RCA

RSCA

Avg 1991–1993

683.07

0.49

20,282.70

22,421.97

3.80

0.58

Avg 1994–1996

1076.45

4.63

30,499.05

34,786.54

4.72

0.65

Avg 1997–1999

1132.76

11.38

34,973.68

44,621.76

4.75

0.65

Avg 2000–2002

1319.36

7.15

45,444.85

53,688.28

4.41

0.63

Avg 2003–2005

1295 0.62

15.01

78,539.17

104,137.22

2.89

0.48

Avg 2006–2008

1453.69

35.37

149,653.19

237,666.67

2.05

0.34

Avg 2009–2011

2262.61

69.29

232,885.35

359,333.33

1.75

0.27

Avg 2012–2014

4418.78

53.36

314,573.67

471,333.33

2.52

0.43

Avg 2015–2017

5449.74

67.89

273,024.14

397,167.29

3.08

0.51

2018

6253.14

98.16

322,492.10

507,615.73

3.1

0.52

2019

6179.90

111.30

323,250.73

478,883.73

2.9

0.49

8.31

22.58

12.54

14.06

CAGR (1991–2019)

Source Estimated from UN COMTRADE

7.5.3 EU–India Marine Trade Linkages EU has been one of the largest trading partners in India’s marine export. India’s marine export direction in value and quantity has been shown in Tables 7.7 and 7.8, respectively. It can be observed from Tables 7.7 and 7.8 that the EU is the second largest partner in India’s marine export. However, its share is highly fluctuating with a coefficient of variation (CV) value of 56.92% during the year 1995–1996 to 2018– 2019. It is observed that in recent years, the EU’s share in India’s export is on the decline. During the years 2010–2011 to 2014–2015, it has come down to 22.44% from 32.10% during 2005–2006 to 2009–2010. EU’s share in India’s marine export in terms of quantity and value shows that share in value is substantially higher than quantity, indicating that India’s marine export towards the EU are high valued. On the other hand, India’s marine export in quantity and value has increased towards the USA, South-East Asia and the Middle East. The share of South-East Asia in India’s marine export in value and quantity has increased from 6.89% and 10.89% during 1995–1996 to 1999–2000 to 23.34% and 36.60% during 2010–2011 to 2014–2015,

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Table 7.6 EU’s total and marine trade Year

EU’s total export share in the world total export

EU’s total import share in the world total import

EU’s marine export share in the world marine export

EU’s marine import share in the world marine import

EU’s marine export share in its total merchandise export

EU’s marine import share in its total merchandise import

2001

13.07

14.09

3.66

19.85

0.19

1.06

2002

13.51

14.06

4.04

19.92

0.20

1.05

2003

13.52

14.21

4.36

21.82

0.20

1.06

2004

13.42

14.00

4.43

21.48

0.19

0.95

2005

13.26

14.46

4.24

22.43

0.18

0.93

2006

12.65

14.73

4.18

23.78

0.17

0.93

2007

12.94

14.50

4.52

24.03

0.17

0.90

2008

12.94

14.83

4.90

23.43

0.17

0.80

2009

13.09

14.19

4.25

22.96

0.18

0.97

2010

12.01

13.42

4.28

21.94

0.19

0.91

2011

12.11

13.37

4.28

21.04

0.19

0.87

2012

12.13

12.79

4.64

19.50

0.20

0.81

2013

12.42

12.12

4.42

19.93

0.19

0.89

2014

12.21

12.17

4.24

20.31

0.20

0.97

2015

12.29

11.84

4.09

20.51

0.20

1.03

2016

12.38

12.10

4.02

21.04

0.22

1.17

2017

13.68

11.93

4.18

20.73

0.22

1.07

2018

12.24

12.22

4.24

20.30

0.21

1.00

2019

15.72

14.94

5.46

23.78

0.22

1.01

Source Estimated from UN COMTRADE

respectively. There was a further increase in this trend in 2016–2017 and 2017–2018 as well. A similar observation can be made in the case of Middle East and the USA. The analysis of India’s marine export to the EU indicates that despite being a major marine export destination for India, its share in India’s total marine export has been continuously declining over time. In this context, the question of how an FTA between India and EU can enhance India’s marine exports to the EU is examined.

7.5.4 India–EU Tariff on Marine Products Trade This section analyses the present marine tariff level of India and the EU. The simple average most-favoured nation (MFN) applied marine tariffs of India and EU are shown in Tables 7.9 and 7.10. It shows that the average MFN applied tariff of the EU is much lower than that of India. An analysis of the marine tariff structure of India

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B. H. Nagoor and S. Eiti

Table 7.7 India’s marine export direction (percentage share in total marine export to the world, in value) Year

Japan

Avg1995–1996 to 1999–2000

46.85

Avg 2000–2001 to 2004–2005

EU

China

12.40

17.18

11.66

6.89

2.39

2.62

25.94

24.52

21.38

11.16

8.79

3.19

5.03

Avg 2005–2006 to 2009–2010

15.18

14.79

32.10

14.31

9.55

4.97

9.10

Avg 2010–2011 to 2014–2015

10.80

21.39

22.44

8.09

23.34

5.59

8.35

2015–2016

8.61

28.46

20.71

4.71

24.59

5.90

7.03

2016–2017

6.83

29.97

17.98

3.50

29.91

4.78

7.03

2017–2018

6.29

32.76

15.77

3.21

31.59

4.10

6.28

2018–2019

6.29

34.84

13.38

12.06

22.76

4.26

6.41

27.20

102.79

56.92

61.19

116.26

82.18

79.21

CV (1995–1996 to 2018–2019)

USA

South-East Asia

Middle East

Others

Source Estimated from MPEDA exports

Table 7.8 India’s marine export direction (percentage share in total marine export to the world, in quantity) Year

Japan

USA

EU

China

South-East Asia

Avg1995–1996 to 1999–2000

18.94

Avg 2000–2001 to 2004–2005

9.45

18.74

33.89

10.89

3.82

4.27

13.48

11.60

20.86

33.38

11.44

3.96

5.30

Avg 2005–2006 to 2009–2010

10.77

7.17

25.76

26.30

14.27

4.52

11.22

Avg 2010–2011 to 2014–2015

8.33

9.53

18.33

10.44

36.60

5.27

11.49

2015–2016

7.97

16.25

19.70

5.29

34.77

5.70

10.32

2016–2017

6.08

16.62

16.73

4.00

42.72

4.67

9.18

2017–2018

6.22

17.99

13.82

3.61

44.78

4.52

9.07

2018–2019

6.04

20.24

11.89

16.19

32.10

4.33

9.21

14.58

87.05

38.04

41.82

98.10

58.18

69.40

CV (1995–1996 to 2018–2019)

Middle East

others

Source Estimated from MPEDA exports

and the EU shows that India imposes 29.9% of average tariffs on its marine imports and duty-free import is only 0.1% of total marine import. Whereas the EU imposes 10.33% of tariffs and duty-free import is 7.4%. In the case of India, the EU imposes 5.93% of average tariffs.

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Table 7.9 India’s tariffs and imports by product groups Product groups Final bound duties

MFN applied duties

Imports

AVG

Duty-free in %

Share in %

Animal products

100

31.1

0

0.0

0

Dairy products 100

33.5

0

0.0

0

Fruit, vegetables, plants

100

29.4

0.5

2.1

0.0

Coffee, tea

100

56.3

0

0.1

0

Cereals and preparations

100

31.3

15.4

0.4

82.6

Oilseeds, fats and oils

100

34.0

0.9

3.1

0.5

Sugars and confectionery

100

35.9

0

0.3

0

Beverages and tobacco

100

69.5

0

0.2

0

Cotton

100

6.0

80.0

0.3

99.9

Other agricultural products

100

22.3

13.6

0.5

4.8

Fish and fish products

68.6

29.9

0.1

0.0

3.7

Minerals and metals

61.3

8.5

2.0

31.4

0.1

Petroleum

0

4.2

16.7

19.8

95.0

Chemicals

89.0

8.1

0.4

10.7

2.9

Wood, paper, etc

64.2

8.9

3.5

2.0

2.4

Textiles

69.9

11.9

0

1.3

0

Clothing

58.4

15.1

0

0.2

0

Leather, footwear, etc

51.6

10.1

2.6

1.1

0.0

Non-electrical machinery

95.4

7.2

4.0

8.6

22.3

Electrical machinery

93.5

7.3

15.9

9.8

51.6

Transport equipment

70.0

24.9

3.3

5.1

1.4

Manufactures, n.e.s

43.9

8.9

5.7

3.0

21.3

Duty free in %

Source European Commission, Trade Market Access database -EU Tariffs, year 2018

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Table 7.10 EU tariffs and imports by product groups Product groups Final bound duties (Max)

MFN applied duties

Imports

AVG

Duty-free in %

Share in %

Animal products

116

15.5

28.4

0.4

7.1

Dairy products 218

35.9

0

0.0

0

Fruit, vegetables, plants

188

10.3

19.8

2.0

14.9

Coffee, tea

20

6.0

27.1

1.1

73.0

Cereals and preparations

52

12.3

13.0

0.6

30.1

Oilseeds, fats and oils

158

5.2

48.1

1.6

68.4

Sugars and confectionery

91

21.1

11.8

0.1

10.2

Beverages and tobacco

158

19.3

18.4

0.6

18.8

Cotton

0

0.0

100.0

0.0

100.0

Other agricultural products

486

3.2

65.5

0.5

66.2

Fish and fish products

26

11.6

7.4

1.6

4.5

Minerals and metals

12

2.0

50.0

16.4

69.9

Petroleum

5

2.5

33.7

12.1

98.3

Chemicals

7

4.6

22.4

11.7

49.8

Wood, paper, etc.

10

0.9

81.5

2.8

84.2

Textiles

12

6.5

Clothing

12

11.5

Leather, footwear, etc.

17

Non-electrical machinery

Duty free in %

2.1

2.6

2.1

0

5.1

0

4.1

27.2

2.7

12.1

10

1.8

24.0

11.6

48.0

Electrical machinery

14

2.5

23.9

12.9

56.1

Transport equipment

22

4.7

12.9

6.5

9.4

Manufactures, n.e.s

14

2.3

28.4

7.1

49.8

Source European Commission, trade market access database EU tariffs, year 2018

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Table 7.11 EU marine tariffs on India and other country HS code

Avg tariffs on India

0301

5.67

Avg tariffs on any other country (MFN applied) 7.88

0302

5.74

9.97

0303

5.28

9.82

0304

7.66

11.53

0305

8.50

12.00

0306

7.45

12.13

0307

3.35

8.29

0308

3.80

11.00

Average All

5.93

10.33

Source European Commission, Trade market access database on EU tariffs, year 2018

The product variety-wise tariff structure shows that India imposes 32.8% of tariffs on agricultural imports, whereas the EU imposes 10.8% of tariffs. In the case of nonagricultural imports, India imposes 10.7% of tariffs on imports, whereas the EU imposes 4.2% of tariffs. It clearly shows that under possible India–EU FTA, India may need to reduce its present high import tariffs. On the other hand, the EU’s present tariffs are already low; hence, it may not require a further reduction in tariffs. This implies that an India–EU FTA may be more advantageous to the EU rather than India. The EU has already undertaken the necessary reforms, and therefore, its adjustment costs might be much lower should it further reduce any tariffs. On the contrary for India, this cost might be higher. From the above analysis, it can be observed that EU’s marine products import tariff on India is relatively low, but the EU’s share in India’s marine products export is on a decline. Even though the EU imposes a relatively lower tariff on India’s marine products, India is facing many export constraints to export marine products to the EU. From the various studies (Datta and Chakrabarthi 2001; Henson et al. 2005; Bozby and Roberts 2011; MPEDA 2014) and discussion with major marine products exporting companies of Kerala and Karnataka, it was found that the EU has been applying restrictions on India’s marine products export. Marine products export items from India have faced diverse non-tariff barriers in the form of sanitary and phytosanitary (SPS)-related market access problems in the EU. In 1997, the EU banned fisheries products exports from India on SPS grounds. More recently, exports of Indian marine products have faced several detentions or rejections in the EU, on the grounds of use of antibiotics and bacterial inhibitors. From the available literature, it is found that SPS and TBT-related measures are major constraints for India’s marine exports. India’s fisheries sector, which has become fairly export-intensive continues to get affected by food safety regulations, faces the highest import refusals in the USA and the EU (Bozby and Roberts 2011). The study by MPEDA (2014) reveals that from 2002 to 2014, 821 consignments are rejected

154

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by EU and 421 by the USA. Such rejection of consignments raises many issues such as cost and predictability of future export. Among the EU, USA and Japan, the EU imposes significantly stricter controls than Japan or the USA. However, it is also evident that antibiotics are emerging as an issue in the USA. The EU’s requirements, perhaps, are an indicator of the food safety controls that will be required in all industrialized country markets in the future. The significant challenges for the Indian fish and fishery product sector in meeting emerging food safety requirements in the EU and USA have been particularly pronounced in Kerala. Kerala is more dependent on EU and US markets than the rest of India, and the state is dominated by exports of crustaceans and cephalopods. Historically, these problems were mainly related to US exports. However, through the 1990s, the EU’s food safety requirements related to general hygiene controls and limits on antibiotics, as well as biological and chemical contaminants, have emerged as a significant challenge. In turn, the EU has undoubtedly become the dominant driving force behind the upgrading of food safety controls within the fish and fishery products sector in both Kerala and India in general (Henson, Saqib and Rajasenan, 2005). The export to the EU still faces serious challenges due to the quality aspects raised by the importers and the characteristics of a buyer market, for example, the case of shrimp export from India which has been of serious concern (Datta and Chakrabarthi 2001). It is clear from the above studies that SPS measures have emerged as strong non-tariff barriers to marine exports from developing countries, as is also explained in the subsequent section. Indian marine exports are also facing challenges in EU, USA and Japan markets.

7.6 Interaction with Major Marine Products Exporting Companies of Kerala and Karnataka As part of the study, to understand the difficulties faced by Indian marine products exporters to the EU region, interviews were conducted for 20 major marine products exporting companies of Kerala and Karnataka. Discussions were also held with senior officials of the Marine Products Exports Development Authority (MPEDA), Kochi. The interactions with the major marine products exporting companies of Kerala and Karnataka revealed that compared to India’s other marine products export destinations, the EU’s trade regulations on food safety are more stringent. Importantly, the EU makes frequent changes in trade regulations on food safety nets. Among non-tariff barriers imposed by EU, extremely low maximum residue level (MRL) limits for fishery products creating major problems in exporting India’s marine products to the EU. MRL is the maximum amount of pesticide residue that is expected to remain on food products when a pesticide is used according to label directions that will not be a concern to human health. WTO also has trade regulations on food safety. All the member nations of WTO shall adhere to trade regulations on food safety of the WTO. However, member nations of the WTO can also have their own

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trade regulations on food safety, which are akin to their domestic food regulations, subject to certain conditions prescribed under the Agreement on the Applications of Sanitary and Phytosanitary measures. Such varied trade regulations on food safety net by trading countries make it difficult for exporters to meet the requirements of each country’s food standard and more difficulty to meet the requirements with frequent change in trade regulations by some of the developed countries particularly the EU. India has raised concerns over the EU’s practice of setting MRL limits to default (extremely low) levels, which it says creates major barriers for the exports of rice, peanuts, chillies, spices, tea, fruits (like grapes), vegetables and sea food. Most of these exported items do not find a market in the EU countries as it is not possible to meet the (low) default level for pesticides. Canada raised similar concerns as well stating that the EU should implement its SPS measures in a way that does not unjustifiably restrict international trade. However, the EU has brushed aside charges made by countries including India at the WTO against its extremely low MRL limits for pesticides in food products. The low MRL limits are alleged to create non-tariff barriers for exports. The bloc pointed out that WTO rules allow it to deviate from international standards if a health concern is raised by the risk assessment body (Business Line 2020). EU further insists on more documentation, certifications and labelling on exportable marine products from India. This increases the administrative burden on marine producers of India. At each stage from production, processing, packaging and until it reaches the buyer in the EU, documents are required to be produced to trade and health authorities of EU. A minor error in any of the stages amounts to rejection by the EU authorities. There are many instances of rejection of Indian marine products at various ports of EU countries. For a rejection in any of the port in EU, an alert will be given in all ports of EU regarding the rejected marine product of an exporting company. If frequent rejection occurs, such a company will be deregistered by the EU trade authority. In this regard, the Indian exporting companies of marine products are required to take two to three samples of each consignment for it to be thoroughly tested in approved laboratories in India and inspected by EU representatives in India. Even with such a procedure of testing and approval by Indian authority and inspection by the EU representative, additional testing by the EU authorities on few samples drawn from each consignment at the EU ports is also conducted. If any contaminant is found in drawn samples, the whole consignment is rejected. The apprehension of the Indian marine exporters is that despite inspections by the Indian authority and the EU representative in India, rejection by the authorities at the EU ports, puts them at a great loss. There have also been instances of rejections on the grounds of variation in temperature due to problem with the supply of electricity and plugging in the shipment. Discussions with the MPEDA officials reveal that India mainly trades with EU, USA and Japan. Compared to the USA and Japan, the EU’s trade restrictions on marine products are more stringent. The EU insists on more documentations such as labelling, adherence to labour laws time and date of catching, processing and packing the fish, environmental-related certificates and illegal and unregulated fishing (IUU).

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EU’s MRL on marine products is already low, and there are plans to lower it further. Though the EU trade norms are more stringent, however, over a period, by adopting such norms, the Indian exporters have become globally more competitive. Presently, India is exporting marine products to the EU under the generalized system of preference (GSP), under which the EU imposes lesser duties. However, Thailand, Indonesia and Vietnam are also export their marine products to the EU under the GSP, which is affecting India’s marine products export to the EU. With reference to NTBs, the EU insists more documentations and its pre-shipment inspections are more elaborate and time-consuming than other countries. However, there seem to be no issues with valuation, clearance and rules of origin. In case of technical barriers to trade, unlike the USA, the EU does not impose any antidumping duties. However, the EU trade norms are more stringent on regulations and standards, such as the MRL, and require many certifications. The registration procedures of EU for exporting firm are well laid out and are more capital-intensive. Such registration procedures by the EU have become major entry barriers for new entrants in the market. Under the proposed India–EU FTA, the present non-tariff barriers, technical barriers to trade, particularly the stringent regulations and standards needs to be addressed by way of mutual recognition of agreement on testing and conformity assessment procedures. The above discussion on India’s marine products exports in the EU reveals that the major challenge for Indian marine products export is the non-tariff measures imposed by the EU countries. Even though for India, the EU is a major export destination of marine products, it faces several constraints to these products to the EU. Marine products export items from India have faced diverse SPS-related market access problems in the 28-nation bloc. Exports of Indian marine products have faced several detentions or rejections in the EU, on the grounds of use of antibiotics and bacterial inhibitors.

7.7 Conclusions The stalemate Doha round of trade talks at the WTO and unaddressed market access issues have necessitated a shift to bilateral and regional free trade agreements. An FTA between India and the EU is likely to take place, especially with the recent calls to resume the negotiations. With the growing trade integration of India with the world, trade in marine products, like any other sector of the Indian economy, has become exposed to heightened international competition. Analysis of India’s marine external trade reveals that India is a major marine trading player in the world. The percentage share of its marine exports in the global marine export is progressively increasing. Though the domestic demand for marine products is increasing, the imports of marine products have not affected the domestic market. The EU is the largest marine products importer in the world, and India has a huge potential to increase its marine output. A proposed India–EU FTA may enhance India’s marine products export to the EU. India and the EU have been trading in

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marine products for long, and India has made commendable progress in meeting EU’s conditions with respect to quality aspects of fishery exports. Since the EU is market for high-valued fishery products, and India is market for low-valued fishery products, a proposed India–EU FTA may not affect the domestic marine market. The discussion with major marine products exporting companies of Kerala and Karnataka reveals that, compared to India’s other marine product export destinations, the European Union’s trade regulations on food safety are more stringent. Importantly, the EU’s frequent changes in trade regulations on food safety nets. Under possible India–EU FTA, the present non-tariff barriers, technical barriers to trade, particularly the stringent regulations and standards (MRL), need to be addressed. The India–EU FTA provides India with the opportunity to negotiate a better deal on market access for SPS and TBT issues for its marine product exports to the EU. Note This is part of ICSSR Project carried out in the Department of Economics, Karnatak University, Dharwad. India.

