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 D I S C U S S I O N PA P E R 5 2 68710 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs): A Case Study of the Blue Swimming Crab Fisheries in Indonesia and Philippines MAY 2012 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 D I S C U S S I O N PA P E R 5 2 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs): A Case Study of the Blue Swimming Crab Fisheries in Indonesia and Philippines © 2012 International Bank for Reconstruction and Development / International Development Association or The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The �ndings, interpretations, and conclu- sions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. 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Cover Photos: Finnbogi Alfredsson CONTENTS III TABLE OF CONTENTS List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix About the Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi Acronyms and Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1: Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2: Purpose of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.3: Structure of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Chapter 2: Overview of FPIs and Studied Fisheries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1: Fishery Performance Indicators (FPIs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2: Case Study Fisheries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Chapter 3: FPIs’ Application on BSC Fisheries— Output Results . . . . . . . . . . . . . . . . . . . . . 15 3.1: Ecological Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2: Harvest Sector Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.3: Post-Harvest Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Chapter 4: FPIs’ Application on BSC Fisheries— Inputs Results. . . . . . . . . . . . . . . . . . . . . . 35 4.1: Macro Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4.2: Property Rights and Responsibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.3: Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.4: Post-Harvest Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Chapter 5: Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.1: Regarding the Studied Fisheries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.2: Regarding the Fishery Performance Indicators (FPIs). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Appendix A: Fishery Performance Indicators—Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Appendix B: Suggested Revision and Additional Indicators . . . . . . . . . . . . . . . . . . . . . . . . 75 Appendix C: Milestones of Fishery Performance Indicators (FPIs). . . . . . . . . . . . . . . . . . . . 93 Appendix D: FPIs Application—Output Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Appendix E: FPIs Application—Input Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 LI S T O F F I G U R E S V LIST OF FIGURES Figure 2.1: Blue Swimming Crab Landings in Indonesia (1970–2008) . . . . . . . . . . . . . . . . . . . . . . . . . 8 Figure 2.2: Major Blue Swimming Crab Catching Areas in Indonesia (1990–2006) . . . . . . . . . . . . . . . . . . 9 Figure 2.3: Value Chain and Stakeholders Involved in BSC Fisheries in Indonesia . . . . . . . . . . . . . . . . . 10 Figure 2.4: Landings of BSCs in the Philippines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Figure 2.5: Supply Chain in the Philippines’ Blue Swimming Crab Industry . . . . . . . . . . . . . . . . . . . . . 13 Figure 3.1: Fish Stock Health and Environmental Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Figure 3.2: Ecologically Sustainable Fisheries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Figure 3.3: Harvest Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Figure 3.4: Summary of Harvest Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Figure 3.5: Asset Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Figure 3.6: Summary of Asset Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Figure 3.7: Risk Exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Figure 3.8: Summary of Risks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Figure 3.9: Boat Owners/Captain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Figure 3.10: Summary of Boat Owners/Captain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Figure 3.11: Crew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Figure 3.12: Summary of Crew Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Figure 3.13: Summary of Harvest Sector Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Figure 3.14: Market Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Figure 3.15: Summary of Market Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Figure 3.16: Processing and Support Industry Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Figure 3.17: Summary of Processing and Support Industry Performance. . . . . . . . . . . . . . . . . . . . . . 28 Figure 3.18: Post-Harvest Asset Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Figure 3.19: Summary of Post-Harvest Asset Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Figure 3.20: Processing Owners and Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Figure 3.21: Summary of Processing Owners/Managers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 VI LIST O F FIGUR ES Figure 3.22: Processing Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Figure 3.23: Summary of Processing Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Figure 3.24: Summary of Post-Harvest Sector Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Figure 4.1: General Environmental Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Figure 4.2: Country-Level Governance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Figure 4.3: Economic Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Figure 4.4: Exogenous Environmental Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Figure 4.5: Summary of Macro Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Figure 4.6: Asset Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 4.7: Summary of Asset Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 4.8: Harvest Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Figure 4.9: Summary of Harvest Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Figure 4.10: Collective Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Figure 4.11: Summary of Collective Actions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Figure 4.12: Summary of Property Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Figure 4.13: Management Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Figure 4.14: Summary of Management Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Figure 4.15: Data Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Figure 4.16: Participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Figure 4.17: Summary of Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Figure 4.18: Market and Market Institution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Figure 4.19: Summary of Market and Market Institution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Figure 4.20: Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Figure 4.21: Summary of Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Figure 4.22: Summary of Post-Harvest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Figure 5.1: Summary of FPIs’ Output—Measuring Wealth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Figure 5.2: Summary of FPIs’ Input—Enabling Wealth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) LI S T O F TA B L E S V II LIST OF TABLES Table 2.1: Prototype Fishery Performance Indicators—Outputs (Measuring Success) . . . . . . . . . . . . . . . . 4 Table 2.2: Prototype Fishery Performance Indicators—Inputs (Enabling Factors) . . . . . . . . . . . . . . . . . . . 5 Table 2.3: Questions FPIs Attempt to Answer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Table 2.4: Immature BSC Catch Rate for Different Gears . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Table 3.1: Score System for Indicators of Ecological Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Table 3.2: Score System for Indicators of Harvest Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 3.3: Score System for Indicators of Asset Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Table 3.4: Score System for Indicators of Risk Exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Table 3.5: Score System for Indicators of Boat Owners/Captain . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Table 3.6: Score System for Indicators of Crew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Table 3.7: Score System for Indicators of Market Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Table 3.8: Score System for Indicators of Processing and Support Industry Performance . . . . . . . . . . . . . 28 Table 3.9: Score System for Post-Harvest Asset Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Table 3.10: Score System for Processing Owners/Managers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Table 3.11: Score System for Processing Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Table 3.12: Summary of FPIs’ Output Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Table 4.1: Score System for General Environmental Performance . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Table 4.2: Score System for Governance—Country Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Table 4.3: Index of Economic Freedom (IEF), 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Table 4.4: Score System for Economic Conditions—Country Level . . . . . . . . . . . . . . . . . . . . . . . . . 37 Table 4.5: Score System for Exogenous Environmental Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Table 4.6: Score System for Access Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Table 4.7: Score System for Harvest Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Table 4.8: Score System for Collective Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Table 4.9: Score System for Management Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Table 4.10: Score System for Data Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSS ION PA PER 52 VIII LIST OF TA B LES Table 4.11: Score System for Participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Table 4.12: Score System for Market and Market Institution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Table 4.13: Score System for Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Table 4.14: Summary of FPIs’ Output Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) ACK N O W L E D G ME NT S IX ACKNOWLEDGMENTS This study was written by Jingjie Chu (Natural Resource Economist, Agriculture and Rural Development Department, World Bank), James L. Anderson (Fisheries and Aquaculture Adviser, Agriculture and Rural Development Department, World Bank), and Christopher M. Anderson (Associate Professor, University of Washington). James and Christopher developed the proto- type method and manual of the Fishery Performance Indicators (FPIs) sponsored by ALLFISH (Public Private Partnership of PROFISH). Jingjie Chu produced the FPIs survey design, completed the manual revision, and managed the implementation. This study was built on the results of a survey applying FPIs to blue swimming crab �sheries in Indonesia and the Philippines which was conducted by Dessy Anggraeni (Sustainable Fisheries Partnership) and Jimely Flores (Sustainable Fisheries Partnership), respectively. ALLFISH �nancially supported the survey. Stetson Tinkham (International Coalition of Fisheries Associations) and Purbasari (Sari) Surjadi (Sustainable Fisheries Partnership) helped the coordination. Additionally, Finnbogi Alfredsson, as a �shery specialist when working in PROFISH, applied FPIs to the Icelandic lobster �shery as a comparison benchmark. The authors are grateful for the support and clear guidance from Juergen Voegele (director, Agriculture and Rural Development Department [ARD], World Bank) and Mark Cackler (sector manager, ARD, World Bank). The authors wish to thank the peer reviewers for their contributions and also the participants of the Project Concept Note Review Meeting and Decision Meeting for their constructive and insightful suggestions and comments, including Marea Eleni Hatziolos (senior environmental spe- cialist, East Asia Social, Environment and Rural [EASER], World Bank), John Virdin (senior natural resource management specialist, Africa Environment and Natural Resource Management [AFTEN], World Bank), Michael Arbuckle (senior �sheries specialist, ARD, World Bank), Grahame Dixie (senior agribusiness specialist, ARD, World Bank), Andrew Kaelin (consultant, AIS Development LLC), Xavier Vincent (senior �sheries specialist, AFTEN, World Bank), Oleg Martens (senior �sheries spe- cialist, World Wildlife Fund [WWF]), Tim Bostock (senior �sheries specialist, ARD, World Bank), Randall Brummett (senior aquaculture specialist), Kieran Kelleher (consultant, ARD, World Bank), James Smith (senior livestock specialist, ARD, World Bank), and Irina Gabrial (operations specialist, ARD, World Bank). The authors wish to thank Felicitas Doroteo-Gomez (pro- gram assistant, ARD, World Bank) for her logistic support. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 ABO U T T H E A U T H ORS XI ABOUT THE AUTHORS Jingjie Chu is currently a natural resource economist in the Africa Environment and Natural Resource Management (AFTEN) unit at the World Bank. This study was mainly done when she was a young professional in the Agriculture and Rural Development Department (ARD) of the World Bank. She joined the World Bank in 2009 after receiving her Ph.D. in Environmental and Natural Resource Economics from the University of Rhode Island. She has been involved in the Fishery Performance Indicators (FPIs) development and implementation, and economic analysis for other �sheries projects in Africa and East Asia. James L. Anderson is the World Bank’s advisor in �sheries and aquaculture and leader of the Bank’s Global Program on Fisheries (PROFISH). He is involved with numerous projects related to �sheries and aquaculture management, seafood mar- kets, and international trade. Recent projects have focused on global salmon, tuna, scallop, oyster, and shrimp markets and management. In 2003, his book entitled The International Seafood Trade was published. In 2007, he coauthored The Great Salmon Run: Competition between Wild and Farmed Salmon with Gunnar Knapp and Cathy Roheim. He was the editor of Marine Resource Economics, the leading international journal in the �eld for over 10 years. He has served on three National Research Council committees related to aquaculture and cochaired the committee on the introduction of nonnative Asian oysters. He earned his Ph.D. in Agricultural and Resource Economics from the University of California at Davis. Chris M. Anderson is currently an associate professor in the School of Aquatic and Fishery Sciences at the University of Washington. His research uses game theory, behavioral economics, experimental economics, and applied econometrics to understand the individual decisions underlying natural resource use, and to design methods and institutions for managing them. His projects include designing auctions for �shing quota in New Zealand and oil tract leases in the Gulf of Mexico; developing and testing mechanisms for the provision of ecosystem service public goods; and studying alternative rules of trade that better facilitate price discovery in transferable �shing quota systems. He is currently building a new dynamic common pool resource environment for evaluating catch share �shery management, and developing a rapid assessment instrument for assessing wealth generation in �shery-dependent communities. He earned a bachelor degree in Applied Math and Economics at Brown University, and a Ph.D. in Social Science at the California Institute of Technology. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 ACR O N Y MS A N D A BBRE VIAT IONS X III ACRONYMS AND ABBREVIATIONS AFTEN Africa Environment and Natural Resource ICFA International Coalition of Fisheries Management, the World Bank Group Associations APRI Asosiasi Pengelolaan Rajungan Indonesia IEF Index of Economic Freedom (Indonesia Blue Swimming Crab Processing Association) ITQ Individual Transferable Quota ARD Agriculture and Rural Development LGU Local Government Unit Department, the World Bank Group MEY Maximum Economic Yield ATC Airtight container MMAF Ministry of Marine Affairs and Fisheries, BFAR Department of Agriculture–Bureau of Fisheries Indonesia and Aquatic Resources, the Philippines MSC Marine Stewardship Council BSC Blue Swimming Crab MSY Maximum Sustainable Yield CPUE Catch per Unit of Effort NFI National Fisheries Institute EASER East Asia-Social, Environment, and Rural NMFS National Marine Fisheries Services EPI Environmental Performance Index NIACDEV Northern Iloilo Alliance for Community FAO Food and Agriculture Organization of the Development United Nations PROFISH Global Program on Fisheries, the World Bank FIP Fisheries Improvement Project Group FPIs Fishery Performance Indicators SFP Sustainable Fisheries Partnership JICA Japan International Cooperation Agency WGI Worldwide Governance Indicators AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSS ION PA PER 52 EX E C U T I V E S U MMARY XV EXECUTIVE SUMMARY Currently, the World Bank has about $600 million invested in its �shery-related portfolio. It is anticipated that the commitment to �sheries and aquaculture will increase considerably in the next few years. However, the task team leaders have been struggling to identify an adequate monitoring and evaluation tool. None of the proposed indicators capture the full effective- ness of �shery management, and none help the decision makers understand causal links. Some indicators primarily focus on ecological sustainability, such as measuring the status of �sh stock, while others narrowly focus on the economic aspects, such as net economic bene�t or �shery revenue. Additionally, the cost of collecting detailed biological or economic data can be prohibitive or simply not feasible in some developing countries. There is an urgent need to develop indicators that can measure the success of �sheries management systems in achieving the “triple bottom line� of environmental, economic, and social sustainability. The measurement approach should also help decision makers understand the linkage between success and management inputs, infrastructure, enforcement, the market- ing system, and exogenous factors. Furthermore, the indicators must be relevant, accurate, quanti�able, understandable, replicable, comparable between developed and developing regions, and readily available using current expertise and data. The new Fishery Performance Indicators (FPIs) aspire to meet these conditions (Anderson and Anderson 2010). The FPIs are a new set of indicators for evaluating and comparing the world’s �sheries management systems based on their success in being ecologically sustainable, socially acceptable, community enriching, and generating sustainable resource rents or pro�ts. The FPIs fall into two categories. The �rst category is indicators of outputs that identify and measure key factors that reflect success or failure in achieving the triple bottom line from �sheries. The second consists of input factors that enable or contrib- ute to the process of developing sustainable and wealth-creating �sheries. FPIs are designed to be clearly de�ned and easy to apply for a knowledgeable expert. The FPIs are intended to be completed within days. This rapid assessment approach can give a clear picture of the ecological, social, and economic situation associated with the �sheries management system. The objectives of this report are to: a. Field-test the FPIs as an evaluation tool for the Philippine and Indonesian blue swimming crab �sheries. b. Compare the results with those for the Icelandic lobster �shery. This provides an aspirational target for improvement as well as an additional test of the FPIs. c. Evaluate the limitations and strengths in FPIs based on the application above; feedback of the workshop conducted in May 2011; and input from over 30 researchers, government agencies, the private sector, and nongovernmental organizations (NGOs) from around the world. Special attention is given to application in data-poor situations. d. Provide explicit revisions to the FPIs based on (c) as a �nal step prior to broader application. The results of the �eld test indicate that the FPIs represent a useful and powerful tool for �shery project monitoring and evaluation. The experience indicates that application in the Philippines, Indonesia, and Iceland can be completed in about 2 weeks at relatively low cost. Despite the ease of application, the quality of the data is high, yielding a good snapshot of the biological, economic, and community conditions associated with the corresponding �shery. Notably, the indicators capture key features of success: Fish Stock Health and Environmental Performance Harvest Performance Ef�ciency Harvest Asset Performance (Vessels, etc.) AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 XV I EX EC UTIV E S UM M A RY Risk Exposure Conditions Facing Owners, Permit Holders, and Captains Conditions Facing the Crew Market Performance Processing and Support Industry Performance Post-Harvest Asset Performance (Processing Plants, etc.) Conditions Facing Processing Owners and Managers Conditions Facing Processing Workers The indicators also capture essential features of the enabling input factors: General Environmental Conditions Exogenous Environmental Factors (especially pollution and climate change–related factors) National Governance Conditions National Economic Conditions Characteristics of Fishing Access Rights Characteristics of Fishing Harvest Rights Participation in Co-Management Management Inputs (e.g., expenditure and enforcement) Data Collection and Analysis Participation by Stakeholders Markets and Market Institutions Infrastructure Although the application of the FPIs and the feedback from the research workshop in May 2011 was very positive, there were several improvements to the scaling of the indicators and a few omissions that need to be revised for scaled-up application. The suggested revisions in the scaling are identi�ed in the text, and some speci�c recommendation for additions are found in Appendix B. Overall, once the revisions have been incorporated the FPIs are ready to be scaled up as a tool for all the �shery projects in the World Bank, as a management assessment tool or a tool to evaluate investment opportunity. A detailed FPI assessment for each targeted country will assist management decisions for all the target �shery projects regardless of their implementation status. For projects that are in the planning stage, the output will help identify the strengths and weaknesses of the �sheries and thus enable the identi�cation of evidence-based policy suggestions. For projects under implementation, the output will help measure their effectiveness in improving �shery performance. The Bank is moving to enhance its activity related to the oceans, and the FPIs will have great value in identifying key target �sheries and measuring progress. At maturity, the FPIs could be implemented and accessed via a dashboard containing hun- dreds of �sheries, with data collected at regular intervals to monitor sustainable wealth-creating �sheries within and across management systems. The idea, logic, and design of the indicators can help develop a broadened set of indicators that can be applied to codependent �shery-aquaculture and aquaculture management systems. Above all, the impact of these indicators is potentially transformative. They will be effective levers to promote change but also suggest what changes should be made to result in sustainable improvement in the �shery, the economic conditions, and community status. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 1 — I N T R ODUCT ION 1 Chapter 1: INTRODUCTION 1.1 BACKGROUND evaluating and comparing the world’s �sheries management In 2005, the World Bank formally reengaged in the �sheries systems based on their success in being ecologically sustain- sector, with the establishment of a multidonor trust fund, able, socially acceptable, community enriching, and generat- Global Program on Fisheries (PROFISH), to provide seed capi- ing sustainable resource rents or pro�ts. This triple bottom tal for a new portfolio of investments that would focus on as- line measurement metrics ensure the �shery management sisting countries to reform �sheries governance. Over the sub- system is not biased toward one aspect and neglects the sequent years, a number of new investments were launched other as these three dimensions are critical for achieve long- with PROFISH’s support, particularly in Africa and East Asia. term sustainability. The FPIs integrate ecological, social, and Currently, the Bank’s portfolio related to �sheries has grown to economic dimensions to measure the output of the �sheries over $600 million and is expected to continue to grow rapidly. (identifying where wealth accumulates within the value chain) and input factors (assessing the levels of factors contributing Building on these experiences and continued interest from the to the sustainable wealth creation). They are designed not global community, in 2011 the World Bank launched a Strategy only as a basic measurement tool, but also as a framework Vision for Fisheries and Aquaculture articulated by PROFISH for identifying what policies and interventions are likely to to guide further implementation of these investments and ex- have the greatest impact. This work was originally supported panded support for �sheries governance reforms and sustain- by ALLFISH (a public private partnership initiative the World able �sheries and aquaculture management in client countries Bank established and that is managed by the International (PROFISH 2011). Following this, a note on the application of Coalition of Fisheries Associations-ICFA). this strategy to the Africa region was developed to meet the demand of the growing portfolio in the region (AFTEN 2011). 1.2 PURPOSE OF THE STUDY There is a strong need for the Bank and its partners to take To further develop and �nalize the FPIs for scaling up to the a global view of the success of these investments. For this Bank’s entire �sheries portfolio, a number of speci�c pilots reason, the Bank has supported work to de�ne a global set and case studies have been conducted. This report provides of Fishery Performance Indicators (FPIs). The goal is to de- an overview of the FPIs, and a summary of two case studies velop indicators that can measure the success of �sheries in its application, the blue swimming crab (BSC) �sheries in management systems in achieving the “triple bottom line� Indonesia and the Philippines. A comparative analysis with of environmental, economic, and social sustainability—a set an Icelandic lobster �shery is conducted as a benchmark, as of core indicators that can be applied across a diverse set the Icelandic lobster �shery is also export oriented and has of �sheries to evaluate and monitor the performance. The been recognized as a well-managed �shery. measurement approach should also help decision makers understand the linkage between success and management The objective of this study is to: inputs, infrastructure, enforcement, the marketing system, Field-test the application of FPIs for the Philippine and and exogenous factors. Furthermore, the indicators must be Indonesian blue swimming crab �sheries to evaluate relevant, accurate, quanti�able, understandable, replicable, the applicability of the FPIs for developing countries in comparable between developed and developing regions, and order to �nalize the FPIs for scaling up. readily available using current expertise and data. Compare the results with results for the Icelandic lobster The new FPIs aspire to meet these conditions (Anderson �shery. This provides an aspirational target for improve- and Anderson 2010). The FPIs are a new set of indicators for ment as well as providing an additional test of the FPIs. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 2 CH A PTER 1 — INTR OD UC TION Evaluate the limitations and strengths in FPIs, based Chapter 3 presents the results for FPIs that measure on the application above, feedback of the workshop the success (“Outputs�) in achieving the “triple conducted in May 2011, and input from over 30 bottom line� of environmental, social, and economic researchers, government agencies, the private sector, sustainability and provides a critical evaluation of and NGOs from around the world. Special attention is strengths, weaknesses, and omissions of the current given to application in data-poor situations. FPIs design. Provide explicit revisions to the FPIs based on the Chapter 4 presents the results for FPIs that mea- above step as a �nal step prior to broader application. sure factors (“Inputs�) that enable (or undermine) the likelihood that the triple bottom line will be An additional bene�t, but not the central goal of this study, achieved and provides a critical evaluation of is to provide useful information for conservation and man- strengths, weaknesses, and omissions of the agement of the blue swimming crab �sheries in these two current FPIs design. countries by identifying the strengths and weaknesses of Chapter 5 summarizes the results and draws conclu- current �shery management in terms of wealth generation sions about the applicability of FPIs and next steps. as reflected in economic, environmental, and community Five appendices provide supplementary informa- conditions. tion. Appendix A provides detailed explanation of the rationale and measurement for each indicator. 1.3 STRUCTURE OF THE STUDY Appendix B lists additional suggested indicators The study is organized as follows: based on the case studies. Appendix C lists the participants who have attended the workshops in Chapter 2 provides a brief introduction of Fishery London and Hawaii. Appendixes D and E illustrate Performance Indicators (FPIs) and the blue swim- the FPIs’ output and input results for the studied ming �sheries in Indonesia and the Philippines. �sheries, respectively. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES 3 Chapter 2: OVERVIEW OF FPIs AND STUDIED FISHERIES 2.1 FISHERY PERFORMANCE INDICATORS (FPIs) Market Performance Fishery Performance Indicators (FPIs) make up a multidi- Processing and Support Industry Performance mensional index used to provide a rapid assessment of the Post-Harvest Asset Performance (Processing Plants, successes and failures of a particular �shery and manage- etc.) ment system with regard to sustainable wealth generation Conditions Facing Processing Owners and Managers (Anderson and Anderson 2010). The rationale behind the FPI Conditions Facing Processing Workers is that a �sheries ecological sustainability is a necessary but not suf�cient condition to ensure the maximum economic There are 46 input factors that enable (or undermine) the suc- yield. The FPIs are designed to evaluate and compare the cess of a �shery to achieve the triple bottom line (table 2.2), world’s �sheries management systems based on their suc- including the following: cess in being ecologically sustainable, socially acceptable, community enriching, and generating sustainable resource General Environmental Conditions rents or pro�ts. This triple-bottom measurement metrics en- Exogenous Environmental Factors (especially pollution sures the �shery management system is not biased toward and climate change–related factors) one aspect and neglects the others as all three dimensions National Governance Conditions are critical to achieve long-term sustainability. National Economic Conditions Characteristics of Fishing Access Rights The FPIs fall into two categories. The �rst category is indica- Characteristics of Fishing Harvest Rights tors of outputs that identify and measure key factors that reflect success or failure in achieving the triple bottom line Participation in Comanagement from the �sheries. The second consists of input factors that Management Inputs (e.g., expenditure and enable or contribute to the process of developing sustainable enforcement) wealth-creating �sheries. FPIs are designed to be clearly de- Data Collection and Analysis �ned and easy to apply for a knowledgeable expert. The FPIs Participation by Stakeholders are intended to be completed within days. This rapid assess- Markets and Market Institutions ment approach can give a clear picture about the ecological, Infrastructure social, and economic situations associated with the �sheries management system. All of the indicators are coded in a �ve-point scale, with the bins generally chosen to reflect the quintiles of performance There are 62 output indicators that capture key features of on the metric globally. Output indicators scored below 3.5 success (table 2.1), including the following: have substantial room for improvement. Output indicators Fish Stock Health and Environmental Performance scored below 2 (in the bottom two quintiles) are considered Harvest Performance Ef�ciency to require urgent attention. Input factors are not necessarily monotonic (a higher score is not necessarily better). Harvest Asset Performance (Vessels, etc.) Risk Exposure A few distinguished features of FPIs include the following: Conditions Facing Owners, Permit Holders, and FPIs integrate governance, economic, and social dimensions Captains with ecological measurements to evaluate a �shery at a Conditions Facing the Crew given point in time; FPIs evaluate the whole value chain, not AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 4 C H A PTER 2 — OVERVIEW OF FPIs A ND S TUD IED FIS H ER IES TABLE 2.1: Prototype Fishery Performance Indicators—Outputs (Measuring Success) COMPONENT DIMENSION MEASURE CATEGORY Ecologically Sustainable Fisheries Fish Stock Health and Proportion of Harvest with a Third-Party Certi�cation Ecology Environmental Performance Fish Stock Sustainability Index (NMFS) Ecology Percentage of Stocks Over�shed Ecology Nonlandings Mortality Ecology Harvest Sector Performance Harvest Performance Landings Level Economics Excess Capacity Economics Season Length Economics Harvest Asset Performance Ratio of Asset Value to Gross Earnings Economics Total Revenue versus Historic High Economics Asset (Permit, Quota) Value versus Historic High Economics Borrowing Rate Relative to Risk-Free Rate Economics Source of Capital Economics Functionality of Harvest Capital Economics Risk Annual Total Revenue Volatility Economics Annual Landings Volatility Economics Intra-annual Landings Volatility Economics Annual Price Volatility Economics Intra-annual Price Volatility Economics Spatial Price Volatility Economics Contestability and Legal Challenges Community Owners, Permit Holders, and Earnings Compared to National Average Earnings Community Captains Fishery Wages Compared to Non�shery Wages Community Education Access Community Access to Health Care Community Social Standing of Boat Owners and Permit Holders Community Proportion of Nonresident Employment Community Crew Earnings Compared to National Average Earnings Community Fishery Wages Compared to Non�shery Wages Community Education Access Community Access to Health Care Community Social Standing of Crew Community Proportion of Nonresident Employment Community Crew Experience Community Age Structure of Harvesters Community Post-Harvest Performance Market Performance Ex-Vessel Price versus Historic High Economics Final Market Use Economics International Trade Economics Final Market Wealth Economics Wholesale Price Relative to Similar Products Economics Capacity of Firms to Export to the United States and European Union Economics Ex-Vessel to Wholesale Marketing Margins Economics (Continued) EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES 5 TABLE 2.1: Prototype Fishery Performance Indicators—Outputs (Measuring Success) (Continued) COMPONENT DIMENSION MEASURE CATEGORY Processing and Support Yield of Processed Product Economics Industry Performance Capacity Utilization Rate Economics Product Improvement Economics Regional Support Businesses Economics Time to Repair Economics Post-Harvest Asset Borrowing Rate Relative to Risk-Free Rate Economics Performance Source of Capital Economics Age of Facilities Economics Processing Owners and Earnings Compared to National Average Earnings Community Managers Manager Wages Compared to Non�shery Wages Community Education Access Community Access to Health Care Community Social Standing of Processing Managers Community Nonresident Ownership of Processing Capacity Community Processing Workers Earnings Compared to National Average Earnings Community Worker Wages Compared to Non�shery Wages Community Education Access Community Access to Health Care Community Social Standing of Processing Workers Community Proportion of Nonresident Employment Community Worker Experience Community Source: Anderson and Anderson, 2010, as revised based on comments received at the May 2011 workshop. TABLE 2.2: Prototype Fishery Performance Indicators—Inputs (Enabling Factors) COMPONENT DIMENSION MEASURE Macro Factors General Environmental Environmental Performance Index (EPI) Performance Exogenous Environmental Disease and Pathogens Factors Natural Disasters and Catastrophes Pollution Shocks and Accidents Level of Chronic Pollution (A) Level of Chronic Pollution (B) Governance Governance Indicator—Effectiveness Governance Indicator—Voice and Accountability Economic Condition Index of Economic Freedom Gross Domestic Product (GDP) Per Capita Property Rights and Responsibility Access Proportion of Harvest Managed Under Limited Access Transferability Index Security Index Durability Index Flexibility Index Exclusivity Index (Continued) AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 6 C H A PTER 2 — OVERVIEW OF FPIs A ND S TUD IED FIS H ER IES TABLE 2.2: Prototype Fishery Performance Indicators—Inputs (Enabling Factors) (Continued) COMPONENT DIMENSION MEASURE Harvest Proportion of Harvest Managed with Rights-Based Management Transferability Index Security Index Durability Index Flexibility Index Exclusivity Index Collective Action Participation in Harvester Organizations Harvester Organization Influence on Fishery Management and Access Harvester Organization Influence on Business and Marketing Management Inputs Management Expenditure to Value of Harvest Management Employees to Value of Harvest Management Employees per Permit Holder Research as a Proportion of Fisheries Management Budget Level of Subsidies Data Data Availability Data Analysis Participation Days in Stakeholder Meetings Industry Financial Support for Management Post-Harvest Markets and Market Landings Pricing System Institutions Availability of Ex-Vessel Price and Quantity Information Number of Buyers Degree of Vertical Integration Level of Tariffs Level of Nontariff Barriers Infrastructure International Shipping Service Road Quality Index Technology Adoption Extension Service Reliability of Utilities/Electricity Access to Ice and Refrigeration Source: Anderson and Anderson, 2010, as revised based on comments received at the May 2011 workshop. only the harvest sector, but also the post-harvest sector; with They do not generally require detailed data. They are quanti�- the separation between output result and input factors, FPIs able, understandable, accurate, and feasible. have the potential to provide solid quantitative proof to iden- tify the most influencing factors for performance improve- The case studies in Indonesia and the Philippines for blue ment. This can give a clear direction for policy change and swimming crab �sheries are the �rst to be applied FPIs in the intervention to obtain the most effective results. developing countries.1 Anderson and Anderson (2010) developed a detailed manual 1 Recently, FPIs have been applied to Bangladesh inland �sher- to explain each indicator (see Appendix A). A user-friendly ies, Uganda Nile Perch �sheries, Uganda tilapia �shery, Uganda Excel spreadsheet is designed for local experts to �ll out eas- dagaa �shery, Seychelles artisanal and semi-industrial �sheries, Seychelles sea cucumber and lobster �sheries, Ghana artisanal ily with summarized results and graphs. FPIs are designed to �shery, Peruvian anchovy �shery, and Vietnam coastal �shery in be easy to collect and score across a wide range of �sheries. Thanh Hoa. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES 7 TABLE 2.3: Questions FPIs Attempt to Answer CATEGORY QUESTIONS Outputs Indicators (Measuring Success) 1. What is the �sh stock status (Percentage of stocks over�shed, third-party certi�cation)? 2. What is the harvest sector status (landing level, excess capacity)? 3. How is the harvest sector asset performing (source of capital, borrowing rate, asset value trend)? 4. What are the risks this industry is facing (price, trade, legal, environmental)? 5. What is the status of boat owners/captain (income level, social standing, and proportion of nonresident employment)? 6. What is the status of the crew (income level, social standing, proportion of nonresident employment)? 7. What is the market performance (�nal market, capacity of �rms to export, market margins)? 8. What is the processing industry (yield rate, capacity utilization rate, product improvement, source of capital, borrowing rate)? 9. What is the status of processing facility owners (income level, social standing, and proportion of nonresident employment)? 10. What is the status of processing workers (income level, social standing, proportion of nonresident employment, child labor issue)? Input Factors (Enabling) 1. What is the general macro environment (EPI, governance indicator, GDP per capita, index of economic freedom)? 2. What is the level of the environmental risks (pollution, tsunami, hurricane)? 