Methodology - European Commission - Europa EU

Ref. Ares(2015)1349665 - 27/03/2015

Framework contract MARE/2011/01 Evaluation and impact assessment activities for DG MARE. Lot 3 – retrospective and prospective evaluations on the international dimension of the common fisheries policy Specific contract n° 09 Economic analysis of the European Union tuna fleets involved in fishing activities governed by Regional Fisheries Management Organisations (RFMO) or Fisheries Partnership Agreements (FPA)

Methodology December 2014

MUL166R01

DG MARE 2011/01/Lot 3 – CS09

décembre 2014, MUL166R01B

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This methodology has been prepared with the financial support of the European Commission. The views expressed in this study are those of the authors and do not necessarily reflect the views of the European Commission or of its services. The content of this report may not be reproduced, or even part thereof, without explicit reference to the source. This report must be cited as follows: COFREPECHE, MRAG, NFDS et POSEIDON, 2014. Economic analysis of the European Union tuna fleets – Methodology. Contrat cadre MARE/2011/01 - Lot 3, contrat spécifique n° 09. Bruxelles, 30 p. COFREPECHE: 32 rue de Paradis, 75010 Paris, France. [email protected]

Methodology – Final version

Report ref.: MUL166R01B Number of pages: 30

Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

Date issued: 18 December 2014

DG MARE 2011/01/Lot 3 – CS09

Novembre 2014, MUL166R01B

Table of contents 1

Introduction .................................................................................................................................... 1

2

Typology of the EU’s external fishing fleet .................................................................................. 2

3

First point of sale analysis ............................................................................................................ 3

4

5

6

3.1

Specific objectives.................................................................................................................... 3

3.2

Method ..................................................................................................................................... 3

3.3

Data types and sources ........................................................................................................... 4

3.4

Possible presentation of the results of the flow analysis and marketing ................................... 5

3.4.1

Flow analysis.................................................................................................................... 5

3.4.2

Price at first sale............................................................................................................... 6

3.4.3

Historical analysis of trade in quantity and/or price .......................................................... 7

Analysis of the operating costs of the different segments ........................................................ 8 4.1

Collection of accounting and financial data .............................................................................. 8

4.2

Data processing ....................................................................................................................... 8

4.3

Data analysis............................................................................................................................ 8

4.4

Definition of a dynamic economic model .................................................................................. 9

Analysis of the economic and financial results of the different segments ............................. 11 5.1

Analysis of the operating cycle ............................................................................................... 12

5.2

Performance indicators .......................................................................................................... 13

Analysis of direct and indirect value added and its components ............................................ 14 6.1

Estimates of jobs created ....................................................................................................... 16

6.1.1

Direct jobs ...................................................................................................................... 16

6.1.2

Indirect upstream jobs .................................................................................................... 17

6.1.3

Indirect downstream jobs ............................................................................................... 18

6.2

Measure of the overall value added generated ...................................................................... 18

6.2.1

Overall value added ....................................................................................................... 18

6.2.2

Direct value added ......................................................................................................... 19

6.2.3

Indirect value added ....................................................................................................... 21

6.3

Indicators to present and analyse the results ......................................................................... 23

Annexes: .................................................................................................................................................. I Annex 1: Examples of European fleet segmentation ............................................................................ I

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List of acronyms used: ACP ASEAN AU VA CAU CECAF CFP COMEXT DVA EC EU EUMOFA FAD FAO FPA GTA GVA IVA ICCAT ICES IOTC MERCOSUR MS NAFO NGO RFMO RFO SFPA STECF T

African, Caribbean and Pacific Group of States Association of Southeast Asian Nations Activity Unit Value Added Cost per Activity Unit Fisheries Committee for the Eastern Central Atlantic Common Fisheries Policy Statistical database on the intra- and extra-trading goods of all EU member states Direct Value Added European Commission European Union European Market Observatory for fisheries and aquaculture Fish Aggregating Device United Nations Food and Agriculture Organisation Fisheries Partnership Agreement Global Trade Atlas Gross Value Added Indirect Value Added International Commission for the Conservation of Atlantic Tunas International Council for the Exploration of the Sea Indian Ocean Tuna Commission Mercado Común del Sur Member State (European Union) Northwest Atlantic Fisheries Organisation Non-Governmental Organisation Regional Fisheries Management Organisation Regional Fisheries Bodies Sustainable Fisheries Partnership Agreement Scientific, Technical and Economic Committee for Fisheries Turnover

UEMOA

West African Economic and Monetary Union

WTO

World Trading Organisation

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Décembre 2014, MUL166R01B

Introduction

An analysis of the dynamics of the European Union (EU) fleet operating outside European waters1 through Fisheries Partnership Agreements (FPA), soon to be Sustainable Fisheries Partnership Agreements (SFPA2), is crucial to the assessment and renewal of current protocols, to the development of strategies aimed at reactivating dormant agreements and to enter new ones. The analysis is also useful to improve the EU's contributions as members of Regional Fisheries Management Organisations (RFMOs). This technical note describes the methodology proposed to develop a typology of fleet and markets, necessary to analyse turnover and other accounting and financial indicators as well as the study of the direct and indirect value added, its breakdown between economic agents and their geographical distribution. The note also considers the time scales for time series, selected indicators and expected data sources. In this point, if producer organisations and vessel owners are currently the most reliable source of financial and accounting data, there remains significant uncertainty regarding the possibility of obtaining data in full, mainly due to confidentiality issues. Thus, in the event of the necessary data sets being unavailable, a harmonised method will be proposed to obtain the most reliable result possible, for any fleet segment studied. Hypotheses will be developed for each fleet segment based on expert advice to ensure an overall consistency and make it possible to compare dynamics at regional or global scale. The analysis aims to estimate direct employment, direct value added and operating revenue for each fleet segment, indirect value added and indirect employment (in economic sectors upstream and downstream of fishing activity). This is done in 5 steps: 1. Split EU vessels into homogeneous fleet segments, in particular according to identical or similar technical characteristics and fishing strategies, and level of dependency on fishing areas and fisheries resources, including those relating to FPAs; 2. Establish a typology of flows of fisheries product caught by EU vessels, from landing to consumers, through processing and packaging; 3. Estimate the accounting and financial results of each fleet segment. Coast and earning will, as much as possible, be allocated by fishing area (EU community waters, international waters and fishing areas in the waters of third countries), taking into account the level of effort in each area; 4. Determine the number of direct and indirect employment associated from the vessels’ activities; 5. Estimate the direct, indirect and total value added, broken down by economic agents (operators, employees and state), by function (work remuneration, capital remuneration, investment renewal, taxes and duties), as well as its distribution between political entities (EU, third countries and other countries). On a case-by-case basis, and in order to obtain quantitative and the most accurate information possible, field work may be included. Other data may be used, particularly those compiled in previous studies, regional studies or retrospective and prospective evaluation studies of various FPAs (and other sources detailed in this note).

