A G R I C U LT U R E A N D R U R A L D E V E L O P M E N T 47606 The Sunken Billions THE ECONOMIC JUSTIFICATION FOR FISHERIES REFORM THE SUNKEN BILLIONS A G R I C U LT U R E A N D R U R A L D E V E L O P M E N T Seventy-five percent of the world's poor live in rural areas and most are involved in agriculture. In the 21st century, agriculture remains fundamental to economic growth, poverty alleviation, and environmental sustainability. The World Bank's Agriculture and Rural Development publication series presents recent analyses of issues that affect the role of agriculture, including livestock, fisheries, and forestry, as a source of economic development, rural livelihoods, and environmental ser- vices. The series is intended for practical application, and we hope that it will serve to inform public discussion, policy formulation, and development planning. Titles in this series: Agriculture Investment Sourcebook Changing the Face of the Waters: The Promise and Challenge of Sustainable Aquaculture Enhancing Agricultural Innovation: How to Go Beyond the Strengthening of Research Systems Forests Sourcebook: Practical Guidance for Sustaining Forests in Development Cooperation Gender in Agriculture Sourcebook Organization and Performance of Cotton Sectors in Africa: Learning from Reform Experience Reforming Agricultural Trade for Developing Countries, Volume 1: Key Issues for a Pro-Development Outcome of the Doha Round Reforming Agricultural Trade for Developing Countries, Volume 2: Quantifying the Impact of Multilateral Trade Reform Shaping the Future of Water for Agriculture: A Sourcebook for Investment in Agricultural Water Management The Sunken Billions: The Economic Justification for Fisheries Reform Sustainable Land Management: Challenges, Opportunities, and Trade-Offs Sustainable Land Management Sourcebook Sustaining Forests: A Development Strategy THE SUNKEN BILLIONS The Economic Justification for Fisheries Reform FAO Rome © 2009 The International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved 1 2 3 4 12 11 10 09 This volume is a product of the staff of the International Bank for Reconstruction and Development / The World Bank. 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For permission to photocopy or reprint any part of this work, please send a request with complete information to the Copyright Clearance Center Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; telephone: 978-750-8400; fax: 978-750-4470; Internet: www.copyright.com. All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. ISBN: 978-0-8213-7790-1 eISBN: 978-0-8213-7914-1 DOI: 10.1596/978-0-8213-7790-1 Library of Congress Cataloging-in-Publication data has been requested. Cover illustration and design: Critical Stages C O N T E N T S Boxes, Figures, and Tables vii Acknowledgments xi About the Authors xiii Acronyms and Abbreviations xv Executive Summary xvii 1. Global Trends in Fisheries 1 Introduction 1 The Deteriorating State of the Marine Fishery Resources 2 Profile and Trends in Global Fisheries Production 5 Trade and Fish Consumption 5 2. The Economic Performance of World Marine Capture Fisheries 9 Value of Production and Global Fish Prices 9 Fishing Costs and Productivity 12 Fishing Effort and Fishing Fleets 18 Subsidies 23 The Costs of Fishery Management 24 3. Estimate of Net Economic Loss in the Global Marine Fishery 27 Background 27 Use of the Terms Net Benefits and Economic Rents 29 Description of the Aggregate Model 31 Model Parameters and Data 32 v 4. Results 41 Main Results 41 Evidence from Global Studies 42 Evidence from Case Studies 42 Links to the Broader Economy 44 Sensitivity Analysis and Confidence Intervals 46 5. The Way Forward 49 Fisheries Reform Makes Economic Sense 49 Rebuilding Global Fish Capital 50 Summary:The Way Forward 55 Appendix One: The Concept of Economic Rent in Fisheries 57 Appendix Two: Model and Model Estimation 61 Appendix Three: Stochastic Specifications and Confidence Intervals 69 Appendix Four: Supplementary Data 77 References 85 Index 95 vi CONTENTS B OX E S , F I G U R E S , A N D TA B L E S Boxes 1.1 Stagnating Global Marine Catch 3 2.1 What Are Subsidies? 23 3.1 The Framework of Prior Studies 28 3.2 Net Benefits, Economic Rents, and Overfishing 30 4.1 Downstream Efficiency Gains in Alaska and Peru 45 Figures 1.1 Catch of Selected Species Groups in Marine Fisheries 4 1.2 World Marine and Inland Capture and Aquaculture Production, 1950­2005 6 1.3 World Capture and Aquaculture Production, 1950­2005 6 1.4 Total Recorded Marine Capture Production by Economic Group, 1970­2005 7 1.5 World Population and Global Fish Supply, 1970­2003 7 1.6 Regional Trends in Annual Fish Supply, 1961­2003 8 2.1 Trends in the Nominal and Real Unit Export Value of Fishery Products 10 vii 2.2 Trends in U.S. Real Price Indexes for Fish and Seafood Products, 1947­2006 11 2.3 Real Trends in Crude Oil Price,Vessel Material Costs, and Fish Export Unit Value 13 2.4 Trends in Fish, Food, and Fuel Prices 14 2.5 Global Population Growth and Trend of Total Number of Capture Fishers 15 2.6 Total Number of Capture Fishers by Region 16 2.7 Gross Revenue per Marine and Inland Capture Fisher 17 2.8 Annual Catch (Marine and Inland) per Capture Fisher, 1970­2000 18 2.9 Total Number of Decked and Undecked Fishing Vessels per Region, 1970­98 19 2.10 Estimated Number of New Fishing Vessels Built and Total Registered Fleet Size 20 2.11 Evolution of Global Fleet Productivity (Total Decked Vessels) 21 3.1 Comparative Yield-effort Curves Corresponding to the Logistic (Schaefer) and Fox Biomass Growth Functions 32 4.1 Sensitivity Analysis of the Results for the Logistic and Fox Models 47 4.2 Density and Distribution Functions for the Estimated Rents Loss for Logistic, Fox, and Combined Logistic and Fox Functions 48 A1.1 Economic Rents 58 A1.2 Illustrative Resource Rents in a Resource Extraction Industry 59 A2.1 The Equilibrium Fisheries Model 63 A2.2 Graphical Illustration of the Global Fishery 68 A3.1 Graphical Illustration of Stochastic Simulations Using the Logistic Model 71 A3.2 Graphical Illustration of Fox Model Stochastic Simulations 72 A3.3 Graphical Illustration of Combined Logistic and Fox Model Stochastic Simulations 72 A3.4 Simulated Distributions 74 A4.1 Example of Increasing Rents in New Zealand and Icelandic Fisheries 84 viii BOXES, FIGURES, AND TABLES Tables 2.1 The Effects of Fuel and Food Price Increases 22 2.2 Estimate of Fisheries Subsidies with Direct Impact on Fishing Capacity per Year, 2000 24 3.1 Model Empirical Inputs and Estimated Parameters 33 3.2 Estimated Capital Cost of Global Fishing Fleet 37 3.3 Global Fleet Estimated Profits, Current and Previous Studies 38 4.1 Main Results--Point Estimates of Rents 42 4.2 Estimates of the Economic Losses from Global Marine Fisheries 43 4.3 Illustrative Rents Losses in Major Fisheries Assessed with the Model Used in This Study 43 4.4 Effects of Fuel and Food Prices Increases on Economic Rents 46 4.5 Confidence Intervals for Rent Loss Estimate 48 A2.1 Summary of Model Coefficients and Variables That Need to Be Estimated 65 A2.2 Data for Estimation of Model Coefficients and Variables 65 A2.3 Formulae to Calculate Model Parameters 66 A2.4 Empirical Values and Assumptions for Estimation of Model Coefficients 67 A2.5 Calculated Model Coefficients (Implied) 67 A3.1 Empirical Values and Assumptions: Stochastic Specifications 70 A3.2 Estimated Rent Loss: Main Results 72 A4.1 Motorized Fishing Fleets in Selected Major Fishing Countries, 2004 78 A4.2 Selected Examples of Relationship between Estimated MSY and Biomass Carrying Capacity 78 A4.3 Estimation of the Weighted Average Global Schooling Parameter 79 A4.4 Indicative Results of Selected Case Studies on Economic Rents in Fisheries 80 A4.5 Projection of Rent Loss, 1974­2007 82 BOXES, FIGURES, AND TABLES ix A C K N O W L E D G M E N T S This study was led by Rolf Willmann (Fisheries and Aquaculture Department, FAO) and Kieran Kelleher (Agriculture and Rural Development Department, World Bank). Ragnar Arnason (University of Iceland) developed the theory and modeling underpinning the study and undertook the economic rents loss calculations. Nicole Franz (FAO) helped with the statistical analyses. The study was undertaken as part of "The Rent Drain" activity of the World Bank's PROFISH Partnership. The study would not have been possible without the support of the Ministry of Foreign Affairs, Iceland, and Agence Française de Développement, France, through their contributions to the initial PROFISH Trust Fund. The authors are grateful for the contributions provided by John Ward (NMFS), Rashid Sumaila (UBC), and Andrew Smith and Stefania Vannuccini (FAO); and to Ann Shriver (IIFET) and Rebecca Lent (NMFS, moderator) for facilitating special sessions of the Biennial Conference of the International Institute for Fisheries Economics and Trade on "The Rent Drain" in Portsmouth, UK, in 2006 and in Nha Trang, Vietnam, in 2008. The authors wish to thank the participants in the study design workshops held in Washington, DC and Rome in 2006 for their counsel and advice: Max Agüero, Jan Bojo, Kevin Cleaver, John Dixon, Lidvard Gronnevet, Marea Hatziolos, Eriko Hoshino, Glenn-Marie Lange, Matteo J. Milazzo, Giovanni Ruta, Gert van Santen, Kurt E. Schnier, William E. Schrank, Jon Strand, Laura Tlaiye, John Ward, Ron Zweig; and Serge Garcia, Rognvaldur Hannesson, and John Sutinen. xi The authors also wish to express their gratitude for the guidance provided by the concept note peer reviewers: Giovanni Ruta (Environment Department, World Bank), Gert van Santen (consultant), and John Ward (NMFS). The authors are indebted to the insights and encouragement received from commentators and the peer reviewers of the study: Kirk Hamilton (ENV, World Bank), Serge Garcia (consultant), Gordon Munro (UBC), Carl-Christian Schmidt (OECD), Craig Meisner (DECRG, World Bank), Gert van Santen (consultant), and Jon Strand (IMF). The authors acknowledge the mentoring of Francis (Chris) Christy over the years; the valuable exchanges of views with PROFISH team members in the Sus- tainable Development Network of the World Bank, including Michael Arbuckle, Lidvard Gronnevet, Marea Hatziolos, Eriko Hoshino, and Oleg Martens; with ARD advisers Chris Delgado, Nwanze Okidegbe, and Cees de Haan; and the logistical support provided by Regina Vasko, Felicitas Doroteo-Gomez, and Joyce Sabaya. The study was initiated under the guidance of Kevin Cleaver and Sushma Ganguly and completed under the guidance of Juergen Voegele, Director, and Mark Cackler, Manager, of the Agriculture and Rural Development Depart- ment of the World Bank. xii ACKNOWLEDGMENTS A B O U T T H E A U T H O R S Ragnar Arnason is a leading fisheries economist and a professor in the Eco- nomics Faculty at the University of Iceland. He is an expert on the economics of individual transferable quotas (ITQs) used to manage fisheries. ITQs are sometimes considered to be the basis for the economic success of Iceland's fish- eries. He has been an advisor to several developing countries on fisheries man- agement issues. He developed the bioeconomic model used to estimate the $50 billion annual loss of potential economic benefits in the global ocean fishery. Kieran Kelleher is the Fisheries Team Leader in the World Bank's Agriculture and Rural Development Department. He is the manager of the World Bank's Global Partnership on Fisheries--PROFISH--which supported The Sunken Billions study. The partnership includes developing countries, leading bilateral donors to the fisheries sector, and technical institutions such as FAO. With a background in biology and economics, he has spent most of his career in developing countries and worked as a fisherman, fish farmer, fisheries scientist, and economic advisor on fisheries to governments. He is the author of global studies on discards, on aquaculture, and on fisheries enforcement. Rolf Willmann is a Senior Fisheries Planning Officer in FAO's Fisheries and Aquaculture Department. He focuses on policy and management issues in marine capture fisheries, especially on the implementation of the Code of Conduct for Responsible Fisheries. He has led the development of the FAO Ecolabeling Guidelines for Marine Capture Fisheries and undertaken numerous assessments of the economics of capture fisheries in developing countries, with a particular focus on small-scale fisheries and poverty issues. He was the secretary of the Global Conference on Small-Scale Fisheries held in Bangkok in 2008 (http://www.4ssf.org/index.htm). xiii A C R O N Y M S A N D A B B R E V I AT I O N S ARD Agriculture and Rural Development Department, World Bank DECRG Development Research Group, World Bank ENV Environment Department, World Bank EU European Union FAO Food and Agriculture Organization of the United Nations FIES Fisheries and Aquaculture Information and Statistics Service, FAO FIEP Fisheries and Aquaculture Development Planning Service, FAO GDP gross domestic product GRT gross registered tonnage GT gross tonnage IIFET International Institute for Fisheries Economics and Trade IMF International Monetary Fund IPCC Intergovernmental Panel on Climate Change IPOA International Plan of Action ITQ individual transferable quota IUU illegal, unreported, and unregulated fishing kg kilogram kW kilowatt xv MEY maximum economic yield MSY maximum sustainable yield NMFS National Marine Fisheries Service (U.S.) OECD Organisation for Economic Co-operation and Development PoI Plan of Implementation ton metric ton (1,000 kg) UBC University of British Columbia WSSD World Summit on Sustainable Development WTO World Trade Organization All dollar amounts are U.S. dollars unless otherwise indicated. xvi ACRONYMS AND ABBREVIATIONS E X E C U T I V E S U M M A RY The contribution of the harvest sector of the world's marine fisheries to the global economy is substantially smaller than it could be. The lost economic benefits are estimated to be on the order of $50 billion annually. Over the past three decades, this cumulative global loss of potential economic benefits is on the order of $2 trillion. The losses represent the difference between the potential and actual net economic benefits from global marine fisheries. By improving governance of marine fisheries, society could capture a sub- stantial part of this $50 billion annual economic loss. Through comprehensive reform, the fisheries sector could become a basis for economic growth and the creation of alternative livelihoods in many countries. At the same time, a nation's natural capital in the form of fish stocks could be greatly increased and the negative impacts of the fisheries on the marine environment reduced. In economic terms, some 60 percent of the world's marine fish stocks were "underperforming assets" in 1974, the year when the Food and Agriculture Organization (FAO) initiated its reports on the state of the world's marine fish stocks. By 2004, more than 75 percent of the fish stocks were underperform- ing, at an estimated annual loss of $50 billion to the global economy. The "sunken billions" is a conservative estimate of this loss. The estimate excludes consideration of losses to recreational fisheries and to marine tourism and losses attributable to illegal fishing are not included. The estimate also excludes consideration of the economic contribution of dependent activities such as fish processing, distribution, and consumption. It excludes the value of biodi- versity losses and any compromise to the ocean carbon cycle. These exclusions suggest that the losses to the global economy from unsustainable exploitation of living marine resources substantially exceed $50 billion per year. xvii For over three decades, the world's marine fish stocks have come under increasing pressure from fishing, from loss of habitats, and from pollution. Rising sea temperatures and the increasing acidity of the oceans are placing further stress on already stressed ecosystems. Illegal fishing and unreported catches undermine fishery science, while subsidies continue to support unsustainable fishing practices. THE STATE OF MARINE FISH STOCKS AND FISHERIES The global marine catch has been stagnant for over a decade, while the natural fish capital--the wealth of the oceans--has declined. FAO reports that an increasing proportion of the world's marine fish stocks is either fully exploited or overexploited. Most of the world's most valuable fish stocks are either fully exploited or overexploited. The 25 percent that remains underexploited tends to consist of lower-value species or the least profitable fisheries for such stocks. When fish stocks are fully exploited in the biological sense, the associated fisheries are almost invariably performing below their economic optimum. In some cases, fisheries may be biologically sustainable but still operate at an economic loss. For example, the total catch may be effectively limited by regulations, but in a world of increasing fuel subsidies, the real cost of harvesting the catch may exceed the landed value. The depletion in fish capital resulting from overexploitation is rarely reflected in the reckoning of a nation's overall capital and GDP growth. This study and previous studies indicate that the current marine catch could be achieved with approximately half of the current global fishing effort. In other words, there is massive overcapacity in the global fleet. The excess fleets competing for the limited fish resources result in stagnant productivity and economic inefficiency. In response to the decline in physical productivity, the global fleet has attempted to maintain profitability by reducing labor costs, lobbying for subsidies, and increasing investment in technology. Partly as a result of the poor economic performance, real income levels of fishers remain depressed as the costs per unit of harvest have increased. Although the recent changes in food and fuel prices have altered the fishery economy, over the past decade real landed fish prices have stagnated, exacerbating the problem. The value of the marine capture seafood production at the point of harvest is some 20 percent of the $400 billion global food fish market. The market strength of processors and retailers and the growth of aquaculture, which now accounts for some 50 percent of food fish production, have contributed to downward pressure on producer prices. THE ESTIMATE OF THE "SUNKEN BILLIONS" In technical terms, this study estimates the loss of potential economic rent in the global fishery. For the purposes of this study, economic rent is considered xviii EXECUTIVE SUMMARY broadly equivalent to net economic benefits, which is the term used throughout most of the report. The lost benefits, or the difference between the potential and actual net benefits, can be largely attributed to two factors. First, depleted fish stocks mean that there are simply fewer fish to catch and therefore that the cost of catching is greater than it could be. Second, the massive fleet overca- pacity, often described as "too many fishers chasing too few fish," means that the potential benefits are also dissipated through excessive fishing effort. This study estimated the difference between the potential and actual net eco- nomic benefits from global marine fisheries using 2004 as the base year. The esti- mate was made using a model that aggregated the world's highly diverse fisheries into a single fishery. This made it possible to use the available global fisheries data such as production, value of production, and global fisheries profits as inputs to the model. Some of the global data sets and inputs required for the model are either deficient or less than robust. Consequently, several further assumptions were required, and in each case the rationale behind the assumption is provided. For example, based on available estimates, the maximum sustainable (biological) yield from the world's fisheries was assumed to be 95 million metric tons (tons). To account for the inherent uncertainties in the data and the simplification in the model, estimates of the most likely range of lost economic benefits were obtained using sensitivity analyses and stochastic simulations. For the base year, 2004, the 95 percent confidence interval for the lost eco- nomic benefits in the global marine fishery was found to be between $26 billion and $72 billion, with the most likely estimate to be on the order of $50 billion. The estimate of $50 billion--the sunken billions--does not take account of several important factors and is thus a conservative estimate of the potential losses. The model does not include the costs of fisheries management and does not reflect the costs to the marine environment and biodiversity resulting from weak fisheries governance. The model does not fully capture the costs of sub- sidies, or the benefits that would result from efficient fisheries that would favor the least-cost producers. Nor does the model capture the potential downstream economic benefits of more efficient fisheries. The estimate does not count the benefits from recreational fisheries, from marine tourism, or from healthy coral reefs. The estimate is consistent with previous studies, however, and the study provides a replicable and verifiable baseline for future tracking of the economic health of marine fisheries. The real cumulative global loss of net benefits from inefficient global fish- eries during the 1974­2008 period is estimated at $2.2 trillion. To derive the $2.2 trillion value, the estimated loss of $50 billion in 2004 was used as a base value to construct a time series of losses. The 1974­2008 period was used because the FAO produced its first "state of the marine fisheries" report in 1974, the first of a series of 14 such reports. The changing proportion of global fish stocks reported as fully or overexploited in this series was used to build the annual loss estimate. An opportunity cost of capital of 3.5 percent was assumed. EXECUTIVE SUMMARY xix CAPTURING THE SUNKEN BILLIONS The depletion of a nation's fish stocks constitutes a loss of the nation's stock of natural capital and thus a loss of national wealth. The depletion of global fish stocks constitutes a loss of global natural capital. Economically healthy marine fisheries can deliver a sustainable flow of economic benefits, a natural bounty from good stewardship, rather than being a net drain on society and on global wealth. Recovery of the sunken billions can take place in two main ways. First, a reduction in fishing effort can rapidly increase productivity, profitability, and net economic benefits from a fishery. Second, rebuilding fish stocks will lead to increased sustainable yields and lower fishing costs. Some fish stocks can rebuild rapidly, but the uncertain dynamics of marine ecosystems means that certain stocks may not be readily rebuilt. One such example is the Canadian cod stocks, which, despite a reduction in fishing effort, have not recovered. The crisis in the world's marine fisheries is not only a fisheries problem, but one of the political economy of reform. Fisheries reform requires broad-based political will founded on a social consensus. Building such a consensus may take time and may require forging a common vision that endures changes of governments. Experience shows that successful reforms may also require champions or crises to catalyze the process. Fisheries reform will require reduction in fishing effort and fleet capacity. Thus, successful reforms should take the time to build consensus among fishers on the transition pathways, make provisions for creating alternative economic opportunities, establish social safety nets for affected fishers, and generally manage transition in an equitable manner. Successful reforms will require strengthening of marine tenure systems, equitable sharing of benefits from fisheries, and curtailment of illegal fishing. Successful reforms will require reduction or elimination of per- nicious subsidies in the transition to sustainability. Rising food prices and a growing fish food gap for over 1 billion people dependent on fish as their primary source of protein add to the rationale for fishery reform. Rising fuel prices and the need for greater resilience in marine ecosystems in the face of growing pressures from climate change reinforce the arguments for concerted national and international actions to rebuild fish wealth. The heavy carbon footprint of some fisheries and emerging evidence that depletion of marine fisheries may have undermined the ocean carbon cycle add to the justification for fisheries reform. The depletion of global fish stocks cannot, however, be attributed solely to fishing. Pollution, habitat destruction, invasive species, and climate change all play a role in this process. THE COSTS OF REFORM Comprehensive reform of marine fisheries governance can capture a substantial proportion of the sunken billions. The transition to economically healthy xx EXECUTIVE SUMMARY fisheries will require political will to implement reforms that incur political, social, and economic costs. These are the costs of investing in rebuilding fish stocks, which requires an initial reduction in fishing activity and harvest rates. The benefits of this investment accrue later when fish stocks have grown and when fishing fleets have adjusted. Once recovered, many ocean fisheries can generate a substantial economic surplus and turn a net economic loss to soci- ety into a significant driver of economic growth and a basis for alternative livelihood opportunities. However, the social, economic, and institutional costs of this transition must be financed. The allocation of this cost burden between public and private sectors presents challenges both to fiscal policy and man- agement practice. The most critical reform is the effective removal of the open access condi- tion from marine capture fisheries and the institution of secure marine tenure and property rights systems. Reforms in many instances would also involve the reduction or removal of subsidies that create