3. Are property/tenure rights in place and how are they de�ned (security, durability, flexibility, exclusivity)? 4. To what degree can stakeholders participate in the management process (comanagement/corporate management system setup, role of industry organizations)? 5. What are the levels of subsidies? 6. Are the data on �sheries sectors collected and decisions being made based on data analysis? 7. What is the business environment (time to get permit, easiness to renew, cost of compliance, tax level)? 8. What are the market conditions (quality of the product, number of buyers/sellers, supply chain)? 9. What is the relative condition of the infrastructure (transportation, utility, ice supply)? Source: Authors. FPIs have value to many different users. For example, the international trade and have attracted the interest of the private development and aid agencies can use FPIs’ assessment sector in maintaining the sustainability of these �sheries. The results to track the progress of the project and compare the private sector, especially processors, traders, retail, and res- performance before and after projects. The academic and re- taurants, is concerned about the health of the �shery because search community can use FPIs to test different hypotheses it will affect their business and pro�t. A National Fisheries regarding which factors have the most impact. Government Institute (NFI) Crab Council consisting of 12 U.S. importers and �shery managers can use FPIs to identify areas for im- was formed in 2009 to encourage and support sustainability provement. Additionally, an assessment of FPIs for a �shery management in crab-producing countries. They are support- management system will help answer many critical ques- ing local �sheries associations to conduct stock assessment, tions, such as whether a �shery is sustainable, whether the capacity building, and �shermen training. In July 2011, their property rights are well de�ned, and whether the market milestone action was to approve a supply-driven minimum performance is acceptable. Table 2.3 lists more examples. size purchase policy targeting the phaseout of the use of un- dersized crabs in member company products and supporting science-based studies (NFI 2011). The latest initiative is to limit 2.2 CASE STUDY FISHERIES markets for berried female crabs and crab roe which went into This section will give a brief overview of the studied �sher- effect on November 1, 2011 (Fishupdate 2011). This case ies: Blue Swimming Crab (BSC) (Portunus pelagicus) �sher- study was done before the implementation of these policies, ies in Indonesia and the Philippines. The rapid development which provides a good baseline for the situation. In the future, of BSC �sheries in these two countries is mainly driven by applying FPIs again can measure the impact of these policies. increasing demand in the international market, particularly in the United States. Swimming crabmeat was the second largest (by volume) imported crabmeat to the United States, 2.2.1 Indonesian Blue Swimming Crab (BSC) Fishery2 after snow crab, contributing to 23 percent of total volume 2.2.1.1 Landings of crab imports in 2008 (25,652 MT) (NMFS 2010). The main The Indonesian BSCs (Portunus pelagicus), locally known BSC exporting countries are Indonesia (31 percent), China as rajungan, are distributed throughout the Indo-Paci�c. The (24.7 percent), Thailand (13 percent), Vietnam (11 percent), landing levels have experienced an uptrend over the past and the Philippines (7.3 percent) (NMFS 2011). The BSC �sheries in Indonesia and the Philippines are par- 2 This part is based on the report written by Dessy Anggraeni from ticularly interesting because these �sheries are a product of Sustainable Fisheries Partnership (SFP). AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 8 C H A PTER 2 — OVERVIEW OF FPIs A ND S TUD IED FIS H ER IES FIGURE 2.1: Blue Swimming Crab Landings in Indonesia (1970–2008) 40,000 tons 30,000 20,000 10,000 0 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: FAO 2011. 40 years (�gure 2.1). There was a signi�cant drop during Daily �shermen: They start �shing in the evening and the period of 2004 and 2005, but levels soon recovered af- land in the morning. They carry fuel for only one trip ter 2005. In 2008, Indonesia harvested over 34,000 tons of and use gillnet or collapsible traps. The operation area BSCs, contributing to 20 percent of global BSC production is nearby the coastline (onshore). and ranking as the second largest BSC-producing country Babangan �shermen: They usually sail in groups of right after China (FAO 2011). three to �ve for 2 to 7 days. They carry enough fuel and supplies to reach distant �shing grounds. Crab BSCs in Indonesia generally live on sandy or on a combina- traps are commonly used. Cooking facilities and ice tion of sand and mud bottoms, sand flats bordering grassy are also available to boil and store BSCs on the boat. areas, and shallow brackish water to depths beyond 40 me- ters. They are fast growers. Female BSCs may reach sexual In addition, there are some 13,000 pickers working at hun- maturity at 98 mm while the males do at 87 mm (Sulistiono dreds of mini processing plants. Moreover, there are several et al. 2009). In terms of landing areas, North Java has been thousand other direct stakeholders involved as middlemen, the major catching area for BSCs in Indonesia, contributing operators of the miniplants where initial processing is carried to about 28 percent of total production in the period from out, and the �nal processors/packagers who export the prod- 1990 to 2006, followed by East Sumatra (21 percent), South ucts. There are at least 28 crab processors and exporters Sulawesi (21 percent), and Malacca Strait (14 percent) operating in Indonesia. (�gure 2.2). 2.2.1.3 Processing 2.2.1.2 Stakeholder Involvement in the Fishery Most BSCs caught are processed into frozen, canned, and In the BSC �shery value chain, six stakeholder groups are pasteurized crabmeat in miniplants. In the past, miniplants involved, including �shermen, collectors/middlemen (ba- (picking plants) normally got �nancial support from the kul), miniplants/peelers, processors/exporters, distributors/ processor/exporter to run the business. All the facility and central market, and retail/supermarkets/seafood restaurants equipment were supplied by a speci�c processor/exporter. In (�gure 2.3). return, these miniplants have to supply to these processor/ exporters. But, nowadays, most miniplants are independent, Crab �shing in Indonesia is mostly carried out by small-scale and they can sell their crabs to any processors/exporters if operators. About 65,000 �shermen directly relied on this �sh- the prices permit. ery (SFP 2012). They use boats of less than 10 gross tonnes (GT) with or without motors (although in some cases �sher- There are two main activities in the miniplant: cooking and men do not use boats). The gear is primarily bottom gillnets picking. The miniplants buy raw material from the �sherman and collapsible traps, and to a lesser extent, the now illegal or middleman (bakul) by cash. Raw materials are sorted, shallow bottom trawls (baby trawls). There are two types of grouped, and weighted according to size. If the crabmeat �shermen involved in BSC �sheries across Indonesia: products are rejected due to quality failure (off-flavors and EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) FIGURE 2.2: Major Blue Swimming Crab Catching Areas in Indonesia (1990–2006) 95° 100° 105° 110° 115° 120° 125° This map was produced by the Map Design Unit of The World Bank. The boundaries, I ND ONE SI A colors, denominations and any other information shown on this map do not imply, on SELECTED CITIES AND TOWNS the part of The World Bank Group, any judgment on the PROVINCE CAPITALS legal status of any territory, 15° or any endorsement or NATIONAL CAPITAL acceptance of such INDONESIA boundaries. RIVERS MAIN ROADS MYANMAR VIETNAM RAILROADS PHILIPPINES PROVINCE BOUNDARIES 10° 10° INTERNATIONAL BOUNDARIES THAILAND Sulu Sea 135° 140° Banda Aceh L A Y 5° A BRUNEI 5° 1 14% S Natuna Talaud Medan M Besar I Celebes Is. Tarakan PACIFIC OCEAN Pematangsiantar Sea 24 A Simeulue 19 Morotai 2 Manado SINGAPORE 23 Nias Tanjungpinang C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES Pekanbaru Ternate Halmahera 25 3 Pontianak KA LIMA NTA N Gorontalo Waigeo 0° 26 0° Lingga 20 Samarinda Manokwari Biak 30 Me 3% Padang Palu Sorong Balikpapan Peleng nt Siberut 4 5 Jambi 21 Obi Bangka AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 Yapen aw SULAWESI Sula Is. Misool 32 Jayapura Palangkaraya ai SUMATERA 21% Pangkalpinang Mamuju Ceram 9 Belitung 22 Palembang 27 Amahai Fakfak Is 6 1% . 7 Bandjarmasin 28 Kendari Buru 29 33 PAPUA Bengkulu 5% Parepare Ambon Timika Puncak Jaya 8 Muna (5030 m) 5° Java Sea Makassar Kai Enggano Bandar 11 Baubau Banda 31 Is. Lampung JAKARTA 28% Serang Sea Aru 21% Is. 0 200 400 Kilometers 12Bandung Semarang Madura PAPUA 10 13 2% Surabaya Wetar Babar Tanimbar JAWA Yogyakarta 16 Sumbawa Alor Moa Is. 0 100 200 300 400 Miles 15 Bali Lombok Raba Flores NEW GUINEA 14 Merauke 95° 100° 105° 1% Denpasar Mataram Ende 18 TIMOR-LESTE 17 PROVINCES: 10° Waingapu Sumba Timor Arafura Sea 10° Kupang 1 NANGGROE ACEH DARUSSALAM 12 JAWA BARAT 23 KALIMANTAN TIMUR 2 SUMATERA UTARA 13 JAWA TENGAH 24 SULAWESI UTARA 3 RIAU 14 D.I. YOGYAKARTA 25 GORONTALO 2% 4 SUMATERA BARAT 15 JAWA TIMUR 26 SULAWESI TENGAH 5 JAMBI 16 BALI 27 SULAWESI BARAT 6 BENGKULU 17 NUSA TENGGARA BARAT 28 SULAWESI SELATAN 7 SUMATERA SELATAN 18 NUSA TENGGARA TIMUR 29 SULAWESI TENGGARA INDIAN OCEAN 8 LAMPUNG 19 RIAU KEPULAUAN 30 MALUKU UTARA 15° 15° 9 BANGKA-BELITUNG 20 KALIMANTAN BARAT 31 MALUKU 10 BANTEN 21 KALIMANTAN TENGAH 32 PAPUA BARAT AUSTRALIA 11 D.K.I. JAKARTA 22 KALIMANTAN SELATAN 33 PAPUA 115° 120° 125° 130° 135° 140° Source: Statistics of Indonesia Capture Fisheries, Ministry of Marine and Fisheries Affairs (various years). 9 FIGURE 2.3: Value Chain and Stakeholders Involved in BSC Fisheries in Indonesia Retail Food Service (Supermarkets) (Seafood Restaurant) Retail Price: Special crabmeat (16 oz): $ 14.99 per lb Broadline Specialty Seafood Central Markets Distributors Distributor FOB Price: Importers/Wholesalers Jumbo lump: $ 16.75 – 17.00 per lb Backfin: $ 11.00 – 11.25 per lb Super lump: $ 13.25 – 13.75 per lb Special lump: $ 9.75 – 10.25 per lb Claw meat: $ 6.75 – 6.95 per lb (Source: Urner Barry Seafood Price, 4 Dec 2008) Processors/Exporters Miniplants sell peeled crab to processor/exporter. The average price depends on the meat size and the season: Colosal: $ 24.5 per kilo Local Market (for Jumbo lump: $ 23.5 per kilo crab rejected by Backfin: $ 14 per kilo processor) Flower lump: $ 13 per kilo Super lump: $ 12 per kilo Special lump: $ 8 per kilo Claw meat: $ 6 per kilo (Source: major processors/exporters– Miniplants 2008 price) (Peeler) Collector usually take $ 0.2 – 0.4 per kilo margin profit upon raw material; or $ 0.4 – 0.8 for boiled crab. Collector (Bakul) This collector may or may not be lender/tengkulak to the fishermen. Fishermen sell crab to collector for $ 0.9 – 1.4 per kilo Fishermen Note: - Exchange Rate: 1 USD = Rp 11,000 (as rate per 20 Jan 2009) - 1 kilogram = 2.204 lb, lbs Source: Anggraeni 2011. C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES 11 off-textures), miniplants will sell them to the local market. A Marine Stewardship Council (MSC) preassessment of The worst quality product will be sold to shrimp paste (terasi) Indonesia BSC �shery was conducted in 2009 and highlight- manufacturing. ed the lack of reliable scienti�c data on stock status and the absence of any �shery management as signi�cant issues. 2.2.1.4 Market Currently, a work plan has been developed and implemented The BSC is not in high demand in Indonesia. Almost 95 per- in order to address the de�ciencies identi�ed by the MSC cent of the BSCs caught in Indonesia are exported. The export preassessment report and improve the �shery management of BSCs started in 1994 due to increased demand from over- to meet MSC standards. Some management options have seas. Before this, BSCs were only consumed locally and the been proposed by stakeholders, such as the adoption of an price was very low. Currently, crab products have been the incremental minimum legal size; a ban on the take of ber- third largest export �shery product by value, following shrimp ried (egg bearing) females; changes in �shing gear (such (46 percent) and tuna (14 percent). In 2007, BSCs contrib- as escape gaps in crab pots); a hatchery project; efforts to uted to about 8 percent of total Indonesian �shery products protect nursery and spawning grounds; time/area closures; export, valued at US$179 million, up 33 percent from 2006. a registration system for all purchasers of crabs, both live Total crab exports amounted to 21,510 tons in 2007, consist- and processed (to improve data collection); and �shing effort ing of nonfrozen crab (82 percent), canned crab (11 percent), controls (including specifying legal gear types and minimizing and frozen crab (7 percent) (MMAF and JICA 2009). net length and the number of pots). More than half of the BSC products are exported to the United States, followed by Singapore (17 percent), Malaysia 2.2.2 The Philippines Blue Swimming Crab (BSC) (10 percent), Taiwan (7 percent), European Union (6 percent), Fishery3 3 4 China (5 percent), and Japan (2 percent). In 2008, the total 2.2.2.1 Landings U.S. crab import from Indonesia was 9,372 tonnes, a de- The Philippines BSC (Portunus pelagicus) is called kasag crease of 15 percent from 2007. However, the average price (Hiligaynon), alimasag (Tagalog), lambay (Bisaya), kagang has increased by 21 percent from US$14.5 per kilo in 2007 to sukay (Tausog), and kappi (Ilokano) in different languages. It US$17.5 per kilo in 2008, leading to a 6 percent increase by is traditional seafood in the country, but was not a targeted value (NMFS 2011). More than 85 percent of crab imported species. It used to be a preferred by-catch of �n�sh �shery to the United States from Indonesia was in ATCs (airtight and some �shing gears such as �sh corrals. BSC �shery has containers) or canned, while another 10 percent was frozen become an important �shery since the increase in demand of and another 5 percent was in other preparations. pasteurized BSC meat from the United States. The trend of the total landings of BSCs in the Philippines shows two ma- 2.2.1.5 Over�shing jor eras (�gure 2.4). Before the early 1990s, the major market Currently, there are no direct controls on the harvest of BSCs was mostly domestic. From the mid-1990s to the present, in Indonesia. Fishers can catch any size of crab and sell it to the industry became more export oriented. In the past the picking plants. The utilization level of BSC has probably 10 years, average production has been around 34,000 tons. met or even exceeded the Maximum Sustainable Yield level. BSCs’ distribution is within the coastal areas on sandy sub- Some catch reports in recent years indicate that the aver- strates and on strictly marine environment. Juvenile BSCs age size of landed BSCs is becoming smaller. Preliminary are usually found on the intertidal and subtidal areas where assessment by a stock modeling expert suggests that the they land for shelter and foraging, particularly on seagrass, resources have been �shed down to some extent, but there seaweed, and algal beds and mangrove areas. There were is insuf�cient data to proceed much further toward any form at least two biological stocks of BSCs in the Philippines: one of quantitative stock assessment (SFP 2010). in the Visayan Sea and surrounding inland waters (i.e., Bohol 2.2.1.6 Measures Taken Toward Sustainability Sea) and one in Tawi-tawi waters (Romero 2009). The major �shing grounds of BSCs in the Philippines are the inland wa- In 2007, an Association of Indonesian BSC Processors ters of Central Philippines, which are almost interconnected (Asosiasi Pengelolaan Rajungan Indonesia, APRI) was formed, with the Visayan Sea, including San Miguel Bay facing the with the goal of sustainable procurement from healthy stocks. APRI currently consists of 11 leading crab process- ing and exporting companies in Indonesia, representing over 3 This part is based on the report written by Jimely Flores from 90 percent of crab exported from Indonesia to the U.S. market. Sustainable Fisheries Partnership (SFP). AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 12 C H A PTER 2 — OVERVIEW OF FPIs A ND S TUD IED FIS H ER IES FIGURE 2.4: Landings of BSCs in the Philippines 45,000 36,000 27,000 tons 18,000 9,000 0 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: FAO 2011. Paci�c Ocean, Malampaya Sound facing South China, and and the effort needed (based on the existing catch and effort the Tawi-tawi group of islands (Ingles 2004). Some small- data from 1990 to 1993) was about 13,150 gillnet panels. In scale crabbing areas include Lingayen Gulf, Manila Bay, and 2000, the effort in the western Visayas alone was already Honda Bay. The major crabbing areas comprise 87.7 percent 60,047 gillnet panels, 4.5 times more than the effort sug- of the total BSC landings in 2007. gested to reach MSY level (Ingles and Flores 2000). 2.2.2.2 Fishing Efforts Growth Over�shing: Catch of juveniles is a concern for sustain- The traditional methods of collecting BSCs include simple able development of BSC �shery. Gillnet has higher probability picking and diving, bintol (crab liftnet), �sh corrals, and to catch immature BSC than the bamboo trap/pot (table 2.4). bamboo pots/traps (Ingles 1996; Ingles 2004). At present One hundred percent of the catch of the pushnet, which oper- the industry is using gillnet as major �shing gear, and some ate in the seagrass areas were juveniles (Ingles and Flores are using traps/pots. It is also a retained by-catch species of 2000). Without any management intervention for this kind of trawls and Danish seines. practice, the overexploitation will likely become more serious. BSC �sheries in the Philippines are mostly artisanal. Crabbers High by-catch: By-catch is also a great concern, particularly use either motorized or nonmotorized boats, which are usu- for those using the gillnets. In the Northern Guimaras Strait, ally below 3 GT with lengths ranging from 10 to 50 feet. over half of the total catch of gillnet was by-catch, compris- Motorized �shing boats could be powered by 4 to 16 HP, ing 19 species of crabs (7 were retained and the remaining while the big ones (lengths of 20 to 50 feet) may use the 12 species were discarded). Only about 40 percent of the converted engines of land vehicles referred to by the �shers catch is BSC. A variety of mollusks, sponges, and even some as 4DR (Isuzu) or 3R (Kubota). corals were not accounted for because they were removed upon hauling of the net. Ingles (2003) also identi�ed the There are no updated data on the number of �shers, �sh- entanglment in gillnets used in BSC �sheries as one of the ing gear, and �shing boats involved in the BSC industry for causes of death for the Irrawady dolphins, Orchaella briviro- the whole country. A study conducted in 2002 to 2004 in stris, an endangered species in Malampaya Sound, Taytay, the Visayan Sea counted at least 2,522 �shing boats from and Palawan. Flores (2005) indicated that the BSC gillnet 17 landing sites using either gillnet, bamboo pots, or PVC �sheries are also catching a signi�cant volume of juvenile traps (Romero 2009). There were about 1,814 full-time �sh- sharks (retained species) and other stingrays. ers and 708 part-time �shers from those sites. 2.2.2.4 Value Chain 2.2.2.3 Issues of the Fisheries The value chain for the Philippines BSC �shery is demonstrat- Overcapacity: Overcapacity in the BSC �shery started when ed in �gure 2.5. The �shers are using either gillnets (about the export of pasteurized meat was intensi�ed. In the Visayan 60 percent of the total production), traps/pots (about Sea, Ingles (1996) estimated that the MSY level was 1,383 tons 30 percent share), or other �shing gear (10 percent) to catch EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 2 — O V E RVIE W OF F P Is AND ST UDIE D F IS H ER IES 13 TABLE 2.4: Immature BSC Catch Rate for Different Gears FISHING GEAR MALE CAUGHT IMMATURE FEMALE CAUGHT IMMATURE Pushnet 100% 100% Gillnet 27.5% 34.2% Bamboo trap/pot 12.2% 26.5% Source: Ingles and Flores 2000. FIGURE 2.5: Supply Chain in the Philippines’ Blue Swimming Crab Industry Philippines’ BSC supply chain Retailers Consumers Consumers (abroad) (Phil) Exporters/importers Exporter’s mini-processing plant Other traders Picking plants Crab local traders Small-scale pickers Bait EN T/P Others ~60% ~30% ~10% Source: Flores 2011. BSCs. The �shers sell their crabs to the local traders, who $22/kg) for the jumbo and US$4 to 6/lb($8.8 to $13.2/kg) for sometimes are also the �nanciers. The crab traders will sell the lower classes of meat (like special). The pasteurized meat their crabs to the picking plants with a margin of 20 to 30 pe- of the BSCs ranked as the fourth top export in 2007, amount- sos/kg (US$0.5 to 0.7/kg) of live whole crab. In some cases ing to about US$41 million export revenue. In addition to the when the local trader delivers exclusively to one picking plant, United States, the Philippines also exports crabmeat to Hong traders will also cook the crabs by using the facilities provided Kong, Singapore, and other Asian countries (BFAR 2008). by the picking plant. Cooked crabs have an additional margin 2.2.2.5 Management Framework of PhP20 to 40/kg (US$0.5 to 0.9/kg).4 Picking plants are set up 4 5 and maintained by the exporters/processors. A price for picked The main legal framework with jurisdiction to the �sheries re- crabmeat ranges from PhP600 to 700/kg (US$13.7 to 16/kg). sources of the Philippines is the Republic Act 8550 (Philippine The picked crabmeat is then delivered to the main processing Fisheries Code). Under this law, the BSC �shery is classi�ed plants for further quality control, packaging, and pasteuriza- under the municipal �sheries sector and is allowed to �sh tion. There are very few players in the BSC export market. within the 15 km (radius from the shoreline) municipal waters Six exporting companies dominate the exports. The products of the country. This means that the use and management of are transported to the �nal country of destination in a chilled this type of �shery is under the jurisdiction of the local gov- container with strictly controlled temperature. The wholesale ernment units (municipalities and provinces) as mandated by prices in the United States are about US$8 to 10/lb ($17.6 to Republic Act 7160 (The Local Government Code). Further, Executive Order 305 (by the president of the Philippines) de- volves the registration of �shing vessels 3 GT and less to the 4 1 US$ = 43.7 PhP (http://themoneyconverter.com/usd/php.aspx). responsibility of the municipal and city governments. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 14 C H A PTER 2 — OVERVIEW OF FPIs A ND S TUD IED FIS H ER IES The Bureau of Fisheries and Aquatic Resources (BFAR) There are also local government units. The Province of is mandated to manage the fisheries sector. At present, Negros Occidental in 2003 enacted a law prohibiting the the BFAR initiated the creation of a BSC Management catching and trading of berried crabs and crabs less than Plan wherein some regulatory measure would be imple- 11 cm in carapace width. The municipalities in Northern Iloilo mented to ensure the sustainability of resources such as (NIACDEV) prohibit the catching and trading of berried crabs a creating a minimum legal size of 10.16 cm; putting a and crablets; in 2012, this law was amended and crablets cap on the fishing effort by limiting the number and size was changed to 11 cm as minimum carapace width limit. (or number) of fishing gear; closing and opening fishing The municipalities of Guiuan, Eastern Samar, and Talibon, seasons and areas; and protecting the nursery sites of Bohol, enacted regulations banning the catching and trading juvenile crabs. of crabs less than 4 inches in size. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 15 Chapter 3: FPIs’ APPLICATION ON BSC FISHERIES— OUTPUT RESULTS FPIs are applied to BSC �sheries in Indonesia and the The Indonesian BSC �shery has lower nonlanding mortal- Philippines. FPIs have set up 3.5 as a benchmark, meaning ity but a higher percentage of over�shing compared to the any �shery that has an indicator scored under 3.5 will have Philippines BSC �shery. substantial room for improvement. It is useful to understand how a well-managed �shery will perform and how far these In summary, with regard to Ecological Sustainability, the two studied �sheries are away from a currently well-managed Icelandic lobster �shery performed well (4.8), indicating it is �shery. Therefore, the Icelandic lobster �shery is selected ecologically sustainable (�gure 3.2). In contrast, ecological as another benchmark because it is also an export-oriented sustainability is a big concern for both Indonesian (1.8) and �shery and has been recognized as a well-managed �shery the Philippines BSC (1.3) �sheries. If the �shery resources after adopting the Individual Transferable Quota (ITQ) system are not physically healthy, it will undermine the potential for in 1984 (Arnason 2002). wealth creation for the local communities in the long run. According to the FPIs, the Indonesia BSC �shery needs to The FPI output indicators include three components, reduce over�shing, and the Philippines BSC �shery needs Ecological Sustainability, Harvest Sector Performance, to reduce both over�shing, high retained by-catch species, and Post-Harvest Sector Performance (Anderson and and nonlanding mortality of other species (high nonretained Anderson 2010). This chapter will describe detailed results by-catch species) to improve ecological sustainability. for each of these components. 3.1.1.1 Comments 3.1 ECOLOGICAL SUSTAINABILITY Proportion of Harvest with a Third-Party Certi�cation: Different countries can choose different certi�cations The �rst component is Ecological Sustainability, measuring as long as they are well-recognized third-party certi�ca- the �sh stock health and its harvest status in order to under- tions. With an increasing demand for certi�ed seafood, stand whether the physical �shery resource is in good shape this indicator should be easy to score and well repre- and has the ability to create sustainable wealth. It is the aver- sent the situation of the ecological sustainability for age of four indicators, including Proportion of Harvest with developed countries. However, because it is relatively a Third-Party Certi�cation, Fish Stock Sustainability Index expensive to obtain one certi�cation for developing (NMFS), Percentage of Stocks Over�shed, and Nonlandings countries, it is expected the score will be very low or Mortality. The scoring scale and additional information for unattainable for many �sheries, particularly for artisanal each indicator are shown in table 3.1. A more detailed expla- small-scale �sheries in developing countries. nation is found in Appendix A. Fish Stock Sustainability Index: This indicator mea- sures if there are any measurements or efforts to 3.1.1 Fish Stock Health correct over�shing and if the over�shing situation As shown in �gure 3.1, Icelandic lobster obtained full scores is improving. It is suggested that the de�nition be for three out of the four indicators of ecological sustainability. revised without referring to NMFS. This indicator can For Indonesian and Philippine BSC �sheries, three out of four be changed to “Over�shing and Rebuilding,� with a scored in the range indicating a need for urgent improve- new de�nition of “Extent to which current effort af- ment. Neither of these two �sheries obtained third-party fects stock status. For multistock �sheries, score each certi�cation or have a �sh stock sustainability index because signi�cant stock 1 to 5, then take a value-weighted there is no effective management in place and lack of data. average� (see Appendix B1). AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 16 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.1: Score System for Indicators of Ecological Sustainability MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Proportion of Harvest with a 5: 76–100% of landings are certi�ed The proportion of harvest (quantity) harvested under one Third-Party Certi�cation 4: 51–75% of landings are certi�ed of the recognized third-party programs that certify eco- 3: 26–50% of landings are certi�ed logical sustainability, such as the Marine Stewardship Council (MSC) certi�cation. 2: 1–25% of landings are certi�ed 1: No landings have third-party certi�cation Fish Stock Sustainability Index For each of four components, each stock receives: one point if the status of The Fish Stock Sustainability Index. The FSSI is calcu- (NMFS) the stock is over�shed or subject to over�shing; two points if management lated by assigning a total score between 0 and 4 to each measures are succeeding at preventing over�shing; three points if the priority �sh stock. Note: The number of priority stocks stock biomass is above the level de�ned as over�shed for the stock; and will differ between management systems (The Fish four points if the stock is rebuilt or is at its “optimal� level, within 80% of Stock Sustainability Index, 2009). that required to achieve maximum sustainable yield. The FSSI is computed by summing the scores of the individual stocks. Points by quintile are rela- tive to the maximum possible score; with 5 points for the highest quintile. Percentage of Stocks 5: None over�shed Percentage of commercial stocks within the manage- Over�shed 4: 1–25% of stocks over�shed ment authority’s preview that are considered over�shed, 3: 26–50% over�shed to be experiencing over�shing, or in generally unknown stock status (whether actively managed or not). 2: 51–75% over�shed 1: 76–100% over�shed Nonlandings Mortality 5: Virtually none Ratio of estimated mortality of the assessed target 4: Less than 5% species from illegal harvest, by-catch, illegal discards, 3: 5–10% regulatory (legal) discards, and other nonlandings waste to actual landings. 2: 10–20% 1: More than 20% Source: Anderson and Anderson 2010. FIGURE 3.1: Fish Stock Health and Environmental FIGURE 3.2: Ecologically Sustainable Fisheries Performance 4.8 5.0 Proportion of harvest with a 3rd 4.0 party certification 5 3.0 4 3 1.8 2.0 2 1.3 1 Fish stock Non-landings 1.0 0 sustainability mortality index (NMFS) 0.0 Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Percentage of stocks overfished Indonesia BSC Philippines BSC Icelandic lobster of FPIs is to be able to conduct a rapid assessment Source: Authors. for data-poor countries. Experts’ good estimation and judgment of the situation is enough. For example, if the average catch size and volume or catch per unit effort (CPUE) is declining with years, it is reasonable Percentage of Stocks Over�shed: This states the to judge that the stock is over�shed without formal situation of whether the studied �shery is over�shed. stock assessment data. Experts from Indonesia and the Philippines felt it was Nonlandings Mortality: Similar to over�shing, this dif�cult to score because there was no biological will rely on experts’ experience or studies for those reference point. This issue will occur whenever the �sheries lacking data and management in place. expert wants to rely on precise data to score. The goal Additionally, there are two types of mortality. One is EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 17 induced by regulatory requirements to discard landed FIGURE 3.3: Harvest Performance �sh. One is induced by the selection of gears, �shing Landings level methods, and so forth. In order to distinguish these 5 two, it is suggested to change this one indicator to 4 two indicators, Regulatory Mortality and Selectivity. 3 2 See Appendix B1 for the score systems. 1 There are also no indicators to show whether the criti- 0 cal habitat is protected or if there are MPAs existing and functioning, because these will affect the recruit- Season length Excess capacity ment of �sheries. It is suggested to add Status of Critical Habitat to capture the habitat’s situation (see Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Appendix B1 for the suggested score system). 3.2 HARVEST SECTOR PERFORMANCE 3.2.1 Harvest Performance The score of the Harvest Performance is an average of The second component is Harvest Sector Performance. It Season Length, Excess Capacity, and Landing Level. The includes �ve dimensions, the Harvest Performance, Asset score system for each indicator is shown in table 3.2. Performance, Risk, Boat Owner/Manager Performance, and Crew Performance. Harvest Performance captures es- Icelandic lobster �shery achieved full scores for all the indica- sential aspects of ef�ciency in harvesting and thus the abil- tors (0.0.5) (�gure 3.3). Regarding the Landings Level, Icelandic ity to generate sustainable wealth from the landings. Asset lobster harvest is less than MSY (Maximum Sustainable Yield) Performance characterizes how well harvest capital owners to increase pro�t. Indonesia BSC’s harvest is constraining are able to invest in the �shery and how much future wealth stock recovery, and Philippines BSC’s harvest is over�shed. is capitalized into the value of their rights and equipment. The Risk dimension reflects sources of risk in the �sheries Regarding the Excess Capacity, Icelandic lobster scored 5 that may inhibit investment or prevent the development of because the harvesting effort is managed by the process- high-value supply chains. The indicators on Owners, Permit ing manager according to the needs of �nal customers. Holders, and Captains and Crew capture the social dimen- Therefore, the excess capacity issue is not substantive. Both sion of wealth distribution. Who bene�ts from the �shery? Indonesia and the Philippines BSC �sheries have an overca- What are the relative income levels and social standing? pacity issue in general—there are too many �shing boats. Each dimension is an averaged result of a few indicators The number of boats needed is much less than what are cur- which will be explained as follows. rently operating. However, the overcapacity issue can vary TABLE 3.2: Score System for Indicators of Harvest Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Landings Level 5: Harvest is less than MSY (stock is above MSY level) to increase pro�t Average annual harvest over the last 3 years. Note: 4: Harvest is approximately at MSY in practice there are very few estimates of MEY, 3: Harvest reduced to promote recovery (stock is below MEY level) however where it has been calculated it is typically 5 to 10 percent less than maximum sustainable yield 2: Harvest is constraining stock recovery (stock is stable below MEY level) (MSY). 1: Harvest is causing over�shing (stock is below MEY and declining) Excess Capacity 5: Within 5% of days required Estimated standardized vessels-days required to 4: 105–120 or 90–95% catch the maximum economic yield (MEY) compared 3: 120–150% or 75–90% to the number of standardized vessel-days available. Days are considered not to be restricted by trip limits. 2: 150–200% or 50–75% 1: More than 200%, or less than 50%, of days required Season Length 5: Virtually no regulatory closures Ratio of number of days on which �shing occurs 4: 91–99% to the number of days the species is available in 3: 51–90% economically feasible quantities. 2: 11–50% 1: Less than 10% Source: Anderson and Anderson 2010. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 18 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS FIGURE 3.4: Summary of Harvest Performance and relevant studies. Usually it is calculated as 5 to 10 percent less than maximum sustainable yield (MSY). 6.0 5.0 It is noticed that the Catch per Unit of Effort (CPUE) 5.0 is not used here. It might be because it is dif�cult 4.0 to compare across boat types, across �sheries, and 2.7 across countries. It is not easy to quantify what effort 3.0 1.7 really means for each �shery. It can be per pot, per 2.0 day, per person, per boat, or per mile. Unless a �shery 1.0 and effort are clearly de�ned, it won’t be comparable 0.0 between �sheries. Therefore, even though it is a com- Indonesia BSC Philippines BSC Icelandic lobster monly used term, the authors support the idea of not Source: Authors. using CPUE in the FPIs system. among regions. For example, in Indonesia, the excess capac- 3.2.2 Harvest Asset Performance ity issue is much more serious in North Java Sea compared The Asset Performance dimension consists of six indicators, to East Sumatra. ranging from Source of Capital to Borrowing Rate. Table 3.3 gives a detailed score system for each indicator in this Regarding the Season Length, both the Icelandic lobster dimension. �shery and the Philippines BSC �shery have no constraints on �shing. This does not mean they will go �shing all the Icelandic lobster received high scores in all the categories time. Usually, they go when the weather is good. During low except Asset Value versus Historic High (�gure 3.5) because season, some �shermen will shift to other commodities or recent political unrest has downgraded the quota transfer activities. value. The asset value in Indonesia and the Philippines re- flects only the value of the boats and gear because there is In summary, the Icelandic lobster �shery performed well no quota or permit system in these two �sheries. There is no in the harvest sector. The Indonesia BSC �shery and the substantial difference between the boat value now and the Philippines BSC �shery received an average of 1.7 and 2.7, past 10 years for BSC �sheries. respectively, lower than the benchmark 3.5 (�gure 3.4). They have an overcapacity issue, and the harvest level is con- Icelandic lobster achieved the highest revenue in 2009. straining the stock recovery or causing over�shing. There is The BSC prices dropped in 2009 compared to the historic substantial improvement space in the harvest performance. high, leading to a satisfactory score for the Icelandic lob- ster �shery (5) on Total Revenue versus Historic High. Both 3.2.1.1 Comments Indonesia (3) and the Philippines (2) BSC �sheries are below The scale for the Season Length indicator is confus- benchmark 3.5. ing. The de�nition now is the “ratio of number of days The capital is relatively well maintained among these �sh- on which �shing occurs to the number of days the eries. In Indonesia, boats last for about 10 years. Trap can species is available in economically feasible quanti- be used for approximately 1 year, and the gillnet has to be ties.� This is primarily a measure of the extent of replaced at least once a month. In the Philippines, boats derby (including short regulatory seasons to limit total are constructed with materials that are easily available and effort), not lack of biological availability or closures to replaced. Therefore, the scores for Functionality of Harvest prevent within-season growth over�shing. It does not Capital are satisfactory. count when it is bad weather or when the boat is un- der repair/maintenance. There is also a natural peak or Indonesia and the Philippines BSC �sheries received the low season for certain �sheries during different times same scores for Source of Capital (2) and Borrowing Rate of the year. For countries where there is no derby and Relative to Risk-Free Rate (5), but the situations are different. �shermen can �sh anytime they can, score 5 for this In Indonesia, there is a vertical integration. The miniplants indicator. (picking plant) invest or loan to the collectors (bakul) through MSY, especially MEY (Maximum Economic Yield), data formal or well-recognized oral purchasing contracts. The are not always available. This requires the expert to miniplant will allow a collector to get a certain margin. If, judge the situation according to his or her experience somehow, both �shermen and collectors break the supply EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 19 TABLE 3.3: Score System for Indicators of Asset Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Ratio of Asset Value to Gross 5: 10 or higher Ratio of average price of access to the �shery over the last Earnings 4: 7.5–10 5 years to the average annual landings value for a similarly 3: 5–7.5 scaled access right in the same period. Same business or same family sales are excluded, where they can be identi�ed. 2: 2.5–5 1: Below 2.5 Total Revenue versus Historic 5: Above 95% The indicator is the ratio of total revenue to the average of High 4: 86–95% the three highest total revenues in the past 10 years. 3: 71–85% 2: 50–70% 1: Below 50% Asset (Permit, Quota) Value 5: Above 95% The indicator is the ratio of asset to the average of the three versus Historic High 4: 86–95% highest asset values in the past 10 years. 3: 71–85% 2: 50–70% 1: Below 50% Borrowing Rate Relative to 5: Less than 1.75; cf. 30-year conforming mortgage Average ratio between the interest rate on loans made in the Risk-Free Rate 4: Less than 2.5; cf. personal bank loan industry to risk-free rates over the last 3 years. 3: Less than 4; cf. good credit card rates 2: Less than 7; cf. bad credit card rates 1: Greater than 7; usury Source of Capital 5: Unsecured business loans from banks/venture capital Points to be assigned based on the category of lenders or 4: Secured business loans from banks/public stock offering investors that is most typically used in the �shery. 3: Loans from banks secured by personal (not business) assets/ government-subsidized private lending/government-run loan programs/international aid agencies 2: Microlending/family/community-based lending 1: Ma�a/no capital available Functionality of Harvest 5: Capital is new Average age of the key durable harvesting capital unit Capital 4: Capital is older but well maintained (e.g., freshly painted) (vessels, weirs). 