References Bozby and Roberts. (2011). Food trade and food safety violations: What can we learn from import refusal data? American Journal of Agricultural Economics, 93(2), 560–565. Business Line. (2020). All its measures are aligned with agreed global standards, says Brussels. Business Line Daily News Paper February, 21. Datta, K. S., & Milindo, C. (2001). A perspective on global competitiveness of Indian fish—The case of shrimp. In: S. Shyam (Eds.), Proceedings of the National Conference on fisheries Economics Research and Education in India: An Overview, Mumbai, 2001. Henson, S., Saqib, M., Rajasenan, D. (2005). Impact of sanitary measures on exports of fishery products from India: The case of Kerala. World Bank Agriculture and Rural Development Discussion Paper. Kumar, A. (2004). Export performance of indian fisheries: Strengths and challenges ahead. Economic and Political Weekly, 39(38), 4264–4270. Kumar, R., Kumar, R. R., Stauverman, P., Chakradhar, J. (2019). The effectiveness of fisheries subsidies as a trade policy tool to achieving sustainable development goals at the WTO Marine. Policy Journal, 100. Meenakshi, R. (2008). Fisheries trade in India: Understanding potentials and barriers working paper (741), Department of International Economics, Norwegian Institute of International Affairs. MPEDA. (2014). MPEDA: An overview. The Marine Products Export Development Authority. Raa, T., & Chakrabort. (1991). An equilibrium analysis of regional industrial diversification. Regional Science and Urban Economics, 24(1), February 1994, 115–133. Shinoj, P., Ganesh, B. K., Joshi, Datta, K. (2009). Export of India’s fish and fishery products: Analysing the changing pattern/composition and underlying causes. Indian Journal of Agricultural Economics, 64(4). Sikdar, C. (2008). Free trade between India and the European union—15: A theoretical and empirical analysis. The IUP Journal of Applied Economics VII, I, 28–60.

Part III

Indian Agriculture: Cross-Cutting Issues

Chapter 8

Evaluating the Role of Subsidies in Sustainable Agriculture: A Case Study of India Anjali Tandon and Roopali Aggarwal

Abstract The issue of agricultural subsidies is contentious due to the complexities that occur through changes in production, consumption and trade patterns. The changes are often criticised for their trade-distortion effects and implications for sustainability. Among other factors, the impact also depends on the type of support provided. Particularly, subsidy on inputs is often used to promote or alter production patterns. In the process, over-application of specific inputs tends to ignore the associated environmental externalities. Although the emission impact of input overuse in agriculture is well acknowledged and attributed to the subsidised nature of inputs, the relationship remains yet to be appraised in the existing literature. This contribution attempts to fill the void by analysing the impact of inputs—measured through their use and the associated subsidy—on net returns for the farmer and the emissions from the agricultural sector. The results are helpful not only to quantify the relationship between subsidised inputs and emissions from agriculture but also to assess the relative impact of inputs in causing emissions from the agricultural sector. A key finding is that the gains in net returns from the use of subsidised inputs are more than offset by the adverse effects of emissions. Furthermore, the use of fertilisers has a more substantial contribution to emissions, in comparison to the effect of electricity consumption on emissions. In view of the relatively significant impact of fertilisers, the use of inorganic inputs demands attention through policy re-orientation. The cash transfers, if linked to the use of organic fertilisers, will be more effective in incentivising the farmers to switch. Simultaneously, the business model for fertiliser manufactures should also be revisited early to transform into semi-organic production arrangements. Keywords Agricultural emissions · Agricultural inputs · Agricultural subsidies · Fertiliser · Electricity · Sustainable agriculture · India A. Tandon (B) Institute for Studies in Industrial Development (ISID), New Delhi, India e-mail: [email protected] R. Aggarwal Jawaharlal Nehru University, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_8

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8.1 Introduction India’s economic planning through the formulation of the centralised 5-year-plans has supported growth in an integrated manner. The development strategy resulted in an increase in India’s national and per capita incomes, a remarkable achievement as the world’s third-largest economy and home to 17.5% of the world population. It has transformed from an agrarian to a service-led economy. Despite the declining significance in Gross Domestic Product (GDP), the total production as well as per capita availability of food grains has increased over time, mainly due to expansion of the cropped area and intensive cropping, which were initiated during the green revolution period. Agriculture occupies around 60% of India’s land, with most of the agricultural households having marginal and small lands under their possession. As an occupation, it is viewed with higher risk and uncertainty due to increasing incidence of farmer suicides that have been attributed to farmer indebtedness and volatile ecological climate. Agriculture has remained a vital source of employment for both males and females, although with a declining significance alongside an increasing livelihood diversification index (Mehta 2009). The National Sample Survey Office (NSSO) survey also points out that in 2004–05, more than half of the rural households have been agricultural, with as many as 62% engaged as self-employed in agriculture, while the remaining are employed as casual labourers in agriculture. Thus, agricultural growth would be a critical factor in improving the livelihood prospects of a majority of rural households. The growing fragmentation of farm holding is evident from the increase in the number of households possessing land less than 1 hectare (ha) from 51.4 million in 2002–03 to almost 62.6 million in 2012–13.1 During the same period, the number of households possessing medium-sized farms decreased from 4.3 million to 3.3 million, while the number of large-sized farms of more than 10 ha declined by half, from 0.8 to 0.4 million. With a small piece of land, most farmers can only accomplish subsistence farming, implying the household engages to mostly produce for self-consumption, with minimal quantity left for commercial sale. These households are also largely dependent on rainfall for water supply, which can affect the yield and output due to extreme conditions of flood or drought. A disproportionately high employment with low sectoral growth has led to negative employment elasticities in the agriculture sector (Planning Commission 2014). This reflects on low productivity of the sector, which has also been a reason for farmer suicides. Raising agricultural productivity is the key to output growth, income and food security. However, achieving increased productivity through a sustainable approach is a challenge.

1 Calculations

respectively.

based on NSSO survey 59th and 70th rounds for the years 2002–03 and 2012–13,

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8.2 The Sustainability Issue of Input Use The income of a farmer is dependent on yield and prices. Although the use of key inputs—fertilisers, electricity and water (irrigation) is a characteristic of the cropping practise, farmers often tend to overuse specific inputs, which are subsidised, to realise higher output yields. However, in the more recent years of the post-Green revolution period, productivity gains have either stagnated or declined, indicating diminishing returns to input use (Kumar and Mittal 2006). This is attributed to the continuous excessive use of inputs. For instance, problems of water-logging and soil salinity develop due to over-irrigation, which in turn disturbs the nutrient balance in the soil. Similarly, use of fertilisers beyond the recommended level also damages soil health. Overuse of agrochemicals, such as fertilisers, further increases their presence in environmental sinks with severe implications for quality and safety of life. For instance, nitrogen fertilisation increases emissions of harmful gases into the environment. The use of inputs in more than recommended quantities and the inefficiency in the application of inputs contribute to damages. These are realised in the form of point source damages such as degradation in soil health, contamination and loss of water sources leading to non-point source damages on human and animal health. Similarly, excessive use of water, particularly in a water deficit country like India, not only leads to a hydro-crisis but also drains soil nutrients and salts through return flows. Flooding of farms is also known to be a key contributor to methane emissions, which further contribute to climate change due to their high warming potential. These conditions lead to extreme climate changes such as drought and floods, adversely impacting the farmer. The plateauing of productivity gains in agriculture has led to a dangerous treadmill effect, with farmers using additional doses of inputs to enhance or maintain productivity (Schutter and Frison 2017). As a result, it is challenging to be productive while being sustainable in the agriculture system. The necessity to adopt environmentally sustainable practises is well recognised as a key to Sustainable Development Goal (SDG)—2, and its Target 2.4 stated as follows: “By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters and that progressively improve land and soil quality”.2 Despite changing conditions of Indian agriculture in terms of the sustainability challenge, the incentives for farmers have not been revised to suit the present context. These have resulted in misaligned policies, which have promoted continued and excessive use of specific agricultural inputs, primarily including fertiliser, water and power.

2 Sustainable

Development Goals, Goal 2: Zero Hunger, UNDP, https://www.undp.org/content/ undp/en/home/sustainable-development-goals/goal-2-zero-hunger/targets.html.

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Input subsidies are recognised as the most expensive aspect of the Indian agricultural policy (Grossman and Carlson 2011). The farmer subsidies, as a proportion of production costs, are high for fertiliser, irrigation and electricity, relatively more for the latter two. In addition to rising subsidy bills, pricing policies are also resulting in diverting resources from other important aspects such as investments in the agriculture sector, adversely affecting the long-term growth of the sector. The small and marginal farmers are beneficiaries of high proportions of fertiliser subsidy. However, since most of the production is for self-consumption, these farmers do not benefit from higher output prices (Sharma and Thakkar 2010). Therefore, their consciousness to improve fertiliser efficiency is likely to be low, because they thrive on subsistence agriculture, look for benefits on the input side, which are primarily in the form of subsidies. The incentive for income gains from output prices is relatively weak due to small land size and lack of participation in the downstream supply chain. Low input prices encourage skewed application, which affects soil, water, ecosystems while also breeding greenhouse gases (GHGs). This ultimately threatens the viability and sustainability of agriculture. The agricultural input costs include expenses towards the use of seed, pesticide, fertiliser, irrigation, power for irrigation, diesel, repair and maintenance of machinery and equipment, land and labour. Inputs such as fertiliser, irrigation and electricity are subsidised to lower costs for farmers. Fertiliser and electricity are particularly recognised for their high energy intensity, which poses challenges for sustainable agriculture growth and achieving SDGs. The environmental implications of energyintensive inputs (fertiliser), energy using services (electricity) and exploitation of water resources are often quantified from the quantum of corresponding GHG emissions, which have established climate change effects on the magnitude and nature of growth. For instance, the frequency of extreme weather events—droughts, floods and irregular erratic rainfall—is expected to increase (World Bank 2012). These disasters are expected to have the greatest impact in rain-fed areas, further threatening the sustainability of agricultural growth and incomes. Given this background, this chapter tries to analyse the impact of agricultural subsidies and input use on net returns to the farmer. The analysis also attempts to quantify the relationship between input use, subsidy and related emission in the Indian agriculture sector. The methodological approach makes use of time-series regression analysis to investigate the net effect of input use and the related/associated emission on net returns to the farmers. It will be interesting to see if the gain in net returns to farmers from the use of subsidised inputs is actually reversed, or perhaps more than offset, due to emissions originating from their (over) use.

8.3 Methodology and Data The methodological approach makes use of the time-series regression analysis. The time-series regression analysis is based on alternate specifications with explanatory variables—subsidies on fertilisers, electricity and irrigation, their consumption in the

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agricultural sector, along with rainfall, net irrigated area, irrigation intensity, total emissions, emissions from rice cultivation and emissions from synthetic fertiliser use. Additionally, food grain availability, food grain yield and capital investment in agriculture and irrigation have been included as control variables. The response variables include value of agricultural output, net returns of the farmers and emissions from the agricultural sector. The details of these variables are provided in Table 8.1. The empirical analysis studies the impact of agricultural inputs and related subsidies on net returns of the farmers as well the GHG emissions. The period covers 27 years of post-liberalisation, from 1991–92 to 2017–18. Most of the explanatory variables are measured in physical quantities. The emissions are measured in physical quantities such as gigagrams (Gg), electricity measured in gigawatt-hours (GWh) and fertiliser use is measured in lakh metric tonnes (LMT). The economic series of monetary variables is adjusted for inflation. This is required to see the impact of input quantities on output, returns and emissions. The nominal variables have been converted into real ones using GDP deflators with 2011–12 as the base year. All the quantity variables have been converted into per hectare terms by dividing them by the net sown area. However, in the case of net returns, the per hectare values are based on the all-India area under selected food grains. The data are extrapolated to fill the gap in a particular year.3 All specifications are in the double log form, which means the coefficients are nothing but the elasticities. Net returns from food grain production have been calculated as the difference between the value of the output of the food grains and the cost of cultivation. Food grains include paddy, jowar, bajra, maize, ragi, wheat, barley, gram, urad, moong, lentil, arhar and sugarcane. Costs are defined in various ways. The analysis makes use of the C2 cost, which includes all paid-out costs, rent paid for leased-in land, interests and imputed value of family labour. The cost values are available crop-wise for major producing states in per hectare terms. Thus, these have been converted into absolute value by dividing with the state-wise area under the particular crop. The values are then aggregated to get the all-India representative value of the cost of food grain production. The data on the area under crops have been taken from the Ministry of Agriculture. The value of output data has been collected from National Accounts Statistics (NAS) of Government of India (2007b, 2012, 2018). Although the per hectare value of product and by-product is provided in the cost of cultivation also but since NAS provides more nationally represented data, the value of output has been sourced from NAS. However, for cost data, there is no other source, and therefore we rely on the cost of cultivation data as provided by the Ministry of Agriculture. Following models have been implemented using STATA:

3 Extrapolation

has been done using the trend command in MS-Excel if data for previous years of the given series are not available and using the forecast command if data for following years of the given series are not reported.

Thousand CO2 eq

Thousand CO2 eq

Thousand CO2 eq

Total emissions from agriculture

Emissions from rice cultivation

Emissions from synthetic fertilisers

Fertiliser subsidy

Rs million

Rs crore

Net returns

Explanatory variables

Rs crore

Units

GDP agriculture

Dependent variables

Variables

Table 8.1 Description of variables used in empirical analysis

1991–92 to 2016–17

1991–92 to 2014–15

1991–92 to 2014–15

1991–92 to 2014–15

1996–97 to 2015–16

1991–92 to 2012–13

Availability

Union budget (various years), Government of India (2007a), India Stat

FAO Stat

FAO Stat

FAO Stat

Value of output from National Accounts Statistics, Cost of cultivation from the Ministry of Agriculture

Economic and Political Weekly Research Foundation (EPWRF)

Source

(continued)

Consists of nitrous oxide gas from synthetic nitrogen additions to managed soils

Consists of methane gas from the anaerobic decomposition of organic matter in paddy fields

Contains all the emissions produced from enteric fermentation, manure management, rice cultivation, synthetic fertilisers, manure applied to soils, manure left on pastures, crop residues, cultivation of organic soils, burning of crop residues, burning of savanna, energy use

Imputed by calculating the difference between the value of output from food grains and cost of cultivation (C2) of food grains

GDP at factor cost accruing to the agriculture sector

Details

166 A. Tandon and R. Aggarwal

Rs crore

Rs crore

Lakh Metric Tonnes

GWh

Percentage

Rs crore

Rs crore

Thousand hectare

Percentage

mm

Kg per year

Kg per hectare

Irrigation subsidy

Electricity subsidy

Total fertiliser use

Electricity consumption in agriculture

Share of electricity consumption in agriculture

Capital investment in irrigation

Total investment (agri + irri)

Net irrigated area

Irrigation Intensity

Annual rainfall

Per capita food grain availability

Food grain yield

Table 8.1 (continued)

1991–92 to 2016–17

1991–92 to 2017–18

1992–93 to 2015–16

1991–92 to 2014–15

1991–92 to 2013–14

1991–92 to 2015–16

1991–92 to 2015–16

1991–92 to 2014–15

1991–92 to 2014–15

1991–92 to 2016–17

1993–94 to 2008–09

1993–94 to 2008–09

EPWRF

EPWRF

EPWRF

Authors’ calculation

Ministry of Agriculture

EPWRF

EPWRF

EPWRF

EPWRF

Annual report of Dept of fertiliser 2013–14, Fertiliser Association of India

Government of India (2007a)

Government of India (2007a)

Overall rainfall (June–May)

(Gross irrigated area/Gross cropped area)*100

Combined expenditure of central and state governments

Combined expenditure of central and state governments

Summation of physical consumption of nitrogen, phosphorous and potash

Includes all subsidies to Electricity Boards and Corporations. Separate estimates of electricity subsidy accountable exclusively to the agricultural sector are not available

The rates for supply of water to farmers are kept low as a matter of policy, resulting in losses to the Government irrigation system. The excess of operating costs over the gross revenue is treated as imputed irrigation subsidy

8 Evaluating the Role of Subsidies in Sustainable Agriculture … 167

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 GDP agri = β1 + β2 ln(Food grain yield)t NSA t   Electricity consumption in agri +β3 ln + NSA t     Annural rainfall Total fertilizer use β4 ln + β5 ln NSA NSA t t   Net returns ln Area under food grains t 

ln

(8.1)

= β1 + β2 ln(Per capita food grain availability) t +β3 ln(Share of electricity consumption in agri)t   Electricity subsidy in agri +β4 ln NSA t   Annual rainfall +β5 ln NSA t   Irrigation subsidy +β6 ln NSA t    Fertitizer subsidy Total fertitizer use +β7 ln + β8 ln NSA NSA t t  Net returns = β1 ln Area under food grains t   Total agri input subsidy +β2 ln + NSA t   Total emissions from agriculture β3 ln NSA t   Annual rainfall +β4 ln NSA t   Total emissions from agri ln = β1 + β2 ln (Food grain yield)t NSA t   Electricity consumption in agri +β3 ln NSA t     Annual rainfall Total fertitizer use +β4 ln + β5 ln NSA NSA t t

(8.2)



(8.3)

(8.4)

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 Total emissions from agri = β1 + β2 ln (Food grain yield)t + NSA t     Electricity subsidy in agri Irrigation subsidy β3 ln + β4 ln (8.5) NSA NSA t t   Fertilizer subsidy +β5 ln NSA t   Emissions from rice cultivation ln = β1 + β2 ln (Net irrigated area) t NSA t   Irrigation subsidy +β3 ln (8.6) NSA t   Capital investment in irrigation +β4 ln t NSA   Emissions from synthetic fertilizer ln = β1 + β2 ln (Net irrigated area)t + NSA t   Total fertilizer use β3 ln NSA t (8.7)   Emissions from synthetic fertilizer = β1 + β2 (Net irrigated area) t + ln NSA t   Fertitizer subsidy β3 ln NSA t (8.8) 

ln

To check whether each model has been specified correctly, the Breusch– Pagan/Cook–Weisberg test for heteroscedasticity, variance inflation factor (VIF) for multicollinearity and Breusch–Godfrey LM test for autocorrelation have been referred. Wherever there is a problem of heteroscedasticity, robust standard errors have been calculated.4

8.4 Empirical Results The empirical exercise uses time-series regression models to analyse the relationship between key input use, which has an emission impact, and the value of agricultural output, net returns to farmers and related emissions. Inputs such as electricity, fertiliser and irrigations are directly associated with agricultural emissions and are therefore of key interest for the analysis. Equation (8.1) of the preceding Sect. 8.3 4 “Robust”

standard errors provide under heteroscedastic conditions.

unbiased

standard

errors

of

OLS

coefficients

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in the paper shows the relationship between the value for agricultural output per hectare and the use of inputs such as electricity, rainfall and fertiliser. As expected, the results show a positive and significant influence of electricity consumption (per ha) and fertiliser consumption (per ha) on the value of agricultural output (per ha). It is found that one percent additional use of electricity and fertiliser inputs tend to increase the value of output by 0.5% and 0.3%, respectively (refer Table 8.2 for results of the regression equations specified in Sect. 8.3). However, the effect of rainfall on output per ha is found to be negative indicating the uncertainty associated with the rainfall since the variability in rainfall may have harmful effects on the production and therefore on the value of output (Aggarwal 2008; Singh et al. 2014). The water requirement varies from crop to crop, and it is important to fulfil these requirements for a higher value of output in a timely and adequate manner for better output. The determinants of per hectare net returns are discussed in Eqs. (8.2) and (8.3). Equation (8.2) includes subsidies on key inputs—fertilisers, irrigation and power; as well as their consumption indicator together with per capita food grain availability. The coefficients show a positive and significant impact of the share of electricity consumption in agriculture (27%) and per hectare fertiliser subsidy (6.6%), while the negative and significant impact of per capita food grain availability (−26%). Higher availability of food grain implies better supply, which might affect the prices of food grains through demand and supply mechanism leading to price suppression for the producers resulting in lower net returns per hectare. It is important to note that irrigation and electricity subsidies are found insignificant. This could be attributed to the extrapolation methodology used in the computation of the missing values for the variables. Data extrapolation techniques have been used due to non-availability of disaggregate subsidy data for the agricultural sector. To overcome these data issue, the regression specification of Eq. (8.3) considers an aggregate of all the input subsidies. This specification shows the impact of per hectare total input subsidies, per hectare total agricultural emissions and per hectare annual rainfall on the net returns per hectare. The total input subsidy variable now has a positive and statistically significant impact, contributing to a 5.2% increase in net returns per hectare. The specification in Eq. (8.3) includes agricultural emissions as an additional explanatory variable. Agricultural emissions are noted to have a strong and negative influence on net returns to the farmer as can be seen from the corresponding (elasticity) coefficient value of 54.7, with a negative sign. This indicates income reducing effect of agricultural emissions. The income supporting effect of rainfall can be attributed to lower expenses of the farmer for rent/purchase of irrigation equipment. The next two Eqs. (8.4) and (8.5) analyse the effect of key input use and their respective subsidies on total emissions from agriculture (per hectare). Yield has been used as a control variable in both these regressions to control for all the other input variables, such as seeds, pesticides, manure, etc., that do not directly or notably contribute to agricultural emissions. As per the specification in the fourth regression, emissions are more elastic to fertiliser use than compared with electricity consumption as noted from the coefficient values of 0.2 and 0.1, respectively. However, rainfall, as a natural source of irrigation, has a controlling effect on emissions. This is attributed to the absorption of atmospheric emissions such as nitrous