excess fishing effort and fishing capacity. Reduction or removal of subsidies can, however, cause undesirable economic and social hardship, especially at a time when fishers face volatile prices of fuel and food. Subsidies that create perverse incentives for greater investment and fishing effort in overstressed fisheries tend to reinforce the sec- tor's poverty trap and prevent the creation of economic surplus that can be invested in alternatives, including education and health. The World Bank has suggested that any subsidies should be temporary, as part of a broader strategy to improve fisheries management and enhance productivity. Rather than sub- sidies, the World Bank has emphasized investment in quality public goods such as science, infrastructure, and human capital, in good governance of natural resources, and in an improved investment climate. The alternative to reform--business as usual--is a continued decline in global fish wealth, harvest operations that become increasingly inefficient, and growing poverty in fishery-dependent communities. Failure to act implies increased risks of fish stock collapses, increasing political pressure for subsi- dies, and a sector that, rather than being a net contributor to global wealth, is an increasing drain on society. THE BIOLOGICAL AND ECONOMIC HEALTH OF FISHERIES The focus on the declining biological health of the world's fisheries has tended to obscure the even more critical deterioration of the economic health of the fisheries, which stems from poor governance and is both a cause and a result of the biological overexploitation. Economically healthy fisheries are fundamental to achieving accepted goals for the fisheries sector, such as improved livelihoods, food security, increased exports, and the restoration of fish stocks, which is a key objective of the World Summit on Sustainable Development Plan of Implementation. This study makes the economic case EXECUTIVE SUMMARY xxi for comprehensive reform of fisheries governance and complements ecological and conservation arguments. Many national and international fishery objectives focus on maintaining or increasing capture fishery production, and it is argued that national policies would benefit from a greater focus on maximizing net benefits and choosing economic or social yield as an objective rather than continuing to manage fish- eries with maximum sustainable yield as an objective. Such a socioeconomic focus implies that planners and decision makers devote greater attention to reform of the pernicious incentive structures driving fisheries overexploitation. A clear picture of the economic health of fisheries is fundamental to build- ing the economic sustainability necessary to conserve and rebuild fish stocks. Such a health check needs to take account of subsidies, environmental exter- nalities, and depletion of fish capital, and underpins any coherent policy debate on fishery reform. NET BENEFITS AND TENURE It has long been understood that because the benefits from fish harvests are to individuals but costs of resource reduction are shared, the net benefits from use of common pool resources, such as fish stocks, will tend to be dissipated. In many countries, marine fishery resources are considered to belong to the nation, and governments are charged with stewardship of this public asset. This has in some instances undermined the traditional rights systems observed by local communities and led to a de facto open access condition. The public, or common pool, character of marine fish resources is often deeply embedded in law and practice, so strengthening marine fisheries tenure is a complex undertaking and faces political, social, and legal challenges. It will require good understanding of traditional or de facto fishing rights systems and of the func- tionality and legitimacy of national fisheries legislation as a basis for bridging the divide between community and national stewardship functions. It is not the role of this study to be prescriptive with regard to marine fish- eries tenure but to raise awareness of the link between tenure and net benefits and to suggest that avoidance of the sensitive issues of marine use rights is likely to result in a continued slide toward poverty for many fishery-dependent communities. Reforms will require empowerment of poor fisher communities, establishment of secure user and property rights, and investment in collective action by a strengthened civil society. In a world of volatile fuel and food prices, any apparent advantage held by small-scale fisheries also needs to be supported by a greater investment in the management of small-scale fisheries. These are among the many reasons why the economic objectives--increas- ing the net benefits and wealth from fisheries--need to be at center stage in efforts to resolve the crisis in marine fisheries. Public awareness and under- standing of the potential and actual flows of economic benefits can inform the xxii EXECUTIVE SUMMARY political economy of reform and help leaders move toward socially responsible and sustainable fisheries underpinned by sound scientific advice. RECOMMENDATIONS 1. Use the results of this study to raise awareness among leaders, stakeholders, and the public of the potential economic and social benefits from improved fisheries governance in contrast to the sector's current drain on society in many countries. 2. Promote country- and fishery-level estimates of the potential economic and social benefits of fisheries reform and assessment of the social and political costs of reform as a basis for national- or fishery-level dialogue. 3. Build a portfolio of experiences in the process of fisheries reform with a focus on the political economy of reform and the design of the reform process, including consideration of the timing and financing of reform and structuring a national dialogue on the reform process. Fisheries reform initiatives should draw on the knowledge and lessons of reforms in other sectors, in particular with regard to the impact on the poor and the effectiveness and equity of adjustment mechanisms. 4. Progressively identify a portfolio of reform pathways based on a consensus vision for the future of a fishery and founded on transparency in the distri- bution of benefits and social equity in reforms. The common elements of such pathways could include effective stakeholder consultation processes; sound social and economic justifications for change; and an array of social and technical options, including decentralization and comanagement initia- tives to create more manageable fishery units. A reform process will bend the trusted tools of fisheries management to new tasks. Sound scientific advice, technical measures such as closed seasons, and effective registration of vessels are likely to form synergies with poverty reduction strategies, tran- sitions out of fisheries, social safety nets, and community comanagement. 5. Review fiscal policies to phase out subsidies that enhance fishing effort and fishing capacity and redirect public support measures toward strengthening fisheries management capacities and institutions, while avoiding social and economic hardships in the fisheries reform process. 6. In an effort to comply with the call of the World Summit on Sustainable Development Plan of Implementation for restoration of fish stocks, coun- tries could, on a timely basis, provide to their public an assessment of the state of national fish stocks and take measures to address the underreport- ing or misreporting of catches. EXECUTIVE SUMMARY xxiii C H A P T E R O N E Global Trends in Fisheries 1.1 INTRODUCTION conomically healthy fisheries are fundamental to achieving accepted E goals for the fisheries sector, such as improved livelihoods, exports and food security, and the restoration of fish stocks, which is a key objective of the Plan of Implementation adopted at the World Summit on Sustainable Development in Johannesburg in 2002. Many national and international fishery objectives focus on maintaining or increasing the quantity of capture fishery production while less attention is devoted to the economic health of fisheries. An analysis of key global trends in fisheries--including fish production and consumption, the state of the fish stocks, and employment in the sector-- provides the context and builds a profile of the economic health of the world's marine fisheries. Estimates of the economic value of global marine fishery production and costs of production are used as inputs to an aggregate economic model to derive a range of estimates of potential economic rents lost, largely as a result of suboptimal governance of the marine fisheries worldwide. Key assumptions underlying the model are described. 1.1.1 Purpose and Outcomes of the Study The purpose of this study is to raise the awareness of decision makers regard- ing the economic dimensions of the crisis in the world's marine capture fish- eries. The target group includes not only fisheries professionals, many of whom grapple with this crisis on a daily basis, but a broader audience of policy and decision makers who can foster reforms in fisheries with a view to rebuilding CHAPTER TITLE 1 fish wealth and capital as a basis for economic growth and biologically and eco- nomically healthy fisheries. The study shows that, in aggregate, the global marine fisheries in the base year, 2004, represent a net economic loss to society and often a poverty trap for dependent communities. The study shows that if marine capture fisheries were organized to move fisheries in the direction of maximizing economic effi- ciency, then national fisheries sectors, fishing communities, and society as a whole would reap substantial economic benefits. The political, social, and eco- nomic costs of such reforms are briefly discussed. 1.1.2 Structure of the Study Chapter 1 provides an overview of trends in global fisheries to set the context for the study. Chapter 2 describes the economic performance of the world's capture fish- eries. The study reviews the main determinants for the economic performance of global fisheries, such as the value of fish production, the cost of factors of production, and productivity trends. The available global data sets are described as a framework for selection of the parameters used in the model. Fisheries are shown to benefit from significant subsidies that often undermine sustainability and maintain inefficiency. Illegal fishing is recognized as a gov- ernance failure undermining the economic and biological health of fisheries. Substantial additional work is suggested to remove uncertainties with respect to the magnitude of unrecorded catches at the global level. Chapter 3 presents the approach and method used to build a bioeconomic model of the aggregate global fishery. Additional technical details of the model are provided in the appendixes. Chapter 4 presents the results of the analysis, highlighting the poor eco- nomic health of the world's marine fisheries and the need for greater attention to improving the economic well-being of fisheries and fishers: as a sustainable source of economic growth, as a pathway out of poverty, as a means of con- tributing to food security, and as a way to build resilience to the impending effects of climate change. Chapter 5 discusses the results and draws on available case studies to identify key elements in moving fisheries toward a more economically rational base with- out sacrificing fundamental social objectives in pursuit of economic efficiency. Four appendixes provide supplementary information. 1.2 THE DETERIORATING STATE OF THE MARINE FISHERY RESOURCES The crisis in marine fisheries has been well documented in biological terms. This study focuses on the economic health of the world's fisheries as a com- plement to the numerous reviews of the ecological state of the global marine 2 THE SUNKEN BILLIONS fisheries. Globally, the proportion of fully exploited, and either overexploited, depleted, or recovering fish stocks has continued to increase from just above 50 percent of all assessed fish stocks in the mid-1970s to about 75 percent in 2005 (box 1.1) (FAO 2006). This indicates that, in economic terms, more than 75 percent of the world's fisheries are underperforming or are subject to eco- nomic overfishing. In 1974, about 40 percent of the assessed stocks were rated as underexploited or moderately exploited. By 2005, this percentage had fallen to 25 percent (FAO 2007c). Between 1950 and 1970, the recorded catch of both the demersal (bottom- dwelling) and pelagic species (species that live in the upper layers of the sea) Box 1.1 Stagnating Global Marine Catch The box figure indicates that the reported global marine catch has stagnated at a level of 80­85 million tons since 1990. This stagnation hides several underlying trends in the composition of the catch as described below. One-half of the marine capture fish stocks monitored by the FAO are des- ignated as fully exploited, producing at or close to their maximum sustainable yield. Another 25 percent of the marine fish stocks are either overexploited, depleted, or recovering from depletion and are yielding less than their maxi- mum sustainable yield (FAO 2007c). The remaining 25 percent of the marine capture fish stocks are underexploited or moderately exploited, and although this implies that more could be produced, many of these underexploited stocks are low-value species or species for which harvesting may be uneco- nomical. Global production of seafood from wild stocks is at or close to its long-run biological maximum. Reported Global Marine Catch, 1950­2006 95 85 75 65 tons 55 45 Million 35 25 15 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Source: FAO FishStat Plus. GLOBAL TRENDS IN FISHERIES 3 grew considerably (figure 1.1). Since 1970, demersal fish catches have stabilized at around 20 million tons a year, while pelagic catches grew to a peak volume of almost 44 million tons in 1994. Since then, annual pelagic catches have fluc- tuated between 36 and 41 million tons. Thus, the global fish supply from marine capture fisheries increasingly relies on lower-value species characterized by large fluctuations in year-to- year productivity, concealing the slow degradation of the demersal high- value resources. About 17 percent of the global catch reported to FAO by member countries is not reported by species group. Thus, the FAO's FishStat Plus database does not readily allow assessment of these species composi- tion changes on a global basis. This change in the species composition of the catch is commonly referred to as "fishing down marine food webs" (Pauly et al. 1998). The stagnant level of production is thus maintained by the rela- tively higher growth rate of a higher proportion of smaller fish species lower on the food web and a likely decrease in the average age of the catch, which jointly contribute to maintaining fish biomass. In some fisheries, the targets of fishing have also expanded to cover an entire spectrum of species in the ecosystem "fishing through the food webs" (Essington, Beaudreau, and Weidenmann 2006). The changing patterns of discards (fish caught but dumped unwanted at sea) also suggests that the global catch now comprises substantial quantities of lower- value, previously discarded fish: the amount of fish discarded may have decreased by over 10 million tons between 1994 and 2004 (Kelleher 2005). For example, the quantity of so-called trash fish used for aquaculture feed is estimated to be 5­7 million tons (Tacon 2006; APFIC 2006). There is also growing evidence that the Figure 1.1 Catch of Selected Species Groups in Marine Fisheries 45 Cephalopods Crustaceans 40 Demersal marine fish 35 Pelagic marine fish Others 30 tons 25 20 Million 15 10 5 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Source: FAO FishStat Plus. 4 THE SUNKEN BILLIONS biomass of large predatory fishes has declined substantially from preindustrialized levels in many regions (Myers and Worm 2003; Ahrens and Walters 2005), although this may not hold true for all fisheries (Sibert et al. 2006). Climatic variability has always been a significant determinant of fish stock growth and decline, and response to variability is part of the daily business of fishing. However, climate change, as described by the Intergovernmental Panel on Climate Change (IPCC 2007), is placing additional stress on fish- eries already stressed by pollution, habitat loss, and fishing pressure. Although recent studies on coral reefs (Baird et al. 2007) and reviews of the likely impacts of climate change on the fisheries of the North Atlantic pro- vide important guidance on trends, in the case of developing countries, the impact of changes in sea temperature and ocean acidity on their fish stocks remains largely undetermined. Similarly, the impact of sea-level rise and erratic climatic events on the community and household wealth of coastal fishing populations remains largely unquantified. These added ecological, environmental, and economic stresses caused by climate change add to the urgency and economic justification for restoring the resilience and health of fish stocks (FAO 2008; European Commission 2007; Sustainable Fisheries Livelihoods Project 2007). 1.3 PROFILE AND TRENDS IN GLOBAL FISHERIES PRODUCTION In 2006, total reported world fishery production (excluding aquatic plants) reached almost 160 million tons (figure 1.2), of which 53 percent originates from marine capture fisheries. Over the past 20 years, the continued growth in world fish production is largely attributable to aquaculture (see figure 1.2). China is the largest producing country, contributing 49 million tons in 2005, of which 32 million tons are from aquaculture (figure 1.3). Developing countries have contributed more than one-half of total capture fish pro- duction since 1990 (figure 1.4) and this share reached more than two-thirds in 2005. 1.4 TRADE AND FISH CONSUMPTION Rising demand for fish has been a major driver of increased fishing effort. Spurred by the globalization of markets for fish, some 37 percent of global fish production flows into international trade, making fish one of the most traded "agricultural" commodities and accounting for up to 13 percent of global "agricultural" trade. The benefits of increasing globalization in fish trade have nevertheless been reduced by growing overexploitation because ineffective governance of fisheries has allowed the depletion of fish stocks--the natural capital, or fish wealth (ICTSD 2006). GLOBAL TRENDS IN FISHERIES 5 Figure 1.2 World Marine and Inland Capture and Aquaculture Production, 1950­2005 100 90 Inland 80 Marine 70 Aquaculture tons 60 of 50 40 Millions 30 20 10 0 1950 1956 1962 1968 1974 1980 1986 1992 1998 2004 Source: FAO FishStat Plus. Figure 1.3 World Capture and Aquaculture Production, 1950­2005 150 Rest of the world - aquaculture China - aquaculture Rest of the world - capture 120 China - capture tons 90 of 60 Millions 30 0 1950 1956 1962 1968 1974 1980 1986 1992 1998 2004 Source: FAO FishStat Plus. In 2006, total world trade of fish and fishery products reached a record (export) value of $86.4 billion, more than a 10-fold increase since 1976, when global fish trade statistics first became available. The share of developing coun- tries in total fishery exports was 48 percent by value and 57 percent by quan- tity. Growth in aquaculture production has been an important factor for the global expansion of seafood trade. The growth in reported global fish production has more than kept pace with population growth (figure 1.5). Based on the reported global fish production, the total amount of fish available for human consumption is estimated to have reached 107 million tons in 2005, providing an average 6 THE SUNKEN BILLIONS Figure 1.4 Total Recorded Marine Capture Production by Economic Group, 1970­2005 90 Developed countries or areas 80 Developing countries or areas 70 Total marine capture 60 tons of 50 40 30 Millions 20 10 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Source: FAO FishStat Plus. Figure 1.5 World Population and Global Fish Supply, 1970­2003 12 10 6.0 Fish supply from capture fisheries 8 Fish supply from aquaculture (kg) Population (billions) supply 6 capita 5.0 Per Population 4 2 0 4.0 1980 1983 1986 1989 1992 1995 1998 2001 Source: FAO FishStat Plus; World Bank 2006. global per capita fish supply of 16.5 kilograms, but with large differences across regions and countries as well as within countries (FAO 2007c). These global values, however, may not adequately reflect important subsistence fish consumption and consumption of unreported commercial production from small-scale fisheries. GLOBAL TRENDS IN FISHERIES 7 Figure 1.6 Regional Trends in Annual Fish Supply, 1961­2003 Africa South America 20.0 Asia Asia excl. China Europe Global average 16.0 capita per 12.0 Kilograms 8.0 4.0 1961 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 Source: FAO FishStat Plus; FAO 2007a. Aquaculture products continue to capture an increasing share of global mar- kets for fish. This is driven by technological advances in production, relatively lower production costs (compared with capture fisheries), and globalization of fish trade. The competition from aquaculture places additional economic stress on capture fisheries and contributes to trade disputes as farmed fish capture market share from traditional producers. Rising demand in China and Europe has largely driven the increase in aver- age global per capita fish consumption (figure 1.6). This global increase was particularly pronounced in the 1980s and 1990s but has since stabilized at around 16 kilograms per capita per year (FAO 2007a). Per capita consump- tion of fish in South America is stabilizing after a peak in 1995, but per capita consumption in Africa and South America remains low (see figure 1.6). In both regions, but especially in sub-Saharan Africa, low animal protein intake is believed to be largely a result of low per capita incomes. Traditionally, low- value fish and fishery products provide cheap protein to the poorer popula- tions in these regions and in Asia. Africa is the only continent where per capita fish consumption has been in decline (less than half the global average), and because fish tends to be the lowest priced animal protein, this trend raises concern about the nutritional quality of the diet, particularly in sub-Saharan Africa. Aquaculture production has responded to the increasing demand in Asia. However, despite recent growth, African aquaculture has been unable to respond to the continent's nutritional needs. The increased demand for aquaculture and livestock feeds based on trash fish and low-value species has a potential negative impact on the availability and accessibility of these products for direct human consumption (APFIC 2006). 8 THE SUNKEN BILLIONS C H A P T E R T W O The Economic Performance of World Marine Capture Fisheries he economic performance of global marine capture fisheries is deter- T mined by the quantity of fish caught, the price of fish, the harvesting costs, and the productivity of the fisheries. The following sections sum- marize the global profile of each of these determinant factors and discuss the closely related issues of subsidies and excess capacity in the global fishing fleet. 2.1 VALUE OF PRODUCTION AND GLOBAL FISH PRICES In 2004 (the base year for the study), the total nominal value1 of reported global fish production was estimated at $148 billion, of which capture fisheries was $85 billion and aquaculture was $63 billion. The total estimated value of the reported marine catch of 85.7 million tons was $78.8 billion (FAO 2007c).2 2.1.1 Ex-vessel Prices The nominal average ex-vessel price was $918 per metric ton for the reported marine catch and $666 per ton for the reported inland (freshwater) catch. The average farmgate price for cultured fish was $1,393 per ton. The higher unit price for aquaculture products is a result of the production of high-value species (for example, shrimp and salmon). The ex-vessel prices are considered to be conservative and close to true market prices, being relatively free of taxes, subsidies, and other market-distorting influences. CHAPTER TITLE 9 2.1.2 Export Prices Fish price data sets are relatively incomplete at the global level: the primary long-term price data series is the fish export unit value derived from FAO's FishStat Plus trade statistics. The unit value of exports may underestimate the global trend in real fish prices. On the one hand, higher-value fish products tend to be exported. On the other hand, aquaculture has a growing share in world fish trade, and prices of many cultured species have tended to decline from the initial elevated price levels. Because of the changing product composition of exports, the export values are only indicative of the price trends, but the values nevertheless show several interesting features (see figure 2.1). There was a significant decline in fish prices between 1978 and 1985, followed by a strong price rise from the mid- 1980s to the early 1990s, a gradual decline until 2001, and a recovery in prices during the most recent years. The real unit value of exports in 2004 was no higher than it was in the late 1980s. This strongly suggests that the global price of fish in 2004 was not significantly different from that in the late 1980s. Setting aside numerous supply-driven real price fluctuations, the real prices of many fish commodities saw little change between the early 1990s and late 2007 (Josupeit 2008, Asche and Bjørndal 1999). The notable exceptions are increased fish meal and fish oil prices, which have been driven by higher demand for meat and aquaculture products. Tuna prices and some whitefish Figure 2.1 Trends in the Nominal and Real Unit Export Value of Fishery Products 3,000 Real export unit value (US$ per ton) 75 Nominal unit value (US$ per ton) 65 2,500 Total nominal export value (right axis) 55 2,000 45 ton per 1,500 35 millions US$ 25 US$ 1,000 15 500 5 0 ­5 1976 1980 1984 1988 1992 1996 2000 2004 Source: FAO FishStat Plus. Note: The deflator used for real values is the U.S. producer price index for all commodities, base year 1982 (Delgado et al. 2003). Values exclude aquatic plants. 