3: Capital is moderately well maintained 2: Maintenance is poor 1: Serious concerns about seaworthiness or safety throughout �shery Source: Anderson and Anderson 2010. FIGURE 3.5: Asset Performance Ratio of asset value to gross earnings 5 contract by selling their products to other competitors, the 4 Total revenue miniplant, as the biggest capital owner, will terminate all con- Functionality 3 versus tracts with those �shermen and collectors. The �shermen’s of harvest 2 historic high boats or other assets of collectors may be taken away. In capital 1 the Philippines, most small-scale �shers use their savings or 0 loans from family or close friends to invest, rarely from the Asset bank. (permit, quota) value Source of versus historic high capital In summary, the Icelandic lobster �shery achieved an aver- age of 4.2 in the Harvest Asset Performance (�gure 3.6). The Borrowing rate lower asset value versus Historic High dragged the average relative to risk-free score down. Both Indonesia and the Philippines BSC �sher- rate ies received an average of 3.2, indicating a substantial im- Indonesia BSC Philippines BSC Icelandic lobster provement need, particularly on better availability of �nancial Source: Authors. system, asset value, and functionality of asset. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 20 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS FIGURE 3.6: Summary of Asset Performance The Indonesia BSC �shery did not have signi�cant spatial price difference compared to the Philippines �shery, but it had more 5.0 4.2 Landings and Price Volatility between years and months. This 4.0 may be because (1) there are some “peak seasons� and “low 3.2 3.2 seasons� in crab �shing in Indonesia that create monthly price 3.0 differences. Usually the price will be higher during the low 2.0 season and lower during the peak season. (2) The Indonesian expert used U.S. import data to calculate this group of indica- 1.0 tors, and the Philippine expert used ex-vessel data. 0.0 In summary, all three �sheries are facing relative manageable Indonesia BSC Philippines BSC Icelandic lobster risks with an average score higher than 3.5 (�gure 3.8). The Source: Authors. Indonesia BSC �shery is facing more potential economic risk; therefore, more attention needs to be paid to annual landing and price volatility. 3.2.2.1 Comments Borrowing Rate Relative to Risk-Free Rate: If the mon- 3.2.3.1 Comments ey is borrowed from family or friends, the rate should Risk Exposure indicators are clearly identi�ed and be the interest rate of savings as opportunity cost if quantitative. There might be a data availability issue putting money to the bank is a common practice. Or in some developing countries in price data collection, else, the interest rate can be zero. However, there especially on monthly data and regional price data. might be some in-kind payback, which is not reflected This will help identify data gap and encourage setting in the score system or explanation. Additionally, for up economic data collection. developing countries, a risk-free rate can be hard to de�ne. It is suggested to add “family or friend’s sup- 3.2.4 Boat Owners/Captain port� to 5 and “in-kind payback� to 4 (Appendix B). The earning and status of Boat Owners/Captains reflect Source of Capital: It is suggested that “contract rela- whether a �shery is pro�table, equitable, and sustainable. tionship between the processors and producers� be This group of indicators is meant to capture not only the eco- added into score 2. nomic well-being, but also the social stability level, including the relative income level, Education and Health Care Access, 3.2.3 Risk Exposure Social Standing, and Proportion of Nonresidents (table 3.5). The �shery industry is a high-risk industry. Risk exposure uses a series of indicators to summarize the potential expo- The Indonesia BSC �shery performed well with three indi- sure of the �shing industry to various economic and social cators achieving higher scores (�gure 3.9). The earnings of risks (table 3.4), including price volatility, revenue volatility, Indonesia BSC boat owners, who are often miniplant owners and legal challenges. or people with �nancial ability, were eight times more com- pared to the national average. The captain’s average wage The Icelandic lobster �shery has very limited risks in terms of is nearly twice that of average non�shery wages. This leads harvest revenue, landings, and price volatility (�gure 3.7). It is to their relatively high social standings. In contrast, the rela- a well-managed, demand-driven �shery. There is no obvious tive situation of boat owners and captain for Icelandic lobster difference between months, years, and areas due to con- �shery and the Philippines BSC �shery is not as good as sistent supply and demand of lobster. The Icelandic lobster those in Indonesia. �shery only has some political risk, leading to a lower score on Contestability and Legal Challenges. Both Indonesia and the Philippines BSC �sheries did not receive high scores in terms of Access to Health Care. In The Philippines BSC �shery has relative low risks in terms Indonesia, there are some government-owned small health of Landings and Price Volatilities between years and months care facilities (Puskesmas) in each subdistrict (kecamatan) based on FPIs scores (�gure 3.7). However, the Spatial Price that provide health service to local people. In the Philippines, Volatility, Legal Volatility, and Annual Revenue Volatility are medical treatment is seldom accessible and relies more on concerns. Legal volatility comes from low enforcement of self-meditation by buying basic drugs from some community most regulations. stores. Access to Education is satisfactory for all of them. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 21 TABLE 3.4: Score System for Indicators of Risk Exposure MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Annual Total Revenue 5: 0.14 or less Ratio of the standard deviation of the �rst differences of Volatility 4: 0.15–0.21 annual total revenue to the mean total revenue over the 3: 0.22–0.39 last 10 years. 2: 0.40–0.99 1: 1 or greater Annual Landings Volatility 5: 0.14 or less Ratio of the standard deviation of the �rst differences of 4: 0.15–0.21 annual total landings sold to the mean landings over the 3: 0.22–0.39 last 10 years. 2: 0.40–0.99 1: 1 or greater Intra-Annual Landings 5: 0.14 or less Ratio of the standard deviation of the weekly/monthly Volatility 4: 0.15–0.21 total sold landings over the last 3 years to the mean 3: 0.22–0.39 landings. Observations of zero landings are included if there is biological availability. If the biological season 2: 0.40–0.99 is so short that there is no meaningful variation at a 1: 1 or greater monthly level, this measure can be NA. Annual Price Volatility 5: 0.12 or less Ratio of the standard deviation of the �rst differences 4: 0.13–0.19 of annual ex-vessel price to the mean price over the last 3: 0.20–0.30 10 years. 2: 0.31–0.84 1: 0.85 or greater Intra-Annual Price Volatility 5: 0.12 or less Ratio of the standard deviation of average monthly 4: 0.13–0.19 ex-vessel price over the last 3 years to the mean. 3: 0.20–0.30 Observations of zero landings are included if there is biological availability. If the biological season is so short 2: 0.31–0.84 that there is no meaningful variation at a monthly level, 1: 0.85 or greater this measure can be NA. Spatial Price Volatility 5: 0.12 or less Ratio of the standard deviation across data collection 4: 0.13–0.19 regions of average annual ex-vessel price to the mean. 3: 0.20–0.30 Measure should be averaged over the last 3 years. 2: 0.31–0.84 1: 0.85 or greater Contestability and Legal 5: No signi�cant legal challenges, civil actions, or protests Challenges regarding the �shery management system 4: Minor legal challenges slow implementation 3: Legal challenges, civil actions, or protests impede some management measures 2: Legal challenges, civil actions, or protests suspend major elements of the management system 1: Legal challenges, civil actions, or protests suspend or prohibit implementation of key management reforms and regulation certi�cation Source: Anderson and Anderson 2010. Boat owners in the Philippines and Indonesia can have ac- 3.2.4.1 Comments cess to good education. The annual earnings and wages are sensitive data. For In summary, Indonesia BSC �shery and Icelandic lobster �sh- some developing countries, it is not easy to obtain the ery boat owners/captains are doing better than the benchmark data. (�gure 3.10). They are relatively wealthy, ranked with high Currently, there are two wage comparison indicators, social standing, and receive good health care and education. one to national average and one to non�shery. It is The Philippines BSC �shery boat owners/captain achieved suggested to use Earnings Compared to Regional an average score of 2.8, lower than the benchmark 3.5. Average to replace the original two indicators as it They need to improve their access to the health care system is more relevant to compare to the regional average and income in general. instead of the national average (see Appendix B). AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 22 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS FIGURE 3.7: Risk Exposure FIGURE 3.8: Summary of Risks Annual total 4.9 revenue 5.0 4.3 volatility 4.0 3.7 5 Contestability 4 Annual & legal landings 3.0 3 challenges volatility 2 2.0 1 0 Intra-annual 1.0 Spatial price landings volatility volatility 0.0 Intra-annual Indonesia BSC Philippines BSC Icelandic lobster price Annual price Source: Authors. volatility volatility Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. TABLE 3.5: Score System for Indicators of Boat Owners/Captain MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Earnings Compared to 5: More than 50% above the national average Ratio of annual earnings from �shing National Average Earnings 4: Between 10 and 50% above national average per owner to the national average 3: Within 10% above the national average earnings. In many cases, the captain is an owner of a vessel or permit, 2: Between 50% and 90% of the national average but in other cases, captains are 1: Less than half of the national average considered as crew. Fishery Wages Compared to 5: More than 50% above the national average Ratio of captain’s average daily wage Non�shery Wages 4: Between 10 and 50% above the national average to average daily wage in region/ 3: Within 10% above the national average country. 2: Between 50 and 90% of the national average 1: Less than half of the national average Education Access 5: Higher education is accessible 4: High school–level education or advanced technical training is accessible 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic education is accessible 1: Formal education is not accessible Access to Health Care 5: Global standard treatment for illness is accessible 4: Licensed doctors provide trauma, surgical, and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of Boat 5: Among the most respected in the community, comparable with civic and Owners and Permit Holders religious leaders and professionals, such as doctors and lawyers 4: Comparable to management and white-collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue collar or service jobs 1: Among the least respected, such as slaves or indentured servants Proportion of Nonresident 5: 95–100% local Employment 4: 71–95% local 3: 36–70% local 2: 5–35% local 1: Virtually no local crew Source: Anderson and Anderson 2010. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 23 FIGURE 3.9: Boat Owners/Captain However, their Social Standings are similar with a score of 2 or 3 as most of the time, �shery crews are regarded as Earnings compared to national average skilled or nonskilled labor. earnings 5 The scores of Access to Education for Indonesia and the 4 Philippines BSC �sheries crew are low (2), compared to Proportion of Fishery wages nonresident 3 compared to Icelandic lobster crews (5) or their own countries’ boat own- employment 2 non-fishery wages ers/captains (4). In the Philippines, elementary and second- 1 ary education in state-run schools is free, but parents have 0 to pay for the school supplies, uniforms, and other contribu- Social standing of tions which can be a hindrance for kids from going to school. boat owners Education and permit holders access Most crabbers’ children �nished at least the elementary level. After that, some male children are often asked to help their parents in the crabbing activities or other livelihoods. Access to health care It is hard for the family to continue sending kids to school when they can make extra money for the family. These kids Indonesia BSC Philippines BSC Icelandic lobster will probably grow and follow the paths of their parents. Thus Source: Authors. the cycle of poverty, less education, and lack of opportunity repeat. FIGURE 3.10: Summary of Boat Owners/Captain 5.0 4.5 The score of Access to Health Care for the crew in Indonesia 4.0 and the Philippines BSC �sheries crew is 2, the same as the 4.0 one for boat owners/captain in these two countries, indicat- 2.8 ing a weak national health care system and a substantial im- 3.0 provement space. 2.0 Regarding the nonresident employment, the Philippines BSC 1.0 �shery has almost all local crabbers (score 5), while Indonesia and Iceland have more nonresident �shermen (score 3) in 0.0 their BSC and lobster �sheries. Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. In summary, Icelandic lobster crews are performing above the 3.5 benchmark in their communities with average scores For certain �sheries, it is not necessary to have a cap- of 4.3 (�gure 3.12). Indonesia BSC crews and the Philippines tain. In those cases, this group of indicators is about BSC crews are doing marginally �ne in their communities the situation of boat owners. with an average score of 3.5 and 3.3, respectively. Their education and health care access have room for substantial 3.2.5 Crew improvement. Similar to the Boat Owner/Captain, this group of indicators fo- cuses on the social status of the crews (table 3.6). Evaluating 3.2.5.1 Comments the economic and social performance of crew members can Similar to Boat Owner/Captain, it is suggested to use help us understand the equity of wealth distribution within Earnings Compared to Regional Average to replace the �shery sector by comparing with the performance of the the original two indicators (see Appendix B). boat owners/captains, or the cross-country situation by com- The status of crew can vary with regions, boat type, paring with other countries’ crews. or gear type. It is suggested to use the average or the All three �sheries have well-represented age groups (score 5) representative crew to score this group of indicators. and crew experiences (score 4), indicating a relatively stable �shery sector (�gure 3.11). The difference is that Indonesia 3.2.6 Summary BSC �shery crews and Icelandic lobster �shery crews have The FPIs reasonably represent the situation of these three better economic conditions compared to national average �sheries with regard to the Harvest Sector Performance or non�shery, but not the Philippines BSC �shery crews. (�gure 3.13). In general, the harvest sector of the Icelandic AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 24 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.6: Score System for Indicators of Crew MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Earnings Compared to 5: More than 10% above the national average Ratio of crew’s average daily wage to average National Average Earnings 4: Within 10% of the average national wage. 3: Between 50 and 90% of the average 2: Between 25 and 50% of the average 1: Less than 25% of the average Fishery Wages Compared to 5: More than 10% above the national average Ratio of crew’s average daily wage to average Non�shery Wages 4: Within 10% of the average daily wage in region/country. 3: Between 50 and 90% of the average 2: Between 25 and 50% of the average 1: Less than 25% of the average Education Access 5: Higher education is accessible 4: High school–level education or advanced technical training is accessible 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic education is accessible 1: Formal education is not accessible Access to Health Care 5: Global standard treatment for illness is accessible 4: Licensed doctors provide trauma, surgical, and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of Crew 5: Among the most respected in the community, comparable with civic and religious leaders and professionals, such as doctors and lawyers 4: Comparable to management and white-collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Proportion of Nonresident 5: 95–100% local Employment 4: 71–95% local 3: 36–70% local 2: 5–35% local 1: Virtually no local crew Crew Experience 5: More than 20 years (skilled career crew) Average years of experience of crew 4: 5–20 years members. 3: 3–5 years 2: 1–3 years 1: 0 full years of experience (mostly new crew each season) Age Structure of Harvesters 5: All working ages are well represented Age range of both captains and their crews. 4: Slightly skewed toward younger or older 3: Skewed toward younger or older 2: Almost entirely younger or older, but working age 1: Harvesters primarily younger or older than working age Source: Anderson and Anderson 2010. lobster �shery is performing well, with all the average scores 3.3 POST-HARVEST PERFORMANCE for each category above the benchmark 3.5. The Indonesia The third component is the processing and marketing sectors BSC �shery performed well in terms of the Boat Owner/ (Post-Harvest Performance). The Post-Harvest Performance Captain but has a huge opportunity for potential improve- components measure success in the market and value chain. ment with regard to Harvest Performance and Harvest Asset Performance. The Philippines BSC �shery does not appear This component includes �ve dimensions, Market Perfor- to have substantial risk exposure, but every other category in mance, Processing and Support Industry Performance, the harvest sector needs to improve substantially. Asset Performance, Processing Owners/Managers, and EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 25 FIGURE 3.11: Crew Processing Workers. The Market Performance dimension captures the effects of handling and processing on the Earnings compared to price received for the product. The Processing and Support national average earnings Industry Performance dimension captures processing ef- 6 Fishery wages �ciency and the extent to which the value of the product Age structure of compared to non-fishery is being maximized. The remaining dimensions reflect harvesters 4 wages wealth accumulation in the processing sector. The Asset 2 Performance dimension captures the wealth accumulating Crew experience 0 Education access to processing capital owners and the extent to which they can and do reinvest in the industry. The Processing Owners Proportion of and Managers and Processing Workers dimensions capture nonresident Access to health care the wealth that goes to each group as income and the extent employment Social standing of to which it supports the �shing communities (Anderson and crew Anderson 2010). Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. 3.3.1 Market Performance The Market Performance is the average of seven indicators shown in table 3.7, measuring the price trend, margin, and market orientation. The U.S. markets and EU markets are the main targets for FIGURE 3.12: Summary of Crew Performance these three �sheries; therefore, the Capacity of Firms to 5.0 Export to those countries, the Final Market Wealth, and Final 4.3 Market Use all receive high scores (�gure 3.14). Indonesia 4.0 3.5 3.3 exports most of their BSC products because BSC is not a 3.0 locally favored species. Only rejected crabmeat product will go to the local market as food or shrimp paste material. The 2.0 wholesale price of BSC depends on the type of crabmeat (usually categorized as Back�n, Lump, Super Lump, Claw, 1.0 Jumbo Lump, and Special). Indonesia BSC received higher 0.0 wholesale price (US$17/lb) ($37.4/kg) than the Philippines Indonesia BSC Philippines BSC Icelandic lobster (US$8 to 10/lb) ($17.6 to $22/kg). The reason for this price Source: Authors. difference is not clear from this quick assessment. One FIGURE 3.13: Summary of Harvest Sector Performance 5.0 4.9 5.0 4.3 4.5 4.3 4.2 4.0 4.0 3.7 3.5 3.2 3.2 3.3 2.7 2.8 3.0 2.0 1.7 1.0 0.0 harvest harvest sector risk exposure owners, permit crew performance asset performance holders & captains Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 26 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.7: Score System for Indicators of Market Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Ex-Vessel Price versus 5: Above 95% Historic High 4: 86–95% The indicator is the ratio of annual ex-vessel 3: 71–85% prices to the average of the three highest annual 2: 50–70% ex-vessel prices in the past 10 years. 1: Below 50% Final Market Use 5: Premium human consumption (premium quality and products) 4: High-value human consumption 3: Moderate-value human consumption 2: Low-value human consumption 1: Fish meal/animal feed/bait or nonconsumptive International Trade 5: 91–100% export 4: 61–90% export Percentage of the �shery’s value that is from �sh 3: 31–60% export exported for consumption. 2: 2–30% export 1: Virtually no export Final Market Wealth 5: Greater than US$35,000 Average per capita GDP of the consumer of a 4: Greater than US$25,000 �shery’s �nal product (pounds weighted by GDP). 3: Greater than US$12,500 (U.S. CIA’s rank of per capita GDP of all countries 2: Greater than US$5,000 https://www.cia.gov/library/publications/the- 1: Less than US$5,000 world-factbook/rankorder/2004rank.html). Wholesale Price 5: More than twice global average Relative to Similar 4: 120–200% of global average Ratio of average price for �sh weight in whole- Products 3: Within 20% of global average sale (primary) �sh product from the base country, 2: 50–80% of global average to a global average for similar species. 1: Less than half global average Capacity of Firms to 5: 96–100% approved Export to the United 4: 71–95% Percentage of a country’s �sh exports that are States and European 3: 36–70% approved for export to the United States or Union European Union. 2: 5–35% 1: Virtually none approved Ex-Vessel to Wholesale 5: Less than 0.3 Ratio of ex-vessel price to wholesale price Marketing Margins 4: 0.3–0.5 (adjusted for standard meat yield rates). To make 3: 0.5–0.8 the adjustment, divide the ex-vessel price by 2: 0.8–0.95 a standard processing yield, and divide by the 1: 0.95 or more wholesale price. Source: Anderson and Anderson 2010. possible reason is the Philippines have a bigger domestic due to the lower price (�gure 3.15). Both the Philippines and market compared to Indonesia for the BSC. However, the Indonesia BSC �sheries have huge opportunities to improve ex-vessel price has dropped over 40 percent compared to their ex-vessel margins. the historic high in Indonesia. One bene�t of the lower price is to broaden the range of consumers. The key issue facing 3.3.1.1 Comments Indonesia and the Philippines BSC �sheries with regard to It can be hard to estimate the average price for some market performance is that the margin pro�t is not highly �sheries because of different product forms. It is sug- captured within these two countries. They both received gested to use the major product form as a representa- the lowest score (1) on Ex-Vessel to Wholesale Marketing tive to calculate. Margins, indicating a potential signi�cant wealth transfer 3.3.2 Processing and Support Industry Performance outside these two countries. The Processing and Support Industry Performance is In summary, the market performance for both Indonesia BSC the average of �ve indicators, Yield of Processed Product, and Iceland lobster �sheries are above the benchmark 3.5. Capacity Utilization Rate, Product Improvement, Regional The Philippines BSC �shery received an average score of 3.3 Support Businesses, and Time to Repair. This group of EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 27 FIGURE 3.14: Market Performance adequate raw material supply in Indonesia and thus is more fully utilized than the Philippines. Ex-vessel price versus historic high In summary, the average performance of the Processing and 5 Ex-vessel to 4 Support Industry in both Indonesia BSC and Icelandic lob- wholesale 3 Final market use ster �sheries are above the benchmark 3.5 (�gure 3.17). Only marketing margins 2 the Philippines BSC �shery received a score of below 3.5. 1 It has substantial room for improvement on the utilization 0 Capacity of firms International rate, yield ef�ciency, and regional support. to export to the trade US & EU 3.3.2.1 Comments Wholesale price Final market With regard to Yield of Processed Product, there relative to similar wealth appears to be some confusion. The de�nition of this products indicator is “Ratio of actual yield (pounds) to the Indonesia BSC Philippines BSC Icelandic lobster maximum yield technically achievable.� The Philippine Source: Authors. expert scored it according to the de�nition. Based on the maximum yield of 30 percent, the Philippines BSC processing yield is 23 percent; therefore, the ratio is 76.7 percent, indicating a score of 2 “within FIGURE 3.15: Summary of Market Performance 25 percent.� The Indonesian expert thought it meant 5.0 what is the maximum they can sell. According to 4.3 their rejection rate of 2 to 5 percent for the processed 4.0 3.7 3.3 crabmeat, they scored 5 since they can sell almost ev- erything they processed. This was not what the score 3.0 intended to do. It is more likely that the Indonesia BSC 2.0 �shery received 2 or 3 for this indicator instead of 5 considering their technology will not be very different. 1.0 However, the rate of yield also depends on the size of the crabs. The bigger the crab, the higher is the 0.0 crabmeat yield. It is suggested to use the average rate Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. if there are a few different forms or sizes. In terms of Regional Support Businesses, the indicators is designed to capture the potential of the value Indonesia expert gave a score of 5 because all of the required equipment for processing is simple and easy chain. The detailed score system is shown in table 3.8. to replace. The Philippines expert gave a score of 1 According to the FPIs scores, the Indonesia BSC is doing because there is no other regional business support. very well in the Processing and Support Industry, with full Regional support has a much broader meaning than scores for all of the indicators (�gure 3.16). This might be due repairing the equipment. It is more than the process- to some misunderstanding of the scale de�nition, which will ing sector itself, including the business environment, be explained below. All of these �sheries achieve full scores transportation, services, and so on. Therefore, it is on Product Improvement because they all target the value- more likely this score for Indonesia is lower, maybe added export market. Both Indonesia and the Philippines 4 or 3 instead of 5. serve as BSC landing and processing centers. They export With the above two corrections, the average score for canned, pasteurized BSCs and frozen BSCs. The speci�ca- the Indonesia BSC �shery will be between 4 and 4.4, tions and packaging come from the order of the buyer or still higher than the benchmark. importer, which are usually large seafood companies. The Time to Repair is usually short because the processing equip- 3.3.3 Post-Harvest Asset Performance ment is not sophisticated. They only need knives, scissors, The Asset Performance is the average of Borrowing Rate and electric pumps. In Indonesia, the processing facilities Relative to Risk-Free Rate, Source of Capital, and Age of open every day except religious holidays (Hari Raya). There is Facilities (table 3.9). AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 28 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.8: Score System for Indicators of Processing and Support Industry Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Yield of Processed Product 5: At feasible frontier Ratio of actual yield (pounds) to the maximum yield 4: Within 5% of the feasible frontier technically achievable. 3: Within 10% 2: Within 25% 1: Less than 75% of maximum yield Capacity Utilization Rate 5: Virtually year-round Days open for processing each year. Such days would 4: 76–95% of days not normally include religious or civic holidays, or weekly 3: 51–75% rest days. 2: 20–50% 1: Less than 20% Product Improvement 5: 76–100% of landings are enhanced Proportion of harvest meat weight going into certi�ed, 4: 51–75% branded, or value-added products. 3: 26–50% 2: 1–25% 1: No landings have enhancements Regional Support Businesses 5: All types of support are plentiful 4: Some types of support are capacity constrained or unavailable 3: Most types of support are capacity constrained or unavailable 2: Support limited to variable inputs 1: Industry support is not locally available Time to Repair 5: Less than a week Days required to make a major mechanical repair to a 4: One week to one month vessel (e.g., blown valve) that requires a replacement 3: One month to less than a season part, including wait time. 2: Full season 1: Major repair not possible Source: Anderson and Anderson 2010. FIGURE 3.16: Processing and Support Industry FIGURE 3.17: Summary of Processing and Support Performance Industry Performance Yield of 5.0 processed 5.0 4.4 product 4.0 5 3.2 4 3.0 3 2 Capacity 2.0 Time to repair 1 utilization rate 1.0 0 0.0 Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Regional Product support improvement businesses Indonesia BSC Philippines BSC Icelandic lobster of from banks or any formal lending agencies, particularly Source: Authors. for the picking plants. For the very few pasteurizing plants, they can get secured loans at the rate of 9 to 16 percent. In Indonesia, the miniplants (picking plants) normally get �nan- Both Indonesia and the Philippines perform well with regard cial support from the processors/exporters. All the facility to the asset performance for post-harvest chain (�gure 3.18). and equipment were supplied by speci�c processors/export- In the Philippines, Sources of Capital for the crabbing indus- ers and became assets of the miniplants. As a return, these try are usually from family savings or informal loans, instead miniplants have to supply to these processors/exporters. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 29 TABLE 3.9: Score System for Post-Harvest Asset Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Borrowing Rate Relative to 5: Less than 1.75; cf. 30-year conforming mortgage Average ratio between the interest rate Risk-Free Rate 4: Less than 2.5; cf. personal bank loan on loans made in the industry to risk- 3: Less than 4; cf. good credit card rates free rates over the last 3 years. 2: Less than 7; cf. bad credit card rates 1: Greater than 7; usury Source of Capital 5: Unsecured business loans from banks/Venture capital Points to be assigned based on 4: Secured business loans from banks/public stock offering category of lenders or investors that is 3: Loans from banks secured by personal (not business) assets/government- most typically used in the processing subsidized private lending/government-run loan programs/international aid sector. agencies 2: Micro lending/family/community-based lending 1: Ma�a/no capital available Age of Facilities 5: Less than 7 years; �rst quarter of expected life Average age of the key durable 4: 7–15 years; second quarter of expected life processing capital unit (plants, catcher- 3: 16–20 years; third quarter of expected life processor vessels). 2: 21–25 years; fourth quarter of expected life 1: Greater than 25 years; exceeding expected life Source: Anderson and Anderson 2010. FIGURE 3.18: Post-Harvest Asset Performance FIGURE 3.19: Summary of Post-Harvest Asset Performance Borrowing rate relative to risk- 5.0 free rate 4.2 4.0 5 4.0 3.3 4 3 3.0 2 1 2.0 0 1.0 Age of facilities Source of capital 0.0 Indonesia BSC Philippines BSC Icelandic lobster Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Source: Authors. There are also very limited government programs called processors and producers� be incorporated into score PNPM (National Program for Community Empowerment) 2 as the situation for the harvest sector. that give small credits to the local community. Because of these types of informal �nancial support, the Borrowing Rate 3.3.4 Processing Owners/Managers Relative to Risk-Free Rate scored high for all of them. They Similar to the dimension for the Boat Owners/Captain, the also performed satisfactorily with regard to Age of Facilities. social status of Processing Owner/Managers is evaluated in In summary, both Icelandic lobster and the Philippines BSC are the same way by using indicators that can give a proxy pic- performing satisfactorily in Post-Harvest Asset Performance ture about their wealth and social sustainability. This dimen- (�gure 3.19). The Indonesia BSC �shery performed close to sion includes six indicators as shown in table 3.10. the benchmark 3.5 due to the low score on Source of Capital. Processing Owners/Managers in Indonesia and Philippines 3.3.3.1 Comments for BSC are generally doing well (�gure 3.20). They have rela- Source of Capital: For developing countries, it is tively good access to education and health care, and make suggested that “contract relationship between the more money than the national average or non�shery. In AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 30 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.10: Score System for Processing Owners/Managers MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Earnings Compared to 5: More than 50% above the national average Ratio of annual earnings from National Average Earnings 4: Between 10 and 50% above national average processing per owner to the national 3: Within 10% above the national average average earnings. 2: Between 50 and 90% of the national average 1: Less than half of the national average Manager Wages Compared to 5: More than 50% above the national average Ratio of managers’ average Non�shery Wages 4: Between 10 and 50% above national average daily wage to average daily wage 3: Within 10% above the national average in region. 2: Between 50 and 90% of the national average 1: Less than half of the national average Education Access 5: Higher education is accessible 4: High school–level education or advanced technical training is accessible 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic education is accessible 1: Formal education is not accessible Access to Health Care 5: Global standard treatment for illness is accessible 4: Licensed doctors provide trauma, surgical, and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of Processing 5: Among the most respected in the community, comparable with civic and reli- Managers gious leaders and professionals, such as doctors and lawyers 4: Comparable to management and white-collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Nonresident Ownership of 5: 96–100% local Proportion of ex-vessel value Processing Capacity 4: 71–95% local processed by regionally owned 3: 36–70% local processing capital. 2: 5–35% local 1: Virtually no local crew Source: Anderson and Anderson 2010. Indonesia, the processing company refers to the processor/ packer/exporter (generally big companies) who buys crab- meat from miniplants, processes, packs, and then exports. In FIGURE 3.20: Processing Owners and Managers a miniplant, the owners usually manage the facility. The aver- age processing capacity is about 500 kilo of raw material per Earnings compared to national average day, resulting in 100 kilo of crabmeat. With a margin pro�t of earnings IDR 5,000/kg5 ($0.6/kg), their daily earnings are IDR 500,000/ 6 6 day ($60/day) or about IDR 15 million per month (US$1,775/ Nonresident 4 Manager wages month). Additionally, some processing plants also process ownership of compared to non- processing capacity 2 fishery wages brangkas (mainly chitin) mostly as feed, which will bring an additional IDR6 million (US$710) per month from sales of 0 wastes. This income level allows the processing owners to Social standing of have the �nancial ability to obtain good medical treatment Education access processing managers or provide for their children higher levels of education (uni- versity). One key difference between these three countries Access to health is the proportion of nonresident ownership. The Philippines care Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. 5 1 US$ = 8450 IDR (http://coinmill.com/IDR_USD.html#USD=1). EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 31 FIGURE 3.21: Summary of Processing Owners/ 3.3.5 Processing Workers Managers The social situation of Processing Workers is reflected by the 5.0 same indicators as the Processing Owner/Managers, plus 4.2 4.3 one indicator on Worker Experience (table 3.11). 4.0 3.7 Icelandic lobster processing workers have good Access to 3.0 Education and Health Care (�gure 3.22). Their wages are relatively better compared to non�shery wages. However, 2.0 Icelandic lobster processing workers have lower social standing. This might be because of the high proportion of 1.0 nonresident employment in this sector in Iceland. Most of 0.0 the processing workers in Iceland are from other countries. Indonesia BSC Philippines BSC Icelandic lobster Indonesia processing worker conditions received a score just Source: Authors. above 3.5, with more experience and better health care ac- cess. The Philippines has room for improvement. This group of indicators basically reflects the situation of processing has the highest local ownership. In Iceland, over half of the workers in each country. They are clear and easy to score. owners are nonresidents. In summary, the conditions facing processing workers In summary, the Processing Owners/Managers performed could be substantially improved in both Indonesia BSC and above the benchmark for all three �sheries (�gure 3.21). The Philippine BSC �sheries (�gure 3.23), particularly on educa- high proportion of nonresident ownership can be a concern tion and health care access, income, and social standing. The for the Icelandic lobster �shery but not an issue for Indonesia conditions are marginally satisfactory for Icelandic lobster and the Philippines BSC �sheries. The Indonesia BSC �shery �shery, but the earnings and social standings are still much needs to raise the social standing for processing managers. below the benchmarks. 3.3.4.1 Comments 3.3.5.1 Comments Nonresident Ownership of Processing Capacity: The Nonresident Ownership of Processing Capacity: It is de�nition of bin 5 is 96 to 100 percent, and bin 4 is 71 suggested to change bin 5 to “91 to 100 percent� and to 95 percent. This leaves bin 5 a very narrow scale bin 4 to “71 to 90 percent� (see Appendix B). that is hard to achieve. For example, Indonesia chose 4, and their explanation is that most of the owners are 3.3.6 Summary local. It is suggested to change bin 5 to “91 to 100 The FPIs reasonably represent the situation of these three percent� and bin 4 to “71 to 90 percent.� �sheries (�gure 3.24) with regard to the Post-Harvest Processing Owner or Manager: Whether FPIs are Sector Performance. The social situation of the processing measuring managers or owners creates some confu- workers is the weakest area for all three �sheries. Indonesia sion because they are two different groups and BSC �shery also needs improvement on Post-Harvest Asset the score for each can be different. For example, in Performance. The Philippines BSC �shery needs substantial Indonesia, owners run the processing facilities. There improvement on Processing and Support Industry. is no manager in miniplants. There are �eld managers/ coordinators whose responsibilities are to supervise When averaging the score for each of the components and oversee quality control. Those �eld managers/ discussed above, a summary of FPIs’ output results can coordinators are hired by the large company to ensure be obtained (table 3.12), which provides a big picture of the their raw material supply. Their annual income is much outcomes and illustrates clearly the ecological, economic, and lower than that of the owners. If all of the scores are social performance for each �shery. In all, the ecological status about processing facility owners, the shape of the of both Indonesia BSC and Philippines BSC �sheries is a critical graph will change, and Indonesia will perform exactly concern. They are below satisfactory to maintain the ecological the same as the Icelandic lobster processing facility sustainability. The harvest sector performance has substantial owners, except Indonesia will have more local own- room for improvement in Indonesia and Philippines BSC �sher- ers. It is suggested to change the title to “Processing ies. The post-harvest sector for all these three �sheries per- owner,� deleting “manager.� forms better than the harvest sector, above the benchmark 3.5. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 32 CH A PTER 3 — FPIs’ A PPLICATION ON B S C FIS H ER IES—OUTPUT R ES ULTS TABLE 3.11: Score System for Processing Workers MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Earnings Compared to 5: More than 10% above the national average Ratio of annual earnings from per National Average Earnings 4: Within 10% above the average processing worker to the national 3: Between 51 and 90% of the average average earnings. 2: Between 25 and 50% of the average 1: Less than 25% of the average Worker Wages Compared to 5: More than 10% above the national average Ratio of workers’ average daily Non�shery Wages 4: Within 10% above the average wage to average daily wage in 3: Between 51 and 90% of the average region. 