1

For the sake of simplicity, in this note "European waters" refers exclusively to the waters of EU Member States involved in the application of the Common Fisheries Policy (CFP). 2 Agreements concluded since the end of 2014 are called “Sustainable Fisheries Partnership Agreements (SFPA)” instead of the previous “Fisheries Partnership Agreements”. Page 1 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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Typology of the EU’s external fishing fleet

2.1 – Specific objectives The fleet typology is established by grouping vessels with similar technical characteristics and operating strategies. The resulting fleet segments are the most homogeneous sets possible and, it is assumed, that they also are homogeneous in terms of economic dynamics. This fleet typology therefore enables to build segments that are more homogeneous, which are used as the basic unit in the accounting, financial and economic analysis. 2.2 – Method The classification into fleet segments of EU vessels operating outside EU waters aims to facilitate the analysis of a complex reality. Depending on the case, particularly based on the data available, the typology may be obtained from: 

either a statistical data analysis methods3;



or “expert” knowledge, involving cumulative knowledge based on experience.

2.3 – Data types and sources The data required for the typology of the EU’s external fleet, whether it is based on a statistical data analysis or on “expert” knowledge, will cover at least the following variables, bearing in mind that some may have some degree of evident or hidden correlation (which the data analysis should help identify): 





Vessel technical characteristics and fishing gear: o Length, tonnage, vessel’s main and auxiliary engine power data o Fishing gear used o Fishing aids employed (i.e. Fish Aggregating Devices - FADs and support vessels) Catch and fishing effort: o Vessel’s overall catch and effort data o Spatial and temporal distribution data of catch and effort o Catch species composition data o Data on various components of fishing effort (i.e. cruising time, search time, fishing time) Economic variables: o Amount of fixed capital o Annual turnover o Modality of crew remuneration and total payroll

The use of these variables in the typology will depend on data availability and representativeness. Various sources may be used; In the first instance fishing vessel operators and producer organisations. Data on fishing vessel characteristics may also be collected from the EU fishing vessel register4. Compilation of catch or effort data per vessel per month and by area of jurisdiction and coastal States should be possible from data provided by Member States (MS) to the services of the European Commission (EC). More detailed spatial and temporal data exists, but it is not directly available and access would require specific agreements with operators and producer organisations, or with national administrations of flag States.

3 see for example the presentation of statistical methods in

http://fr.wikipedia.org/wiki/Analyse_des_donn%C3%A9es

4 http://ec.europa.eu/fisheries/fleet/index.cfm

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Finally, aggregate data corresponding to the segments derived from the typology may possibly be extracted from reports prepared and published by the Scientific Technical and Economic Committee for Fisheries (STECF), including reports on fishing effort and on the economic performance of the EU fishing fleet 5. Similarly, it should be possible to extract some data from the International Council for the Exploration of the Sea (ICES) database and from the Northwest Atlantic Fisheries Organization (NAFO) database with respect to the North Atlantic or from any relevant tuna RFMO (i.e. ICCAT6 and IOTC7) or Regional Fisheries Bodies (RFB) such as CECAF8 (Fishery Committee for the Eastern Central Atlantic) for demersal and small pelagic species fisheries on the West African coast. In addition, information previously collected through FPA assessments conducted on the three oceans (eastern Atlantic, south-west Indian Ocean and Central West Pacific) and particularly “regional” studies may be used to achieve the typology of EU tuna vessels. It will also be possible to ask operators and producer groups. For an example see Annex 1, where several typology levels are proposed, based on expert knowledge originating from past evaluations of FPA and their protocols. These proposals are complemented by a diagram showing an empirical application of segmentation for the distant EU tuna fleet.

3 3.1

First point of sale analysis Specific objectives

The objectives of this section are threefold: 1. Establish a simplified analysis of the various sectors in which the segments of the external EU fleet operate, by briefly describing the path of fish products from capture to final consumers9 and with more detail on the flow and characteristics of first point sale of fish; 2. Identify the market or markets in which fishery products are offered for sale for the first time (first sale) and estimate the factors fixing these prices, in order to assess the turnover generated by fishing activities in case of difficulties accessing financial records; 3. Subsequently identify flows of goods and services and cash flows established between the fishing company and its direct customers or suppliers, and the Value Added (VA) / turnover ratios observed in the relevant economic sectors and geographical areas, therefore allowing a detailed estimate of the indirect value added generated by the fishing activity of the EU fleet.

3.2

Method

The classification of product flow is used to inform the main fish trading pathways and the various stages that take place from landing, packaging and processing through to consumption, and to better characterise the economic momentum behind these flows. This will be the basis for the financial and economic analysis including the estimate of the number of jobs and the creation of the VA in the processing and packaging industry (upstream sector10) as well as their distribution between countries within which these product flows are observed.

5 http://stecf.jrc.ec.europa.eu/reports 6 https://www.iccat.int/en/accesingdb.htm 7 http://www.iotc.org/data/datasets 8 http://www.fao.org/fishery/rfb/cecaf/en 9 The downstream sector of first sale requires a simplified analysis. It can indeed

influence the sale and landing / transhipment strategies of EU vessels fishing outside EU waters. 10 In operational base, landing and refuelling ports, data may be gathered to identify intermediate consumption of fishing operations and assess employment and upstream value added. Page 3 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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The product flow typology can be established using a number of discriminating factors (or filters) as follows:     

Geographical area of landing or transhipment, Species or group of species landed or transhipped, Quality and other differentiating criteria of raw product (size, weight, onboard processing, etc.), Type of packaging and processing (for human / animal consumption, fresh, canned, frozen, whole, loin, etc.), Final market (EU, Eastern Europe, Asia, African, Caribbean and Pacific - ACP, North Africa, subSaharan Africa, etc.)

The aim is to quantitatively define the main flows and the various steps that fish products follow from the vessel to final consumer. The quantification of flow is in live weight11 throughout. Conversion factors from live to net weight are used for the output of factories, exports, imports and consumption that use net weight only. A tree diagram may be used to specify and inform the main flows from EU vessels landing and transhipment. Flows of fishery products may be common to several segments targeting the same species or group of species with different fishing gears. Fish product flow data series will cover 5 to 10 years12. The aim is then to document the commercial arrangements13 of first sales, to reflect market opportunities and strategies of EU vessels14 operators notably for vertically integrated companies15 and large seafood processing and trading groups. Another aim is to assess the prospects for future investments in production facilities, dependent on the global economic situation and demand forecasts for different product types. Finally, available information permitting, the different first sale markets will be described dynamically specifying:    

3.3

Supply and demand of main products (including supply sources16 and competition’s products) on a global scale and its effects on the EU market; Price setting (identifying the main factors involved in price variations); Factors influencing price elasticity of supply (i.e. seasonality, competition with a similar product, competition by area); Factors influencing price elasticity17 (direct or cross) of demand.