26.987** (10.016) −1.999 (1.414)

Per ha electricity subsidy in agriculture

0.541* (0.076)

0.704* (0.212)

−25.767** (10.657)

2

1

−54.739** (20.500)

5.234*** (2.574)

3

Per ha net returns

Per ha GDP agriculture

Dependent variables

Share of electricity consumption in agriculture

Per ha electricity consumption in agriculture

Electricity/power related

Per ha total emissions from agriculture

Emission related

Per ha total agri input subsidy

Subsidy

Food grain yield

Per capita food grain availability

Output related

Explanatory variables

Table 8.2 Regression results

0.069* (0.024)

0.078 (0.067)

4

0.017** (0.008)

0.324* (0.071)

5

Per ha total emissions from agriculture 6

Per ha emissions from rice cultivation 7

(continued)

8

Per ha emissions from synthetic fertilisers

8 Evaluating the Role of Subsidies in Sustainable Agriculture … 171

0.644

0.385

27 0.980

27

0.948

27

5.35

0.036** (0.013)

0.039 (0.036)

0.499

27

2.99

0.321* (0.094)

0.077* (0.026)

−0.051* (0.018)

0.987

27

−9.06

0.426* (0.068)

1.391* (0.182)

0.970

27

−17.69

0.053** (0.027)

2.151* (0.183)

Note 1. All variables are taken in natural log form, except irrigation intensity 2. *, ** and *** indicate statistical significance at 1%, 5% and 10% levels, respectively 3. Figures within the parentheses are standard errors 4. The sample size of 27 observations is mainly due to data limitations 5. Although R-square corresponding to Eqs. (8.2), (8.3) and (8.6) is relatively low, some explanatory variables are found to be statistically significant

0.985

R-square

27

7.21

Number of observations

−136

1.41

27

Constant

0.169* (0.025)

−2.385 (6.380)

−0.070*** (0.037)

0.284* (0.094) 383.02

17.384*** (9.976)

Per ha total fertiliser use

0.611 (5.113)

7.529 (9.831)

6.604** (2.479)

−0.255*** (0.144)

Per ha fertiliser subsidy

Fertiliser related

Irrigation intensity

Per ha total investment (agri + irri)

Net irrigated area

Per ha irrigation subsidy

Per ha annual rainfall

Per ha capital investment in irrigation

Irrigation related

Table 8.2 (continued)

172 A. Tandon and R. Aggarwal

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oxide in rainwater. Research has shown that rainfall leads to leaching out of artificially added nitrogen (fertiliser) from the soil. This results in lower nitrogen content in the soil, in turn reducing nitrogen emissions (Geng et al. 2017). The fifth regression model analyses the impact of the input subsidies on emissions. The results of Eq. (8.5) again show that electricity and fertiliser subsidies have a positive and significant impact on the emissions with elasticity of 0.02 and 0.036, respectively. As noted in an earlier result, the fertiliser subsidy has a relatively stronger influence in enhancing emissions, due to the emission-intensive nature of the chemical fertilisers. Emissions from rice cultivation occur due to methane formation from standing water (Garg et al. 2000). Further, as per the agricultural census, the proportion of irrigated area under rice cultivation has increased from 55% in 2000–01 to 60% in 2015–16 (Government of India 2001, 2016). The regression results of Eq. (8.6) show a statistically significant impact of investment in irrigation, irrigation subsidy and net irrigated area on the emissions from rice cultivation. However, per-hectare irrigation subsidy and net irrigated area are contributing to emissions by 0.08% and 0.32%, respectively, while capital investment in irrigation has a controlling effect on emissions. One of the reasons is a higher emitting factor of irrigated areas than that of rain-fed areas (Ananda et al. 2004). Thus, as irrigated area increases under rice cultivation, methane emissions also increase. However, investing in better farming practices such as utilisation of less water in rice cultivation, more productive cultivars and efficient use of fertilisers would help in improving productivity as well as mitigating emissions (Garg et al. 2000). The next two models specified in Eqs. (8.7) and (8.8) describe emissions from synthetic fertiliser usage (per ha) as a function of variables such as fertiliser use, fertiliser subsidies, yield, net irrigated area and irrigation intensity. The net irrigated area has a positive and significant impact on emissions from fertiliser applications, in both the specifications with fertiliser consumption as well as with fertiliser subsidy, respectively. The rise in emissions due to net irrigated area is as high as 1.4% and 2% under alternate specification, respectively. This further validates the findings of an earlier specification on emissions, although in the context of emissions from rice cultivations.

8.5 Conclusion The issue of agricultural subsidies is contentious due to the complexities that occur through the changes in production, consumption and trade patterns. The changes are often criticised for their trade-distortion effects and implications for sustainability. Among other factors, the impact also depends on the type of support provided. Particularly, subsidy on inputs is often used to promote or alter production patterns. In the process, over-application of specific inputs tends to ignore the associated environmental externalities. The input-intensive agricultural practices of the past have been instrumental in achieving productivity gains in Indian agriculture. However, overuse of subsidised inputs such as industrial agrochemicals (fertilisers), power and diesel

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have contributed to environmental damages in the form of poor soil conditions, depleting water tables and increasing emissions. Continued applications of inputs have shown diminishing returns, thus limiting the increase in both farmer incomes and agricultural output. Since agriculture is the key source of livelihood for rural India, sustaining productivity is a major concern and challenge. Although the emission impact of the input overuse in agriculture is well acknowledged and attributed to the subsidised nature of inputs, the relationship remains yet to be quantified in the existing literature. The present analysis attempts to fill the void by analysing the impact of inputs— measured through their use and the associated subsidy—on net returns to the farmers and on the emissions from the agricultural sector. The empirical results of the timeseries analysis show that electricity and fertiliser usage have emission-enhancing effect of the agricultural practices. The results are robust for the quantity of input use and subsidy on inputs, as well in alternate specifications of the model. Furthermore, the subsidy on irrigation has an increasing effect on the emissions from rice cultivation. Although our results show a positive effect of inputs—both quantity and subsidy values—on the value of output and net returns to the farmer; an alternate specification established the negative effect of the emissions from agricultural inputs on returns to the farmer. These results are broadly in sync with the findings of an earlier study by Fan et al. (2007), which recognised diminishing returns to agricultural GDP from government subsidy expenditure on fertiliser, irrigation and power; even though not in a context of related emissions. A key finding from our analysis is that the gains in net returns from the use of subsidised inputs are more than offset by the adverse effects of emissions. The rising trend in agricultural emissions has an underlying increase in output from the use of subsidised inputs, which have disturbed the soil balance and water tables, both of which have implications on productivity. The results are helpful not only to quantify the relationship between subsidised inputs and emission from agriculture but also to establish the relative impact of inputs in causing emissions from the agricultural sector. The use of fertilisers has a more substantial effect on emissions, in comparison to the effect of electricity consumption on emissions. The results are validated both in terms of input use as well as subsidy accrued on each of the two inputs. The strong and depressing influence of emissions on farmers’ returns draws attention to the existing subsidies and cropping practices. Therefore, it is vital to encourage farmers to use these inputs judiciously, not only in their economic interest but also for the sustainability of agriculture, which is deeply interlinked to the environment and climate change. In view of the relatively significant emisison impact of fertilisers, the continued application of inorganic inputs demands corrective measures through policy reorientation. In an attempt to encourage switching away from excessive dependence on inorganic fertilisers, the government has opted for Direct Benefit Transfers (DBT). Recently, 14 states have implemented the system of fertiliser distribution through DBT from January 1, 2018. The policy decision is attempted to address the skewed use of fertilisers, which is generally driven by the relative price difference in nutrients.

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Nevertheless, shifting towards organic fertilisers seems to be a plausible solution in the medium to long run. Although fertiliser use is inevitable, choosing an optimum combination with organic fertilisers will help mitigate the emission and subsidy impact of synthetic fertilisers. The cash transfers, if linked to the use of organic fertilisers, will be more effective in incentivising the farmers to switch from inorganic fertilisers and the cultivation of water-intensive crops, which require a high dosage of fertilisers. Simultaneously, the business model for fertiliser manufactures should also be revisited early to transform into semi-organic production arrangements by encouraging them through subsidy in capital equipment for organic production. The measures would also contribute towards mitigtaing climate change impact and also in achieving the nationally determined commitments (NDCs) of the Government.

References Aggarwal, P. K. (2008). Global climate change and Indian agriculture: Impacts, adaptation and mitigation. Indian Journal of Agricultural Sciences, 78(10), 911–919. Ananda, S., Dahiya, R., Talyan, V., & Vrat, P. (2004). Investigations of methane emissions from rice cultivation in Indian context. Environment International. De Schutter, O., & Frison, E. (2017). Modern agriculture cultivates climate change—We must nurture biodiversity. Global Development, The Guardian. Fan, S, et al. (2007). Investment, subsidies, and pro-poor growth in rural India. IFPRI Discussion Paper 716. IFPRI, Washington D.C. Garg, A., Bhattacharya, S., Shukla, P., & Dadhwal, V. (2000). Regional and sectoral assessment of greenhouse gas emissions in India. Atmospheric Environment, 35(2001), 2679–2695. Geng, S., Chen, Z., Han, S., Wang, F., & Zhang, J. (2017). Rainfall reduction amplifies the stimulatory effect of nitrogen addition on N2 O emissions from a temperate forest soil. Scientific Report, 7, 43329. Government of India. (2001). Agricultural Census Database 2000–01. Department of Agriculture and Cooperation. https://agcensus.nic.in/. Government of India. (2007a). Agricultural Statistics at a Glance. Ministry of Agriculture & Farmers Welfare, New Delhi: Government of India. Government of India. (2007b). National Accounts Statistics. MOSPI. Government of India. (2012). National Accounts Statistics. MOSPI. Government of India. (2016). Agricultural Census Database 2015–16. Department of Agriculture and Cooperation. https://agcensus.nic.in/. Government of India. (2018). National Accounts Statistics. MOSPI. Grossman, N., & Carlson, D. (2011). Agriculture Policy in India: The Role of Input Subsidies. USITC Executive Briefings on Trade. Kumar, P., & Mittal, S. (2006). Agricultural productivity trends in India: Sustainability issues. Agricultural Economics Research Review, 19(Conference No.), 71–88. Mehta, R. (2009). Rural livelihood diversification and its measurement issues: Focus India. In Wye City Group on Rural Statistics and Agricultural Household Income, Second Annual Meeting, 11–12 June, FAO, Rome. Planning Commission. (2014). Data-book compiled for use of planning commission. New Delhi: Government of India. Sharma, V. P., & Thaker, H. (2010). Economic policy reforms and Indian fertilizer industry. CMA Publication No. 233.

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Singh, S. K., Singh, K. M., Singh, R. K., Kumar, A., & Kumar, U. (2014). Impact of rainfall on agricultural production in Bihar: A zone-wise analysis. Environment & Ecology, 32(4A), 1571–1576. World Bank. (2012). India: Issues and priorities for agriculture. https://www.worldbank.org/en/ news/feature/2012/05/17/india-agriculture-issues-priorities.

Web References https://www.epwrfits.in/. Accessed 18 Aug 2018. https://www.fao.org/faostat/en/. Accessed 20 Aug 2018. https://www.indiastat.com/default.aspx. Accessed 14 Aug 2018. https://eands.dacnet.nic.in. Accessed 10 Aug 2018. https://www.indiabudget.gov.in/previous_union_budget.php. Accessed 30 Sept 2018. https://www.undp.org/content/undp/en/home/sustainable-development-goals/goal-2-zero-hunger/ targets.html. Accessed 21 Dec 2019.

Chapter 9

The Role of Sustainability and Policy Measures in Export Performance Shubham Kumar and Tapas Kumar Giri

Abstract There have been significant changes in the international trade policy regime in recent years, along with an increasing emphasis on policy alignment and sustainability-related issues. The paper aims to empirically examine the role of sustainability and policy measures in influencing export performance. The study uses the stochastic frontier approach to estimate gravity equation on the export performance of 10 leading world exporters from the Asia Pacific Economic Cooperation (APEC) region over the time period 2012–2017. While the absolute difference in real exchange rates shows trade-inhibiting effects, estimates for reduced tariffs and interdependence among economies suggest trade-enhancing effects and significance in all specifications. There is a conspicuous difference in the export performance from the perspective of intra-regional and inter-regional trade. The study underscores the important role of regional trading blocs in policy alignment and sustainable development. Keywords Export performance · Sustainability · Trade policy · Stochastic frontier approach · Trade efficiency

9.1 Introduction International trade is one of the main drivers for economic development. Trade brings a variety of choices and quality for consumers, efficiency in firms and competition to the local producers. The expansionary fiscal policies and structural reforms in countries all around the world are pushing for upswings in exports as well as outputs simultaneously. The revival in global demand and acceleration in global growth, in principle, increases export performance. Table 9.1 presents the annual percentage S. Kumar (B) · T. K. Giri Indian Institute of Management, Shillong, Meghalaya, India e-mail: [email protected] T. K. Giri e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_9

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Table 9.1 Annual percentage change in merchandise trade volume and real GDP 2014

2017

2018

2.68

2.51

1.79

4.65

3.0

Developed economies

2.10

2.30

1.10

3.50

2.1

Developing and emerging economiesb

2.74

2.44

2.29

5.66

3.5

Volume of world merchandise tradea

2015

2016

Exports

North America South and Central America and the Caribbean Europe Asia

4.62

0.78

0.58

4.16

4.3

−2.13

1.84

1.92

2.94

0.6

1.61

2.93

1.14

3.47

1.6

4.52

1.46

2.30

6.66

3.8

−0.96

5.52

2.56

2.26

2.7

Developed economies

3.40

4.30

2.00

3.10

2.5

Developing and emerging economiesb

2.42

0.56

1.92

7.23

4.1

North America

4.26

5.40

0.06

4.00

5.0

Other regionsc Imports

−2.71

−6.36

−6.80

3.98

5.2

Europe

3.03

3.71

3.12

2.53

1.1

Asia

3.72

3.98

3.49

9.58

5.0

South and Central America and the Caribbean

0.48

−5.62

0.16

0.91

0.5

Real GDP at market exchange rates

2.74

2.75

2.30

3.01

2.9

Developed economies

1.96

2.27

1.61

2.30

2.2

Other

regionsc

Developing and emerging

economiesb

4.28

3.68

3.61

4.32

4.1

North America

2.55

2.70

1.53

2.35

2.8

South and Central America and the Caribbean

0.86

−0.93

−2.15

0.99

0.6

Europe

1.95

2.35

1.93

2.64

2.0

Asia

4.15

4.21

4.11

4.54

4.3

Other regionsc

2.46

1.14

2.19

2.05

2.2

a Average

b Includes

Source World Trade Statistical Review, 2018; Note of exports and imports; the Commonwealth of Independent States (CIS) including associate and former member States; c Other regions comprise Africa, Middle East and Commonwealth of Independent States (CIS)

change in the world merchandise trade volume and real gross domestic product (GDP) over the time period 2014–2017 for different regions. During 2016, the growth rate in world merchandise trade volume dropped from 2.5 to 1.8% because of the continuous shrinking of exports to North America, South and Central America and the Caribbean regions. However, Asia witnessed the strongest growth of 6.7%. North America (4.2%) rebounded strongly in the merchandise exports during 2017 as the dollar value of world merchandise exports grew by 11%. Figure 9.1 plots the dollar value of total exports of the ten leading exporters in 2017 globally. China, Germany and the USA are the top leading exporters followed by Japan and South Korea.

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2500 2000 1500 1000 500 0

Fig. 9.1 Leading world exporters in 2017 (In US$ billions). Source UN COMTRADE

Recently, restrictive and protectionist policies, as well as tightening of monetary policies have become the popular instruments in international trade policy regime. As a result, standards and regulations have emerged as the prime obstacles to market access, especially for the emerging economies. These obstacles have become implicit and the counterfactual to the globalisation and liberalisation arguments of international trade. For example, with falling tariffs as a result of multiple rounds of multilateral trade negotiations, and post-2008 global economic recession, non-tariff measures (NTMs) have come to the forefront of trade policymaking, often to protect domestic producers from imports. NTMs play a key role in increasing the domestic prices, altering the demand curve and responsiveness of imports (Deardorff and Stern 1997). A wide array of instruments in terms of policy measures such as trade defence measures and sustainability-based measures like health and environmental protection can be applied under NTMs as technical barriers to trade, which are WTO compliant (UNCTAD 2010). The impositions of restrictions through NTMs fragment the export performance for the most vulnerable economies as the share in world merchandise exports for the least developed economies came down and stayed below 1% in the last 3 years. For example, USD 23 billion of export, accounting for 15% of their total exports, is lost by the 48 least developed economies because of failing on at least one of the NTMs (World Economic Forum 2016). The negative economic impact of such NTMs has become almost twice in comparison to that of tariffs. However, tariffs and NTMs have continued as instruments of protection for the developed economies. The recent trade wars between such countries have put tariff escalation to the centre of action in the Asia Pacific region. One such example is between the USA and China. The onset of the trade war started with imposing tariffs of USD 50 billion of goods on either side, which subsequently led to the trade war escalation when USA prompted to impose additional tariffs of USD 200 billion on Chinese goods (The New York Times 2018).

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In 2018, for example, the USA imports USD 564 billion worth of Chinese goods while China imports USD 121 billion worth of US goods. Therefore, China can only levy additional tariffs on around USD 100 billion of goods only. China may shift to NTMs to escalate the rift, as it had done the same earlier with Japan and South Korea. The multidimensional issues pertaining to NTMs have direct and indirect linkages with the delivery of Sustainable Development Goals (SDGs). For example, the Trade Analysis and Information System (TRAINS) database developed a concordance matrix that reflects 119 entries of which 42 entries show a direct impact on SDGs (e.g., ending hunger, health, sustainable production and consumption). One of the principal objectives of promoting international trade through economic integration and international cooperation is to eradicate poverty and achieve prosperity in low-income countries. International trade policies related to standards and regulations compliance and transparency can help to ensure sustainable development and to boost growth further. International trade policies should assimilate SDGs in order to align with the objectives of the World Trade Organisation (WTO) to foster stable and equitable trading. The promotion of sustainable production and to create a market demand for sustainable products has met an innovative market-based approach in terms of Voluntary Sustainability Standards (VSS) system (Komives and Jackson 2014). VSS are norms and standards that are used to ensure that a product in question is produced, processed or transported in accordance with certain sustainability metrics, such as environmental impacts, basic human rights, labour standards, and gender equality. The demand for compliance with such standards is driven by exports, and about 500 VSS are applied to key export products such as organic agri-foods. In growing dominance towards regionalism over multilateralism, the role of regional trade agreements has become very important in international business. Many studies (Wilson 2015; Lee and Cheong 2017) have noted the importance of regional trade blocs in contributing to increased exports and thus to economic development. The role of regional trade blocs has become prominent in creating fast-pace growth for the economies in recent times. For example, the creation of regional blocs such as Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), Regional Comprehensive Economic Partnership (RCEP) and Free Trade Area of the Asia-Pacific (FTAAP) could play an important role in this regard. The unprecedented rise of Asian economies like Hong Kong, Japan and South Korea was due to their participation in regional trade blocks (Lee and Cheong 2017). Wilson (2015) argued that the Asia-Pacific Region is actively indulged in making mega-regional trade agreements since 2010. Asia Pacific Economic Cooperation (APEC) is one such regional economic forum that aims to promote inclusive and sustainable growth by accelerating regional economic integration. APEC is one of the key regional blocs in the world from the viewpoint of international business. Figure 9.2 presents the share of exports of the 10 leading exporters in the APEC region, including India to total world exports. The leading exporting countries that are also part of the APEC Region generally have a high share of exports in the region with leading the trend. The share of exports in the APEC region is clear evidence of the central role of regional blocs in the export performance. Figure 9.3 plots the time trend of the share of exports of the

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181

2500

2000

1500

1000

500

0

APEC

WORLD

Fig. 9.2 Exports in APEC region by the 10 leading exporters in 2017 (in US$ billions). Source Authors’ calculation, UN COMTRADE Netherlands

Italy

France

Germany

UK

USA

China

South Korea

Japan

Mexico

100 90 80 70 60 50 40 30 20 10 0 2012

2013

2014

2015

2016

2017

Fig. 9.3 Percentage share in exports in the APEC region. Source Authors’ calculation, UN COMTRADE

ten leading exporters in the APEC region. The general conclusion is the increasing share of exports in the APEC region except for Mexico. The paper contributes to international business literature in two distinctive ways. First, stochastic frontier analysis is applied to estimate the export frontier for the group of 10 leading exporters of the world in the Asia Pacific Economic Cooperation(APEC) region including India over the time period 2012–2017. Further, the efficiency scores are generated from the stochastic frontier approach. There are recent

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studies (Ravishankar and Stack 2014; Asche et al. 2015; Demir et al. 2017) in a similar approach, which examined the determinants of export performance using a stochastic frontier approach to estimate the gravity equation and trade efficiency. Second, the role of sustainability and policy variables are the focus of attention. This approach considers the variables applied in international economics literature such as real exchange rate as a vital tool in industrial policy, especially for emerging economies (Damill et al. 2015; Sequeira 2016) and included some new variables as proxy indicators of sustainability and policy characteristics for exporter as well as importer countries. The remainder of the paper is as follows: Sect. 2 discusses the literature review, Sect. 3 explains the data sources and rationale, and the methodology applied for the analysis, Sect. 4 notes the empirical results and discussions and Sect. 5 provides the concluding remarks.