2: Between 25 and 50% of the average 1: Less than 25% of the average Education Access 5: Higher education is accessible 4: High school–level education or advanced technical training is accessible 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic education is accessible 1: Formal education is not accessible Access to Health Care 5: Global standard treatment for illness is accessible 4: Licensed doctors provide trauma, surgical, and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of Processing 5: Among the most respected in the community, comparable with civic and religious Workers leaders and professionals, such as doctors and lawyers 4: Comparable to management and white-collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Proportion of Nonresident 5: 96–100% local Employment 4: 71–95% local 3: 36–70% local 2: 5–35% local 1: Virtually no local crew Worker Experience 5: More than 20 years (skilled career crew) Average years of experience of 4: 5–20 years workers. 3: 3–5 years 2: 1–3 years 1: 0 full years of experience (mostly new crew each season) Source: Anderson and Anderson 2010. FIGURE 3.22: Processing Workers FIGURE 3.23: Summary of Processing Workers Earnings compared to national average 5.0 earnings 4.0 3.7 5 3.4 4 Worker wages 3.0 Worker experience 3 compared to non- 3.0 fishery wages 2 1 2.0 Proportion of 0 nonresident 1.0 Education access employment 0.0 Indonesia BSC Philippines BSC Icelandic lobster Social standing of Access to health Source: Authors. processing workers care Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 3 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—OUTPUT RES ULTS 33 FIGURE 3.24: Summary of Post-Harvest Sector Performance 5.0 5.0 4.4 4.3 4.0 4.2 4.2 4.3 4.0 3.7 3.7 3.7 3.3 3.2 3.3 3.4 3.0 3.0 2.0 1.0 0.0 market processing & post-harvest processing processing performance support industry asset owners & workers performance performance managers Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. TABLE 3.12: Summary of FPIs’ Output Results COMPONENT INDONESIA BSC PHILIPPINES BSC ICELANDIC LOBSTER FPIs’ Output Ecologically Sustainable Fisheries 1.8 1.3 4.8 Harvest Sector Performance 3.2 3.2 4.6 Post-Harvest Performance 3.9 3.6 4.1 Source: Authors. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 35 Chapter 4: FPIs’ APPLICATION ON BSC FISHERIES— INPUTS RESULTS This chapter will focus on the enabling factors that contribute 4.1.2 Governance—Country Level either the success or the failure of the �sheries. The governance indicator uses the World Bank’s Worldwide Governance Indicators (WGI), which is updated annually since 2002 (World Bank 2011a). It consists of six dimen- 4.1 MACRO FACTORS sions. FPIs regroup them into two categories: Governance The Macro Factors take advantage of the existing indicators Indicator—Effectiveness, taking the average of Government from other sources to capture the General Environmental Effectiveness (GE), Regulatory Quality (RQ), Rule of Law Performance, Economic Condition, and Governance. It also (RL), and Control of Corruption indicators (CC) (four out of includes Exogenous Environmental Factors to capture any six dimensions); and Governance Indicator—Accountability, exogenous shocks. More details are presented as follows. taking the average of Voice and Accountability and Political Stability indicators (two out of six dimensions). The score 4.1.1 General Environmental Performance—Country system is shown in table 4.2. Level Indonesia and the Philippines received 2 or 3 for these two The General Environmental Performance uses the Environ- indicators, indicating the general perceptions regarding the mental Performance Index (EPI) developed by researchers stability, public services, ability to implement sound policies, from Yale University and Columbia University (EPI 2011). con�dence in the quality of property rights, and corruption The EPI tracks 10 policy categories covering both environ- situation in these two countries could be greatly improved mental public health and ecosystem vitality. It has been re- (�gure 4.2). visited biannually since 2006. The score system is de�ned in table 4.1. 4.1.3 Economic Condition—Country Level The economic condition is composed of two economic In 2010, Iceland achieved the highest score (93.6). Indonesia indicators. One is the Index of Economic Freedom (IEF) and the Philippines scored 44.6 and 65.7, respectively. developed by The Heritage Foundation and The Wall Street Therefore, the General Environmental Performance scores Journal to evaluate 10 components of freedom, such as busi- for Iceland, Indonesia, and the Philippines were 5, 3, and 4, ness freedom, investment freedom, trade freedom, labor respectively (�gure 4.1). freedom, �nancial freedom, and so on (table 4.3). Another is TABLE 4.1: Score System for General Environmental Performance MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION General Environmental • 5: EPI of 81–100 The EPI considers factors such as disease, Performance • 4: 61–80 water quality, air pollution, biodiversity, natural • 3: 41–60 resources, and climate change. The EPI ranges from 1–100. • 2: 21–40 • 1: 1–20 Source: Anderson and Anderson 2010. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 36 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS FIGURE 4.1: General Environmental Performance FIGURE 4.2: Country-Level Governance 5.0 5 5.0 4.0 4 4.0 3.0 3 3.0 2 2.0 1 1.0 0 0.0 governance indicator– governance indicator–voice effectiveness & accountability Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Indonesia BSC Philippines BSC Iceland lobster Source: Authors. TABLE 4.2: Score System for Governance—Country Level MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Governance 5: 1st quintile The Governance Indicators (Kaufman, Kraay, and Mastruzzi 2008) assign coun- Indicator—Effectiveness 4: 2nd tries to ranks based on six dimensions. This measure is the average percentile 3: 3rd ranking of the (1) Government Effectiveness, (2) Regulatory Quality, (3) Rule of Law, and (4) Control of Corruption indicators (four out of six dimensions). Assign 2: 4th average percentile to a quintile and give points according to the left criteria. 1: 5th Governance Indicator—Voice 5: 1st quintile The Governance Indicators (Kaufman, Kraay, and Mastruzzi 2008) assign coun- and Accountability 4: 2nd tries to ranks based on six dimensions. This measure is the average percentile 3: 3rd ranking of the (1) Voice and Accountability and (2) Political Stability indicators (two out of six dimensions). Assign average percentile to a quintile and give 2: 4th points according to the left criteria. 1: 5th Source: Anderson and Anderson 2010. TABLE 4.3: Index of Economic Freedom (IEF), 2011 THE PHILIPPINES INDONESIA ICELAND AVERAGE Government Spending 91.0 88.9 0.0 63.9 Fiscal Freedom 78.8 83.0 69.8 76.3 Trade Freedom 77.8 73.8 88.2 74.8 Monetary Freedom 76.3 74.3 68.6 73.4 Labor Freedom 50.7 51.8 60.7 61.5 Financial Freedom 50.0 40.0 60.0 48.5 Business Freedom 43.4 54.9 92.7 64.3 Investment Freedom 40.0 35.0 65.0 50.2 Property Rights 30.0 30.0 90.0 43.6 Freedom from Corruption 24.0 28.0 87.0 40.5 Source: http://www.heritage.org/index/ranking. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 37 TABLE 4.4: Score System for Economic Conditions—Country Level MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Index of Economic Freedom (IEF) 5: IEF of 81–100 The 10 factors are equally weighted and the �nal composite 4: 61–80 index has a range from 1 to 100. A detailed discussion of 3: 41–60 these factors and methodology is found in Miller and Holmes (2009). 2: 21–40 1: 1–20 Gross Domestic Product (GDP) 5: Greater than US$30,000 Bin boundaries based on quintiles of the U.S. CIA’s rank of Per Capita 4: Greater than US$12,400 per capita GDP of all countries (https://www.cia.gov/library/ 3: Greater than US$6,000 publications/the-world-factbook/rankorder/2004rank.html). 2: Greater than US$2,500 1: Less than US$2,500 Source: Anderson and Anderson 2010. FIGURE 4.3: Economic Condition 4.1.3.1 Comments This group of macroeconomic indicators seems to 5.0 adequately characterize the general economic and 4.0 environmental conditions. This macro environment will affect the success of �shery management. It is 3.0 important to understand all these macro constraints 2.0 when designing �shery policies. 1.0 4.1.4 Exogenous Environmental Factors—Country Level 0.0 This group of indicators on Exogenous Environmental index of economic gross domestic product Factors adds a new dimension on the macro factors to cap- freedom (GDP) per capita ture the impact of exogenous environmental shocks. It in- Indonesia BSC Philippines BSC Iceland lobster cludes �ve different aspects, Disease and Pathogens, Natural Source: Authors. Disasters and Catastrophes, Pollution Shocks and Accidents, Level of Chronic Pollution (A), and Level of Chronic Pollution (B) (table 4.5). Gross Domestic Product Per Capita based on the data from These three �sheries are not affected by chronic pollution, the World Bank to evaluate the general wealth situation of a disease, and pathogens (�gure 4.4). The BSC harvests in particular country (World Bank 2011b). The score system is Indonesia and the Philippines are reduced by 10 to 30 per- shown in table 4.4. cent due to natural disasters and catastrophes. Additionally, Iceland has good macro conditions on these two indicators the BSC harvest in Indonesia is affected by pollution shocks (�gure 4.3). Both Indonesia and the Philippines are in the mid- and accidents. This means that even if Indonesia has better range in terms of economic freedom but are relatively low �shery management, they still need to pay attention to other for GDP per capita. The Philippines and Indonesia obtained sectors and the corresponding impact on the �shery. 56.2 and 56 for IEF. Both face serious limitations resulting from corruption, weak property rights, and investment free- 4.1.4.1 Comments dom. Iceland faces serious issues associated with govern- These indicators adequately characterize the general ment spending and �scal and monetary policy (table 4.3). exogenous environmental factors and their impact on Iceland is one of the wealthiest countries in the world the stock and consumption. with per capita GDP of nearly $40,000 per year. The GDP For Pollution Shocks and Accidents, it is suggested in Indonesia is $3,039 per year, and the Philippines GDP is to add “piracy� as this has become an issue for West $2,132 per year. Indian Ocean �sheries. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 38 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS TABLE 4.5: Score System for Exogenous Environmental Factors MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Disease and Pathogens 5: Harvest unaffected by disease 4: Harvest reduced by less than 10% 3: Harvest reduced by less than 10–30% 2: Harvest reduced by more than 30% 1: Harvest almost completely closed by shocks Natural Disasters and Catastrophes 5: Harvest unaffected by disaster 4: Harvest reduced by less than 10% 3: Harvest reduced by less than 10–30% 2: Harvest reduced by more than 30% 1: Harvest almost completely closed by shocks Pollution Shocks and Accidents 5: Harvest unaffected by pollution 4: Harvest reduced by less than 10% 3: Harvest reduced by less than 10–30% 2: Harvest reduced by more than 30% 1: Harvest almost completely closed by shocks Level of Chronic Pollution (A) 5: Not detectable 4: Minimal detectable levels 3: Major detectable levels 2: Pollution affects stock growth 1: Pollution leading to severe stock decline Level of Chronic Pollution (B) 5: No consumption affected 4: Minimal consumption affected 3: Of�cial consumption advisories 2: Temporarily ban harvest for consumption 1: Completely closed for consumption Source: Anderson and Anderson 2010. FIGURE 4.4: Exogenous Environmental Factors FIGURE 4.5: Summary of Macro Factors Disease and pathogens 5.0 5.0 5.0 5 5.0 4.6 4.5 4 4.0 4.2 Level of chronic 3 4.0 2 Natural disasters pollution (B) 1 and catastrophes 3.0 0 3.0 2.5 2.5 2.0 2.0 2.0 Level of chronic Pollution shocks pollution (A) and accidents 1.0 0.0 Indonesia BSC Philippines BSC Iceland lobster country level exogenous country level country level Source: Authors. environmental environmental governance economic performance factors condition Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. For the Level of Chronic Pollution, it is suggested to add “stock effect� and “consumption effect� at the end of each indicator to distinguish each other instead of using “A� and “B� (see Appendix B). the Philippines have substantial room for improvement in gov- 4.1.5 Summary ernance effectiveness and economic conditions (�gure 4.5). In summary, the Icelandic lobster �shery is located in a country None of them experienced severe exogenous environmental with generally high-performing macro factors. Indonesia and shocks. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 39 TABLE 4.6: Score System for Access Rights MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Proportion of Harvest 5: Virtually all The proportion of total harvest that is Managed Under Limited 4: 71–95% under limited-access �shing regulation. Access 3: 36–70% 2: 5–35% 1: Virtually none Transferability Index 5: Very Strong: Fully transferable through well-established, ef�cient market institutions 4: Strong: Fully transferable, but institutions are poor or illiquid 3: Moderate: Transferable, but with severe restrictions on who can hold, or how much 2: Weak: Transferable only under highly restricted and limited condition 1: Access rights not transferable Security Index 5: Very Strong: Access rights are completely respected and are not diluted (e.g., by issuing more Extent to which the government reduces access rights) by the government or dilutes the access rights. 4: Strong: Rights are mostly respected by the government; generally survive changes in govern- ment administration 3: Moderate: Rights are at risk of retraction or dilution with changes in administration 2: Weak: Rights are highly diluted or there is high political uncertainty 1: None: Access rights are not protected Durability Index 5: Very Strong: More than 10 years to perpetuity Duration of the property right. 4: Strong: 6 to 10 years 3: Moderate: 1 to 5 years 2: Weak: Seasonal 1: None: None/daily Flexibility Index 5: Very Strong: All decisions on time of harvest, gear used, and handling practices are in the Ability of right holders to be flexible in owner’s control the timing and production technology 4: Strong: Minimal restrictions on time of harvest and technology employed. 3: Moderate: Modest restrictions on time of harvest and technology 2: Weak: Signi�cant restrictions on time of harvest and technology 1: Time of harvest, gear used, and handling practices are not in the owner’s control Exclusivity Index 5: Very Strong: All decisions and access to the property are controlled by the right’s owner (rath- Ability of right holders to exclude those er than those without rights, competing resource users [like recreational or by-catch �sheries]) who do not have the right from affect- 4: Strong: Little intrusion on resource by those without rights ing the resource or market 3: Moderate: Modest intrusion on resource by those without rights 2: Weak: Signi�cant intrusion on resource by those without rights 1: None: Completely unrestricted open access, despite putative right Source: Anderson and Anderson 2010. 4.2 PROPERTY RIGHTS AND RESPONSIBILITY Flexibility Index, and Exclusivity Index. The score system is The Property Rights and Responsibilities component con- illustrated in table 4.6. sists of Access Rights, Harvest Rights, and Collective Action. Access Rights and Harvest Rights are different. Access The subindicators for Access Rights reflect the basic char- Rights de�ne the rights to access the �shery, which focus on acteristics of any property rights, such as exclusivity, trans- accessibility. Harvest Rights explicitly convey rights to a spe- ferability, security, durability, and flexibility. Icelandic lobster ci�c share or quota of quantity of the harvest. These groups �shery achieved high scores on transferability (5) and flex- of indicators shed light on the characteristics of these rights. ibility (5) but needs substantial improvement on security (3) and durability (3). Both Indonesia and the Philippines BSC 4.2.1 Access Rights �sheries operate under an open access regime. There are no Access Rights is the average of six indicators, including formally de�ned access rights (there are elements of implicit Proportion of Harvest Managed under Limited Access, access rights by tradition) and basically anyone can go �shing Transferability Index, Security Index, Durability Index, whenever they want to. The Philippines BSC �shery has no AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 40 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS FIGURE 4.6: Asset Rights FIGURE 4.7: Summary of Asset Rights Proportion of 5.0 harvest managed 4.2 under limited access 4.0 5 4 3.0 2.5 Exclusivity 3 Transferability index index 2 1.7 2.0 1 0 1.0 Flexibility 0.0 index Security index Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Durability index Indonesia BSC Philippines BSC Iceland lobster Source: Authors. have access rights, they will score 1 for Proportion of Harvest Managed Under Limited Access, but may formally de�ned access rights but received score 5 on the have high scores for other indicators depending on Flexibility Index because there are no constraints on timing, the situation. Informal management, such as �shing gear, or handling (�gure 4.6). agreement, or community-based management, will affect the score, even without of�cial authority. Indonesia has some management in place (e.g., registration), resulting in weak access rights. Vessels of less than 10 GT 4.2.2 Harvest Rights are managed by the district. The provinces deal with ves- Similar to the Access Rights, Harvest Rights measure the sels between 10 and 30 GT, and larger vessels are managed same characteristics but on the harvest aspect. The score on the national level. The local authorities are in charge of system is shown in table 4.7. managing the BSC �sheries as most crab �shermen use no motor or motors under 5 GT. Without national policy or The Icelandic lobster �shery has strong Harvest Rights, but guidance, there are considerable differences in management there is still substantial room for strengthening Security and throughout the country. Some district governments recently Durability (�gure 4.8). For the Philippines BSC �shery, the took initiative to monitor the licensed small-scale vessels Harvest Rights essentially do not exist. The Indonesia BSC (<10 GT), including those used in the BSC �shery. In some �shery has no formal Harvest Rights either, but because of areas the �shermen have self-organized to control the �sh- some management in place there are some weak implicit ing gear used in this �shery. In some districts the miniplants characteristics of harvest rights. encourage better handling and pay premium price for high- In summary, the Icelandic lobster �shery has relatively strong quality product. All these practices have positively affected Harvest Rights. Indonesia and the Philippines BSC �sheries the security, durability, exclusivity, and flexibility scores. have very weak Harvest Rights (�gure 4.9). They received As shown in �gure 4.7, the Icelandic lobster �shery achieved average scores of 2.7 and 1.7, respectively, much below the 4.2, indicating a healthy Access Rights in place. Both benchmark (3.5). The same as Access Rights, the Indonesia Indonesia and the Philippines BSC �sheries have substantial BSC �shery needs to set up total allowable catch (TAC) and room to strengthen their Access Rights. The Indonesia BSC strengthen the harvest exclusivity, durability, flexibility, and �shery needs to limit access and strengthen the asset exclu- transferability. The Philippines BSC �shery could strengthen sivity, durability, flexibility, and transferability. The Philippines every category of their Harvest Rights except flexibility. BSC �shery could strengthen every category of their Access Rights except flexibility. 4.2.2.1 Comments The Harvest Rights indicators seem to adequately 4.2.1.1 Comments reflect the characteristics of these �sheries in terms This group of indicators is clear and easy to under- of harvest share or quota system. They are clearly stand and score. For �sheries where they do not de�ned and easy to score. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 41 TABLE 4.7: Score System for Harvest Rights MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Proportion of Harvest 5: Virtually all The proportion of total harvest that is Managed with Rights-Based 4: 71–95% under rights-based �sheries manage- Management 3: 36–70% ment (e.g., Individual or Community Quotas, Catch Shares or Territorial Use 2: 5–35% Rights [TURFs]). 1: Virtually none Transferability Index 5: Very Strong: Fully transferable through well-established, ef�cient market institutions 4: Strong: Fully transferable, but institutions are poor or illiquid 3: Moderate: Transferable, but with severe restrictions on who can hold, or how much 2: Weak: Transferable only under highly restricted and limited conditions 1: Access rights not transferable Security Index 5: Very Strong: Harvest rights are completely respected and are not diluted (e.g., Extent to which the government reduces by issuing more access rights) by the government or dilutes the access rights. 4: Strong: Rights are mostly respected by the government; generally survive changes in government administration 3: Moderate: Rights are at risk of retraction or dilution with changes in administration 2: Weak: Rights are highly diluted or there is high political uncertainty 1: None: Harvest rights are not protected Durability Index 5: Very Strong: >10 years to perpetuity Duration of the property right. 4: Strong: 6 to 10 years 3: Moderate: 1 to 5 years 2: Weak: Seasonal 1: None: None/daily Flexibility Index 5: Very Strong: All decisions on time of harvest, gear used, and handling practices Ability of right holders to be flexible in are in the owner’s control the timing and production technology 4: Strong: Minimal restrictions on time of harvest and technology employed. 3: Moderate: Modest restrictions on time of harvest and technology 2: Weak: Signi�cant restrictions on time of harvest and technology 1: Time of harvest, gear used, and handling practices are not in the owner’s control Exclusivity Index 5: Very Strong: All decisions and access to the property are controlled by the Ability of right holders to exclude those right’s owner (rather than those without rights, competing resource users [like who do not have the right from affect- recreational or by-catch �sheries]) ing the resource or market. 4: Strong: Little intrusion on resource by those without rights 3: Moderate: Modest intrusion on resource by those without rights 2: Weak: Signi�cant intrusion on resource by those without rights 1: None: Completely unrestricted open access, despite putative right Source: Anderson and Anderson 2010. 4.2.3 Collective Action Influence on Fishery Management and Access (�gure 4.10). The Collective Action is the average of three indicators, in- The stakeholders in Indonesia are proactive, partially because cluding Participation in Harvester Organizations, Harvester of the establishment of Indonesia Blue Swimming Crab Organization Influence on Fishery Management and Access, Processing Association (APRI). APRI consists of 11 process- and Harvest Organization Influence on Business and ing companies and exporters, representing over 90 percent Marketing (table 4.8). This group of indicators measures how of all crab exported from Indonesia to the U.S. market. the local �shing communities participate in the management Currently, APRI, along with Sustainable Fisheries Partnership process. (SFP) have a joint Fisheries Improvement Project (FIP) that has been partly implemented in order to address the de�- Both Icelandic lobster �shery and Indonesia BSC �shery ciencies identi�ed by the MSC Pre-Assessment report and received higher scores than the benchmark in Participation improve the �shery management to meet MSC standards. in Harvester Organizations and Harvester Organization APRI has been actively doing collective action in trying to AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 42 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS FIGURE 4.8: Harvest Rights FIGURE 4.10: Collective Action Proportion of harvest managed Participation in harvester with rights-based organizations management 5 5 4 4 3 Exclusivity 3 Transferability 2 index 2 index 1 1 0 0 Harvester organization Harvester organization influence on business & influence on fishery marketing management & access Flexibility index Security index Indonesia BSC Philippines BSC Iceland lobster Source: Authors. Durability index Indonesia BSC Philippines BSC Iceland lobster Source: Authors. FIGURE 4.9: Summary of Harvest Rights FIGURE 4.11: Summary of Collective Actions 5.0 4.3 5.0 4.0 3.7 4.0 4.0 2.7 3.0 3.0 1.7 2.0 1.3 2.0 1.0 1.0 0.0 0.0 Indonesia BSC Philippines BSC Icelandic lobster Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Source: Authors. TABLE 4.8: Score System for Collective Action MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Participation in Harvester 5: Virtually all Proportion of harvest where the primary har- Organizations 4: 71–95% vesters are organized into associations. 3: 36–70% 2: 5–35% 1: Virtually none Harvester Organization 5: Harvesters effectively determine allocation of resources Subjective measure of how much influence Influence on Fishery 4: Harvesters have signi�cant influence in determining allocation harvesting organizations have, either directly or Management and Access 3: Harvesters are politically active but not controlling through political collective action, on manage- ment and access to the �shery. 2: Social or informal monitoring participation and allocation 1: No active effort or capacity to influence management Harvester Organization 5: Harvesting organizations cooperatively determine marketing and Subjective measure of how much influence Influence on Business and operational details harvesting organizations have, either directly or Marketing 4: Extensive joint marketing through political collective action, on manage- 3: Large subgroups facilitating marketing; joint purchasing ment and access to the �shery. 2: Small subgroups cooperating in purchasing or operations 1: No active effort or capacity to influence business operations Source: Anderson and Anderson 2010. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 43 FIGURE 4.12: Summary of Property Rights rights. Without institutions for well-de�ned rights, responsi- bility and participation improvements in other areas can be 5.0 4.2 4.3 undermined. 4.0 4.0 3.7 4.3 MANAGEMENT 3.0 2.5 2.7 Management consists of three dimensions, Management 2.0 1.7 1.7 1.3 Inputs, Data Management, and Participation. 1.0 4.3.1 Inputs 0.0 Management Inputs is the average of �ve indicators, in- access rights harvest rights collective action cluding Management Expenditure to Value of Harvest, Indonesia BSC Philippines BSC Icelandic Lobster Management Employees to Value of Harvest, Management Source: Authors. Employees per Permit Holder, Research as a Proportion of Fisheries Management Budget, and Level of Subsidies (table 4.9). influence the government and market to improve the sustain- ability of the �shery. The Icelandic lobster �shery obtained full scores for all the management input indicators. Scores correspond to govern- In the Philippines, the local communities have virtually no ment commitments. However, there may be decreasing influence in the management process, indicated by the low returns to scale, so there may be a nonlinear relationship scores in �gure 4.11. Because the �shing ground for the with use of public resources (�gure 4.13). The Philippines BSC �sheries is within the municipal waters (15 km from has virtually no management, subsidies, or research on BSC the shoreline), the jurisdiction is under the local government �sheries, therefore it received high scores for Management units (LGUs). There was no management system in place Expenditure to Value of Harvest and Level of Subsidies, and in most areas, leading weak rights and low participation. low scores for everything else. Indonesia expert did not score Management and regulation of the �sheries are therefore because it was dif�cult to calculate the number of employ- dependent heavily on the initiative of the LGU’s Elected ees, and expenditures related to the BSC �shery manage- Administrators and law-makers. Awareness of marine re- ment. However, because the government does not allocate sources protection is very high, particularly on coastal habi- lots of resources on subsidies and research for BSC �shery tats and lesser on �sheries. Recently, the Philippines govern- in Indonesia, it is possible to score Research as a Proportion ment has drafted �shery management plan for BSC �shery. of Fisheries Management Budget and Level of Subsidies as 5 based on the score system. In summary, both the Icelandic lobster �shery and the Indonesian BSC �shery are characterized by a high level of In summary, the Icelandic lobster �shery has correct stakeholder involvement, with average scores of 3.7 and 4.3, magnitude of management inputs (�gure 4.14). Both the respectively. However, they both need to improve their influ- Philippines BSC �shery and Indonesia BSC �shery need to ence on �shery management and access. The Philippines strengthen management inputs. Some positive progress has BSC �shery needs to substantially strengthen their stake- been made by the Philippines government by drafting and holders’ participation in every aspect. consulting their �shery management plan. In the future, the score will be changed. 4.2.3.1 Comments The Collective Actions indicators are clear and easy to 4.3.1.1 Comments score. They adequately reflect the degree of stake- The main concern is whether this group of indicators holders’ participation. is informative and useful enough given the dif�culty in accessing the data. Research as a Proportion of 4.2.4 Summary Fisheries Management Budget can be important In summary, Icelandic lobster adopted an Individual because that can provide some basic data about the Transferable Quota (ITQ) system and therefore has strong �sheries and in turn help with policy and decision property rights, reflected in strong Access Rights and Harvest making. Level of Subsidies is important because it will Rights (�gure 4.12). Both the Philippines and Indonesia BSC directly affect the harvest cost of �shing and exploita- have considerable opportunity to strengthen their property tion level and thus sustainability. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 44 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS TABLE 4.9: Score System for Management Inputs MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Management Expenditure to 5: Less than 5% of ex-vessel value This measure divides the budget (million $) for �sheries Value of Harvest 4: 5–25% management by the ex-vessel value of the harvest. 3: 26–50% 2: 51–100% 1: More than the value of harvest Management Employees to 5: More than 0.35 per million Public sector �shery management employee FTEs devoted Value of Harvest 4: 0.26–0.35 to managing the �shery divided by the ex-vessel value of 3: 0.16–0.25 the harvest. 2: 0.01–0.15 1: 0 Management Employees per 5: 4 or more per 100 permit holders Fishery management FTE employees divided by the num- Permit Holder 4: 3 per 100 permit holders ber of �shing units (in 100s) (vessels or permit holders). 3: 2 per 100 permit holders 2: 1 per 100 permit holders 1: 0 Research as a Proportion 5: Over 20% Research expenditures divided by total �sheries manage- of Fisheries Management 4: 11–20% ment budget. Budget 3: 6–10% 2: 0.5–5% 1: Virtually none Level of Subsidies 5: Near zero (less than 2.5%) Measure the annual value of all subsidies as a proportion 4: 2.5–7.5% of the value of the �shery. 3: 7.6–12.5% 2: 12.6–20% 1: More than 20% Source: Anderson and Anderson 2010. FIGURE 4.13: Management Inputs FIGURE 4.14: Summary of Management Inputs Management 5.0 expenditure to 5.0 value of harvest 5 4.0 3.7 4 3 3.0 2.6 Management Level of 2 employees to Subsidies 1 value of harvest 2.0 0 1.0 Research as a Management 0.0 proportion of fisheries employees per management budget Indonesia BSC Philippines BSC Icelandic lobster permit holder Source: Authors. Indonesia BSC Philippines BSC Iceland lobster Source: Authors. Management Employees to Value of Harvest and Management Employees per Permit Holder can be tricky and dif�cult to score, especially for a single �sh- To make it easier to score for Management Expenditure ery when the management employees have to deal to Value of Harvest, it is suggested to change the with multiple species. It is suggested to delete these de�nition to “Government, industry and aid agency two indicators (see Appendix B). expenditures on �shery management activities includ- Additionally, enforcement has been a common issue ing research, enforcement, and management capacity for many developing countries’ �sheries. They often development (but not infrastructure)� (see Appendix B). have rules but lack enforcement. Therefore, it is EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 45 suggested to add Enforcement Capacity as one indica- FIGURE 4.15: Data Management tor in Management Input (see Appendix B). 5 For many �shery species, it is hard to avoid the transboundary issue. Whether there is an effective 4 regional coordination will affect the success of one 3 country’s �shery management. It is suggested to add 2 Management Jurisdiction to capture this issue (see Appendix B). 1 4.3.2 Data Management 0 data availability data analysis The dimension of Data Management is composed of Data Availability and Data Analysis (table 4.10). For many coun- Indonesia BSC Philippines BSC Iceland lobster Source: Authors. tries, lack of data collection and analysis is common, which directly affects the effectiveness of management. The idea of including these indicators is to promote the proper data collection system. The Icelandic lobster �shery industry has put �nancial sup- port for the �shery management, accounting over half of the According to the FPIs evaluation, the Icelandic lobster �shery �shery management budget, but the people who are active collects and fully utilizes data (�gure 4.15). The Indonesia BSC in management only spend less than 5 days in stakeholder �shery has some data, but not enough analysis for decision meetings per year (�gure 4.16). Both Indonesia and the making. The Philippines BSC �shery has very limited data Philippines BSC industries give virtually no support for �shery from the government. However, universities have studied management. The participation of the stakeholder meetings the BSC population and have some measurement of MSY, in Indonesia BSC �shery management is slightly higher than biological parameters, and even genetic stocks. There is still that in the Philippines but still less than one day a month. substantial room for improvement in this category. 4.3.3.1 Comment 4.3.2.1 Comment These two data indicators are simple, clear, and easy These two data indicators are simple, clear, and easy to score. to score. 4.3.4 Summary 4.3.3 Participation In summary, the Icelandic lobster �shery has consider- The Participation dimension is the average of Days in able management inputs and data collection, but with Stakeholder Meetings and Industry Financial Support for limited participation (�gure 4.17). Management inputs for Management. The score system is illustrated in table 4.11. Philippines BSC �shery are minimal. Both data collection and TABLE 4.10: Score System for Data Management MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Data Availability 5: Regular stock assessment and economic data available 4: Landings and price data available 3: Only landing data available 2: Only boat registration and license data available 1: No data is tracked Data Analysis 5: Biological and economic data used in prospective analysis of management 4: Biological data dominate simple prospective analysis 3: Biological or economic data are used to track performance retrospectively 2: Data are used inconsistently or irregularly 1: No data analysis conducted in management process Source: Anderson and Anderson 2010. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 46 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS TABLE 4.11: Score System for Participation MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Days in Stakeholder Meetings 5: More than 24 days per year Days in stakeholder meetings per year spent 4: 12–24 by a participant in the �shery who is active in 3: 6–11 management. 2: 1–5 1: None Industry Financial Support for 5: Virtually all Proportion of the �shery management budget Management 4: 51–95% paid for by the �shing sector. 3: 6–50% 2: 1–5% 1: None Source: Anderson and Anderson 2010. FIGURE 4.16: Participation called Community which includes Leadership and Social Cohesion into the FPIs (see 5.0 Appendix B). 4.0 Gender is another dimension that has not been in- 3.0 cluded. Women can play an important role in different aspects, but the role of women as pure work labor 2.0 will be different from the role of women as business 1.0 managers or policy makers. Therefore, it is suggested 0.0 to add a group of indicators related to gender by ex- days in stakeholder meetings industry financial support for amining the role and degree of women’s influence in management harvest, post-harvest, and management. Indonesia BSC Philippines BSC Iceland lobster With new indicators, it is suggested to restruc- Source: Authors. ture the indicators by adding a new component Co-Management separate from Management. participation in the Philippines and Indonesia BSC �sheries are Co-Management will include Collective Action, very low. Participation, Community, and Gender (see Appendix B). Under Management, it is also suggested to add 4.3.4.1 Comments another dimension on Management Methods, includ- Leadership and social cohesion were left out in ing MPAs and Sanctuaries, Spatial Management, and the FPIs. Considering the importance of these two Fishing Mortality Limits, to measure whether differ- aspects, it is suggested to add a new dimension, ent management methods are in place to protect the FIGURE 4.17: Summary of Management 5.0 5.0 5.0 4.0 3.7 3.0 3.0 2.6 2.5 2.0 1.5 1.5 1.5 1.0 0.0 inputs data participation Indonesia BSC Philippines BSC Icelandic Lobster Source: Authors. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 47 critical spawning area and period, spatial access rights, In summary, the Icelandic lobster �shery just meets the and mortality control. See Appendix B for detailed benchmark. Both Indonesia and the Philippines BSC �sheries de�nition and scale for each of them. perform below the benchmark, particularly the Philippines BSC �shery has substantial opportunities for improvement 4.4 POST-HARVEST INPUTS in terms of price, information sharing, and export conditions (�gure 4.19). The Post-Harvest Inputs component includes two dimen- sions, Market and Market Institutions and Infrastructure, to 4.4.1.1 Comments measure the economic and physical infrastructure availability This group of indicators is clearly identi�ed and easy for sustainable wealth creation. to score. They adequately reflect the Post-Harvest inputs in each �shery. 4.4.1 Market and Market Institution The ability to access competitive, free markets will give 4.4.2 Infrastructure buyers and sellers an unbiased and ef�cient price. This is Good infrastructure is essential for successful business essential for participants to allocate resources ef�ciently. as it can help reduce the production and transportation A well-established market with a transparent pricing sys- cost. The FPIs measure a few key aspects of infrastruc- tem will facilitate the success of this sector. Market and ture related to �sheries business. Infrastructure Input is Market Institution is the average of Landings Pricing System, the average of International Shipping Service, Road Quality Availability of Ex-Vessel Price and Quantity Information, Index, Technology Adoption, Extension Service, Reliability Number of Buyers, Degree of Vertical Integration, Level of of Utilities/Electricity, and Access to Ice and Refrigeration Tariffs, and Level of Nontariff Barriers (table 4.12). (table 4.13). Nontariff barriers are not a major factor in any of these three Iceland has good infrastructure to support the �shery busi- �sheries (�gure 4.18). Iceland sells their lobster to the EU ness (�gure 4.20). Indonesia BSC has relatively good inter- market with virtually no tariff, much lower than the 15 per- national shipping, ice access, and reliability of utilities, but cent tariff both Indonesia and the Philippines have to pay the road quality, extension service, and technology adop- when exporting to the United States. However, Icelandic lob- tion require substantial improvement. Regarding Extension sters are purchased by a small number of coordinated buy- Service, Indonesia expert scored this indicator as 1 because ers, less competitive than the BSC market. In Indonesia, the there was no extension service provided by the government. miniplant will follow wherever the boat lands and buy all the All the trainings are provided by the processors/exporters. crabs captured at the competitive beach prices with subtrac- The Philippines expert thought any kind of extension service tion of transportation cost. Because of the high demand, it counted, so this indicator scored 2. In Indonesia, ocean/air is dif�cult to get enough raw materials, the processing com- shipping is readily available. Cell phone is the main equip- panies are competing to get the products from miniplants. ment for the �eld manager to get the raw material from the Most of the companies sent their �eld staff to ensure they miniplant. Regarding the Reliability of Utilities/Electricity, have enough supply from miniplants. Regarding the vertical most of the processing facilities have generators as backup integration, the Indonesia BSC �shery scored 3, the Icelandic for electricity outage in Indonesia. But in the Philippines, lobster �shery scored 2 and the Philippines BSC �shery only some picking plants and pasteurizing plants can afford scored 1. This is because most miniplants belong to the pro- large generators. With better Technology Adoption ability, cessor/exporter from the beginning. They were built and set more Reliable Utilities/Electricity and Ice Supply, Indonesia up to supply speci�c exporters/processors. Miniplants have is more prepared for international trade. Both Indonesia and been strengthened during the past several years and have the Philippines need to improve their road quality as this will become very important players in the crab business. Now affect their transportation cost and competitiveness in the most of the miniplants are operating independently and do business. not have any obligation to supply to any speci�c processing companies. The Availability of Ex-Vessel Price and Quantity In summary, the Icelandic lobster �shery has the best infra- Information is still not transparent in both Indonesia and the structure to support (�gure 4.21). The Indonesia BSC �shery Philippines. The �shermen rarely depend on the miniplant for just meets the benchmark criteria, and the Philippines BSC the price information. �shery needs to improve the infrastructure for every dimen- AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 48 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS TABLE 4.12: Score System for Market and Market Institution MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Landings Pricing System 5: Virtually all Proportion of the harvest sold in a transparent 4: 71–95% daily competitive pricing mechanism, such as 3: 36–70% an auction or centralized ex-vessel to whole- sale market. 