Data types and sources

Wherever possible, sales prices of fishery products will come from cross-checking prices of operators and consignees (landed price), processing plants (purchase of raw materials and sale of finished or semifinished product). For comparison these data may also be extracted from public databases when 11 Live weight caught 12 The choice of a given time period will have to be systematically justified in the annexes of the analysis. 13 For example, the tariff and non-tariff barriers to trade measures of the World Trade Organization (WTO) and the derogations

put in place by coastal States, port States and importing/exporting States related to fish caught by EU fleets placed on the markets. 14 And specify limits in terms of fisheries resources availability and access, the EU fleet capacity to supply their markets, considering commercial advantages and constraints from the EU policy framework (CFP, FPA, trade agreements) and other market constraints (regional, national and international frameworks). 15 Vertical integration: activities at different levels of the value chain by a group of companies owned by common shareholders or owners; Horizontal integration: similar activities at the same level of the supply chain of several sectors by a group of companies owned by common shareholders or owners (Consultant’s definitions). 16 From non-EU fleet and non-EU vessels with an EU link (vessels flying third country flags, with capital and operators similar to European-registered vessels, i.e. Spanish or French vessels registered in the Seychelles or Mauritius fishing for tuna. 17 « Ratio of the change in the amount requested or supplied to the price changes that caused the change » (translated from interactive terminology for Europe database, IATE: http://iate.europa.eu, accessed 17 December 2014). Page 4 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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available, such as FAO GLOBEFISH18, EU COMEXT or EUMOFA19; and the Global Trade Atlas (GTA) for tuna products when possible20. In the absence of relevant data in countries where EU external fleet products are present, the prices of imported products from these countries into the various countries importing fisheries products caught by EU vessels may possibly be considered as first approximations (indicators available in COMEXT and EUMOFA). In future regional assessments or for each retrospective and prospective evaluation, comparing the prices from different sources will be paramount. This would help clarify empirically the scope of their benefits by DG MARE. The main information sources to perform flow analysis are:    

 

3.4

EU legislation (notably through the DG Trade database, export helpdesk, TARIC database and DG SANCO), third countries legislation and international legislation on trade in fisheries products. Reports and raw data of the FPA evaluation reports and regional studies of the framework contract MARE 2011/01 Lot 3 covering sections “market and trade” (including trade flows diagrams). Similar study reports from technical and financial partners and Non-Governmental Organisations (NGO). Databases of regional economic markets areas (EU, WAEMU, MERCOSUR, ASEAN, GTA, etc.), for major countries involved in trade flows (i.e. databases from Norway 21, Iceland22, Greenland23, Canada24, Morocco25) and study reports of these databases in order to understand the marketing of products from the active EU fleets in mixed agreements. Press articles (Le Marin, Seafood Source News, Intrafish, etc.). Sector stakeholders (institutions including DG MARE, DG Trade and DG SANCO and regional economic organisations, operators, processors, importers).

Possible presentation of the results of the flow analysis and marketing

The tables and charts below may provide a basis for the presentation of results. 3.4.1

Flow analysis

The pattern of flow analysis of the concerned products can be adapted from the example below, focusing the quantitative analysis on the downstream sector (catch - landing - first sale - processing).

18 http://www.globefish.org/homepage.html, FAO information source on international trade of fisheries products. 19

In the COMEXT database, the price of the imported product is the value of imported goods at the time and place where it crosses the border of a MS (Commission Regulation (EU) No 113/2010, Article 4). This value would then correspond to the "CIF" purchase price (cost, insurance and freight) submitted to the customs authorities of the MS by the exporter. It could be possible to identify the price of first sale by going upstream in the sector but it would increase the level of uncertainty in the estimate. The EUMOFA database includes first sale prices but does not appear to have the first sale price for products caught by the EU's external fleet landed in third countries. 20 By subscription only. The GTA database is particularly well documented for tuna products. 21 http://www.ssb.no/en/jord-skog-jakt-og-fiskeri/statistikker/fiskeri 22 http://www.statice.is/Statistics/Fisheries-and-agriculture/Catch-and-value-of-catch 23 http://www.stat.gl/dialog/topmain.asp?lang=en&subject=Fisheries and Catch&sc=FI 24 http://www.dfo-mpo.gc.ca/stats/commercial/sea-maritimes-fra.htm 25 http://www.onp.co.ma/Onp/Home.aspx Page 5 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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Catch


Processing

Marketing

Final market place

Local fish trade

Local transport means

National market

Imports 46 000 t/year Freshwater fisheries 12 000 t/year

74 000 t/year

Traditional and artisanal catch

Traditional processing

38 000 t/year

12 000 t/year

Marine aquaculture

Modern processing

5 000 t/year

National industrial catch 7 000 t/year Foreign industrial catch

86 000 t/year

11 500 t/year

Packaged frozen 12 000 t/year

86 000 t/year

Cargo

Africa t/year

11 500 t

negligible

Cargo freezer

Mauritius, Kenya and Seychelles

12 000 t/year

14 500 t/year

Landed directly in port

Europe 39 250 t/year

14 500 t/year

20 000 t/year

Packaged frozen onboard

Transhipment to cargo

Asia (Thailand, Korea, etc.)

(including EU

18 500 t/year

4 000 t/year

2 750 t/year

10 000 t/year)

Figure 3.1: Sectors of fisheries products in Madagascar (data: averages 2008-2012 live weight) Note: Key components of tuna industries are displayed in blue; Source: compilation extracted from COFREPECHE et al, 201426.

3.4.2

Price at first sale

The estimated price at first sale could be presented using the following table in order to carry out prospective and retrospective assessments of FPA.

26

COFREPECHE, MRAG, NFDS and POSEIDON, 2014. Ex-post evaluation of the current Protocol to the Fisheries Partnership Agreement between the European Union and Madagascar. Framework contract MARE/2011/01 - Lot 3, Specific contract n° 10. Brussels, 175 p Page 6 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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Table 3.1: Estimation of first sale price Geographic area (or location)

Possible conversion of price at first sale Calculation

Source Operators

Method

Indicator Price at first sale

Consignees

Uncertainty level – conclusion*

Landed price Price of a) purchase of raw material or b) sale of the finished or partly finished product Sale price Import price (location)

Processing factories Public databases

*: e.g. Decision to use or not use the data to estimate the price at first sale. Source: own compilation.

3.4.3

Historical analysis of trade in quantity and/or price

The figures used should be readable in black and white versions and homogeneous in style. The figure below will then serve as a template. 80 000 70 000 60 000

en tonnes

50 000 40 000 30 000 20 000 10 000 0

Japon

Europe

Afrique

tous marchés confondus

Figure 3.2: Mauritian exports according to market destination from 1987 to 2011 (in tonnes) Japan, Europe, Africa and altogether; Source: SMCP, 2012; from COFREPECHE et al., 201327

27

COFREPECHE, NFDS, POSEIDON and MRAG, 2014. Ex-post evaluation of the current Protocol to the Fisheries Partnership Agreement between the European Union and Mauritania. Framework contract MARE/2011/01 - Lot 3, Specific contract n° 8. Brussels, 176 p. Page 7 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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Analysis of the operating costs of the different segments

Operating costs are analysed from a presentation and discussion of their nature and structure, including those related to the production cycle by characterising the dynamics of their origin and their change over time.

4.1

Collection of accounting and financial data

The data source (when available) is the accounting balance: summary of a period, drawn from the list of all accounts from the company’s books and containing all debit and credit amounts of these accounts and by difference all debit and credit balances. The expense account breakdown is based on the analysis of the accounting balance where each item is taken one after the other and its variability is identified. In the case of fishing companies a basic breakdown is possible and can be adapted for different “metiers”, to take into account specific items (i.e. the cost of the bait for longliners or the cost of ice for fresh fish trawlers).