9.2 Literature Review In international economics literature (Bhagwati 1964; Krugman 1993; Feenstra 2015), there are evidences of the international economy showing less resemblance with a perfectly competitive market, optimal resource distribution and competitive advantage. In imperfect market conditions, international trade is driven by firms’ heterogeneity (Melitz and Redding 2014), increasing returns to scale (Krugman 1991), political nature of international business (Boddewyn and Brewer 1994) and declining returns on innovation (Bonaiuti 2018). In economic development literature, there are wide discussions on the relationship between exports and economic development. Many studies (Feder 1983; Bodman 1996) support the export-led growth argument, whereas a few studies accept it with some threshold levels or within the limited sample (Ghartey 1993), while others (Kunst and Martin 1989; Greenaway and Sapsford 1994) reject the export-led growth hypothesis. However, the neoclassical view of the international trade theory views in favour of export-led growth, based on the growth records of Asian newly industrialized economies like Singapore, Republic of Korea and Thailand (Giles and Williams 2000). In the ecological economics literature, there are many studies, which address the issues like social responsibility, differences in international environmental standards and regulations, and North–South environmental conflicts (Proops et al. 1999; Bhagwati and Srinivasan 1995; Muradian and Martinez-Alier 2001). There is a strong link between environmental enhancement, social cohesion and international trade liberalisation (Kirton and Maclaren 2018). For example, Proops et al. (1999) consider the effects of international trade on the ecological footprint in closed as well as open economies, using input–output analysis. Therefore, international business is increasing focus on poverty eradication and social responsibility paradigms. Kolk (2016) examined the changing role of international business in the last five decades

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from the historical perspective and subsequently identified three subthemes; environment, ethics and sustainable development. There are many targets within the Sustainable Development Goals (SDGs) framework, which is explored in international business practices. Some of the key issues addressed in international business practices through Multinational Enterprises (MNE) are poverty, inequality, energy and strong institutions that directly address SDG 1 (No Poverty), SDG 7 (Affordable and Clean Energy), SDG 10 (Reduced Inequalities), SDG 13 (Climate Action) and SDG 16 (Peace, Justice and Strong Institutions) respectively (Kolk et al. 2017). However, the development of the international trade regime in the current scenario depends on partnerships for the goals (SDG 17). There is a need for strong commitment and comprehensive partnerships between governments and institutions to foster global economic growth within a sustainable development framework. Such objectives will directly depend upon the delivery of coherent policies in international finance, Information and Communications Technology (ICT), capacity building, trade and accountability. In international trade, the developing countries have remained in trade surplus to the rest of the world. However, the least developed countries’ trade share has come down from 1.1% of global trade in (2007) to 0.97% in 2015 and remained at such low levels till 2017, primarily due to the fall in international commodity prices (WTO 2018). However, in the last 15 years, the total exports from the least developed countries have almost doubled, primarily due to a massive rise in demand and price for natural resources metals and fuels. Kirton and Maclaren (2018) noted the interlinks between the sustainable development goals and international trade. The role of environment and related policies play a crucial part in the current form of obstacles, standards and regulations. There is wide literature on the role policy variables and ecological footprints in affecting the export performance (Damill et al. 2015; Kolk 2016; Kirton and Maclaren 2018). Damill et al. (2015) argued that the high growth period of Argentina during 2003–2008 was a result of the macroeconomic policy approach of preserving a stable and competitive real exchange rate. Sequeira (2016) examined the gains of tariff liberalisation schemes on trade elasticities, reduction in briberies and trade costs in the Southern Africa region. However, the literature is scant on the role of sustainability variables along with policy variables in affecting the export performance. Therefore, our paper fills this gap by applying a stochastic frontier approach to gravity equation for the 10 leading exporters in the APEC region, including India over the 2012–2017 period.

9.3 Data and Methodology The panel dataset consists of bilateral trade flows of the 10 leading exporters to the major trading partners of the Asia Pacific Economic Cooperation (APEC) including India over the time period 2012–2017. The assumptions made for any cross-country study are that these countries have different economic structure, manufacturing productivity and production technology (Shan and Sun 1998). The time-series analysis considers these effects, unlike cross-sectional data analysis. The data for annual

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bilateral exports are obtained from UN COMTRADE database and the data for GDP at constant year 2010 USD prices, the worldwide weighted mean of applied tariff rates, total merchandise exports to low- and middle-income countries and share of exports as a percentage of GDP are obtained from World Development Indicator (WDI), The World Bank. The data for the organic area as a percentage share of total farmland are obtained from the Research Institute of Organic Agriculture (FiBL) Statistics of key indicators on organic agriculture worldwide. The data for NTMs are obtained from UNCTAD TRAINS database through the integrated trade intelligence portal. The data for consumer price index-based on Real Effective Exchange Rate (REER) are obtained from the Darvas (2012) database, which covers REER for 178 countries, including all the countries in our panel dataset. Data for distance and official common language are obtained from CEPII database. All the continuous variables are taken in natural log form for the analysis. The empirical evidences of relationship between economic size, distance and other variables are estimated by many models. The Gravity Model of trade (Tinbergen, 1962) considers the positive relationship between the economic sizes of the two countries and the negative relationship between their geographic distance and bilateral international trade to predict the bilateral trade potential. T rade = (β1 G D Pit + β2 G D P jt + β3 trade_costi j ) + εi j

(1)

where, G D Pit and G D P jt are the GDP (economic size) of the exporter and importer countries, respectively, and trade_costi j is the trade cost at a given point of time and εi j is the error term. and,   trade_cost = f distancei j

(2)

where, distancei j is the geographical distance between the trading partners. The empirical gravity model does not take relative trade costs, trade barriers and overall resistances for exporting and importing countries. Anderson and Wincoop (2003) explained the effect of importer and exporter specific drivers such as access to market and trade liberalisation in trade flows. Anderson and Wincoop (2003) used the multilateral resistance to measure the price raising effects in trade. Multilateral resistances are the resistances experienced by the countries involved in bilateral trade from the entire export and import market. The gravity model literature includes many dummy variables like common border (McCallum 1995), common colony (Head et al. 2010) and common language (Frankel et al. 1995) as variables which either induce as trade-inhibiting or trade-enhancing effects to the bilateral trade. However, there are some drawbacks like heteroscedastic residuals, deviation from correct predictive abilities of maximum trade between the countries and effect of multilateral resistances on trade (Kalirajan 2007; Ravishankar and Stack 2014). The Stochastic Frontier Analysis (Aigner et al. 1977) addresses these issues and estimates the bilateral trade values which are close to free trade estimates and assess the further possible trade expansion. Stochastic Frontier Analysis (SFA) is used to estimate

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the maximum value of bilateral trade and to calculate the degree of inefficiency (Ravishankar and Stack 2014). Armstrong et al. (2008) argue that the SFA approach is applied to measure the regulatory and policy reforms. The model specification of our analysis for the stochastic frontier estimation is given by, E x por t Per f or mance =β0 + β1 G D Pit + β2 G D P jt + β3 Distanceit + β4 Comlangi j + β5 N T M j + β6 T ari f f it + β7 V SSi + β8 D R E Ri jt + β9 ScT radei + β10 E x pL Mi − u i j + vi j

(3)

where, G D Pit and G D P jt are the GDPs of the exporting and importing countries for a given year, Distanceit is the geographic distance between the exporting and importing countries, Comlangi j is the dummy variable for institutional proximity, which equals to one when the exporting and importing countries have the same official common language, N T M j is the total non-tariff measures applied on multilateral as well as bilateral trade by the importing country, T ari f f i is the worldwide weighted mean of applied tariffs on all products of the exporting country for a given year, which acts as a proxy for openness and transparency, V SSi is the proxy variable for Voluntary Sustainability Standards, which is the share of total farmland under organic farming for the exporting country, ScT radei is the variable for share of total exports as a percentage of GDP of the exporter and E x pL Mi is the variable for share of exports to the low- and middle-income countries, which acts a proxy for interdependence between the exporting and the poor countries worldwide. There is a lag length of 1 year in E x pL Mi to accommodate the delayed responsiveness in demand due to exports to the low- and middle-income countries. The variable D R E Ri jt is the absolute difference between the real effective exchange rates of the exporting and importing country for a given year, which acts a proxy for relative price movements between the two countries. There are two error terms in the equation u i j and vi j . The first error term is the stochastic error term for inefficiency, and the second term is normally distributed double-sided error term.

9.4 Results and Discussions The results of the summary statistics of all the variables of our model specification are presented in Table 9.2. The mean logarithmic value of total exports has remained around 22.30 across the time period 2012–2017 for all the top ten leading exporters in the world with a standard deviation of 1.95 to all the major trading partners in the APEC Region including India. The mean GDP value of exporting countries is 28.73 with a small standard deviation of 0.88 suggests larger economies are the part of the cluster of biggest exporting partners. On the contrary, the standard deviation of the mean value of importer GDP is 1.59, larger than exporting country GDP within the range (23.31, 30.48). The proximity variables, distance and dummy variable common

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Table 9.2 Summary statistics Variables

Mean

Standard deviation

Minimum

Maximum

22.30

1.95

14.41

26.79

Exporter GDP

28.73

0.88

27.46

30.48

Importer GDP

27.20

1.59

23.31

30.48

Distance

8.98

0.64

6.31

9.87

Common language

0.11

0.31

0.00

1.00

Worldwide weighted mean of tariff

0.86

0.56

0.02

2.16

Voluntary sustainability standards

0.47

1.27

−1.61

2.72

Export to low- and middle-income countries

2.97

0.78

0.77

3.97

Difference in real exchange rate

0.15

0.13

0.01

0.70

Non-tariff barriers

6.33

1.51

1.10

8.66

Share of export as a percentage of GDP

3.43

0.52

2.45

4.46

Dependent variable Export value Market size variables

Proximity variables

Sustainability variables

Policy variables

Source: Authors’ calculation

language have mean values of 8.98 and 0.11, respectively. The sustainability variables, the worldwide weighted mean of the applied tariff as an indicator of openness of the economy and SDG 17 has a mean value of 0.86 with a high standard deviation of 0.56 suggest inequalities in the openness and transparency in the leading global exporters (Table 9.2). The share of organic farmland in total farmland as a proxy variable for voluntary sustainability standards is quite low 0.86, and this indicates the lack of awareness for exports in organic agricultural products. The interdependence between big economies and economies in transition can be measured by the share of global exports to lowand middle-income countries. The mean value share of export to low- and middleincome countries as a percentage of GDP is 2.97 within the range (0.77, 2.97). The real exchange rate is one of the main indicators of the macroeconomic environment and industrial policy, especially for emerging economies. The mean value of the absolute difference of the real exchange rate between the exporter and importer is 0.15, with a standard deviation of 0.13. NTMs are one of the key policy variables in the international business regime, and share of export as a percentage of GDP indicates the dependence of an economy on international business, and thus it becomes an

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important policy variable. The mean value of NTMs is 6.33 and Export as a percentage of GDP is 3.43 with standard deviations 1.51 and 0.52, respectively. The results from the stochastic frontier analysis, including other specifications like time-effects and country-effects are presented in Table 9.3. The parameter estimates for the exporter GDP and importer GDP are positive and significant for all the specifications. Bigger economies like China, the USA and Germany have better export competitiveness due to factors like technology and innovation, institutional capabilities and strong financial markets. Table 9.3 Stochastic frontier specification of leading exporters and APEC region countries export determinants Variables

(1)

(2)

(3)

(4)

Exporter GDP

0.795***

0.952***

0.688***

1.040***

(0.08)

(0.07)

(0.20)

(0.095)

Importer GDP

0.712***

0.293***

0.772***

0.7836***

(0.03)

(0.12)

(0.03)

(0.03)

Distance

−0.918***

−0.865***

−0.622***

−0.805***

(0.10)

(0.07)

(0.10)

(0.10)

0.654***

0.244***

0.732***

0.497***

(0.20)

(0.14)

(0.21)

(0.19)

−0.474***

−0.377***

−0.217***

0.089

Common language Difference in real exchange rate

(0.08)

(0.08)

(0.08)

(0.09)

Share of export as percentage of GDP

0.640***

0.746***

0.0915

0.487***

(0.12)

(0.10)

(0.14)

(0.11)

Non-tariff barriers

−0.007

−0.398**

−0.026

−0.005

(0.04)

(0.17)

(0.03)

(0.04)

Worldwide weighted mean of tariff

−0.051***

−0.009

−0.128***

−0.058**

(0.03)

(0.02)

(0.03)

(0.03)

−0.154***

−0.156***

−0.003

0.014

(0.04)

(0.03)

(0.06)

(0.04)

Export to low- and middle-income countries

0.503***

0.494***

−0.125

0.350***

(0.07)

(0.05)

(0.18)

(0.08)

Intercept

−15.27***

−11.58***

−29.32***

−24.34*** (3.28)

Voluntary sustainability standards

(3.15)

(3.23)

(6.55)

σu

0.81

0.51

0.79

0.79

Wald chi square

813

2316

1011

992

Number of observations

1170

1170

1170

1170

Note Standard errors are shown in parentheses ***Significance at 1%, **significance at 5% and *significance at 10% level

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The estimates for distance are negative and significant suggest trade-inhibiting effects and rising cost trade cost effect on trade due to increasing distance. The coefficient estimates for common language as the proximity variable are positive and significant for all the specifications. Except in column (4), the estimates for the difference in the real exchange rate between the countries are negative and significantly suggest some degree of misalignment in the price movements of the two countries leading to trade-inhibiting effects for exports. The sustained depreciation in the comparative real exchange rate will act as a trade-enhancing variable in export performance. The success of many Asian and South American economies are examples of how real exchange rate could impact the export performance, by managing their cyclical swings in external financing and promoting economic development (Guzman et al. 2018). Except in column (3), the share of export as a percentage of GDP is positive and significantly suggests a positive association between GDP and rise in exports. Except in column (2), the estimates for NTMs are not statistically significant in affecting the export performance. The estimates of NTMs in column (2) are negative and significant suggest trade-inhibiting effects of NTMs on exports. Except column (3) and column (4), the estimates for the share of organic farmland of total farmland are negative and significant. The worldwide weighted mean of applied tariff is negative and significant for various specifications except column (2). The proxy variable for interdependence between the economies, the share of export to low- and middle-income countries is positive and significant for specifications except column (3). The results suggest that the interdependence between economies, whether with low- and middle-income economies or with developed economies, brings positive effects to export performance. Overall, the empirical results of the stochastic frontier analysis provide a reasonable estimation of the policy as well as sustainability variables on the export performance of the 10 leading exporters to the APEC Region including India during 2012–2017 time period. Table 9.4 shows the trade efficiency scores for every distinct bilateral pair, averaged over the time period 2012–2017. Few countries exhibit a high degree of trade association with the leading exporters over the time period 2012–2017. Hong Kong, Singapore and South Korea have the maximum trade efficiency among the countries in the APEC Region with the leading exporters. Australia, Mexico, Malaysia and Thailand show a mediocre level of trade efficiency with the leading export countries. Philippines, Japan, Russia and Indonesia perform the worst in the trade efficiency matrix for all the exporting countries. Within the context of intra-APEC Region trade and inter APEC Region trade, many interesting results are emerging. Chile and USA are exhibiting positive export performance within APEC Region only whereas Australia and Malaysia are exhibiting positive export performance with outside APEC Region. China has the best export performance, whereas the Netherlands has the worst export performance in the APEC Region. Mexico has the maximum variance in the export performance, having maximum trade efficiency with USA and Canada while showing almost zero trade efficiency with Brunei and Indonesia. Overall, the export performance in the APEC has low mean efficiency

0.1638

0.0961

0.0804

0.1513

0.0923

Mexico

Malaysia

New Zealand

Peru

Philippines

0.0965

0.1150

0.1600

0.1502

0.0229

0.0470

0.0221

0.0387

0.0913

0.0568

0.0355

–

0.0174

0.0491

0.1581

0.0386

0.0387

0.0331

0.0055

0.0557

Japan

0.2337

0.0869

0.0454

0.1615

0.0302

0.0524

0.0513

0.0396

0.0679

0.0862

–

0.0103

0.0300

0.0452

0.1504

0.0309

0.0684

0.0283

0.0079

0.0611

South Korea

0.0528

0.7909

0.0585

0.1200

0.0109

0.0173

0.0542

0.0190

0.0430

–

0.1157

0.0486

0.1120

0.0110

0.1327

0.0812

0.0770

0.1250

0.0044

0.0528

Mexico

0.0994

–

0.0923

0.1541

0.0153

0.0424

0.0590

0.0262

0.1290

0.2419

0.1389

0.0688

0.0238

0.0393

0.1852

0.0992

0.1057

0.0212

0.0243

0.0509

USA

0.0688

0.0852

0.0660

0.1455

0.0436

0.0454

0.0287

0.0604

0.0963

0.0781

0.1122

0.0454

0.0346

0.0301

0.1292

0.1243

0.0659

0.0369

0.0139

0.1054

Germany

0.0537

0.0423

0.0531

0.2190

0.0195

0.0440

0.0126

0.0451

0.0718

0.0366

0.0558

0.0302

0.0217

0.0337

0.1915

0.0502

0.0338

0.0096

0.0043

0.0542

France

0.0282

0.0376

0.0583

0.1081

0.0157

0.0109

0.0122

0.0399

0.0696

0.0209

0.0812

0.0289

0.0172

0.0158

0.1691

0.0582

0.0361

0.0184

0.1153

0.0554

Britain

Note China, Japan, South Korea, Mexico and USA are part of the APEC Region as well as top leading world exporters

0.2565

0.0489

South Korea

Vietnam

0.0492

Japan

0.2993

0.0651

India

0.1155

0.0962

Indonesia

USA

0.4102

Hong Kong

Thailand

–

China

0.0895

0.2812

Chile

0.1171

0.0997

Canada

Singapore

0.0412

Brunei

Russia

0.1406

Australia

China

Table 9.4 Trade efficiency scores estimates from the SFA estimation

0.0577

0.0731

0.0491

0.0982

0.0351

0.0280

0.0390

0.0547

0.0492

0.0690

0.0701

0.0371

0.0257

0.0277

0.2630

0.0445

0.0576

0.0356

0.0133

0.1022

Italy

0.0451

0.0343

0.0356

0.2059

0.0199

0.0220

0.0174

0.0412

0.0465

0.0408

0.0617

0.0191

0.0148

0.0180

0.0972

0.0333

0.0304

0.0230

0.0109

0.0613

Netherlands

9 The Role of Sustainability and Policy Measures … 189

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S. Kumar and T. K. Giri

scores and trade integration. Second, the role of regional integration is an important characteristic in affecting export performance. In addition, the role of proximity variables becomes crucial in affecting the export performance.

9.5 Concluding Remarks The expansionary fiscal policies and tightening monetary policies are affecting the export performance in many ways (WTO 2018; Guzman et al. 2018). The role of sustainability variables, as well as policy variables, has become prominent in pushing the export performance, especially for emerging economies (Damill et al. 2015; Sequeira 2016). The study examined the role of sustainability variables as well as policy variables for the 10 leading exporters during 2012–2017 in the Asia Pacific Economic Cooperation (APEC) region using stochastic frontier analysis method. The results show trade-enhancing and significant estimates for all specifications. The results indicate that the reduction in the absolute difference of real exchange rate and worldwide weighted applied tariff brings trade-enhancing effects and contribute to economic development by improving export performance. The economic size, as well as proximity variable, brings trade-enhancing effects for economies, suggests homogeneity as an important factor in international trade. Distance still acts as a significant and trade-inhibiting factor for export performance. In terms of trade efficiency, the results show some interesting characteristics. First, the role of regional trading blocs is prominent and thus presents a strong premise for the context of trade-enhancing effects of better partnerships, collaboration and policy alignments. Second, the countries in the APEC region, which are showing maximum trade efficiency, are also the top exporters, of which some are the leading exporters like South Korea. Third, there is low mean trade efficiency in the APEC region with the leading exporters and thus suggest high export potential and trade expansion. The objectives of sustainable development goals will help to improve the export performance by raising the openness, transparency and interdependence between economies. The future study may focus on the role of country-specific variables such as institutional and governance prudence for sustainable development. The role of NTMs at the sectoral level should be examined, as there are unequal effects on export performance.