2: 5–35% 1: Virtually none Availability of Ex-Vessel Price 5: Complete, accurate price and quantity information available to market and Quantity Information participants immediately 4: Reliable price and quantity information is available prior to the next market clearing 3: Price information is available but no timely quantity information 2: Price and quantity information are inaccurate, lagged, or available to only a few 1: No information available Number of Buyers 5: Highly competitive Typical number of buyers of ex-vessel product 4: 4–6 buyers in a given market. 3: 2–3 competing buyers 2: A small number of coordinating buyers 1: There is one buyer Degree of Vertical Integration 5: Virtually all Proportion of harvest where the primary 4: 71–95% harvester and primary processor/distributor are 3: 36–70% the same �rm. 2: 5–35% 1: Virtually none Level of Tariffs 5: Virtually none Based on quintile once data on an appropriate 4: 0.5–2.5% number of systems are collected. However, ini- 3: 2.6–5% tially tariff rate on key seafood exports relative to international average for food commodities. 2: 6–10% 1: Over 10% Level of Nontariff Barriers 5: Are not used to limit international trade Nontariff barriers include quantity restrictions 4: Have very limited impact on international trade (import quotas), regulatory restrictions, invest- 3: Act to impede some international trade ment restrictions, customs restrictions, and direct government intervention. 2: Act to impede a majority of potential international trade 1: Act to effectively impede a signi�cant amount of international trade Source: Anderson and Anderson 2010. FIGURE 4.18: Market and Market Institution Landings pricing system 5 FIGURE 4.19: Summary of Market and Market 4 Institution Level of non- 3 Availability of ex-vessel price & quantity 5.0 tariff barriers 2 information 1 4.0 3.5 0 3.2 3.0 2.3 Level of Number of tariffs buyers 2.0 1.0 Degree of vertical integration 0.0 Indonesia BSC Philippines BSC Iceland lobster Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. Source: Authors. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 4 — F P I s ’ AP P L ICAT ION ON BSC F ISHE RIES—INPUTS RES ULTS 49 TABLE 4.13: Score System for Infrastructure MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION International Shipping 5: Ocean/Air shipping services are readily available at lower than average rates Average of the two measures (one for Service 4: Ocean/Air shipping services are readily available at average rates ocean shipping and another one for air 3: Ocean/Air shipping services are readily available at higher than average rates shipping) on the left. 2: Ocean/Air shipping services are available but irregular 1: International shipping is not available at reasonable rates Road Quality Index 5: High-quality paved roads and extensive highways Mile-weighted average road quality 4: Primarily paved two-lane roads and moderate highway between the �shery’s primary port and 3: Primarily paved two-lane roads and minimal highway its major consumption center (or export shipping port for exported product). 2: Paved two-lane roads and well-graded gravel roads Score according to the left. 1: Poorly maintained gravel or dirt roads Technology Adoption 5: Cell phones/�sh �nders/computers/processing/production technology are readily available 4: Cell phones/�sh �nders, and so forth, are common, but some other technology is not always available 3: Cell phones/�sh �nders, and so forth, are common, but some other technology is dif�cult to obtain 2: Cell phones are common, but most other technology is prohibitive 1: Very little advanced technology is accessible for the industry Extension Service 5: Broad extension service with �eld of�ces and close linkage with research community 4: Extension service with moderate �eld coverage and adequate linkage with the research community 3: Extension service, but with weak links to the research community 2: Minimal, poorly supported extension service 1: No extension service Reliability of Utilities/ 5: Electricity readily available with rare outages Electricity 4: Electricity readily available with less than six short outages per year 3: Electricity readily available with less than two outages per month 2: Electricity readily available with more than two outages per month 1: Electricity is not available except through generators Access to Ice and 5: Ice is readily available in various forms Refrigeration 4: Ice is readily available in various forms with occasional shortages 3: Ice is available in limited quantity/form (e.g., block only) 2: Ice is available in very limited quantity/form 1: Ice is unavailable Source: Anderson and Anderson 2010. sion, including the road, ice supply, electricity, and shipping hard to achieve for many developing countries. It is services. suggested not to use number of outage as the criteria. The suggested scale will be more vague but easy to 4.4.2.1 Comments understand and score, such as 5: Reliable electrical Road Quality Index: For archipelagic countries, grid provides power in suf�cient quantity to prevent domestic and interisland shipping should also be product loss; 4: Processors rely on grid, but maintain considered. It is suggested to change the indicator to backup generators; 3: Supply chains rely on own Transportation Quality Index to capture both road and generation capacity; 2: Supply chain sometimes loses other types of transportation (see Appendix B). product due to condition or irregular fuel supply for Extension Service: It is suggested to add “private sec- generators; 1: Reliable generators or fuel supply not tor initiated extension services� into the explanation available (see Appendix B). (see Appendix B). Access to Ice and Refrigeration: This indicator can add Reliability of Utilities/Electricity: For many develop- affordability of ice for �shermen and the relative cost ing countries, electricity outage is common. The of ice compared to the selling price to get a better benchmark is more likely for developed countries, and sense about the ice use situation and understand why AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 50 C H A PTER 4 — FPIs’ A PPLICATION ON B S C FIS H ER IES—INPUT S R ES ULTS FIGURE 4.20: Infrastructure FIGURE 4.21: Summary of Infrastructure International 5.0 4.7 shipping service 5 4.0 3.5 4 3.0 2.3 Access to ice 3 Road quality & refrigeration 2 index 2.0 1 0 1.0 0.0 Reliability of Technology adoption Indonesia BSC Philippines BSC Icelandic lobster utilities/electricity Source: Authors. Extension service The Indonesia BSC �shery has better post-harvest inputs Indonesia BSC Philippines BSC Iceland lobster but fewer inputs on the management and property rights Source: Authors. aspects besides a relatively weak macro environment. The Philippines BSC �shery has a slightly better macro environ- ment but limited inputs on every other aspects, including it is not always available or used. It is suggested to re- vise the indicators to reflect the affordability, such as property rights, management, and post-harvest inputs. 5: Ice is available in various forms and in suf�cient ca- pacity to support fresh icing of all �sh that needs to be FIGURE 4.22: Summary of Post-Harvest iced; 4: Ice is available in various forms, but quantity limits prevent applying to entire catch throughout sup- 5.0 4.7 ply chain; 3: Ice is available in limited form and quan- 4.0 3.5 3.5 tity, and thus applied only to most valuable portions of 3.2 catch; 2: Ice is available but capacity constrained; ice 3.0 2.3 2.3 often reused, or used through melting stage; 1: Ice 2.0 quantities are extremely limited (see Appendix B). 1.0 4.4.3 Summary 0.0 In summary, the Post-Harvest Inputs for the Icelandic lobster markets & market infrastructure �shery are characterized as adequate infrastructure, trans- institutions parent price and quantity information, limited competition on Indonesia BSC Philippines BSC Icelandic lobster purchasing, and relative low vertical integration (�gure 4.22). Source: Authors. The Indonesia BSC �shery is characterized as high tariff, lack of price and quantity information, relatively good ice and en- ergy supply, but received low scores on road and extension TABLE 4.14: Summary of FPIs’ Output Results service. The Philippines BSC �shery is characterized as high INDONESIA PHILIPPINES ICELANDIC tariff, lack of price and quantity information, less competitive COMPONENT BSC BSC LOBSTER purchasing market, primary vertical integration, inadequate FPIs Macro Factors 2.9 3.3 4.9 ice and energy supply, inadequate road, shipping services, Input Property 2.9 1.6 4.2 and extension services. Rights and Responsibility When averaging the score for each of the components dis- Management 2.6 1.9 4.3 cussed above, a summary of FPIs Input Factor results can be Inputs obtained (table 4.14), which provides a picture of the input Post-Harvest 3.3 2.3 4.1 factors. In all, the Icelandic lobster �shery has high inputs. Inputs Source: Authors. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 5 — C O NCL USIONS 51 Chapter 5: CONCLUSIONS 5.1 REGARDING THE STUDIED FISHERIES opportunity to improve. All the rest have substantial room for The results of FPIs for the Indonesia BSC and the Philippines improvement, including the Harvest Sector, Boat Owners/ BSC �sheries, along with the comparison with Icelandic lobster Captains, Processing and Support Industry and Processing �shery give a clear picture regarding the governance, social, Workers. The Fish Stock and Environmental Performance economic, and ecological situation in these �sheries. Three received the lowest score and is in urgent need of attention critical benchmarks have been presented. One benchmark is to reverse the situation. the score of 3.5. Any score under 3.5 indicates a substantial Figure 5.2 summarizes the average indictor scores for the improvement potential. One benchmark is the score of 2. Any wealth input factors. Icelandic lobster �shery received high score under 2 indicates a warning sign. Emergent actions need scores for most of the categories, including environmental to be taken. The third benchmark is another �shery, such as performance, good governance, good infrastructure, well- the Icelandic lobster �shery in this case. The following summa- established data collection system, and considerable �shery rizes the results for both output indicators and input indicators. management inputs (expenditures and personnel). However, Figure 5.1 illustrates the average scores for the wealth indi- the participation of the �shing industry in �shery manage- cators. The Icelandic lobster �shery received high scores ment is low and market institution is around the edge. for all the categories except for the Processing Workers. As The Indonesia BSC �shery does not face exceptional risk analyzed above, it is because of the high proportion of non- from exogenous environmental shocks. The infrastructure resident workers who have relatively lower wages and lower and market institution are marginally acceptable. However, social standings. the majority of the input factors may create signi�cant con- The Indonesia BSC �shery received relatively high scores straints to enabling economic, ecological, and community in the Processing and Support Industry and Market, margin- sustainability. The macro factors, such as country-level gov- ally acceptable scores in the Boat Owners/Captains, Fishing ernance, the economic conditions, and environmental perfor- Crews, Processing Owners/Managers, Processing Workers, mance scored poorly and may undermine the long-term suc- and Risk Exposure. The Harvest Sector Asset Performance cess of the BSC industry. Access rights and harvest rights, and Post-Harvest Asset Performance have room for substan- such as individual or community quotas or catch shares, are tial improvement. The scores for Harvest Performance and not formally de�ned. The data collection system is not set Fish Stock Health and Environmental Performance are within up. All these contribute to limiting the accomplishment of the the warning zone, suggesting an urgent need to improve �sh triple bottom line. stock health and harvest performance. In the long run, sus- The Philippines BSC �shery has relatively acceptable envi- tainability of the �shery is at risk, and high scores for other ronmental performance and exogenous environmental shock categories will be undermined. is not an inordinate risk. Most of the other enabling factor The Philippines BSC �shery showed relative better scores suggest weak governance and economic conditions, risk exposure, satisfactory performance for Processing and under investment in access rights and harvest rights, Owners/Managers and Post-Harvest Assets. The Market data collection and analysis, the market institutions, and the Performance, Crew and Boat Owners/Captains have an basic infrastructure. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 52 C H A PTER 5 — C ON C LUS IONS FIGURE 5.1: Summary of FPIs’ Output—Measuring Wealth Fish stock health & environmental performance Processing 5 Harvest workers 4 performance Processing owners & 3 Harvest sector asset managers 2 performance 1 0 Post-harvest asset performance Risk exposure Owners, permit Processing & support holders & captains industry performance Market Crew performance 3.5 Benchmark Indonesia BSC Philippines BSC Icelandic lobster Warning zone Source: Authors. FIGURE 5.2: Summary of FPIs’ Input—Enabling Wealth Country level environmental performance 5 Exogenous Infrastructure environmental 4 factors Markets & market 3 Country level institutions governance 2 1 Participation Country level 0 economic condition Data Access rights Inputs Harvest rights Collective action 3.5 Benchmark Indonesia BSC Philippines BSC Icelandic lobster Source: Authors. 5.2 REGARDING THE FISHERY PERFORMANCE and economic status of the �sheries management systems. INDICATORS (FPIs) FPIs are useful and powerful tools for �shery project moni- The application of the FPIs to the Indonesia and Philippine toring and evaluation. Because the cost of applying this is BSC �sheries and the Icelandic lobster �sheries was re- relatively low, only a few local experts who know the �shery markably successful. Furthermore, the feedback from the well and who understand some basic economics and statis- research workshop in May 2011 and the decision meeting tics are needed to �ll out the FPIs survey form. in November 2011 were very positive and encouraging. FPIs are well organized and easy to apply. The rapid assessment Based on the case study and comments received from the result can give a clear indicator about the ecological, social, decision meeting, a few indicators need to be modi�ed, EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) C H A P T E R 5 — C O NCL USIONS 53 several scalings of the indicators need to be improved, and The Bank is moving to enhance its activity related to the some omissions need to be added, particularly on the eco- oceans, and the FPIs will have great value in identifying key logical output indicators and management and comanage- target �sheries and measuring progress. At maturity, the ment input indicators. These have been revised6 and the FPIs 6 7 FPIs could be implemented and accessed via a dashboard are ready to be scaled up. containing hundreds of �sheries, with data collected at regu- lar intervals to monitor sustainable wealth-creating �sheries FPIs could serve as a tool to benchmark and monitor all the within and across management systems. The idea, logic, and �shery projects in the World Bank. A detailed FPI assess- design of the indicators can help develop a broadened set ment for each targeted country will assist management de- that can be applied to codependent �shery-aquaculture and cisions for all the target �shery projects regardless of their aquaculture management systems. implementation status. For projects that are in the planning stage, the output will help identify the strengths and weak- Above all, the impact of these indicators is potentially trans- nesses of the �sheries and thus enable the identi�cation formative. They will be effective levers to promote changes of evidence-based policy suggestions. For projects under and suggest what changes should be made to result in implementation, the output will help measure their effective- sustainable improvement in the �shery, the economic condi- ness in improving �shery performance. tions, and community status. 6 After the decision meeting, all of the above suggestions have been integrated into the FPIs’ survey sheets. A few case studies have been done since November 2011, including Uganda Nile perch and tilapia �sheries, Gambia sole �shery, Seychelles arti- sanal and semi-industrial �sheries, and Ghana artisanal �sheries. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 55 Appendix A: FISHERY PERFORMANCE INDICATORS— MANUAL A.1.1.3 Percentage of Stocks Over�shed FISHERY PERFORMANCE RATIONALE: The percentage of stocks considered to be over- INDICATORS—OUTPUT �shed reflects the extent to which over�shing has compro- mised the ability to generate wealth. Over�shed stocks can- A.1. ECOLOGICALLY SUSTAINABLE FISHERIES not be harvested at a level that maximizes wealth until they A.1.1 Fish Stock Health and Environmental Performance are recovered. A.1.1.1 Proportion of Harvest with a Third-Party PROPOSED MEASURE: Percentage of commercial stocks within Certi�cation the management authority’s purview that are considered RATIONALE: Fish stocks must be sustainable to generate sus- over�shed, to be experiencing over�shing, or in generally tainable returns and create wealth. Certi�cation also may be unknown stock status (whether actively managed or not): 5: essential for market access in developed countries. None over�shed; 4:1~25 percent of stocks over�shed; 3:26 to 50 percent over�shed; 2: 51 to 75 percent over�shed; 1: PROPOSED MEASURE: The proportion of harvest (quantity) harvest- 76 to 100 percent over�shed. ed under one of the recognized third-party programs that cer- tify ecological sustainability, such as the Marine Stewardship A.1.1.4 Nonlandings Mortality Council (MSC) certi�cation. Individual stocks are weighted by RATIONALE: Nonlandings mortality is a direct measure of waste their proportion of landings value: 5: 76 to 100 percent of land- and potentially foregone wealth. This represents �sh that ings are certi�ed; 4: 51 to 75 percent; 3: 26 to 50 percent; 2: possibly could have been sold, but were not. 1 to 25 percent; 1: No landings have third-party certi�cation. PROPOSED MEASURE: Ratio of estimated mortality of the as- A.1.1.2 Fish Stock Sustainability Index sessed target species from illegal harvest, by-catch, illegal RATIONALE: Fish stocks must be sustainable to generate sus- discards, regulatory (legal) discards, and other nonlandings tainable returns and create wealth. waste to actual landings. PROPOSED MEASURE: The Fish Stock Sustainability Index. The Bin boundaries can be established by quintile once data are FSSI is calculated by assigning a total score between 0 and collected on many �sheries. For the pilot studies, the bound- 4 to each priority �sh stock. Note: The number of priority aries will be coarsely established by the following table: 5: stocks will differ between management systems (The Fish Virtually none; 4: Less than 5 percent; 3: 5 to 10 percent; 2: Stock Sustainability Index 2009). 10 to 20 percent; 1: More than 20 percent. For each of four components, each stock receives: 1) one point if the status of the stock is over�shed or subject to A.2. HARVEST SECTOR PERFORMANCE over�shing; 2) two points if management measures are A.2.1 Harvest Performance succeeding at preventing over�shing; 3) three points if the stock biomass is above the level de�ned as over�shed for A.2.1.1 Landings Level the stock; and 4) four points if the stock is rebuilt or is at its RATIONALE: Harvests at the level of maximum economic yield “optimal� level, within 80 percent of that required to achieve (MEY) reflect management and/or harvest policies that re- maximum sustainable yield. The FSSI is computed by sum- flect economic goals. This is primarily a measure of the ex- ming the scores of the individual stocks. Points by quintile tent to which the �shery is realizing its potential wealth over relative to the maximum possible score; with 5 points for time, ensuring the future reproductive value remains in the highest quintile. water. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 56 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L PROPOSED MEASURE: Average annual harvest over the last A.2.1.4 Ratio of Asset Value to Gross Earnings 3 years. Note: in practice there are very few estimates of RATIONALE: In addition to income, �shery wealth can also accu- MEY, however where it has been calculated it is typically 5 mulate to the harvesters through the value of the assets that to 10 percent less than maximum sustainable yield (MSY). allow access and participation in the �shery. The price of the Bin boundaries can be established by quintile once data are privilege or right to access a �shery in the form of a vessel, collected on many �sheries. For the pilot studies, the bound- license, lease, or quota, is a direct measure of the accumu- aries will be coarsely established by the following table: 5: lation of wealth from the �shery to the harvest sector. The Harvest is less than MSY (stock is above MSY level) to in- price of access should reflect the present discounted value crease pro�t; 4: Harvest is approximately at MSY; 3: Harvest of the stream of pro�ts arising from accessing the �shery. reduced to promote recovery (stock is below MEY level); 2: This will include expectations for changes in management, Harvest is constraining stock recovery (stock is stable below harvest levels, prices, and harvesting costs. Gross earnings MEY level); 1: Harvest is causing over�shing (stock is below is used to normalize the asset value to the levels of the �sh- MEY and declining). ery. Gross earnings are a proxy for net earnings because cost data are rarely available, and this normalization is standard in A.2.1.2 Excess Capacity agricultural frameworks. For a �xed level of gross earnings, if the �shery’s income is highly uncertain, or costs are exces- RATIONALE: Excess capacity in the �shing fleet reflects man- sive, then the ratio will be lower. agement that has either allowed the stock to decline so that a once-ef�cient harvesting operation scale is now too PROPOSED MEASURE: Ratio of average price of access to the large, or that has induced a derby wherein harvesters have �shery over the last 5 years to the average annual landings had to purchase inef�ciently large vessels, or both. These value for a similarly scaled access right in the same period. inef�ciently large vessels are more expensive to operate and Same business or same family sales are excluded, where maintain than necessary, reducing wealth in the harvesting they can be identi�ed. The highest bin boundary was estab- sector. lished by calculating the rate of return for large-scale farming operations in the United States, reflecting a stable industry PROPOSED MEASURE: Estimated standardized vessels-days re- where key inputs are controlled by the business owner: 5: 10 quired to catch the maximum economic yield (MEY) com- or higher; 4: 7.5 to 10; 3: 5 to 7.5; 2: 2.5 to 5; 1: 2.5 or below. pared to the number of standardized vessel-days available. Days are considered not to be restricted by trip limits. Bin boundaries can be established by quintile once data are col- A.2.2 Asset Performance lected on many �sheries. For the pilot studies, the bound- A.2.2.1 Total Revenue versus Historic High aries will be coarsely established by the following table: 5: RATIONALE: If the �shery is generating wealth, it is expected Within 5 percent of days required; 4: 105 to 120 or 90 to 95 that the total revenue for the �shery is likely to increase to percent; 3: 120 to 150 percent or 75 to 90 percent; 2: 150 to some sustainable maximum range. Fisheries with declining 200 percent or 50 to 75 percent; 1: More than 200 percent, total revenue are likely to be in decline as a result of over�sh- or less than 50 percent, of days required. ing, poor marketing, and distribution. In contrast, a �shery managed for wealth creation should be harvested sustain- A.2.1.3 Season Length ably, and the sector is likely to orient toward market access RATIONALE: The length of the season reflects the extent to and innovation. This should be observable in stable or in- which management allows harvesters to determine when to creasing total revenue. harvest and how much. Choosing how and when to harvest PROPOSED MEASURE: The indicator is the ratio of total revenue allows harvesters to land when the prices are highest, or to to the average of the three highest total revenues in the past spread the harvest over a long period of time to stabilize ex- 10 years. 5: Above 95 percent; 4: 85 to 95 percent; 3: 70 to vessel prices at high levels, and allow processors to time 85 percent; 2: 50 to 70 percent; 1: Below 50 percent. product flow to implement ef�cient methods. A.2.2.2 Asset (Permit, Quota, etc.) Value versus PROPOSED MEASURE: Ratio of number of days on which �sh- Historic High ing occurs to the number of days the species is available RATIONALE: If the �shery is generating wealth, it is expected in economically feasible quantities: 5: Virtually no regulatory that the value of the permit, quota, or other right to the �sh- closures; 4: 91 to 99 percent; 3: 50 to 90 percent; 2: 11 to 50 ery is likely to increase to some sustainable maximum range. percent; 1: Less than 10 percent. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 57 Fisheries with declining assets are likely to be in decline as �shery and reinvested in capital. Second, it is a measure of a result of over�shing, poor marketing, distribution, or other the potential wealth in the �shery, as newer facilities will be constraints to innovation. In contrast, a �shery managed for more ef�cient and less costly to operate. Third, if harvesters wealth creation should be harvested sustainably; the sector are willing to invest in new capital, it reflects their assess- is likely to orient toward improved marketing and innovation. ment that the �shery will be pro�table into the future. Finally, if new facilities are funded by private loans, newer facilities PROPOSED MEASURE: The indicator is the ratio of asset to the reflect the capital markets’ assessment that the �shery is average of the three highest asset values in the past 10 suf�ciently low risk to warrant investment. years. 5: Above 95 percent; 4: 85 to 95 percent; 3: 70 to 85 percent; 2: 50 to 70 percent; 1: Below 50 percent. PROPOSED MEASURE: Average age of the key durable harvest- ing capital unit (vessels, weirs): 5: Capital is new; 4: Capital A.2.2.3 Borrowing Rate Relative to Risk-Free Rate is older but well maintained, e.g., freshly painted; 3: Capital RATIONALE: The size of the premium the capital market de- is moderately well maintained; 2: Maintenance is poor; 1: mands to make loans in the �shery is a direct measure of Serious concerns about seaworthiness or safety throughout �nancial risk in the industry. It is locally normalized to reflect �shery. the overall riskiness in the region and the opportunities avail- able to local capital. A.2.3 Risk PROPOSED MEASURE: Average ratio between the interest rate A.2.3.1 Annual Total Revenue Volatility on loans made in the industry to risk-free rates over the last RATIONALE: Annual total revenue volatility is primarily a mea- 3 years. Bin boundaries are based on the ratio of consumer sure of the riskiness of the �shery. When future harvests loan rates for different types of rates to the regional 10-year are variable, it is dif�cult to make investment decisions and risk-free rate (3.60 percent for U.S. T-bill; example ratios be- secure capital because future income streams are highly un- low): 5: Less than 1.75; cf. 30-year conforming mortgage; 4: certain. High landings volatility also presents an obstacle to Less than 2.5; cf. personal bank loan; 3: Less than 4; cf. good developing �nal product markets in nonspecialty �sheries, as credit card rates; 2: Less than 7; cf. bad credit card rates; 1: large processors and exporters prefer to deal with products Greater than 7; usury. for which they can develop long-term contracts. A.2.2.4 Source of Capital PROPOSED MEASURE: Ratio of the standard deviation of the �rst RATIONALE: Whether lending capital from a particular source differences of annual total revenue to the mean total revenue is even available is a direct measure of how the capital mar- over the last 10 years. Bin boundaries should be established ket assesses risk in the �shery. If a certain type of lender or by quintile once data are collected on many �sheries. Pilot investor is not willing to make capital available in the �shery study boundaries were established by calculating the score at any price, it reveals the �shery is much riskier than other for each country-�sh category (�n�sh, shell�sh, and crusta- available investments. This measure is less re�ned than the ceans only) in FishStat (FAO), then determining the quintile relative rate, but much easier to obtain. values7: 5: 0.14 or less; 4: 0.15 to 0.21; 3: 0.22 to 0.39; 2: 8 0.40 to 0.99; 1: 1 or greater. PROPOSED MEASURE: Points to be assigned based on the cat- egory of lenders or investors that is most typically used in the A.2.3.2 Annual Landings Volatility �shery. Points assigned as follows: 5: Unsecured business RATIONALE: Annual landings volatility is primarily a measure of loans from banks/venture capital; 4: Secured business loans the riskiness of the �shery. When future harvests are vari- from banks/public stock offering; 3: Loans from banks se- able, it is dif�cult to make investment decisions and secure cured by personal (not business) assets/government-subsi- capital because future income streams are highly uncertain. dized private lending/government-run loan programs/interna- High landings volatility also presents an obstacle to develop- tional aid agencies; 2: Microlending/family/community-based ing �nal product markets in nonspecialty �sheries, as large lending; 1: Ma�a/no capital available. processors and exporters prefer to deal with products for A.2.2.5 Functionality of Harvest Capital which they can develop long-term contracts. RATIONALE: The functionality of the vessels and other capital used in harvesting (e.g., weirs, traps, docks/marinas, and ice production) reflects wealth in several ways. First, it is a di- 7 This approach uses more highly aggregated �sheries than are likely to be used in case studies. This probably results in lower rect measure of wealth that has been accumulated from the variance, and thus biases our bins toward lower scores. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 58 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L PROPOSED MEASURE: Ratio of the standard deviation of the �rst future income streams are highly uncertain. High price volatil- differences of annual total landings sold to the mean landings ity may reflect obstacles to developing �nal product markets over the last 10 years. Bin boundaries should be established in nonspecialty �sheries, as large processors and exporters by quintile once data are collected on many �sheries. Pilot prefer to deal with products for which they can develop long- study boundaries were established by calculating the score term contracts. for each country-�sh category (�n�sh, shell�sh and crusta- PROPOSED MEASURE: Ratio of the standard deviation of the ceans only) in FishStat (FAO), then determining the quintile �rst differences of annual ex-vessel price to the mean price values8: 5: 0.14 or less; 4: 0.15 to 0.21; 3: 0.22 to 0.39; 2: over the last 10 years. Bin boundaries should be established 9 0.40 to 0.99; 1: 1 or greater. by quintile once data are collected on many �sheries. Pilot A.2.3.3 Intra-Annual Landings Volatility study boundaries were established by calculating the score RATIONALE: High-frequency (weekly or monthly, as available) for each country-�sh category (�n�sh, shell�sh, and crusta- landings volatility is primarily a measure of the potential for ceans only) in FishStat (FAO), then determining the quintile wealth generation in the �shery. High volatility may reflect a values10: 5: 0.12 or less; 4: 0.13 to 0.19; 3: 0.20 to 0.30; 2: 11 seasonality of the availability of the �sh for harvest, or man- 0.31 to 0.84; 1: 0.85 or greater. agement that limits the harvest season directly, or induces A.2.3.5 Intra-Annual Price Volatility a derby. Spikes in landings during certain parts of the year RATIONALE: Intra-annual price volatility complements intra- hinder wealth creation in several ways. First, concentrat- annual harvest volatility to capture the wealth generation ing landings in a short period spikes supply and often sup- potential in the �shery. Price changes arise from: 1) shifts presses ex-vessel prices. Second, processing capacity must in demand stemming from seasonal changes in tastes (e.g., be established to handle the spikes, and if it is not applied traditional holiday �sh dishes) or 2) changes in supply stem- to other �sheries, it will be underutilized and costly per unit ming from the seasonal availability of �sh or management- processed. Third, spikes in processing volume often compro- induced periods of high effort. If price volatility is high, un- mise the yield and quality of the processed product. Finally, constrained harvesters could shift landings from a period of intra-annual volatility can make it dif�cult for processors to low price to a period of higher price and increase �shery rent. make forward contracts for their products; thus they receive Periods of high landings at low prices are associated with lower prices. �shing derbies and the problems associated with high intra- PROPOSED MEASURE: Ratio of the standard deviation of the annual landings volatility. weekly/monthly total sold landings over the last 3 years to PROPOSED MEASURE: Ratio of the standard deviation of average the mean landings. Observations of zero landings are includ- monthly ex-vessel price over the last 3 years to the mean. ed if there is biological availability. If the biological season is Observations of zero landings are included if there is biologi- so short that there is not meaningful variation at a monthly cal availability. If the biological season is so short that there is level, this measure can be NA.9 Bin boundaries should be not meaningful variation at a monthly level, this measure can 10 established by quintile once data are collected on many �sh- be NA. Bin boundaries should be established by quintile once eries. Absent monthly landings data on a range of �sheries, data are collected on many �sheries. Absent monthly price the pilot study uses the same bins as for Annual Landings data on a range of �sheries, the pilot study uses the same Volatility: 5: 0.14 or less; 4: 0.15 to 0.21; 3: 0.22 to 0.39; 2: bins as for Annual Price Volatility11: 5: 0.12 or less; 4: 0.13 to 12 0.40 to 0.99; 1: 1 or greater. 0.19; 3: 0.20 to 0.30; 2: 0.31 to 0.84; 1: 0.85 or greater. A.2.3.4 Annual Price Volatility A.2.3.6 Spatial Price Volatility RATIONALE: Annual price volatility complements annual har- RATIONALE: The extent to which ex-vessel price for the same vest volatility to capture the wealth generation potential in product varies across different ports within the �shery re- the �shery. When future revenues are variable, it is dif�cult flects market integration and opportunities for arbitrage to make investment decisions and secure capital because 10 This approach uses more highly aggregated �sheries than are 8 This approach uses more highly aggregated �sheries than are likely to be used in case studies. This probably results in lower likely to be used in case studies. This probably results in lower variance, and thus biases our bins toward lower scores. variance, and thus biases our bins toward lower scores. 11 This approach uses more highly aggregated �sheries than are 9 More precisely prescribing the circumstances under which this likely to be used in case studies. This probably results in lower should be NA will be determined in the case studies. variance, and thus biases our bins toward lower scores. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 59 across space within the �shery. A market that is well inte- following table: 5: More than 50 percent above the national grated spatially will have similar prices at different ports, average; 4: Between 10 and 50 percent above national aver- whereas isolated landings ports or ports that are differentially age; 3: Within 10 percent of the national average; 2: Between well connected to markets, and therefore posing greater �- 50 and 90 percent of the national average; 1: Less than half nancial risk, will have higher levels of spatial volatility. the national average. PROPOSED MEASURE: Ratio of the standard deviation across A.2.4.2 Fishery Wages Compared to Non�shery Wages data collection regions12 of average annual ex-vessel price 13 RATIONALE: This is a direct measure of �shery-produced wealth to the mean. Measure should be averaged over last 3 years. accumulating to harvesters. Scaling wages by average local Bin boundaries should be established by quintile once data earnings reflects whether the �shery is able to attract the are collected on many �sheries. Absent spatial price data on most talented workers in the community and is doing well at a range of �sheries, the pilot study uses the same bins as wealth generation relative to local standards. Here, the local for Annual Price Volatility13: 5: 0.12 or less; 4: 0.13 to 0.19; 3: 14 standard is the local wage, rather than national income lev- 0.20 to 0.30; 2: 0.31 to 0.84; 1: 0.85 or greater. els, which could pick up important rural/urban differences in A.2.3.7 Contestability and Legal Challenges heterogeneous countries. RATIONALE: Legal challenges, protests, and contentious public PROPOSED MEASURE: Ratio of captain’s average daily wage hearings reflect discontent with the management system. It to average daily wage in region/country. Bin boundaries is an indicator of a lack of social acceptance and a source of can be established by quintile once data are collected on considerable risk. many �sheries. For the pilot studies, the boundaries will PROPOSED MEASURE: 5: No signi�cant legal challenges, civil ac- be coarsely established by the following table: 5: More tions, or protests regarding the �shery management system; than 50 percent above the national average; 4: Between 4: Minor legal challenges slow implementation; 3: Legal chal- 10 and 50 percent above national average; 3: Within 10 lenges, civil actions, or protests impede some management percent of the national average; 2: Between 50 and 90 measures; 2: Legal challenges, civil actions, or protests sus- percent of the national average; 1: Less than half the na- pend major elements of the management system; 1: Legal tional average. challenges, civil actions, or protests suspend or prohibit implementation of key management reforms and regulation. A.2.4.3 Educational Access RATIONALE: A community that is successfully using its resourc- A.2.4 Owners, Permit Holders, and Captains es will be able to provide high levels of education to its chil- dren, ensuring a step beyond resource dependence in the A.2.4.1 Earnings Compared to National Average Earnings next generation. If capture �shing is an important part of this RATIONALE: This is a direct measure of �shery-produced community, the boat owners or captains’ families will have wealth accumulating to owners of harvesting capital. Scaling access to education. earnings by national average earnings reflects whether the �shery is able to attract the most talented workers in the PROPOSED MEASURE: Measure is based on the highest level community and is doing well at wealth generation relative to of education that is politically, culturally, and �nancially ac- national standards. cessible to families of harvesters, rather than the actual at- tainment levels of current harvesters. 