4.2

Data processing

A breakdown of operating costs will be done on two levels: Fixed costs (or structural costs): remain constant regardless of the level of fishing activity.  Financial expenses, insurance, technical depreciation, repair maintenance (after compensation with potential insurance reimbursements), fishing equipment, radio equipment, taxes, payroll taxes and overheads on land. Variable costs: Increase or decrease proportionally to the volume of fishing activity. They can be divided into two sub-categories:  Operational (depending on the vessel's activity): fuels and lubricants, packaging and boxes, ice.  Proportional (based on the volume or value – turnover - of catch) unloading costs, port fees and taxes, remuneration of vessel crew. Simple breakdown: Operating costs: Expense items

Variable costs:

Fixed costs:

% of variability

Unit of variation

% fixed costs

Fuel

100 %

Number of litres used

50 %

Fishing gear

50 %

Number of days at sea

50 %

Maintenance and repair

50 %


50 %

Other external costs

50 %


Taxes

100 %

Turnover

Salaries

Crew share (CSTA x NTS)

Payroll taxes

100 %

The processed data will determine key indicators to analyse costs formation, and estimate the sensitivity of the profitability for the fleet segments studied.

4.3

Data analysis

The financial indicator commonly used to assess the profitability of a company is the “Breakeven point”: level of activity (turnover) from which the company is in equilibrium, or compensates its fixed costs. Calculating the breakeven point by the contribution margin method: Page 8 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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1) 2) 3) 4) 5) 6) 7) 8)

4.4


Determining the turnover Determining variable costs Calculation of the contribution margin (CM) Calculation of the contribution margin ratio (CMR) Determining fixed operating costs Determining fixed investment costs Calculation of all the fixed costs Calculation of the breakeven point (BP)

T VC CM = T - VC CMR = CM / T FOC FIC FC = FOC + FIC BP = FC / CMR

Definition of a dynamic economic model

From this process it will be possible to determine a dynamic economic model broken down by activity unit. Activity Unit (AU): allows the allocation of indirect expenses (not directly involved in the operation of the vessel – for example support vessel’s operating cost shared between tuna seiners, management and operating costs on land) according to general criteria (specific allocation keys) Activity Unit Cost (AUC): unit of measure of activity (i.e. days at sea, landed tonnage, fuel bunkering, etc.)


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Table 4.1: Example of dynamic modelling Activity unit

Fuel

Number of litres per phase* and day at sea

0.6


88

Other common costs

Crew remuneration

Variable costs

Fixed costs

Cost per activity unit (€ unless specified)

Crew share ** Net to share

Fishing gear


17



22

mechanical


9

hydraulic/electric


2

electronic


2

various


9

Taxes

1 € of turnover

0.062

Payroll taxes

“staff onboard”

6 529

Fishing gear

3 232


4 194

mechanical

1 677

hydraulic/electric

419

electronic

419

various

1 677

other external costs (k€)

6 227

* The Activity unit for fuel is the number of litres used by phase of the energy cycle (cruising or fishing) ** NTS: Net To Share. It is the turnover - joint costs Note: The table refers to a specific case (netters) study by the contractor. The concepts of Net To Share (NTS) for common costs and of Crew Share to Allocate (CSTA), relate to the wage formation typology and are not applicable to all segments.

Given sufficient and consistent data, modelling may be used to expand the simulation to a fleet or a fleet segment. Below is a list (not exhaustive) of potential variables generating a change in the economic model:    

Variation in the number of days at sea; Variation in cruising hours per day at sea; Variation in fishing hours per day at sea; Variation in average fuel prices; Page 10


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    


Volume effect No 1: constant yield, by varying the fishing effort (increase / decrease in the number / intensity of fishing gear used - nets, pots, trawls, etc.) to measure the impact in terms of number of days to achieve this yield; Volume effect No 2: measuring the impact of the increase / decrease in the number / intensity of fishing gear deployed the same number of days; Variation of onboard crew; Variation in crew and operators share; Increase of fixed costs.

The financial approach should be made as far as possible by fleet segment resulting from the previously mentioned typology. Depending on the availability and relevance of information, data from the Data Collection Framework Regulation (EC) No 199/2008 of the European Council of 25 February 2008, as well as annual economic reports from the STECF will be used for the analysis. Similarly, economic surveys conducted by national authorities of EU Member States28 will be used, collected through survey or accounting balance (data collection method). In case of unavailability of the above data, the data will be collected from owners affected by the segment(s) studied.

5

Analysis of the economic and financial results of the different segments

The objectives of this section include: Describe objectively the economic activity generated by all fleet segments defined above. This step focuses on the analysis of the operating cycle29.  Develop socio-economic indicators to compare the performance of the various segments.  Define the way in which financial and economic flows generated by the fishing activity between suppliers and customers of fisheries companies are distributed. Depending on whether a short (2-3 years) or long (greater time period) time series is considered, figures will be provided in current or constant Euro (EUR). Constant Euro will be used for long series avoiding distortions in the comparison by currency fluctuations and the current Euro will be used for shorter time series of 2 or 3 years due to the stability of the currency and thus the low rate of inflation. 

The analysis of economic performance requires three different components:  

The operating profit (OP) is the result of the comparison of the company's products (turnover) with its expenses (operating costs). It therefore depends on endogenous (specific management strategy of each company) and exogenous (sectoral context and economic environment) factors. The acquisition of a fishing vessel and of all the goods and services required to generate a fishing activity is the investment cost (K). It represents the entry cost to the business30 (investment) including,

28

Examples : Spain: http://www.magrama.gob.es/es/estadistica/temas/estadisticas-pesqueras/pesca-maritima/encuestaeconomica-pesca-maritima/ France: http://sih.ifremer.fr/Description-des-donnees/Les-donnees-collectees/Enquetes-economiques 29 In financial terms, the term operating cycle is used for the breakdown of expense items to work out the operating income after they are deducted from the turnover (the operating cycle is used for operations contributing to turnover) 30 In addition to the financial cost of the investment in production facilities (vessel) access to the resource is subject to authorisations, whether administrative or financial (real costs of fishing authorisations in third countries ...) Page 11 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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


in the case of fishing, taking into account other restrictions to entry (obtaining quota, fishing authorisations, etc.). Investment may be achieved through own or outside capital (banks or specific subsidies). This source of funding will generate a cost of raising capital. This is the financing cost (i).

Figure 5.1: Determinants of overall profitability of a fishing business For a business to be viable from an economic point of view, it must be able to make its production facilities profitable and also to renew them. The company should generate an operating profit at least equal to its financial commitments (K + i) to generate profit from its production facilities and generate sufficient reserves to finance their renewal.