References Aigner, D., Lovell, C. A. K., & Peter, S. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37. Anderson, J. E., & Van Wincoop, E. (2003). Gravity with gravitas: A solution to the border puzzle. American Economic Review, 93(1), 170–192. Armstrong, S., Drysdale, P., & Kalirajan, K. (2008). Asian trade structures and trade potential: An initial analysis of South and East Asian trade.

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Asche, F., Bellemare, M. F., Roheim, C., Smith, M. D., & Tveteras, S. (2015). Fair enough? Food security and the international trade of seafood. World Development, 67, 151–160. Bhagwati, J. N. (1964). The pure theory of international trade: A survey. The Economic Journal, 74(293), 1–84. Bhagwati, J. N., & Srinivasan, T. N. (1995). Trade and the environment: Does environmental diversity detract from the case for free trade? Boddewyn, J. J., & Brewer, T. L. (1994). International-business political behavior: New theoretical directions. Academy of Management Review, 19(1), 119–143. Bodman, P. M. (1996). On export-led growth in Australia and Canada: Cointegration, causality and structural stability. Australian Economic Papers, 35(67), 282–299. Bonaiuti, M. (2018). Are we entering the age of involuntary degrowth? Promethean technologies and declining returns of innovation. Journal of Cleaner Production, 197, 1800–1809. Damill, Mario, Frenkel, Roberto, & Rapetti, Martín. (2015). Macroeconomic policy in Argentina during 2002–2013. Comparative Economic Studies, 57(3), 369–400. Darvas, Z. (2012). Real effective exchange rates for 178 countries: A new database. Deardorff, A., & Stern, R. M. (1997). Measurement of nontariff barriers. Demir, M. A., Bilik, M., & Utkulu, U. (2017). The impact of competitiveness on trade efficiency: The Asian experience by using the stochastic frontier gravity model. Eurasian Journal of Economics and Finance, 5(4), 1–15. Feder, G. (1983). On exports and economic growth. Journal of Development Economics, 12(1–2), 59–73. Feenstra, R. C. (2015). Advanced international trade: Theory and evidence. Princeton University Press. Frankel, J., Stein, E., & Wei, S. J. (1995). Trading blocs and the Americas: The natural, the unnatural, and the super-natural. Journal of Development Economics, 47(1), 61–95. Ghartey, E. E. (1993). Causal relationship between exports and economic growth: some empirical evidence in Taiwan, Japan and the US. Applied Economics, 25(9), 1145–1152. Giles, J.A., & Williams, C. L. (2000). Export-led growth: A survey of the empirical literature and some non-causality results. Part 1. The Journal of International Trade & Economic Development, 9(3), 261–337. Greenaway, D., & Sapsford, D. (1994). What does liberalisation do for exports and growth? WeltwirtschaftlichesArchiv, 130(1), 152–174. Guzman, M., Ocampo, J. A., & Stiglitz, J. E. (2018). Real exchange rate policies for economic development. World Development, 110, 51–62. Head, K., Mayer, T., & Ries, J. (2010). The erosion of colonial trade linkages after independence. Journal of International Economics, 81(1), 1–14. Kalirajan, K. (2007). Regional cooperation and bilateral trade flows: An empirical measurement of resistance. The International Trade Journal, 21(2), 85–107. Kirton, J. J., & Maclaren, V. W. (2018). Linking trade, environment, and social cohesion: NAFTA experiences, global challenges. Routledge. Kolk, A. (2016). The social responsibility of international business: From ethics and the environment to CSR and sustainable development. Journal of World Business, 51(1), 23–34. Kolk, A., Kourula, A., & Pisani, N. (2017). Multinational enterprises and the sustainable development goals: What do we know and how to proceed? UNCTAD, 24(3). Komives, K., & Jackson, A. (2014). Introduction to voluntary sustainability standard systems. In Voluntary standard systems (pp. 3–19). Springer, Berlin, Heidelberg. Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–499. Krugman, P. R. (1993). The narrow and broad arguments for free trade. The American Economic Review, 83(2), 362–366. Kunst, R. M., & Marin, D. (1989). On exports and productivity: A causal analysis. The Review of Economics and Statistics, 699–703.

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Lee, C. S., & Cheong, I. (2017). Regional contents in exports by major trading blocs in the AsiaPacific region. Journal of Korea Trade, 21(2), 145–160. McCallum, J. (1995). National borders matter: Canada-U.S. regional trade patterns. American Economic Review, American Economic Association, 85(3), 615–623. Melitz, M. J., & Redding, S. J. (2014). Heterogeneous firms and trade. In Handbook of international economics (Vol. 4, pp. 1–54). Elsevier. Muradian, R., & Martinez-Alier, J. (2001). Trade and the environment: From a ‘Southern’ perspective. Ecological Economics, 36(2), 281–297. Proops, J. L., Atkinson, G., Schlotheim, B. F. V., & Simon, S. (1999). International trade and the sustainability footprint: A practical criterion for its assessment. Ecological Economics, 28(1), 75–97. Ravishankar, G., & Stack, M. M. (2014). The gravity model and trade efficiency: A stochastic frontier analysis of Eastern European countries’ potential trade. The World Economy, 37(5), 690–704. Sequeira, S. (2016). Corruption, trade costs, and gains from tariff liberalization: Evidence from Southern Africa. American Economic Review, 106(10), 3029–3063. Shan, J., & Sun, F. (1998). On the export-led growth hypothesis: The econometric evidence from China. Applied Economics, 30(8), 1055–1065. The New York Times. (2018). Trump hits China with tariffs on $200 billion in goods, escalating trade War. Retrieved September 25, 2018, from https://www.nytimes.com/2018/09/17/us/politics/ trump-china-tariffs-trade.htmllast. Tinbergen, J. (1962). Shaping the world economy: Suggestions for an international economic policy. New York: Twentieth Century Fund. UNCTAD. (2010). Non-tariff measures: Evidence from selected developing countries and future research agenda. New York and Geneva: United Nations publication. Wilson, J. D. (2015). Mega-regional trade deals in the Asia-Pacific: Choosing between the TPP and RCEP? Journal of Contemporary Asia, 45(2), 345–353. World Economic Forum. (2016). 5 ways to make global trade work for developing countries. Retrieved September 24, 2018, from https://www.weforum.org/agenda/2016/09/global-trade-dev eloping-countries-unctad/. World Trade Organization. (2018). World trade statistical review. https://www.wto.org/english/res_ e/statis_e/wts2018_e/wts2018_e.pdf.

Chapter 10

Dairy Industry in India Under Trade Liberalisation S. Mohanakumar

Abstract India is the largest producer of milk after the USA. It’s fast-growing domestic market for milk and milk products in the world leaves it with a little surplus for external trade. Unlike in developed countries, the dairy sector is yet to be established as an independent economic activity in India. The sector continues to be a supplementary activity to the crop production sector for most of the farmers. Dairy contributes 28% to the Gross Value Added (GVA) in agriculture and allied activities in India. In India, cattle rearing and milk production is a potential source of income for farmers to fall back during a crisis in the crop production sector. However, India’s share in world trade of dairy products is not commensurate with its size of the domestic market and the scale of production. A major bottleneck in the world market is the low productivity of milch animals in India. It is argued that dairying in India is still subsistence in character and growth of the sector is largely driven by domestic demand. The protection available to dairy farmers in the domestic market for dairy products in India has declined under trade liberalisation. This poses a threat to the millions of small-scale farmers employed in the sector. Therefore, government interventions become necessary for supporting the sector. Keywords Dairy products · International trade · Animal husbandry · Liberalisation · Cow · Buffalo

10.1 Introduction The farming system in India is known for its mixed crop-livestock production. The livestock economy of India houses 58% of buffalos and 15% of cows, ranking top in cattle and buffalo population in the world. India is the largest producer of milk in the world, with a share of 20% in world production. Cattle rearing has been an offshoot of the crop production sector, and therefore, changes in the crop production and allied sectors leave a direct impact on the dairy sector as well. Dairy farmers in S. Mohanakumar (B) Institute of Development Studies, Jaipur, Rajasthan, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_10

193

194

S. Mohanakumar

India have been under severe stress for the last quarter of the century as the crisis of reproduction1 of small producers in the crop production sector has percolated into the milk production sector as well, since the economic liberalisation of 1991. Production conditions in the dairy sector are more industry-like as compared to agriculture. For crop production, agro-climatic conditions limit productivity augmentation of the crops, while in the dairy sector, cattle rearing and productivity augmentation are not much influenced by agro-climatic conditions. Milk production in India grew at 4% during the last two decades and is more than double the rate of growth of milk production in the world (Government of India 2017). Protagonists of neo-liberal views argued that trade liberalisation would make Indian agriculture more competitive in the international market. It would eliminate supply-side bottlenecks and further the liberalised exports of agricultural commodities, enable farmers to have better access to the international market and enabling competitiveness (Gulati 2018). On the other hand, some studies have shown the negative impact of trade reforms on agriculture, including dairy sector (Mohanakumar 2018). In the international trade scenario, productivity, and scale of production matter more than the size of the bovine stock. Merely the numero uno status in milk production is not a sufficient condition for trade in the global market. The productivity of milch animals (cow and buffalo) in India is on a lower side, as compared to that of the major milk producers in the world. This low productivity of cow and buffalo in India is attributed to both intrinsic (genetic potential) and extrinsic variables including management, poor veterinary and extension services, and sub-standard breed improvement programme. Although extrinsic variables can be improved with advanced management practices, intrinsic factors are difficult to change in the short run, especially for small producers or subsistence farmers, who produce for the market in the neighbourhood. It has been estimated that the informal sector handles more than 80% of the milk marketed in developing countries, and India is no exception (FAO 2018). The change in the breed of milch animals involves substantial investment, and it is hard for most milk producers in India to make a substantial investment in the short run. However, dairy farmers need to be assured a remunerative price along with adequate investment in infrastructure for productivity enhancement. Given the size of the operation and limited investment capacity of dairy farmers in India, productivity-augmenting capital investment for the dairy sector comes from the public sector. In light of the above, this study examines the following: (i) What is the structure and composition of milk production and milch animals in India? Are milk producing farmers in India prepared to compete in the international market? (ii) What does the trend in the foreign trade of dairy products forecast for farmers in India? The remainder of the chapter is as follows: In Sect. 10.2, the production structure and trend in the dairy sector are analysed. Section 10.3 analyses the trend 1 Crisis

of reproduction or reproduction crisis refers to the social process of production of capital and labour with incessant renewal. Crisis is a situation wherein the existing system of organization of production has been worn out and the new has not yet been developed. In this case, the trade liberalisation programme since 1991 has eroded profitability in agriculture and in this space new system of production has not yet emerged. It is therefore called crisis of reproduction.

10 Dairy Industry in India Under Trade Liberalisation

195

in the foreign trade of the dairy industry during the trade liberalisation phase. The findings are summarised in Sect. 10.4.

10.2 Structure and Trend in Milch Animal Population and Milk Production It has been sufficiently explored in the Indian context that there has been a significant decline in the relative contribution of agriculture and allied sectors in the GVA in India for the last three decades. While the share of agriculture and allied sectors decline in GVA, the relative contribution of the livestock sector has been increasing over the years and is indicative of the importance of the sub-sector within agriculture (Fig. 10.1). The structure, composition and changes in regional concentration of milch animal population assume a special significance in the international trade in dairy products. Competitiveness of dairy products from India in the international market is influenced primarily by its quality and relative price. In the international market, buffalo milk-based products are preferred to cow milk. Further, Domestic Resource Cost (DRC) of exporting cow-milk based items from non-descript and indigenous cow is not competitive as the productivity of animals is much below the exotic breed. In the cattle population, there exist mainly three varieties, viz., exotic breed, non-descript (Murrah) and indigenous. Similarly, non-descript and indigenous varieties are more common in the buffalo population. Productivity does vary significantly across different types of cattle as well as buffalo and, therefore, the change in the composition of the population has a bearing on the competitiveness of dairy products in the domestic and international markets. 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 2011-12

2012-13

2013-14

2014-15

2015-16

Agriculture

Livestock

2016-17

2017-18

2018-19

Fig. 10.1 Relative share of livestock and agriculture in GDP. Note Relative share of Agriculture and allied sectors in GDP do not include the share of the livestock sector. Source Derived from Agricultural Statistics at a Glance, 2019

196

S. Mohanakumar

During the livestock inter-census period (2012 and 2019), there was an increase in buffalo population by 11.5 lakhs and cow population by 25.50 lakhs. The trend in milch animal population provides a broad pointer to the current phase of the animal husbandry sector in India. Table 10.1 shows changes in the relative share of cow and buffalo population by states (milch animal) in 2007 and 2012. Cow accounted for 63% of the total milch animals in India, indicating a regional concentration and preference for milch animals in India. In the north-east and south India, cow is the preferred Table 10.1 Distribution of Cattle and Buffalo Population by States in India 2007 and 2012 (percentage) State

2007

2012

Cow

Buffalo

Cow

Buffalo

Andhra Pradesh

45.82

54.18

47.46

52.54

Assam

95.26

4.74

95.95

4.05

Bihar

65.24

34.76

61.78

38.22

Chhattisgarh

85.54

14.46

87.59

12.41

Gujarat

47.62

52.38

49.01

50.99

Haryana

20.68

79.32

22.91

77.09

Himachal Pradesh

74.87

25.13

75.01

24.99

Jammu & Kashmir

76.63

23.37

79.11

20.89

Jharkhand

85.36

14.64

88.04

11.96

Karnataka

70.82

29.18

73.28

26.72

Kerala

96.77

3.23

92.85

7.15

Madhya Pradesh

70.59

29.41

70.54

29.46

Maharashtra

72.71

27.29

73.46

26.54

Manipur

84.62

15.38

79.90

20.10

Meghalaya

97.51

2.49

97.60

2.40

Nagaland

93.06

6.94

87.78

12.22

Odisha

91.19

8.81

94.12

5.88

Punjab

25.98

74.02

32.00

68.00

Rajasthan

52.21

47.79

50.66

49.34

Tamil Nadu

84.78

15.22

91.87

8.13

Tripura

98.53

1.47

98.87

1.13

Uttar Pradesh

44.23

55.77

38.97

61.03

Uttarakhand

64.70

35.30

67.01

32.99

West Bengal

96.17

3.83

96.51

3.49

Delhi

24.83

75.17

34.77

65.23

India

65.40

34.60

63.72

36.28

Source Department of Animal Husbandry, Dairying & Fishing. Ministry of Agriculture & Farmers Welfare

10 Dairy Industry in India Under Trade Liberalisation

197

milch animal as compared to buffalo. Five states, viz., Andhra Pradesh, Gujarat, Haryana, Punjab and Uttar Pradesh have a buffalo population above 50% of the total cow–buffalo population. In 12 states, the relative share of the cow population is more than 75% of the total milk population. It may be noted that animal preference is rooted in socio-cultural aspects and is further warranted by other enabling factors. More than 25% of the milch animal population is reared in two states, viz., Uttar Pradesh (16%) and Madhya Pradesh (10%) followed by Rajasthan (8%), Maharashtra (7%), Gujarat (7%), Andhra Pradesh (6.6%), Bihar (6.2%). West Bengal (6%), Karnataka (4%), Odisha (4%) and Tamil Nadu (3%). Those nine states in the second group account for more than 50% of the milch animal population in India. About 40% of the buffalo population in India is reared in two states, viz., Uttar Pradesh (28%) and Rajasthan (11%). At the national level, the population of exotic breed cow saw a rate of growth of 5.39% between 2007 and 2012. Broadly, there has been a shift in the structure of the milch animal population in India. Out of 25 states considered for the analysis, relative share of buffalo population in the milch animal population has registered a fall in 14 states (Table 10.1). However, a silver lining in the otherwise disparaging trend is that major milk-producing states like Rajasthan and Uttar Pradesh have recorded an increase in buffalo population. States can be classed under three categories based on the relative share of crossbreed and indigenous cow (Table 10.2). Category 1: A relatively high share in indigenous cow population as compared to crossbreed cow population; Category 2: A high share of crossbreed cow population as compared to indigenous cow population; Category 3: Equal share in both types of cow population. Assam, Chhattisgarh, Jharkhand, MP, Odisha, Uttar Pradesh and West Bengal fall under category 1 states. Bihar, Karnataka, Maharashtra, Tamil Nadu, Haryana, Himachal Pradesh, Jammu and Kashmir, Kerala and Punjab are in the advantageous group as the relative share of crossbreed is higher than indigenous as compared to Category 1 states. The two broad trends emerging from the geographical concentration of milch animal population are: (i) there has been a concentration of milch animal population by animal type; and (ii) buffalo population in relation to cow population has been on the decline for most of the states, notwithstanding the fact that the buffalo population has marginally increased in India during the reference period. Spearman rank correlation showed that there was a positive association between population density of crossbreed cows and indigenous cows for the period 2007 and 2012 in India. It implies that the shift from indigenous or low productivity animal to high breed or high productivity animal is a process of transformation involving several phases. Table 10.3 shows per capita availability of milk in India by states for the period 2009–10 to 2016–7. The coefficient of variation of per capita availability of milk has remained unchanged for the last 15 years. This implies that the geographical concentration of milk production/or animal composition remains unaltered. Important observations emerging from Table 10.3 are: (i) per capita availability of milk varied significantly across states in India. Nine out of 28 states and union territories considered for the analysis, recorded a higher per capita availability in milk production as compared to the national average. It is worth mentioning that major milk-producing states such as Uttar Pradesh recorded a per capita availability

198 Table 10.2 Regional distribution of crossbreed and indigenous cow population by states in India—2012 (Percentage share)

S. Mohanakumar State

Crossbreed

Indigenous

Andhra Pradesh

5.90

4.05

Arunachal Pradesh

0.05

0.28

Assam

0.95

6.38

Bihar

8.87

6.84

Chhattisgarh

0.38

5.44

Goa

0.05

0.03

Gujarat

5.14

5.64

Haryana

2.48

0.56

Himachal Pradesh

2.44

0.67

Jammu & Kashmir

3.34

0.94

Jharkhand

0.61

4.47

Karnataka

8.02

4.29

Kerala

3.30

0.07

Madhya Pradesh

2.02

11.99

Maharashtra

9.50

5.66

Manipur

0.10

0.15

Meghalaya

0.08

0.58

Mizoram

0.03

0.02

Nagaland

0.25

0.07

Odisha

2.92

5.39

Punjab

5.40

0.19

Rajasthan

4.43

9.60

Sikkim

0.26

0.01

16.20

1.93

Tamil Nadu Tripura

0.30

0.56

Uttar Pradesh

8.73

13.12

Uttarakhand

1.24

0.99

West Bengal

6.68

10.01

Delhi

0.15

0.03

India

100.00

100.00

Source Department of Animal Husbandry, Dairying & Fishing. Ministry of Agriculture & Farmers Welfare

less than the national average; (ii) there are states with milk availability of less than 100 grams per day, and in those states, there is less possibility that the production can be increased in the short run. In such states, the demand for different forms of milk products will be met from cheap imports, posing a threat to the sustainability of the dairy sector in India.