5: Higher education is PROPOSED MEASURE: Ratio of annual earnings from �shing per accessible; 4: High school–level education or advanced tech- owner to the national average earnings. In many cases, the nical training is accessible; 3: Middle school–level education captain is an owner of a vessel or permit, but in other cases, or simple technical training is accessible; 2: Basic literacy and captains are considered as crew. Bin boundaries can be es- arithmetic education is accessible; 1: Formal education is not tablished by percentile once a range of data is collected. For accessible. the pilot studies, the boundaries will be established by the A.2.4.4 Health Care Access 12 Data collection regions can either be �shery relevant or politically RATIONALE: A community that is successfully using its resourc- relevant. De�ning this generally allows local standards to estab- es will be able to provide high levels of health care, ensuring lish which is most important. a quality of life and decreasing health risk. If capture �shing is 13 This approach uses more highly aggregated �sheries than are an important part of this community, harvester’s families will likely to be used in case studies. This probably results in lower variance, and thus biases our bins toward lower scores. have access to the best available health care. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 60 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L PROPOSED MEASURE: Measure is based on the quality of health captain is an owner of a vessel or permit, but in other cases, care that is politically, culturally, and �nancially accessible to captains are considered as crew. Bin boundaries can be es- harvesters. 5: Global standard treatment for trauma and ill- tablished by percentile once a range of data are collected. For ness is accessible; 4: Licensed doctors provide trauma, sur- the pilot studies, the boundaries will be established by the gical, and drug treatments; 3: Nurses or medical practitioners following table: 5: More than 10 percent above the average; provide emergency and routine drug treatments; 2: First aid 4: Within 10 percent of the average; 3: Between 60 and 90 and basic drug (e.g., penicillin) treatment is accessible; 1: percent of the average; 2: Between 25 and 50 percent of the Science-based health care is not accessible. average; 1: Less than 25 percent of the average. A.2.4.5 Social Standing of Boat Owners and Permit A.2.5.2 Fishery Wages Compared to Non�shery Wages Holders RATIONALE: Crew wage is a direct measure of the �shery RATIONALE: This is a proxy for income associated with boat and wealth that accumulates to crew. It is normalized by wages permit ownership, which may be much easier to collect than typical of the region to provide a relative standard of living actual income information. It also allows informal incorpora- afforded to crew, and also reflect whether the �shery is able tion of part-time harvesting jobs into other careers. Social to attract the most skilled workers. standing reflects whether the �shery is able to attract the PROPOSED MEASURE: Ratio of crew’s average daily wage to av- most talented workers in the community and is doing well at erage daily wage in region/country. Bin boundaries can be wealth generation relative to local standards. established by quintile once data are collected on many �sh- PROPOSED MEASURE: 5: Among the most respected in the com- eries. For the pilot studies, the boundaries will be coarsely munity, comparable with civic and religious leaders and pro- established by the following table: 5: More than 10 percent fessionals, such as doctors and lawyers; 4: Comparable to above the average; 4: Within 10 percent of the average; 3: management and white-collar jobs; 3: Comparable to skilled Between 60 and 90 percent of the average; 2: Between 25 labor jobs; 2: Comparable to unskilled blue-collar or service and 50 percent of the average; 1: Less than 25 percent of jobs; 1: Among the least respected, such as slaves or inden- the average. tured servants. A.2.5.3 Educational Access A.2.4.6 Proportion of Nonresident Employment RATIONALE: A community that is successfully using its re- RATIONALE: The ability of a country or region to improve itself sources will be able to provide high levels of education to using its resources depends on its ability to maintain local mul- its children, ensuring a step beyond resource dependence tipliers by keeping wealth within the region. A large portion of in the next generation. If capture �shing is an important part nonresident harvesters reflects that much of the harvesting of this community, harvesters’ families will have access to wealth will be leaving the region, failing to boost the regional education. economy. In developing regions, it may also reflect an inability PROPOSED MEASURE: Measure is based on the highest level of of local resource users to generate suf�cient capital to harvest. education that is politically, culturally, and �nancially accessi- PROPOSED MEASURE: 5: 95 to 100 percent local; 4: 71 to 95 per- ble to families of harvesters, rather than the actual attainment cent local; 3: 36 to 70 percent local; 2: 5 to 35 percent local; levels of current harvesters. 5: Higher education is accessible; 1: Virtually no local harvesters. 4: High school–level education or advanced technical train- ing is accessible; 3: Middle school–level education or simple A.2.5 Crew technical training is accessible; 2: Basic literacy and arithmetic education is accessible; 1: Formal education is not accessible. A.2.5.1 Earnings Compared to National Average Earnings A.2.5.4 Health Care Access RATIONALE: This is a direct measure of �shery-produced wealth RATIONALE: A community that is successfully using its resourc- accumulating to crew. Scaling earnings by average national es will be able to provide high levels of health care, ensuring earnings reflects whether the �shery is able to attract the a quality of life and decreasing health risk. If capture �shing is most talented workers in the community and is doing well at an important part of this community, harvesters’ families will wealth generation relative to local standards. have access to the best available health care. PROPOSED MEASURE: Ratio of annual earnings from �shing per PROPOSED MEASURE: Measure is based on the quality of health owner to the national average earnings. In many cases, the care that is politically, culturally, and �nancially accessible to EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 61 harvesters. 5: Global standard treatment for trauma and ill- believe the future to be worthwhile and that they will have ness is accessible; 4: Licensed doctors provide trauma, sur- the means to succeed to captain. gical, and drug treatments; 3: Nurses or medical practitioners PROPOSED MEASURE: Average years of experience of crew provide emergency and routine drug treatments; 2: First aid members. Bin boundaries can be established by quintile and basic drug (e.g., penicillin) treatment is accessible; 1: once data is collected on many �sheries. For the pilot stud- Science-based health care is not accessible. ies, the boundaries will be coarsely established by the fol- A.2.5.5 Social Standing of Crew lowing table: 5: More than 20 years (skilled career crew); 4: 5 to 20 years; 3: 3 to 5 years; 2: 1 to 3 years; 1: 0 full years of RATIONALE: This is a proxy for income associated with crewing experience (mostly new crew each season). on �shing boats, which may be much easier to collect than actual wage information. It also allows informal incorporation A.2.5.8 Age Structure of Harvesters of part-time harvesting jobs into other careers. Social stand- RATIONALE: A widely distributed age structure is an indirect ing reflects whether the �shery is able to attract the most tal- measure of several key variables. Broadly, it reflects both ented workers in the community and is doing well at wealth that experienced older crew is willing to stay in the �shery, generation relative to local standards. possibly as captains, and that younger crew members are PROPOSED MEASURE: 5: Among the most respected in the com- willing to enter and that job opportunities in the �shery are munity, comparable with civic and religious leaders and pro- available. First, it reflects wealth accumulation to crew be- fessionals, such as doctors and lawyers; 4: Comparable to cause an experienced crew member will only stay in the management and white-collar jobs; 3: Comparable to skilled �shery, and a new crew member will only enter, if the wage labor jobs; 2: Comparable to unskilled blue-collar or service is comparable to, or better than, other jobs he could obtain. jobs; 1: Among the least respected, such as slaves or inden- Second, crew longevity often means the crew are resident tured servants. in the community, and thus their earnings stay in the com- munity and are spent locally, rather than being sent away A.2.5.6 Proportion of Nonresident Employment by itinerant or immigrant crews. Third, experienced crew de- RATIONALE: The ability of a country or region to improve itself velop specialized knowledge and re�ned skills that make har- using its resources depends on its ability to maintain local vesting more ef�cient, so the �shery is better able to reach multipliers by keeping wealth within the region. A large por- its wealth-generating potential. Finally, many crew will only tion of nonresident harvesters reflects that much of the har- enter (young) or stay in (older) the �shery if they believe the vesting wealth will be leaving the region, failing to boost the future to be worthwhile and that they will have the means to regional economy. In developing regions, it may also reflect succeed to captain. an inability of local resource users to generate suf�cient capi- PROPOSED MEASURE: Age range of both captains and their tal to harvest. crews: 5: All working ages are well represented; 4: Slightly PROPOSED MEASURE: 5: 95 to 100 percent local; 4: 71 to 95 per- skewed toward younger or older; 3: Skewed toward younger cent local; 3: 36 to 70 percent local; 2: 5 to 35 percent local; or older; 2: Almost entirely younger or older, but working age; 1: Virtually no local crew. 1: Harvesters primarily younger or older than working age. A.2.5.7 Crew Experience RATIONALE: The rate at which the crew force turns over in the A.3. POST-HARVEST PERFORMANCE �shery is an indirect measure of several key variables. First, it A.3.1 Market Performance reflects wealth accumulation to crew because a crew mem- A.3.1.1 Ex-Vessel Price versus Historic High ber will only stay in the �shery if the wage is comparable RATIONALE: If the �shery is generating wealth, it is expected to, or better than, other jobs he could obtain. Second, crew that the orientation of the �shery will shift from competing longevity often means they are resident in the community, for �shery resource access, to market access and develop- and thus their earnings stay in the community and are spent ment. This should be observable in stable or increasing ex- locally, rather than being sent away by itinerant or immigrant vessel prices. crews. Third, experienced crew develop specialized knowl- edge and re�ned skills that make harvesting more ef�cient, PROPOSED MEASURE: The indicator is the ratio of annual ex- so the �shery is better able to reach its wealth-generating vessel prices to the average of the three highest annual ex- potential. Finally, many crew will stay in the �shery if they vessel prices in the past 10 years. 5: Above 95 percent; 4: AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 62 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L 85 to 95 percent; 3: 70 to 85 percent; 2: 50 to 70 percent; 1: global average for similar species: 5: More than twice global Below 50 percent. average; 4: 120 to 200 percent global average; 3: Within 20 percent of global average; 2: 50 to 80 percent of global aver- A.3.1.2 Final Market Use age; 1: Less than half global average. RATIONALE: The use of the �shery product that is �nally con- sumed reflects the extent to which the �shery, its process- A.3.1.6 Capacity of Firms to Export to the United States ing, and trade products are maximizing the potential value and European Union from the resource. RATIONALE: Companies with unreliable, low-quality, or unsecure supply chains may not be able to export to the United States PROPOSED MEASURE: 5: Premium human consumption (pre- or European Union without detention. The more freely a com- mium quality and products); 4: High-value human consump- pany can export to the United States or European Union, the tion; 3: Moderate-value human consumption; 2: Low-value broader the market. Access reflects the success of quality human consumption; 1: Fish meal/animal feed/bait or control systems and breadth of market. It is also a measure of nonconsumptive. the �nancial risk associated with international trade. A.3.1.3 International Trade PROPOSED MEASURE: Percentage of a country’s �sh exports RATIONALE: Maximizing the wealth generation potential of a that are approved for export to the United States or European �shery requires delivering the product to the people who val- Union: 5: 95 to 100 percent approved; 4: 71 to 95 percent; ue it most. The level of exports reflects how well the �shery 3: 36 to 70 percent; 2: 5 to 35 percent; 1: Virtually none has maximized its wealth potential by accessing the market approved. that is willing to pay the most for the product globally. A.3.1.7 Ex-Vessel to Wholesale Marketing Margins PROPOSED MEASURE: Percentage of the �shery’s value that is RATIONALE: The value added by processing and marketing at from �sh exported for consumption: 5: 90 to 100 percent the wholesale level is a direct measure of wealth accumula- export; 4: 61 to 90 percent export; 3: 31 to 60 percent export; tion in the processing sector. When compared across prod- 2: 2 to 30 percent export; 1: Virtually no export. ucts, it can also represent how well a �shery is realizing the A.3.1.4 Final Market Wealth maximum potential value from its landed �sh. RATIONALE: The income of the people who �nally consume the PROPOSED MEASURE: Ratio of ex-vessel price to wholesale price �shery product reflects the extent to which the �shery, its (adjusted for standard meat yield rates). To make the adjust- processing, and trade products are maximizing the poten- ment, divide the ex-vessel price by a standard processing tial value from the resource. Products that are being sold in yield, and divide by the wholesale price. Bin boundaries can wealthier countries are competing favorably, reflecting high- be established by quintile once there is data on a range of quality, effective marketing, and are drawing wealth to the �sheries. For the pilot studies, the following table can be �shery. used: 5: Less than 0.3; 4: 0.3 to 0.5; 3: 0.5 to 0.8; 2: 0.8 to PROPOSED MEASURE: Average per capita GDP of the consumer 0.95; 1: 0.95 or more. of a �shery’s �nal product (pounds weighted by GDP). (U.S. CIA’s rank of per capita GDP of all countries https:// A.3.2 Processing and Support Industry Performance www.cia.gov/library/publications/the-world-factbook/ A.3.2.1 Yield of Processed Product rankorder/2004rank.html): 5: Greater than US$35,000; 4: RATIONALE: Processing yield is a measure of the potential value Greater than US$25,000; 3: Greater than US$12,500; 2: of the landed �sh that is being realized as wealth. Yield will Greater than US$5,000; 1: Less than US$5,000. likely be higher in more ef�cient processing operations and those with a steady supply of landed product where there is A.3.1.5 Wholesale Price Relative to Similar Products time to take more care in processing and develop downline RATIONALE: The extent to which a country’s �shing industry is customers who will pay a premium for reliable forward con- realizing its wealth generation potential is captured by com- tracts for premium products. They may also be able to turn paring the price that country receives with the price for sub- processing by-products (bones, blood) into revenue streams, stantially similar products in other countries. increasing value per landed weight. PROPOSED MEASURE: Ratio of average price for �sh weight in PROPOSED MEASURE: Ratio of actual yield (pounds) to the maxi- wholesale (primary) �sh product from the base country, to a mum yield technically achievable. Bin boundaries can be EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 63 established by quintile once there is data on a range of �sh- PROPOSED MEASURE: 5: All types of support are plentiful; 4: eries. For the pilot studies, the following table can be used: Some types of support are capacity constrained or unavail- 5: At feasible frontier; 4: Within 5 percent of the feasible fron- able; 3: Most types of support are capacity constrained or tier; 3: Within 10 percent; 2: Within 25 percent; 1: Less than unavailable; 2: Support limited to variable inputs; 1: Industry 75 percent of maximum yield. support is not locally available. A.3.2.2 Capacity Utilization Rate A.3.2.5 Time to Repair RATIONALE: In many �sheries, a hindrance to wealth accumu- RATIONALE: The amount of time required to make a major re- lation is an excess of capital, even in processing. This may pair, including especially that to acquire parts, reflects how occur because the �shery was once larger than it is now and well the �shery is connected to the infrastructure necessary it is dif�cult to downsize plants, or because management or to maintain capital. Because this connectedness arises when biology forces landings to be concentrated in a short period there is a market for capital maintenance services, this cap- of time. Potential wealth is then consumed in maintaining a tures how well the �shery is adopting new, ef�cient technol- larger than necessary facility, or in tying up capital in a facility ogies that maximize wealth generation. It is also a measure that is not used to full capacity. In �sheries where landings of riskiness of capital investment, as the ability to effectively and processing are concentrated within a short season, this maintain new capital is critical to extracting and preserving inef�ciency may be compounded by using processing tech- its value. nology at a rate that does not support high yields when land- PROPOSED MEASURE: Days required to make a major mechani- ings are occurring. cal repair to a vessel (e.g., blown valve) that requires a re- PROPOSED MEASURE: Days open for processing each year. Such placement part, including wait time: 5: Less than a week; days would not normally include religious or civic holidays, 4: One week to one month; 3: One month to less than a or weekly rest days. Bin boundaries can be established by season; 2: Full season; 1: Major repair not possible. quintile once there is data on a range of �sheries. For the pi- lot studies, the following table can be used: 5: Virtually year- A.3.3 Post-Harvest Asset Performance round; 4: 75 to 95 percent of days; 3: 51 to 75 percent; 2: 21 A.3.3.1 Borrowing Rate Relative to Risk-Free Rate to 50 percent; 1: Less than 20 percent. RATIONALE: The size of the premium the capital market de- mands to make loans in the processing sector is a direct A.3.2.3 Product Improvement measure of �nancial risk in the industry. It is locally normal- RATIONALE: One way processors can maximize the value of a ized to reflect the overall riskiness in the region and the op- product is to market it with improvements that make it more portunities available to local capital. appealing to the consumer, who will then pay more for the product. Sale with a certi�cation, value-enhancing branding, PROPOSED MEASURE: Average ratio between the interest rate or value-added processing can increase wholesale and retail on loans made in the industry to risk-free rates over the last prices, and thus the wealth brought to the �shery. 3 years. Bin boundaries are based on the ratio of consumer loan rates for different types of rates to the regional 10-year PROPOSED MEASURE: Proportion of harvest meat weight going risk-free rate (3.60 percent for U.S. T-bill; example ratios be- into certi�ed, branded, or value-added products: 5: 76 to 100 low): 5: Less than 1.75; cf. 30-year conforming mortgage; 4: percent of landings are enhanced; 4: 51 to 75 percent; 3: Less than 2.5; cf. personal bank loan; 3: Less than 4; cf. good 26 to 50 percent; 2: 1 to 25 percent; 1: No landings have credit card rates; 2: Less than 7; cf. bad credit card rates; 1: enhancements. Greater than 7; usury. A.3.2.4 Regional Support Businesses A.3.3.2 Source of Capital RATIONALE: The strength of the marine support sector is im- RATIONALE: Whether lending capital from a particular source is portant to realizing the maximum potential wealth through even available is a direct measure of how the capital market ef�cient harvesting. Sales in the support sector are a di- assesses risk in the �shery’s processing sector. If a certain rect measure of wealth accumulation in the support sector. type of lender or investor is not willing to make capital avail- However, they also reflect the ability of the �shery to access able in the processing sector at any price, it reveals that it is and adopt new technology to make harvesting more ef�cient much riskier than other available investments. This measure and pro�table, and the propensity for the �shery to do so, as is less re�ned than the relative rate but is much easier to sales to harvesters support these businesses. obtain. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 64 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L PROPOSED MEASURE: Points to be assigned based on catego- A.3.4.2 Manager Wages Compared to Non�shery Wages ry of lenders or investors that is most typically used in the RATIONALE: The processing owner or manager wage is a direct processing sector. Points assigned as follows: 5: Unsecured measure of �shery wealth that accumulates to processing business loans from banks/venture capital; 4: Secured busi- workers. It is normalized by wages typical of the region to ness loans from banks/public stock offering; 3: Loans from provide an indicator of the relative standard of living afforded banks secured by personal (not business) assets/govern- to managers, and also reflect whether the industry is able to ment-subsidized private lending/government-run loan pro- attract the most skilled managers. grams/international aid agencies; 2: Microlending/family/ PROPOSED MEASURE: Ratio of managers’ average daily wage to community-based lending; 1: Ma�a/no capital available. average daily wage in region. Bin boundaries can be estab- A.3.3.3 Age of Facilities lished by quintile once data are collected on many �sheries. RATIONALE: The age of the facilities used in processing har- For the pilot studies, the boundaries will be coarsely estab- vests, primarily processing plants and storage facilities, re- lished by the following table: 5: More than 50 percent above flects several dimensions of �shery wealth. First, it is a di- the national average; 4: Between 10 and 50 percent above rect measure of wealth that has been accumulated from the national average; 3: Within 10 percent of the national aver- �shery and reinvested in capital. Second, it is a measure of age; 2: Between 50 and 90 percent of the national average; the potential wealth in the �shery, as newer facilities will be 1: Less than half the national average. more ef�cient and less costly to operate. Third, if processors are willing to invest in new capital, it reflects their assess- A.3.4.3 Educational Access ment that the �shery will be pro�table into the future. Finally, RATIONALE: A community that is successfully using its re- if new facilities are funded by private loans, newer facilities sources will be able to provide high levels of education to reflect the capital market’s assessment that the �shery is its children, ensuring a step beyond resource dependence in suf�ciently low risk to warrant investment. the next generation. If processing is an important part of this community, processing owners’ families will have access to PROPOSED MEASURE: Average age of the key durable processing education. capital unit (plants, catcher-processor vessels): 5: Less than 7 years; �rst quarter of expected life; 4: 7 to 15 years; second PROPOSED MEASURE: Measure is based on the highest level quarter of expected life; 3: 15 to 20 years; third quarter of ex- of education that is politically, culturally, and �nancially ac- pected life; 2: 20 to 25 years; fourth quarter of expected life; cessible to families of harvesters, rather than the actual at- 1: Greater than 25 years; exceeding expected life. tainment levels of current harvesters. 5: Higher education is accessible; 4: High school–level education or advanced tech- A.3.4 Processing Owners and Managers nical training is accessible; 3: Middle school–level education A.3.4.1 Earnings Compared to National Average Earnings or simple technical training is accessible; 2: Basic literacy and RATIONALE: This is a direct measure of �shery-produced wealth arithmetic education is accessible; 1: Formal education is not accumulating to processing owners and managers. Scaling accessible. earnings by average national earnings reflects whether the �shery is able to attract the most talented workers in the A.3.4.4 Health Care Access community and is doing well at wealth generation relative to RATIONALE: A community that is successfully using its resourc- local standards. es will be able to provide high levels of health care, ensuring a quality of life and decreasing health risk. If processing is an PROPOSED MEASURE: Ratio of annual earnings from processing important part of this community, processing owners’ fami- per owner to the national average earnings. In many cases, lies will have access to the best available health care. the captain is an owner of a vessel or permit, but in other cases, captains are considered as crew. Bin boundaries can PROPOSED MEASURE: Measure is based on the quality of health be established by percentile once a range of data are col- care that is politically, culturally, and �nancially accessible to lected. For the pilot studies, the boundaries will be estab- harvesters: 5: Global standard treatment for trauma and ill- lished by the following table: 5: More than 50 percent above ness is accessible; 4: Licensed doctors provide trauma, sur- the national average; 4: Between 10 and 50 percent above gical, and drug treatments; 3: Nurses or medical practitioners national average; 3: Within 10 percent of the national aver- provide emergency and routine drug treatments; 2: First aid age; 2: Between 50 and 90 percent of the national average; and basic drug (e.g., penicillin) treatment is accessible; 1: 1: Less than half the national average. Science-based health care is not accessible. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 65 A.3.4.5 Social Standing of Processing Managers A.3.5.2 Worker Wages Compared to Non�shery Wages RATIONALE: This is a proxy for income associated with owning RATIONALE: The processing worker wage is a direct measure or running processing plants, which may be much easier to of �shery wealth that accumulates to processing workers. collect than actual wage information. Social standing reflects It is normalized by wages typical of the region to provide an whether the �shery is able to attract the most talented work- indicator of the relative standard of living afforded to work- ers in the community and is doing well at wealth generation ers, and also reflect whether the �shery is able to attract the relative to local standards. most skilled workers. PROPOSED MEASURE: 5: Among the most respected in the com- PROPOSED MEASURE: Ratio of workers’ average daily wage to munity, comparable with civic and religious leaders and pro- average daily wage in region. Bin boundaries can be estab- fessionals, such as doctors and lawyers; 4: Comparable to lished by quintile once data are collected on many �sheries. management and white-collar jobs; 3: Comparable to skilled For the pilot studies, the boundaries will be coarsely estab- labor jobs; 2: Comparable to unskilled blue-collar or service lished by the following table:5: More than 10% above the jobs; 1: Among the least respected, such as slaves or inden- average; 4 Within 10% of the average; 3 Between 50 and tured servants. 90% of the average; 2 Between 25 and 50% of the average; 1 Less than 25% of the average. A.3.4.6 Nonresident Ownership of Processing Capacity RATIONALE: The ability of a country or region to improve itself A.3.5.3 Educational Access using its resources depends on its ability to maintain local RATIONALE: A community that is successfully using its re- multipliers by keeping wealth within the region. A large por- sources will be able to provide high levels of education to tion of nonresident-owned processing reflects that much of its children, ensuring a step beyond resource dependence in the processing wealth will be leaving the region, failing to the next generation. If processing is an important part of this boost the regional economy. In developing regions, it may community, processing workers’ families will have access to also reflect an inability of local resource users to generate education. suf�cient capital to process. PROPOSED MEASURE: Measure is based on the highest level PROPOSED MEASURE: Proportion of ex-vessel value processed of education that is politically, culturally, and �nancially ac- by regionally owned processing capital: 5: 95 to 100 per- cessible to families of harvesters, rather than the actual at- cent local; 4: 71 to 95 percent local; 3: 36 to 70 percent tainment levels of current harvesters. 5: Higher education is local; 2: 5 to 35 percent local; 1: Virtually no locally owned accessible; 4: High school–level education or advanced tech- processing. nical training is accessible; 3: Middle school–level education or simple technical training is accessible; 2: Basic literacy and A.3.5 Processing Workers arithmetic education is accessible; 1: Formal education is not A.3.5.1 Earnings Compared to National Average Earnings accessible. RATIONALE: This is a direct measure of �shery-produced wealth accumulating to processing workers. Scaling earn- A.3.5.4 Health Care Access ings by average national earnings reflects whether the RATIONALE: A community that is successfully using its re- �shery is able to attract the most talented workers in the sources will be able to provide high levels of health care, community and is doing well at wealth generation relative ensuring a quality of life and decreasing health risk. If pro- to local standards. cessing is an important part of this community, process- ing workers’ families will have access to the best available PROPOSED MEASURE: Ratio of annual earnings from �shing per health care. owner to the national average earnings. In many cases, the captain is an owner of a vessel or permit, but in other cases, PROPOSED MEASURE: Measure is based on the quality of health captains are considered as crew. Bin boundaries can be es- care that is politically, culturally, and �nancially accessible to tablished by percentile once a range of data is collected. For harvesters: 5: Global standard treatment for trauma and ill- the pilot studies, the boundaries will be established by the ness is accessible; 4: Licensed doctors provide trauma, sur- following table: More than 10 percent above the average; gical and drug treatments; 3: Nurses or medical practitioners Within 10 percent of the average; Between 50 and 90 per- provide emergency and routine drug treatments; 2: First aid cent of the average; Between 25 and 50 percent of the aver- and basic drug (e.g., penicillin) treatment is accessible; 1: age; Less than 25 percent of the average. Science-based health care is not accessible. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 66 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L A.3.5.5 Social Standing of Processing Workers FISHERY PERFORMANCE Rationale: This is a proxy for income associated with working in processing plants, which may be much easier to collect FACTORS: INPUTS than actual wage information. Social standing reflects wheth- A.4 MACRO FACTORS er the �shery is able to attract the most talented workers in A.4.1 General Environmental Performance the community and is doing well at wealth generation rela- tive to local standards. 5: Among the most respected in the A.4.1.1 Environmental Performance Index (EPI) community, comparable with civic and religious leaders and RATIONALE: Wealth creation is dependent on the general con- professionals, such as doctors and lawyers; 4: Comparable dition of the environment. An Environmental Performance to management and white-collar jobs; 3: Comparable to Index (EPI) has been developed to evaluate: 1) environmental skilled labor jobs; 2: Comparable to unskilled blue-collar or health and 2) ecosystem vitality (Esty et al. 2008). service jobs; 1: Among the least respected, such as slaves PROPOSED MEASURE: The EPI considers factors such as dis- or indentured servants. ease, water quality, air pollution, biodiversity, natural resourc- es, and climate change. The EPI ranges from 1 to 100: 5: EPI of 81 to 100; 4: 61 to 80; 3: 41 to 60; 2: 21 to 40; 1: 1 to 20. A.3.5.6 Proportion of Nonresident Employment RATIONALE: The ability of a country or region to improve itself A.4.2 Exogenous Environmental Factors using its resources depends on its ability to maintain local A.4.2.1 Disease and Pathogens multipliers by keeping wealth within the region. A large por- RATIONALE: Even a well-managed �shery can fail to accumu- tion of nonresident processing workers reflects that much late wealth if exogenous events or conditions threaten the of the processing wealth will be leaving the region, failing to stock, or the harvestability of the stock. This measure is in- boost the regional economy. tended primarily to identify when other management inputs PROPOSED MEASURE: 5: 95 to 100 percent local; 4: 71 to 95 per- will not be correlated with outcomes for reasons exogenous cent local; 3: 36 to 70 percent local; 2: 5 to 35 percent local; to the �shery. 1: Virtually no local harvesters. PROPOSED MEASURE: Measure is based on the extent to which harvest is thought to be adversely affected by exogenous dis- ease, pathogens, toxic algaes, or similar factors: 5: Harvest A.3.5.7 Worker Experience unaffected by disease; 4: Harvest reduced by less than 10 RATIONALE: The rate at which workers turn over in the �sh- percent; 3: Harvest reduced by 10 to 30 percent; 2: Harvest ery is an indirect measure of several key variables. First, it reduced by more than 30 percent; 1: Harvest almost com- reflects wealth accumulation to workers, because a worker pletely eliminated by shocks. will only stay in the �shery if the wage is comparable to, or better than, other jobs he could obtain. Second, worker A.4.2.2 Natural Disasters and Catastrophes longevity often means the workers are resident in the com- RATIONALE: Even a well-managed �shery can fail to accumu- munity, and thus their earnings stay in the community and late wealth if exogenous events or conditions threaten the are spent locally, rather than being sent away by itinerant stock, or the harvestability of the stock. This measure is in- or immigrant workers. Third, experienced workers develop tended primarily to identify when other management inputs specialized knowledge and re�ned skills that make process- will not be correlated with outcomes for reasons exogenous ing more ef�cient, so the �shery is better able to reach its to the �shery. wealth-generating potential. PROPOSED MEASURE: Measure is based on the extent to which PROPOSED MEASURE: Average years of experience of work- harvest is thought to be adversely affected by natural disas- ers. Bin boundaries can be established by quintile once ters such as earthquakes, volcanoes, tsunamis, hurricanes, data are collected on many fisheries. For the pilot stud- and typhoons. These are typically one-time events, not long- ies, the boundaries will be coarsely established by the term ecosystem scale shifts induced by climate change: 5: following table: 5: More than 20 years (skilled career Harvest unaffected by disaster; 4: Harvest reduced by less workers); 4: 5 to 20 years; 3: 3 to 5 years; 2: 1 to 3 years; than 10 percent; 3: Harvest reduced by 10 to 30 percent; 2: 1: 0 full years of experience (mostly new workers each Harvest reduced by more than 30 percent; 1: Harvest almost season). completely eliminated by disaster. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 67 A.4.2.3 Pollution Shocks and Accidents has developed a Worldwide Governance Indicator which RATIONALE: Even a well-managed �shery can fail to accumulate considers six dimensions: Voice and Accountability, Political wealth if exogenous events or conditions threaten the stock, or Stability and Absence of Violence/Terrorism, Government the harvestability of the stock. This measure is intended primar- Effectiveness, Regulatory Quality, Rule of Law, and Control ily to identify when other management inputs will not be cor- of Corruption (Kaufman et al. 2008). related with outcomes for reasons exogenous to the �shery. PROPOSED MEASURE: The Governance Indicators (Kaufman, PROPOSED MEASURE: Measure is based on the extent to which Kraay, and Mastruzzi 2008) assign countries to ranks based harvest is thought to be adversely affected by pollution on six dimensions. This measure is the average percentile shocks, such as oil spills, industrial accidents, or peak runoff ranking of the Government Effectiveness, Regulatory Quality, events. These are typically one-time events, not chronically Rule of Law, and Control of Corruption indicators. Assign av- high levels of pollution: 5: Harvest unaffected by pollution; 4: erage percentile to a quintile and give points according to: 5: Harvest reduced by less than 10 percent; 3: Harvest reduced First quintile; 4: Second quintile; 3: Third quintile; 2: Fourth by 10 to 30 percent; 2: Harvest reduced by more than 30 per- quintile; 1: Fifth quintile. cent; 1: Harvest almost completely closed by shocks. A.4.3.2 Governance Indicator—Voice and Accountability A.4.2.4 Level of Chronic Pollution—Stock Effect RATIONALE: Good governance is an essential condition for RATIONALE: Even a well-managed �shery can fail to accumu- sustainable �sheries and wealth creation. The World Bank late wealth if exogenous events or conditions threaten the has developed a Worldwide Governance Indicator that con- stock, or the harvestability of the stock. This measure is in- siders six dimensions: Voice and Accountability, Political tended primarily to identify when other management inputs Stability and Absence of Violence/Terrorism, Government will not be correlated with outcomes for reasons exogenous Effectiveness, Regulatory Quality, Rule of Law, and Control to the �shery. of Corruption (Kaufman et al. 2008). PROPOSED MEASURE: Measure is based on the level of chronic PROPOSED MEASURE: The Governance Indicators (Kaufman et pollution that is detected in the �shery. Chronic pollution can al. 2008) assign countries to ranks based on six dimensions. be either always present, or frequently recurring, such as af- This measure is the average percentile ranking of the Voice ter each moderate rainfall: 5: Not detectable; 4: Minimal de- and Accountability and Political Stability indicators. Assign tectable levels; 3: Major detectable; 2: Pollution affects stock average percentile to a quintile and give points according to: growth; 1: Pollution leading to severe stock decline. 