5.1

Analysis of the operating cycle

This analysis examines all factors that describe the operating cycle of fishing companies. The analysis will be based on a long historic and representative time series (minimum 3 years), subject to the availability of information.  Technical data They include all administrative and technical characteristics of the vessel (length, power, gear type, year of construction, crew on board, community fishing license, fishing authorisations, etc.).  Activity data Activity data used to define the different operating modes of vessels, i.e. vessel operating intensity (number of days at sea), the energy cycle (fuel volume) and fishing effort depending on gear used (fishing time / cruising time and crew on board).  Operating Economic Data Operating economic data make it possible to define the operating margin (synonym: operating profit) from an analytical point of view, based on all fixed and variable costs described in the previous section. They make it possible to measure the wealth created in real terms by the operating structure (Value Added) and to assess the distribution of wealth between the crew onboard (remuneration) and the operator (operating profit). The indicators used to describe the operating cycle are summarised in the table below. They will be used as a normative accounting framework to compare segments and thereafter to estimate potential differences in fleet performance. Page 12 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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Table 5.1: Summary of operating economic data by business segment Average Technical data Average age of fleet Average vessel length Fleet capacity (Kw) Vessel tonnage (GT) Number of vessels Activity data Days at sea Fuel consumption (tonnes) Cruising/fishing time Number of crew employed Economic data Turnover per vessel Operating grants Total income Fuel price Fixed costs Other variable costs Maintenance and repair costs Value Added (a-(b+c+d+e)) Wage bill and payroll Operating profit (VA-f)

Source: own work

5.2

Performance indicators

Four indicators are used to assess the economic performance of each business segment identified:  The gross operating margin. This indicator measures the “income” of the company generated by its activities. The gross operating margin ratio is the gross operating margin (obtained by taking out employment costs and taxes from the value added) relative to the turnover of the business. This is an indicator of the ability of companies to invest and to meet their financial commitments.  The economic rate of return. The investment costs are the means used by the company to operate. Depending on the availability of data, the investment costs can be estimated by their historical cost or replacement value. The economic rate of return is the ratio of operating profit to capital costs of the business. This indicator compares the performance of different business segments and verifies the efficiency of the production process.  The short term solvency ratio. The prolonged lack of payment of financial expenses (or interest) may cause bankruptcy of a company at the demand of its creditors. To assess this risk, the short-term solvency ratio represents the company's ability to meet its financial commitments from its operations. It is calculated by dividing the operating profit by the repayment of borrowed capital and related interests. It is generally accepted that the precautionary ratio in the fisheries sector, is in excess of 1.5. In other words, when the company generates a surplus ratio of operating / repayment of borrowed capital of more than 1.5, it is considered in good financial Page 13 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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health. Conversely, when the ratio is below 1, the company must draw on its reserves from previous years to meet its financial commitments. This ratio is another key indicator to assess the ability of companies to invest in the renewal or change of its production facilities.  The overall debt ratio. This indicator measures the level of debt incurred by the company in relation to its assets. It is calculated by dividing the amount of debt (short-term and long term) to total assets held by the company. This indicator is complementary to the short-term solvency ratio and can demonstrate the company’s financial independence in relation to its creditors.

6

Analysis of direct and indirect value added and its components

To address the analysis of value added and its composition, it is important to consider the overall economic environment of each fleet segment. In order to understand all of the jobs and the chain of value added by these fishing activities, three branches of activity are taken into account:   

The industry of “operators” represented by the fishing companies, The “downstream” industry (adding value, including possible processing and distribution) consisting of the first buyers (auction or fish market), the processors and distributors, responsible for the sale of seafood and a direct link with the operators, The “upstream” industry brings together providers of port goods and services, commercial and non-commercial, essential for the proper operation of upstream and downstream activities.

Figure 6.1: Fishing industry schematic Source: Cellule MER, Nantes University (2004) Page 14 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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The operators industry covers businesses and services directly related to the management and supply of vessels to make them operational for fishing. This is the main industry because it ensures fishing activity and is the source of wealth creation. In their operating procedures, operators’ activities require the assistance of other port operators. The operator industry maintains relations with: 

The industry supplying goods and services (upstream industry); itself segmented into two categories: o On the one hand, providers of market goods and services consist of refuelling companies, maintenance and repair, management agencies, banks, insurance, etc. o On the other, non-commercial service providers that offer generally regulated services. They bring together private non-profit and public institutions (government agencies, producer organisations, fisheries committees, local authorities, etc.).



Downstream of the operator industry, port structures are in charge of marketing, processing of landed and processed / packaged products. These are the fish trading companies, wholesalers, processors, logistics and packaging.

These three industries are interdependent and linked by two flows: flows of goods and services in return for cash flows. Analysis of the operating accounts will breakdown these economic flows between actors of each industry. From the types of goods and services (industry suppliers of goods and services) and the types of target markets (“distribution” industry) assumptions regarding the geographical distribution will distinguishing: 

flows generated in the EU economic area



flows related to third-party economic areas including: o Flows to and from third countries, notably with which FPAs were agreed; o Flows to and from developing countries and mainly ACP countries; o Flows to and from other countries.

These assumptions will be specified with more or less detail depending on data quality and the detail of information obtained from operators, port authorities and factory owners. Thus, when the data are abundant and well researched, the presentation of flows is made in detail, quantitatively and geographically. This concerns both the flows of products and of inputs (intermediate consumption), including fuel, which can then be broken down by country of destination for the first and country of origin for the latter. When these conditions are not fully met, the analysis will still endeavour to provide the most important qualitative and quantitative elements with the finest possible level of detail, differentiating flows at least between Europe and the rest of the world. The method for estimating employment and value added presented below is based on that used in the context of the 1999 study of fisheries agreements for the services of the European Commission and the European Parliament, by the Ifremer-Cep-CEMARE team31 as well as in the 2008 report for the European Commission by the Oceanic-Megapesca team32.

31

Ifremer, CEMARE et CEP, 1999. Evaluation of European Fishing agreements with Third countries”, Full Report, European Commission, 370 p. 32 Oceanic Développement, MegaPesca Lda, 2008. ‘Evaluations, impact analyses and monitoring services in the context of FPAs: Establishment of a Framework Contract Management Unit (FCMU) to manage, monitor and coordinate the activities under the Framework contract and the relevant specific agreements, 56 p. Page 15 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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6.1


Estimates of jobs created

Three categories of jobs are taken into account in calculating the number of jobs related to the activity of a fleet segment: 

Direct jobs, directly associated with the activities of fishing vessels (operators industry),



Indirect employment, limited to those generated by the activities of suppliers (upstream industry), and,



To those generated by clients of the fishing companies (downstream industry).

For each job category, a distinction is made between those for workers from the European Union and those filled by nationals of other countries. For FPAs, a further distinction is made between employment of seafarers of the FPA country and those of other countries, including from the ACP group33. The tables following present the basis of the calculations of jobs used in FPA evaluations to date. The investigative work will test and refine this to the extent possible. 6.1.1

Direct jobs

The number of crew on board vessels of each fleet segment is obtained from surveys to be carried out primarily with operators34. It takes into account crew rotations if relevant. The following table shows, for example, the basis for calculating the actual number of jobs in the different segments. This table was used to present the evaluations conducted on the segment of tuna seiners and on two of the surface longliners segments as part of the retrospective and prospective FPA evaluation between the EU and Madagascar35 (the tables that follow served as a basis for those presented in the evaluation report and are examples of the type of results that can be expected). The number of sea going jobs is added to the number of land-based jobs in the operator’s industry (directly related to the production activity). Are thus taken into account, the fishing companies’ internal personnel jobs who manage fleets, refuelling and equipment maintenance, on the basis of a ratio of 15% of seagoing personnel36 (percentage to be checked with operators and updated accordingly). Table 6.1: Example of calculation for direct employment in the EU fleet Segment 1

Segment 2

Segment 3

Total

N1

N2

N3

Sum (N1-N3)

