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DCF ECONOMIC DATA CALL 2012

ON AQUACULTURE SECTOR

COVERAGE REPORT

JRC G.04 FISHREG Data Collection Team

Report EUR 25576 EN

European Commission

Joint Research Centre

Institute for the Protection and Security of the Citizen

Further information https://stecf.jrc.ec.europa.eu/home http://ipsc.jrc.ec.europa.eu/ http://www.jrc.ec.europa.eu/ http://fishreg.jrc.ec.europa.eu/

Contact: [email protected]

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JRC76295

EUR 25576 EN

ISBN 978-92-79-27200-4

ISSN 1831-9424

doi:10.2788/62529

Luxembourg: Publications Office of the European Union, 2012

© European Union, 2012

Reproduction is authorised provided the source is acknowledged

Printed in Italy

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TABLE OF CONTENTS SUMMARY ................................................................................................................... 4 1 INTRODUCTION / BACKGROUND ................................................................ 5 2 ECONOMIC DATA CALL CONTENTS ........................................................... 6 3 COVERAGE and DATA CHECKING PROCEDURES .................................... 9 3.1 Checks carried out during the uploading procedure (Syntactic checks) ......... 9 3.2 Checks carried out after the uploading procedure .......................................... 9 4 OVERALL EVALUATION .............................................................................. 11 4.1 Data submissions .......................................................................................... 12 4.2 Coverage ....................................................................................................... 16 4.3 Comparison with FAO data ........................................................................... 18 5 COUNTRY BY COUNTRY EVALUATION .................................................... 20 5.1 Belgium .......................................................................................................... 21 5.2 Bulgaria .......................................................................................................... 22 5.3 Cyprus ............................................................................................................ 24 5.4 Denmark ........................................................................................................ 26 5.5 Estonia ........................................................................................................... 30 5.6 Finland ........................................................................................................... 32 5.7 France ............................................................................................................ 35 5.8 Germany ........................................................................................................ 39 5.9 Greece ........................................................................................................... 41 5.10 Ireland ............................................................................................................ 42 5.11 Italy ................................................................................................................ 45 5.12 Latvia ............................................................................................................. 47 5.13 Lithuania ........................................................................................................ 48 5.14 Malta .............................................................................................................. 49 5.15 The Netherlands ............................................................................................ 51 5.16 Poland ............................................................................................................ 53 5.17 Portugal .......................................................................................................... 55 5.18 Romania ......................................................................................................... 58 5.19 Slovenia ......................................................................................................... 60 5.20 Spain .............................................................................................................. 63 5.21 Sweden .......................................................................................................... 66 5.22 United Kingdom ............................................................................................. 69

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SUMMARY

This Data Collection Framework (DCF) coverage report was prepared by the Joint Research Centre (JRC) as part of an Administrative Arrangement with DG MARE. The purpose of the document is to provide an overview of the timeliness and completeness of the Member States data submissions to JRC in response to the call for aquaculture data concerning 2008-2010 issued by DG MARE under the DCF (Council Regulation No 199/2008).

Additionally, the report provides some indication of data quality, summarising major quality issues detected by Expert Working Groups convened under the Scientific, Technical and Economic Committee for Fisheries (STECF). The report is part of the end user feedback provided to DG MARE to facilitate the evaluation of EU Member State compliance with obligations under the DCF.

The 2012 call for economic data on aquaculture sector was the second data call under the Data Collection Framework (DCF). JRC enhanced existing uploading procedures to improve the transmission of the data from Member States, and carried out a number of coverage and quality checking procedures on the data submitted before, during and after the STECF EWG 12-13 meeting. During EWG 12-13, national experts were requested to report on these data quality checks. The present document reports on the coverage and quality of the data submitted by the Member States during the 2012 call on aquaculture economic data. The main findings of this report are: A) In terms of compliance with the data call deadline, most Member States succeeded to upload data in time. Only the UK data submission totally failed to follow the deadline. The data was submitted in September. However, after the data validation checks performed by JRC and those done by STECF EWG most of the datasets were resubmitted. B) In terms of the completeness of the Member States data submissions, most countries submitted the majority of parameters requested under the call. Overall, coverage was at the same level in comparison to the results of the 2011 data call. France improved providing data on economic variables. On the other hand Greece did not submit any data opposite to 2011 call. In addition there are question marks as to whether some countries have submitted data on the entirety of their national marine aquaculture sector. All in all significant amounts of economic data was not provided making an evaluation of the overall economic performance of the EU aquaculture sector in 2008-2010 impossible. C) In terms of data quality, inevitably some ‘abnormal’ estimates for various parameters were detected by JRC or the experts. Also in many countries sum of variables provided by segment did not correspond to the national total. Some issues were rectified by the Member States while many issues remained outstanding whilst preparing the economic report on aquaculture sector.

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INTRODUCTION / BACKGROUND The purpose of this report is to evaluate Member States data submission related to the 2012 call for economic data on the EU Member States aquaculture industry. The data collected was used by the JRC and STECF to produce the report on Economic performance of the EU Aquaculture sector. The data was requested under the framework of the Data Collection Regulation; cf. Council regulation (European Commission (EC) No 199/2008 of 25th February 2008). All EU member States are required to collect and provide data on salt water aquaculture, while collection of data for fresh water aquaculture is not compulsory. The data call requested data for the years 2008-2010. For evaluation, three aspects of the Member States data submissions were considered in this report: 1) timeliness of the submissions (did they comply within the deadline), 2) completeness (coverage) of the data submitted (were all parameters provided for all segments and all years requested), and 3) data quality (based on STECF EWG 12-13 evaluation). Section two of this report presents the contents of the data call that was issued to the Member States. Section three presents the coverage and data procedures carried information relating to procedures undertaken by the JRC to evaluate the coverage and data checking procedures of the data submitted. Section four contains an overall evaluation of Member States data submission with the data call, while section five looks at the timeliness, coverage and quality of each Member States data submissions.

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1 ECONOMIC DATA CALL CONTENTS This was the second time aquaculture data was requested from Member states. Tables 2.1 and 2.2, outline all the DCF economic variables to be submitted for the years 2008–2010, along with their corresponding aggregation levels. Table 2.1 lists all the economic variables required under the DCF. These variables are requested at the national level and disaggregated at the segment level described in the regulation (see table 2.3). Statistical quality indicators are also requested for each variable at the national totals level. Table 2.2. describes the data requested relating to production. Both production value and volume are requested at the national totals and by segments. Also data on sampling strategy, achieved sample size and precision are requested. All the various definitions for variables, aggregation levels, sampling strategies and precision and accuracy measures can be found by navigating through the data collection website. https://datacollection.jrc.ec.europa.eu/home Separate Excel upload files were needed for transmitting the DCF datasets. Upload templates were made available to download from the samples folder on the data collection website. The data call was issued by DG MARE on the 21 May 2012. MS were requested to submit the data within 1 month of the call, making the submission deadline 21 June 2012. The official data call letter can be found at the following link: http://datacollection.jrc.ec.europa.eu/c/document_library/get_file?uuid=90f93dc7-0187-4bcf-8722-06723d947c4d&groupId=10213

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Table 2.3 Segmentation of the economic data

seg1_1 Salmon Hatcheries & nurseries seg1_2 Salmon on growing seg1_3 Salmon combined seg1_4 Salmon cages seg2_1 Trout Hatcheries & nurseries seg2_2 Trout on growing seg2_3 Trout combined seg2_4 Trout cages seg3_1 Sea bass & Sea bream Hatcheries & nurseriesseg3_2 Sea bass & Sea bream on growing seg3_3 Sea bass & Sea bream combined seg3_4 Sea bass & Sea bream cages seg4_1 Carp Hatcheries & nurseries seg4_2 Carp on growing seg4_3 Carp combined seg4_4 Carp cages seg5_1 Other freshwater fish Hatcheries & nurseries seg5_2 Other freshwater fish on growing seg5_3 Other freshwater fish combined seg5_4 Other freshwater fish cages seg6_1 Other marine fish Hatcheries & nurseriesseg6_2 Other marine fish on growing seg6_3 Other marine fish combined seg6_4 Other marine fish cages seg7_1 Mussel rafts seg7_2 Mussel Long line seg7_3 Mussel Bottom seg7_4 Mussel Other seg8_1 Oyster rafts seg8_2 Oyster Long line seg8_3 Oyster Bottom seg8_4 Oyster Other seg9_1 Clam rafts seg9_2 Clam Long lin seg9_3 Clam Bottom seg9_4 Clam Other seg10_1 Other shellfish rafts seg10_2 Other shellfish Long line seg10_3 Other shellfish Bottom seg10_4 Other shellfish Other

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2 COVERAGE AND DATA CHECKING PROCEDURES Data Collection Framework (DCF) requires data quality assurance by Member States, while the evaluation of the data quality is the responsibility of STECF. JRC undertakes a number of coverage and data checking procedures on the data submitted, some are carried out during the uploading procedure and some afterwards. Data checks returning any inconsistencies, abnormal or missing values in the data submissions are sent back to the Member State, who are requested to report on these data checks, re-submitting corrected data when necessary. The overall quality of the data submitted was subsequently considered during the Expert Working Group (STECF EWG 12-13). 2.1 Checks carried out during the uploading procedure (Syntactic checks) During the data uploading procedure a number of automatic syntactic checks are carried out on the data before it is accepted. Member States are required to use specific Excel templates when uploading the data. The templates can be accessed on the following link: http://datacollection.jrc.ec.europa.eu/web/dcf/dc/aquaculture The syntactic checks are carried out without any specific knowledge of what the data contains or its meaning. They inform JRC if the data is present or not and in the correct format. These checks automatically reject data that do not confirm to specific restrictions, such as ensuring textual data is validated against defined parameters lists e.g. Species types, FAO code, country code etc. In addition, numeric data are checked to make sure they contain numbers and not strings. In the event of errors, a message is sent to the person uploading the data Member States receive immediate feedback when attempting to upload their data submissions. This helps Member States to identify inconsistencies with their own data and to fix them without intervention from the data collection team. Intervention is generally only required on technical issues with the upload server, and more complex issues regarding the datasets. These basic Syntactic quality checks and immediate feedback have contributed significantly to the overall improvement of the quality of the data submitted. 2.2 Checks carried out after the uploading procedure Once the datasets are successfully uploaded by the Member States, JRC evaluates how well the data complies with the terms of the data call by checking the coverage and quality of the data. In case of abnormal or missing data the MS is contacted for clarification. For each Member State, checks are carried out to ensure that all the necessary data have been submitted, i.e. that data is provided for all variables by national totals and by production segments. In the case of any inconsistencies, the data check results are sent back to the MS for clarification. Results of these checks on the data submitted for the 2012 call on aquaculture data are summarised in section 4.