10 Dairy Industry in India Under Trade Liberalisation Table 10.3 Per capita milk availability by states (per day/gram)

State

199 2009–10

2016–17

Growth rate

All India

273

355

3.34

Andhra Pradesh

342

522

5.43

Arunachal Pradesh

59

109

7.97

Assam

69

71

0.36

Bihar

175

228

3.36 −4.22

Goa

96

68

Gujarat

418

563

3.79

Haryana

662

930

4.34

Himachal Pradesh

397

521

3.46

Jammu & Kashmir

379

400

0.68

Karnataka

226

291

3.21

Kerala

201

189

−0.77

Madhya Pradesh

278

468

6.73

Maharashtra

190

243

3.12

Manipur

88

75

−1.98

Meghalaya

83

83

0

Mizoram

29

62

9.96 −0.67

Nagaland

96

91

Orissa

112

128

1.68

Punjab

944

1075

1.64

Rajasthan

509

785

5.56

Sikkim

200

228

1.65

Tamil Nadu

278

294

0.7

Tripura

77

114

5.03

Uttar Pradesh

283

348

2.62

West Bengal

133

148

1.34

A&N Islands

−5.25

137

89

Chandigarh

95

76

−2.75

Dadra & Nagar Haveli

86

62

−4.01

Daman & Diu

15

5

−12.83

Delhi

72

35

−8.62

Lakshadweep

84

110

3.43

Puducherry

96

107

1.37

Chhattisgarh

110

141

3.15

Uttarakhand

387

440

1.62

Jharkhand

130

157

2.39

Source Department of Animal Husbandry, Dairying & Fisheries, Ministry of Agriculture & Farmers Welfare, Government of India

200

S. Mohanakumar

10.2.1 Trends in Milk Production For trade in food items to take place, it is the precondition that there should be sufficient production of a marketable surplus, defined in terms of excess of production over own consumption. Milk production continues to be an engagement of small capital owners, governed by the purpose of subsistence or livelihood rather than a commercial activity for profit. However, milk production in India has been growing faster, both in absolute and relative terms. The per capita availability of milk has increased from 160 grams per day to 355 grams per day between 1985–86 and 2016–17. During this period, milk production in India has increased from 44 million to 165 million ton, and the annual rate of growth in milk production has surpassed the population growth, driving up the per capita availability. Milk and milk products being income elastic, marketable surplus depends on the rate of growth in per capita income and decline in inequality of income distribution, and level and growth in milk production. Per capita availability of milk in India is much on a lower side as compared to the same in major milk producers and exporters in the world. There are a couple of factors influencing per capita consumption of milk and milk products in a country like India where a substantial segment of the population is vegetarian, and the required nutrients are derived from dairy products and milk. Table 10.4 gives the geographical spread of milk production and its composition in 2016–17. The relative share of buffalo and cow milk is almost the same in India, albeit there exist significant differences across states. It may be noted that more than 50% of buffalo milk production is concentrated in five major states, while cow milk production is more evenly distributed. Another important observation that emerges from Table 10.4 is that buffalo milk-producing states have registered surplus milk production in terms of per capita availability. Table 10.5 shows the per capita monthly expenditure on milk and milk products in India. The relative share of milk and milk products in total food expenditure increased from 11.67% to 18.72% in rural India between 1970–71 and 2012–13. In the case of urban India, per capita monthly expenditure on milk and milk products in total food expenditure increased from 14.71 to 20.25% during the reference period. The observed increase in expenditure on dairy products pulls down the available marketable surplus for export while it widens the scope for large-scale imports to India. The per capita consumption of different types of milk and milk products in India is much less as compared to other developed countries in the world. For instance, the per capita consumption of dairy products is 53 kg per annum in India, and it does not constitute even 1/4th of the per capita consumption of milk equivalent of developed countries like USA, Australia, and Canada. It, in turn, implies that per capita consumption of milk and milk products would substantially increase with the spike in income in India. Over the years, as income increased, the per capita consumption of dairy products increased much faster, as evidenced in Table 10.6. The increasing demand for dairy products will be met through imports if the dairy products are not made available in the domestic market at competitive prices. This would be disastrous for the waning livestock sector in the country.

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Table 10.4 Percentage share in milk production in states by type of animals 2016–17 States

Andhra Pradesh Assam

Milk production (million tonnes)

State’s share in Share of milk total milk within a state production Buffalo Cow milk milk

Million ton

Percentage

State’s share in India’s production Buffalo milk

Cow milk

12,175

7.6

68.2

32.0

10.2

5.0

843

0.5

13.6

86.0

0.1

0.9

Bihar

8508

5.3

39.5

61.0

4.1

6.6

Chhattisgarh

1321

0.8

25.5

74.0

0.4

1.3

51

0.0

33.7

66.0

0.0

0.0

Goa Gujarat

12,478

7.8

53.6

46.0

8.2

7.4

Haryana

8926

5.6

81.4

19.0

8.9

2.1

Himachal Pradesh

1283

0.8

29.4

71.0

0.5

1.2

J & Kashmir

2300

1.4

20.2

80.0

0.6

2.3

Jharkhand

1764

1.1

19.6

80.0

0.4

1.8

Karnataka

6482

4.1

29.6

70.0

2.4

5.8

Kerala

2394

1.5

0.5

99.0

0.0

3.0

Madhya Pradesh

12,753

8.0

48.6

51.0

7.6

8.4

Maharashtra

10,182

6.4

39.4

61.0

4.9

7.9

Manipur

79

0.1

17.9

82.0

0.0

0.1

Meghalaya

84

0.1

1.6

98.0

0.0

0.1

Mizoram

24

0.0

0.0

100.0

0.0

0.0 0.1

Nagaland

78

0.1

8.0

92.0

0.0

Odisha

1999

1.3

13.0

87.0

0.3

2.2

Punjab

11,222

7.0

71.9

28.0

9.9

4.0

Rajasthan

18,801

11.8

59.1

41.0

13.7

9.8

54

0.0

0.0

100.0

0.0

0.1

Tamil Nadu

7442

4.7

4.9

95.0

0.4

9.1

Telangana

4675

2.9

70.5

30.0

4.1

1.8

147

0.1

1.2

99.0

0.0

0.2

26,455

16.6

66.9

33.0

21.8

11.2

Uttarakhand

1641

1.0

46.2

54.0

0.9

1.1

West Bengal

5051

3.2

4.9

95.0

0.3

6.2

A&N Islands

15

0.0

10.2

90.0

0.0

0.0

Chandigarh

36

0.0

53.3

47.0

0.0

0.0

1

0.0

0.0

100.0

0.0

0.0

48

0.0

4.6

95.0

0.0

0.1

Sikkim

Tripura Uttar Pradesh

Lakshadweep Puducherry

(continued)

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Table 10.4 (continued) States

India

Milk production (million tonnes)

State’s share in Share of milk total milk within a state production Buffalo Cow milk milk

Million ton

Percentage

159,365

100.0

51.1

State’s share in India’s production

49.0

Buffalo milk

Cow milk

100.0

100.0

Note Total milk production does not include goats’ milk, which accounts for 3% of the total milk production in India Source Derived from Basic Statistics of Animal Husbandry and Fisheries, Government of India (2017) Table 10.5 Per capita monthly consumer expenditure on milk and milk products in India NSS round/Year

Percent share of milk and milk products in total food expenditure

Percent share of milk and milk products in total expenditure

Rural

Urban

Rural

Urban

25th (1970–1971)

11.66

14.72

8.58

9.48

38th (1982)

11.46

15.62

7.51

9.24

46th (1990–1991)

14.28

17.42

9.42

9.91

56th (July 2000–June 2001)

15.43

18.95

8.68

8.30

66th (July 2009–June 2010)

16.04

19.16

8.60

7.80

68th (July 2011–June 2012)

18.72

20.26

9.10

7.80

Source NSSO, Various Rounds Table 10.6 Per capita Consumption of different types of milk and milk products (Milk equivalent) in India and other countries in 2017 Country

Milk equivalent (Kg)

Excess consumption of milk in Kg Equivalent in Other countries compared to India (in KG)

New Zealand

238.72

185.44

Australia

251.2

197.92

USA

240.5

187.22

Canada

207.84

154.56

EU-28

246.21

192.93

Russia

146.87

93.59

India

53.28

0.00

China

23.22

(-) 30.06

Source CLAL Dairy Forum, October 5, 2018

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In the total production of milk in India, Uttar Pradesh, Rajasthan, Gujarat, Karnataka, Maharashtra, Punjab and Kerala accounted for 52% of the total milk production in India in 2016–17. Among these states, barring Punjab, compound growth rate of milk production during the last 5 years was less than the rate of growth in the national average. Moreover, Punjab recorded the lowest growth rate, followed by Kerala. The major milk-producing states can be grouped into three, viz., (i) best performers; (ii) moderate performers; (iii) poor performers. The classification is based on last 5 years compound growth rate in milk production. The best performers included Madhya Pradesh, Andhra Pradesh, Chhattisgarh, Karnataka, Tripura, Haryana and Himachal Pradesh. All these states registered a compound growth rate ranging between 4 and 6%. Poor performers included Punjab, Odisha, Assam, Uttarakhand, Kerala, Bihar and West Bengal. These states have registered a growth rate less than the national average. It is worth noting that most of the milk-producing states have a growth rate between 1 and 4%. Table 10.5 shows the trend in the consumption of milk and milk products in relation to the total food items and total expenditure on all items. Findings of Tables 10.4 and 10.5 are complementary to each other. There has been a significant increase in the relative share of milk and milk products in total food expenditure in both urban and rural area. However, in the total expenditure of households, there has only been a marginal increase in the share of milk and milk products while the same has registered a decline in urban India over the years. Table 10.6 gives per capita consumption of different types of milk and milk products in major milk-producing and exporting countries in the world. Per capita consumption of milk and milk products in India is significantly lower compared to major milk producers in the world. Its implication is that India provides a large market for dairy products for traders in the international market. In the context of trade liberalisation, there might be a possibility that largescale imports of milk and milk products from major producers may destroy the fragile domestic producers in India. It is important to know if there is any endogenous or exogenous break in the growth of milk production in India in the long run (1985–86 to 2016–17). Structural break is employed to detect breaks in the growth of milk production in India. It was found that there was a break in the annual growth of milk production in India in 2001–02 (Table 10.7). Milk production in India grew at the rate of 4.04% per annum during 1985–86 to 2001–02, and it grew by 4.14% per annum during 2001–02 to 2016–17. The growth rates for different sub-periods were estimated using a kinked exponential function. The observed break in the long-run growth movement of the Table 10.7 Rate of growth in milk production by break period

Period

Growth rate

1985–86 to 2013–14

4.08**

1985–86 to 2001–02

4.04**

2001–02 to 2016–17

4.14**

Note **Significant at 1% level Source CLAL Dairy Forum, October 5, 2018

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trend warrants scrutiny. It has been documented that farmers produce more milk for subsistence during the crisis period in the crop production sector and the crop production sector in India has undergone a deep crisis since the early 2000s. The kinked exponential function to estimate growth rates for different sub-periods in a series without losing degrees of freedom is explained below. The trend growth rate was estimated using the semi-log or log-lin model of the following form (Gujarati and Sangeetha 2007) Yt = Y0 (1 + r)t

(10.1)

where ‘r’ is the rate of growth of milk production in percentage and Y0 is the initial value or constant term. Yt is the quantity of milk produced in the current year (t) in India. Taking natural logarithm of both sides in Eq. 10.1, it takes the form as in Eq. 10.2. ln Yt = ln Y0 + t ln(1 + r)

(10.2)

Substituting β1 for lnY0 and β2 for ln (1 + r), the Eq. (10.1) can be rewritten as: ln Yt = β1 + β2 t + Ut

(10.3)

Whereas: ln Yt stands for natural logarithm of milk produced, β1 is the initial production or constant, β2 is the rate of growth or slope coefficient, ‘t’ is the time, Ut is the error term. The rate of growth in a series with numerous unknown breaks can be detected employing kinked exponential growth (Boyce 1986; Balakrishnan and Parameswaran 2007). The advantage of estimating log-lin growth model with a single equation is that it allows the estimation of growth rate for relatively smaller periods without compromising the degrees of freedom. The kinked exponential growth rate with linear regression with a single break at point ‘K’ in a time series data for milk production takes the following form: ln Yt = α1 D1 + α2 D2 + (β1 D1 + β2 D2 )t + ut

(10.4)

where D1 is dummy and it takes the value ‘1’ for the period 1985–86 to 2001–02 and ‘0’ for the rest of the period. The discontinuity is eliminated with the linear restriction as given below α1 + β1 K = α2 + β2 K

(10.5)

Whereas: α1 D1 + α2 D2 = α1

(10.6)

Substituting Eq. 10.5 in Eq. 10.4, the restricted form is transformed into a linear regression form as Eq. 10.7. Equation 10.7 is applicable for a series with single break point at ‘K’.

10 Dairy Industry in India Under Trade Liberalisation

ln Yt = α1 + D1 + β1 (D1 t + D2 K) + β2 (D2 t − D2 K) + ut

205

(10.7)

10.3 Foreign Trade of Dairy Products India has been an important player in the international market for agricultural commodities with a relative share of 2.69% in total exports and 1.31% in imports in the world trade in 2016–17. During the period from 2011–12 to 2018–19, agricultural exports as a percentage of Gross Value Added (GVA) from agriculture declined from 12.37 to 9.39% (Government of India 2017). Alongside, import of agricultural commodities as a percentage of agricultural GDP increased from 3.94 to 6.5% during the reference period. The share of dairy products in agricultural imports has increased from 0.05 to 0.26% between 2002–03 and 2015–16 (Elumalai 2007 and Elumalai and Sharma 2008). In the case of the export of dairy products, its relative share in total value of exports of agricultural commodities is still below 1%. In 2003–04, dairy products accounted for 0.51% of the value of agricultural exports, and it increased to 0.78% in 2015–16. In the national exports, share of dairy products increased from 0.06% to 0.09% during the reference period. The trend broadly indicates that dairy products have been mostly confined to domestic market and its extension to the international market has limitations, and it calls for a detailed scrutiny. The foreign trade of milk and milk products in India may be viewed against hard facts elaborated above. In the international market, global commodity prices of both spot and futures markets have been on the decline and the commodity prices are likely to remain weak on account of low demand in the international market exacerbated further by excess supply (Government of India 2017). In 2016–17 and 2017–18, there has been a surplus production of milk in major milk-producing countries and the international market surplus has led to a fall in the price of dairy products. India has a comparative advantage over other countries, particularly over Europe and North America, in milk production, because of its low cost of production. Since the introduction of trade liberalisation in 1991, there has been a change in the structure and pattern of foreign trade of milk and milk products in India and the shift can be broadly described as demand driven (Joshi 2012). The dairy sector is characterised by sustained price and market. Since the World Trade Organisation (WTO) came into operation in the agricultural trade, the domestic market access for dairy products has significantly widened for dairy products from major milk producers in the world with the reduction in import tariff. However, trade restrictions have been increasingly used by the USA and the European Union to prevent low-cost producing countries like India from entering the world market. In the last decade, the volume of trade in dairy products grew at the rate of 3% per annum which was on a higher side as compared to the production of dairy products (2.4%). It has been estimated that the observed increase in the demand for dairy products in developing countries would reduce the volume of trade by 6% in the next decade. In the next 10 years, world

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Table 10.8 Average milk production per animal per day in India and other countries Countries

2010–12 (Kg)

2022 (Kg)

India’s yield ratio in 2010–2012 with reference to other countries

India’s yield ratio in 2012–2022 with reference to other countries

USA

9.7

11.6

0.11

0.12

European Union

6.6

7.2

0.17

0.19

Australia

5.9

6.6

0.19

0.21

Mexico

4.7

5

0.23

0.28

Argentina

4.6

5.8

0.24

0.24

New Zealand

3.9

4.3

0.28

0.33

Russian Federation

3.5

4.9

0.31

0.29

China

3.3

3.6

0.33

0.39

Ukraine

2.9

3.8

0.38

0.37

Brazil

1.4

1.4

0.79

1.00

Pakistan

1.2

1.5

0.92

0.93

India

1.1

1.4

1

1.00

Source Derived from Joshi (2012)

milk production is expected to increase by 164 million tons, of which India’s contribution is projected to be 29% (Joshi 2012). However, the projected milk production in developing countries is 2.5% per annum as against 1% growth of the same in developed counties. It is indicative of widening market opportunities for developing countries while the structural limitations in developing countries, including India, to make use of the opportunity to expand its market pose challenges in the external market for dairy products. Another limitation in international trade of dairy products from India is the difference in milk yield as compared to major milk producers in the world. Table 10.8 compares the milk yield per animal in India and other countries. The average yield per animal in India is much lower than in other countries in the world, particularly that of the developed countries. It is indicative of the fact that the productivity of animals in India, which is one of the major factors determining the competitiveness the international trade, has been in a disadvantageous position.

10.3.1 Composition of World Trade of Dairy Products In international trade, cheese, curd, milk and cream concentrates accounted for 70% of the total exports from dairy products in 2017 (DGCIS 2018). Other items of importance in terms of the value of exports are non-concentrated and non-sweetened milk, butter, cheese and curd, whey, and natural milk. Germany is the major exporter (13%) followed by New Zealand, Netherlands, France and the USA. It is important to

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note that India has not yet figured as an important player in the international market for dairy products. Although the price of dairy products in the international market does not fluctuate as in the case of agricultural commodities, there are fluctuations in the price of milk. The price of dairy products has declined since 2011 as has been the case with agricultural commodities in the international market. In real terms, the price of milk and milk products has flattened over the years since 2011. Though India is the largest milk producer in the world, she continued to be a net importer of dairy products till early 2000s. It is contributed, in part, by her large population size and partly by rising per capita income. Milk and milk products have income elasticity of demand of greater than 1. India’s share in world milk export was 0.68% in 2016 against a share of import of the same of 0.04% in the same year. As mentioned, imports of dairy products continued till 1993 and India became a net exporter of dairy products by early 2000s. There is no significant difference between the export structure of India and the world in the commodity composition. In the total value of dairy products exported from India, 89% was accounted for by milk and cream concentrates in 2001 and the share of the commodity in the total export value declined substantially over the years. Moreover, the market for exports from India does follow the world pattern. Bangladesh, United Arab Emirates and Egypt are major destinations of India’s export, and it can also be stated that the export destinations are concentrated in Asia. It means that India has not yet succeeded in advancing its exports to developed markets of the world or where the large market for dairy products is concentrated. On the contrary, major countries from where India imports its dairy products are developed nations, viz., USA, New Zealand and the Netherlands.

10.3.2 Tariff Structure and Unit Price of Dairy Products in India Competitiveness of dairy products for external trade is measured as a price ratio between domestic and international markets. In this case, import value represents international, and export price is representative of the domestic market price of dairy products under consideration. There were several attempts to measure the competitiveness of Indian dairy products in the international market. Often the Nominal Protection Coefficient (NPC) is used for measuring competitiveness. Rakotoarisoa and Gulati measured NPC for Butter and Skimmed Milk Powder (SMP) under importable hypothesis for the period 1975–2001. It was found that NPC for SMP declined from 2.165 in the 1970s (pre-liberalisation) to 1.388 in the 1990s (postliberalisation) (Rakotoarisa and Gulati 2006: 200). Rajarajan et al. measured NPC for five important dairy products traded in the domestic market in India for pre- and postliberalisation periods. For butter, NPC was more than unity in the pre-liberalisation phase but declined to unity during the liberalisation period (Rajarajan et al. 2007: 426–439). For other dairy products such as SMP and WMP, NPC or domestic market

208

S. Mohanakumar

2.00 1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 2018-19

2017-18

2016-17

2015-16

2014-15

2013-14

2012-13

2011-12

2010-11

2009-10

Export

Import

Fig. 10.2 Share of dairy export and import in agricultural trade. Source Agricultural Statistics at Glance 2019

protection rate has declined during the post-liberalisation phase as compared to the pre-liberalisation period (Rajarajan et al. 2007). Elumalai and Sharma estimated both NPC and Effective Protection Coefficient (EPC) for the period 1990–91 to 2002–03 for four states in India for SMP and the study also confirmed the findings of earlier studies (Elumalai and Sharma 2008: 68–83). Dairy products comprising mainly five commodity groups enjoyed domestic protection of more than 200% in the pre-WTO regime. The bound rate of import duty for dairy product under the WTO varied between 100% and 150%. Similarly, basic customs duty ranged between 30% (fresh milk and cream) and 60% for cheese. Figure 10.2 shows the percentage share of dairy products in the value of agricultural imports and exports in India. The relative share of imports of dairy products has been negligible during the 2000s while they have started rising by 2010–11. Similarly, the relative share of export of dairy products, particularly milk and concentrated milk remained high till the end of the 2010s and it has started declining thereafter. There were intermittent jumps in the quantity and value of imports of milk and milk cream or concentrated milk to India. Often, the quantity of imports to India increases when unit price declines and in contrast to the observed trend, the unit price too has increased along with the rise in the quantity of imports of milk and milk products during the last few years. The value of exports of dairy products and its share in the total value of agricultural exports remain relatively high as compared to the share of the value of imports of dairy products in agricultural imports. There are exceptional years such as 2008–09 and 2012–13 during which the value of exports has markedly increased. In the total value of export of agricultural product, the share of dairy product is still 0.77%. It may also be noted that there have been wide fluctuations in the unit value of exports of dairy products and the observed trend is indicative of the non-sustainability of the sector in India in the international market.