10 THE SUNKEN BILLIONS prices have also increased, while supplies from aquaculture have dampened prices for some products. Fillet and product yields have improved, wastage has been reduced, and supply chains shortened, making downstream industry increasingly more efficient and competitive, often decreasing profit margins for primary producers and intermediaries. Thus, although the unit value of the aggregate reported catch has remained relatively constant, the higher proportion of relatively lower-value "trash fish" and small pelagic species is buoyed up by the increasing scarcity value of species higher on the food web, such as lobster or grouper. The scarcity of some higher-value species has created opportunities to fish in deeper waters, often at a higher cost per unit of catch and also at a cost to the relatively unknown bio- diversity of the continental slopes. Growth in demand for fish is concentrated in developing countries where populations and per capita incomes show strong growth. However, survey data from China in the period 1980­2000 indicate only slight increases in the real price of fish (Delgado et al. 2003). Recent studies show substantial increases in Chinese seafood consumption with increases of over 100 percent in lower- income households to over 150 percent for higher-income families between 1998 and 2005 (Pan Chenjun 2007). In contrast, while demand continues to grow in the United States and real prices of fresh fish show a long-term increas- ing trend, the price of the traditional frozen products and particularly of canned products has declined during the last 30 years (figure 2.2). More Figure 2.2 Trends in U.S. Real Price Indexes for Fish and Seafood Products, 1947­2006 2 1.8 Frozen packaged fish and seafood Canned and cured seafood 1.6 Fresh packaged fish and seafood 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1950 1958 1966 1974 1982 1990 1998 2006 Source: Calculated from U.S. Bureau of Labor Statistics 2007. This is an update of figure 3.2 in Delgado et al. (2003). Note: 1982 is the base year ("1" on the y-axis). THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 11 recently, a weakening U.S. dollar exchange rate and consumer spending may be contributing to a recent decline in U.S. shrimp imports, a key seafood indica- tor (Seafood International 2008). 2.1.3 Value of Intangibles Healthy marine ecosystems generate a range of intangible values, which are difficult to estimate in the absence of robust global data sets and agreed valu- ation methods. These values arise from marine biodiversity, the existence value of megafauna, and the value of environment services from natural assets such as healthy reefs (Cesar 2000; UNEP-WCMC 2006; Worm et al. 2006). There may be additional potential benefits from ocean carbon sequestration resulting from healthy fish stocks (Lutz 2008). The global fishing fleet cur- rently has substantial excess capacity, but a global fleet that is "in balance" with the fish stocks can significantly reduce the carbon footprint of the indus- try. The bioeconomic model used in this study does not include a valuation of these intangibles. 2.2 FISHING COSTS AND PRODUCTIVITY There is no representative global data set on the costs of fishing. However, costs and earnings studies are available from a number of countries and fisheries. Fishing costs vary greatly by type of fishery and locality: for exam- ple, trawl fisheries tend to have high fuel costs, while many smaller vessels are nonmotorized and the cost of subsistence fishing may be little more than the cost of the labor involved. In general, the major cost factors for most fisheries are: labor (30­50 percent of total costs); fuel (10­25 percent); fishing gear (5­15 percent); repair and maintenance (5­10 percent); and capital cost, such as depreciation and interest (5­25 percent). The trends in the costs of each of these factors of production are relevant not only for an understanding of the historical trends in fisheries but also to provide a basis for future projections of, for example, the effect of changing fuel prices. Available cost data must be treated with some caution, because the true cost data tend to be confounded by taxes and subsidies. There is ample evi- dence that at the global level productivity has deteriorated, especially in recent years, as the majority of producers incur higher fishing costs while the global catch has remained stagnant. 12 THE SUNKEN BILLIONS 2.2.1 Fuel Prices and Productivity The cost of crude oil not only directly relates to fishing fuel costs but also indi- rectly affects the cost of fishing nets and lines and of vessel construction and repair. Figure 2.3 shows an index of the real price of crude oil and an index of the real material costs in U.S. ship building. For comparison purposes, the index of the real unit value of fish exports is also illustrated. It shows that until about mid-1980, real unit export value rose faster than crude oil and unit material costs, but since the late 1980s price and cost trends have been fairly similar, with the crude oil price climbing steeply since 2000. Since 2000, fuel subsidies have probably played an increasingly important role in supporting the financial viability of fishing operations in some coun- tries. Such fuel subsidies (mostly forgone taxes) to the fishing sector by gov- ernments globally are estimated to be in the range of $4.2 billion to $8.5 billion per year (Sumaila et al. 2008). In the absence of productivity gains, figure 2.3 strongly suggests that the economic performance of global marine fisheries is unlikely to have improved since the early 1990s. Several factors continue to undermine productivity. These include rising oil prices; rising costs of fishing gear and vessels, often compounded by unfavorable exchange rates (for countries that import factors Figure 2.3 Real Trends in Crude Oil Price,Vessel Material Costs, and Fish Export Unit Value (1998 = 100) 250 Real crude oil price index Real material cost index 230 Real export unit value index 210 190 170 150 130 110 90 70 50 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 Source: FAO FishStat Plus; FAO FIEP; U.S. Department of Energy, Energy Information Administration; http://www.coltoncompany.com/shipbldg/statistics/index.htm, based on data from the U.S. Bureau of Labor Statistics. Deflator used for real values: U.S. producer price index for all commodities, base year 1982 (Delgado et al. 2003). THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 13 of production); an increasing regulatory burden; and depletion of inshore stocks, causing fishers to travel farther to fishing grounds. By contrast, nonmotorized fisheries, fisheries that use passive gears (such as traps) and thus relatively less fuel, and fisheries that have ready access to export markets may have seen an improvement in profitability in this period. Tech- nology also has driven productivity gains. Using sophisticated fish-finding equipment, tuna purse seiners in the western Indian Ocean can now harvest three times the annual catch of seiners operating in the mid-1980s. New designs of trawls reduce the required engine power and fuel consumption by a factor of 33 percent or more (Richard and Tait 1997). Electronic sale of fish while vessels are still at sea reduces transaction costs, helps prevent loss of product quality and value, and makes markets more efficient (Jensen 2007). However, as these innovations are adopted and spread throughout a fleet, aggregate productivity falls, and the economic rents generated through the increasing productivity are not maintained. Fuel consumption varies considerably, depending not only on different fish- ing methods and types of fisheries but also on the fuel efficiency of engines. At the global level, on average each ton of fish landed required nearly half a ton of fuel. In value terms, production of a ton of fish worth $918 required $282 worth of fuel, or 31 percent of the output value, in 2004. The impact of the recent (2007­08) doubling of fuel prices is briefly addressed in a subsequent section and the overall trend in fish, food, and fuel prices is illustrated in figure 2.4. Figure 2.4 Trends in Fish, Food, and Fuel Prices 140 Food price index 140 Fish export price index imputed (r2=0.97) 130 120 Fuel price ) 120 100 indexes price 110 80 US$/barrel( fish ricep and 100 60 Fuel food 90 40 80 20 2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: FAO FishStat Plus; FAO FIEP; U.S. Department of Energy, Energy Information Administration. The imputed fish price index for 2006 and 2007 was derived from a corre- lation with the FAO Food Price Index. 14 THE SUNKEN BILLIONS 2.2.2 Trends in Employment, Labor Productivity, and Fishing Incomes During the past three decades, the number of fishers and fish farmers has grown at a higher rate than the world's population growth rate (figure 2.5). Catching and fish-farming activities provided livelihoods to an estimated 41 million peo- ple in 2004 employed as either part-time or full-time fishworkers.3 Applying an assumed ratio of 1:3 for direct employment (production) and secondary activities (postharvest processing, marketing, distribution), respectively (FAO 2007b), about 123 million people are estimated to be involved in postharvest processing, distribution, and marketing activities. Many countries do not separate capture fisheries and aquaculture employment data. Based on available fisheries labor sta- tistics, the number of capture fishers account for three-quarters of employment in fisheries globally. Although employment in capture fisheries has been growing steadily in most low- and middle-income countries, fisheries employment in most industrial economies has been declining. This decline can be attributed to several factors, including the relatively low remuneration in relation to often high-risk and dif- ficult working conditions, growing investment in labor-saving onboard equip- ment (FAO 2007c), and a failure to attract younger workers. The increase in numbers of fishworkers in developing countries is not only a result of increased fish production activities. For some communities, fisheries is a growing poverty trap and, in the absence of alternatives, a livelihood of last resort. Asia has by far the highest share and growth rate in the numbers of fishers and fish farmers (figure 2.6). In this region, the number of fishers increased threefold over the three decades from 1970 to 2000--reflecting both a strong increase in Figure 2.5 Global Population Growth and Trend of Total Number of Capture Fishers 7 Population 35 Fishers 6 30 5 25 ) (billions) 4 20 millions( 3 15 2 10 Fishers Population 1 5 0 0 1970 1980 1990 2000 Source: FAO 1999 (1970, 1990 data); FAO 2007c (1990, 2000 data); FAO FIES. THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 15 Figure 2.6 Total Number of Capture Fishers by Region 3.0 Africa North and Central America 2.5 Europe South America 2.0 Oceania (millions) 1.5 1.0 Fishers 0.5 0 1970 1980 1990 2000 35 Total Asia 30 Rest of the world 25 20 (millions) 15 Fishers 10 5 0 1970 1980 1990 2000 Source: FAO 1999 (1970, 1990 data); FAO 2007c (1990, 2000, 2004 data). part-time and occasional employment in capture fisheries and the growth in aquaculture activities. In Africa, growth was more moderate until 1990 but has accelerated sharply since then. An indicator of labor productivity is the output per person measured either in physical or value terms. Figure 2.7 shows the average output per fisher val- ued at average ex-vessel prices in 1998­2000. Average output per fisher ranged from a high of just above $19,000 in Europe to about $2,231 in Africa and $1,720 in Asia, about a 10-fold difference. The low labor productivity in Africa and Asia reflects low fishing incomes in most countries in these regions. For example, the estimated average gross revenue per full-time fisher in India's marine fisheries was $3,400 in 2004. Small-scale fishers grossed an average of $1,870, and the figure for fishers on 16 THE SUNKEN BILLIONS Figure 2.7 Gross Revenue per Marine and Inland Capture Fisher (average 1998­2000 in US$) 20,000 15,000 10,000 5,000 0 South Europe North and Oceania Africa Asia America Central America Source: FAO 2002, 2007c; FAO FishStat Plus. Note: Data for South America have been adjusted to take low-value fish used for reduction (fishmeal) into account. industrial vessels was $5,490 (Kurien 2007). Average labor productivity is higher when only full-time fishers are considered, but labor productivity is still significantly below labor productivity values in other primary sectors of these economies. There is both hard and anecdotal evidence of low levels of crew remuner- ations in many of the world's marine fisheries. For example, Vietnamese workers on fishing vessels operating in African waters and flagged in coun- tries with per capita income some 10 times higher than in Vietnam receive a monthly pay of $150­180 and working conditions include 16- to 18-hour work days.4 A significant share of crews on Thai industrial fishing vessels are from Myanmar and Cambodia, two countries with widespread poverty and average incomes some eight times lower than those of Thailand. Based on average country poverty data, some 5.8 million, or 20 percent, of the world's 29 million fishers, may be small-scale fishers that earn less than $1 a day (FAO 2004). The strong growth in capture fisheries employment (that is, fishers operating full time, part time, occasionally, or with unspecified status) has not resulted in a commensurate increase in inland and marine capture fisheries production. As shown in figure 2.8, the average reported harvest per capture fisher has declined by 42 percent, from more than 5 tons annually in 1970 to only 3.1 tons in 2000. The significance of this decline in average output per fisher has to be seen in the context of the enormous technological developments that have taken place in the world's capture fisheries during this period, including large-scale motorization of traditional small-scale fisheries, the expansion of active fish- ing techniques such as trawling and purse seining, the introduction of THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 17 Figure 2.8 Annual Catch (Marine and Inland) per Capture Fisher, 1970­2000 5.5 5 year per 4.5 fisher 4 per Tons3.5 3 1970 1980 1990 2000 Source: FAO FishStat Plus; FAO 2002; FAO 2007c; FAO FIES. increasingly sophisticated fish-finding and navigation equipment, and the growing use of modern means of communication. Although this technologi- cal progress has certainly increased labor productivity in many fisheries, at the aggregate global level the resource constraint in combination with widespread open access conditions have prevented an increase in average labor produc- tivity in the world's capture fisheries. Overall, productivity has significantly declined, a decline caused by a shrinking resource base and a growing num- ber of fishers. Because the number of fishing vessels has also increased significantly over the last several decades (see below), at the global level the productivity-enhancing investments in capture fisheries have on average yielded poor returns and have stymied growth in labor productivity and incomes in the sector. 2.3 FISHING EFFORT AND FISHING FLEETS Fishing effort is a composite indicator of fishing activity. It includes the num- ber, type, and power of fishing vessels and the type and amount of fishing gear. It captures the contribution of navigation and fish-finding equipment, as well as the skill of the skipper and fishing crew. Effective effort is difficult to quan- tify even in a single fishery, and there is considerable uncertainty about the cur- rent level of global fishing effort. Given the multiple dimensions of fishing effort, it is understandable why no global statistics are available. The primary factor influencing fishing effort is the size of the global fishing fleet, characterized in terms of vessel numbers, tonnage, and engine power, and type of fishing gear as described in the following section. In biological terms, fishing effort equates with fishing mortality. The func- tional relationship is determined by a factor known as the "catchability coeffi- cient." This coefficient is a measure of both the level of harvesting technology 18 THE SUNKEN BILLIONS and fishing skill as well as the relative ease of harvesting the fish stock in terms of its distribution and abundance. This variable is captured in the bioeconomic model by the schooling parameter discussed in chapter three. 2.3.1 Development in the Global Fishing Fleet The reported global fleet has increased numerically by about 75 percent over the past 30 years to a total of approximately 4 million decked and undecked units in 2004 (FAO 2007c; figure 2.9 ). The number of decked (motorized) ves- sels more than doubled in this period, and the average age of the global fleet of Figure 2.9 Total Number of Decked and Undecked Fishing Vessels Per Region, 1970­98 UNDECKED 3.0 2.5 2.0 1.5 millions 1.0 0.5 0 1970 1975 1980 1985 1990 1995 1998 Asia Africa Oceania North America South America Europe DECKED 1.4 1.2 1.0 0.8 millions0.6 0.4 0.2 0 1975 1980 1985 1990 1995 1998 Asia Africa Oceania North America South America Europe Source: FAO FIES; FAO 1999. THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 19 large fishing vessels has continued to increase. Asia accounts by far for the highest number of vessels, both decked and undecked. FAO data on national fishing fleets are primarily derived from administra- tive records, which may not always be current. For example, national records may include fishing vessels that are not currently operational and they fre- quently omit large numbers of unregistered small-scale fishing vessels (FAO 2007c). A further difficulty in maintaining a consistent data set results from the progressive change in the measurement of vessel size from gross registered tonnage to gross tonnage and the reflagging of vessels to flags of convenience. For large vessels, the Lloyd's database (http://www.lrfairplay.com/) of ves- sels provides a relatively robust global data set for fishing vessels above 100 gross tons. However, coverage is incomplete. Although FAO fleet statistics show an increase in global fleet size since the early 1990s, the Lloyd's register shows a decline in recent years in the number of fishing vessels larger than 100 gross tons (figure 2.10). This divergence in trends can be explained partly by the evolution of the Chinese fleet, which is incompletely listed in the Lloyd's Register because it is domestically insured. The FAO statistics used for this fleet and for smaller vessels have been compiled from national statistics. In 2002, China adopted a five-year program to reduce its commercial fleet by 30,000 vessels (7 percent) by 2007. However, the numbers of commercial fish- ing vessels reported to FAO in both 2003 and 2004 are above the number reported as being in operation in 2002 (FAO 2007c). Figure 2.10 Estimated Number of New Fishing Vessels Built and Total Registered Fleet Size (Vessels over 100 GT/GRT) 1974­85 Oil crisis 2,500 35,000 New registrations Total fleet size 30,000 2,000 25,000 1,500 size 20,000 fleet registrations 1,000 15,000 Total New 500 10,000 0 5,000 1945 1965 1985 2005 2025 2045 Source: Based on Lloyd's data for vessels 100 gross tons or more and reproduced with per- mission; S. Garcia and The Royal Society (Garcia and Grainger 2005, fig. 11, p. 29). 20 THE SUNKEN BILLIONS 2.3.2 Development in Fishing Capacity and Fleet Productivity Fishing capacity is the amount of fishing effort that can be produced in a given time by a fishing vessel or fleet under full utilization for a given fishery resource condition (FAO 2000). Both the increase in vessel numbers and in vessel technology have enhanced the capacity of the global fleet and facilitated access to an expanding range of marine fishery resources and more efficient use of these resources. Fitzpatrick (1996) estimated that the technological coefficient, a parameter of vessel capacity, grew at a rate of 4.3 percent per year.5 Assuming that this trend has continued, growth in technological efficiency coupled with growth in the number of vessels suggests a steeply rising global fleet capacity. The capac- ity index shown in figure 2.11 is a multiple of the total number of decked ves- sels and the technological coefficient.6 The trend line of the catch/capacity index demonstrates that the global harvesting productivity has on average declined by a factor of six. The exploitation of a growing number of less productive fish stocks partly explains this decline in harvesting productivity, but the buildup of fishing overcapacity is clearly a major contributing factor. Thus, the gains from tech- nological progress have generally not been realized because the limited fish stocks require a concomitant reduction in the number of vessels to allow for improved vessel productivity. The decline in physical productivity is compounded by the decreasing spread between average harvesting costs and average ex-vessel fish prices, Figure 2.11 Evolution of Global Fleet Productivity (Decked Vessels) 3.5 Decked vessels (number) 140 Fleet capacity index (fishing power) 3.0 Catch per vessel (tons) 120 capacity Catch per unit capacity (tons) capacity 2.5 unit (million) 100 2.0 per vessels/fleet power) 80 (tons) 1.5 decked (fishing 60 vessel/catch of 1.0 per index 40 0.5 Number Catch 0.0 20 1970 1980 1985 1990 1995 2000 2005 Source: Authors' calculations; Garcia and Newton (1997); FAO FishStat Plus; FAO FIEP. THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 21 causing depressed profit margins and reinvestment. Although this has a damp- ening effect on growth in fleet capacity, depressed fleet reinvestment may retard a shift to more energy-efficient harvesting technologies and a reduction in the carbon footprint of the fishing industry. Many countries have adopted policies to limit the growth of national fish- ing capacity, both to protect the aquatic resources and to make fishing more economically viable for the harvesting enterprises (FAO 2007c). These policies have proven difficult and costly to implement in many instances, and even when numbers of vessels have been successfully reduced (Curtis and Squires 2007), the reduction in fishing effort has been considerably less than propor- tional, because it is the less efficient vessels that tend to exit the fishery, and expansion in technical efficiency counters the reduction in vessel numbers. The global fleet has attempted to maintain its profitability in several ways: by reducing real labor costs, by fleet modernization, and by introduction of fuel-efficient technologies and practices, particularly in developed countries. Vessels are also reported to remain in harbor for increasingly longer periods of the year, focusing harvesting on peak fishing seasons. The receipt of government financial support has also assisted both vessel operators and crews, for instance, through income compensation for crews. Subsidies in the world's marine fisheries have received growing attention in recent years and are further discussed later. 2.3.3 The Effects of Changing Fuel and Food Prices The impact of higher fuel and food prices on marine capture fisheries is becoming clearer. The effect depends on the interplay between the impact of the fuel price change on the level of fishing effort; the price elasticity of demand for fish in economies in which the cost of the entire food basket increases; and the changes in per capita incomes that underlie the demand for fish. The outcome of this interplay is likely to be specific to the economy of individual fisheries and the markets for the products of that fishery (table 2.1). Table 2.1 The Effects of Fuel and Food Price Increases Fuel price increases may: Food price increases may: · reduce fishing effort as a result · increase fish prices to more than of higher costs compensate for higher harvest costs · reduce fish supply and drive fish · redirect forage fisheries (fish meal) catches prices higher to higher-value human food products · change fishing patterns to · allow aquaculture products to permanently less fuel-intensive modes capture market share from marine capture · result in higher fuel subsidies fishery products · stimulate increased fishing effort Source: Authors. 22 THE SUNKEN BILLIONS A number of fuel-intensive fleets ceased to operate in mid-2008; others are benefiting from subsidized fuel to stay operational. The past trend to replace labor with capital is likely to slow or reverse as labor-intensive fisheries become relatively more viable. Products from less fuel-intensive aquaculture may also capture markets. Reduced fishing effort is likely to result in recovery of some fish stocks. Meanwhile, the economic hardship may offer an opportunity for measures to bring fishing capacity into balance with resources. 