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JRC checked the uploaded data by comparing the national totals with the sum of all production segments submitted by MS. All indicators at national and segment levels were cross checked and MS were also asked to clarify any inconsistencies or missing data. Additional checks, such as trend analysis and time consistency of parameters over the period analysed, were performed and tables produced for each MS prior to the STECF EWG 12-13 meeting. Any irregular results, for example, a significant decrease in one or more parameters while all others remained stable, were highlighted and experts or MS representatives were requested to check and validate these data issues. JRC also carried out checks against other official data sources. A comparison was made between DCF data provided by MS and data contained in the FAO data base, which covers information on aquaculture production by Member State including inland and marine aquaculture production. Both data sets were compared to examine the coverage of data submitted, taking into account that DCF only requires data on marine aquaculture. Again, the EWG 12-13 were asked to comment on any data inconsistencies regarding coverage of the DCF data. A table overview of the two data sets is presented in section 4. The STECF EWG elaborations are provided in section 5.

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3 OVERALL EVALUATION The DCF requires data only on marine aquaculture; submission of data on inland freshwater aquaculture production is voluntary. Therefore, the EU landlocked countries (Austria, Czech Republic, Hungary, Luxemburg and Slovakia) are not part of the DCF. According to Eurostat, the aquaculture production in these MS was less than 3% of the total EU aquaculture production in 2010. Aquaculture production in Latvia and Lithuania is based on freshwater species that are not mandatory and, hence these MS do not carry out a data collection system for the aquaculture sector. Nonetheless, the production of these countries is negligible at the European level (less than 0.5% of the EU total production in 2010). All other Member States are obliged to provide data under DCF. However, Greece and Belgium did not provide any data on the call. While, Greece did not respond to the data call, Belgium sent a note saying that their survey had failed and were unable to estimate the economic parameters required. The remaining Member States provided data, with a varying degree of submission between Member States. The main shortfalls included:

• Non provision of detailed cost structure data (provision of basic data only) • Non provision of data by segment (provision by national totals only) • Underestimation of the national production

For some Member States - Germany, Poland and Slovenia – the data collection system only covers the mandatory marine aquaculture data. The production of freshwater aquaculture from these three MS accounted for 6% of the EU aquaculture production in 2010. The United Kingdom failed to provide detailed cost structure data. France provided a full set of economic variables for 2010 only. Poland and Romania provided data for 2009 and 2010. The Netherlands has a 2 year time lag on their data collection and so did not provide data for 2010. Some MS provided national level data but failed to provide the required data at the segment level. The reasons for this varied between MS and are mentioned in the national chapters. In some cases when data was provided by segment, the information was insufficient to calculate the economic performance of each segment. Italy provided production data that was consistent with data contained in the FAO database. However, production data by segment was not consistent with the data provided at the national level. Furthermore, economic data was provided for only part of the production. These inconsistencies were never clarified by MS. Finally, it should be noted that the DCF data provided by some Member States did not always match with data contained in other sources (Eurostat or FAO). As mentioned above, the DCF regulation does not require data on the whole aquaculture sector. Also, methodologies and sector definitions between these data sources may differ. These issues should be considered when relating to this comparison exercise.

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3.1 Data submissions Timely submission of data with respect to the data call deadline is necessary given the timescale for the production of the annual report. The data call was issued on 21 May 2012 and Member States were given one month to submit their data; deadline the 21 June 2012. The official data call was sent to the Permanent Representations of the MS at the date. JRC sent an early warning of the call to National Correspondents two weeks before the call was launched. JRC also sent the official call to all National Correspondents when it was launched. Table 3.1.1 shows the uploading activity by each Member State with respect to the data call deadline. It presents the first and the last data submission. A total of 16 MS uploaded data before the deadline, while two MS uploaded after the deadline: Italy on the 26 June and the UK on 19 September 2012. The remaining four (Belgium, Greece, Latvia, Lithuania) MS did not upload any data. JRC performed coverage and quality checks on the data submitted. Where issues were found, MS were contacted and asked to check and validate the data, and re-submit when necessary. Most MS corrected the data and resubmitted, some providing further explanations on the data issues. Other MS did not respond and the issues remained unresolved. During the STECF EWG 12-13 on Economic performance of the aquaculture sector some national experts found issues with the uploaded data that required rectifying. This led to further uploading activity during, as well as, after the meeting.

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Table 3.1.1 Member States uploading activity in response to the 2012 call for aquaculture economic data

Country name First upload date Last upload date

Belgium

Bulgaria 2012‐06‐18 2012‐08‐31

Cyprus 2012‐06‐21 2012‐10‐17

Denmark 2012‐06‐21 2012‐09‐07

Estonia 2012‐06‐21 2012‐08‐10

Finland 2012‐06‐18 2012‐09‐25

France 2012‐06‐21 2012‐06‐22

Germany 2012‐06‐20 2012‐08‐30

Greece

Ireland 2012‐06‐15 2012‐10‐17

Italy 2012‐06‐26 2012‐06‐26

Latvia

Lithuania

Malta 2012‐06‐21 2012‐06‐21

Netherlands 2012‐06‐19 2012‐10‐15

Poland 2012‐06‐19 2012‐09‐27

Portugal 2012‐06‐21 2012‐09‐27

Romania 2012‐06‐19 2012‐06‐19

Slovenia 2012‐06‐13 2012‐08‐31

Spain 2012‐06‐21 2012‐09‐26

Sweden 2012‐06‐18 2012‐08‐13

United Kingdom 2012‐09‐19 2012‐09‐20

The overall number of uploads, including successful and unsuccessful attempts, during and after the data call is presented in Figure 3.1. The first Member State to upload data was Slovenia on the 13 June. The majority of the uploading activity was performed during the last week of the data call. Uploading activity after the deadline was mainly driven by the data quality checks. The United Kingdom was the only MS that did not respect the deadline, starting the uploading procedure less than one week before the meeting. Italy informed that they would miss the deadline.

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deadline EWG 12‐13 start

0

10

20

30

40

50

60

70

80

13/06/20

1215

/06/20

1218

/06/20

1219

/06/20

1220

/06/20

1221

/06/20

1222

/06/20

1226

/06/20

1231

/07/20

1202

/08/20

1203

/08/20

1210

/08/20

1213

/08/20

1214

/08/20

1228

/08/20

1230

/08/20

1231

/08/20

1207

/09/20

1219

/09/20

1220

/09/20

1224

/09/20

1225

/09/20

1226

/09/20

1227

/09/20

1215

/10/20

1217

/10/20

12

Figure 3.1 The total number of uploads during and after the Data call for aquaculture data

Table 3.1.2 presents the uploading activity by Member State, indicating the number of templates uploaded during each attempt.

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Table 3.1.2 Uploading activity by Member State. Numbers indicate upload attempts, including unsuccessful attempts.

Count of status Colu

Country 13‐Jun

‐12

15‐Jun

‐12

18‐Jun

‐12

19‐Jun

‐12

20‐Jun

‐12

21‐Jun

‐12

22‐Jun

‐12

26‐Jun

‐12

31‐Jul‐12

2‐Au

g‐12

3‐Au

g‐12

10‐Aug

‐12

13‐Aug

‐12

14‐Aug

‐12

28‐Aug

‐12

30‐Aug

‐12

31‐Aug

‐12

7‐Sep‐12

19‐Sep

‐12

20‐Sep

‐12

24‐Se p

‐12

25‐Sep

‐12

26‐Sep

‐12

27‐Sep

‐12

15‐Oct‐12

17‐Oct‐12

upload attemptBulgaria 21 6 27Cyprus 21 6 27Denmark 6 3 9Estonia 6 6 12Finland 6 3 9France 17 3 20Germany 23 6 29Ireland 11 12 4 6 33Italy 7 7Malta 9 9Netherlands 32 15 47Poland 6 3 3 3 3 18Portugal 11 15 3 3 3 35Romania 11 11Slovenia 10 6 16Spain 6 12 18Sweden 20 9 3 32United Kingdom 21 3 24

deadline meeting EWG 12‐13

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Table 3.1.3 summarises the data uploading by country. Belgium, Greece, Latvia and Lithuania did not submit any datasets. Table 3.1.3 Member States uploading: templates successfully upload (green); templates not

uploaded (red)

Template nameAQUA_MA_2008

AQUA_MA_2009

AQUA_MA_2010

TURNOVER_SALES_2008

TURNOVER_SALES_2009

TURNOVER_SALES_2010

Belgium No No No No No NoBulgaria Yes Yes Yes Yes Yes YesCyprus Yes Yes Yes Yes Yes YesDenmark Yes Yes Yes Yes Yes YesEstonia Yes Yes Yes Yes Yes YesFinland Yes Yes Yes Yes Yes YesFrance Yes Yes Yes Yes Yes YesGermany Yes Yes Yes Yes Yes YesGreece No No No No No NoIreland Yes Yes Yes Yes Yes YesItaly Yes Yes Yes Yes Yes YesLatvia No No No No No NoLithuania No No No No No NoMalta Yes Yes Yes Yes Yes YesNetherlands Yes Yes Yes Yes Yes YesPoland Yes Yes Yes Yes Yes YesPortugal Yes Yes Yes Yes Yes YesRomania Yes Yes Yes No Yes YesSlovenia Yes Yes Yes Yes Yes YesSpain Yes Yes Yes Yes Yes YesSweden Yes Yes Yes Yes Yes YesUnited Kingdom Yes Yes Yes Yes Yes Yes 3.2 Coverage Table 3.2.1 shows the coverage of economic data provided by Member State, year and variable highlighting missing variables within each Member States’ data set (at the national level). Overall, 10 MS provided all the requested data at national level and for the time period analysed. Eight MS had at least one minor issue in their datasets. For some of these MS, the data issues were more problematic and limited the analysis of the sector. The remaining four MS did not provide any data. These issues are further discussed by Member State in section 5.