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Table 10.9 provides details on the relative share of dairy products in the exports for the year 2001–2019. In the value of exports, milk, and milk cream concentrates (IFSC code 0402) accounted for 75% of the total value of exports in certain years, but the relative importance of the product group in the export basket is inconsistent and has been on the decline for the last few years. The decline in the total value of exports of dairy products from India consecutively since 2014 is partly attributable to the decline in the export quantity and value of the item. The content and value of the import basket of dairy products are given in Table 10.10. Interestingly, major items of imports of dairy products to India are the same as the product that India exports and it poses a threat in the context of trade liberalisation. It has already been mentioned that the commodity characteristics of exports of dairy products in India are more or less the same as the product composition of trade in the international market. Moreover, dairy products have relatively less scope for diversity and the diversification are distinguished based on the quality of the product. The export from India faces the challenge in light of the above. Although there has been a decline in the value of imports of dairy products into India during the last few years, the rate of decline in imports is much less than that of exports. Whey, cheese, curd, butter and ghee remain the major, items of imports into India. It may be noted that there has been a continuous increase in the positive trade balance of dairy products from Rs 463.35 crores to Rs 3120 crores in 2018–19, barring a negative trade balance of (-) 571.62 in 2011–12.

10.4 Conclusion It has come out categorically that the domestic market protection enjoyed by domestic producers of dairy products in India has substantially declined under trade liberalisation. Given the structure and composition of milk production and cattle rearing in India, the decline in the competitiveness of dairy products would lead to massive import of dairy products, which would, in turn, work out to be detrimental to the domestic dairy industry. Even though India is the largest producer and consumer of milk in the world, significant portions of the milk produced are consumed without value addition. A large part of the milk production segments comprises landless, small, and marginal farmers rearing cattle and 80% of the product is sold in the informal sector. Though India remains a net exporter of dairy products, the price of liquid milk, the form in which major part of the production is sold by farmers, remain non-remunerative. The very nature of production and the characteristics of the ownership of capital of majority of cattle rearing farmers in India indicate that the sector has not yet been prepared to withstand the effects of trade liberalisation as well as neo-liberal policies affected through the crop production sector. India’s share in world trade of dairy products is not commensurate with its share in production. Further, the productivity of animals in India is much on the lower side as compared to the same in major milk producing and consuming countries. It is one of the major limitations of expanding the market for dairy products from India in the world market.

155,877

269,994

88950

115,333

2007

2008

2009

2010

575,360

109,154

2006

2013

147,163

2005

75,446

50,533

2004

157,320

25,782

2003

2012

24,889

2002

2011

39,713

Thousand US$

7.5

22.2

64.6

35.1

29.5

22.7

14.0

12.6

10.5

16.7

21.7

19.2

12.7

Percentage share

Total exports in Butter, incl. 000 dehydrated butter and ghee, and other fats and oils derived from milk

2001

Year

88.7

64.3

15.3

52.8

57.0

67.6

65.8

81.0

84.8

78.4

70.0

76.3

83.5

Milk and cream concentrated or containing added sugar or other sweetening matter

0.8

4.0

7.2

2.2

4.2

1.9

2.5

1.9

0.7

1.1

0.8

0.4

0.0

Milk and cream, not concentrated nor containing added sugar or other sweetening matter

2.5

8.5

11.1

7.5

8.0

4.7

3.1

2.0

1.5

1.0

3.7

1.8

0.8

Cheese and curd

0.5

0.3

1.1

0.4

0.2

1.1

6.7

0.8

0.2

0.4

2.0

0.3

0.2

Buttermilk, curdled milk and cream, yogurt and other fermented milk

0.1

0.7

0.8

2.1

1.1

2.1

7.9

1.8

2.4

2.4

1.9

2.0

2.8

Whey, whether or not concentrated

Table 10.9 Export value and relative share by product of milk and milk products from India—2001 to 2019 (Percentage share)

(continued)

265.7

108.5

−34.6

29.7

−67.1

73.2

42.8

−25.8

191.2

96.0

3.6

−37.3

Annual change

210 S. Mohanakumar

121,455

130,531

161,406

291,804

265,195

2015

2016

2017

2018

2019

Source Trade Map

311,558

2014

31.8 11.1

71.4

25.6

43.5

44.9

75.4

Milk and cream concentrated or containing added sugar or other sweetening matter

51.1

50.5

34.3

36.3

14.9

Total exports in Butter, incl. 000 dehydrated butter and ghee, and other fats and oils derived from milk

Year

Table 10.9 (continued)

3.9

2.7

4.4

2.6

3.3

3.3

Milk and cream, not concentrated nor containing added sugar or other sweetening matter

12.8

12.4

18.4

18.7

15.2

6.2

Cheese and curd

0.5

0.4

0.9

0.8

0.3

0.2

Buttermilk, curdled milk and cream, yogurt and other fermented milk

0.3

1.6

0.3

0.1

0.0

0.0

Whey, whether or not concentrated

−9.1

80.8

23.7

7.5

−61.0

−45.8

Annual change

10 Dairy Industry in India Under Trade Liberalisation 211

6.2

11.2

17.0

57.8

15,177

63,398

2008

2009

2010 183,777

2011 177,392

2012 101,238

2013

34,609

8.0

13,636

2007

28.3

30.0

15.1

23.4

7648

13.9

21,671

2004

6.6

6.0

2006

13,069

2003

19.6

2005

13135

27,106

2002

4861

23.3

7.9

4.2

3.7

7.0

32.9

30.1

13.8

30.3

15.2

7.2

13.3

20.0

6.5

24.5

1.3

40.2

69.3

12.7

17.4

63.4

26.5

48.8

28.5

73.2

41.6

Whey, whether or Cheese and curd Butter, incl. not concentrated dehydrated butter and ghee, and other fats and oils derived from milk

Thousand US$ Percentage

Total import

2001

Year

11.3

50.0

83.0

49.5

14.1

20.8

19.9

6.6

18.3

20.8

57.6

6.6

18.2

Milk and cream, not concentrated nor containing added sugar or other sweetening matter

0.7

0.3

0.2

0.3

1.3

3.2

2.1

0.9

1.5

0.9

0.2

0.9

0.5

Buttermilk, curdled milk and cream, yogurt and other fermented milk

Table 10.10 Import value and relative share by product of milk and milk products from India—2001 to 2019

0.5

0.2

0.2

0.1

0.3

2.2

0.5

0.2

0.0

0.4

0.0

0.0

0.2

(continued)

−65.8

−42.9

−3.5

189.9

317.7

11.3

−37.1

183.4

−41.5

−51.8

106.4

170.2

Milk and cream, Annual change not concentrated nor containing added sugar or other sweetening matter

212 S. Mohanakumar

45,025

40,437

41,436

30,077

32,787

2016

2017

2018

2019

Source Trade Map

47,117

2015

Total import

2014

Year

33.2

30.4

47.6

20.0

18.7

16.0

18.4

45.6

51.2

46.8

46.1

59.3

6.6

7.4

12.7

29.9

27.9

6.7

Whey, whether or Cheese and curd Butter, incl. not concentrated dehydrated butter and ghee, and other fats and oils derived from milk

Table 10.10 (continued)

6.8

5.4

10.4

3.3

8.9

13.8

Milk and cream, not concentrated nor containing added sugar or other sweetening matter

4.1

2.4

3.6

0.3

0.1

0.5

Buttermilk, curdled milk and cream, yogurt and other fermented milk

4.4

5.6

2.2

1.1

1.0

1.4

9.0

−27.2

2.5

−10.2

−4.4

36.1

Milk and cream, Annual change not concentrated nor containing added sugar or other sweetening matter

10 Dairy Industry in India Under Trade Liberalisation 213

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S. Mohanakumar

Moreover, India’s export basket of dairy products is confined to milk concentrates, butter and cheese, while India’s import is concentrated in yogurt and other dairy products with value addition. The commodity composition of world trade in dairy products is more or less the same as that of India and that is yet another constraint in the world market. Despite the marginal increase in the export value of dairy products from India, import of the same has also increased particularly during the last few years. The content of import basket for dairy products underlines that items of exports and imports converge to a great extent. This might pose a threat to the existence of the dairy sector in India if further liberalisation of the sector takes place in the future. It must be noted that the dairy sector in India is dominated by small-scale farmers, as opposed to large-scale commercial farms in many developed countries. As a result, government interventions are necessary to support the sector for food security and livelihood. At the same time, it is also vital that measures be adopted to increase the productivity of the bovine stock by addressing both intrinsic and extrinsic variables and making the sector globally competitive.

References Balakrishnan, P., & Parameswaran, M. (2007). Understanding economic growth in India: A prerequisite. Economic and Political Weekly, XLII(27–28), 2915–2922. Boyce, J. K. (1986). Kinked exponential models for growth rate estimation. Oxford Bulletin of Economics and Statistics, 48(4), 385–391. Elumalai, K. (2007). Measuring comparative advantage in export of India’s dairy products. The Asian Economic Review, 49(3), 407–420. Elumalai, K, & Sharma, R. K. (2008). Trade protection of India’s milk products: Structure and policy implications. Indian Journal of Agricultural Economics, 63(1), 67–83. FAO. (2018). Retrieved February 9, 2019, from fao.org/dairy-production-productivity/socioeconomics/markets and trade/en. Government of India. (2017). Economic survey, 2015–16. New Delhi: Oxford University Press. Gujarati, N. D., & Sangeetha. (2007). Basic econometrics (4th ed., pp. 280–284). New Delhi: Tata McGraw-Hi ll Publishing Company Limited. Gulati, A. (2018). Taxed through trade policies, farmers need stable income policy. Indian Express, Editorial Column, January 21, 2019. Joshi, R. M. (2012). India’s dairy exports: Opportunities, challenges and strategies. Research and International Collaborations, Indian Institute of Foreign Trade, New Delhi-11001. Mohanakumar, S. (2018). Crisis of petty commodity producers in the crop production sector under neoliberal regime: Response of a village economy in Kerala. Social Scientist, 46(7–8). Rajarajan, et al. (2007). Implications of trade liberalisation on Indian Dairy Sector: An empirical analysis. Indian Journal of Agricultural Economics, 62(3), 426–439. Rakotoarisoa, M., & Gulai, A. (2006). Competitiveness and trade potential of India’s dairy industry. Food Policy, 31, 216–227.

Chapter 11

Genetically Modified Crops and Indian Agriculture: Issues Relating to Governance and Regulation Anurag Kanaujia and Sujit Bhattacharya

Abstract This study investigates the issues related to the commercialisation of genetically modified (GM) crops and examines the regulatory framework for GM crops development and commercialisation in India. It explores the positioning of various organisations and stakeholders that have directly or indirectly influenced this technology and delineates their roles in the technological governance system. The findings of this study show that institutions promoting research and innovation are not appropriately linked with the institutions for its governance and regulation in India. As a result, even after extensive debate and creation of new institutions, there is a persisting situation of antagonism and low public trust in GM technology as a viable solution for India’s agricultural problems. This has impeded the innovation and translation process despite successful field trials of many indigenous GM crop. Further, it underlines that individual and group concerns regarding the environmental, health and economic viability of GM crops as technological intervention can be addressed by promoting it as an alternative in specific conditions only. In conclusion, a group of interventions such as the development of a system to encourage innovation, capacity building and investment in alternate technologies is suggested to equip for the ever-increasing demand of agricultural products in the future. Keywords GM crops · Regulation · Innovation system · Government policy · Risk · Management

A. Kanaujia (B) · S. Bhattacharya Academy of Scientific and Innovative Research (AcSIR), CSIR-National Institute of Science Technology and Development Studies (NISTADS), New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 R. Sudesh Ratna et al. (eds.), Indian Agriculture Under the Shadows of WTO and FTAs, India Studies in Business and Economics, https://doi.org/10.1007/978-981-33-6854-5_11

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11.1 Introduction Genetically Modified (GM) Bt cotton1 was introduced in India in 2002, leading to high production of cotton in the following years. This provided a stimulus to the biotechnology-based interventions in agriculture. Meanwhile, India became one of the largest exporters of cotton in the world (Chaturvedi and Arora 2014). According to many scientists, GM crops were the answer to food security and climate change induced crop failures. Countries worldwide, adopted new varieties of corn, brinjal, soybean, canola, sugarbeet, alfalfa, papaya, squash, potato, etc. to reduce the use of pesticides, increase productivity and other benefits. The estimated market value of GM crops being grown across the world is US$17.2 billion2 (GeneWatch UK 2016, ISAAA 2018). However, even after 18 years since the introduction of GM crops in India, Bt cotton remains the only GM crops allowed for commercial cultivation in India. This is due to controversies about the potential long-term impacts of the plants on the environment and animals. The use of GM crop in agriculture has assumed significant importance across the globe. Controversies pertaining to the use of GM crops have sprung up in the USA (Ishii and Araki 2016), European Union (EU) (Kuntz et al. 2013), Egypt (Adenle 2011; Sarant 2012), Japan (Morris 2013), Korea (Choi 2015), Brazil (do MST 2015), and Taiwan (Hsiao 2013). In Asia as well, concerns have been raised in China (Sun 2019) and Bangladesh (Nasiruddin 2011; Jitendra 2019), where they have adopted GM crops in their agricultural food production systems. In India, the issue around GM crops has remained in limbo for more than a decade. Different stakeholders have expressed their concerns about the introduction of GM crops in agriculture and food chain of the country. These concerns span from health (human, animal and environment), economics, and ethical issues; and they are the primary reasons for the delay in the commercialisation of GM-based crops. Two attempts to introduce GM crops namely, Bt Brinjal in 2009 and GM mustard in 2015 had met with resistance and the approval for their release, as a result, was withdrawn by the ministry of environment and forest. The issue of GM crop cultivation in India is characterised by changing policy stances of the government. On the one hand, the government has generously funded research in the development of indigenous GM varieties, investing a considerable amount in field trials. On the other hand, the government has placed a moratorium on the commercialisation of GM food crops in India. This decision was based on the recommendations of various committees constituted at different periods; as the government has not been able to clearly articulate responses to convince those who have questioned the suitability of this technological intervention. The failure of regulatory agencies is evident in the fact that the Supreme Court of India had to intervene in the decision-making process (Technical Expert Committee 2013; Nuziveedu Seeds Ltd. and Ors. vs. Monsanto Technology LLC and Ors. 2018). 1 Bt stands for Bacillus thuringiensis, a soil bacteria from which the gene Cry is taken for the cotton plant. 2 Estimates of 2017 by the latest ISAAA report 2018 as available on May 12, 2020.

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In this chapter, we discuss some of the effects these interventions had on the development of GM crops in India and try to answer the following questions. What is the reason for the current deadlock between the regulators and the developers of GM technology? Does the existing review system have any shortcomings? Or is it because of an improper understanding of recommendations made by the review committees? Can there be a plausible way to utilise the best parts of GM technology still, while keeping in sight the associated risks being pointed out continuously? It is important to answer these questions, as many new technologies are coming up with the rapid boom in the information and technology sector. Many of these have the potential to fall in similar situations of system failure if proper policy guidance framework is not provided. This could entail environmental, health as well as economic and commercial costs in management or mitigation of their negative effects. In the available literature on GM crops, a lot has been debated regarding the reasons for GM crops not performing well (Levidow and Carr 2007; Dogra 2012; Gilbert 2013; Herring 2014) but studies on their regulation in India are limited. Thus, the reasons for the continued moratorium on the commercialisation of GM crops in India, despite promising research, regulatory interventions, a comprehensive portfolio of regulatory bodies, and continuous review of the issues by different bodies are worth examining (Chaturvedi and Arora 2014).

11.2 Highlighting the Governance and Regulation/Conceptual Framework 11.2.1 High Importance of Regulatory Governance and Participation of Stakeholders Innovation which is at the heart of technological change, is the process that depends on the accumulation and development of relevant knowledge of a wide variety. This brings back the argument from previous section on innovation systems, and we can infer that economic development and technological changes are positively related to each other. Both regulation and governance are necessary for management of innovation and are unified as ‘regulatory governance’ (Kotsemir and Abroskin 2013; Tidd 2006). Such coherence is essential for the development of new technological innovations and their appropriate acceptance from all stakeholders. They must be aware of the opportunities and risks involved in the use of technology. They should also share a need to accommodate change while retaining sufficient mutual trust and certainty in other stakeholders. This cannot happen in the absence of regulation as high competition may lead to malpractices for higher benefits (Heldeweg and Kica 2011).

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11.2.2 Role of Regulation in Promoting Innovation ‘Regulation is the sustained and focused attempt to alter the behaviour of others according to standards or goals with the intention of producing a broadly identified outcome or outcomes, which may involve mechanisms of standard-setting, information gathering and behaviour modification’ (Black 2002). In terms of innovation governance, regulation is the act of balancing factors pertaining to innovation. It demarcates the extent of freedom available to companies to collaborate or receive protection for their inventions so as to ensure that downstream innovation remains unaffected. It defines the boundary for dissonance in public values so as to strike a balance between consumer interests and those of the producers, between manager and employee interests and between stakeholder and other interests in the pursuit of innovation. It also explores new roles that are of public interest considerations for technological innovation (Donnelly 2011). There can be both positive and negative impacts of regulation on activities of business, affecting their capabilities for technological innovation, and therefore regulatory agencies play a critical role. As a result, the outlook towards regulation has been evolving. In the UK, as early as the 1980s, the law-makers consider regulation as a service and treat the companies and citizens as consumers. In contrast, the traditional outlook considers them as objects of ‘regulatory implementation and enforcement’. Other ways of facilitative use of regulation are promoting for standardisation of products and allowing block exemptions for the leading responsible firms for example, firms sharing their knowledge in research and development (Crouch and Streeck 1997; Hall and Soskice 2000). Regulation ensures monopolistic competition as production and R&D activities are segregated. In the post-industrial economies, most of the R&D activities happen while production is done in emerging market economies. On the flip side, if regulation is used to minimise the level of competition too much, it may lead to adverse impact on the performance of companies or the whole economies (Arezzo 2007). Cultivation and propagation of technological change encompass multifaceted interactions between institutions, organisations and firms. Individual firms play a crucial role in the development of specific innovations, but the role of government is complex and important. Government is an intermediary between the firms and the consumers. The government should operate based on the additionality principle3 to foster innovation (Heldweg 2011). It must carefully plan any intervention. If required to intervene, government intervention should be minimal and withdrawn as soon as the issue is addressed (Wetenschappelijke 2008). The government may have the potential to rectify market and innovation failure, as seen in the case of GM crop technology. Government interventions can be characterised based on the position it takes in the innovation ecosystem. When acting intrinsically, its focus will be on

3 ‘Additionality

is the property of an activity being additional. It is a determination of whether an intervention has an effect, when the intervention is compared to a baseline. ‘Interventions’ can take a variety of forms, but often include economic incentives.’ (for more detailed description see- A practical guide to adding value through non-financial support, 2015 EVPA).

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securing innovation as such. This can be done by the government by making improvement in the rules deciding the overall innovation processes instead of focusing on one single product or technology. This way, the whole innovation ecosystem will be affected and not only the targeted technology. On the other hand, when it acts extrinsically, the interventions made by governments are based on specific technologies aimed at solving a (set of) challenges or improve the quality or efficiency of an existing process for safety and quality purposes (e.g. regular improvements in vehicular engine efficiency standards from BS-I to BS-V). Based on its requirement, the government when acting extrinsically may assume roles of a customer, a partner in the production unit, guarantee the sale of products or make laws to govern the activities related to the use of technology (Bochm and Frederick 2010; Heldweg 2011).

11.2.3 Factors Restricting Innovation Innovation is a concept that includes a new functionality or a new way of using existing functionality. It is a ‘complex system’, comprising of ways to create new knowledge and new technologies, and their faster identification, diffusion and application. This often involves modification in the labour, its management and overall organisations in favour of faster systems (Wetenschappelijke 2008). However, innovation governance mainly focuses on the first part of the definition and often overlooks the need for complementing new technology with changes in the organisation structure, labour capacity/expertise, legal frameworks, etc. Market failures in adoption and commercialisation of innovation can be the reason behind these inefficiencies. Major causes for these failures are ‘reluctance to initiate innovation with positive external effects’, ‘uncertainty regarding returns on investment’, ‘insufficient or slow knowledge transfer’ and ‘insufficient cooperation between firms’ (Wetenschappelijke 2008; Heldweg 2011). ‘There is ‘systemic failure’ within the innovation process itself’. New technologies can be used and leveraged more effectively if the market structure also adapts to the requirement of the technology through institutional changes. Some of these changes are adoption of improved technological standards, implementation of better safety protocols, and creation of new production and distribution chains. New institutions and technological standards are required because the existing ones may not be suitable for the evaluation of the products based on new technology, hence impeding the process and leading to failure of innovation (Heldweg 2011). Many of these concepts are useful in understanding why regulatory failure has occurred in the GM crop debate. In the following sections, we look at the regulatory framework and relate them to the concepts of regulation, governance and risk analysis.

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11.3 Governance and Regulation of GM Crops The regulation of GM crops has a long history spanning more than a decade. During this time, different situations have arisen that have helped shape the regulatory policies pertaining to GM crops around the world. In India, its regulation has been under debate owing to the constant rebuttal between the pro-GM researchers (supporting adoption of GM crops), developing and marketing firms; and the anti-GM activists (opposing adoption of GM crops) and non-government organisations (NGOs). The influence of these stakeholders on the regulatory landscape is evidenced in the changing policy stances of the government.