2.4 SUBSIDIES Many subsidies in the fisheries sector are pernicious because they foster overca- pacity and overexploitation of fish stocks. By reducing the cost of harvesting, for example, through fuel subsidies or grants for new fishing vessels, subsidies enable fishing to continue at previously uneconomic levels. Subsidies effectively counter the economic incentive to cease fishing when it is unprofitable (box 2.1). Box 2.1 What Are Subsidies? There is a wide range of definitions of subsidies. The most precise is probably that used by the World Trade Organization (Article 1 of the Agreement on Subsidies and Countervailing Measures), which can be summarized as follows: a financial contribution by the public sector that provides private benefits to the fisheries sector. The contribution can be direct or indirect (such as forgone tax revenue). The contributions can be provided as goods or services, or as income or price supports. Subsidies exclude provision of general infrastruc- ture, or "purchases goods." Common fisheries sector subsidies include grants, concessional credit and insurance, tax exemptions, fuel price support (or fuel tax exemption), direct payments to industry, such as vessel buyback schemes, fish price support, and public financing of fisheries access agreements. In addition, subsidies have variously been considered to include government fisheries extension and sci- entific research services. Policy changes, such as relaxation of environmental regulations governing fisheries or special work permits for migrant fishwork- ers (crew), can also reduce costs in the sector and such distortions also have been regarded as a form of subsidy. The justification offered for subsidies ranges from protection of infant indus- tries, through national food security and prevention of fish spoilage, to social rationales such as preservation of traditional livelihoods and poverty reduction. Fuel subsidies are an example of a transfer that reduces the cost of fishing. The reduced costs restore profitability and create perverse incentives for con- tinued fishing in the face of declining catches. The result is overfishing, fleet overcapitalization, reduced economic efficiency of the sector, and resource rent dissipation. Source: Authors; Schrank 2003; WTO 1994. THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 23 Table 2.2 Estimate of Fisheries Subsidies with Direct Impact on Fishing Capacity per Year, 2000 ($ billion) Developing Developed Global Percent of Subsidy types countries countries total global total Fuel 1.3 5.08 6.4 63.5 Surplus fish purchases 0 0.03 0 0.3 Vessel construction, renewal 0.6 1.30 1.9 18.9 and modernization Tax exemption programs 0.4 0.34 0.7 7.3 Fishing access agreements 0 1.00 1.0 9.9 Global total 2.3 7.75 10.05 100 Source: Compiled from Milazzo 1998, with updated information from Sumaila and Pauly 2006; Sharp and Sumaila forthcoming; and Sumaila et al. 2007. Several direct estimates of subsidies and financial transfers to the fisheries sector have been made (Millazo 1998; Pricewaterhouse Coopers 2000; OECD 2000; Sumaila and Pauly 2006), and several attempts have been made to classify fisheries subsidies in relation to their perceived impact on the sustainability of fisheries and on international trade (for example, "traffic lights," as proposed by the United States to the WTO (World Trade Organization) Negotiating Group on Rules. Recent discussions also have focused attention on both the social rationale and potential negative impacts of subsidies to small-scale fishing (Schorr and Caddy 2007). An updated global estimate of capacity-enhancing subsidies for both developing and developed countries is shown in table 2.2. Over $10 billion in subsidies that directly impact fishing capacity and foster rent dissipation were provided in 2000. Close to 80 percent of the total global subsidy is provided by developed countries. Transfers of public funds and sup- ports to the fisheries sector are directed at a spectrum of goods ranging from the purely public to the purely private. The issue of subsidies is closely linked to the policies and principles underlying fiscal regimes for fisheries, which must untangle the web of weak property rights prevalent in most fisheries. The issue of subsidies is further addressed later in the discussion. Subsidies are not distinguished as a separate input to the bioeconomic model used to estimate the sunken billions. 2.5 THE COSTS OF FISHERY MANAGEMENT Both fishers and the public sector incur fisheries management costs. The costs to the public are significant, ranging from 1 to 14 percent of the value of land- ings for enforcement (monitoring, control, and surveillance) activities alone 24 THE SUNKEN BILLIONS (Kelleher 2002a) and imposing a substantial burden on international fisheries management processes (High Seas Task Force 2006). The generation of scien- tific advice and the process of management also represent significant costs (Arnason, Hannesson, and Schrank 2000). The public costs of fisheries management have not been taken into account in the estimate of lost rents. These costs are not included in the global bioeconomic model because representative global data are deficient and because the relation- ship between expenditures on fisheries management and net benefit from the fishery remains unclear. The few studies that have been made of fisheries man- agement costs in developing countries suggest inadequately low levels of manage- ment expenditures (Willmann, Boonchuwong, and Piumsombun 2003). 2.5.1 Costs Associated with Illegal, Unreported, and Unregistered Fishing The International Plan of Action to combat illegal, unreported, and unregis- tered (IUU) fishing (FAO 2001a) bundles these three related activities and, as a result, studies have tended to bundle rather than disaggregate estimates of the economic impact of these quite distinct fishing activities. Illegal and unre- ported fishing are of particular interest for the estimate of rents. However, to account for the economic impacts of illegal and unreported fishing, greater knowledge on the scale of both and a greater understanding of the economics of illegal fishing is required (Sutinen and Kuperan 1994; OECD 2006; Sumaila, Alder, and Keith 2006; MRAG and UBC 2008). The estimates of unreported fishing, or more specifically of underreported or misreported catches, are of considerable interest for the purposes of assess- ment of economic benefits from fishing. By definition, such estimates are not reflected in FAO's FishStat Plus. The estimates range from multiples of national FishStat Plus values, for example, in the case of some countries that underre- port catches from highly dispersed small-scale fisheries to deliberate underre- porting of 10­20 percent or more in managed fisheries where fishers seek to circumvent quota restrictions. However, in the absence of a robust basis for adjusting the reported catch to the estimated real catch, the FAO FishStat Plus values remain as the core global data set used in the global bioeconomic model. Illegal fishing can be considered as additional effort that takes place at a lower cost than legitimate effort. However, the production from this illegal effort may be recorded or included in the estimates of catches, or landings. For example, the catch from use of an illegal type of net may be indistinguishable from that of a legal net. Illicit catches affect rent generation by undermining the governance structure of the fishery, by undermining market prices for legitimate product, and by imposing added management enforcement costs as indicated earlier. Illicit catches are frequently unreported--for example, fish under a legal size limit, or catch in excess of quota. The resulting inaccuracies in catch THE ECONOMIC PERFORMANCE OF WORLD MARINE CAPTURE FISHERIES 25 statistics are an important source of uncertainty with respect to scientific advice on fisheries management (Pauly et al. 2002; FAO 2002; Kelleher 2002b; Pitcher et al. 2002; Corveler 2002), and the depletion of many stocks has been attributed partly to the inaccuracy of the historical catch data. The parallel markets for illicit fish set a discounted price for fish, not only directly through illicit landings but also by avoidance of sanitary controls or rules of origin reg- ulations, such that normally compliant fishers may be compelled to revert to illicit practices to remain solvent. NOTES 1. Nominal value is the value of money in different years; real value adjusts for differ- ences in the price level in those years. 2. Estimate provided by FAO Fisheries and Aquaculture Information and Statistics Service (FIES). All values exclude marine plants. The unit values from "FAO World Fishery Production Estimated Value by Species Groups" were weighted by the quantity of the respective marine catches in 2004. Discards are assumed to have zero value. 3. Preliminary results of a new World Bank­FAO­WorldFish Center study indicate that this may be a substantial underestimate. 4. The International Labour Organization of the United Nations recently adopted a comprehensive new labor standard, the "Work in Fishing Convention," which will come into effect when ratified by 10 of the ILO's 180 member states, of which at least 8 are coastal states. 5. For 13 different vessel types (from pirogues of 10 meters up to super trawlers of 120 meters), the coefficient increased on average from 0.54 in 1965 to 1.98 in 1995, or by about 366 percent in 30 years. 6. In some managed fisheries, increase in technological capacity has been limited by gear regulations and other fishery management measures. 26 THE SUNKEN BILLIONS C H A P T E R T H R E E Estimate of Net Economic Loss in the Global Marine Fishery 3.1 BACKGROUND T his study draws on previous efforts to develop an economic assessment for the world's marine capture fisheries. Christy and Scott (1965) sug- gested that the growth of marine fisheries production would stagnate and proposed that the "maximize sustained yield" objective be replaced by a "maximize rent from the sea" objective. In 1992 (revised, 1993) FAO esti- mated the aggregate operating deficit incurred by the world's fishing fleets at $54 billion in 1989, the base year of the study (see box 3.1). A study by Garcia and Newton (1997) indicated that an economically efficient global capture fishery required a reduction of between 25 percent and 53 percent in the global fishing fleet. Because of the deficit of information on the economic health of the world's fisheries, the 2005 World Bank report "Where Is the Wealth of Nations?" was unable to take specific account of fisheries. To address this deficit in the knowledge of the global fishery economy, a workshop was held under the auspices of the World Bank's PROFISH Program (Kelleher and Willmann 2006). The workshop also recognized the need to highlight the current level of global economic rents loss and to raise awareness on economic objectives of fisheries management. The workshop identified two alternative approaches to the task. One approach is to estimate the rents and rents loss in each of the world's fisheries or a representative sample of them. This is a major undertaking. CHAPTER TITLE 27 Box 3.1 The Framework of Prior Studies The 1992 FAO study "Marine Fisheries and the Law of the Sea--a Decade of Change" (revised, 1993) estimated the aggregate operating deficit incurred by the world's fishing fleets at $22 billion for the base year of the study (1989). If the cost of capital cost is added, aggregated deficit was estimated at $54 billion per year, or nearly three-fourths of the estimated gross revenue of $70 billion from the global marine fish harvest. The primary causes of these deficits were attributed to the open access management regime that governed most of the world fisheries and rampant subsidization of the global fishing fleet. Building on the FAO study, Garcia and Newton (1997) examined the trends and future perspective of world fisheries. The authors confirmed the broad conclusions of the 1992 FAO study, the large overcapacity of the global fishing fleet, and the need to reform fishery management systems if long- term economic and environmental sustainability of the world fishery system was to be achieved. They concluded that even though the world's oceans seemed to be exploited at maximum sustainable yield levels, an economically efficient global capture fishery would require either a 43 percent reduction in global fishing costs, or a 71 percent global price increase of capture fish- ery products, or a global capture fleet capacity reduction between 25 percent and 53 percent. An alternative, simpler approach is to regard the global ocean fishery as one aggregate fishery. This approach has several advantages. The data requirements are immensely reduced. Many of these global fisheries data are readily avail- able, and the model manipulation and calculations are a fraction of that required for a study of a high number of individual fisheries. The aggregate approach, regarding the global fisheries as a single fishery is considered the only way to quickly and inexpensively obtain reasonable estimates of the global fisheries rents loss in a transparent and replicable manner. On this basis, the workshop recommended that two independent approaches to the estimation of the loss of economic rents in global marine fisheries be prepared. Each estimate would serve as a cross-check on the other: The first study would estimate the global rent drain (or potential loss of net benefits) through an aggregate model of the global fishery. This report doc- uments the results of this first approach. The second, companion study would undertake a set of case studies on economic rents in a representative set of fisheries and endeavor to extrap- olate results and lessons of case studies to the global level. This work is still in progress. 28 THE SUNKEN BILLIONS The study reported here is based on a simple aggregative model for the global fishery. It improves on the previous FAO studies mentioned above in at least three important ways. First, the concept of fisheries rents and rents loss is made explicit. Second, the theoretical assumptions, the assumptions based on empirical data, and the way the conclusions are derived are clearly and systematically specified. This allows testing, improvement, and updat- ing. Third, the study systematically accounts for a level of uncertainty in the estimated values and assumptions. This is done in two ways: first, a standard sensitivity analysis of the calculated rents loss to the basic input data for the global aggregated fishery model provides upper and lower bounds on the rent loss estimates. Second, reasonable probability distributions for the basic input data for the model are assumed and the resulting probability distribu- tion of the calculated rents loss derived. On this basis, statistical confidence intervals are produced for the rent loss estimate using stochastic (Monte Carlo) simulations. 3.2 USE OF THE TERMS NET BENEFITS AND ECONOMIC RENTS Economists traditionally use economic rents as a measure of the net economic benefits attributable to a natural resource. Rents are not equal to profits--the difference is fixed costs and so-called intramarginal profits. However, rents and profits are usually similar and may sometimes be identical. The economic per- formance of the global marine fisheries may be measured as the difference between maximum rents obtainable from the fisheries and the actual rents currently obtained. This estimate of the loss of fisheries rents in global marine capture fisheries focuses on the harvesting sector, that is, the fishery up to the point of first sale. An economically efficient fishery up to the point of first sale will also drive additional downstream efficiencies, for example, in fish processing. This is because, to be efficient, the harvesting sector will adjust the quantity, quality, and timing of landings to the demand from downstream sectors. Estimates of rents from such potential downstream efficiency gains are not captured in the model presented here but are briefly addressed in the subsequent discussion. In this study, the terms net benefits, economic rents, and rents are equivalent, and these terms are used interchangeably in the text. In the pure economic sense, however, they are not equivalent. Box 3.2 and appendix 1 describe these concepts in more technical detail. As already mentioned, this study estimates this loss of potential economic benefits, or rent dissipation, at an aggregate global level. The global level of rent dissipation is an excellent (inverse) metric of the economic and biological health of the global fishery. The economic objective is to maximize the net economic benefits (sustainable rents) flowing from the fishery. For the great majority of ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 29 Box 3.2 Net Benefits, Economic Rents, and Overfishing The resource rent is a measure of the net economic benefits from the harvest of wild fish stocks. Different fisheries generate different levels of resource rent. For example, a fishery for a high-value species in coastal waters (which has a low cost of harvesting) will generate more rent (or profits to fishers) than a fishery for a low-value species harvested at high cost in deep water. As more fishers join a profitable fishery, they add to the aggregate costs of catch- ing the limited quantity of fish available. As a result, the aggregate net bene- fit, or economic rent, decreases, becoming dissipated among the fishers in the form of higher costs and lower returns for their fishing operations or fishing effort. The rents may even become negative when public financial transfers or subsidies are provided to support an economically unhealthy fishery. As more fishers make greater efforts (for example, by fishing longer hours or investing in more fishing gear) to maintain their previous profits or catch levels, the fishers tend to deplete the fish stock capital that sustains the productivity of the fishery. This further reduces the potential net benefits. As soon as the level of fishing effort moves above the point of maximum economic yield, a situation of economic overfishing exists. Such economic overfishing can exist even if the fish stock itself remains healthy or biologically sustainable. This is illustrated in the box figure. Maximum Sustainable Yield (MSY) and Maximum Economic Yield (MEY) Catch at MSY Negative rents Catch at MEY rents Positive MEY Cost curve Catch/yield Catch/yield curve Fishing effort at Fishing effort at maximum maximum sustainable yield economic yield Fishing effort Economists traditionally measure the net economic benefits from a natural resource such as a fish stock by economic rents. Rents are not equal to profits but are usually similar, and may sometimes be identical, to profits. Thus, the inefficiency of fisheries may be measured as the difference between maximum rents obtainable from the fisheries and the actual rents currently obtained. 30 THE SUNKEN BILLIONS commercial fish stocks, this implies a biomass level in excess of the one pro- ducing the maximum sustainable yield. Even in fisheries with quite high dis- count rates and comparatively low biomass growth rates, the biomass level at which the economic rents are maximized almost always exceeds the biomass level that can provide the maximum sustainable physical yield (Grafton, Kompass, and Hilborn 2007). Thus, as a general rule, economically healthy fisheries require biologically healthy fish stocks, while biologically healthy fish stocks do not necessarily mean economically healthy fisheries. 3.3 DESCRIPTION OF THE AGGREGATE MODEL Based on Arnason 2007, an aggregate model of the global fisheries is specified to estimate rents loss for the global marine fishery. This model and procedure for fitting the model are detailed in appendix 2. The model entails several gross abstractions from the real world. In particular, the model assumes that global fisheries can be modeled as a single fish stock with an aggregate biomass growth function. Similarly, the global fishing industry is represented by an aggregate fisheries profit function, composed of an aggregate harvesting func- tion, relating the harvest to fishing effort and biomass, and an aggregate cost function relating fishing effort to fisheries costs. Fisheries and the rents they generate are dynamic and rarely in equilib- rium, implying several approaches for calculating rents losses. This study compares maximum sustainable rents to the actual rents in the base year (2004). The difference is taken to represent the rents loss in the base year. In this study, sustainable (or long-run) rents are identical to profits, so that max- imum sustainable rents (MSR) are obtained at the fishing effort level corre- sponding to the maximum economic yield (MEY) (see figure in box 3.1). The rents loss estimate assumes that the existing biological overfishing is entirely reversible in the long run. Finally, the estimate does not take account of the costs of restoring the global fishery to economic health. Treating the diverse global fisheries as a single aggregate fishery allows for a model with a manageable number of parameters. A set of available observa- tions on the global fisheries is used to estimate the parameters. The model's simplifications and uncertainty with respect to global fisheries parameters are partially offset by sensitivity analysis of the results and sto- chastic simulations to establish reasonable upper and lower bounds and con- fidence limits for the global fisheries rents loss. It is anticipated that the model will be further tuned and cross-checked using a series of case studies currently in preparation. 3.3.1 Schaefer and Fox Models The population dynamics of the exploitable aggregate biomass (the global fish- ery) are modeled through a logistic, or Schaefer-type, model and through a Fox ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 31 Figure 3.1 Comparative Yield-effort Curves Corresponding to the Logistic (Schaefer) and Fox Biomass Growth Functions value Fox Schaefer/logistic Catch/catch Fishing effort Source: Authors' depiction. model. The main difference between these two biomass growth functions is that the Fox model assumes that, all else being equal, the biomass is much more resilient to increasing fishing effort, in other words, the sustainable biomass and harvest will decline more slowly as fishing effort increases (figure 3.1). The Fox model is consistent with the experience from the global fishery that even though many of the most valuable demersal fish stocks have become depleted, the aggregate global harvest has continued to increase and has not contracted significantly despite ever-increasing fishing effort. These models were selected because they are in widespread use for fisheries assessment. Two models are used to reflect the uncertainty with regard to the shape of the biomass growth function of the global aggregate fishery, which may not necessarily equate to a simple sum of individual fishery functions. Other types of aggregate biomass growth functions exist of course. Many of them, however, fall within the range defined by the logistic and the Fox functions. The shape of the yield-effort curve is given principally by the carrying capacity, or pristine state, of the fish stock(s), the maximum sustainable yield, and the parameters of the harvesting (catch production) function. Of these parameters, estimates of the maximum sustainable yield are more robust than estimates of the other two parameters because comprehensive global marine fish catch statistics are available for over 50 years and harvest trends have been relatively stable for nearly two decades in the range of 79­88 million tons. 3.4 MODEL PARAMETERS AND DATA As noted earlier, this study assumes that global fisheries can be modeled as a single fish stock. Recovery of lost rent also assumes that biological overfishing 32 THE SUNKEN BILLIONS is reversible. The basic data used to estimate model parameters and parameter assumptions are listed in table 3.1. The sources for the data and justification for assumptions are provided in the following sections. Further details and the theoretical relationships are further explained in appendix 2. The year 2004 is taken as the base year for the model because several robust data sets are avail- able for that period. However, adjusted data from other years, or a series of years, is used where data for 2004 are deficient. 3.4.1 Global Maximum SustainableYield and Carrying Capacity The global MSY is assumed to be higher than the reported marine catch in the base year (85.7 million tons, FAO FishStat Plus) plus estimated discards (7.3 million tons), which gives a total of 93 million tons. A conservative value of 95 million tons is used in the model. Though higher than the catch in the base year, this value is lower than the sum of the maximum reported catch for each species group in the past (101 million tons) (FAO FishStat Plus). It is also in the same range as that suggested by Gulland in 1971 (100 million tons) and lower than a maximum of 115 million tons suggested by Christy and Scott (1965). This estimate of the global MSY refers to conventional fisheries only. For example, Antarctic krill is the subject of increasing attention as new harvesting technologies develop and markets for Omega 3 fish oils expand. A major expansion of this fishery could substantially raise the global MSY. Since the 1990s, reported marine catches have fluctuated between 79 million and 86 million tons without an apparent trend. Given the estimate of the MSY, Table 3.1 Model Empirical Inputs and Estimated Parameters Model Units of Model inputs input values measurement Biological Maximum sustainable yield 95 Millions of tons Global biomass carrying capacity 453 Millions of tons Biomass growth in 2004 ­2 Millions of tons Fishing industry Landings in 2004 85.7 Millions of tons Value of landings in 2004 78.8 $ billions Fisheries profits in 2004 ­5 $ billions Other parameters Schooling parameter 0.70 No units Fixed cost ratio in 2004 0 No units Elasticity of demand with respect 0.2 No units to biomass Source: See following sections. ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 33 this suggests that the current global fishery is now located to the right of the MSY (see figure in box 2.2). This means that current global fish stocks are smaller than those corresponding to the MSY, in accordance with the general belief that the global fishery is biologically overfished. The carrying capacity corresponding to the equilibrium MEY is assessed as 453 million tons. This is based on the average relationship between the known carrying capacity and the MSY for a number of fisheries (see table A4.2 in appendix 4). 