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Table 3.2.1: Summary of provided and missing data for all countries at the national level 2008-2010

Variables 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10 8 9 10

Income

Total income N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Other income N N N 0 0 0 Y Y Y Y Y 0 Y Y Y Y Y Y Y Y Y Y Y Y N N Y 0 0 0 N N N Y Y Y Y Y Y N N N N N N 0 Y Y Y Y N N Y Y 0 0 0 N Y 0 Y Y Y Y Y Y

Subsidies N N N 0 0 0 Y Y Y Y Y 0 0 0 0 Y Y Y Y Y Y Y Y Y N N Y 0 0 0 N N N 0 Y 0 Y Y Y N N N N N N Y Y 0 0 0 N N Y Y 0 0 0 N 0 0 0 0 Y 0 Y Y

Turnover N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Expenditure

Wages and salaries N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Imputed value of unpaid labour N N N Y Y Y 0 0 Y Y 0 0 Y Y Y Y Y Y 0 0 Y Y Y Y N N Y 0 N N N N N Y Y Y Y Y 0 N N N N N N 0 0 0 0 0 N N Y Y N Y Y N Y Y 0 0 Y Y Y Y

Energy costs N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Raw material costs: Livestock costs N N N Y Y Y Y Y Y 0 Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Raw material costs: Feed costs N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Repair and maintenance N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Other operational costs N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Capital Costs

Depreciation of capital N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Financial costs, net N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Extraordinary Costs

Extraordinary costs, net N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y 0 0 0 Y Y Y N N Y N N N N N N 0 0 Y Y Y Y N N N N N N Y Y Y Y Y N N 0 Y N Y Y N Y Y Y Y Y Y Y Y

Capital Value

Total value of assets N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Net Investments N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Debt N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Production

Raw material volume: Livestock N N N Y Y Y Y Y Y 0 0 Y Y Y Y N N N Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N N N Y 0 0 N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Raw material volume: Feed N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y Y Y Y Y N N Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y 0 0 N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Total sales volume N N N Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y Y Y Y Y Y Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Employment

Total employees N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Female employees N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 0 0 0 N N N Y Y Y Y Y Y N N N N N N Y Y Y 0 0 N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Male employees N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y Y Y Y N N N N N N Y Y Y 0 0 N N Y Y N Y Y N Y Y Y Y Y Y Y Y

FTE N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N Y Y Y 0 0 N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Female FTE N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y 0 0 0 N N N Y Y Y N N N N N N N N N Y Y Y 0 0 N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Male FTE N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N Y Y Y 0 0 N N Y Y N Y Y N Y Y Y Y Y Y Y Y

Structure

Number of enterprises N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N Y Y Y N Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Number of enterprises <=5 employees N N N Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N 0 0 0 N Y N N Y Y Y Y Y N Y Y Y Y Y Y Y Y

Number of enterprises 6‐10 employees N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y 0 Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N Y Y 0 N 0 N N 0 0 Y Y Y N Y Y Y 0 Y Y Y Y

Number of enterprises >10 employees N N N Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y 0 0 0 Y Y Y Y Y Y Y Y Y N N N Y Y Y N N N N N N N N N Y Y Y N 0 N N Y Y Y Y Y N Y Y 0 Y Y Y Y Y

IRLBEL BGR CYP DEU DNK ESP EST FIN FRA GBR GRC PRT ROU SVN SWEITA LTU LVA MLT NLD POL

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3.3 Comparison with FAO data FAO data was used to compare the coverage of DCF data provided and the total aquaculture production by Member States. Data contained in FAO data was preferred over EUROSTAT because FAO provided data for 2010. The results are presented in Table 4.3.1. It should be noted that definitions and target population behind the two datasets differ leading to logical differences. FAO aquaculture covers all aquaculture production, while DCF requires only marine production (freshwater aquaculture production is optional). Definitions of aquaculture production units also differ. In DCF, definition follows that of the Structural Business Statistics, where a firm is considered an aquaculture firm only if the main activity of that firm is aquaculture, leaving secondary aquaculture out of scope. Additionally, production is defined differently: under DCF, juvenile production is included but not in the FAO dataset. The table below was prepared using data on production volume. It should be noted that in some cases the economic data was provided only for a part of total production. Acknowledging these differences, the comparison gives a good overview of the coverage of the data provided in the DCF data call. In the individual Member State evaluations in section 5, an EWG 12-13 comment on the differences is provided when available.

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Table 3.3.1: Comparison between FAO and DCF production data 2008-2010

Marine2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010 2008 2009 2010

Austria 2087 2141 2167Belgium 126 576 539Bulgaria 595 807 698 4562 5916 7222 595 294 496 6651 4056 3252 9081 6555 3766 100% 36% 71% 146% 69% 45% 176% 98% 48%Cyprus 2810 3337 4045 77 78 71 3874 3275 4034 53 67 70 3928 3343 3976 138% 98% 100% 68% 86% 99% 136% 98% 97%Czech Republic 20395 20071 20420Denmark 12676 12774 13752 22661 21356 25755 1481 2534 1325 43122 42849 40425 44603 45383 41750 12% 20% 10% 190% 201% 157% 126% 133% 106%Estonia 813 654 573 334 422 488 334 421 488 41% 65% 85% 41% 64% 85%Finland 10712 10508 9269 2727 3119 2503 16485 14137 12879 16485 14137 12879 0% 0% 0% 605% 453% 515% 123% 104% 109%France 194773 192044 183330 43475 41956 41190 216466 222708 273385 40803 42691 39953 257269 265399 313339 111% 116% 149% 94% 102% 97% 108% 113% 140%Germany 7004 3700 4999 36973 35207 35695 6830 4040 4985 6830 4040 4985 98% 109% 100% 0% 0% 0% 16% 10% 12%Greece 110706 118654 110096 4362 3357 3390 0% 0% 0% 0% 0% 0% 0% 0% 0%Hungary 15687 14825 14245Ireland 44030 46253 45457 838 958 732 43240 45974 45264 1765 1436 1166 45005 47410 46430 98% 99% 100% 211% 150% 159% 100% 100% 101%Italy 109713 123086 114846 39290 39346 38640 25673 33749 32885 6138 2849 20478 157810 148056 153276 23% 27% 29% 16% 7% 53% 106% 91% 100%Latvia 584 517 549Lithuania 3008 3422 3191Malta 2702 2868 2916 6724 6331 5415 6724 6331 5415 249% 221% 186% 249% 221% 186%Netherlands 38241 47779 60455 8575 7862 6490 0 0 0 55347 46000 31355 0% 0% 0% 0% 0% 0% 118% 83% 47%Poland 36813 36503 30757 11 14 15 36813 36503 30757 36824 36517 30772 100% 100% 100% 100% 100% 100%Portugal 6696 3975 1803 656 2753 1386 6158 5690 5848 725 518 669 6883 6208 6518 92% 143% 324% 111% 19% 48% 94% 92% 204%Romania 12532 13131 8981 0 12 9 7281 12854 7293 12863 55% 143% 0% 56% 143%Slovakia 1071 823 687Slovenia 274 377 119 1041 930 659 295 380 125 295 380 125 108% 101% 105% 0% 0% 0% 22% 29% 16%Spain 226010 246745 233151 23705 19924 19202 0% 0% 0% 0% 0% 0% 0% 0% 0%Sweden 3579 4556 3665 4016 3984 6979 0 2128 1384 6315 8234 10338 6315 10362 11722 0% 47% 38% 157% 207% 148% 83% 121% 110%United Kingdom 168622 168449 188370 10565 10643 12721 295045 325444 341211 16436 18433 16204 179843 196603 201364 175% 193% 181% 156% 173% 127% 100% 110% 100%Totals 959536 1005982 997392 276245 269982 264324 606392 652573 716382 175640 179476 189533 833576 844437 881022 63% 65% 72% 64% 66% 72% 67% 66% 70%

DCF production (Volume of Sales)Marine areas Inland waters National totalsFreshwater

FAO data (production) Coverage (DCF (Sales)/FAO (production) %)Marine Freshwater Total country

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4 COUNTRY BY COUNTRY EVALUATION In this section, a more in-depth analysis of the data coverage and quality issues relating to each Member State is provided. All MS were analysed in terms of compliance with the time schedule (Table 4.1.1) of the data call and in terms of the variable list provided (Table 4.2.1). A traffic lights system was used in order to evaluate the coverage of the data submitted. Each indicator was marked as either:

• Green (Yes), showing that the indicator was provided by the Member State; • Yellow (0), showing cases, then the indicator was equal to zero. In this case

separation was done in order to detect strange values, as not all values might be equal to 0, e.g. subsidies could be equal to 0 if there are no direct subsidies for aquaculture in that MS, however in the case of raw material costs it is possible that the value is missing if the aquaculture sector is not represented only by shellfish farms. Another example of a missing value could be the imputed value of unpaid labour when a sector is represented by small enterprises, while in the case of enterprises with high levels of employment and production, the imputed value of unpaid labour may in fact be equal to zero;

• Red (No) – showing that no data was provided by the Member State.

Subsequent to the coverage evaluation performed by the JRC data collection team and national experts, several MS needed to re-upload data after the data call as well as during the STECF EWG 12-13 meeting. The first and last dates of uploading activity are presented as well as the total number of uploading attempts.

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4.1 Belgium 4.1.1 Delivery of data At the launch of the aquaculture data call, the JRC Data collection team was informed by the Belgium representative that the Belgium Institute for Agricultural and Fisheries Research surveyed 107 fish farmers. However, the return rate was very low, with a total of four companies responding to the questionnaire, of which two were complete and the other two were only partly filled and considered as “invalid”. Furthermore, none of the valid respondents dealt with marine species and in fact, marine aquaculture is rare in Belgium. In 2010, the only two mussel producers ceased their farming activities and only one oyster farmer was active in 2011. Therefore, as the response was so low, data were not provided for the data call due to confidentiality issues. Furthermore, there was incompatibility between the year of reporting and the firms accounting year. The accounting year for most firms is 1 April to 31 March, while for other firms it is from 1 June to 31 May of the year n+1. None of the survey respondents used the calendar year. Under DCF, the collection of fresh water species is not mandatory. FAO FishStat Plus classifies all Belgian aquaculture as freshwater; Eurostat data confirms that Belgian aquaculture is “inland”. ‘FPS Economy, SMEs, Self-Employed and Energy’ requested and obtained a derogation and did not collect economic data for aquaculture sector during the reported period. Belgium does not expect any major changes in the aquaculture sector during 2012 and 2013 and therefore requested derogation for 2012 and 2013. 4.1.2 Coverage Not applicable 4.1.3 Quality Not applicable

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4.2 Bulgaria 4.2.1 Delivery of data Bulgaria submitted all datasets within the deadline. After the initial JRC data checks, Bulgaria re-uploaded data correcting for technical errors that arose during the processing of files between the Bulgarian Department of Statistics and the data call xls format templates. The data were corrected and validated in due time prior to the STECF EWG 12-13 meeting.