Average number of EU seafarer per vessel

mU1

mU2

mU3

Sum

Average number of non-EU seafarer per vessel

mA1

mA2

mA3

Sum

mAP1

mAP2

mAP3

Sum

Total EU jobs

EU1=N1 x mU1

EU2

EU3

Sum

Total non EU jobs

EA1=N1 x mA1

EA2

EA3

Sum

EAP1 = N1 x mAP1

EAP2

EAP3

Sum

TE1= EU1 + EA1

T2

T3

Sum

Number of vessels

Including FPA countries

Including seafarers from FPA country Total crew

33

The effects for the ACP countries, as the FPA protocols usually refer to crew and scientific observers of the ACP group of countries. 34 Other sources may possibly be used (see section 4.4 - Economic data processed by the STECF, economic surveys conducted by the national administrations of the Member States for example). 35 COFREPECHE, MRAG, NFDS and POSEIDON, 2014. Ex-post evaluation of the current Protocol to the Fisheries Partnership Agreement between the European Union and Madagascar. Framework contract MARE/2011/01 - Lot 3, Specific contract n° 10. Brussels, 175 p. 36 Ratio estimated by Océanic Développement in 2009. Page 16 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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EU management personnel (15 % of the crew)

GE1= EU1 X 1.15

G2

G3

Total direct jobs TED1= TE1 + GE1 TED2 TED3 *: taking into account crew rotations; source: Oceanic Développement et al. (2011) and operators.

Sum Sum

In the case of an FPA evaluation, job totals are broken down by fishing area (European waters, international waters and third country fishing zone) according to the proportion of the catch or the number of days spent. In light of the FPA evaluations conducted between 2012 and 2014, the location of catches per area is usually documented whereas the number of days in a fishing area of a third country, though generally known for demersal vessels, is seldom made public for vessels fishing for tuna or small pelagic species. It will then be necessary to make some assumptions about how catches are distributed according to the different geographical areas considered, especially after discussion with the operators. Table 6.2: Employment directly attributable to FPA Segment 1

Segment 2

Segment 3 Total

% of catches in the third country’s fishing area / total vessel catches

P1%

P2%

P3 %

Direct jobs linked to the FPA EU crew

EU1 X P1

EU2 X P2

EU3 X P3

Sum

Non-EU crew

EA1 X P1

EA2 X P2

EA 3 X P3

Sum

EAP1 X P1 GE1 X P1 TED1 X P1

EAP2 X P2

EAP3 X P3

Sum

GE2 X P2

GE3 X P3

Sum

TED 2 X P2

TED3 X P3

Sum

Including FPA crew Crew and fleet management personnel Total direct jobs

Observers on board, paid by the operators are also taken into account in the calculation of direct employment. Their numbers are obtained from operators, RFMOs and third countries in the fishing areas in which EU fleet segments operate. Numbers were adjusted for the FPA evaluation, according to the procedure, in proportion to the catch (regional observer) and time spent on board in the national fishing area (national observer). 6.1.2

Indirect upstream jobs

Jobs that are not internal to fishing companies but concern goods and services providers (repair, consignment, stevedoring, maintenance and more generally the provision of commercial and noncommercial goods and services) are considered indirect upstream jobs. This job category may be estimated in two ways: 

From the total number of jobs in this industry in the ports of call of vessels. The information is generally available from the port management, the chamber of commerce or the institution that manages the port. Having broken down the various upstream activities between ports and established for each of them, the number of vessels served or the quantities of goods and services provided, one can obtain a ratio “number of vessels in the segment studied / total number of vessels served” or “amount used by vessels of the segment studied / total quantity of goods and services provided”. This ratio is then used to estimate the number of jobs created upstream by multiplying it by the total number of jobs in each upstream port.



Based on the number of vessels and the number of indirect upstream jobs known to be attached to them using a ratio known by the operators. For example, for the tuna fleet, the number of jobs in ACP countries in the upstream sector is eight per vessel and in the EU Member States that number is 22.5 (ratios used so far, regardless of the refuelling port and services rendered during Page 17


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the tuna FPA evaluations from the estimate made by Oceanic Développement in 2008 and the observations made in the Atlantic and Indian Ocean tuna ports). The use of previous FPA evaluations and of studies regarding dependence of European regions on fisheries 37 should improve the precision of this ratio. 6.1.3

Indirect downstream jobs

Downstream indirect jobs are generated by the distribution industry through landing, transhipment, product processing and the direct marketing of fish for consumption. As before, the estimation begins by breaking down the catch by port of landing; in the case of transhipment, the final destination port is considered. The data on the quantities and categories of landed and transhipped fish is available to port authorities. The final destination of transhipped fish is not always known to port authorities but can generally be obtained from the port customs service. If this is not the case, it is possible, after identifying the operators of the vessels involved in the transhipment, to ask the operators directly. The next step is to determine the number of jobs that are directly related to the flows of fish on land. Here, two methods can be used on the same principle as above: 



Either from the estimated total number of jobs related to the activities of landing / fuelling, processing and direct sale. The data is usually available in major ports; it can be obtained from various companies operating in this sector when on site. The total number is then adjusted according to the rate of use of these services by fleet segment (i.e. considering the landings by the segment studied compared to the total amounts passing through the port of landing). Or from ratios that were previously developed under studies specific to FPAs or dependence to European regions with regards fishing. The ratios are then applied to the vessel, per tonne of fish landed and processed according to the sector concerned.

For example, for tuna FPAs, jobs generated in the downstream industry were estimated from estimates made in the landing ports and / or transhipment from the various companies involved downstream as follows:  

Approximately 1 job per 500 tonnes of fish landed. 1 job per 50 tonnes of tuna processed;

Wherever possible, the ratios must be refined, particularly by highlighting the differences between ports: it takes more labour in less automated ports but the cost of labour is also higher. The same must be done for the mode of processing in order to obtain a ratio by type of processing (canning, fresh / frozen packaging, etc.). In the case of an FPA evaluation, the volume of catches that enters the distribution industry must also be compared to the volume of catches in the fishing area of third countries to reflect the downstream effects of EU vessels’ fishing activity on the third country’s on-land economic sector.

6.2 6.2.1

Measure of the overall value added generated Overall value added

The calculation of the overall value added gives an estimation of the wealth created by EU vessels in the fishing area of the FPA country. Direct value added linked to vessel activity (operator industry) is estimated by the calculation of the operating profit (see above). The calculation of the indirect value added gives an 37

Last set of studies « Regional social and economic impacts of change in fisheries - dependent communities » 2011. See : http://ec.europa.eu/fisheries/documentation/studies/regional_social_economic_impacts/index_en.htm Page 18 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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indication of the wealth created both upstream (direct suppliers) and downstream (clients) according to the nomenclature defined above for employment. Overall value added represents the total wealth created, in the case of the FPA evaluations, it breaks down into total value added for the EU and total value added for the third country/countries. This creation of value added generally benefits both EU companies that own the vessels and third country companies that provide services to vessels and those that process fish.

Figure 6.2: Distribution of the total value added between Member States and third countries The estimate of the total value added is limited to the supply of goods and services necessary for the operation of the production unit (fishing vessel) for the upstream sector; and limited to landing / transhipment activities, processing and packaging and direct marketing of fish to local consumers for the downstream sector. The delivery of products after packaging / processing and wholesale or retail sales is not taken into account. 6.2.2

Direct value added

Direct value added is the difference between turnover (sales of fish products) and intermediate consumption (maintenance of the vessel, fishing equipment, food, ice, bait, fuel and lubricants, and various services) related to fishing activities. It represents the wealth created from the exploitation of fisheries resources by using a number of inputs (whether in the waters of a third country or international waters). Its calculation makes it possible to establish turnover and deduce intermediate consumption. It is obtained from the amount and composition of catches reported by vessels and first sale prices (see section on typology of product flows). Data on various intermediate consumptions are obtained from operators. The following table shows the calculation steps for a fleet segment that catches three different species.