3.4.2 Biomass Growth in the BaseYear The stability of the aggregate reported catch over the recent past is consistent with a relatively constant aggregate global biomass. During this period, some stocks (for example, demersal stocks such as cod and hake in parts of the Atlantic) have declined markedly in response to fishing pressure, climatic fac- tors, and other influences. Other stocks, such as some pelagic stocks in the North Atlantic, have increased while other large stocks have remained largely unchanged (FAO 2005). Overall, it appears unlikely that in the base year, 2004, there was a significant net increase or decline in global stocks of commercial marine species. However, because global reported catches in 2004 were close to the upper boundary of annual global catches since the 1990s and reported catches in 2005 were lower, it is conservatively assumed, that in 2004 global marine commercial biomass growth was negative, or ­2 million tons. 3.4.3 Volume of Landings in the BaseYear and Reported and Real Marine Fisheries Catches In accordance with official FAO statistics (FAO FishStat Plus), the global catch in the base year is taken to be 85.7 tons. Acknowledging the deficiencies of the FAO FishStat Plus records, the FAO has repeatedly called for more comprehensive and accurate reporting of fish catches (FAO 2001a). The level of acknowledged mis- and underreporting of catch has been addressed with varying degrees of success by different authors. The reasons for misreporting vary widely from deliberate underreporting of quota species and deficiencies in transmission of information to FAO, to widespread underestimates of small-scale fisheries production, and to reported overestimates of fish production in the case of China and possibly in other countries. The estimated level of underreporting varies widely. The esti- mates of underreporting range from 1.2 to 1.8 times the catch (as reported to FAO) in reportedly well-managed fisheries to several times the reported catch in countries with extensive and isolated small-scale fisheries or with high levels of illegal fishing (Oceanic Développement 2001; Kelleher 2002b; MRAG and UBC 2008; Zeller and Pauly 2007; Pauly 1995; Watson and Pauly 2001). However, in the absence of a robust basis for adjusting the reported catch to the estimated real catch, the FAO FishStat Plus values remain as the core data set for this study. 34 THE SUNKEN BILLIONS 3.4.4 Value of Landings in the BaseYear The value of landings in 2004 is discussed extensively in chapter 2. Based on published production value data and other information, it is estimated that this value was $78.8 billion (FAO 2007c), which corresponds to an average landed price of $0.918 per kilogram. 3.4.5 Harvesting Costs As indicated in chapter 2, the estimate of harvesting costs must be treated with due caution because of the weak and incomplete data on the world's fishing fleets. The data sets used include: A robust set of fleet and productivity data for 21 major fishing nations that contribute about 40 percent to global marine capture production (see table A4.1 in appendix 4).1 These data are biased toward industrial fisheries but are considered to be representative of all industrial fisheries. Sample cost and earnings data for the European fleets (EU 25). The data refer to the fleets of 20 countries that contributed 6.8 percent to the global fish harvest in 2004 (Salz 2006; Concerted Action 2004). A recent set of cost and earnings data for India's industrial and small-scale fisheries (Kurien 2007). These fisheries contribute about 2.5 percent to global marine fish harvest. This data set has been taken to represent tropi- cal developing countries' fisheries. Cost of fuel Fuel consumption and costs are estimated on the basis of the vessel and engine horsepower data of the fleets listed in table A4.1 in appendix 4. It is assumed that the average vessel activity is 2,000 hours per year and the average world market price of diesel fuel is $548 per ton.2 Fuel consumption and costs are raised to the global level on a pro rata basis of the contribution of these fleets to global catches. The result is an estimated annual global fuel consumption of 41 million tons valued at $22.5 billion.3 This decrease in the fuel consumption of the global fishing fleet, compared with the previous estimate (46.7 million tons valued at $14 billion in 1989 prices [FAO 1993]), results from a relatively con- stant number of fishing vessels above 100 gross tons in the Lloyd's database and from a reduction in overall tonnage from about 15 million gross tons in 1992 to 12.6 million gross tons in 2004. Fuel efficiency has also improved in some fleets and closed seasons may have reduced fishing time. Cost of labor The 1993 FAO study based its labor cost estimate on a total number of employed crew of 12.98 million and an average annual crew income of $1,749, leading to an estimated total labor cost of $22.7 billion. The growth in the num- bers of fishers, including part-time and occasional fishers, since 1992 suggests ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 35 that total labor cost of the global fishing fleet has increased. However, labor productivity in terms of catch per fisher and catch value per fisher has decreased. Working hours have increased and safety at sea has deteriorated (ILO 2000), making fishing the profession with the highest labor mortality rate. However, the deterioration in working conditions is not necessarily reflected in labor costs. It is concluded that real per capita crew remuneration has declined and that global labor cost has remained at a relatively constant nominal level of $22.7 billion per year. Costs of other factors of production Total operating costs (average 2002­04) exclusive of fuel and labor costs of the fleets from 20 EU countries amounted to $292,000 per 1,000 kilowatt engine power (Salz 2006).4 Applying this value to the fleets of the 21 fishing nations listed in table A4.1 gives annual operating costs of $13.97 billion (exclusive of fuel and labor). These fleets contribute about 40 percent to world harvest, which would make the estimated global total $34.9 billion. However, these operating costs are lower in small-scale fisheries in developing countries. In India, for example, the operating costs (excluding fuel and labor) in small- scale marine fisheries are on average $90 per ton of fish landed (Kurien 2007). Assuming that small-scale fisheries contribute about 25 percent5 to the global marine catch and that the cost structure of the remaining 75 percent of fish- eries is accurately represented by the 21 fleets referenced above, the global estimate for these other operating costs is $28.1 billion. This estimate is consistent with the comprehensive costs and earnings data compiled for the European fleet (Salz 2006). However, it is substantially lower than the cost of comparable items indicated in the FAO (1993) study (a total of $55.9 billion--maintenance and repair, $30.2 billion; supplies and gear, $18.5 billion; and insurance, $7.2 billion). The FAO estimates are higher largely because they are based on percentages of the vessel replacement costs and on vessels normally insured and subject to regular surveys. Many fishing vessels do not fall in this category, especially small-scale fishing vessels both in developed and in developing countries. Cost of capital The estimate is based on the comprehensive costs and earnings data set avail- able for the European fishing fleet. A capital value per unit of vessel power (kilowatt) was applied to the fleets of 21 fishing nations in the European Union (see table A4.1 in appendix 4). This value was then raised to the global total by dividing by the ratio of the contribution of these fleets to the world marine fish harvest, resulting in a value of $127 billion for total fleet investment.6 Total capital costs were conservatively calculated at 8.3 percent of the capi- tal value of the fleet. This resulted in total capital costs of $10.5 billion. Depre- ciation of this capital was conservatively calculated at 4.3 percent per year, 36 THE SUNKEN BILLIONS Table 3.2 Estimated Capital Cost of Global Fishing Fleet (US$ billion) 1993 Current Category FAO study estimate Total fleet investment 319.0 127.0 Depreciation cost -- 5.4 Interest cost -- 5.1 Total cost of capital 31.9 10.5 Source: Authors' calculations. Note: -- Data are not available. resulting in global fishing fleet depreciation of $5.4 billion. Interest costs were calculated at 4 percent, which is an estimate based on secure long-term U.S. dollar investments such as 30-year U.S. treasury bonds. Total estimated capital costs are summarized in table 3.2. For comparison purposes, total capital costs according to the FAO 1993 study are also listed. The estimate for the total capital invested in the fleet given in the 1993 FAO is higher than the current estimate because it was based on the estimated replacement value (FAO 1993). However, this value ($319 million) is considered an overestimate because the method was applied in the absence of knowledge of the age structure of the fleet and the market prices of vessels at the time. 3.4.6 Profitability The world's fishing fleet is estimated to have had an operating profit of $5.5 billion in 2004. However, the fleet incurred a capital cost estimated at $10.5 billion, which puts the global fisheries profitability into negative territory, with an estimated deficit of $5 billion in 2004, the base year (table 3.3). These estimates are net of financial subsidies; that is, subsidies have already been subtracted. It should be noted that profit estimates for the global fishing fleet suffer from a scarcity of reliable fleet cost and earnings data. Many countries do not systematically collect fisheries cost and earnings or profitability data, and these data are particularly deficient for small-scale, artisanal, and subsistence fishing. Even when such data are collected, fishers are often reluctant to provide com- plete and accurate information, and available information is often distorted by subsidies or taxes. Although based on limited samples, there are nevertheless indications that substantial numbers of fisheries are unprofitable or experience declining profitability (Lery, Prado, and Tietze 1999; Tietze et al. 2001; Tietze et al. 2005; Watson and Seidel 2003; Hoshino and Matsuda 2007). Fishing that operates at a real economic loss is unlikely to continue without subsidies or forms of vertical integration that capture downstream value. This further narrows the possible range of values for global fleet and fishing profits. ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 37 Table 3.3 Global Fleet Estimated Profits, Current and Previous Studies Category 1993 FAO study Current estimate Value of catch 70 78.8 Fuel costs 14 22.5 Labor costs 22.7 22.7 Other operating costs 55.9 28.1 Operating profit or loss ­22.6 5.5 Total cost of capital 31.9 10.5 Global fleet profitability (deficit) ­54.4 ­5.0 Source: Author's calculations; FAO 1993 (base year 1989). In addition, the "tragedy of the commons" suggests that where forms of open access persist (which is the case in many of the world's fisheries), profits will be dissipated. The value of landings and costs of many factors of production are often known. This again narrows the range for the estimate of profits. 3.4.7 Schooling Parameter Harvests of species with a strong tendency to congregate in relatively dense schools or shoals (such as herrings, anchovies, and sardines) are often little influenced by the overall biomass of the stock (Hannesson 1993). The opposite is true for species that are relatively uniformly distributed over the fishing grounds (such as cod or sharks). For these species, harvests tend to vary pro- portionately with the available biomass for any given level of fishing effort. The schooling parameter reflects these features of fisheries and normally has a value between zero and unity. The lower the schooling parameter, the more pronounced the schooling behavior and the less dependent the harvest is on biomass. For many commercial species (for instance, many bottom- dwelling, or demersal, species and shellfish), the parameter would be close to unity (Arnason 1984). For pelagic species (such as tuna, herring, or sardine), it is often much lower (Bjorndal 1987). A schooling parameter of less than unity leads to a discontinuity in sustainable yield and revenue functions. These dis- continuities are of concern because they correspond to a fisheries collapse if fishing effort is maintained above that level for some time. In the harvesting function for the global fishery, the aggregate schooling parameter should reflect the schooling behavior of the different fisheries. An average of schooling parameters by fishery groups weighted by their maximum sustainable yield levels gives an aggregate schooling parameter of approximately 0.7, which is the value used in this study (see table A4.3 in appendix 4). 38 THE SUNKEN BILLIONS 3.4.8 Elasticity of Demand with Respect to Biomass In the global fisheries model employed in this study, the average price of land- ings depends on the global marine commercial biomass according to a coeffi- cient referred to as the elasticity of demand with respect to biomass. The model uses a value of 0.2 for this parameter, which means that if the global biomass doubles, then the average price of landing increases by 20 percent. The coeffi- cient and the value of the coefficient are based on following rationale. Fishing activities initially target the most valuable fish stocks and the most profitable fisheries. These high-value species tend to be (but are not always) those high in the marine food chain. As the fishing effort increases, the most valuable stocks become depleted and the fishing activity targets less valuable fish stocks (or in some cases operates in deeper waters on the continental slopes) or targets species at lower trophic levels. This is known as "fishing down and through the food webs." In this situation of overfishing, the higher proportion of lower-value species tends to depress the average price of the aggregate catch. However when the reverse takes place, under a governance regime that restores biomasses and the health of fish stocks, the average price will tend to rise. However, this generalization must be qualified in terms of the trophic level of the target species and efforts to achieve ecosystem balance across related fisheries. If the target species is a high-value prey species (such as shrimp), then rebuilding the stock of predators (in this example, lower-value fish at a higher trophic level that eat shrimp) may in fact reduce the average price of the aggregate landings (Hannesson 2002). Nevertheless, in general, as stocks rebuild there will tend to be more, larger fish in the catch. Larger fish are generally (but not always) more valuable, which results in a higher average price for the global catch. Under an effective fisheries management system, the unit price of landed fish usually increases, sometimes substantially (Homans and Wilen 1997; Homans and Wilen 2005). For example, in individual-transferable-quota- based fisheries (one of many choices for improved fisheries management), the average price of landings increases substantially compared with the price before introduction of the ITQ scheme (Herrmann 1996). The reasons include more selective fishing practices, better handling of caught fish, and better coor- dination between demand for fish and the supply of landings. The increased price is not necessarily related to the more valuable composition of the catch referred to earlier. Finally, there is growing evidence that heavily fished resources are less stable (Anderson et al. 2008), so stock recovery is likely to sta- bilize supplies and prices and improve the efficiency of harvesting. 3.4.8 The Fixed Cost Ratio In this study, the loss of potential rents is estimated as the difference between rents in the base year and maximum sustainable rents, that is, maximum rents ESTIMATE OF NET ECONOMIC LOSS IN THE GLOBAL MARINE FISHERY 39 where biomass (the fish stock) and the capital stock (fleet) are in equilibrium. This equilibrium prevails when fish stocks have been rebuilt and when the fleet has fully adjusted to sustainable catch levels. During the period of fleet adjust- ment, or long-run economic change, the capital costs, normally regarded as fixed costs, are actually variable. Therefore, for the purposes of comparing base year and maximum sustainable rents, all costs are considered variable costs, and for these theoretical reasons, the fixed cost ratio is set to zero in these cal- culations. This does not mean that capital costs are ignored in this study but that, for the purposes of the rents loss calculation in this study, they are regarded as variable. 3.4.9 Management Costs and Subsidies As explained earlier, the costs of fisheries management are not included in the bioeconomic model. Nor are subsidies separately identified in the cost esti- mates. The existence of subsidies reduces the observed costs so the reported deficit may be underestimated. These additional factors underline the conser- vative nature of the rents loss estimate. NOTES 1. The countries are China, EU-15, Iceland, Japan, Republic of Korea, Norway, and the Russian Federation. 2. The impact of recent changes in fuel prices is discussed elsewhere in this report. 3. Taking as a basis data from more than 250 fisheries and spatially resolved catch statistics for 2000, Tyedmers, Watson, and Pauly (2005) estimated global fuel con- sumption at almost 50 billion liters, equal to 42.5 million tons. On the basis of country-by-country fishing fleet data, Smith (in press) estimated global fuel con- sumption at 38 million tons. 4. Averages of 2002­04 have been used and converted into US$ at an exchange rate of 1 euro = US$1.107. 5. Because the production from small-scale fisheries tends to be underestimated, or underreported, this value may be an underestimate. Chuenpagdee et al. 2006 sug- gest that 25 percent may be a minimum value. Current work in progress by the FAO and the WorldFish Center under the World Bank's PROFISH Program (the "Big Numbers" project) also confirm that production from small-scale fisheries may be substantially underestimated. 6. The use of EU cost data may overestimate capital cost because of the presumed higher capital intensity of EU fishing fleets. However, a comparison with Kurien's marine capture data set for India comprising primarily small-scale and semi- industrial fishing fleets suggest that this is not the case. Capital investment per unit of harvest show comparatively similar values: world (based on EU data) $1,494 per ton; and India $1,240 per ton. In the case of depreciation costs, these were estimated even higher, on average, in Indian than in EU marine fisheries. 40 THE SUNKEN BILLIONS C H A P T E R F O U R Results 4.1 MAIN RESULTS T he loss of net benefits, expressed as forgone rents, is estimated to be on the order of $50 billion in 2004, the base year. Because of model and input data limitations, this estimate is best considered as the most probable value of a range of possible values. Specifically, the most probable point estimate of the global fisheries rent loss is $51 billion with an 80 percent confidence level that the value is between $37 billion and $67 billion. The rents loss estimate ranges between $45 and $59 billion in the base year, depending on whether the underlying biomass growth function applied is the Schaefer logistic or the Fox function. Table 4.1 summarizes the main results of these calculations for the two biomass growth functions. The Fox biomass growth function estimates a higher current fisheries rents loss primarily because the current level of overexploitation is substantially greater when the Fox function applies. A priori, there is no reason to choose one biomass growth function above the other and the point estimate of $51 billion assumes an equal probability of each function applying. Based on the loss of net benefits in 2004, the real cumulative global loss of wealth over the past three decades is estimated at $2.2 trillion. This estimate is made by assuming a linear relationship between the rents and the state of the world's fish stocks as reported by FAO at various intervals since 1974. The esti- mated rents loss in the base year is projected from 1974 to 2007 and raised on the basis of the changing percentage of global fish stocks, reported by FAO as CHAPTER TITLE 41 Table 4.1 Main Results--Point Estimates of Rents Current Optimal Difference Category Units Logistic Fox Logistic Fox Logistic Fox Biomass Million of tons 148.4 92.3 314.2 262.9 165.8 170.6 Harvest Million of tons 85.7 85.7 80.8 81.6 ­4.9 ­4.1 Effort Index 1.00 1.00 0.56 0.46 ­0.44 ­0.54 Profits US$ billions ­5.000 ­5.000 39.502 54.035 44.502 59.035 Rents US$ billions ­5.000 ­5.000 39.502 54.035 44.502 59.035 Source: Authors. fully or overexploited. A conservative opportunity cost of capital of 3.5 percent is assumed. Details of the estimate are provided in table A4.5 in appendix 4. To maximize sustainable rents from the global fishery, the model indicates that fishing effort should be reduced by 44 to 54 percent depending on whether the aggregate global commercial fishery biomass growth is better described by the logistic or the Fox biomass growth function. The models indicate that bio- mass levels more than double in the case of the logistic and triple in the case of the Fox biomass growth function compared with the base year estimates. In both cases, sustainable marine fishery harvests are reduced by about 4 million tons compared with the base year harvest. A summary of the results of the sensitivity analysis and the confidence intervals for the rents loss estimate is provided in section 4.5 below. 4.2 EVIDENCE FROM GLOBAL STUDIES Although this study is not directly comparable with previous studies, all stud- ies (table 4.2) carry the same message: at the aggregate level, the current annual net benefits from marine capture fisheries are tens of billions of U.S. dollars less than the potential benefits. Society continues to be a net contributor to the global fisheries economy through depletion of the national and global fish cap- ital and through subsidies. 4.3 EVIDENCE FROM CASE STUDIES A range of case studies strongly indicates the potential for substantial increases in rents and net benefits from fisheries. The different approaches to estimating current and potential rents or similar indexes of net benefits preclude a syn- thesis of all the available studies in a coherent manner as part of this study.1 However, table 4.3 and table A4.4 in appendix 4 demonstrate that potential rents range from a significant fraction of the current fishery revenues to multiples of 42 THE SUNKEN BILLIONS Table 4.2 Estimates of the Economic Losses from Global Marine Fisheries Drivers / focus of Source Estimate of losses proposed solutions FAO 1993 $54 aggregate loss, or Open access, subsidies approximately 75 percent of the gross revenue Garcia and Newton 1997 $46 billion deficit Overcapacity, loss of high-value species Sanchirico and Wilen $90 billion (future Rents in ITQ fisheries 2002 projection) approach 60­70 percent of gross revenues. Wilen 2005 $80 billion Secure tenure World Bank $51 billion Comprehensive (this study) governance reform Table 4.3 Illustrative Rents Losses in Major Fisheries Assessed with the Model Used in This Study Base year Base year harvest revenues Rents loss as Base (1,000 (US$ percentage Fishery year tons) millions) of revenues Vietnam Gulf of Tonkin demersal multigear 2006 235 178 29 Iceland cod multigear 2005 215 775 55 Namibia hake demersal trawl 2002 156 69 136 Peru anchoveta purse seine 2006 5,800 562 29 Bangladesh hilsa artisanal multigear 2005 99 199 58 Source: Selected case studies in progress FAO/World Bank (see appendix A4.4). the current fishery revenues. Several fisheries managed in a scientific and responsible manner may yet continue to underperform with regard to rent generation (Kirkley et al. 2006). For example, the potential economic benefits from rebuilding 17 overfished stocks in the United States is estimated at $567 million, or approximately three times the estimated net present value of the fisheries without rebuilding (Sumaila and Suatoni 2006). In a followup to this study, rents loss estimates for a representative range of fisheries will help tune the global rents loss estimate and raise stakeholder awareness on the potential net benefits from improved governance in specific fisheries. RESULTS 43 4.4 LINKS TO THE BROADER ECONOMY The fisheries rents that are generated may be invested in productive physical, human, or social capital, and the net gains from these investments can subse- quently be reinvested. Thus, generation of fisheries rents allows fishing economies to choose a higher economic growth path. For countries that are highly dependent on fisheries, harnessing the potential economic growth effects of fisheries rationalization can substantially improve general economic welfare. 