Table 4.2.1Table 4.2.2: Summary of uploads for Bulgaria template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012 ‐06 ‐18 2012 ‐08 ‐31 6 6DCF_AQUA_MA_2009 2012 ‐06 ‐18 2012 ‐08 ‐31 6 0DCF_AQUA_MA_2010 2012 ‐06 ‐18 2012 ‐08 ‐31 2 6DCF_TURNOVER_SALES_2008 2012 ‐06 ‐18 2012 ‐08 ‐31 2 1DCF_TURNOVER_SALES_2009 2012 ‐06 ‐18 2012 ‐08 ‐31 2 0DCF_TURNOVER_SALES_2010 2012 ‐06 ‐18 2012 ‐08 ‐31 2 1

4.2.2 Coverage Bulgaria provided all the requested variables for the total national production (Table 4.2.3). There is no ‘other income’ or ‘direct subsidies’ in the aquaculture sector of this MS. Only a few variables (turnover, livestock costs (2008), livestock volume and total sales volume) were disaggregated at the segment level. The turnover and sales volume by specie were only partially reported by DCF segment.

Table 4.2.3: Coverage of data, provided by Bulgaria by variable

Variables 2008 2009 2010

Income Total income yes yes yes Other income 0 0 0 Subsidies 0 0 0 Turnover yes yes yes

Expenditure

Wages and salaries yes yes yes

Imputed value of unpaid labour yes yes yes

Energy costs yes yes yes

Raw material costs: Livestock costs yes yes yes

Raw material costs: Feed costs yes yes yes

Repair and maintenance yes yes yes

Other operational costs yes yes yes

Capital Costs

Depreciation of capital yes yes yes

Financial costs, net yes yes yes

Extraordinary Costs

Extraordinary costs, net yes yes yes

Capital Value

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Variables 2008 2009 2010

Total value of assets yes yes yes

Net Investments yes yes yes

Debt yes yes yes

Production

Raw material volume: Livestock yes yes yes

Raw material volume: Feed yes yes yes

Total sales volume yes yes yes

Employment

Total employees yes yes yes

Female employees yes yes yes

Male employees yes yes yes

FTE yes yes yes

Female FTE yes yes yes

Male FTE yes yes yes

Structure

Number of enterprises yes yes yes

Number of enterprises <=5 employees yes yes yes

Number of enterprises 6‐10 employees yes yes yes

Number of enterprises >10 employees yes yes yes

4.2.3 Quality The quality of the data was not evaluated during the expert working group due to lack of expertise.

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4.3 Cyprus 4.3.1 Delivery of data Cyprus provided all the requested variables on the deadline. Following the JRC data collection team’s quality checks and communication with national authorities, there were several data re-submissions. The last update took place on 17 October 2012 (Table 4.3.1).

Table 4.3.1: Summary of uploads for Cyprus template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐21 2012‐10‐17 7 3DCF_AQUA_MA_2009 2012‐06‐21 2012‐10‐17 7 1DCF_AQUA_MA_2010 2012‐06‐21 2012‐10‐17 2 3DCF_TURNOVER_SALES_2008 2012‐06‐21 2012‐10‐17 3 3DCF_TURNOVER_SALES_2009 2012‐06‐21 2012‐10‐17 2 1DCF_TURNOVER_SALES_2010 2012‐06‐21 2012‐10‐17 2 1

4.3.2 Coverage Cyprus provided all economic variables at the national level. However, due to a low number of firms only turnover and sales volume by specie were provided by segments.

Table 4.3.2: Coverage of data, provided by Cyprus by variable

Variables 2008 2009 2010

Income Total income yes yes yes Other income yes yes yes Subsidies yes yes yes Turnover yes yes yes

Expenditure


Imputed value of unpaid labour 0 0 yes






Capital Costs



Extraordinary Costs


Capital Value



Debt yes yes yes

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Variables 2008 2009 2010

Production




Employment




FTE yes yes yes



Structure






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4.4 Denmark

4.4.1 Delivery of data All datasets requested were uploaded to the database during the last day of the data call. Re-submissions occurred in order to upload employment for 2010 and extraordinary costs of 2008–2009. The last data upload took place on the 7 September 2012 (Table 4.4.1).

Table 4.4.1: Summary of uploads for Denmark template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐21 2012‐09‐07 2 0DCF_AQUA_MA_2009 2012‐06‐21 2012‐09‐07 2 0DCF_AQUA_MA_2010 2012‐06‐21 2012‐09‐07 2 0DCF_TURNOVER_SALES_2008 2012‐06‐21 2012‐06‐21 1 0DCF_TURNOVER_SALES_2009 2012‐06‐21 2012‐06‐21 1 0DCF_TURNOVER_SALES_2010 2012‐06‐21 2012‐06‐21 1 0

4.4.2 Coverage Data provided by Denmark covered all parameters including at the segment level. The difference between the national and segments totals was explained by unavailability of economic indicators for small segments falling under confidentiality rules. Denmark also provided all variables for fresh water aquaculture. The full list of data provided by variable by year is presented in Table 4.4.2. There are no direct subsidies in the Danish aquaculture sector.

Table 4.4.2: Coverage of data, provided by Denmark by variable

Variables 2008 2009 2010

Income Total income yes yes yes Other income yes yes yes Subsidies 0 0 0 Turnover yes yes yes

Expenditure








Capital Costs



Extraordinary Costs

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Variables 2008 2009 2010


Capital Value



Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure





4.4.3 Quality The accounting statistics for 2010 is based on a sample of 137 aquaculture farms, covering 53% of the total population and 77% of the total income of the population (257 farms). Furthermore, data on sales volume and value, purchase of livestock raw material of fish are available for all farms. The Danish Directorate of Fisheries has registered the total population of farms and enterprises engaged in aquaculture production in Denmark. It is mandatory for all aquaculture producers in Denmark to report their production in volume and value each year at the farm level. Additionally, species produced and the technique used in the production is reported. The data for The Danish Account Statistics for Aquaculture is collected by Statistics Denmark. The collection is based on the total population of farms provided by the Danish Directorate of Fisheries. The data is collected at the farm level to get the most homogenies segments in terms of species and technique, and can be aggregated to the enterprise level. The Danish Account Statistics for Aquaculture collects economic data for costs and earnings and balance sheets. Data is collected on a voluntary basis from the owner’s chartered accountant. The accountant’s task is to report the accounts of his aquaculture clients to Statistics Denmark in a special form where the account information is harmonised for statistical use. Statistics Denmark validates the data from each account in a specially designed data system for quality control. The Danish Commerce and

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Companies Agency (DCCA) also collects account data for enterprises, but not for single holders. For enterprises which are not reported by the chartered accountant, the accounts from DCCA are used. The extrapolation of the sample to the total population is done in two steps. In the first, all results from the collected accounts are entered into a database containing information on all existing aquaculture producers in Denmark. From the collected accounts, an average is calculated for all indicators in each segment. In the second step, an account for the remaining population is estimated based on the average calculated in the first step and the information collected by the Danish Directorate of Fisheries. The underlying assumptions for this calculation are that the production function for each farm is identical within each segment. When the production function is identical, the costs and earnings can be distributed from the sales volume and value in each account. Confidentiality To avoid confidentiality problems, segments should in general include more than 10 enterprises. In Denmark, both the production of sea cage farms and eel production in recirculation systems are quite significant in terms of value, and even though these two segments include less than 10 firms, they are surveyed. In order to present detailed data collected from these two segments, nearly all enterprises agreed to participate in the survey. Input of expertise was available on the segmentation at the enterprise level and homogeneity of the segments in terms of techniques and species. All segments provided by Statistics Denmark have a high degree of homogeneity both concerning the species and technique. The separation of species into segments is 100%, but if an enterprise produces more than one species, then it is allocated to the segment of the species that contributes the most to turnover. Some enterprises own more than one farm using different techniques. In Denmark these activities are split up because the farm is used as a data collection unit. When farms are subsequently aggregated into enterprises, the enterprise is allocated to the segment, where its turnover is highest. There are only a few examples of enterprises using more than one technique. Under the existing regulation, the farmer’s main focus is to optimise production based on the feed quota, whilst he has no incentive to reduce pollution discharged from the farm since there is no feedback between this, production and profit. A regulatory change to individual pollution rights on nitrogen can ensure that the most efficient farmers will be the ones who produce. This can potentially increase production and profit without increasing pollution. Furthermore, it would provide farmers with an incentive to reduce pollution in order to increase production and profitability, which could lead to further development and the adoption of new environmentally friendly production methods and technologies. It is important to identify the possible gains and losses of regulatory changes because if a regulation is not optimal, it can lead to welfare losses for the society and individual producers. Differences with other official data sources (Eurostat) There are some differences in the volume and value collected by the Danish Directorate of Fisheries and Statistics Denmark. In general, both volume and value

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are higher in the Aquaculture Account Statistics. The reason for this is that the value and volume in the Account Statistics are measured in enterprise sales, while the numbers from the Danish Directorate of Fisheries are measured as farm production. Secondly the data collected by Statistics Denmark are account data and the accounting year does not necessarily coincide with the calendar year.

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4.5 Estonia

4.5.1 Delivery of data All requested datasets under the DCF were submitted in due time during the last day of the data call. The data was resubmitted after the JRC Data collection team’s checks. Subsidies and other income data needed to be corrected. Last resubmission date was 10 August 2012.

Table 4.5.1: Summary of uploads for Estonia template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0DCF_AQUA_MA_2009 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0DCF_AQUA_MA_2010 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0DCF_TURNOVER_SALES_2008 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0DCF_TURNOVER_SALES_2009 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0DCF_TURNOVER_SALES_2010 2012 ‐06 ‐21 2012 ‐08 ‐10 2 0

4.5.2 Coverage Estonian data covered all parameters (by national totals and segments) for 2008–2010 except imputed value of unpaid labour for 2008-2009. Table 4.5.2 provides the full list of data by variable by year.