11.3.1 Agencies Involved in Regulation and Governance In the past decade, there have been generous funding for research and field trials of GM crops, which has resulted in the development of many new varieties. Government agencies have actively shown their support for research and development of new crops (EPW Corrospondent 2003, Warrier and Pande 2016, Express News Service 2016, BioSpectrum Bureau 2016, Aggarwal 2016, Haq and Chauhan 2015, GeneWatch UK 2016). Regulation can assist or suppress economic and technological innovation in different ways. Innovation takes place in the business environments set up by regulation. Regulation can, therefore, have an impact on a company’s capacity to attract investments for adoption of innovation for fixed and human capital in its business. The entry of a company in a new market, its ability and chances of establishing collaboration with other companies and protection of company’s investments are also dependent on the regulatory processes. Thus, the role of regulation is not only in the development of an environment for technological innovation but also in determining the type of innovations happening in a system. A liberal regulatory framework will facilitate companies for exploring risky ideas and hence promote radical technological innovations, while regulation that emphasises on continuity of service and improvement in the existing standards may promote incremental innovations by skilled manufacturers (Brownsword and Somsem 2009). Although the institutional support for research has been high, the regulatory authorities have remained sceptical regarding the introduction of GM-based food crops in India. The result of this scepticism is evident in the ongoing moratorium on the release of GM food crops. The committees that have reviewed the possibility of introducing GM food crops in India have unequivocally rejected the idea based on the lack of capacity building and unpreparedness of the system to manage the risks associated with the technology. The two committees, Jairam Ramesh Report (2010) and Sopory Committee (2012) had implicitly supported the concerns about safety and species intermixing raised by various groups of scientists, progressive farmers and civil society activists and vindicated the moratorium placed on conducting new field trials. The Parliamentary Standing Committee on Agriculture; and Parliamentary

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Standing Committee on Science and Technology, Environment and Forests (PSCST) in their reports in 2012 and 2017, respectively, had pointed at the flaws in structure and process of assessment of the impact of GM crops for environmental release. In response to a public interest litigation, the Technical Expert Committee set up by the Supreme Court of India evaluated the regulatory framework and supported the continuation of the ongoing moratorium on the environmental release of GM food crops because of unpreparedness of system to deal with the associated risks (Technical Expert Committee 2013). In addition, the focus of policy attention has been on risk management; specifically, environmental and technological risk. Historically, risk analysis conducted in social sciences focused on quantifying and understanding the magnitude and causes of public perceptions and concerns regarding the risk by utilising quantitative or qualitative methods (Sjoberg 2000). In the case of GM crops, the nuances from these studies can be useful for conflict resolution. The government has been unable to clearly articulate their responses to convince those who have questioned the suitability of this technological intervention. Only one argument springs out to justify the introduction of GM crops, i.e. growing population needs more food to survive (Qiam 2001; Qaim 2009; Chaturvedi and Arora 2014; FAO 2015a, b). This argument holds little to no water for the public as tonnes of agricultural produce procured by the public distribution scheme rots away in the absence of proper storage and distribution mechanisms (NAAS 2019). Improving shelf life is not going to matter if the storage facilities cannot shield the produce from natural elements. Over the years, many issues have come up, and different regulatory agencies have engaged in the management of technology, subsequently defining their roles and positions in the web of agencies. Looking at these events and the agencies involved have helped us to place these important stakeholders on a map that provides a bird’s eye view perspective of the regulatory landscape. Figure 11.1 presents the map with the important agencies involved in regulation and development of GM crops in India. Notice that there is no emphasis on monitoring and review of yields and performance of crops; this is one of the major issues pointed out by the committees that have reviewed the regulatory system (Lalitha et al. 2009; ICAR 2012; Banerjee 2018). Additionally, there is apparent compartmentalisation of responsibilities among the different bodies. However, this distribution of functions is yet to result in a streamlined conveyor of regulation for development, assessment and commercialisation of new crops. In the next section, we look at these bodies, their proposed functions and their actions in the past, before connecting it to regulation and governance literature to draw conclusions about the effectiveness of past exercises in GM crop development in India. Our understanding of the innovation processes has been greatly informed by the study of system of innovation framework (Xue and Zhang 2006). This strategy and conceptual approach require qualitative methodologies to determine the sources of frustration, individual level of knowledge and the associated perception of risk, in order to interpret the associated underlying social, organisational and political processes (Gregory and Sattrfield 2002; Brownsword and Somsem 2009). The approach contrasts with previous attempts such as the traditional Organisation for Economic Co-operation and Development’s (OECD) approach to technological

Fig. 11.1 Agencies Involved in Regulation and Development of GM crops in India. Source: Authors’ compilation based on observations from governance and policy documents, Press Information Bureau briefs, and review reports on GM crops in India

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change and innovation, which analysed resource inputs and system outputs from the research and development (R&D) system based on a narrower interpretation of innovation systems. In the traditional approaches, innovative activities of a few types are noticed while others are overlooked. This narrow focus on R&D is one of the major shortcomings of the traditional approach to innovation (Fischer 2000).

11.3.2 Legal Framework on GM Crops in India To understand these issues comprehensively, it is necessary to first understand in detail the legal framework and debates around these crops.

11.3.2.1

Core Regulatory Setup

The evolution of laws regarding the development and release of GM organisms has happened in response to the emerging controversies over time. The Environment Protection Act, 1986 forms the basic framework, which has been used by Ministry of Environment and Forest & Climate Change (MoEF&CC), Department of Biotechnology (DBT) and the Ministry of Agriculture (MoA) in regulating this technology. Table 11.1 presents the salient features of the important laws under which the GM crops are regulated. Any transgenic crop cannot be introduced and commercialised in India without receiving environmental clearance under 1989 ‘Rules for Manufacture, Use, Import, Export and storage of hazardous microorganisms/Genetically Engineered Organisms or Cells’ notified under the Environment (Protection) Act, 1986. The research, large-scale applications of GMOs and hazardous microorganism (GM or otherwise) are covered under the biosafety regulatory frameworks issued by the MOEF in 1989. Presently, there are six committees under the rules of 1989 constituted by the DBT. These include the Genetic Engineering Appraisal Committee (GEAC), the State Biotechnology Coordination Committee (SBCC’s), District Level Committees (DLCs), the Recombinant DNA Advisory Committee (RDAC), the Review Committee on Genetic Manipulation (RCGM) and the Institutional Biosafety Committee (IBSC) (MoEF 2003). These committees have remained in the shadow of DBT and MoEF for one or the other reason. Allegations of conflict of interest, favouritism and oversight have marred the reputation of these committees and as a result, waned the public trust in the decision these bodies take (Rajya Sabha Secretariat 2017). The proposal to constitute a new independent regulatory body under the National Biotechnology Regulatory Authority Bill, 2012 has been rejected in the face of staunch opposition by NGOs and civil society (PIB 2012). Expectations from this bill were high as it would have clearly defined the union and state jurisdiction and their respective responsibilities for decision-making in the regulation of GM crops in India (Choudhary et al. 2014).

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Table 11.1 Regulation of genetically modified crops in India Guidelines

Issued by

Features

1. Rules for the Manufacture, Ministry of Environment and Use, Import, Export and Forest (MoEF) Storage of Hazardous Microorganisms/Genetically Engineered Organisms or Cells, 1989 (Rules 1989)

Research and application of GMOs and Products. Overarching set of regulations dictating all GM governance activities

2. Recombinant DNA Safety Guidelines 1990 and 1994

Department of Biotechnology (DBT)

Prescribe safety measures for research on GM organisms and the criteria for ecological assessment on a case-by-case basis

3. Revised Guidelines for Research in transgenic plants and Guidelines for toxicity and allergenicity evaluation of transgenic seeds, plants and plant parts, 1998

Department of Biotechnology (DBT)

Development and growth of GM plants in soil. Import and shipment of GM plants of research use

4. Guidelines and standard (safe) operating procedures (SOPs) for confined field trials of regulated GE plants, 2008

Genetic Engineering Three-part Appraisal Committee (GEAC) regulations/guidelines for transport and handling of regulated material for import, export, inter and intra-state movement. Contains field trial application and data formats

5. Guidelines for Safety Indian Council of Medical Assessment of food derived Research (ICMR) from GE plant, 2008

Focus in Risk linked to GM food

6. Protocols for food and feed safety assessment of GM crops, 2008

Five tests to be conducted for the safety of a food product from GM source

Department of Biotechnology (DBT)

Source: Authors’ compilation based on a study of websites of DBT, GEAC and IGMORIS, and policy documents of the Government of India related to the regulation of GM crops

11.3.2.2

Supplementary Setup

Early on in the acknowledgement of the possible bio-safety4 risks associated with the application of modern biotechnology, provisions have been developed under the National Biological Diversity Act 2002 to deal with the unforeseen risks. Under 4 Bio-Safety:When

Genetic modification of organisms are introduced into the ecosystem they can have unpredictable results. The products of such food crops may be unsafe for consumption by human and animals. In addition to this, they may also harm the soil bacteria, bees and other important organisms, thereby affecting entire food web and biodiversity. GM crop may eliminate the wild/indigenous species by cross-pollination. (for detailed description, see—Conner et al. 2003. The release of genetically modified crops into the environment, The Plant Journal 33(1), pp 19–46.)

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the Act, an autonomous body is formed and is known as the National Biodiversity Authority (NBA) at national level and state level biodiversity board at state level. The authority functions as an advisory body, undertaking facilitative and regulatory roles for the Government of India. It deals with issues about conservation of biodiversity and sustainable use of biological resources. The authority is also mandated to ensure fair and equitable sharing of benefits arising out of the use of biological resources (website: https://nbaindia.org/). Many new bodies had to assume the responsibility of managing certain aspects of GM crop regulation. The most noticeable of these were the Director General of Foreign Trade (DGFT), Competition Commission of India (CCI), Food Safety and Standard Association of India (FSSAI) and the Central Information Commission (CIC). Even the judiciary, including the Supreme Court of India, had to get involved amid tensions between the technology holding companies, the government and the civil society activists to decide on the proper mechanisms of governance. Allegations of bio-piracy5 and bio-profiteering6 against MNCs by NGOs and activists were found to be valid by investigations ordered by the court. The spat between the government and MNCs around the royalty or trait fee paid by local seed companies to Mahyco Monsanto Biotech (India) for using its technology, pushed government price interventions and litigation to check the exploitative policies of MNCs. Over recent years, more issues related to consumer safety and environmental sustainability have come up. This has contributed to the uncertainty associated with the use of GM crops among the stakeholders. In a recent study including various stakeholders and conducted across different selected states of India, we observed that there is a need to further develop the clarity on regulations for research, testing and use of GM crops (Kanaujia and Bhattacharya 2018). Labelling is one such issue, where the FSSAI has framed the Food Safety and Standards (Labelling and Display) Amendment Regulations 2018.7 These regulations specified threshold levels for labelling requirements of GM foods to be sold in the Indian markets (Banerjee 2018). Intellectual property and patent rights are another class of issues, which pertain to sustainability, and economic viability of the technology for the agricultural sector. Indian agriculture is a source of livelihood for rural marginal farmers (Vigani and Olper 2013, Nuziveedu Seeds Ltd. and Ors. vs Monsanto Technology LLC and Ors. 2018). These farmers depend on government subsidies and other forms of monetary support for their crops. In light 5 Bio-piracy: It is a concept similar to piracy in software, movies and other intellectual properties. When corporations use the genetic materials well known to farmers and indigenous people without sharing the benefits or paying a compensation for the genetic material it is termed as bio-piracy. Many people believe that GM technology in agriculture is ‘bio-piracy’ because of unfair patenting and patent licensing by MNCs (see Roberts R. 2000, Biopiracy: Who Owns the Genes of the Developing World?, Science Wire). 6 Bio-profiteering: MNCs introduce terminator gene in their GM seeds. This makes the resultant plant sterile, thereby requiring farmers to repurchase seeds for every cropping season. Since GM crops will make wild/indigenous varieties extinct by cross-pollination, so farmer will be at the mercy of these MNCs for the future seeds. 7 FSSAI Gazette Notification no. F.No. REG/11/27/BEVO-Labelling/FSSAI-2018.

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of India’s socioeconomic background, this framework of privatisation of new seeds through patents is a major problem that needs to be addressed before the introduction of GM crops.

11.3.2.3

Research and Development

Indian Council of Agricultural Research (ICAR), Council of Scientific and Industrial Research (CSIR), Central and State Agriculture universities are the primary locations/institutions where research on development and performance of GM varieties have been carried out. However, most of the GM crops developed are yet to secure approval for release in fields. The government had pushed a vocal agenda on GM adoption in agriculture in the recent past. National Institution for Transforming India (NITI) Aayog in a statement in 2016 had called for allowing GM crops in agriculture. As a part of its strategy to bring a Second Green Revolution, India must return to permitting proven and well tested GM technologies with adequate safeguards.

The research and development of GM plants are motivated by the quest for selfsufficiency agriculture because of (1) Sustainable Development Goal of Zero Hunger and (2) Economic goal of low food inflation. In addition to these motivations, international obligations also affect the governance activities. For instance, being a signatory to the Cartagena protocol, the government needs to protect the genetic diversity of plants and animals and ensure that agricultural intervention such as the GM crops does not present any risk to the local biodiversity (World Bank and OECD 2016).

11.3.2.4

International Collaboration and Information Dissemination

Several international institutions have worked continuously for developing crosscountry collaboration and national capacities in the management of genetically modified organisms. Regulation of technology has been one of the agenda for many international organisations. In fact, the regulation and facilitation of international cooperation for technology development and use were the reasons behind the formation of some of the oldest international organisations (Wessel 2011). In the case of GM plants, Food and Agriculture Organization (FAO) of the United Nations is one such body. It promotes the use of a nine-digit alphanumeric code as a unique identifier of any new transgenic variety. Available in its bio-track product database, the OECD’s Unique Identification for transgenic plants is another such identifier, available for each transgenic plant approved for commercial use (OECD 2006). It is a product database maintained and accessible from various platforms (namely, FAO, OECD and Convention on Biodiversity) to allow the “regulatory authorities and other interested stakeholders to easily access and share basic information on products derived from the use of modern biotechnology” (FAO 2015a, b) United Nations Environment Programme (UNEP) had funded a 3-year-long project with

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MoEF for the Indian states to “educate a variety of stakeholders on biosafety and India’s commitments, under international treaties, to treat GMOs responsibly” (The Hindu 2016; MoEF&CC 2018–19). The International Service for the Acquisition of Agri-Biotech Applications (ISAAA) has also come up with reports about the status of GM crops grown worldwide (Vigani and Olper 2013).

11.4 Discussion The development of the policy landscape for the adoption and commercialisation of GM crops has been punctuated with controversies on decisions of the government to allow open field trials in Bt brinjal and GM mustard. Several committees also evaluated the regulatory options and recommended actions for allowing or banning the field trials of GM crops. Their recommendations have not translated into policy actions and regulatory framework for the evaluation of GM crops is still found lacking. New regulatory bodies have entered the governance space, but there has been little to no impact on their introduction. The efforts that these new bodies have made have not taken into account the recommendations from the previous review committees. The draft regulations formulated have not come into effect and have failed to include important stakeholders such as seed corporations, farmers and consumers into the discussions. Responsible risk management for public safety requires institutions to consider many factors when making decisions. Factors such as technological and environmental risks cannot be the sole dictators. A proper risk management plan for the future is crucial in handling these radical technologies. In such cases, public participation in the decision-making process is vital to ensure fair and democratic risk assessment and management (Moon and Balasubramanian 2004). Public engagement can be a process, which addresses the opaque public information campaigns that often leave stakeholders frustrated and dissatisfied. Individual risk perceptions can influence (and be influenced by) trust in institutions, personal knowledge, experience and understanding of the phenomenon of concern (Gregory and Sattrfield 2002; Sjoberg 2000; Poortinga and Pidgeon 2003). Aspersions about manipulated performance reports from the GM crops evaluation and appraisal committees have placed a question mark on the efficacy of the existing regulatory system (Rajya Sabha Secretariat 2017). Public trust also declined as the instances of faulty or incompetent regulation of research projects such as Bikaneri Bt cotton, GM soy and mustard have surfaced. In 2003, the Ministry of Environment and Forest had released a white paper detailing the performance of Bt cotton and the status of its regulation in 2002 (MoEF 2003). Following this paper, most of the studies about the performance of Bt cotton have had individual researchers (Lalitha et al. 2009; ICAR 2012; Qaim 2009; Warrier and Pande 2016). The lack of transparency in the evaluation and monitoring of crop performance fuels the concerns about environmental safety and economic viability of this technological intervention. Apprehensions of civil society about the effects of GM crops have grown more significant as a result of many litigations and instances of incompetent/ineffective

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regulation. The conflict between Monsanto Mahyco Biotechnology Ltd. and the government regarding the pricing of GM traits, royalty payments etc., has created an atmosphere of distrust between the parties. The inability of institutional mechanisms to address farmer welfare in regions where Bt cotton is grown is one of the reasons behind the public anticipation of risk. Several participatory frameworks have been developed and tested for implementation of technologies. However, the decision-makers at institutions responsible for evaluating and managing risks associated with new technologies have to rely on their experience, in the absence of enough practical recommendations from research on diverse perspectives about the technologies. The most notable challenges to regulation of radical technologies that involve human health include mitigating (1) ‘strong vested interests of parties trying to use the deliberative process to sway the discussion or, ultimately, the outcome’, (2) ‘accountability to the participants for the outcome of the deliberation when the deliberative process is only one input into the decisionmaking process or if the final decision is several years into the future’, and (3) ‘building an infrastructure of civic deliberation within communities and public institutions’(Abelson et al. 2003). The public perceptions about the risk associated with new technologies and their trust in institutions have evolved with the changing nature of the relationship between technologies and society. Due to this evolving perception, many previously established approaches to institutional decision-making may no longer be appropriate for current decision-making processes (Morrison 1998). Thus there remains a need for objective research in this field.

11.5 Recommendations and Conclusions 11.5.1 Developing a System to Promote Innovations in Agriculture It is not important that the solution to the problem of GM food crops be in regulations directly intended for them. Many other peripheral activities indirectly linked to the problem can also address the apprehensions regarding their adverse effects. First, let us discuss the actions directly related to the GM crop debate. The Economic Survey, 2016–17 suggested a decision-making matrix for regulators to allow GM seeds if they don’t have terminator gene or high cost and have any of the following properties: (1) disease and pest resistant, (2) resistant to variation in moisture and soil, (3) longer shelf life, (4) shorter crop duration, (5) non-food/tree format crops (Economic Survey 2016). Domestic institutions and companies rely on technology purchased or licenced from large MNCs while there is very low to none in-house R&D undertaken on the development of indigenous varieties. NITI Aayog, in its three-year agenda for development, has recommended the government to encourage domestic institutions and companies to pursue GM research (NITI Aayog 2017).

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11.5.2 Capacity Building Through Existing Systems Indirect interventions include utilising the existing national education infrastructure for capacity building in the field of research. The Indian agriculture extension services provide informal education and training to farmers, both men and women. Currently, their agenda is to change farmers’ outlook towards their agricultural problems, and villagers’ outlook towards economic and health issues. This is done via individual counselling by experts and trained workers at Krishi Vigyan Kendras (KVKs), Group counselling at village seminars and field visits; publicising government magazines/periodicals, mass media such as TV or radio programmes, e-technology through mobile applications, web portals, SMS, etc. Agriculture Technology Management Agencies (ATMAs) started in 1998 by ICAR, agri-clinics by private individuals (usually, agri. graduates) are some of the other notable programmes that can be used for monitoring, training and developing awareness among the farmers. Local participation of progressive farmers, self-help groups (SHG) and Primary Agricultural Cooperative Societies (PACS) and seed/fertiliser traders can act as major facilitators in maximising the reach of these programmes. A well-trained population of farmers and villagers will not only improve the efficiency of agricultural activities but also serve as a monitoring and evaluation network for new crop varieties (of GM or non-GM type). This will address a major problem of on-field monitoring of crop performance.

11.5.3 Investment in Alternate Technologies Along with the push on GM crops, other progressive farming methods also need to be considered in improving the yield of crops. Instead of focussing solely on productivity, the researchers at government-funded laboratories must also seek to develop plants with traits such as better taste, aroma, appearance, shelf life, calorie, nutrient, antioxidants, etc. This would also address the problem of poor farmer income through value addition. Furthermore, a tight control on the prices of GM seeds and other materials required in their cultivation is crucial for ensuring that small farmers can also adopt them with as much ease as the large farmers. Another step towards reducing the risk in agriculture is to shift from a largely food grain production-based system to include pulses, oilseeds, horticulture, etc. Together these changes can create an ecosystem capable of managing risks and extracting highest returns from new technological innovations.

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