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Table 6.3: Calculation of the direct value added for a fleet segment Species 1

Species 2

Species 3

Total

Catches

C1

C2

C3

Sum

Price at first sale

p1

p2

p3

Ca1 = C1 X p1

Ca2 = C2 X p2

Ca3 =C3 X p3

Turnover by species category Total turnover for the segment

Sum Ca1-3

T = Sum Ca1-3

Variable intermediate consumptions

CIV

- fuel and lubricants - bait - foodstuffs - ice and packaging equipment / storage Proportional intermediate consumptions

CIP

- unloading costs - auction and Producer Organisation contributions Core intermediate consumptions

CII

- fishing equipment - radio equipment - maintenance and repair - insurance Total intermediate consumptions

CIT = ICV + CIP + CII

Value Added

VA = T - CIT

As part of the FPA evaluation, calculation of the value added should reflect the percentage catches made in the fishing areas of third countries. The turnover is calculated only for those catches and intermediate consumptions are estimated, depending on the type of variable costs, proportionate or operational (see section 4.2) prorated to the fishing effort or volume of catches made in the fishing area compared to the vessel's total effort or catch volume. Structural costs, when they are part of intermediate consumptions, can be distributed as operating costs in proportion to the effort in the fishing area relative to the total effort. Thus, if 10% of catches are made in the fishing area of a third country, intermediate consumptions of the segment are multiplied by this percentage. This first step of the evaluation and direct value added analysis leads to the estimation of the dependence in terms of wealth generated by the activities of EU vessels vis-à-vis the third country's fishing area with which the EU has an agreement, which is subject of the evaluation. However, it doesn’t give any detail on how that wealth is used for payment of labour, capital and its renewal or natural capital (access to ecosystems and fisheries resources). It also does not give information regarding the geographic and economic areas that benefit from the wealth generated during a production cycle. The second step is to assess the share of the value added used to cover the followings costs, from the data available in the income statements (available or reconstituted):  

Taxes and duties directly related to the activity, including the various costs related to the rights of access and use (fishing authorisations and related expenses); Salaries and employment taxes; Page 20


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


Gross Operating Surplus (GOS).

It is then necessary to distribute the various items corresponding to the use of the direct value added between the different economic groups considered in the assessment. Thus, the costs of fishing authorisations generally go to the third States in whose waters the EU vessels’ fishing activities take place. If these costs cannot be obtained from the income statements or estimated from information provided by the operators, they can usually be estimated directly from the provisions of the various protocols that define the composition, calculation conditions and terms of payment of related expenses to fishing authorisations. Similarly, if the data cannot be directly obtained from the operators, the distribution of the item “salaries and benefits” may be approximated using a ratio between:   

the number of seafarers on board who are nationals of the third country with which the EU has signed the fisheries agreement that is under evaluation, potentially, the number of seamen and nationals of other third countries, particularly ACP countries and The number of seamen who are EU nationals.

These numbers being based on the total crew number. Finally, it can be considered that the Gross Operating Surplus of vessels flying the flag of European Union Member States benefits essentially or exclusively the European Union economic group. 6.2.3

Indirect value added

This section aims to identify and measure the impact of EU vessels activities on suppliers and customers from EU Member States, third countries and other countries involved in port services and initial fish processing. As the diagram above shows, indirect value added (IVA) results from workflow driven, for the upstream sector, by the provision of goods and services to fishing companies in the supply industry and for the downstream sector, by handling activities (landing / transhipment), processing and sales directly to consumers in the retail industry. The calculation of the total value added for EU and third countries should be seen as a way to account for the origin of the creation of value and its share between the EU and third countries. Until now in FPA evaluations, intermediate consumptions, which are a source of wealth creation in the countries where the EU vessels restock (by generating indirect value added upstream), were not taken into account in estimating the indirect economic effects generated by the FPA between the EU and third countries due to the lack of information regarding supply chains of EU vessels. In the Indian Ocean, for example, the ports of Victoria (Seychelles) and Port Louis (Mauritius) seem to provide fuel and other consumables to EU vessels while the port of Antsiranana seems overlooked because of high fuel prices. Investigative work with operators and port authorities must be undertaken for each regional evaluation and each retrospective and prospective evaluation for which this methodology note will be used, in order to gain quantitative knowledge of intermediate consumption in third countries. Similarly, investigative work must be carried out in supply countries to clarify the assumptions for the calculation of ratios such as for the value added / turnover average generated by companies in the upstream sector (including those providing fuel), bearing in mind that the share of their turnover linked to the supply of EU vessels corresponds to a category of intermediate consumptions for these vessels. Wherever possible, this ratio will be estimated by geographical area. The sources of information are of two kinds: 

Existing published information on the subject, especially in countries linked to fuelling and generally available to research centres or fisheries authorities; Page 21


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


Information from supply companies that can be contacted directly on site during field missions either by email or phone.

Table 6.4: Example of calculation of indirect value added upstream for the supply of fuel Country 1 Fuel consumption of vessels in a segment Supply percentage in each country Turnover of the upstream industry related to the sale of fuel Ratio value added / turnover Value added of the upstream industry related to the sale of fuel = indirect value added generated by fuel sales

Country 2

Country 3

Total

Sum

CI fuel (CIc) p1 % CAc1= CIc X p1 % R1

p2 % Cac2 = CIc X p2 % R2

p3 % CAc3 = CIc X p3 % R3

Cac1 X R1

Cac2 X R2

Cac3 X R3

The investigative work must be repeated for other intermediate consumption goods in order to obtain comprehensive detail of all indirect value added created in the supply countries. Regarding the calculation of indirect value added downstream, information on the quantities of fish landed is available either from the port authorities or from the operators. It is possible to develop a calculation system to estimate indirect value added downstream. The information to be collected is mostly the same as the information used to determine the “VA / Intermediate Consumption (CI) ratio related to the purchase of the raw material”, fish. Again the sources of information are the published literature and the use of direct questioning on site or remotely38. Table 6.5: Example of calculation of indirect value added downstream in the country of landing Processing Catches for a segment Percentage of catches for each sub-sector of the distribution industry Purchase price ex-vessel Intermediate consumption of each sub-sector related to the purchase of the raw materials (mp) Ratio VA/CImp VA of the downstream sector = Indirect value added of the distribution industry

Direct sale

Transhipment

Total

T (tonnes) p1 %

p2 %

p3 %

Px1 CImp1= T X p1 X Px1 R1 = VA1/CImp1

Px2 CImp2= T X p2 X Px2 R2 = VA2/CImp2

Px3 CImp3= T X p3 X Px3

CImp1 X R1

CImp2 X R2

Sum

R3 = VA3/CImp3 CImp3 X R3

It is possible to refine the specific ratio for processing by detailing it by category of processed products when the processors can provide this information.