Table 4.5.2: Coverage of data, provided by Estonia by variable

Variables 2008 2009 2010


Expenditure








Capital Costs



Extraordinary Costs

Extraordinary costs, net 0 0 0

Capital Value


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Variables 2008 2009 2010


Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure



Number of enterprises 6‐10 employees yes yes 0

Number of enterprises >10 employees 0 0 0

4.5.3 Quality Considering the reduced number of commercial fish farming firms, it was deemed reasonable to collect data only for rainbow trout as the value of production for other species was too small to justify a sampling survey. There was also a threat to confidentiality. That is one reason why DCF and FAO data may be different. The data were collected through questionnaires by the Estonian Marine Institute and compared with data in the financial statements.

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4.6 Finland

4.6.1 Delivery of data All Finnish data sheets were uploaded before the data call deadline. Following the data checking procedure, production data was changed and resubmitted during the STECF EWG 12-13 meeting (Table 4.6.1).

Table 4.6.1: Summary of uploads for Finland template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012 ‐06 ‐18 2012 ‐06 ‐18 1 0DCF_AQUA_MA_2009 2012 ‐06 ‐18 2012 ‐06 ‐18 1 0DCF_AQUA_MA_2010 2012 ‐06 ‐18 2012 ‐06 ‐18 1 0DCF_TURNOVER_SALES_2008 2012 ‐06 ‐18 2012 ‐09 ‐25 2 0DCF_TURNOVER_SALES_2009 2012 ‐06 ‐18 2012 ‐09 ‐25 2 0DCF_TURNOVER_SALES_2010 2012 ‐06 ‐18 2012 ‐09 ‐25 2 0

4.6.2 Coverage All variables required by DCF were provided by at the national and segment levels, including fresh water and salt water species, for 2008–2010. The only variable not disaggregated at segment level was Net investment for 2008. Table 4.6.2 presents the full list of data provided by variable and year.

Table 4.6.2: Coverage of data, provided by Finland by variable

Variables 2008 2009 2010


Expenditure








Capital Costs



Extraordinary Costs


Capital Value



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Variables 2008 2009 2010

Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure





4.6.3 Quality Economic data collection of the aquaculture sector in Finland combines information from different data sources. Main sources include: production survey, Structural Business Statistics of Statistic Finland (SF) and account survey conducted by FGFRI. Financial statements were available for all firms in Business Register having aquaculture as main activity. The register gives full coverage in number of firms. Primary sources of financial statements data in Statistics Finland are direct inquiries and business taxation material supplemented by Business Register data. Data is based on corporate balance sheet and profit and loss account data. Statistics Finland checks for the validity of the data. Any missing data was estimated with stratum. Account data was surveyed by FGFRI by stratified survey to detect the detailed cost structure of fish farms. Cost and earnings were done by design-based and model-assisted regression and ratio estimation. The cost variables were estimated with ratio estimation from financial statements. Production survey was collected exhaustively from the producers. Any missing information was estimated by stratum. Annual income and production variations per segments are influenced by production changes, but also because of company movements between segments and coding variation accordingly. This is the case especially between the segments of cages and combined methods. Difference between FAO data and DCF data exist because the aquaculture production data for Finland in FAO includes only fish production and does not take into account juvenile or fry production. In addition the production volume in FAO includes all aquaculture food fish production in Finland and not only firms with aquaculture as their main activity. On the other hand, the aquaculture production

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data under DCF not only includes fish production but also juvenile and fry production. Furthermore, it includes only firms having aquaculture as their main activity.

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4.7 France

4.7.1 Delivery of data France uploaded all the requested datasets on the deadline. However, there were errors in the uploading of production and economic templates, but these were successfully resubmitted the following day.

Table 4.7.1: Summary of uploads for France template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐21 2012‐06‐22 5 2DCF_AQUA_MA_2009 2012‐06‐21 2012‐06‐22 5 2DCF_AQUA_MA_2010 2012‐06‐22 2012‐06‐22 1 0DCF_TURNOVER_SALES_2008 2012‐06‐21 2012‐06‐21 3 2DCF_TURNOVER_SALES_2009 2012‐06‐21 2012‐06‐21 3 2DCF_TURNOVER_SALES_2010 2012‐06‐21 2012‐06‐21 1 2

4.7.2 Coverage Production data was provided by species and at the segment level. However, most of the economic variables for 2008-2009 were missing. According to the information provided by the DCF National Correspondent for France, economic data could not be collected for 2008 and 2009 as no such operation was set up in France. France required to first find partners and define methods and a segmentation/stratification strategy. The first results obtained are for 2010 ( Table 4.7.2 gives a full list of data provided by variable by year). As explained by French national correspondent, there are some marine fish segments with statistical confidentiality issues, either because there are too few enterprises or one enterprise is too predominant. In this context, the statistical survey could not publish data for the following segments: salmon cages (seg1.4), sea bass & sea bream on growing (seg3.2), turbot/on growing and combined. Due to the reduced number of enterprises, France did not devise a sampling plan for economic data. The production in volume and value for these segments have been merged with the segment ‘Other marine fish on growing’ (seg6.2) and species production declared under the MZZ code. For shellfish farming, France has enterprises which show a "mixed species production", i.e. they produce oysters, mussels and often other shellfish but none of these species can be seen as predominant in terms of turnover. Their production in volume and value were reported in the data call as "other shellfish" (even if there is some quantity of oyster or mussel) in different segments according to the farming technique. Some segments relate to techniques used in the Mediterranean region. For the first year, France was able to implement sampling for economic indicators with partners but had difficulties in collecting financial account data in the Mediterranean region. Some of these segments had very few enterprises in the sample and were not well representative of the total population. Hence, France did not report economic indicators for the following segments as the results may not be reliable: Mussel rafts (seg7.1), Mussel long line (seg7.2), other shellfish rafts (seg10.1), other shellfish long line (seg10.2).

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For statistical confidentiality reasons, the oyster long line (seg8.2) segment, which includes too few enterprises, was merged with oyster rafts (seg8.1).

Table 4.7.2: Coverage of data, provided by France by variable

Variables 2008 2009 2010

Income Total income no no yes Other income no no yes Subsidies no no yes Turnover yes yes yes

Expenditure

Wages and salaries no no yes

Imputed value of unpaid labour no no yes

Energy costs no no yes

Raw material costs: Livestock costs no no yes

Raw material costs: Feed costs no no yes

Repair and maintenance no no yes

Other operational costs no no yes

Capital Costs

Depreciation of capital no no yes

Financial costs, net no no yes

Extraordinary Costs

Extraordinary costs, net no no yes

Capital Value

Total value of assets no no yes

Net Investments no no yes

Debt no no yes

Production

Raw material volume: Livestock no no yes

Raw material volume: Feed no no yes


Employment




FTE yes yes yes



Structure





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4.7.3 Quality In 2010 DPMA with LEMNA, an economy laboratory from Nantes University, set up a working group with 2 subgroups: shellfish and fish farming. Each subgroup clarified how production data should be used to determine membership of each enterprise to a particular DCF segment, as no precise recommendation was found in the DCF regulation, in particular for species of shellfish. To improve the accuracy of sampling, the subgroup also defined the stratification to be applied in each segment and characterised in more detail the content of each economic indicator. For shellfish farming, the subgroup involves two enterprise account management centres that transmit economic data, on an anonymous basis, from accounting records of enterprises that they cover. In addition to the standard accounting records, these centres also collect information in order to determine the membership of a segment and stratum. For shellfish farming, data was collected from a sample of enterprises selected from files on accounting and financial data kept by chartered accountant or financial management centres specialised in these economic sectors. The planned sample rate is from 15 to 20%. The socioeconomic data of 274 enterprises in the shellfish farms segments (specialised in production of oysters and/or mussels) represent 9,3% of the population. Apart from production and employment, economic data could not be transmitted for the following segments: mussels and other shellfish on raft or long line. Enterprise in these segments are located on the Mediterranean coast where the enterprise account management centres have just started to collect the additional data needed for economic collection. Samples were reduced in number and were not representative of the population. Economic data on 267 samples were used for a population of 2795 enterprises.

Table 4.7.3: Sampling rate and quality of Total income for shellfish farming Segment No Population No

Samples Total income (€] Contri‐

bution Sampling rate Coeff. Var.

estimator

Mussel bottom 347 42 136 553 264 18,3% 0,121 0,075

Oyster raft 258 3 14 743 287 2,0% 0,012 0,351

Oyster bottom 1 934 206 450 824 985 60,4% 0,107 0,101

Oyster other 26 3 10 491 265 1,4% 0,115 0,255

Other shellfish bottom 230 13 133 430 868 17,9% 0,057 0,116

Total 2 795 267 746 043 669 100,0% 0,096 0,066

The three most important segments contribute to 97% of the total income of this sector. With a sampling rate of 11-12%, the data quality (coefficient of variation) is under an acceptable value of 12%. The next data collection will try to increase the sampling rate of the segments that were not transmitted or had a low quality. Concerning the fish farm segments (production of trout, seabass, etc.) socioeconomic data for 53 enterprises were collected in 2011 through direct questioning of producers with the help of the CIPA. Data validity checks lead to retaining only 44 samples, including four relative to caviar production and one

EN 38 EN

enterprise that had to be merged with "other marine fish" due to statistical confidentiality. The small number of saltwater fish farming, their specialised characteristics, and their large size will presumably allow for a higher sample rate, at around 50%.

Table 4.7.4: Sampling rate and quality on Total income for fish farming Segment No

Population NoSamples

Total income (€] Contri‐bution

Sampling rate Coeff. Var. estimator

Trout on growing 248 19 108 540 871 68,9% 0,077 0,310

Trout combined 85 12 18 245 552 11,6% 0,141 0,196

Sea bass & bream hatcheries 5 4 15 050 598 9,6% 0,800 0,200

Sea bass & bream cages 20 4 15 626 628 9,9% 0,200 0,458

Total 358 39 157 463 649 100,0% 0,109 0,221

EN 39 EN

4.8 Germany 4.8.1 Delivery of data All requested data sets were uploaded before the data call deadline. Following checks by JRC, a number of datasets were resubmitted before the STECF EWG 12-13 meeting (Table 4.8.1).