4.4.1 Contributions to Economic Growth and GDP The upstream and downstream economic links, or "multiplier effects," add sig- nificantly to the contribution of the fishing industry to the GDP and to wealth creation, because the fishing industry is a base industry that supports eco- nomic activity in other sectors of the economy including services (Arnason 1995; Agnarsson and Arnason 2007). In addition, the fishing industry is a dis- proportionately strong foreign exchange earner in many developing countries, and to the extent that the availability of foreign currency constrains economic output, the economic benefits from the sector may be greater than is apparent from the national accounts. For example, the contribution of the fishing indus- try in the Pacific Islands has been estimated to be some 30 percent higher than is usually presented in national accounts (Gillett and Lightfoot 2001; Zeller, Booth, and Pauly 2006). An efficient and stable harvest subsector is the basis for maintaining the sector's contribution to GDP. The study has focused on the marine fisheries to the point of landing, or first sale. However, the seafood industry (including aquaculture) is a $400 bil- lion global industry. The marine capture component accounts for an estimated $212 billion, of which 65 percent, or $140 billion, represents the postharvest economy (Davidsson 2007). The downstream benefits from a more efficient harvest sector are considerable, as illustrated by the examples in box 4.1. The upstream benefits are less evident, though fleet and processing plant construc- tion and modernization can contribute to wealth and economic growth. The substantial value of noncommercial uses of fisheries is not included in the rent estimates. For example, in the United States, the total national economic impact from commercial finfish fisheries is 28.5 percent of the impact created by marine recreational fisheries (Southwick Associates 2006), and in the case of the striped bass resources, which are shared between the commercial and recre- ational sectors, anglers harvest 1.28 times more fish, yet produce over 12 times more economic activity as a result (Southwick Associates 2005). Healthy coral reefs provide a further example. In addition to the lost benefits from fisheries, destruction of coral reefs results in an estimated net present loss to society of $0.1 million to $1.0 million per square kilometer of reef (Cesar 1996). The depletion of global fisheries cannot be attributed solely to fishing. Pol- lution, destruction of critical habitats (such as wetlands and coastal zones), 44 THE SUNKEN BILLIONS Box 4.1 Downstream Efficiency Gains in Alaska and Peru The Bering Sea Pollock Conservation Cooperative did not operate under an ITQ system but created the incentives to generate substantial additional rents. This was done by removing the less efficient vessels, extending the fishing sea- son, and allowing the operators to concentrate on product quality. The yield per ton of fish increased by approximately 10 percent, and recovery of by- products such as high-value fish roe increased by 22 percent. The increased benefits occurred in the postcapture operations, but as a result of a more rational harvest regime and investments in the postharvest phase. The estimated loss of rents in the harvest sector of Peru's anchoveta fishery is on the order of $200 million per year. Fleet capacity is some 2.5 to 3.4 times the capacity required to harvest the total allowable catch set as a function of the maximum sustainable yield, and the capacity of the fish meal plants is some 2.9­3.8 times that required to process the catch. The fishing season in the world's largest fishery has been reduced to less than 60 days per year with sub- stantial loss of quality and wastage. If, under a rationalized and modernized postharvest sector, the current production of lower-grade fish meal graduated to higher-grade fish meal and a greater recovery of fish oil, the additional net postharvest revenues generated would be an the order of $228 million per year. Source: Wilen and Richardson 2003; Paredes 2008. invasive species, climate change, and mineral extraction all play a role. However, fishing is considered the greatest single cause of such depletion (Millennium Ecosystem Assessment 2005). The possible effect of a reduction in discards is not captured in the model. Although by definition, discards generally have no commercial value to the discarder, they may have an economic value. It is likely that under improved fisheries management--a necessary step to gain the full benefits from fisheries-- the catch of previously discarded juveniles of commercially valuable species would be reduced. As a consequence, the sustainable yield of valuable species would probably increase, with a further increase in the estimate of potential rents. For example, if reduced discards were to result in an increase of 5 million metric tons in the global MSY, the estimate of forgone rents loss would increase by some $6 billion per year. 4.4.2 The Effects of Higher Fuel and Food Prices The impact of higher fuel and food prices on the rent estimate is unclear. The effect depends on the interplay between the impact of the fuel price change on the level of fishing effort; the price elasticity of demand for fish in economies where the cost of the entire food basket increases; and the changes in per capita RESULTS 45 Table 4. 4 Effects of Fuel and Food Prices Increases on Economic Rents Fuel price increases may: Food price increases may: Increase rents: Increase rents: · if fishing effort decreases as a · if the increase in fish prices more than result of higher costs compensates for higher harvest costs · if fishing patterns change to less · if forage (fish meal) fisheries redirect fuel-intensive modes catches to higher-value food products Decrease rents: Decrease rents: · if fuel subsidies increase · if lower-cost aquaculture products · if the aggregate global fishery permanently capture market share becomes less profitable from marine capture fishery products · if food price increases stimulate increased fishing effort Source: Authors. incomes, which underlie the demand for fish. The outcome of this interplay is likely to be specific to the economy of an individual fishery and the markets for the products of that fishery (table 4.4). Fuel constitutes a significant part of the cost of fishing, and the price of fuel almost doubled between 2004, the base year, and 2007 (U.S. Energy Informa- tion Agency 2007). The recent fluctuations in oil prices greatly increase uncer- tainty, but the gradual increase in oil prices between 2004 and 2008 suggest that the cost of fishing in the base year may underestimate the cost in the future. For example, the variable costs of fishing effort in March 2008 were some 10 percent higher than they were in 2004, given the share of fuel in vari- able fishing costs. This increase would reduce the estimated rents loss com- pared with the base year 2004 by about $4 billion. 4.5 SENSITIVITY ANALYSIS AND CONFIDENCE INTERVALS The rents loss estimates range from a minimum $30 billion (the logistic func- tion and a 10 percent lower MSY) to over $90 billion (the Fox function and 20 percent higher MSY). The results of the sensitivity of the rents loss estimates up to 20 percent deviations in the input data are illustrated in figure 4.1 for the logistic (Schaefer) and the Fox biomass growth functions, respectively. As can be seen in the figure, the rents loss estimate is most sensitive to changes in the assumed global maximum sustainable yield and in the volume of landings in the base year. When the values for the other input data are kept constant, the estimated rents loss increases with an increase in the value of the MSY estimate and decreases as the value of landings in the base year increases. The estimated rents loss is much less sensitive to changes in the values for other 46 THE SUNKEN BILLIONS Figure 4.1 Sensitivity Analysis of the Results for the Logistic and Fox Models a. LOGISTICFUNCTION 80,0 70,0 billions) 60,0 (US$ 50,0 losses 40,0 Rents30,0 20,0 ­20 ­10 0 10 20 Percentage deviation MSY prof(t*) Landings Schooling parameter Base price Elasticity of demand Net biomass growth b. FOXBIOMASS GROWTH 100,0 90,0 80,0 billions) 70,0 (US$ 60,0 losses 50,0 Rents 40,0 30,0 20,0 ­20 ­10 0 10 20 Percentage deviation Source: Authors' calculations. input data such as the price of landed catch, the schooling parameter, and the elasticity of demand. Based on stipulated stochastic distributions for the input data and calcu- lated stochastic distribution of the rents loss estimates, a 90 percent confidence interval for the estimated rents loss is $31 to $70 billion, with the most proba- ble estimate on the order of $50 billion (table 4.5). RESULTS 47 Table 4.5 Confidence Intervals for Rent Loss Estimate Confidence interval Range of estimated rents loss (US$ billions) 95 percent 26­73 90 percent 31­70 80 percent 37­67 Source: Authors' calculations. Figure 4.2 Density and Distribution Functions for the Estimated Rents Loss for Logistic, Fox, and Combined Logistic and Fox Functions Density functions Distribution function 600 1 Combined Logistic 400 0.5 Frequency 200 Fox Probability 0 0 0 50 100 0 50 Rents loss ($US billions) Rents loss ($US billions) Source: Authors' calculations. Details of the stochastic distributions for the input data and calculations of the resulting stochastic distribution of the rents loss estimates are described in detail in appendix 3. The stochastic distribution of the rents loss estimates is non-normal and skewed to the right (longer tail to the left). Combining the logistic (Schaefer) and the Fox models in one distribution with equal proba- bility leads to density and distribution functions as illustrated in figure 4.2. NOTE 1. A representative series of studies using a common methodology is currently being undertaken by FAO and the World Bank under the World Bank's PROFISH Partner- ship. Results of several of these studies are presented in table A4.4 in appendix 4. 48 THE SUNKEN BILLIONS C H A P T E R F I V E The Way Forward 5.1 FISHERIES REFORM MAKES ECONOMIC SENSE T he study shows that an increasing number of fish stocks are overex- ploited; overcapacity in fishing fleets remains high; the real income level of fishers remains depressed; and fish prices have stagnated, even as the costs of harvesting continue to increase. Aquaculture has grown to approximately 50 percent of food fish production, which has contributed to supply and price stabilization as demand for seafood has increased, particu- larly in China. Many thriving and profitable fisheries disguise the fact that at the aggregate level, the economic health of the world's marine capture fisheries is in a state of chronic and advancing malaise that has compromised resilience to fuel price increases, to depressed fish prices, and to the effects of climate variabil- ity and change. The estimated loss of potential net benefits is on the order of $50 billion per year for a cumulative loss of over $2 trillion since 1974. The annual loss is equivalent to approximately 64 percent of the landed value of the global catch, or 71 percent of the value of global fish trade in the base year (2004). These estimates, however, exclude the additional value of the environ- mental benefits of healthy marine ecosystems (such as tourism benefits from healthy coral reefs) and the value of efficiency gains along the value chain. In addition, the full costs of illegal fishing activities and subsidies may not be fully reflected, and the estimated loss of potential benefits is thus conservative. These are among the many reasons why the economic objectives--increasing the net benefits and wealth from fisheries--need to be at the center stage of CHAPTER TITLE 49 efforts to resolve the crisis in marine fisheries. Public awareness and under- standing of the potential and actual flows of economic benefits can inform the political economy of reform and help leaders move toward socially responsible and sustainable fisheries underpinned by sound scientific advice. National fish- eries policies would benefit from a greater focus on maximizing net benefits and choosing economic or social yield as an objective rather than continuing to manage fisheries with the purely biological objective of maximum sustainable yield as the key reference point. 5.2 REBUILDING GLOBAL FISH CAPITAL Most marine wild fish resources are considered to be the property of nations. Governments are generally entrusted with the stewardship of these national assets, and their accepted role is to ensure that these assets are used as produc- tively as possible, for both current and future generations. The depletion of a nation's fish stocks constitutes a loss of national wealth, or the nation's stock of natural capital. Similarly, the depletion of global fish stocks constitutes a loss of global natural capital. The scale of these losses-- the sunken billions--justifies increased efforts by national economic policy makers to reverse this perennial hemorrhage of national and global economic benefits. There is enormous potential to rebuild global fish stocks and wealth and to increase the net benefits that countries could derive from their commercial marine fisheries resources. The rents may not be fully recoverable and efforts to rebuild global fish wealth incur economic, social, and political costs. Nevertheless, the sheer scale of the rent drain provides ample grounds for economic policy makers and planners to direct their attention to the rebuilding of national, regional, and global fish capital. Economically healthy marine fisheries can deliver an unending flow of economic benefits, a natural bounty from good stewardship, rather than constituting a net drain on society and on global wealth. Rising fuel prices, declining fish stocks, and the need for greater fish stock resilience in the face of additional climate change pressures further reinforces the arguments for concerted national and international actions to rebuild fish wealth. Rising food prices, a growing fish food gap for over 1 billion people dependent on fish as their primary source of protein, and the ungainly carbon footprint of some fisheries add to the rationale for reversing the rent drain. 5.2.1 Subsidies The increase in the prices of fuel and food during 2008 combined to strengthen pressure for subsidies. Such pressures stem not only from the harvest sector of the fisheries industry but also from the upstream and downstream economy dependent on the sector, and from consumers in countries where fish is a staple component of the diet. 50 THE SUNKEN BILLIONS The World Bank has recently addressed the subsidies issue. The World Bank does not advocate subsidies as a response to recent food and energy price increases, but supports careful analysis, monitoring, and balancing of compet- ing needs for energy and food security (World Bank 2008a). The World Development Report 2008 (World Bank 2007c) poses two ques- tions with regard to input subsidies. First, "do the economic benefits exceed the costs of subsidies?" The evidence presented in this and other studies shows that, in the case of fisheries the answer is almost invariably "no'' and that the negative environmental externalities generated by input subsidies are considerable. The second question is "are input subsidies justified on social grounds?" The answer depends on whether the alternatives are more cost-effective. In the case of fisheries, subsidies often constitute a politically expedient means of sidestepping the challenge of addressing the alternatives, including the challenge of helping fisher households to take up other gainful economic opportunities. Often conceived as a short-term intervention, subsidies tend to become entrenched at high cost to society and frequently confer more benefits on the more affluent (for example, vessel owners) than on the intended targets (for example, vessel crew or the poorer consumers). The use of subsidies implies that solutions to the crisis in fisheries lie within the sec- tor rather than through local, regional, and national economic growth. By creating perverse incentives for greater investment and fishing effort in over- stressed fisheries, input subsidies tend to reinforce the sector's poverty trap and undermine the creation of surplus that could be invested in alternatives, including education and health. The World Bank has suggested, that if input subsidies are to be used, they should be temporary, as part of a broader strategy to improve fisheries man- agement and enhance productivity. The Bank has emphasized investing in quality public goods, such as science, infrastructure, and human capital; improving the investment climate and access to credit; and strengthening gov- ernance of natural resources, including through secure user and property rights and collective action taken by a strengthened civil society (World Bank 2008a). 5.2.2 The Costs of Reform The transition to economically healthy fisheries will require investment. Assessment of the costs of reform and the improved governance required to capture increased net benefits from marine capture fisheries lies beyond the scope of this study, as does an assessment of the proportion of the potential net benefits that can feasibly be captured. The benefits from stock recovery accrue over a longer period and are shrouded in the uncertainties of the ecosystem. Public funds have been used to finance various elements of reform includ- ing fisher retraining and early retirement. Buyback schemes are one of the many strategies deployed to improve the economic performance of fisheries and are generally financed by public funds, although some cost recovery has THE WAY FORWARD 51 accrued through charges on the remaining fishers. In Norway, Japan, and else- where, private funds have supported buybacks (Curtis and Squires 2007), and dedicated financial instruments have also been proposed (Dalton 2005). The recurrent costs of management are not addressed in the model pre- sented here. Substantial investment is needed in the transition process to eco- nomically healthy fisheries. The investment is required not only in building technical capacity for fisheries management but in the institutional fabric of fisheries tenure at all levels--the fishers, the administration, and the political levels. The recurrent costs of fishery management may decline under an eco- nomically healthy fisheries regime. For example, illegal fishing is likely to decline and the costs of enforcement may decline. The cost of the regulatory burden on the fisher may also decline. The allocation of the management cost burden between public and private sectors presents challenges both for fiscal policy and management practice. 5.2.3 Net Benefits and Tenure It has long been understood that because the benefits of use are individual but costs are shared, the net benefits from use of common pool resources, such as fish stocks, will tend to dissipate (Gordon 1954; Hardin 1968). The nature of the rights over the resources plays an important role in determining the extent of that loss of net benefits, and it is suggested that in general the more clearly defined and enforceable the rights, the less the benefit loss (Scott 1955). In many countries, marine fishery resources are considered to belong to the nation, and governments are charged with the stewardship of this public trust. In some instances, this has undermined the traditional rights systems observed by local communities and led to a de facto open access condition. Because the public or common pool character of marine fish resources is often deeply embedded in law and practice, strengthening marine fisheries is often a com- plex undertaking that faces political, social, and legal challenges, requiring a good understanding of traditional rights systems, accepted practices, and cul- ture. Nevertheless, to increase the net benefits from fisheries, the issue of tenure must be addressed (de Soto 2000). The purpose of this study is not to be prescriptive with regard to marine fisheries tenure, but to raise awareness of this link between tenure and net benefits (Costello, Gaines, and Lynham 2008). A greater understanding of this link implies public awareness of the potential and actual economic benefits from marine fisheries and how these benefits can be captured rather than dis- sipated. It calls for public awareness concerning who benefits and to what extent society underwrites those benefits. It calls for greater understanding of how a balance between secure tenure and the social responsibility for resource stew- ardship can be achieved at local and national levels. Figure A4.1 in appendix 4 demonstrates that quantifies the increasing wealth generally attributed to strengthened tenure in selected New Zealand and Icelandic fisheries. 52 THE SUNKEN BILLIONS 5.2.4 Sustainable Fisheries Are Primarily a Governance Issue As stated in the World Summit on Sustainable Development Plan of Imple- mentation, sound science and an ecosystem approach are fundamental under- pinnings of sustainable fisheries (Articles 30, 36). However, the principal drivers of the overexploitation in marine capture fisheries and the causes of the dissipation of the resource rents and loss of potential economic benefits are the perverse economic incentives embedded in the fabric of fisheries har- vesting regimes, reflecting a failure of fisheries governance. Sustainable fisheries are primarily a governance issue, and the application of the fishery science without addressing the political economy of fisheries is unlikely to rebuild marine fish wealth.1 Restoration of marine fish wealth and rebuilding the flow of net benefits implies fisheries governance reforms with an increased emphasis on the economic and social processes, informed by, rather than centered on, biological considerations and recognizing solutions and opportunities provided in the broader economy outside the fisheries sector. 5.2.5 Fishery Reform Can Advance along the Axes of Sustainability, Productivity, and Equity Three axes of reform can be considered. A sustainability axis would maintain ecosystem and intergenerational integrity while underpinning the physical basis for economic health. A productivity axis would aim to maximize rents by focusing on the economic efficiency of the harvesting regime. An equity axis would qualify the productivity aspiration, addressing the social dimension of resource allocation or benefit flows. The maximum economic yield (or a similar proxy) is generally a more con- servative harvesting target than maximum sustainable yield (Grafton, Kompass, and Hilborn 2007). Framed within a broader ecosystem approach, it satisfies both the sustainability and rent-maximizing objectives. Advancing along the equity axis, the use of fisheries as a social safety net, for example, may involve some sacrifice of the productivity targets. By contrast, a narrow focus of reform on productivity and rent maximization will fail to address the real social and political costs of rebuilding fish wealth. A reform agenda calls for a greater understanding of the political and social processes and drivers of change in fisheries. It calls for approaches to disman- tling perverse incentives through appropriate tenure and property rights systems and the phasing out of subsidies that enhance fishing effort and fishing capacity. Guidance is available on some elements of reform processes, such as limited entry (Townsend 1990; Cunningham and Bostock 2005); buyback schemes (Curtis and Squires 2007; Clark, Munro, and Sumaila 2007); and individual transferable quotas and property rights (Committee to Review Individual Fish- ing Quotas 1999; Shotton 1999; WHAT 2000; Grafton et al. 2008). Guidance is also available on community rights (Christy 1999; Willmann 2000); on gover- nance and corruption (World Bank 2007a; World Bank and IUCN in press); and THE WAY FORWARD 53 on the political economy of reform and the durability of reforms (OECD 2008; Kjorup 2007). However, greater knowledge is required about the assessment and mitigation of social and political costs, the financing of reform, the timescale and sequencing of reform activities within political and investment cycles, and consensus building among competing stakeholders and their political con- stituencies. Fisheries reform can also be seen as part of a broader public policy agenda embracing fiscal reforms, pathways out of poverty, and greater trans- parency in stewardship and accounting for natural capital. A constructive dialogue on the political economy of reform requires a com- mon understanding among stakeholders of the potential net benefits from marine fisheries and of the current level of benefits and transparency in the allocation of those benefits. A constructive dialogue on reform will require knowledge of the political and social costs and benefits of reform options and informed stakeholder discussion on the alternatives (including transitions out of fisheries). Reforms may take time and require forging a political consensus and vision spanning changes of government. Experience shows that successful reforms may require champions or crises to catalyze the process. 5.2.6 Strengthening the Socioeconomic Dimension of the Fisheries Dialogue A target set out in the World Summit on Sustainable Development Plan of Implementation is the restoration of fish stocks to maximum sustainable yield levels by 2015. Harvesting at the MSY level is unlikely to capture a sub- stantial part of the economic rents and can be regarded as a minimum tar- get. The MSY target also implies a focus on the fish, and tilts toward a single species approach, rather than focusing on the underlying economic drivers, the political and social challenges to sharing the fish wealth, and the process of reform. Nevertheless, as a first step in tracking progress toward the restoration of fish stocks, countries, the primary global stakeholders, could report both on the state of fish stocks within their jurisdictional waters (see, for example, NMFS 2008; Department of the Environment, Water, Heritage and the Arts 2008), and on the level and distribution of benefits from the national fish wealth. 