38

All catches in the context of FPAs are not necessarily processed and / or marketed outside the EU (in mixed FPAs part of the production goes directly in the EU), the STECF economic report on the processing sector will be used, as well as the information available on the EUMOFA website on pricing throughout some sectors and other sources to inform VA / CI ratios for the downstream sector in the EU. Page 22 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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6.3


Indicators to present and analyse the results

We can therefore to present data to describe: 

The level and use of direct wealth generated by EU vessels activities in international waters and waters of third countries and between different economic and geographical areas;



The level and distribution of indirect wealth generated directly upstream and downstream of the fishing vessels of the EU external fleet.

This estimate of the overall value added and the manner in which it can be broken down may be analysed in terms of catch volumes, total turnover generated by the fishing activity of the various segments involved in the fisheries agreements evaluated, in terms of the cost of the fisheries agreement covered by the EU budget and the cost of access to fisheries resources supported by EU operators. This can also be done for employment. The ratios presented in the following two tables will help drive this analysis, which may be presented by fleet segment or globally. Table 6.6: Ratios for value added VA

/ Catches

/ EU Financial compensation

/ License fees EU operators

/ total EU Contribution

DVA

DVA/tonne/species

DVA/ EU Compensation

DVA/License fees EU operators

DVA/ EU Contribution

IVA

IVA/tonne/species

-

-

-

GVA*

GVA/tonne/species

GVA/ EU Compensation

GVA/License fees EU operators

GVA/ total EU Contribution

DVA

DVAEU/t/species

DVAEU/ EU Compensation

DVAEU/License fees EU operators

DVAEU/ total EU Contribution

IVA

IVAEU/t/species

-

-

-

GVA

GVAEU/t/species

GVAEU/ EU Compensation

GVAEU/License fees EU operators

GVAEU/t/species

DVA

DVATC/t/species

-

-

-

IVA

IVATC/t/species

-

-

-

GVA

GVATC/t/species

-

-

-

Geographical area

EU + Third countries

EU

Third countries

* Value added - Direct: DVA, Indirect: IVA, Gross: GVA; Gross Value added is profit before labour and capital is deducted

Table 6.7: Ratios linked to employment Geographical area EU + Third countries

EU

Third countries

Jobs

/ Catches

/ Total EU contribution

Direct

DJ/tonne/species

DJ/EU contribution

Indirect

IJ/tonne/species

-

Overall

OJ/tonne/species

OJ/Total EU contribution

Direct

DJEU/t/species

DJEU/Total EU contribution

Indirect

IJEU/t/species

-

Overall

OJEU/t/species

OJEU/t/species

Direct

DJTC/t/species

-

Indirect

IJTC/t/species

-

Overall

OJTC/t/species

-

DJ: Direct jobs; IJ: Indirect jobs; OJ: Overall jobs Page 23 Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

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December 2014, MUL166R01B

Annexes: Annex 1: Examples of European fleet segmentation

Taking into account the vessels technical characteristics, operating strategies, target species and associated species, in a first instance it is possible to separate several segments in the external EU fleet involved in FPAs based on expert knowledge from prior FPA evaluations and their protocol, without the use of tools and sometimes complex methods of data analysis. As follows: 

Demersal trawlers in the EU-Greenland FPA, with three distinct segments: o Northern prawn trawlers; o Trawlers targeting Greenland halibut and redfish on the Greenland continental shelf and upper continental slope with sometimes significant catches of cod; o Trawlers targeting cod on the Greenland continental shelf and upper slope, with large catches of redfish.



Trawlers targeting pelagic species in North Atlantic waters, with two segments: o Trawlers targeting surface pelagic species such as capelin or blue whiting; o Trawlers targeting deepwater pelagic species (Bathypelagic) such as redfish.



Demersal trawlers in the West African plateau: o Fish trawlers; o Shrimp trawlers; o Cephalopod trawlers.



Longline vessels targeting demersal fish in West Africa.



Trawlers targeting small pelagic fish off the coast of West Africa, with distinct segments: o One targeting mainly horse mackerel and mackerel over the continental shelf off Morocco or Mauritania; o The other combining sardinella and sardine gear and depending on the season or trade zones, horse mackerel and mackerel gear.



Tuna seiners targeting tropical tunas in the Atlantic, Indian and Pacific Oceans with two specific segments: o Vessels using Fish Aggregating Devices (FADs) for a majority share of the fishing effort; o Vessels with fishing effort on free schools predominantly.



Pole and line boats targeting tropical tunas.



Longliners targeting tropical tunas.



Longliners targeting swordfish and sharks.

Page I Consortium: COFREPECHE (chef de file) – MRAG – NFDS – POSEIDON Analyse économique de la flotte thonière de l'UE – Note méthodologique

DG MARE 2011/01/Lot 3 – CS09


The first analysis presented here of the EU external fleet fishing activities within FPAs and tuna RFMOs could be deepened, for example by carrying out data analyses on qualitative and quantitative variables describing the characteristics of fishing units and activities. It could be preferable to identify smaller more homogeneous groups of vessels by their characteristics and their operating strategies, particularly with regard to the fleet of vessels targeting small pelagic species or even those targeting demersal species, provided that the analysis includes variables describing the fishing activity outside of areas covered by the FPAs or tuna RFMOs in particular. However, a statistical approach would be time-consuming and expensive, mostly because of data collection constraints. Therefore, the basis of segmentation, expert knowledge or statistical analyses, will be argued case by case. In addition, regrouping segments of the typology will be considered if the economic differences are considered minimal a priori. This step will be important to match the number of fleet segments with available data and the details and complexity of economic analyses that can be undertaken. Thus, segmentation of the tuna fleet could ultimately be based on “expert knowledge”, given the small size of this part of the EU's external fleet and relatively regular monitoring through ex-post / ex ante FPA evaluations.

Page II Consortium: COFREPECHE (chef de file) – MRAG – NFDS – POSEIDON Analyse économique de la flotte thonière de l'UE – Note méthodologique

DG MARE 2011/01/Lot 3 – CS09


category

EU tuna fleet Filter 1 Vessel type/Gear and fishing technique

category

seiners

surface longliners

Pole and line

Filter 2 Target species tuna, tuna-like species, sharks

category

seiners/tuna

surface longliners /tuna-like species

demersal longliners /sharks

Pole and line/tuna



pole and line/tuna



pole and line/tuna


pole and line/tuna

Filter 3 strategy : free schools, FAD, mixed

category

seiners/tuna/mixed

seiners/tuna/FAD

Filter 4 method of payment: tonne or turnover category

seiners/tuna/mixed/ French

seiners/tuna/mixed/Spanish

seiners/tuna/FAD/Spanish

Filter 5 Operational costs : seiners - 100 m and + 100 m (a similar cut off point can be established for longliners of + and – de 100 GT)

segment

seiners/tuna/mixed/ French

seiners/tuna/mixed/ Spanish/- 100 m

seiners/tuna/mixed/ Spanish/+ 100 m

seiners/tuna/FAD/ Spanish/- 100 m

Figure 0.1: Example of segmentation for the European tuna fleet Source: own compilation

Page III Consortium: COFREPECHE (leader) – MRAG – NFDS – POSEIDON Economic analysis of the European Union tuna fleets – Methodology

seiners/tuna/FAD/ Spanish/+ 100 m