Table 4.8.1: Summary of uploads for Germany template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐20 2012‐08‐30 5 1DCF_AQUA_MA_2009 2012‐06‐20 2012‐08‐30 4 1DCF_AQUA_MA_2010 2012‐06‐20 2012‐08‐30 2 2DCF_TURNOVER_SALES_2008 2012‐06‐20 2012‐08‐30 3 5DCF_TURNOVER_SALES_2009 2012‐06‐20 2012‐08‐30 3 0DCF_TURNOVER_SALES_2010 2012‐06‐20 2012‐08‐30 2 1

4.8.2 Coverage Germany provided the full set of data required under DCF. However, provided data covered only marine aquaculture. Due to confidentiality, no data was provided for oyster production. The data was provided only for blue mussel segment and therefore represents the German marine aquaculture. Table 4.8.2 provides the full list of the DCF data submitted by variable by year.

Table 4.8.2: Coverage of data, provided by Germany by variable

Variables 2008 2009 2010


Expenditure








Capital Costs



Extraordinary Costs


Capital Value



EN 40 EN

Variables 2008 2009 2010

Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure





4.8.3 Quality Landing volume and value is obtained from landing declarations and therefore are reliable. Cost data was obtained from a random sample survey, with around one half to two third of the owner responding to the questionnaire for the different years. Results are compared and checked for plausibility with a detailed investigation of costs conducted in 2006.

EN 41 EN

4.9 Greece

4.9.1 Delivery of data No data submitted by Greece for the current data call. 4.9.2 Coverage No data provided. 4.9.3 Quality No data provided.

EN 42 EN

4.10 Ireland

4.10.1 Delivery of data Ireland submitted all the requested datasets in time to meet the deadline. Following JRC quality checking procedures and dialogue with the Irish authorities some datasets were adjusted and re-submitted before and after the meeting. The last resubmission date was 17 October (Table 4.10.1).

Table 4.10.1: Summary of uploads for Ireland template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐15 2012‐10‐17 8 6DCF_AQUA_MA_2009 2012‐06‐15 2012‐10‐17 8 6DCF_AQUA_MA_2010 2012‐06‐15 2012‐10‐17 5 1DCF_TURNOVER_SALES_2008 2012‐07‐31 2012‐07‐31 1 1DCF_TURNOVER_SALES_2009 2012‐07‐31 2012‐07‐31 1 1DCF_TURNOVER_SALES_2010 2012‐06‐15 2012‐07‐31 2 1

4.10.2 Coverage The data covered all parameters required under DCF and was submitted at the segment level. Ireland also provided economic information on freshwater aquaculture segments. Table 4.10.2 presents the full list of data provided by variable and year.

Table 4.10.2: Coverage of data, provided by Ireland by variable

Variables 2008 2009 2010 Income

Total income yes yes yes Other income yes yes yes Subsidies 0 yes 0 Turnover yes yes yes

Expenditure








Capital Costs



Extraordinary Costs

Extraordinary costs, net 0 0 yes

Capital Value

EN 43 EN

Variables 2008 2009 2010



Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure





4.10.3 Quality Variables surveyed by census; production and employment data, are based or derived from an 80% return rate or more by entity number of the total population of aquaculture practitioners for the period 2008 to 2010. As the proportion of entities not returning tends to be small producers, the proportion of national tonnage and turnover required to be estimated is therefore smaller again. The 80 % return rate from producers has been consistent as has the method of estimating the production of non-returnees; either using estimates from the local aquaculture officer or the most recent data of the company held. Operating costs variables have been more difficult to get consistent and reliable data for as these can only be obtained from the producers themselves or from their accountant. The majority of companies are small with just one to two full time staff, including the directors and therefore accountant hire is kept to a minimum. Such companies are only obliged by law to submit abridged accounts to the Company Registration Office, from whose website and others, abridged accounts can be accessed. Variables concerned with assets, liabilities and depreciation that previously were not available for the first data call, are becoming so and are being fed into the templates. The data for these variables is improving. Currently the percentage return rate for the frame population (commercial entities) of the sample survey for 2010 varies from 15.7% to 19.3%. For 2008 'feed costs' and 'Feed volume' variables are still based on very low returns (6-9%), though FCRs based on reliable production tonnage estimates, could be used. Otherwise the return rate for 2008 sample survey ranges from 10-11% while 2009 sample survey variables range from 11 to 15 % of the frame population. The sample survey targeted 20% of the frame population for the three year period.

EN 44 EN

Segment data as far as possible is homogenous and representative. One exception at present is the available data for 'Mussel Bottom (Seg. 7.3)' for 2010. The 'financial' variables of this segment covered by sample survey, may be skewed towards a particular region of national production and this will be updated if more representative data can be found for the segment variables concerned.

EN 45 EN

4.11 Italy

4.11.1 Delivery of data Italy submitted the requested datasets after the deadline on 26 June (Table 4.11.1).

Table 4.11.1: Summary of uploads for Italy template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐26 2012‐06‐26 1 1DCF_AQUA_MA_2009 2012‐06‐26 2012‐06‐26 1 1DCF_AQUA_MA_2010 2012‐06‐26 2012‐06‐26 1 1DCF_TURNOVER_SALES_2008 2012‐06‐26 2012‐06‐26 1 1DCF_TURNOVER_SALES_2009 2012‐06‐26 2012‐06‐26 1 1DCF_TURNOVER_SALES_2010 2012‐06‐26 2012‐06‐26 1 1

4.11.2 Coverage The data covered most of the parameters and was provided by segments: employment in full time equivalent and number of enterprises were missing (see also Table 3.3.1 coverage by segments groups). However, turnover and volume of sales were different in the economic data and the production data sheets, where the segment total also did not equate to the national total. The production volume provided with economic data only covered 24% of the national total. Explanation for this discrepancy was inquired from MS but no clarification was provided. For DCF data, the following parameters were not submitted:

• Employment in FTE • Employment in Male FTE • Employment in Female FTE • Number of enterprises by size category

Table 4.11.2: Coverage of data, provided by Italy by variable

Variables 2008 2009 2010 Income

Total income yes yes yes Other income yes yes yes Subsidies yes yes yes Turnover yes yes yes

Expenditure


Imputed value of unpaid labour yes yes 0






Capital Costs


EN 46 EN

Variables 2008 2009 2010


Extraordinary Costs


Capital Value



Debt yes yes yes

Production




Employment




FTE no no no

Female FTE no no no

Male FTE no no no

Structure

Number of enterprises no no no

Number of enterprises <=5 employees no no no

Number of enterprises 6‐10 employees no no no

Number of enterprises >10 employees no no no

4.11.3 Quality There was no evaluation carried out in the expert working group for the Italian data.

EN 47 EN

4.12 Latvia

4.12.1 Delivery of data All aquaculture production in Latvia is freshwater. As the collection of freshwater aquaculture data is not compulsory under the DCF, Latvia provided no data. 4.12.2 Coverage Not applicable 4.12.3 Quality Not applicable

EN 48 EN

4.13 Lithuania 4.13.1 Delivery of data At the time of the data call launch, the Lithuanian national correspondent informed the JRC Data collection team that all aquaculture production in Lithuania is represented by freshwater species. As the collection of freshwater aquaculture data is not compulsory under the DCF, Lithuania did not foresee the collection of this type of data in the National Programme for Fisheries Data Collection. 4.13.2 Coverage Not applicable 4.13.3 Quality Not applicable

EN 49 EN

4.14 Malta

4.14.1 Delivery of data All datasets were uploaded in time during the last day of the data call. There were no subsequent changes (Table 4.14.1).

Table 4.14.1: Summary of uploads for Malta template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐21 2012‐06‐21 2 0DCF_AQUA_MA_2009 2012‐06‐21 2012‐06‐21 2 0DCF_AQUA_MA_2010 2012‐06‐21 2012‐06‐21 2 0DCF_TURNOVER_SALES_2008 2012‐06‐21 2012‐06‐21 1 0DCF_TURNOVER_SALES_2009 2012‐06‐21 2012‐06‐21 1 0DCF_TURNOVER_SALES_2010 2012‐06‐21 2012‐06‐21 1 0

4.14.2 Coverage Data covered all the parameters required and were provided by segments. Values for raw material volume: livestock were not available for the years 2008 and 2009 for segment 3.4. Zero values should not be interpreted as missing values in the case of Malta, as they relate to factual collected data.

Table 4.14.2 provides a full list of data submitted by variable and year.

Table 4.14.2: Coverage of data, provided by Malta by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income 0 yes yes Subsidies yes yes 0 Turnover yes yes yes

Expenditure


Imputed value of unpaid labour 0 0 0






Capital Costs



Extraordinary Costs


Capital Value

EN 50 EN

Variables 2008 2009 2010



Debt yes yes yes

Production

Raw material volume: Livestock no no yes



Employment




FTE yes yes yes



Structure


Number of enterprises <=5 employees 0 0 0

Number of enterprises 6‐10 employees yes yes 0


4.14.3 Quality No expert evaluation was carried out during the expert working group for the Maltese data.

EN 51 EN

4.15 The Netherlands

4.15.1 Delivery of data The Netherlands data was submitted on time. However, due to errors and following the JRC data checks, turnover and sales volume by species was resubmitted. The last update took place on 15 October (Table 4.15.1).

Table 4.15.1: Summary of uploads for the Nederlandtemplate name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐19 2012‐06‐19 9 3DCF_AQUA_MA_2009 2012‐06‐19 2012‐06‐19 9 3DCF_AQUA_MA_2010 2012‐06‐19 2012‐06‐19 1 3DCF_TURNOVER_SALES_2008 2012‐06‐19 2012‐10‐15 9 4DCF_TURNOVER_SALES_2009 2012‐06‐19 2012‐10‐15 7 2DCF_TURNOVER_SALES_2010 2012‐06‐19 2012‐10‐15 2 1

4.15.2 Coverage The Netherlands has a two year data collection lag, i.e. data for 2010 had not yet been collected. The 2010 data templates were uploaded with no data. For DCF data, the following parameters were not submitted:

• Number of enterprises (2008) • Number of employees by gender; • FTE;

Imputed value of unpaid labour and raw material volume was provided as zero values.