5.2.7 Accounting for Fish Wealth Is a National Role It is a matter of considerable concern that the depletion of fish wealth--natural capital--normally does not show up in the national accounts of countries. Because of weak property rights in national and international fisheries and because of difficulties in establishing market prices for these resources, fisheries assets fall outside the asset boundary of the System of National Accounts 1993 (the internationally recognized system for maintaining national accounts). As a result, a fishing country can run down fish resources and thus temporarily increase catch rates, which show up as an addition in the national accounts, without having to subtract the corresponding reduction in fish stock capital. In 54 THE SUNKEN BILLIONS other words, fishing nations have drawn upon the fishing sector's opaque natural capital account to "artificially" improve the nation's GDP and simul- taneously use this capital to (temporarily) support the operating accounts of fishers and the fishing companies. Ideally, the system of national accounts should, as a matter of course, include changes in natural capital just as it does for man-made capital. Given their economic importance, the omission of natural assets such as fish stocks from the national accounts entails a substantial oversight in economic accounting. National accounts including changes in natural capital are often referred to as green accounts, and specific guidance is readily available on envi- ronmental accounting for fisheries (UN and FAO 2004, Danielsson 2005). Because of the deficit of information on the economic health of the world's fisheries, the World Bank report "Where Is the Wealth of Nations?" was unable to take account of fisheries. Greater awareness of the scale of this capital asset depletion at the level of national policy makers and economic planners could build support for reform processes. 5.2.8 Rights to Harvest Fish Wealth Are Distinct from Rights to Benefit from Fish Wealth The notion that harvesters (fishers) have an exclusive, rather than a partial and conditional, right to the benefits from marine fisheries has tended to obscure the quest for increased social and economic benefits to society as a whole. This study shows that, in aggregate, the benefits to society as a whole are negative-- that society underwrites the sector, through subsidies, by paying the costs of fisheries management, and through depletion of capital (fish wealth). Rights and obligations are mutually supporting elements of governance, and strengthened marine resource property rights demand both clarity on and respect for the accompanying obligations (Fisman and Miguel 2006). Many traditional regimes distinguished rights to harvest from rights to ben- efits in acknowledgement that society at large also had a claim to the benefits of the harvest (Johannes 1978). The same principles are successfully applied in a modern setting, for example in fisheries in New Zealand (see figure A4.1 in appendix 4) and the Shetland Islands, where the tenure is vested in the com- munity and harvest rights are largely "firewalled" from the fundamental wealth creation and capital formation functions. 5.3 SUMMARY: THE WAY FORWARD 1. Use the results of this study to raise awareness among leaders, stakeholders, and the public on the potential economic and social benefits from improved fisheries governance. 2. Foster country-level and fishery-level estimates of the potential economic and social benefits of fisheries reform and of the social and political costs of reform as a basis for national-, or fishery-level dialogue. THE WAY FORWARD 55 3. Build a portfolio of experiences on the process of fisheries reform with a focus on the political economy of reform, process design, change man- agement, social safety nets, and the timescale and financing. Draw on the knowledge and lessons of reforms in other sectors, in particular with regard to the impact on the poor and the effectiveness and equity of adjustment mechanisms. 4. Progressively identify a portfolio of reform pathways based on a consensus vision for the future of a fishery founded on transparency in the distribu- tion of benefits and reforms that increase social equity. Common elements of such pathways could include effective stakeholder consultation processes; sound social and economic justifications for change; and an array of social and technical options, including decentralization and comanagement initia- tives to create more manageable fishery units. A reform process will bend the trusted tools of fisheries management to new tasks. Sound scientific advice, technical measures such as closed seasons, and effective registration of vessels and existing fishing rights are likely to form synergies with poverty reduction strategies, transitions out of fisheries, social safety nets, and com- munity comanagement. 5. Review fiscal policies in order to phase out subsidies that enhance fishing effort and fishing capacity and to redirect public support measures toward strengthening fisheries management capacities and institutions and avoid- ing social and economic hardships in the fisheries reform process. 6. In an effort to comply with the World Summit on Sustainable Development Plan of Implementation call for restoration of fish stocks, countries could, on a timely basis provide to their public an assessment of the state of national fish stocks and take measures to address the underreporting or misreporting of catches. 7. Countries can further justify reforms in fisheries by recognizing that responsible fisheries build resilience to the effects of climate change and reduce the carbon footprint of the industry. NOTE 1. The Code of Conduct for Responsible Fisheries (FAO 1995) provides an overarching framework for sustainable fisheries. 56 THE SUNKEN BILLIONS A P P E N D I X O N E The Concept of Economic Rent in Fisheries conomic rent is defined as "the payment (imputed or otherwise) to a E factor in fixed supply."1 This definition is formulated in terms of a fac- tor of production and can be extended to cover any restricted variable, such as fish catch. Figure A1.1, showing a demand curve and a supply curve, is often used to illustrate Ricardo's theory of land rents. In the figure, the market price is p. However, because the quantity of the factor (for example, land) is fixed, the corresponding supply, y, would be forthcoming even if the price were zero, and so the price, p, may be regarded as a surplus per unit of quantity. The total sur- plus is represented by the rectangle p.y, which also represents the economic rents attributable to the limited factor, y. The economic rents depicted in figure A1.1 represent rental income to the owner of the factor in fixed supply (for example, land) who rents it out to users. The economic rents do not, however, represent the total economic ben- efits of the supply y. These benefits are measured by the sum of economic rents and the demanders' surplus represented by the upper triangle in the diagram. Thus, in the case depicted in figure A1.1, total benefits, those of the owner plus those of the demanders,2 would be greater than economic rents. However, in fisheries (as, indeed, in most other natural resource use), the quantity of supply is not fixed. At each point of time, it is usually possible to extract more or less from the resource stock. Usually in common pool fish- eries, the demand will push the supply to y0 (see figure A1.1), at which point there are no economic rents. At the other extreme, supply may be limited by CHAPTER TITLE 57 Figure A1.1 Economic Rents Supply Intra- marginal Price profits/rents p Demand Economic rents y y0 Quantity Source: Authors' depiction. a management regime with the objective of maximizing fisheries rents. Between these extremes, the various fisheries management regimes restrict the harvest quantity at different levels and in different ways. A cost is associated with resource reduction (a variant of capital reduction cost) for each level of harvest from the stock. This is entirely separate from the cost of the harvesting activity as such, which is included in the demand curve. This cost is the economically appropriate supply price of fish.3 The resource reduction cost increases with the quantity extracted, or level of harvest. This defines an economically appropriate supply curve for harvest (Arnason 2006), as illustrated in figure A1.2. The optimally managed fishery will set the actual quantity of supply (allow- able harvest) at y, corresponding to the intersection between the supply and demand curves in A1.2. At this level point, there will be a price of supply denoted by p in the diagram. The supply y gives rise to fisheries rents as indicated by the rectangle in the figure.4 Under conditions of open access, the supply is not restricted and the quantity of extraction will be at y0 which corresponds to no rents at all. Measurement of fisheries rents means estimating areas represented by such rectangles and requires estimates of the demand curve for harvests. The demand curve for harvests follows from the profit function of the fishing industry. A simple form of this function is written as (y,x), (1.1) where y is the harvest level and x the biomass of the stock. The demand curve for harvest is defined as the instantaneous marginal profits from harvest (Arnason 2006) and may be written as (y,x). y (1.2) 58 THE SUNKEN BILLIONS Figure A1.2 Illustrative Resource Rents in a Resource Extraction Industry Supply Price p Demand Natural resource rents y y0 Harvest quantity Source: Authors' depiction. Accordingly, fisheries rents are defined as R (y, x) = (y, x). y. y (1.3) An estimation of fisheries rents requires a determination of the marginal profits of the fishing industry. To estimate maximum economic rents or economic rents in equilibrium, a bioeconomic model of the fishery is needed. NOTES 1. As defined by Alchian (1987) in the New Palgrave Dictionary of Economics and build- ing on the classical theory by Adam Smith (1776) and David Ricardo (1817). 2. Some authors refer to the demanders' surplus as intramarginal rents. See, for exam- ple, Coglan and Pascoe (1999) for the case of fisheries and Blaug (2000) more gen- erally. DFID (2004) provides a short overview of rents in fisheries, and Clark and Munro (1975) provide an overview of fisheries and capital theory. 3. Also called user cost by Scott (1955) and shadow price of the resource by Dasgupta and Heal (1979). 4. The rectangle, represented by the multiple p.y in the figure, corresponds to economic rents in the traditional (Smith-Ricardian) sense as defined by Alchian. THE CONCEPT OF ECONOMIC RENT IN FISHERIES 59 A P P E N D I X T W O Model and Model Estimation T his appendix sets out the details of the global fisheries model employed in this study and explains how it is applied. THE BASIC MODEL The basic model is the following aggregative fisheries model: x = G(x) - y (biomass growth function). (2.1) y = Y (e, x) (harvesting function). (2.2) p=p.Y(e,x) (profit function). (2.3) R y (y,x) y = p - Ce (e) e y y (fisheries rents).1 (2.4) Equation 2.1 describes net biomass growth, denoted by the derivative, x x t . The variable x represents the level of biomass and y harvest. The function G(x) represents the natural growth of the biomass before harvesting. Equation 2.2 explains the harvest as a function of fishing effort, e, and biomass. Equation 2.3 defines profits as the difference between revenues, p.Y (e, x), where p denotes the average net landed price of fish and costs are represented by the cost function C(e). Equation 2.4 specifies fisheries rents, R. This, as explained in appendix 1, is formally defined as ( y ) y. CHAPTER TITLE 61 Of the six variables in this model, that is, x, y,p, R, p, and e, the first four may be seen as endogenous, that is, determined within the fishery. The fifth, price, is exogenous, determined by market conditions outside the fishery. The sixth, fishing effort, e, may be seen as the control variable, that is, the variable whose values may be selected to maximize benefits from the fishery. THE SPECIFIC MODEL The basic model comprises three elementary functions; the natural growth function, G(x); the harvesting function, Y(e, x); and the cost function, C(e). The specific model is defined by deciding on the form of these functions. Two variants of the biomass growth function G(x) are used: the logistic function (Volterra 1923) and the Fox function (Fox 1970). As explained previ- ously, the main difference between these two functions is that the Fox function exhibits higher biomass growth at relatively low biomass levels and thus is more resilient to high levels of fishing effort than the logistic function. G(x) = a x ­ b x2, . . (Logistic) (2.5) G(x) = a x ­ b ln(x) . . .x (Fox 1970). (2.6) For harvesting, the generalized Schaefer (1954) form is selected: Y (e, x) = q . e.xb, (2.7) where the coefficient b indicates the degree of schooling behavior by the fish (normally b [0,1]). The coefficient q is often referred to as the catchability coefficient. For the cost function, the following linear form is chosen: C (e) = c . e + fk , (2.8) where c represents marginal variable costs and fk fixed costs. Under these functional specifications the complete model becomes: x = x - x 2 - y, , or (biomass growth functions). (2.9) x = x - ln(x) x - y y = q . e. xb (harvesting function). (2.10) p=p .y ­ c .e ­ fk (profit function). (2.11) R = p y - q y x -b c (fisheries rents). (2.12) 62 THE SUNKEN BILLIONS Assuming biomass equilibrium, that is, x. = 0, it is possible to deduce from equations 2.9 and 2.10 the equilibrium or sustainable yield curves as functions of fishing effort for the two biomass growth functions. The corresponding equilibrium revenue curves are illustrated in figure A2.1, where the graph of the cost curve is also depicted. The resulting equilibrium diagram is usually referred to as the sustainable fisheries model (see, for example, Hannesson 1993). The discontinuity in both equilibrium revenue functions illustrated in figure A2.1 is a common feature in real fisheries (see, for example, Clark 1976). In this particular case it occurs because a degree of schooling behavior (b < 1) has been assumed. Equilibrium profits from the fishery are maximized at a fishing effort level where the distance between equilibrium revenues and costs is greatest. As can be seen from figure A2.1, this occurs at different fishing effort levels for the two biomass growth functions. Equilibrium fisheries rents are not generally identifiable from a diagram such as figure A2.1, and fisheries rents are generally not maximized at the same effort level that maximizes profits. However, for the specific model of this study, rents may be identified as the difference between equilibrium revenues and the variable costs curve (that is, a curve parallel to the cost curve but passing through the ori- gin). Also, in this specific model, the rents and profits maximizing fishing effort levels coincide, although maximum rents may well exceed maximum profits. A condensed form of the model may be obtained by combining equations 2.10 and 2.11 to yield = p y - q y x -b - fk c (profit function). (2.13) This condensed form of the model, that is, equations 2.9, 2.12, and 2.13, shows that knowledge of fishing effort is not needed to run the model, and that Figure A2.1 The Equilibrium Fisheries Model Logistic Costs Equilibrium Fox values Fishing effort Source: Authors' depiction. MODEL AND MODEL ESTIMATION 63 marginal costs and catchability, c and q, do not play an independent role in this model. The ratio of the two (c /q) may be regarded as a single coefficient, referred to as "normalized marginal cost." ESTIMATION OF MODEL INPUTS The "specific fisheries model" (that is, equations 2.9, 2.12, and 2.13) contains six unknown coefficients ,, q ,b,p,f k. These have to be estimated from c data or determined in some other way. The model also contains five unknown variables, namely, x, y, p, and R as well as the change in biomass, x. The model can be used to solve for three of these variables endogenously. The other two have to be either estimated from data or determined in some other way. In the rents loss calculations of this study, current or base year rents are compared to maxi- mum equilibrium rents. For the calculations of maximum equilibrium rents, estimates of these two variables are not required. First, the equilibrium biomass is constant, so x = 0. Second, the harvest, y, is determined by the maximization exercise. For the current rents calculations, estimates of base year harvest and biomass growth, y(t) and x (t*), respectively, were obtained. The model inputs (coefficients and variables) that have to be estimated are listed in table A2.1. There are many ways to obtain estimates of the model input data listed in table A2.1. Because the quality of some global fisheries data sets is poor, the study has elected a procedure that minimizes data requirements. The global data needed are listed in table A2.2. The procedure is summarized as a series of estimation formulas listed in table A2.3. These formulas can be verified by the appropriate manipulation of the specific model above. The change in fishing effort from an initial to an optimal fishery can be cal- culated using the same basic data listed in table A2.2. More precisely, it can be shown that e = e(t ), where = p y - , and p y(t ) - (t ) (2.14) where `' indicate the final equilibrium levels of variables and `t' the base year values. If the numerical value of e(t) is known, the numerical value of e can be calculated for this expression. Otherwise, e can be calculated as a fraction of e(t), that is, as an index. The input values used for the estimations and their respective sources are listed in table A2.4. In a long-run economic equilibrium, all costs are variable (Varian 1984). This is because in the long-run equilibrium, all capital (the source of fixed costs) has been adjusted. Therefore, in the movement to long-run equilibrium, all so-called fixed costs are in fact variable. In this study, the equilibrium (or 64 THE SUNKEN BILLIONS Table A2.1 Summary of Model Coefficients and Variables That Need to Be Estimated Coefficient or Permissible variable Characterization values Biological coefficients Biomass growth function a Intrinsic growth rate (only > 0 for the logistic function) Biomass growth function b b>0 Harvesting function b Schooling parameter 0 0 Cost function f k Fixed costs fk 0 Revenues p Net landings price p > 0 Variables (in base year, t*) Landings y (t*) Volume of landings y(t*) 0 Biomass growth x (t*) Biomass growth Source: Authors' models. Table A2.2 Data for Estimation of Model Coefficients and Variables Biological data Symbol Maximum sustainable yield MSY Biomass carrying capacity Xmax The schooling parameter B Fisheries data in a base year t* Biomass growth in year t* x (t*) Landings in year t* y(t*) Price of landings in year t* p(t*) Profits in year t* (t*) Fixed cost ratio in year t* (fk / TC (t*)) e(t*) Source: Authors' models. long-run) maximum rents are going to be compared to current rents. There- fore, within the framework of this study, any fixed costs experienced in the base year are taken to be variable when considering the movement to the rents- maximizing equilibrium. This is equivalent to setting the fixed cost ratio in the MODEL AND MODEL ESTIMATION 65 Table A2.3 Formulas to Calculate Model Parameters Unknowns Formula Logistic function ^ ^ = 4 MSY Xmax ^ ^ = 4 MSY Xmax 2 ^ 0.5 Biomass in base year, x^(t*) x^(t*) =2^ 1± 1- 4 ^ (y(t*) + x (t*)) ^ 2 Fox function ^ ^ = MSY ln(Xmax ) exp Xmax ^ ^ = MSY exp Xmax Biomass in base year, x^(t*) (^ - ^ ln(x^(t*) x^(t*) = x (t*) + y(t*) ) (p(t*) y(t*) - (t*)) (1- ) Normalized marginal cost, c q c^ = y(t*) x^(t*) Fixed costs, f^k f^k = (p(t*) y(t*) - (t*)) (t*) The schooling parameter, b^ B Landings in year t*, y^(t*) y(t*) Price of landings in year t*, y^(t*) p(t*) Source: Authors' models. base year equal to zero. Note that this does not imply that the fixed costs in the base year are ignored. They are included but regarded as variable costs. On the basis of the empirical assumptions listed in table A2.4 and the for- mulas in table A2.3, the model coefficients can be calculated. The results are listed in table A2.5. With the empirical assumption and the estimates above, the condensed form of the global fisheries model employed in this study becomes: x = 0.839 x - 0.002 x 2 , (logistic biomass growth). (2.15) x = 3.486 x - 0.57 ln(x) x , (Fox biomass growth). (y ,x) = 0.918 y - 32.8 y x 0 , .7 (profits for the logistic). (2.16) (y ,x) = 0.918 y - 23.2 y x 0 , .7 (profits for the Fox). 66 THE SUNKEN BILLIONS Table A2.4 Empirical Values and Assumptions for Estimation of Model Coefficients Input data Units Value Biological data Maximum sustainable yield MSY m. metric tons 95 Carrying capacity Xmax m. metric tons 453.0 Fisheries data in base year (2004) Biomass growth in base year t* x(t* ) m. metric tons ­2 Landings in base year t* y(t*) m. metric ton 85.7 Price of landings in base year t* p(t*) 1000 $/ton 0.92 Profits in base year t* (t*) billion $ ­5 Fixed cost ratio in base year t* e(t*) ratio 0 The schooling parameter b no units 0.7 Elasticity of demand with respect d no units 0.24 to biomass Effort (index or real base year effort) Fishing effort (fleet) in base year e(t*) index 1.00 Source: Authors' models. Table A2.5 Calculated Model Coefficients (Implied) Variable Logistic Fox Biomass growth parameter, a 0.839 3.486 Biomass growth parameter, b 0.002 0.570 Biomass, x (2004) 148.4 92.3 Normalized marginal costs, c /q 32.3 23.2 Schooling parameter, b 0.7 0.7 Fixed costs, fk 0 0 Source: Authors' calculations. R(y , x) = 0.918 y - 32.8 y x 0 .7 (fisheries rents for the logistic). R(y , x) = 0.918 y - 23.2 y x 0 (2.17) .7 (fisheries rents for the Fox). In the same way as in figure A2.1, the essence of the empirical global fish- eries model can be illustrated graphically (figure A2.2). MODEL AND MODEL ESTIMATION 67 Figure A2.2 Graphical Illustration of the Global Fishery 120.0 Sustainable revenues Fox function Costs Sustainable revenues Logistic function Costs 100.0 80.0 Fox billions 60.0 US$ 40.0 20.0 Logistic 0.0 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 Fishing effort (index) Source: Authors. NOTE 1. In appendix 1, rent was defined as R y(y,x) y, where y (y,x) is the first derivative of the profit function, that is, marginal profits. For this particular fisheries model with fishing effort rather than harvest as a control variable, y (y,x)=p - Ce (e) e y . 68 THE SUNKEN BILLIONS A P P E N D I X T H R E E Stochastic Specifications and Confidence Intervals ecause of the uncertainties concerning the empirical values and B assumptions underlying the global fisheries model, the resulting rent loss estimates should be regarded as stochastic with associated proba- bility distributions. Because the rents loss calculations involve a complex non- linear function of the empirical data and assumptions, the analytic equations for the probability distribution of these estimates are not readily obtainable. To generate confidence intervals for the rents loss, reasonable probability distri- butions for the empirical data and assumptions are specified, and Monte Carlo stochastic simulations (Davidson and MacKinnon 1993; Fishman 1996) were used to generate probability distributions for the model inputs and outcomes (fisheries rents and fisheries rents loss). Probability distributions for the stochastic input parameters listed below were generated on the basis of 2,000 simulations drawing from the distribu- tions specified here. The stochastic specifications are summarized in table A3.1, and the resulting outcomes and distributions are illustrated in the figures that follow. 1. Global maximum sustainable yield (MSY) 2. Global biomass carrying capacity (Xmax) 3. Biomass growth in the base year (x.) 4. Landings in the base year (y) 5. Landings price (p) 6. Profits in the base year (prof/P ) 7. Schooling parameter (b) 8. Elasticity of demand (D) The remaining input parameter, the fixed cost ratio (e), is assumed to be non- stochastic (see appendix 2). CHAPTER TITLE 69 Table A3.1 Empirical Values and Assumptions: Stochastic Specifications Implied 95 percent Point Type of Standard confidence Variable estimate distribution deviationa interval MSY 95 Log-normal 0.03 89.5 to 100.9 Xmax 453 Log-normal 0.1 370.9 to 553.3 x(t* ) ­2 Normal 3.0 ­8 to 4 y(t*) 85.7 Log-normal 0.015 83.2 to 88.3 p(t*) 0.918 Log-normal 0.03 0.865 to 0.975 P(t*) ­5 Normal 2.5 ­10 to 0 b 0.7 Log-normal 0.05 0.63 to 0.77 D 0.2 Log-normal 0.1 0.164 to 0.244 e(t*) 0 Log-normal 0.0 0 Source: Authors' calculations. a. For lognormal distributions, the standard deviation may be interpreted as an approximate percentage deviation. OUTCOMES OF THE MONTE CARLO STOCHASTIC SIMULATIONS Logistic Model (figure A3.1) Nonnormal distribution Mean rents loss: $43.0 billion Median rents loss: $44.5 billion Mode rents loss (approximately) $48 billion Standard deviation: $8.8 billion 95 percent confidence interval ($ billion): [20.2, 55.7]. Fox Model (figure A3.2) Approximately normal distribution Mean rents loss: $59.0 billion Median rents loss: $59.2 billion Mode rents loss (approximately) $52 billion Standard deviation: $9.0 billion 95 percent confidence interval ($ billion): [38.8,74.6] 70 THE SUNKEN BILLIONS Figure A3.1 Graphical Illustration of Stochastic Simulations Using the Logistic Model Density function Distribution function 600 1 400 0.5 Frequency 200 Probability 00 0 50 20 40 60 Rents loss ($ billion) Rents loss ($ billion) Source: Authors' simulation. The Combined Models The difference between the means of the two models appears to be highly sig- nificant at the 5 percent level. Assuming that the two biomass growth functions are equally likely, the respective stochastic distributions may be combined in one overall distribution as illustrated in figure A3.3. The crucial outcomes from this combined model are: Mean rents loss: $51.0 billion Standard deviation: $12.0 billion 95 percent confidence interval ($ billion): [26.3, 72.8] Calculated Rents and Rents Loss Two thousand draws from the stochastic distributions described earlier were taken and the resulting rents and rents loss calculated. The latter is defined as the difference between the maximum attainable sustainable rents and those that pertain to the base year (2004). Both the current and the maximum rents estimates are stochastic. On this basis, the distributions for the outcomes are derived and confidence intervals calculated. The stochastic specifications for the empirical assumptions are those listed in table A3.1. The key results of the 2,000 draws from the stochastic distributions described earlier and the resulting rents are summarized in table A3.2 (they are also shown in table 4.5 in the main text). The distribution of the rents loss is illustrated in figure A3.4. STOCHASTIC SPECIFICATIONS AND CONFIDENCE INTERVALS 71 Figure A3.2 Graphical Illustration of Fox Model Stochastic Simulations Density function Distribution function 400 1 200 0.5 Frequency Probability 00 0 20 40 60 80 40 60 80 Rents loss ($ billion) Rents loss ($ billion) Source: Authors' simulation. Figure A3.3 Graphical Illustration of Combined Logistic and Fox Model Stochastic Simulations 600 1 Combined Logistic 400 0.5 Frequency200 Fox Probability 0 0 0 50 100 0 50 Rents loss ($ billion) Rents loss ($ billion) Source: Authors' simulation. Table A3.2 Estimated Rent Loss: Main Results (US$ billions) Maximum Current (2004) sustainable rents Rents loss 95 percent 95 percent 95 percent Model Mean confidence Mean confidence Mean confidence interval interval interval Logistic ­5.0 [­10.2, 0.0] 37.6 [4.7, 48.2] 43.0 [20.2, 55.7] Fox ­5.0 [­10.2, 0.0] 53.4 [41.4, 65.4] 59.0 [38.8, 74.6] Combined ­5.0 [­10.2, 0.0] 45.3 [38.1, 63.9] 51.0 [26.3, 72.8] Source: Authors' calculations. 