5: First quintile; 4: Second quintile; 3: Third quintile; 2: Fourth quintile; 1: Fifth quintile. A.4.2.5 Level of Chronic Pollution—Consumption Effect RATIONALE: Even a well-managed �shery can fail to accumu- A.4.4 Economic Conditions late wealth if exogenous events or conditions threaten the A.4.4.1 Index of Economic Freedom stock, or the harvestability of the stock. This measure is in- tended primarily to identify when other management inputs RATIONALE: Wealth creation is dependent on the institution- will not be correlated with outcomes for reasons exogenous al setting and economic conditions in a given country. The to the �shery. Heritage Foundation/Wall Street Journal, Index of Economic Freedom (IEF) reflects the overall economic freedom of the PROPOSED MEASURE: Measure is based on the level of chronic nation within which the �shery sector operates (Miller and pollution that is detected in the �shery. Chronic pollution Holmes 2009). The Index of Economic Freedom includes can be either always present, or frequently recurring, such 10 broad institutional factors: Business freedom; Trade as after each moderate rainfall: 5: No consumption affected; freedom; Fiscal freedom; Government size; Monetary free- 4: Minimal consumption affected; 3: Of�cial consumption dom; Investment freedom; Financial freedom; Property advisories; 2: Temporarily ban harvest for consumption; 1: rights; Freedom from corruption; and Labor freedom. Completely closed for consumption. Construction of the index relies on several other studies for its data sources, including the World Bank’s Doing Business A.4.3 Governances Economist Intelligence Unit (The World Bank 2009a), A.4.3.1 Governance Indicator—Effectiveness the U.S. Department of Commerce, the World Bank’s RATIONALE: Good governance is an essential condition for World Development Indicators (The World Bank, 2009b), sustainable �sheries and wealth creation. The World Bank Eurostat, International Monetary Fund reports, Transparency AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 68 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L International’s, Corruption Perceptions Index (Transparency A.5.1.3 Security Index International 2009), and several other documents. RATIONALE: When property rights are insecure, regardless of PROPOSED MEASURE: The 10 factors are equally weighted and whether the reason is crime, civil unrest, war, government the �nal composite index has a range from 1 to 100. A de- instability, or government’s use of eminent domain, it causes tailed discussion of these factors and methodology is found owners to be more exploitive with resources. Uncertainty in Miller and Holmes (2009): 5: IEF of 81 to 100; 4: 61 to 80; implicitly increases the discount rate. Financing is under- 3: 41 to 60; 2: 21 to 40; 1: 1 to 20. mined (Anderson 2007, 2002). PROPOSED MEASURE: Extent to which the government reduces A.4.4.2 Gross Domestic Product (GDP) Per Capita or dilutes the access rights: 5: Very Strong: Access rights RATIONALE: Richer nations are more likely able to afford the are completely respected and are not diluted (e.g., by issuing institutions and technological factors that are necessary for more access rights) by the government; 4: Strong: Rights wealth creation. are mostly respected by the government; generally survive PROPOSED MEASURE: Bin boundaries based on quintiles of the changes in government administration; 3: Moderate: Rights U.S. CIA’s rank of per capita GDP of all countries (https:// are at risk of retraction or dilution with changes in administra- www.cia.gov/library/publications/the-world-factbook/ tion; 2: Weak: Rights are highly diluted or there is high politi- rankorder/2004rank.html): 5: Greater than US$30,000; 4: cal uncertainty; 1: None: Access rights are not protected. Greater than US$12,400; 3: Greater than US$6,000; 2: Greater than US$2,500; 1: Less than US$2,500. A.5.1.4 Durability Index RATIONALE: Short-duration property rights create more ex- ploitive management. This implicitly increases the discount A.5 PROPERTY RIGHTS AND RESPONSIBILITY rate, thus undermining sustainability and wealth creation (Anderson 2007, 2002). A.5.1 Access A.5.1.1 Proportion of Harvest Managed Under Limited PROPOSED MEASURE: Duration of the property right: 5: Very Access Strong: >10 years to perpetuity; 4: Strong: 5 to 10 years; 3: Moderate: 1 to 5 years; 2: Weak: Seasonal; 1:None: None/ RATIONALE: Limited-access �sheries are an essential step in daily. eliminating the open-access common property problem of rent dissipation. A.5.1.5 Flexibility Index PROPOSED MEASURE: The proportion of total harvest that is un- RATIONALE: Under strong property rights all decisions regard- der limited-access �shing regulation: 5: Virtually all; 4: 71 to ing use, management, and technology employed to extract 95 percent; 3: 36 to 70 percent; 2: 5 to 35 percent; 1: Virtually value from the property are controlled by the owner. Fishing none. time, gear, and handling practices are in the owner’s control. A.5.1.2 Transferability Index PROPOSED MEASURE: Ability of right holders to be flexible in the timing and production technology employed: 5: Very Strong: RATIONALE: Transferability is essential for a functioning market All decisions on time of harvest, gear used, and handling to allocate resources to their best use. If rights are not trans- practices are in the owner’s control; 4: Strong: Minimal re- ferable, �nancing is undermined because the property may strictions on time of harvest and technology; 3: Moderate: not be accepted as collateral. If the markets for the rights Modest restrictions on time of harvest and technology; 2: are not ef�cient, then the value of the right will not be trans- Weak: Signi�cant restrictions on time of harvest and technol- parent, and its price will not necessarily reflect the value. ogy; 1: Time of harvest, gear used, and handling practices are This will lead to misallocation of resources and inef�cien- not in the owner’s control. cies, as well as undermine sustainability and wealth creation (Anderson 2007, 2002). A.5.1.6 Exclusivity Index PROPOSED MEASURE: 5: Very strong: fully transferable through RATIONALE: Under strong property rights all decisions and ac- well-established, ef�cient market institutions; 4: Strong: fully cess to the property are controlled by the owner. With well- transferable, but institutions are poor or illiquid; 3: Moderate: de�ned rights, externalities are internalized and net bene�ts transferable, but with severe restrictions on who can hold, or are captured. Those that produce externalities that infringe how much; 2: Weak: transferable only under highly restricted on the property right are held responsible. If externalities are and limited condition; 1: Access rights not transferable. not internalized, costs are undervalued, market signals are EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 69 biased, resources are misallocated, and sustainability and implicitly increases the discount rate. Financing is under- wealth creation are undermined (Anderson 2007, 2002). mined (Anderson 2002, 2007). PROPOSED MEASURE: Ability of right holders to exclude those PROPOSED MEASURE: 5: Very Strong: Harvest rights are com- who do not have the right from affecting the resource or pletely respected and are not diluted (e.g., by issuing more market: 5: Very Strong: All decisions and access to the prop- harvest rights) by the government; 4: Strong: Rights are erty are controlled by the right’s owner (rather than those mostly respected by the government; generally survive without rights, competing resource users [like recreational or changes in government administration; 3: Moderate: Rights by-catch �sheries]); 4: Strong: Little intrusion on resource by are at risk of retraction or dilution with changes in administra- those without rights; 3: Moderate: Modest intrusion on re- tion; 2: Weak: Rights are highly diluted or there is high politi- source by those without rights; 2: Weak: Signi�cant intrusion cal uncertainty; 1: None: Harvest rights are not protected on resource by those without rights; 1: None: Completely unrestricted open access, despite putative right. A.5.2.4 Durability Index RATIONALE: Short-duration property rights create more ex- ploitive management. This implicitly increases the discount A.5.2 Harvest Rights rate, thus undermining sustainability and wealth creation A.5.2.1 Proportion of Harvest Managed with Rights- (Anderson 2002, 2007). Based Management PROPOSED MEASURE: Duration of the property right: 5: Very RATIONALE: Rights-based management (beyond simple ac- Strong: >10 years to perpetuity; 4: Strong: 5 to 10 years; 3: cess), such as Individual/Community Quotas, Catch Shares Moderate: 1 to 5 years; 2: Weak: Seasonal; 1:None: None/ or Territorial Use Rights (TURFs), induce economic incentives daily. to allocate resources ef�ciently and generate wealth. PROPOSED MEASURE: The proportion of total harvest that is A.5.2.5 Flexibility Index under rights-based �sheries management (e.g., Individual/ RATIONALE: Under strong property rights all decisions regard- Community Quotas, Catch Shares or Territorial Use Rights ing use, management, and technology employed to extract [TURFs]): 5: Virtually all; 4: 71 to 95 percent; 3: 36 to 70 per- value from the property are controlled by the owner. Fishing cent; 2: 5 to 35 percent; 1: Virtually none. time, gear, and handling practices are in the owner’s control. A.5.2.2 Transferability Index PROPOSED MEASURE: Ability of right holders to be flexible in the timing and production technology employed: 5: Very Strong: RATIONALE: Transferability is essential for a functioning mar- All decisions on time of harvest, gear used, and handling ket to allocate resources to for their best use. If rights are practices are in the owner’s control; 4: Strong: Minimal re- not transferable, �nancing is undermined because the prop- strictions on time of harvest and technology; 3: Moderate: erty may not be accepted as collateral. If the markets for Modest restrictions on time of harvest and technology; 2: the rights are not ef�cient, then the value of the right will Weak: Signi�cant restrictions on time of harvest and technol- not be transparent, and its price will not necessarily reflect ogy; 1: Time of harvest, gear used, and handling practices are the value. This will lead to misallocation of resources and not in the owner’s control inef�ciencies, as well as undermine sustainability and wealth creation (Anderson 2002, 2007). A.5.2.6 Exclusivity Index PROPOSED MEASURE: 5: Very strong: fully transferable through RATIONALE: Under strong property rights all decisions and ac- well-established, ef�cient market institutions; 4: Strong: fully cess to the property are controlled by the owner. With well- transferable, but institutions are poor or illiquid; 3: Moderate: de�ned rights, externalities are internalized and net bene�ts transferable, but with severe restrictions on who can hold, or are captured. Those that produce externalities that infringe how much; 2: Weak: transferable only under highly restricted on the property right are held responsible. If externalities are and limited condition; 1: Access rights not transferable. not internalized, costs are undervalued, market signals are A.5.2.3 Security Index biased, resources are misallocated, and sustainability and wealth creation are undermined (Anderson 2002, 2007). RATIONALE: When property rights are insecure, regardless of whether the reason is crime, civil unrest, war, government PROPOSED MEASURE: Ability of right holders to exclude those instability, or government’s use of eminent domain, it causes who do not have the right from affecting the resource or mar- owners to be more exploitive with resources. Uncertainty ket: 5: Very Strong: All decisions and access to the property AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 70 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L are controlled by the right’s owner (rather than those with- PROPOSED MEASURE: Subjective measure of how much influ- out rights, competing resource users [like recreational or ence harvesting organizations have, either directly or through by-catch �sheries]); 4: Strong: Little intrusion on resource by political collective action, on management and access to the those without rights; 3: Moderate: Modest intrusion on re- �shery: 5: Harvesting organizations cooperatively determine source by those without rights; 2: Weak: Signi�cant intrusion marketing and operational details; 4: Extensive joint market- on resource by those without rights; 1: None: Completely ing; 3: Large subgroups facilitating marketing, joint purchas- unrestricted open access, despite putative right. ing; 2: Small subgroups cooperating in purchasing or opera- tions; 1: No active effort or capacity to influence business operations. A.5.3 Comanagement A.5.3.1 Participation in Industry Organizations A.5.4 Management RATIONALE: The degree to which producers are organized A.5.4.1 Management Expenditure to Value of Harvest into cooperatives or associations that can act collectively RATIONALE: This is a measure of the cost of �sheries man- to influence distribution/sharing of resources and facilitate agement in proportion to the value of �sheries. Ef�ciency in both buying and selling power, thereby creating wealth management is essential for wealth creation. enhancement. PROPOSED MEASURE: This measure divides the budget ($ million) PROPOSED MEASURE: Proportion of harvest where the primary for �sheries management by the ex-vessel value ($ millions) harvesters are organized into associations: 5: Virtually all; 4: of the harvest. Government, industry, and aid agency expen- 71 to 95 percent; 3: 36 to 70 percent; 2: 5 to 35 percent; 1: ditures on �shery management activities include research, Virtually none. enforcement, and management capacity development (but not infrastructure). Bin boundaries can be established by A.5.3.2 Industry Organization Influence quintile once data are collected on many �sheries. For the on Management and Access pilot studies, the boundaries will be coarsely established by RATIONALE: Harvesting organizations can influence manage- the following table, which are based on the benchmark of ment and access by directly managing access rights (e.g., managed mutual funds (1 to 2 percent management costs): cooperatives or community quota systems) or by taking po- 5: Less than 5 percent; 4: 5 to 25 percent; 3: 26 to 50 per- litical action to influence the access they and others have cent; 2: 51 to 100 percent; 1: More than the value of harvest. through the management authority. Such harvester participa- tion may facilitate management that increases wealth accu- A.5.4.2 Management Employees to Value of Harvest mulation to harvesters. RATIONALE: This is an indicator of management ef�ciency. PROPOSED MEASURE: Subjective measure of how much influ- Ef�cient management is essential for wealth creation. ence harvesting organizations have, either directly or through PROPOSED MEASURE: Public sector �shery management em- political collective action, on management and access to the ployee FTEs devoted to managing the �shery divided by the �shery: 5: Harvesters effectively determine allocation of ex-vessel value of the harvest. Bin boundaries can be estab- resources; 4: Harvesters have signi�cant influence in de- lished by quintile once data are collected on many �sheries. termining allocation; 3: Harvesters are politically active, but For the pilot studies, the boundaries will be coarsely estab- not controlling; 2: Social or informal monitoring participation lished by the following table: 5: More than 0.35 per million; 4: and allocation; 1: No active effort or capacity to influence 0.25 to 0.35; 3: 0.15 to 0.25; 2: 0.01 to 0.15; 1: 0. management. A.5.4.3 Management Employees per Permit Holder A.5.3.3 Harvester Organization Influence on Business RATIONALE: This is an indicator of management ef�ciency. and Marketing Ef�cient management is essential for wealth creation. RATIONALE: Harvesting organizations can influence business PROPOSED MEASURE: Fishery management FTE employees di- and marketing by working to exert market power in either vided by the number of �shing units (in 100s) (vessels or purchasing of inputs (e.g., marine services or insurance) or permit holders). Bin boundaries can be established by quin- by collectively marketing products, reducing costs, or in- tile once data are collected on many �sheries. For the pilot creasing revenue, respectively. Such joint activity may in- studies, the boundaries will be coarsely established by the crease wealth accumulation to harvesters. following: 4 or more per 100 permit holders; 3; 2; 1; 0. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 71 A.5.4.4 Research as a Proportion of Fisheries A.5.6 Participation Management Budget A.5.6.1 Days in Stakeholder Meetings RATIONALE: This is an indicator of the degree to which �shery RATIONALE: This measure is a proxy for the ef�ciency of management is based on science. It is also an indicator of the management process and stakeholder participation. the potential for innovation and support for entrepreneurs. Stakeholder participation injects stakeholders’ knowledge PROPOSED MEASURE: Research expenditures divided by total into management and may increase legitimacy and com- �sheries management budget. Bin boundaries can be estab- pliance. However, it may also increase management costs lished by quintile once data are collected on many �sheries. and present opportunities for lobbying and rent seeking that For the pilot studies, the boundaries will be coarsely estab- increases the time required to implement management, lished by the following table (based on 18 to 22 percent in or weakens implemented regulations to prevent wealth pharmaceuticals and 4 percent in general manufacturing): 5: generation. Over 20 percent; 4: 12 to 20 percent; 3: 5 to 12 percent; 2: PROPOSED MEASURE: Days in stakeholder meetings per year 0.5 to 5 percent; 1: Virtually none. spent by an participant in the �shery who is active in man- A.5.4.5 Level of Subsidies agement. Bin boundaries can be established by quintile once data are collected on many �sheries. For the pilot studies, RATIONALE: Subsidies distort resource allocation and pricing. the boundaries will be coarsely established by the following Lower subsidies are indicative of greater market ef�ciency. table: 5: More than 24 per year; 4: 12 to 24; 3: 6 to 12; 2: 1 Subsidies include preferential tax rates, input cost reduc- to 6; 1: None. tions, price supports, special borrowing rates, undervaluing resources (e.g., leases), payments-in-kind, and other related actions giving preference. A.5.6.2 Industry Financial Support for Management RATIONALE: If the industry pays for the cost of management, PROPOSED MEASURE: Measure the annual value of all subsidies it is likely that ef�ciency will be improved and the concomi- as a proportion of the value of the �shery: 5: Near zero (less tant control over management exerted by the industry will than 2.5 percent); 4: 2.5 to 7.5 percent; 3: 7.5 to 12.5 per- lead to improved outcomes for harvesters, especially wealth cent; 2: 12.5 to 20 percent; 1: More than 20 percent. generation. PROPOSED MEASURE: Proportion of the �shery management A.5.5 Data budget paid for by the �shing sector. Bin boundaries can be A.5.5.1 Data Availability established by quintile once data are collected on many �sh- RATIONALE: A �shery management program will be more ef- eries. For the pilot studies, the boundaries will be coarsely fective in achieving its social and biological goals if it collects established by the following: 5: Virtually all; 4: 50 to 95 per- data on which to evaluate policy changes, either retrospec- cent; 3: 6 to 50 percent; 2: 1 to 5 percent; 1: None. tively or prospectively. PROPOSED MEASURE: 5: Regular stock assessment and eco- nomic data; 4: Landings and price data; 3: Landings data; 2: A.6 POST-HARVEST Boat registration and license data; 1: No data are tracked A.6.1 Markets and Market Institutions A.5.5.2 Data Analysis A.6.1.1 Landings Pricing System RATIONALE: A �shery management program will be more ef- RATIONALE: Fair and ef�cient price discovery systems are es- fective in achieving its social and biological goals if it ana- sential for ef�cient resource use and wealth creation. Crucial lyzes data to evaluate policy changes, either retrospectively to this is the ability of harvesters to move among ex-vessel or prospectively. buyers to those offering the best prices on a per-landing basis. PROPOSED MEASURE: 5: Biological and economic data used in prospective analysis of management; 4: Biological data domi- PROPOSED MEASURE: Proportion of the harvest sold in a trans- nate simple prospective analysis; 3: Biological or economic parent daily competitive pricing mechanism, such as an auc- data are used to track performance retrospectively; 2: Data tion or centralized ex-vessel to wholesale market: 5: Virtually are used inconsistently or irregularly; 1: No data analysis con- all; 4: 71 to 95 percent; 3: 36 to 70 percent; 2: 5 to 35 per- ducted in management process. cent; 1: Virtually none. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 72 A PPEND IX A — FISH ERY PERFORMA NCE IND IC ATOR S — M A NUA L A.6.1.2 Availability of Ex-vessel Price and Quantity A.6.1.6 Level of Nontariff Barriers Information RATIONALE: Lower nontariff barriers broaden the market, improve RATIONALE: Market transparency is essential for ef�cient re- price discovery, and increase the opportunity to create wealth. source use and wealth creation. Market transparency is PROPOSED MEASURE: Nontariff barriers include quantity restric- characterized by readily available, accurate price and quantity tions (import quotas), regulatory restrictions, investment information. restrictions, customs restrictions, and direct government PROPOSED MEASURE: 5: Complete, accurate price and quantity intervention: 5: Are not used to limit international trade; 4: information available to market participants immediately; 4: Have very limited impact on international trade; 3: Act to im- Reliable price and quantity information is available prior to pede some international trade; 2: Act to impede a majority the next market clearing; 3: Price information is available but of potential international trade; 1: Act to effectively impede a no timely quantity information; 2: Price and quantity informa- signi�cant amount of international trade tion are inaccurate, lagged, or available to only a few; 1: No information available. A.6.2 Infrastructure A.6.1.3 Number of Buyers A.6.2.1 International Shipping Service RATIONALE: This measure is an indicator of relative market RATIONALE: In order to have access to a broader market, com- power. If the market is dominated by a single (or very few) petitively priced international shipping is essential. buyer or seller, price will favor the side with greater market PROPOSED MEASURE: Average of the two measures below: power. 5: Ocean shipping services are readily available at lower than PROPOSED MEASURE: Typical number of buyers of ex-vessel average rates; 4: Ocean shipping services are readily avail- product in a given market: 5: Highly competitive; 4: 4 to 6 able at average rates; 3: Ocean shipping services are read- buyers; 3: 2 to 3 competing buyers; 2: A small number of ily available at higher than average rates; 2: Ocean shipping coordinating buyers; 1: There is one buyer. services are available but irregular; 1: International shipping is not available at reasonable rates A.6.1.4 Degree of Vertical Integration RATIONALE: Vertical integration facilitates the flow of informa- 5: Air shipping services are readily available at lower than tion from the consumer to the harvest sector and tends to average rates; 4: Air shipping services are readily available at reduce transaction costs between market levels. average rates; 3: Air shipping services are readily available at higher than average rates; 2: Air shipping services are avail- PROPOSED MEASURE: Proportion of harvest where the primary able but irregular; 1: International shipping is not available at harvester and primary processor/distributor are same �rm. reasonable rates. Bin boundaries can be established by quintile once data are collected on many �sheries. For the pilot studies, the bound- A.6.2.2 Road Quality Index aries will be coarsely established by the following: 5: Virtually RATIONALE: The quality of roads is directly related to the ability none; 4: 0.5 to 2.5 percent; 3: 2.5 to 5 percent; 2: 5 to 10 of �rms to distribute their products, minimize transportation percent; 1: Over 10 percent. cost, and create wealth. A.6.1.5 Level of Tariffs PROPOSED MEASURE: Mile-weighted average road quality be- RATIONALE: Lower tariffs broaden the market, improve price tween the �shery’s primary port and its major consumption discovery, and increase the opportunity to create wealth. center (or export shipping port for exported product). Score according to: 5: High-quality paved roads and extensive high- PROPOSED MEASURE: Based on quintile once data on an appro- ways; 4: Primarily paved two-lane roads and moderate high- priate number of systems are collected. However, initial tariff way; 3: Primarily paved two-lane roads and minimal highway; rate on key seafood exports relative to international average 2: Paved two-lane roads and well-graded gravel roads; 1: for food commodities. Bin boundaries can be established by Poorly maintained gravel or dirt roads. quintile once data are collected on many �sheries. For the pilot studies, the boundaries will be coarsely established by A.6.2.3 Technology Adoption the following table (based on World Development Indicators RATIONALE: The availability of the latest communication, pro- 2005 Table 6.3, average 2003 tariff for food from low-income cessing, and production technology is important for �rms to countries to OECD countries is 4.1 percent). maintain global competitiveness and create wealth. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X A — F I SHE RY P E RF ORMANCE INDICAT ORS —MA NUA L 73 PROPOSED MEASURE: 5: Cell phones/�sh �nders/computers/ Minimal, poorly supported extension service; 1: No exten- processing/production technology are readily available; 4: sion service. Cell phones/�sh �nders, and so forth, are common, but some A.6.2.5 Reliability of Utilities/Electricity other technology is not always available; 3: Cell phones/�sh �nders, and so forth, are common, but some other technol- RATIONALE: Reliable utilities are essential for �rms to function ogy is dif�cult to obtain; 2: Cell phones are common, but ef�ciently and generate wealth. most other technology is prohibitive; 1: Very little advanced PROPOSED MEASURE: 5: Electricity readily available with rare technology is accessible for the industry. outages; 4: Electricity readily available with less than six short outages per year; 3: Electricity readily available with A.6.2.4 Extension Service less than two outages per month; 2: Electricity readily avail- RATIONALE: Extension services are successful in many coun- able with more than two outages per month; 1: Electricity is tries for transferring technology and information about best not available except through generators. management practices, new technology, market conditions, and regulatory changes. This information is often essential A.6.2.6 Access to Ice and Refrigeration in a widely dispersed industry to help maximize returns and RATIONALE: Ice/refrigeration are essential for quality control generate wealth. and broadening the market. PROPOSED MEASURE: 5: Broad extension service with �eld PROPOSED MEASURE: 5: Ice is readily available in various forms; of�ces and close linkage with research community; 4: 4: Ice is readily available in various forms with occasional Extension service with moderate �eld coverage and ade- shortages; 3: Ice is available in limited quantity/form (e.g., quate linkage with the research community; 3: Extension block only); 2: Ice is available in very limited quantity/form; 1: service, but with weak links to the research community; 2: Ice is unavailable. AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 75 Appendix B: SUGGESTED REVISION AND ADDITIONAL INDICATORS TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Ecologically Fish Stock Health Proportion of 5: 76–100% of landings are certi�ed The proportion of harvest (quantity) har- Sustainable and Environmental Harvest with 4: 51–75% of landings are certi�ed vested under one of the recognized third-party Fisheries Performance a Third-Party 3: 26–50% of landings are certi�ed programs that certify ecological sustainability, Certi�cation such as the Marine Stewardship Council (MSC) 2: 1–25% of landings are certi�ed certi�cation. 1: No landings have third-party certi�cation Percentage of 5: None over�shed Proportion of stocks in the �shery (including dis- Stocks Over�shed 4: 1–25% of stocks over�shed tinct stocks of the same species under the same 3: 26–50% over�shed management plan) whose current biomass level indicates they are over�shed. Single species 2: 51–75% over�shed �sheries will be 1 or 5. (Whether they are cur- 1: 76–100% over�shed rently recovering or being over�shed further is the next question.) Over�shing or 5: Stock is not over�shed or is rebuilt Extent to which current effort affects stock Rebuilding 4: Growth over�shed, but stable or rebuilding status. For multistock �sheries, score each sig- 3: Growth over�shed and experiencing growth ni�cant stock 1 to 5, then take a value-weighted over�shing average. 2: Recruit over�shed, but stable or rebuilding 1: Recruit over�shed and experiencing recruit over�shing Regulatory 5: No regulatory mortality of the target species Nonlanding mortality induced by regulation, Mortality 4: Regulatory mortality is less than 5% of such as regulatory discards total catch 3: 5–25% 2: 25–50% 1: For every 100 lbs of �sh caught, more than 50 lbs are discarded Selectivity 5: There is virtually no nontarget catch Nontarget species are distinct from multispe- 4: Less than 5% of catch is of nontarget species cies �sheries in that the catch of nontarget 3: 5–25% species does not increase the value of �shing, or impose costs on the target �shery. 2: 25–50% 1: For every 100 lbs of �sh caught, more than 50 lbs are nontarget species Illegal, Unregulated, 5: There is virtually no IUU catch Proportion of landings using illegal gear, area, or Unreported 4: Less than 5% of catch is IUU methods, and so forth, or falling outside of the Landings 3: 5–25% regulations. If there is no regulatory reporting requirement, that does not count as unreported 2: 25–50% for purposes of this measure. 1: For every 100 lbs of �sh caught, more than 50 lbs are IUU Status of Critical 5: Critical habitat is healthy and not Critical habitat is de�ned as that playing a sig- Habitat threatened ni�cant role in the life cycle of the �sh. Portion 4: Less than 25% is degraded or dysfunctional damaged is based on area, and from all sources 3: 25–75% is degraded or dysfunctional of damage including �shing damage, pollution, and development. 2: More than 75% of critical habitat is destroyed 1: Nearly all critical habitat is damaged or dysfunctional AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 76 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Harvest Sector Harvest Landings Level 5: Harvest is less than MSY (stock is above Average annual harvest over the last 3 years. Performance Performance MSY level) to increase pro�t In practice, there are very few estimates of 4: Harvest is approximately at MSY MEY, however where it has been calculated it 3: Harvest reduced to promote recovery (stock is typically 5 to 10 percent less than maximum is below MEY level) sustainable yield (MSY). 2: Harvest is constraining stock recovery (stock is stable below MEY level) 1: Harvest is causing over�shing (stock is below MEY and declining) Excess Capacity 5: Within 5% of days required In the absence of a �shery-speci�c measure 4: 105–120 or 90–95% of over�shing, use estimated standardized 3: 120–150% or 75–90% vessels-days required to catch the maximum economic yield (MEY) compared to the number 2: 150–200% or 50–75% of standardized vessel-days available. Days are 1: More than 200%, or less than 50%, of days considered not to be restricted by trip limits. required Season Length 5: Virtually no regulatory closures Ratio of number of days on which �shing occurs 4: 90–99% to the number of days the species is available 3: 50–90% in economically feasible quantities. This is primarily a measure of the extent of derby 2: 10–50% (including short regulatory seasons to limit 1: Less than 10% total effort), not lack of biological availability or closures to prevent within-season growth over�shing. Harvest Safety 5: Less than 0.1 deaths per thousand person Number of harvester (captain or crew) on-the- seasons job deaths, per thousand person �shing season. 4: Less than 0.5 deaths We consider there to be one season per year, 3: Less than 1 but do not annualize mortality if the �shing season is less than a year. 2: Less than 5 1: More than 5 deaths per thousand person seasons Harvest Asset Ratio of Asset Value 5: 10 or higher Extent to which �shery wealth is accumulated Performance to Gross Earnings 4: 7.5–10 in access capital (e.g., quota or vessels). 3: 5–7.5 Typically a 1 if vessels or quota not limited by regulation. Ratio of average price of capital 2: 2.5–5 and licenses require access to the �shery over 1: Below 2.5 the last 5 years to the average annual land- ings value for a similarly scaled access right in the same period. Same business or same family sales are excluded, where they can be identi�ed. Total Revenue ver- 5: Above 95% The indicator is the ratio of total real revenue sus Historic High 4: 85–95% (in local currency) to the average of the three 3: 70–85% highest total real revenues in the past 10 years. Adjust by local CPI if inflation was signi�cant. 2: 50–70% 1: Below 50% Asset (Permit, 5: Above 95% The indicator is the ratio of asset to the average Quota) Value versus 4: 85–95% of the three highest asset values in the past 10 Historic High 3: 70–85% years. Adjust by local CPI if inflation was signi�- cant. Typically 5 if wealth is not accumulating in 2: 50–70% vessels, permits, or quota. 1: Below 50% Borrowing Rate 5: Less than 1.75; cf. 30-year conforming mort- Average ratio between the interest rate on Relative to Risk- gage; family/friend’s support loans made in the industry to risk-free rates Free Rate 4: Less than 2.5; cf. personal bank loan; in- over the last 3 years. If businesses can ac- kind pay back cess the international credit markets, that is 3: Less than 4; cf. good credit card rates appropriate comparison; otherwise, use local risk-free rate. 2: Less than 7; cf. bad credit card rates 1: Greater than 7; usury EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 77 TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Source of Capital 5: Unsecured business loans from banks/ Points to be assigned based on the category of venture capital lenders or investors that is most typically used 4: Secured business loans from banks/public in the �shery. Second scoring method offered stock offering; investment from elsewhere in if the supply chain (e.g., traders, processors, supply chain exporters) are primary source of capital. 3: Loans from banks secured by personal (not business) assets/government-subsidized pri- vate lending/government-run loan programs/ international aid agencies; secured loans from elsewhere in supply chain 2: Microlending/family/community-based lending; loans from supply chain signi�cantly reduce margins 1: Ma�a/no capital available; exploitive rela- tionship from elsewhere in supply chain Functionality of 5: Capital is new Average age of the key durable harvesting capi- Harvest Capital 4: Capital is older but well maintained, e.g., tal unit (vessels, weirs). Ages are not assigned freshly painted to scores due to differences in expected useful 3: Capital is moderately well maintained life, but buildings and industrial vessels have expected life of roughly 20 years. 2: Maintenance is poor 1: Serious concerns about seaworthiness or safety throughout �shery Risks Exposure Annual Total 5: Less than 0.15 Ratio of the standard deviation of the �rst Revenue Volatility 4: 0.15–0.22 differences of annual total revenue to the mean 3: 0.22–0.40 total revenue over the last 10 years. Best guess may be calculated based on shorter time series 2: 0.40–1 if data not available. 1: Greater than 1 Annual Landings 5: Less than 0.15 Ratio of the standard deviation of the �rst Volatility 4: 0.15–0.22 differences of annual total landings sold to the 3: 0.22–0.40 mean landings over the last 10 years. 2: 0.40–1 1: Greater than 1 Intra-annual 5: Less than 0.15 Ratio of the standard deviation of the weekly/ Landings Volatility 4: 0.15–0.22 monthly total sold landings over the last 3 years 3: 0.22–0.40 to the mean landings. Observations of zero landings are included if there is biological avail- 2: 0.40–1 ability. If the biological season is so short that 1: Greater than 1 there is not meaningful variation at a monthly level, this measure can be NA. Annual Price 5: Less than 0.13 Ratio of the standard deviation of the �rst dif- Volatility 4: 0.13–0.20 ferences of annual ex-vessel price to the mean 3: 0.20–0.30 price over the last 10 years. 2: 0.30–0.85 1: Greater than 0.85 Intra-annual Price 5: Less than 0.13 Ratio of the standard deviation of average Volatility 4: 0.13–0.20 monthly ex-vessel price over the last 3 years 3: 0.20–0.30 to the mean. Observations of zero landings are included if there is biological availability. If the 2: 0.30–0.85 biological season is so short that there is not 1: Greater than 0.85 meaningful variation at a monthly level, this measure can be NA. Spatial Price 5: Less than 0.13 Ratio of the standard deviation across data Volatility 4: 0.13–0.20 collection regions of average annual ex-vessel 3: 0.20–0.30 price to the mean. Measure should be averaged over last 3 years. 2: 0.30–0.85 1: Greater than 0.85 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 78 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Contestability and 5: No signi�cant legal challenges, civil This captures the degree to which political Legal Challenges actions, or protests regarding the �shery activity limits the ability to implement effective management system �shing regulations. 4: Minor legal challenges slow implementation 3: Legal challenges, civil actions, or protests impede some management measures 2: Legal challenges, civil actions, or protests suspend major elements of the management system 1: Legal challenges, civil actions, or protests suspend or prohibit implementation of key management reforms and regulation certi�cation Owners, Permit Earnings Compared 5: More than 50% above the regional average Ratio of annual earnings from �shing per owner Holders, and to Regional Average 4: Between 10% and 50% above regional to the regional average earnings. In many Captains (Those Earnings average cases, the captain is an owner of a vessel or Holding the Right or 3: Within 10% above the regional average permit, but in other cases, captains are consid- Ability to Access) ered as crew. 2: Between 50% and 90% of the regional average 1: Less than half of the regional average Fishery Wages 5: More than 50% above the regional average Ratio of captain’s average daily wage in this Compared to 4: Between 10 and 50% above regional �shery to average daily wage in the captain’s Non�shery Wages average economic sphere (e.g., village if all economic 3: Within 10% above the regional average activity is within the village, but nation if par- ticipates in national markets as a consumer). 2: Between 50% and 90% of the regional May differ from above measure if �shery is not average year-round and there is no income or income 1: Less than half of the regional average from other �sheries or other occupations. Education Access 5: Higher education is accessible The level of education attained by (available 4: High school–level education or advanced and affordable) the families (i.e., children) of technical training is accessible permit holders and captains. 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic training is accessible 1: Formal education is not accessible Access to Health 5: Global standard treatment for illness is The level of health care accessible to (available Care accessible and affordable) the families of permit holders 4: Licensed doctors provide trauma, surgical, and captains. and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of 5: Among the most respected in the com- Boat Owners and munity, comparable with civic and religious Permit Holders leaders and professionals, such as doctors and lawyers 4: Comparable to management and white- collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Proportion of 5: 95–100% local “Local� is de�ned as coming from, and spend- Nonresident 4: 70–95% local ing their earnings within, the local �shing Employment 3: 35–70% local community. Nationals who are transient non- residents or considered outsiders in the �shing 2: 5–35% local community are not local. 1: Virtually no local permit holders EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 79 TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Crew (Those Earnings Compared 5: More than 50% above the regional average Ratio of annual earnings from �shing per crew Depending on to Regional Average 4: Between 10% and 50% above regional to the regional average earnings. In many Others for Access) Earnings average cases, the captain is an owner of a vessel or 3: Within 10% above the regional average permit, but in other cases, captains are consid- ered as crew. 2: Between 50% and 90% of the regional average 1: Less than half of the regional average Fishery Wages 5: More than 50% above the regional average Ratio of crew’s average daily wage to average Compared to 4: Between 10% and 50% above regional daily wage in the crew’s economic sphere (e.g., Non�shery Wages average village if all economic activity is within the 3: Within 10% above the regional average village, but nation if participates in national markets as a consumer). May differ from above 2: Between 50% and 90% of the regional measure if �shery is not year-round and there average is no income or income from other �sheries or 1: Less than half of the regional average other occupations. Education Access 5: Higher education is accessible The level of education attained by (available 4: High school–level education or advanced and affordable) the families (i.e., children) of technical training is accessible crew. 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic training is accessible 1: Formal education is not accessible Access to Health 5: Global standard treatment for illness is The level of health care accessible to (available Care accessible and affordable) the families of crew. 4: Licensed doctors provide trauma, surgical, and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing of 5: Among the most respected in the com- Crew munity, comparable with civic and religious leaders and professionals, such as doctors and lawyers 4: Comparable to management and white- collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Proportion of 5: 95–100% local “Local� is de�ned as coming from, and spend- Nonresident 4: 70–95% local ing their earnings within, the local �shing Employment 3: 35–70% local community. Nationals who are transient non- residents, or considered outsiders in the �shing 2: 5–35% local community, are not local. 1: Virtually no local crew Crew Experience 5: More than 10 years (skilled career crew) Average years of experience of crew members. 4: 5–10 years 3: 3–5 years 2: 1–3 years 1: 0 full years of experience (mostly new crew each season) Age Structure of 5: All working ages are well represented Age range of both captains and their crews. Harvesters 4: Slightly skewed toward younger or older 3: Skewed toward younger or older 2: Almost entirely younger or older, but work- ing age 1: Harvesters primarily younger or older than working age AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 80 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Post-Harvest Market Performance Ex-Vessel Price 5: Above 95% The indicator is the ratio of annual ex-vessel Performance versus Historic High 4: 85–95% prices to the average of the three highest an- 3: 70–85% nual ex-vessel prices in the past 10 years. 2: 50–70% 1: Below 50% Final Market Use 5: Premium human consumption (premium Premium products are typically distinct to quality and products) species, or species and source. Where a supply 4: High-value human consumption chain is diverse, score each weight by value. 