Table 4.15.2: Coverage of data, provided by the Nederland by variable Variables 2008 2009 2010 Income

Total income yes yes no Other income yes yes no Subsidies 0 0 no Turnover yes yes no

Expenditure

Wages and salaries yes yes no

Imputed value of unpaid labour 0 0 no

Energy costs yes yes no

Raw material costs: Livestock costs yes yes no

Raw material costs: Feed costs yes yes no

Repair and maintenance yes yes no

Other operational costs yes yes no

Capital Costs

Depreciation of capital yes yes no

Financial costs, net yes yes no

Extraordinary Costs

EN 52 EN

Variables 2008 2009 2010

Extraordinary costs, net yes yes no

Capital Value

Total value of assets yes yes no

Net Investments yes yes no

Debt yes yes no

Production

Raw material volume: Livestock 0 0 no

Raw material volume: Feed 0 0 no

Total sales volume yes yes no

Employment

Total employees yes yes no

Female employees 0 0 no

Male employees 0 0 no

FTE 0 0 no

Female FTE 0 0 no

Male FTE 0 0 no

Structure

Number of enterprises no yes no

Number of enterprises <=5 employees no yes no

Number of enterprises 6‐10 employees no 0 no

Number of enterprises >10 employees no 0 no


EN 53 EN

4.16 Poland

4.16.1 Delivery of data All required datasets were submitted before the deadline. After JRC data checks and consultation with Polish authorities, data resubmissions occurred before and during the STECF EWG 12-13 (Table 4.16.1).

Table 4.16.1: Summary of uploads for Poland template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐19 2012‐09‐24 4 0DCF_AQUA_MA_2009 2012‐06‐19 2012‐09‐24 4 0DCF_AQUA_MA_2010 2012‐06‐19 2012‐09‐24 4 0DCF_TURNOVER_SALES_2008 2012‐06‐19 2012‐09‐27 2 0DCF_TURNOVER_SALES_2009 2012‐06‐19 2012‐09‐27 2 0DCF_TURNOVER_SALES_2010 2012‐06‐19 2012‐09‐27 2 0

4.16.2 Coverage Poland provided all economic indicators for 2009-2010 at the national totals level. Turnover and sales covered all aquaculture production; while economic variables were collected and reported only for marine aquaculture. In 2010 there were around 1000 aquaculture land-based farms in Poland. The legal form termed ‘natural person’ dominated, representing 76% of all aquaculture entities, followed by ‘legal persons’ (22%) and ‘other’ (2%), indicating that aquaculture farms are managed mainly by small family enterprises or small and medium firms. The total number of people employed was estimated at 5,500. In accordance with the provisions of Chapter IV, Part A, point of 2.2. Commission decision of 6 November 2008 (2008/949/WE), collecting economic data for freshwater species is not mandatory. For this reason the economic performance includes only information on fish farms that breed and rear Atlantic salmon fry and cooperate with the Panel for Restocking appointed by the Minister of Agriculture and Rural Development to stocking Polish Marine Areas. In 2009-2010, there were five such land-based farms.

Table 4.16.2: Coverage of data, provided by the Poland by variable Variables 2008 2009 2010 Income

Total income no yes yes Other income no yes yes Subsidies no yes yes Turnover no yes yes

Expenditure

Wages and salaries no yes yes

Imputed value of unpaid labour no yes yes

Energy costs no yes yes

Raw material costs: Livestock costs no yes yes

Raw material costs: Feed costs no yes yes

EN 54 EN

Variables 2008 2009 2010

Repair and maintenance no yes yes

Other operational costs no yes yes

Capital Costs

Depreciation of capital no yes yes

Financial costs, net no yes yes

Extraordinary Costs

Extraordinary costs, net no 0 yes

Capital Value

Total value of assets no yes yes

Net Investments no yes yes

Debt no yes yes

Production

Raw material volume: Livestock no yes yes

Raw material volume: Feed no yes yes

Total sales volume no yes yes

Employment

Total employees no yes yes

Female employees no yes yes

Male employees no yes yes

FTE no yes yes

Female FTE no yes yes

Male FTE no yes yes

Structure

Number of enterprises no yes yes

Number of enterprises <=5 employees no yes yes

Number of enterprises 6‐10 employees no 0 0

Number of enterprises >10 employees no yes yes

4.16.3 Quality The economic performance includes only fish farms that breed and rear Atlantic salmon juveniles and cooperate with the Panel for Restocking appointed by the Minister of Agriculture and Rural Development (MARD) to restocking Polish marine areas and the maintenance and conservation of diadromous fishes in the surface inland waters. In 2010, there were five such farms. A questionnaire was used to collecting all data. In 2010 all completed questionnaires returned.

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4.17 Portugal 4.17.1 Delivery of data All datasets were uploaded just in time to meet the deadline. Following quality checking procedures by the JRC and Portuguese national expert, some data were adjusted and datasets re-submitted before and during STECF EWG 12-13. The latest re-submission took place on the 27 September 2012 (Table 4.17.1).

Table 4.17.1: Summary of uploads for Portugal template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐21 2012‐09‐26 10 2DCF_AQUA_MA_2009 2012‐06‐21 2012‐09‐26 6 3DCF_AQUA_MA_2010 2012‐06‐21 2012‐09‐26 4 1DCF_TURNOVER_SALES_2008 2012‐06‐21 2012‐09‐27 3 3DCF_TURNOVER_SALES_2009 2012‐06‐21 2012‐09‐27 3 0DCF_TURNOVER_SALES_2010 2012‐06‐21 2012‐09‐27 3 3

4.17.2 Coverage The production data covered all years and was provided by segments. Economic data was provided for all parameters for 2009-2010. There were missing employment and economic parameters for 2008. All data was mostly provided by segments. For DCF data, the following parameters were not submitted:

• Wages and salaries 2008 • Imputed value of unpaid labour 2008 • Repair and maintenance 2008 • Capital costs 2008 • Extraordinary costs 2008 • Capital value 2008 • Employment 2008 (except total employees)

See Table 4.17.2 for the full list of data provided by variable by year.

Table 4.17.2: Coverage of data, provided by the Portugal by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income 0 0 0 Subsidies 0 0 0 Turnover yes yes yes

Expenditure






EN 56 EN

Variables 2008 2009 2010



Capital Costs



Extraordinary Costs

Extraordinary costs, net no yes yes

Capital Value



Debt no yes yes

Production




Employment




FTE no yes yes


Male FTE no yes yes

Structure





4.17.3 Quality The following issues were emphasised by experts during the STECF EWG 12-13:

• Data were registered directly by producers for the first time in 2010, which is an important measure for the sector. However, some inconsistencies were found and the MS is currently checking some of the questioners with producers. The data for 2010 should be analysed with caution;

• The data for 2010 is based on a sample of 597 establishments, which cover 41% of the total population of 1459 establishments;

• It is obligatory for all aquaculture producers in Portugal to annually report production in volume and value as well as economic and social data by species and type of production system;

• The large number of segments constitute some confidentiality issues and aggregations were needed. The techniques used in the production and the species were taken into account for segmentation;

EN 57 EN

Concerning 9.3 segments, where most of the Portuguese aquaculture establishments (94%) are included, their ownership do not have an organised business accounting, and hence, data was unavailable for several economic indicators, such as total capital value of assets and capital costs (net investment, debts, depreciation, etc.);

According to the experts, the production and sales value and volume data used in the data collection program was the same used to compile the statistics for Eurostat and FAO.

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4.18 Romania 4.18.1 Delivery of data All datasets were uploaded in time to meet the deadline. There was no need to re-upload any of the datasets (Table 4.18.1).

Table 4.18.1: Summary of uploads for Romania template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐19 2012‐06‐19 3 1DCF_AQUA_MA_2009 2012‐06‐19 2012‐06‐19 1 2DCF_AQUA_MA_2010 2012‐06‐19 2012‐06‐19 1 1DCF_TURNOVER_SALES_2008 2012‐06‐19 2012‐06‐19 1 1DCF_TURNOVER_SALES_2009 2012‐06‐19 2012‐06‐19 1 1DCF_TURNOVER_SALES_2010 2012‐06‐19 2012‐06‐19 1 0

4.18.2 Coverage Data, submitted by Romania covered 2009-2010 years, all variables were submitted at the national and segments levels. See Table 4.18.2 for the full list of data provided by variable by year.

Table 4.18.2: Coverage of data, provided by the Romania by variable Variables 2008 2009 2010 Income

Total income no yes yes Other income no yes 0 Subsidies no 0 0 Turnover no yes yes

Expenditure



Energy costs no yes yes

Raw material costs: Livestock costs no yes yes

Raw material costs: Feed costs no yes yes


Other operational costs no yes yes

Capital Costs



Extraordinary Costs

Extraordinary costs, net no yes yes

Capital Value



Debt no yes yes

Production

Raw material volume: Livestock no yes yes

EN 59 EN

Variables 2008 2009 2010

Raw material volume: Feed no yes yes

Total sales volume no yes yes

Employment

Total employees no yes yes



FTE no yes yes


Male FTE no yes yes

Structure

Number of enterprises no yes yes

Number of enterprises <=5 employees no yes yes

Number of enterprises 6‐10 employees no yes yes

Number of enterprises >10 employees no yes yes

4.18.3 Quality No major issues detected.

EN 60 EN

4.19 Slovenia

4.19.1 Delivery of data All datasets were submitted before the deadline, however part of the data was resubmitted after data checks performed by the JRC and national experts. All data was checked and ready by the STECF EWG 12-13 meeting (Table 4.19.1).

Table 4.19.1: Summary of uploads for Slovenia

template name first_date last_date n. success n. errorDCF_AQUA_MA_2008 2012‐06‐13 2012‐08‐31 3 1DCF_AQUA_MA_2009 2012‐06‐13 2012‐08‐31 2 1DCF_AQUA_MA_2010 2012‐06‐13 2012‐08‐31 2 1DCF_TURNOVER_SALES_2008 2012‐06‐13 2012‐08‐31 2 1DCF_TURNOVER_SALES_2009 2012‐06‐13 2012‐08‐31 2 1DCF_TURNOVER_SALES_2010 2012‐06‐13 2012‐08‐31 2 1

4.19.2 Coverage The Data sets covered all parameters and were provided by segments. Data covers only marine fish species production of Slovenia.

Table 4.19.2: Coverage of data, provided by the Slovenia by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income yes yes yes Subsidies 0 0 yes Turnover yes yes yes

Expenditure








Capital Costs



Extraordinary Costs


Capital Value



Debt yes yes yes

Production


EN 61 EN

Variables 2008 2009 2010



Employment




FTE yes yes yes



Structure



Number of enterprises 6‐10 employees yes 0 yes

Number of enterprises >10 employees 0 yes yes

4.19.3 Quality and precision Regards to the data base ‘’The central register of aquaculture and commercial ponds’’ from MAFF (The Ministry of Agriculture, Forestry and Food of the Republic of Slovenia), in 2010, there were 11 operators in Slovenia dealing with shellfish farming and two that were engaged in breeding of fish. The data for the operators mentioned were collected from multiple sources (AJPES (The Agency of the Republic of Slovenia for Public Legal Records and Related Services), questionnaire, MAFF), allowing cross checking. The accounting data, which are collected by the AJPES public agency, are already checked and verified. The data were collected for all 13 subjects. In 2011, questionnaire for the socio-economic data collection for aquaculture was improved. In July 2011 the questionnaires for 2010 were sent to all thirteen operators and all responded, i.e. response rate was 100%. Economic data on the aquaculture sector were collected from accounting records – AJPES and through questionnaires. The national program for collection of economic data for the aquaculture sector combines information from three main resources:

1. Questionnaire information returned from the aquaculture sector on a voluntary basis, 2. Data base: ‘The central register of aquaculture and commercial ponds’ from MAFF, 3. The annual accounts of business enterprises.