72 THE SUNKEN BILLIONS Conclusion In conclusion, the most reasonable estimate of the global rents loss is: Mean: $51 billion per year with 95 percent confidence interval ($billion per year): [26.3,72.8] 90 percent confidence interval ($billion per year): [31.3,69.8] 80 percent confidence interval ($billion per year): [36.5,66.9] DETAILS OF THE PROBABILITY DISTRIBUTIONS FOR THE INPUT PARAMETERS Maximum SustainableYield (MSY) MSY °=MSY eu1 , u1 N (0,1), where MSY ° represents the stochastic maxi- mum sustainable yield and MSY the point estimate. The random term u1 is assumed to be normally distributed with mean zero and standard deviation 1. This specification implies that MSY ° exhibits a lognormal distribution. In the stochastic simulations it is assumed 1 = 0.03. This gives rise to the distribu- tion illustrated in figure A3.4(a). An estimated 5 percent confidence interval for MSY ° is MSY ° [89.5, 100.9] million metric tons. Biomass Carrying Capacity (XMAX) XMAX ° = XMAX eu2 , u2 N (0,2), where XMAX° represents the stochastic carrying capacity of the global commercial biomass with XMAX as the point estimate. The random variable u2 is assumed to be normally distributed with mean zero and standard deviation 2. This specification implies that XMAX ° exhibits a lognormal distribution. In the stochastic simulations, it is assumed that 2 = 0.1. This leads to the distribution illustrated in figure A3.4(b). An estimated 5 percent confidence interval for XMAX ° is XMAX ° [370.9, 553.3] million metric tons. Biomass Growth in BaseYear (XDOT) XDOT ° = XDOT + u3 , where XDOT ° represents the stochastic biomass growth in the base year, and XDOT is the point estimate. The random variable u3 is assumed to be normally distributed with mean zero and standard devia- tion 3. This specification implies that XDOT ° exhibits a normal distribution. In the stochastic simulations, it is assumed that 3 = 3. This generates the distribution illustrated in figure A3.4(c). An approximate 5 percent confidence interval for XDOT ° is XDOT ° [ - 8,4] million metric tons. STOCHASTIC SPECIFICATIONS AND CONFIDENCE INTERVALS 73 Figure A3.4(a)­(h) Simulated Distributions (a) MSY (b) XMAX 400 400 200 200 Frequency Frequency 0 0 90 95 100 105 110 200 300 400 500 600 MSY XMAX (c) XDOT (d) Landings, Y 300 400 200 200 Frequency 100 Frequency 0 0 ­10 ­5 0 5 10 75 80 85 90 XDOT Landings, Y (e) Profits in base year (f) Price, P 400 400 200 200 Frequency Frequency 0 0 ­20 ­10 0 10 0.8 0.9 1 1.1 Profits in base year Price, P (g) Schooling parameter, b (h) Elasticity of price 400 400 200 200 Frequency Frequency 0 0 0.8 0.82 0.84 0.86 0.1 0.15 0.2 0.25 Schooling parameter, b Elasticity of price Source: Authors' simulation. 74 THE SUNKEN BILLIONS Landings in BaseYear (Y) Y ° = Y eu2 , u4 N (0,4 ), where Y° represents the stochastic landings in the base year and Y is the point estimate. The random variable u4 is assumed to be normally distributed with mean zero and standard deviation 4. This specifi- cation implies that Y ° exhibits a lognormal distribution. In the stochastic simulations, 4 = 0.015. This gives rise to the distribution illustrated in figure A3.4(d). A 5 percent confidence interval for Y ° is Y ° [83.2, 88.3]million metric tons. Profits in BaseYear (Prof P ) PROF° = PROF + u5, u5 ~ N (0, 5), where PROF ° represents the stochastic profits in the base year and PROF the point estimate for these profits. The ran- dom variable u5 is normally distributed with mean zero and standard deviation 5. This specification implies that PROF ° exhibits a normal distribution. In the stochastic simulations, 5 = 2.5. This leads to the distribution illustrated in figure A3.4(e). A 5 percent confidence interval for PROF° is PROF ° [ -10, 0] billion $. Landings Price (P) P° = P eu6 , u6 N (0,6), where P° represents the stochastic landings price P, the point estimate of the landings price, and u6 is assumed to be a normally distributed random variable with mean zero and standard deviation 6. This specification implies that P° exhibits a lognormal distribution. In the stochas- tic simulations, 6 = 0.03. This gives rise to the distribution illustrated in figure A3.4(f). A 5 percent confidence interval for P° is P° [0.865, 0.975] dol- lars per kilogram. Schooling parameter (b) b° = b eu2 u7 N(0,7 ), where b° represents the stochastic schooling parame- ter with b being the point estimate. The random variable u7 is assumed to be normally distributed with mean zero and standard deviation 7. This specifica- tion implies that b° exhibits a lognormal distribution. In the stochastic simula- tions, it is assumed that 7=0.05. This gives rise to the distribution illustrated in figure A3.4(g). A 5 percent confidence interval for b° is b° [0.63, 0.77]. Elasticity of Demand (d) d° = d eu2 , u8 N (0,8),where d° represents the stochastic schooling parame- ter with d being the point estimate. The random variable u8 is assumed to be normally distributed with mean zero and standard deviation 8. This specifica- tion implies that d° exhibits a lognormal distribution. In the stochastic simula- tions, it is assumed that 8 = 0.1. This gives rise to the distribution illustrated in figure A3.4(h). A 5 percent confidence interval for d° is d° [0.164, 0.244]. STOCHASTIC SPECIFICATIONS AND CONFIDENCE INTERVALS 75 A P P E N D I X F O U R Supplementary Data CHAPTER TITLE 77 Table A4.1 Motorized Fishing Fleets in Selected Major Fishing Countries, 2004 Reported Fishing fleet parameters, 2004 global Country/ marine Number of Tonnage Power Economy catch* (%) vessels (GT) (kW) China 17 509,717 7,115,194 15,506,720 EU-15 6 85,480 1,882,597 6,941,077 Iceland 2 939 187,079 462,785 Japan 5 313,870 1,304,000 -- Norway 3 8,184 394,846 1,328,945 Republic of Korea 2 87,203 721,398 16,743,102 Russian Federation 3 2,458 1,939,734 2,111,332 Source: China: FAO fishery statistical inquiry; EU-15: Eurostat; Iceland: Statistics Iceland (http://www.statice.is); Japan: Japan Statistical Yearbook 2006 (http://www. stat. go.jp/english/data/nenkan/index.htm); Republic of Korea: Korea Statistical Yearbook 2005 Vol. 52; Norway: Statistics Norway (http://www.ssb.no) and Eurostat; Russian Federa- tion: FAO fishery statistical inquiry, FAO FishStat; Concerted Action 2004. Note: Some vessels may not be measured according to the 1969 International Conven- tion on Tonnage Measurement of Ships. The Icelandic data exclude undecked vessels. The Japanese data refer to registered fishing vessels operating in marine waters. The Russian Federation data refer to powered decked vessels with a national license. *excluding aquatic plants. Table A4.2 Selected Examples of Relationship between Estimated MSY and Biomass Carrying Capacity Carrying Multiple Fishery MSY (tons) capacity (tons) (biomass/MSY) Denmark cod 216 1,443 6.68 Norway cod 602 2,473 4.11 Iceland cod 332 1,988 5.99 Denmark herring 666 4,896 7.35 Norway capelin 2,219 8,293 3.74 Iceland capelin 1,010 3,669 3.63 Bangladesh Hilsa 286 1,084 3.79 Source: International Council for the Exploration of the Sea; FAO. 78 THE SUNKEN BILLIONS Table A4.3 Estimation of the Weighted Average Global Schooling Parameter Imputed Schooling Species group MSY (tons) parameter Weighted Salmons, trouts, smelts 1,016,854 1.00 0.007 Shads 426,754 0.50 0.002 Miscellaneous diadromous fishes 80,134 0.70 0.001 Flounders, halibuts, soles 1,392,052 1.00 0.014 Cods, hakes, haddocks 13,788,742 1.00 0.137 Miscellaneous coastal fishes 6,935,300 1.00 0.069 Miscellaneous demersal fishes 3,162,243 1.00 0.031 Herrings, sardines, anchovies 25,908,711 0.30 0.077 Tunas, bonitos, billfishes 6,243,122 0.60 0.037 Miscellaneous pelagic fishes 14,322,640 0.50 0.071 Sharks, rays, chimaeras 880,785 0.90 0.008 Marine fishes not identified 10,738,831 0.85 0.090 Crabs, sea spiders 1,333,282 0.70 0.009 Lobsters, spiny rock lobsters 233,825 0.70 0.002 King crabs, squatlobsters 163,513 0.70 0.001 Shrimps, prawns 3,478,304 0.80 0.028 Krill, planktonic crustaceans 528,335 0.50 0.003 Miscellaneous marine crustaceans 1,427,312 0.70 0.010 Abalones, winkles, conchs 139,964 1.00 0.001 Oysters 302,526 1.00 0.003 Mussels 317,852 1.00 0.003 Scallops, pectens 804,349 1.00 0.008 Clams, cockles, arkshells 1,129,231 1.00 0.011 Squids, cuttlefishes, octopuses 3,892,145 0.70 0.027 Miscellaneous marine molluscs 1,596,036 0.90 0.014 Sea squirts and other tunicates 21,331 1.00 0.000 Horseshoe crabs and other arachnoids 3,252 1.00 0.000 Sea urchins and other echinoderms 140,461 1.00 0.001 Miscellaneous aquatic invertebrates 539,994 0.90 0.005 TOTAL 100,965,809 n.a. 0.670 Source: MSY values are the historical maximum catches by species group as reported by Fishstat Plus. The schooling parameters are assumed based on information on schooling parameters for several indicative species. n.a. = Not applicable. SUPPLEMENTARY DATA 79 80 Table A4.4 Indicative Results of Selected Case Studies on Economic Rents in Fisheries Rent/revenue loss as % of base revenues/landed values Fishery Base year Percent Rent or proxy Source Vietnam Gulf of Tonkin demersal multigear, 2006 29 rent Nguyen and Nguyen 2008 multispecies Icelandic cod demersal multigear, 2005 55 rent Arnason pers. comm. multispecies Namibian hake trawl 2002 136 rent Sumaila and Marsden 2007 Peruvian anchoveta purse seinea 2006 29 rent Paredes 2008 Bangladesh hilsa artisanal multigear 2005 58 rents Gulf of Thailand demersal multigear 1997 42 net revenues Willmann et al. 2003 multispecies Yemen lobster, artisanal 2008 1,653 net revenues Shotton pers. comm. British Columbia salmon fishery 1982 76 rents Dupont 1990 Cyprus fisheries 1984 5 revenue increase Hannesson 1986 Small pelagic fisheries in northwest 1980­90 79 revenue Tai and Heaps 1996 Peninsular Malaysia U.S.Atlantic sea scallop 1995 75 Repetto 2002 U.S. fisheries 2003 192 net present value Sumaila and Suatoni 2006 New England groundfish 1989 188 rents Edwards and Murawski 1993 Gulf of Mexico shrimp 1990s 50 present value Ward 2006 Western and Central Pacific tuna 1996 59 profit Bertignac et al. 2001 Norwegian trawl 1998 439 rents Ache et al. 2003 Japan coastal squid 2004 77 rents Hoshino and Matsuda Japan Pacific saury stick-held dip-net fishery 2004 89 rents 2007 Lake Victoria Nile perch (freshwater) 2006 61 rents Warui 2008 Danish mussel 2001­03 9 landed value Nielsen et al. 2007 Swedish pelagic fishery 2001­03 50 landed value Nielsen et al. 2007 Faroese pair trawl 2001­03 19 landed value Nielsen et al. 2007 Norwegian coastal (ITQ) 2001­03 40 landed value Nielsen et al. 2007 Note: Values presented refer to different economic indicators and are not necessarily comparable. The table is provided to illustrate the fact that in many fisheries, substantial additional net benefits can be derived through responsible fisheries management with a focus on economic and social benefits. a. Economic returns from pelagic fisheries are highly variable and can be heavily influenced by environmental factors or export markets, not merely by the effectiveness of the management regime. 81 82 Table A4.5 Projection of Rent Loss, 1974­2007 ($ billion) Global fish stock Cumulative exploitation status Rents loss Deflated rents rents loss at fully + over + depleted (US$ DeflatorIndexed b loss by year 3.5 percent Year Percent Index billion) Base 2004 (US$ billions) (US$ billions) 1974 0.61 0.80 40.5 53.5 0.36 14.8 15 1975a -- -- 40.5 58.4 0.40 16.1 33 1976 -- -- 40.5 61.1 0.42 16.9 51 1977 -- -- 40.5 64.9 0.44 17.9 72 1978 0.59 0.77 39.5 69.9 0.48 18.8 93 1979 0.63 0.82 42.0 78.7 0.54 22.5 120 1980 -- -- 42.0 89.8 0.61 25.7 151 1981 0.63 0.82 41.8 98 0.67 27.9 185 1982 -- -- 41.8 100 0.68 28.5 221 1983 0.69 0.91 46.3 101.3 0.69 31.9 262 1984 -- -- 46.3 103.7 0.71 32.7 305 1985 0.68 0.90 45.7 103.2 0.70 32.1 349 1986 -- -- 45.7 100.2 0.68 31.2 393 1987 0.69 0.90 45.8 102.8 0.70 32.1 440 1988 -- -- 45.8 106.9 0.73 33.3 490 1989 0.69 0.91 46.4 112.2 0.76 35.5 544 1990 0.69 0.90 45.8 116.3 0.79 36.3 601 1991 -- -- 45.8 116.5 0.79 36.4 659 1992 0.71 0.93 47.2 117.2 0.80 37.7 721 1993 -- -- 47.2 118.9 0.81 38.2 786 1994 -- -- 47.2 120.4 0.82 38.7 854 1995 0.70 0.92 47.0 124.7 0.85 39.9 925 1996 -- -- 47.0 127.7 0.87 40.9 1,000 1997 0.73 0.96 49.0 127.6 0.87 42.6 1,079 1998 -- -- 49.0 124.4 0.85 41.5 1,159 1999 -- -- 49.0 125.5 0.86 41.9 1,243 2000 0.75 0.98 48.8 132.7 0.90 44.1 1,333 2001 -- -- 48.8 134.2 0.91 44.6 1,425 2002 -- -- 48.8 131.1 0.89 43.6 1,520 2002 -- -- 48.8 131.1 0.89 43.6 1,520 2003 -- -- 48.8 138.1 0.94 45.9 1,621 2004 0.76 1.00 51.0 146.7 1.00 51.0 1,731 2005 -- -- 51.0 157.4 1.07 54.7 1,848 2006 -- -- 51.0 164.7 1.12 57.3 1,972 2007 -- -- 51.0 172.6 1.18 60.0 2,103 2008 -- -- 51.0 -- 1.18 60.0 2,239 Source: FAO State of Marine Fisheries (year for which stock status is available indicated in bold). Note: Section 4.1. in the main text indicates how the calculations in this table were made. -- Data are not available. Base years for indexes are shown in italic. a. Because the FAO's assessment of the state of marine fish stocks is not available for certain years, values from preceding year are used. b. The deflator is that used by the U.S. Labor Department for all commodities. 83 Figure A4.1 Example of Increasing Rents in New Zealand and Icelandic Fisheries 4,000 (a) New Zealand Deepwater Fishery shares 3,500 millions quota of NZ$ 3,000 value 2,500 2000 2001 2002 2003 2004 2005 2006 (b) Icelandic Cod Fishery 5,000 4,000 values 3,000 quota millions 2,000 US$ 1,000 permanent 0 1984 1989 1994 1999 2004 Source: (a) PROFISH Team, World Bank, based on New Zealand deepwater fishery monetary stock accounts; (b) Authors. Note: The quota share value is used as a proxy for rents. 84 THE SUNKEN BILLIONS R E F E R E N C E S Agnarsson, S., and R. Arnason. 2007. 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See costs costs employment and income issues, in aggregate model, 35­37 15­18f capital costs, 36­37, 37t, 40, 40n6 fishing capacity, 21­22 of fishing, 12­18 fishing effort, 18­19 fixed cost ratio, 39­40 fishing fleet, 18­22, 19­21f, 78t fuel prices. See fuel prices intangible values, 12 illegal, unreported, and unregistered management of fisheries, 24­26, 40 fishing, 25­26 net economic loss. See net economic labor, 35­36 loss, estimating major cost factors, 12 pricing. See pricing of fish management of fisheries, 24­26, 40 productivity levels. See productivity 96 INDEX subsidies, effects of, 23­24, 23b, 24t, exploitable aggregate biomass, 40, 50­51 31­32, 32f, 41, 42, 47­48f, 62 tenure issues, xxii­xxiii, 52, 55 Monte Carlo stochastic trends in trade in and consumption specifications, 70, 72f of fish, 5­8, 6­8f fuel prices value of total reported fishery as major cost factor, 13­14f, production, 9­12 22­23, 22t economic rents, 29­31, 30b, 52, 57­59, net economic loss estimates, 35, 40n3 58­59f results of study affected by, elasticity of demand with respect to 45­46, 46t biomass, 39, 74f, 75 employment issues, 15­18f, 35­36 GDP (gross domestic product), equilibrium diagram or sustainable fisheries contribution to, fisheries model, 63f 44­45, 55 equity, as axis of fisheries reform, global marine fisheries, xvii­xxiii 53­54 aggregate model for. See aggregate Europe/European Union (EU) model cost factors derived from, 35, 36, biological and economic health 40n1, 40n6 issues, xxi­xxii, 2­3, 44­45 demand for fish in, 8 current state and trends. See current employment in fisheries, 16f, 17f state and trends in fisheries fishing fleet, 19f, 78t economic performance. See ex-vessel prices, 9 economic performance of exploitable aggregate biomass fisheries Fox model of, 31­32, 32f, 41, 42, losses, estimating. See net economic 47­48f, 62 loss, estimating Schaefer model of, 31­32, 32f, 62 purpose and outcomes of study, 1­2 export prices, 10­12, 10f reform of. See reform of global marine fisheries FAO. See Food and Agriculture tenure issues, xxii­xxiii, 52, 55 Organization global population growth Faroe Islands, 81t employment in fisheries and, 15f fisheries. See global marine fisheries fish production and, 6­7, 7f fishing capacity, 21­22 global trade in and consumption of fishing effort, 18­19 fish, 5­8, 6­8f fishing fleet, 18­22, 19­21f, 78t global warming, impact of, 5, 45 fishing mortality, 18 governance issue, reform of global fixed cost ratio, 39­40 marine fisheries as, 53 Food and Agriculture Organization gross domestic product (GDP), (FAO) fisheries contribution to, Code of Conduct for Responsible 44­45, 55 Fisheries, 56n1 common methodology, series of Iceland, 40n1, 52, 78t, 80t, 84t studies using, 48n1, 80­81t illegal fishing, 25­26 net operating loss estimates, 27, 28b ILO (International Labour reports of, xvii, 41 Organization), 26n4 food prices, 14f, 22­23, 22t, 45­46, 46t income from fishing, 15­18, 17­18f, Fox model 35­36 INDEX 97 India, 14, 16, 35, 40n6 Namibia, 80t individual transferable quotas (ITQs), national capital, fish wealth as, xiii, 39, 43t, 45b 54­55 intangible values of global fisheries, net economic benefits, 29­31, 30b, 52, 12 57­59, 58­59f International Labour Organization net economic loss, estimating, xix, (ILO), 26n4 27­40 ITQs (individual transferable quotas), aggregate model for. See aggregate xiii, 39, 43t, 45b model broader economy, links to, 44­46, Japan, 40n1, 78t, 81t 54­55 comparison of different study Korea, Republic of, 40n1, 78t results, 42­43, 43t, 80­81t confidence intervals, 47, 48t, 69­75 labor issues, 15­18f, 35­36 fuel and food prices, effects of, large predatory fishes, decline in 45­46, 46t biomass of, 5 methodologies for, 27­29, 28b Lloyd's register, 20 overfishing, 30b, 44­45 logistic model, Monte Carlo stochastic projected rent loss (1974­2007), specifications, 70, 71f 82­83t losses, estimating. See net economic results, 41­48 loss, estimating sensitivity analysis, 46­48, 47­48f lower-value species, increasing reliance stochastic distributions, 47­48, on, 4­5 69­75, 70t, 71­72f, 72t, 74f terminological issues, 29­31, 30b management of fisheries, costs of, New Zealand, 52, 55, 84t 24­26, 40 North and Central American fisheries, marine fisheries. See global marine 16f, 17f, 19f fisheries Norway, 40n1, 78t, 81t maximum economic yield (MEY), 30b, 31, 53 Oceania, 16f, 17f, 19f maximum sustainable rents (MSR), 27, overfishing, 30b, 44­45 31, 42 ownership of global marine fisheries, maximum sustainable yield (MSY), xxii­xxiii, 52, 55 27, 30b, 33­34, 45­46, 54, 73, 74f, 78t pelagic stock, 3­4, 4f, 34 MEY (maximum economic yield), 30b, Peru, 44, 45b, 80t 31, 53 political economy of fisheries reform, model. See aggregate model 53­54 Monte Carlo stochastic specifications, population growth 69­70, 71­72f employment in fisheries and, 15f MSR (maximum sustainable rents), 27, fish production and, 6­7, 7f 31, 42 pricing of fish MSY (maximum sustainable yield), in aggregate model, 74f, 75 27, 30b, 33­34, 45­46, 54, 73, ex-vessel prices, 9 74f, 78t export prices, 10­12, 10f multiplier effects, 44­45, 45t food prices generally, 14f, 22­23, 22t, Myanmar, 17 45­46, 46t 98 INDEX fuel prices affecting. See fuel prices Schaefer model of exploitable U.S. real price indexes (1947­2006), aggregate biomass, 11f 31­32, 32f, 62 production cost factors, 37 schooling parameter, 38, 74f, 75, 79t productivity, 12 sensitivity analysis, 46­48, 47­48f in aggregate model, 34­35, 74f, 75 Shetland Islands, 55 as axis of fisheries reform, 53­54 small-scale fisheries employment and labor productivity, advantages of, xxii 15­18, 18f capital costs, 40n6 of fishing fleet, 21­22, 21f consumption statistics and, 7 fuel consumption and, 13­14f cost factors for, 35, 36 technology and, 14 income of laborers in, 16, 17 PROFISH partnership, World Bank profitability of, 37 common methodology, series of subsidies to, 24 studies using, 48n1, 80­81t underestimation of production in, net economic loss estimates 34, 40n5 workshop, 27­29 unregistered vessels, 20, 25 profits of world fisheries, estimating, South American fisheries, 8, 16f, 17f, 37­38, 38t, 74f, 75 19f stagnation/deterioration of resources, rebuilding global fish stocks, 2­5, 3b 50­55 stochastic distributions, 47­48, 69­75, reform of global marine fisheries, 70t, 71­72f, 72t, 74f xx­xxiii, 49­56 sub-Saharan Africa, demand for fish axes of sustainability, productivity, in, 8 and equity, 53­54 subsidies, 23­24, 23b, 24t, 40, 50­51 biological and economic health sustainability, biological, xxi­xxii, 2­3, issues, xxi­xxii, 2­3, 44­45 44­45 costs of, xx­xxi, 51­52 sustainability, economic. See economic economic advantages of, 49­50 performance of fisheries; net as governance issue, 53 economic loss, estimating harvesting rights versus benefit sustainable fisheries, creating. See rights, 55 reform of global marine means of, xx fisheries national capital, raising awareness sustainable fisheries model of fish wealth as, 54­55 (equilibrium diagram), 63f political economy of, 53­54 Sweden, 81t rebuilding global fish stocks, 50­55 System of National Accounts, 54 recommendations regarding, xxiii socioeconomic dimensions of, 54 technology and productivity, 14 subsidies, 50­51 tenure over global marine fisheries, tenure issues, xxii­xxiii, 52, 55 xxii­xxiii, 52, 55 rents, 29­31, 30b, 52, 57­59, 58­59f Thailand, 17, 80t Republic of Korea, 40n1, 78t total reported fishery production, 5, resource reduction costs, 58 9­12 rights to fisheries, xxii­xxiii, 52, 55 trade in fish, 5­8, 6­8f rise in sea level, impact of, 5 tragedy of the commons, 38 Russian Federation, 40n1, 78t trash fish used in aquaculture feed, 4 INDEX 99 trends in fisheries. See current state and value of total reported fishery trends in fisheries production, 9­12 Vietnam, 17, 80t undecked/decked fishing fleet, 19­20, 19f Work in Fishing Convention (ILO), United Kingdom 26n4 Faroe Islands, 81t World Bank Shetland Islands, 55 deficit of information on fisheries United States noted by, 27, 55 Alaska, downstream efficiency gains PROFISH partnership in, 44, 45b common methodology, series of broader economy, links of fisheries studies using, 48n1, 80­81t to, 44 net economic loss estimates capital costs, 37 workshop, 27­29 potential economic benefits from World Development Report 2008 fisheries in, 43 on subsidies, 51 price of fish in, 11­12, 11f world issues. See entries at global selected case study results, 80­81t World Summit on Sustainable on subsidies, 24 Development (Johannesburg, unreported/unregistered fishing, 2002), 1, 53, 54 25­26 World Trade Organization (WTO) on upstream economic links, 44­45 subsidies, 23b, 24 100 INDEX ECO-AUDIT Environmental Benefits Statement The World Bank is committed to preserving Saved: endangered forests and natural resources. The · 4 trees Office of the Publisher has chosen to print · 3 million British The Sunken Billions: The Economic Justifi- thermal units cation for Fisheries Reform on recycled · 348 pounds of net paper with 30 percent post-consumer waste, greenhouse gases in accordance with the recommended stan- · 1,444 gallons of waste dards for paper usage set by the Green Press water Initiative, a nonprofit program supporting · 185 pounds of solid publishers in using fiber that is not sourced waste from endangered forests. For more informa- tion, visit www.greenpressinitiative.org. The Sunken Billions: The Economic Justification for Fisheries Reform shows the difference between the potential and actual net economic benefits from marine fisheries is about $50 billion per year, or some $2 trillion over the last three decades. If fish stocks were rebuilt, the current marine catch could be achieved with approximately half of the current global fishing effort. This illustrates the massive overcapacity of the global fleet. The excess competition for the limited fish resources results in declining productivity, economic inefficiency, and depressed fisher incomes. The focus on the deteriorating biological health of world fisheries has tended to obscure their equally critical economic health. Achieving sustainable fisheries presents challenges not only of biology and ecology, but also of managing political and economic processes and replacing pernicious incentives with those that foster improved governance and responsible stewardship. Improved governance of marine fisheries could regain a substantial part of this annual economic loss and contribute to economic growth. Fisheries governance reform is a long- term process requiring political will and consensus vision, built through broad stakeholder dialogue. Reforms will require investment in good governance, including strengthening marine tenure systems and reducing illegal fishing and harmful subsidies. Realizing the potential economic benefits of fisheries means reducing fishing effort and capacity. To offset the associated social adjustment costs, successful reforms should provide for social safety nets and alternative economic opportunities for affected communities. ISBN 978-0-8213-7790-1 SKU 17790