3: Moderate-value human consumption 2: Low-value human consumption 1: Fish meal/animal feed/bait or nonconsumptive International Trade 5: 90–100% export Percentage of the �shery’s value that is from 4: 60–90% export �sh exported to higher-value markets for 3: 30–60% export consumption. 2: 2–30% export 1: Virtually no export Final Market 5: Greater than US$35,000 Average per capita GDP of the consumer Wealth 4: Greater than US$25,000 of a �shery’s primary �nal product (pounds/ 3: Greater than US$12,500 kilos weighted by GDP). If multiple important products, weight by value. 2: Greater than US$5,000 1: Less than U.S.$5,000 Wholesale Price 5: More than twice global average; Ratio of average price for �sh weight in Relative to Similar 4: 120–200% of global average wholesale (primary) �sh product from the base Products 3: Within 20% of global average country (converted to global currency), to a global average for similar species. 2: 50–80% of global average 1: Less than half global average Capacity of Firms to 5: Over 90% meet U.S. and EU health and Percentage of a country’s �sh exports that Export to the United labeling standards meet U.S. or EU health and labeling standards. States and the 4: 50–90% This is a country-level measure and refers to European Union 3: Less than 50% all processing capacity for export, including to regional markets. 2: A small amount of product meets U.S./EU standards 1: Banned in the United States or European Union, or cost of compliance with U.S./EU standards is prohibitive Ex-Vessel to 5: More than 200% increase in value Increase in value of processed wholesale Wholesale 4: 100–200% product from unprocessed ex-vessel product. Marketing Margins 3: 50–100% [(Wholesale $/lb)*yield]/(ex vessel $/lb) 2: 10–50% 1: Less than 10% increase in value Post-Harvest, Processing Yield 5: At feasible frontier Ratio of actual processing yield (kilos/pounds) Processing, and 4: Within 5% of the feasible frontier to the maximum processing yield technically Support Industry 3: Within 10% achievable. Performance 2: Within 25% 1: Less than 75% of maximum yield Shrink 5: Less than 5% Loss of �shery product value due to handling, 4: 5–10% spoilage, and theft. This is very likely to be an 3: 10–25% estimate. 2: 25–50% 1: More than 50% Capacity Utilization 5: Virtually year-round Days open for processing each year. Such days Rate 4: 75–95% of days would not normally include religious or civic 3: 50–75% holidays, or weekly rest days. 2: 20–50% 1: Less than 20% EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 81 TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Product 5: 75–100% of landings are enhanced Proportion of harvest meat weight going into Improvement 4: 50–75% certi�ed, branded, fresh premium, portioned, 3: 25–50% live, or value-added products. 2: 1–25% 1: No landings have enhancements Sanitation 5: Sanitation in landing and processing areas meets global health standards 4: Basic treatment, but falls short of global standards 3: Human waste is adequately handled, but �sh waste presents sanitation issues 2: Functional toilets are available, but �sh or �sh handlers are exposed to untreated sewage 1: Functional toilets are not available in land- ing or processing areas Regional Support 5: All types of support are plentiful Businesses 4: Some types of support are capacity con- strained or unavailable 3: Most types of support are capacity con- strained or unavailable 2: Support limited to variable inputs 1: Industry support is not locally available Post-Harvest Asset Borrowing Rate 5: Less than 1.75; cf. 30-year conforming Average ratio between the interest rate on Performance Relative to Risk- mortgage loans made in the industry to risk-free rates Free Rate 4: Less than 2.5; cf. personal bank loan over the last 3 years. If businesses can ac- 3: Less than 4; cf. good credit card rates cess the international credit markets, that is appropriate comparison; otherwise, use local 2: Less than 7; cf. bad credit card rates risk-free rate. 1: Greater than 7; usury Source of Capital 5: Unsecured business loans from banks/ Points to be assigned based on the category of venture capital lenders or investors that is most typically used 4: Secured business loans from banks/public in the �shery. Second scoring method offered if stock offering; investment from elsewhere in the supply chain (e.g., processors, exporters) is supply chain primary source of capital. 3: Loans from banks secured by personal (not business) assets/government-subsidized pri- vate lending/government-run loan programs/ international aid agencies; secured loans from elsewhere in supply chain 2: Microlending/family/community-based lending; loans from supply chain signi�cantly reduce margins 1: Ma�a/No capital available; exploitive relationship from elsewhere in supply chain Age of Facilities 5: First quarter of expected life; less than 7 Average age of the key durable processing years for a building capital unit (plants, catcher-processor vessels). 4: Second quarter of expected life; 7–15 years 3: Third quarter of expected life; 16–20 years 2: Fourth quarter of expected life; 21–25 years 1: Exceeding expected life; greater than 25 years Processing Owners Earnings Compared 5: More than 50% above the regional average Ratio of annual earnings per resident owner/ and Managers to National Average 4: Between 10 and 50% above regional manager to the regional average earnings. Earnings average This measure can include wealth accumulated 3: Within 10% above the regional average to traders/middlemen if they represent an important part of the supply chain. 2: Between 50% and 90% of the regional average 1: Less than half of the regional average AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 82 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Manager Wages 5: More than 50% above the regional average Ratio of resident owner/manager’s average Compared to 4: Between 10 and 50% above regional daily wage to average daily wage in their Non�shery Wages average economic sphere (e.g., village if all economic 3: Within 10% above the regional average activity is withing the village, but nation if participates in national markets as a consumer). 2: Between 50% and 90% of the regional average 1: Less than half of the regional average Education Access 5: Higher education is accessible The level of education attained by (available 4: High school–level education or advanced and affordable) the families (i.e., children) of technical training is accessible process owners/managers. 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic training is accessible 1: Formal education is not accessible Access to Health 5: Global standard treatment for illness is The level of health care accessible to (available Care accessible and affordable) the families of processing own- 4: Licensed doctors provide trauma, surgical, ers and managers. and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Social Standing 5: Among the most respected in the com- of Processing munity, comparable with civic and religious Managers leaders and professionals, such as doctors and lawyers 4: Comparable to management and white- collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Nonresident 5: 91–100% local Proportion of ex-vessel value processed by Ownership of 4: 70–90% local regionally owned processing capital Processing Capacity 3: 35–70% local 2: 5–35% local 1: Virtually no local processing ownership Processing Workers Earnings Compared 5: More than 50% above the regional average Ratio of annual earnings per worker to the to National Average 4: Between 10% and 50% above regional regional average earnings. Earnings average 3: Within 10% above the regional average 2: Between 50% and 90% of the regional average 1: Less than half of the regional average Worker Wages 5: More than 50% above the regional average Ratio of worker’s average daily wage to aver- Compared to 4: Between 10% and 50% above regional age daily wage in their economic sphere (e.g., Non�shery Wages average village if all economic activity is within the vil- 3: Within 10% above the regional average lage, but nation participates in national markets as a consumer). 2: Between 50% and 90% of the regional average 1: Less than half of the regional average EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 83 TABLE B.1: FPIs Output Indicators Revision (Revision and Additions Are Highlighted) (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Social Standing of 5: Among the most respected in the com- Processing Workers munity, comparable with civic and religious leaders and professionals, such as doctors and lawyers 4: Comparable to management and white- collar jobs 3: Comparable to skilled labor jobs 2: Comparable to unskilled blue-collar or service jobs 1: Among the least respected, such as slaves or indentured servants Education Access 5: Higher education is accessible The level of education attained by (available 4: High school–level education or advanced and affordable) the families (i.e., children) of technical training is accessible processing workers. 3: Middle school–level education or simple technical training is accessible 2: Basic literacy and arithmetic training is accessible 1: Formal education is not accessible Access to Health 5: Global standard treatment for illness is The level of health care accessible to (available Care accessible and affordable) the families of processing 4: Licensed doctors provide trauma, surgical, workers. and drug treatments 3: Nurses or medical practitioners provide emergency and routine drug treatments 2: Basic and simple drug treatment is accessible 1: Medical or drug treatment is not accessible Proportion of 5: 91–100% local “Local� is de�ned as coming from, and spend- Nonresident 4: 70–90% local ing their earnings within, the local �shing Employment 3: 35–70% local community. Nationals who are transient nonresidents, or are considered outsiders in the 2: 5–35% local �shing community, are not local. 1: Virtually no local workers Worker Experience 5: More than 10 years (skilled career crew) Average years of experience of workers. 4: 5–10 years 3: 3–5 years 2: 1–3 years 1: 0 full years of experience (mostly new crew each season) AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 84 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Macro Factors General Environmental 5: EPI of 69–100 The EPI considers factors such as disease, Environmental Performance Index 4: 62–69 water quality, air pollution, biodiversity, natural Performance (EPI) 3: 56–62 resources, and climate change. The EPI ranges from 1 to 100. Score is by 2010 EPI quintile. 2: 47–56 1: 1–47 Exogenous Disease and 5: Harvest unaffected by disease Extent to which harvest value is affected by Environmental Pathogens 4: Harvest reduced by less than 10% disease or pathogens, such as lobster shell Factors 3: Harvest reduced by 10–30% disease or red tides. 2: Harvest reduced by more than 30% 1: Harvest almost completely closed by shocks Natural Disasters 5: Harvest unaffected by disaster Extent to which harvest value is affected and Catastrophes 4: Harvest reduced by less than 10% by factors such as earthquakes, volcanoes, 3: Harvest reduced by 10–30% hurricanes. Harvest can be affected through stock effects of damage to harvest capacity. 2: Harvest reduced by more than 30% Gradual effects of climate change (e.g., shifts in 1: Harvest almost completely closed by shocks temperature or salinity) are not included here. Pollution Shocks 5: Harvest unaffected by shocks/piracy/ Extent to which harvest value in the reference and Accidents pollution year is affected by an episodic pollution event, 4: Harvest reduced by less than 10% such as an oil spill or piracy. 3: Harvest reduced by 10–30% 2: Harvest reduced by more than 30% 1: Harvest almost completely closed by shocks Level of Chronic 5: Not detectable Extent to which chronic pollution, such as from Pollution (Stock 4: Minimal detectable levels industrial or agricultural runoff, affects the Effects) 3: High levels detected stock. 2: Pollution affects stock growth 1: Pollution leading to severe stock decline Level of Chronic 5: No consumption affected Extent to which chronic pollution limits Pollution 4: Minimal consumption affects consumption. (Consumption 3: Of�cial consumption advisories Effects) 2: Temporarily ban harvest for consumption 1: Completely closed for consumption Country-Level Governance Quality 5: Above 0.92 (highest-performing 2010 Average of four indicators in the World Bank’s Governance quintile) Governance Indicators, each scored [−2.5,2.5] 4: 0.10 to 0.92 • Government Effectiveness 3: −0.43 to 0.10 • Regulatory Quality • Rule of Law 2: −0.81 to −0.43 • Control of Corruption 1: Below −0.81 (lowest-performing 2010 quintile) Governance 5: Above 0.96 (highest-performing 2010 Average of two indicators in the World Bank’s Responsiveness quintile) Governance Indicators, each scored [−2.5,2.5] 4: 0.41 to 0.96 • Voice and Accountability 3: −0.24 to 0.41 • Political Stability 2: −0.82 to −0.24 1: Below −0.82 (lowest 2010 quintile) Country-Level Index of Economic 5: EIF 69.2–100 Country’s scone Heritage Foundation’s Index Economic Condition Freedom 4: 62.5–69.1 of Economic Freedom. A detailed discussion 3: 57.1–62.4 of these factors and methodology is found in Miller and Holmes (2009). Scoring based on 2: 50.5–57.0 2010 percentile. 1: 1–50.5 Gross Domestic 5: Greater than US$30,000 Dollars are 2010 US$. Product (GDP) Per 4: Greater than US$12,400 Capita 3: Greater than US$6,000 2: Greater than US$2,500 1: Less than US$2,500 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 85 TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Property Rights and Fishing Access Proportion of 5: Virtually all The proportion of total harvest that is under Responsibility Rights Harvest Managed 4: 70–95% limited-access �shing regulation. This can Under Limited 3: 35–70% include both regulatory and de facto access Access rights. Likely 1 if no permits issued, or permits 2: 5–35% issued without limits. 1: Virtually none Transferability Index 5: Very Strong: Fully transferable through NA if no limited access. well-established, ef�cient market institutions 4: Strong: Fully transferable, but institutions are poor or illiquid 3: Moderate: Transferable, but with severe restrictions on who can hold, or how much 2: Weak: Transferable only under highly restricted and limited condition 1: Access rights not transferable Security Index 5: Very Strong: Access rights are completely Extent to which the government reduces or respected and are not diluted (e.g., by issuing dilutes the access rights. Even if no limited more access rights) by the government access, can be scored to reflect the extent of 4: Strong: Rights are mostly respected by the other restrictions that limit erosion of access government; generally survive changes in right (though probably low). government administration 3: Moderate: Rights are at risk of retraction or dilution with changes in administration 2: Weak: Rights are highly diluted or there is high political uncertainty 1: None: Access rights are not protected Durability Index 5: Very Strong: >10 years to perpetuity Duration of the property right. Can be scored 4: Strong: 6 to 10 years to reflect harvesters’ expectations of continued 3: Moderate: 1 to 5 years access, even if access licenses/rights are given without limits. 2: Weak: Seasonal 1: None: None/daily Flexibility Index 5: Very Strong: All decisions on time of Ability of right holders to be flexible in the tim- harvest, gear used, and handling practices are ing and production technology employed. Low in the owner’s control scores will reflect restrictions that force inef- 4: Strong: Minimal restrictions on time of �ciencies. Even without limited access, there harvest and technology may still be scorable restrictions (gear, seasons, 3: Moderate: Modest restrictions on time of areas) that limit access flexibility. harvest and technology 2: Weak: Signi�cant restrictions on time of harvest and technology 1: Time of harvest, gear used, and handling practices are not in the owner’s control Exclusivity Index 5: Very Strong: All decisions and access to the Ability of right holders to exclude those who do property are controlled by the right’s owner (rather not have the right from affecting the resource than those without rights, competing resource or market. Can still be scored to capture extent users [like recreational or by-catch �sheries]) of de facto intrusion if access is not limited. 4: Strong: Little intrusion on resource by those without rights 3: Moderate: Modest intrusion on resource by those without rights 2: Weak: Signi�cant intrusion on resource by those without rights 1: None: Completely unrestricted open access, despite putative right Harvest Rights Proportion of 5: Virtually all The proportion of total harvest that is under Harvest Managed 4: 70–95% rights-based �sheries management. Rights with Rights-Based 3: 35–70% include those for some �xed quantity or �sh (e.g., Management a quota), or a �xed share of landings in an area 2: 5–35% (e.g., a TURF gives 100% of landings in an area). 1: Virtually none Rights can be held by individuals or communities, and can include de facto and de jure rights. (Input rights, like trap tags, are strong access rights, but not harvest rights included in this section.) AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 86 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Transferability Index 5: Very Strong: Fully transferable through Probably NA if there is no harvest right. well-established, ef�cient market institutions 4: Strong: Fully transferable, but institutions are poor or illiquid 3: Moderate: Transferable, but with severe restrictions on who can hold, or how much 2: Weak: Transferable only under highly restricted and limited condition 1: Access rights not transferable Security Index 5: Very Strong: Harvest rights are completely Extent to which the government reduces or respected and are not diluted (e.g., by issuing dilutes the harvest rights. Probably NA if there more harvest rights) by the government is no harvest right. 4: Strong: Rights are mostly respected by the government; generally survive changes in government administration 3: Moderate: Rights are at risk of retraction or dilution with changes in administration 2: Weak: Rights are highly diluted or there is high political uncertainty 1: None: Harvest rights are not protected Durability Index 5: Very Strong: >10 years to perpetuity Duration of the harvest right. Probably NA if 4: Strong: 6 to 10 years there is no harvest right. 3: Moderate: 1 to 5 years 2: Weak: Seasonal 1: None: None/daily Flexibility Index 5: Very Strong: All decisions on time of Ability of right holders to be flexible in the harvest, gear used, and handling practices are timing and production technology employed. in the owner’s control Probably NA if there is no harvest right. 4: Strong: Minimal restrictions on time of harvest and technology 3: Moderate: Modest restrictions on time of harvest and technology 2: Weak: Signi�cant restrictions on time of harvest and technology 1: Time of harvest, gear used, and handling practices are not in the owner’s control Exclusivity Index 5: Very Strong: All decisions and access to the Ability of right holders to exclude those who do property are controlled by the right’s owner not have the right from affecting the resource or (rather than those without rights, competing market. Probably NA if there is no harvest right. resource users [like recreational or by-catch �sheries]) 4: Strong: Little intrusion on resource by those without rights 3: Moderate: Modest intrusion on resource by those without rights 2: Weak: Signi�cant intrusion on resource by those without rights 1: None: Completely unrestricted open access, despite putative right Comanagement Collective Action Proportion of 5: Virtually all Proportion of harvest where the primary Harvesters 4: 70–95% harvesters consider themselves to be members in Industry 3: 35–70% of organized associations. Organizations 2: 5–35% 1: Virtually none EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 87 TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Harvester 5: Harvesters effectively determine allocation Subjective measure of how much influence Organization of resources harvesting organizations have, either directly or Influence on Fishery 4: Harvesters have signi�cant influence in through political collective action, on manage- Management and determining allocation ment and access to the �shery. Access 3: Harvesters are politically active, but not controlling 2: Social or informal monitoring participation and allocation 1: No active effort or capacity to influence management Harvester 5: Harvesting organizations cooperatively Subjective measure of how much influence Organization determine marketing and operational details harvesting organizations have, either directly or Influence on 4: Extensive joint marketing through political collective action, on manage- Business and 3: Large subgroups facilitating marketing; joint ment and access to the �shery. Marketing purchasing 2: Small subgroups cooperating in purchasing or operations 1: No active effort or capacity to influence business operations Participation Days in Stakeholder 5: More than 24 days per year Days in stakeholder meetings per year spent Meetings 4: 12–24 by a participant in the �shery who is active in 3: 6–11 management. Note these are days with meet- ings, not FTE days. Include meetings of councils 2: 1–5 with public participation. 1: None Industry Financial 5: Virtually all Proportion of the �shery management budget Support for 4: 50–95% paid for by the harvesting or processing sector. Management 3: 5–50% 2: 1–5% 1: None Community Leadership 5: Widely recognized individual leader, The �shing community has strong leadership or small group of individual leaders, who capable of envisioning and implementing ef- provides vision for management and is able to fective management (this role may be provided attract stakeholders to that vision by processors). Bins 2 and 4 may be scored as 3: Ex of�cio leadership stations that maintain midpoints between descriptions. management institutions, but are not currently providing strong vision 1: No recognized leader providing vision for range of �shery stakeholders Social Cohesion 5: 6 points The resource users are socially connected 4: 5 points and interact regularly in �shing and non�sh- 3: 3–4 points ing spheres. Score one point for each of the following: 2: 1–2 points Common locations for gathering and 1: 0 points meeting on a regular basis for non�shery business, culture, or commerce Presence of shared social norms that facili- tate transactional trust Presence of shared public institutions (government, schools, markets) Absence of differences in social status or caste that prevent interaction Absence of religious differences and/or conflict Absence of cultural, ethnic, or tribal differ- ences that obstruct interaction Gender Business 5: Business management dominated by Extent of women’s influence (not just participa- Management women tion) in the management of harvesting and Influence 3: Business management is balanced between post-harvest businesses, including decision men and women making, ownership, and �nancing. This will not 1: Business management is dominated by men typically include development project staff or other “outsiders.� AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 88 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Resource 5: Resource management and allocation Extent of women’s influence (not just par- Management process is dominated by women ticipation) in the resource management and Influence 3: Resource management and allocation allocation process. Influential people can be process is balanced between men and women members of the harvesting or post-harvest 1: Resource management and allocation sectors, scientists, or community members who process is dominated by men do not work in the �shing sector. This will not typically include development project staff or other “outsiders.� Labor Participation 5: 80%–100% are women Proportion of women involved in the harvest in Harvest Sector 4: 60%–80% sector labor pool, either as captains or crew. 3: 40–60% 2: 20–40% 1: Less than 20% are women Labor Participation 5: 80%–100% are women Proportion of women in the post-harvest sector in Post-Harvest 4: 60%–80% labor pool, as buyers, sellers, managers, or Sector 3: 40–60% workers. 2: 20–40% 1: Less than 20% are women Management Management Inputs Management 5: Less than 5% of ex-vessel value Government, industry, and aid agency expendi- Expenditure to 4: 5–25% tures on �shery management activities includ- Value of Harvest 3: 26–50% ing research, enforcement, and management capacity development (but not infrastructure) 2: 51–100% 1: More than the value of harvest Enforcement 5: Strong capacity to enforce regulations for Enforcement capacity includes that of the Capability entire coastline, both nearshore and offshore government or �shing organization, or any other 4: Capacity to enforce regulations for near- group that can effectively enforce management. shore, but limited offshore 3: Capacity of enforce nearshore in most of the ports, very limited capacity offshore 2: Capacity or enforce only in major ports, minimal effective capacity offshore 1: No capacity to enforce Management 5: Stock’s life cycle within a single manage- Extent to which the life cycle or range of a stock Jurisdiction ment jurisdiction, or multiple jurisdictions, has can be managed under a single coordinated an effective, formal system for joint manage- plan, or through which ineffective management ment throughout the range in one jurisdiction can undermine efforts in 4: Effective coordination institution facilitates another. joint management throughout the region of primary importance 3: There is a coordination structure, but it does not have binding authority 2: Informal institutions for coordinating management 1: Jurisdictions effectively manage the same stock independently Level of Subsidies 5: No subsidies Receive one point each for four key categories 4: 1 subsidy category of “bad� subsidies: fuel subsidies, �sh access 3: 2 subsidy categories payment subsidies; capital or capital loan subsidies; and price support (through inputs or 2: 3 subsidy categories direct payments) 1: 4 subsidy categories EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 89 TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Data Data Availability 5: Annual (or other appropriate period) sampling for stock assessment, landings, and economic data available 4: Consistently collected and comprehensive landings and price data available 3: Limited reliable landings or price data avail- able; data irregularly collected or based on large samples 2: Available data based on small samples, or missing data, signi�cantly impedes making inferences needed for management 1: No data are centrally collected Data Analysis 5: Biological and economic data used in prospective analysis of management 4: Biological data dominate simple prospec- tive analysis 3: Biological or economic data are used to track performance, retrospectively 2: Data are used inconsistently or irregularly 1: No data analysis conducted in management process Management MPAs and 5: More than 25% Percentage of area used in species life cycle Methods Sanctuaries 4: 10–25% where �shing is closed or highly restricted. 3: 5–10% Include total area under rolling or seasonal closures. 2:Less than 5% 1: None Spatial 5: 75–100% Proportion of �shing ground managed through Management 4: 50–75% either direct control by TURF or designated 3: 25–50% community management regions, or through indirect control by limiting access points (launch 2:Less than 25% or landing sites) 1: None Fishing Mortality 5: Hard TAC established against which nearly Extent to which �shing mortality is an explicit Limits all �shing mortality is counted element of management. 4: Hard TAC established, but there are sources of unaccounted mortality totaling less than 10%; or TAC is adjusted from biological guide- line to compensate for sources of greater unaccounted mortality 3: There is a guideline mortality level that is generally met; hard TAC exceeded 10–50% by unaccounted mortality 2: Frequently exceeded guideline; hard TAC exceeded by more than 50% 1: Fishery does not have an explicitly mortality target Post-Harvest Markets and Landings Pricing 5: Virtually all Proportion of the harvest sold in a transparent Market Institutions System 4: 70–95% daily competitive pricing mechanism, such as 3: 35–70% an auction or centralized ex-vessel to wholesale market wherein sellers interact with many buy- 2: 5–35% ers and prices are public information. 1: Virtually none Availability of 5: Complete, accurate price and quantity Scores the ability of the market to provide Ex-Vessel Price information available to market participants timely information to harvesters to which they and Quantity immediately can react by changing what or when they land. Information 4: Reliable price and quantity information is available prior to the next market clearing 3: Price information is available but no timely quantity information 2: Price and quantity information are inac- curate, lagged, or available to only a few 1: No information available AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 90 A PPEND IX B — SUGGESTED REV ISION A ND A D D ITIONA L IND IC ATOR S TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Number of Buyers 5: Highly competitive Typical number of buyers of ex-vessel product 4: 4–6 buyers accessible to a seller in a given market. If 3: 2–3 competing buyers there are many landing sites, this is the buyers per landing site. If harvesters are generally 2: A small number of coordinating buyers indentured to a single buyer through credit 1: There is one buyer relationships, there is one buyer. Degree of Vertical 5: Virtually all Proportion of harvest where the primary har- Integration 4: 70–95% vester and primary processor/distributor are the 3: 35–70% same �rm. The role of vertical integration here is to ensure harvest and delivery of �sh under 2: 5–35% a common management, increasing ef�ciency 1: Virtually none over asynchronous market transactions. Level of Tariffs 5: Virtually none Of�cial tariff rates charged for exports or 4: 0.5–2.5% imports to consumption markets. 3: 2.5–5% 2: 5–10% 1: Over 10% Level of Nontariff 5: Are not used to limit international trade Nontariff barriers include quantity restrictions Barriers 4: Have very limited impact on international (import quotas), regulatory restrictions, invest- trade ment restrictions, customs restrictions, and 3: Act to impede some international trade direct government intervention. 2: Act to impede a majority of potential international trade 1: Act to effectively impede a signi�cant amount of international trade Infrastructure International 5: Ocean/Air shipping services are readily The quality of the service available to access Shipping Service available at lower than average rates global high-value markets, such as the United 4: Ocean/Air shipping services are readily States or European Union (regardless of available at average rates whether product currently exported). Average of 3: Ocean/Air shipping services are readily the two measures (one for ocean shipping and available at higher than average rates another one for air shipping) on the left. 2: Ocean/Air shipping services are available but irregular 1: International shipping is not available at reasonable rates Road Quality Index 5: High-quality paved roads and extensive Travel time-weighted average road quality highways between the �shery’s primary port and the 4: Primarily paved two-lane roads and moder- most practical export shipping port for exported ate highway product. 3: Primarily paved two-lane roads and minimal highway 2: Paved two-lane roads and well-graded gravel roads 1: Poorly maintained gravel or dirt roads Technology 5: Cell phones/�sh �nders/computers/pro- Adoption cessing/production technology are readily available 4: Cell phones/�sh �nders, and so forth, are common, but some other technology is not always available 3: Cell phones/�sh �nders, and so forth, are common, but some other technology is dif- �cult to obtain 2: Cell phones are common, but most other technology is prohibitive 1: Very little advanced technology is acces- sible for the industry EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X B — S U GGE ST E D RE VISION AND ADDIT IONA L IND IC ATOR S 91 TABLE B.2: FPIs Input Indicators Revision (Continued) COMPONENT DIMENSION MEASURE SCORE SYSTEM ADDITIONAL EXPLANATION Extension Service 5: Broad extension service with �eld of�ces Degree to which government or NGOs help and close linkage with research community harvesters improve �shing techniques or man- 4: Extension service with moderate �eld cov- agement through extension activities. erage and adequate linkage with the research community 3: Extension service, but with weak links to the research community 2: Minimal, poorly supported extension service 1: No extension service Reliability of 5: Reliable electrical grid provides power in Utilities/Electricity suf�cient quantity to prevent product loss 4: Processors rely on grid, but maintain backup generators 3: Supply chains rely on own generation capacity 2: Supply chain sometimes loses product due to condition or irregular fuel supply for generators 1: Reliable generators or fuel supply not available Access to Ice and 5: Ice is available in various forms and in Refrigeration suf�cient capacity to support fresh icing of all �sh that needs to be iced 4: Ice is available in various forms, but quantity limits prevent applying to entire catch throughout supply chain 3: Ice is available in limited form and quantity, and thus applied only to most valuable por- tions of catch 2: Ice is available but capacity constrained; ice often reused, or used through melting stage 1: Ice quantities are extremely limited AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 AP P E N D I X C — MI LE ST ONE S OF F ISHE RY P E RF ORMA NC E IND IC ATOR S (FPIs) 93 Appendix C: MILESTONES OF FISHERY PERFORMANCE INDICATORS (FPIs) C.1. CONCEPT WORKSHOP (FEBRUARY 10, C.2. APPLICATION WORKSHOP (MAY 11, 2011, 2010, LONDON) HONOLULU) Summary: �sheries experts reviewed the concept and Summary: 12 �sheries economist reported 15 pilot three initial case studies. Recommendations were case studies of FPIs, mostly in Western countries. made regarding the scope and content. Recommendations were made on the applicability, Participant list: scoreability, weighting system, quality control, • James L. Anderson, University of Rhode Island and so on. • Christopher M. Anderson, University of Rhode Participant list: Island • James L. Anderson, World Bank • Mike Arbuckle, World Bank • Christopher M. Anderson, University of Rhode • Tim Bostock, DFID Island • Steve Cunningham, IDDRA • Jingjie Chu, World Bank • Aaron Hatcher, University of Portsmouth • Gunnar Knapp, University of Alaska • Arthur Neiland, IDDRA • Gil Sylvia, Oregon State University • Stetson Tinkham, International Coalition of Fisheries • Sherry Larkin, University of Florida Associations (ICFA) • Frank Asche, University of Stavanger • James Wilen, Department of Agricultural and • Atle Guttormsen, Norwegian University of Life Resource Economics, UC Davis Sciences • Erin Priddle, DeFRA • Matt Freeman, Louisiana State University • Richard Parsons, DeFRA • Ganesh Thapa, University of Rhode Island • Charlotte Tindall, MRAG/Indep • Tim Ward, South Australian Research and • Pam Masons, DEFRA Development Institute • Nigel Edwards, FDF • Daniel Huppert, University of Washington • Frank Asche, University of Stavanger • Eric Thunberg, National Oceanic and Atmospheric • Ragnar Tveteras, University of Stavanger Administration • Mike Parker, Fishing business representative, Young’s Bluecrest • Carl Christian Smidt, OECD, Fisheries economist • Heike Baumüller, Chatham House AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 AP P E N D I X D — F P Is AP P L ICAT ION—OUT P UT RE SULTS 95 Appendix D: FPIs APPLICATION—OUTPUT RESULTS INDONESIA PHILIPPINES ICELANDIC COMPONENT DIMENSION MEASURE BSC BSC LOBSTER Ecologically Fish Stock Health Proportion of Harvest with a Third-Party Certi�cation 1 1 5 Sustainable Fisheries and Environmental Performance Fish Stock Sustainability Index (NMFS) 1 1 5 1.8 1.3 4.8 Percentage of Stocks Over�shed 1 2 5 Nonlandings Mortality 4 1 4 Harvest Sector Harvest Performance Landings Level 2 1 5 Performance Excess Capacity 1 1.7 2 2.7 5 5.0 Season Length 2 5 5 Harvest Asset Ratio of Asset Value to Gross Earnings 1 1 5 Performance Total Revenue versus Historic High 3 2 5 Asset (Permit, Quota) Value versus Historic High 5 5 2 3.2 3.2 4.2 Borrowing Rate Relative to Risk-Free Rate 5 5 4 Source of Capital 2 2 5 Functionality of Harvest Capital 3 4 4 Risk Exposure Annual Total Revenue Volatility 3 3 5 Annual Landings Volatility 3 5 5 Intra-annual Landings Volatility 3 5 5 Annual Price Volatility 4 3.7 5 4.3 5 4.9 Intra-annual Price Volatility 4 5 5 Spatial Price Volatility 5 3 5 Contestability and Legal Challenges 4 4 4 Owners, Permit Earnings Compared to National Average Earnings 5 2 4 Holders, and Captains Fishery Wages Compared to Non�shery Wages 5 1 4 Education Access 4 4 5 4.0 2.8 4.5 Access to Health Care 2 2 5 Social Standing of Boat Owners and Permit Holders 5 3 4 Proportion of Nonresident Employment 3 5 4 Crew Earnings Compared to National Average Earnings 5 3 5 Fishery Wages Compared to Non�shery Wages 5 3 5 Education Access 2 2 5 Access to Health Care 2 2 5 3.5 3.3 4.3 Social Standing of Crew 2 2 3 Proportion of Nonresident Employment 3 5 3 Crew Experience 4 4 4 Age Structure of Harvesters 5 5 5 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 96 A PPEND IX D — FPIs A PPLICATION—OUTPU T R ES ULTS INDONESIA PHILIPPINES ICELANDIC COMPONENT DIMENSION MEASURE BSC BSC LOBSTER Post-Harvest Market Performance Ex-Vessel Price versus Historic High 2 4 5 Performance Final Market Use 4 4 4 International Trade 5 3 5 Final Market Wealth 5 5 5 3.7 3.3 4.3 Wholesale Price Relative to Similar Products 4 2 3 Capacity of Firms to Export to the United States and 5 4 5 European Union Ex-Vessel to Wholesale Marketing Margins 1 1 4 Processing and Yield of Processed Product 5 2 4 Support Industry Performance Capacity Utilization Rate 5 3 4 Product Improvement 5 5.0 5 3.2 5 4.4 Regional Support Businesses 5 1 5 Time to Repair 5 5 5 Post-Harvest Asset Borrowing Rate Relative to Risk-Free Rate 4 5 4 Performance Source of Capital 2 3.3 2 4.0 4 4.2 Age of Facilities 4 5 4 Processing Owners Earnings Compared to National Average Earnings 5 4 5 and Managers Manager Wages Compared to Non�shery Wages 3 3 4 Education Access 5 5 5 4.2 4.3 3.7 Access to Health Care 5 5 5 Social Standing of Processing Managers 3 4 4 Nonresident Ownership of Processing Capacity 4 5 3 Processing Workers Earnings Compared to National Average Earnings 3 3 3 Worker Wages Compared to Non�shery Wages 3 3 4 Education Access 3 3 5 Access to Health Care 3 3.4 2 3.0 5 3.7 Social Standing of Processing Workers 3 3 2 Proportion of Nonresident Employment 5 4 3 Worker Experience 4 3 4 Note: Scores below 2 are highlighted as they are within the warning zone, indicating immediate actions need to be taken with regard to those aspects. EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) AP P E N D I X E — F P I s AP P L ICAT ION—INP UT RE SULT S 97 Appendix E: FPIs APPLICATION—INPUT RESULTS INDONESIA PHILIPPINES ICELANDIC COMPONENT DIMENSION MEASURE BSC BSC LOBSTER Macro Factors General Environmental Environmental Performance Index (EPI) 3 4 4 3.0 4.0 4.0 Performance Exogenous Environmental Disease and Pathogens 5 5 5 Factors Natural Disasters and Catastrophes 3 3 5 Pollution Shocks and Accidents 3 4.2 5 4.6 5 5.0 Level of Chronic Pollution (A) 5 5 5 Level of Chronic Pollution (B) 5 5 5 Governance Governance Indicator—Effectiveness 2 3 5 2.0 2.5 5.0 Governance Indicator—Voice and Accountability 2 2 5 Economic Condition Index of Economic Freedom 3 3 4 2.5 2.0 4.5 Gross Domestic Product (GDP) Per Capita 2 1 5 Property Rights and Access Proportion of Harvest Managed Under Limited 1 1 5 Responsibility Access Transferability Index 1 1 5 Security Index 4 2.5 1 1.7 3 4.2 Durability Index 3 1 3 Flexibility Index 3 5 5 Exclusivity Index 3 1 4 Harvest Proportion of Harvest Managed with Rights-Based 1 1 5 Management Transferability Index 1 1 5 Security Index 4 2.7 1 1.7 3 4.0 Durability Index 3 1 2 Flexibility Index 3 5 5 Exclusivity Index 4 1 4 Collective Action Participation in Harvester Organizations 4 1 5 Harvester Organization Influence on Fishery 3 2 3 Management and Access 3.7 1.3 4.3 Harvester Organization Influence on Business and 4 1 5 Marketing Management Management Expenditure to Value of Harvest 5 5 5 Management Employees to Value of Harvest n/a 1 5 Management Employees per Permit Holder n/a 1 5 Inputs 3.7 2.6 5.0 Research as a Proportion of Fisheries Management 1 1 5 Budget Level of Subsidies 5 5 5 AGR I C U LT U R E A N D RURAL DE VE L OP ME NT DISCUSSION PA PER 52 98 A PPEND IX E — FPIs A PPLIC ATION—INPU T R ES ULTS INDONESIA PHILIPPINES ICELANDIC COMPONENT DIMENSION MEASURE BSC BSC LOBSTER Data Data Availability 3 1 5 2.5 1.5 5.0 Data Analysis 2 2 5 Participation Days in Stakeholder Meetings 3 2 2 1.5 1.5 3.0 Industry Financial Support for Management 1 1 4 Post-Harvest Markets and Market Landings Pricing System 4 1 2 Institutions Availability of Ex-Vessel Price and Quantity 2 1 5 Information Number of Buyers 5 3.2 5 2.3 2 3.5 Degree of Vertical Integration 3 1 2 Level of Tariffs 1 1 5 Level of Nontariff Barriers 4 5 5 Infrastructure International Shipping Service 4 3 4 Road Quality Index 2 2 4 Technology Adoption 4 2 5 3.5 2.3 4.7 Extension Service 1 2 5 Reliability of Utilities/Electricity 5 2 5 Access to Ice and Refrigeration 5 3 5 EVALUATION OF NEW FISHERY PERFORMANCE INDICATORS (FPIs) REFERENCES 99 REFERENCES AFTEN. 2011. 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