The data collected from all sources are combined in such a way that a complete set of accounting items is compared for each business enterprise. Due to confidentiality only Mussel rafts segment (seg. 7.1) and Sea bass and sea bream caged (seg. 3.4) were analysed in the EWG 12-13 report. In case of differences between Eurostat/FAO and DCF data, the difference is because the Eurostat/FAO data also contain freshwater aquaculture production.

EN 62 EN

EN 63 EN

4.20 Spain

4.20.1 Delivery of data All requested datasets under the DCF were submitted during the last day of data call. Data was resubmitted after the JRC data checks. The last resubmission date was during the STECF EWG 12-13 meeting (Table 4.20.1).

Table 4.20.1: Summary of uploads for Spain


4.20.2 Coverage Data was submitted for all economic parameters for years 2008-2010. Production value was provided by species 2008-2010 but volume information was missing (Table 4.20.2). All data were provided by segments. The following production parameters were not submitted:

• Total sales volume national total and segments (2008-2010) • Raw material volume: Livestock (2008-2010)

Table 4.20.2: Coverage of data, provided by the Spain by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income yes yes yes Subsidies yes yes yes Turnover yes yes yes

Expenditure








Capital Costs



Extraordinary Costs


Capital Value

EN 64 EN

Variables 2008 2009 2010



Debt yes yes yes

Production

Raw material volume: Livestock no no no


Total sales volume no no no

Employment




FTE yes yes yes



Structure





4.20.3 Quality Spain has two surveys directed to the aquaculture sector: the Activity Survey and the Economic Survey. Both surveys are conducted at the same time, using the same population and with a common field work programme. Each survey has its own questionnaire, getting information for different variables, except the value for the production (collected in both questionnaires). In this case, individual answers are checked and if there are inconsistencies, they are checked and errors corrected. So the consistency between both surveys is guaranteed. Data are collected using combined methods; in a part of the population it is used a census and in another part a stratified sampling is the method used. The segmentation used in Economic Survey uses a typology of aquaculture establishments which is coherent with the established groups in the Commission Decision 2010/93/UE. The proposed stratification does not allow for obtaining valid results for the whole population, in the cases where Probability sample survey is used and require certain breakdowns, such as in the following:

• Turnover and “Income. “For species”. Each segment collects large groups of species (salmon, trout, sea bream, sea bass, common carp, etc…). Firms may belong to only one segment. However, they can grow and produce different species. The random sample selection takes into account the main species (in volume). The stratums aren’t representative of the species that

EN 65 EN

are grown or produced. For this reason, an important bias may result when sample results are raised to the population.

• Total sales volume: in addition, volume must be measured in tonnes. The production for human consumption is measured in tonnes; however, different stages of the life cycle (eggs or juveniles) are measured in quantities, making it difficult to estimate a conversion factor between quantities to tonnes since each establishment produces different size juveniles depending on demand. Hence, the main reason for Spain not providing data in DCF is because the end user could interpret the figures given in tonnes as the only production related to the total incomes provided. While this income is due to this production plus another production measured in quantities.

• Raw material volume: Feed: There is some data for feed collected in litres (feed used in mollusc hatcheries and nurseries…).

EN 66 EN

4.21 Sweden

4.21.1 Delivery of data All the datasets were uploaded to the system before the deadline. Following quality checks by JRC and the Swedish expert, some datasets were changed and resubmitted before the STECF EWG 12-13 on the aquaculture meeting, see also Table 4.21.1.

Table 4.21.1: Summary of uploads for Sweden


4.21.2 Coverage All parameters were provided by segments, except employment by gender and FTE by gender. Only some production data was not provided by segments due to confidentiality issues. Sweden provided all parameters required by DCF for all years (2008-2010). The data set also covered aquaculture activities in fresh water.

Table 4.21.2: Coverage of data, provided by the Sweden by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income yes yes yes Subsidies 0 yes yes Turnover yes yes yes

Expenditure








Capital Costs



Extraordinary Costs


Capital Value


EN 67 EN

Variables 2008 2009 2010


Debt yes yes yes

Production




Employment




FTE yes yes yes



Structure





4.21.3 Quality The Swedish Agency for Marine and Water Management (previously The Swedish Board of Fisheries) was responsible for compiling and reporting statistics on the aquaculture sector for the reported period. The Swedish Agency for Marine and Water Management in cooperation with Statistics Sweden conducted two questionnaires and a tax declaration survey for each year. Data was collected by Statistics Sweden in several ways. First, income tax declarations from every enterprise whose main source of income (more than 50 %) came from aquaculture were compiled (EUROSTAT definition under NACE Code 03.2 “Fish farming”). A questionnaire concerning farming techniques, investments, production value and volume was sent to all aquaculture farms. The purpose of this survey was to provide additional information in order to enable a clustering of farming units to enterprises in cases when several farming units are equal to one fiscal enterprise. This method also makes it possible to compare information on value of aquaculture production with declared income from income tax declarations. These comparisons are needed to determine whether aquaculture farming is the main activity of the enterprise or not. Secondly, a questionnaire was sent to a sample of the aquaculture enterprises in order to create a cost allocation key for costs that are not specified in the income tax declaration. This is a non-probability survey.

EN 68 EN

Data on subsidies was collected from The Swedish Agency for Marine and Water Management, the managing authority of the European Fisheries Fund (EFF), and compiled by Statistics Sweden. Lastly, in order to identify the segments, companies using more than one farming technique or growing more than one species, all production, incomes and costs were transferred to the main technique and main species based on turnover.1 Data on aquaculture production is reported from the Swedish official statistics to Eurostat. Hence, the volume of production as reported by Eurostat should coincide with volumes reported in Swedish official statistics. However, disparities can occur due to updates in the data mainly due to changes in the number of active enterprises.

1 Source: The Swedish Agency for Marine and Water Management

EN 69 EN

4.22 United Kingdom

4.22.1 Delivery of data UK started uploading procedure almost 3 months after the deadline and one week before the STECF EWG 12-13 meeting (Table 4.22.1).

Table 4.22.1: Summary of uploads for United Kingdom

template name first_date last_date

n. success

n. error

DCF_AQUA_MA_2008 2012‐09‐19 2012‐09‐19 2 0 DCF_AQUA_MA_2009 2012‐09‐19 2012‐09‐19 2 0 DCF_AQUA_MA_2010 2012‐09‐19 2012‐09‐19 2 0 DCF_TURNOVER_SALES_2008 2012‐09‐19 2012‐09‐20 4 9 DCF_TURNOVER_SALES_2009 2012‐09‐19 2012‐09‐20 1 3 DCF_TURNOVER_SALES_2010 2012‐09‐20 2012‐09‐20 1 3

4.22.2 Coverage UK did not provide any data on production volume as well as raw material. Most of the economic parameters were missing. For DCF data, the following parameters were not submitted:

• Imputed value of unpaid labour (2009-2010) • Energy costs 2008-2010 • Raw material costs 2008-2010 • Repair and maintenance 2008-2010 • Debt 2008-2010 • Depreciation 2008-2010 • Financial costs 2008-2010 • Extraordinary costs 2008-2010 • Net investments 2008-2010 • Raw material volume 2008-2010 • Total sales volume 2008-2010 • All production parameters 2008-2010

Data provided at the national totals level only.

Table 4.22.2: Coverage of data, provided by the United Kingdom by variable Variables 2008 2009 2010 Income

Total income yes yes yes Other income 0 0 0 Subsidies 0 0 0 Turnover yes yes yes

Expenditure

EN 70 EN

Variables 2008 2009 2010


Imputed value of unpaid labour 0 no no

Energy costs no no no

Raw material costs: Livestock costs no no no

Raw material costs: Feed costs no no no

Repair and maintenance no no no


Capital Costs

Depreciation of capital no no no

Financial costs, net no no no

Extraordinary Costs

Extraordinary costs, net no no no

Capital Value


Net Investments no no no

Debt no no no

Production

Raw material volume: Livestock no no no

Raw material volume: Feed no no no

Total sales volume no no no

Employment


Female employees 0 0 0


FTE yes yes yes

Female FTE 0 0 0


Structure





4.22.3 Quality STECF EWG-11-14 commented that the UK "did not provide a complete set of economic indicators". This continues to be the case because it is UK government policy not to impose additional burdens of data reporting on industries. The available data comprises production volumes collected through a census process undertaken as part of statutory health surveillance visits to farms. Other totals for economic indicators are estimated by a separate process drawn from a sample survey covering all industries (ONS Annual Business Survey). This reports on aquaculture as a sector but does not distinguish between production methods.

EN 71 EN

Agreement between the census values and raised values from the sample surveys is good at plus or minus 10%.

European Commission

EUR 25576 EN – Joint Research Centre – Institute for the Protection and Security of the Citizen

Title: DCF Economic data call for aquaculture 2012 – Coverage Report.

Luxembourg: Publications Office of the European Union

2012 – 74 pp. – 21 x 29.7 cm

EUR – Scientific and Technical Research series – ISSN 1831-9424 (online), ISSN 1018-5593 (print)

ISBN 978-92-79-27200-4

doi:10.2788/62529

Abstract

This Data Collection Framework (DCF) coverage report was prepared by the Joint Research Centre (JRC) as part of an Administrative Arrangement with DG MARE. The purpose of the document is to provide an overview of the timeliness and completeness of the Member States data submissions to JRC in response to the call for economic data on aquaculture sector concerning 2008-2010 issued by DG MARE under the DCF (Council Regulation No 199/2008). Additionally, the report provides some indication of data quality, summarising major quality issues detected by JRC and the two Expert Working Groups convened under the Scientific, Technical and Economic Committee for Fisheries (STECF).

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