Animal Production Statistics

Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Eurostat, the statistical office of the European Union.

Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
National metadata - Milk and milk products

National metadata - Livestock and meat

National quality report

National metadata produced by countries and released by Eurostat

For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT


1. Contact Top
1.1. Contact organisation

Eurostat, the statistical office of the European Union.

1.2. Contact organisation unit

E1: Agriculture and fisheries

1.5. Contact mail address

2920 Luxembourg LUXEMBOURG

2. Metadata update Top
2.1. Metadata last certified 20/10/2017
2.2. Metadata last posted 20/10/2017
2.3. Metadata last update 20/10/2017

3. Statistical presentation Top
3.1. Data description

Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements.

  • Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.
  • Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.
  • Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks.

European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned.

The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics.

The same statistics are requested from the candidate countries as acquis communautaire.

Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables.

The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately.

Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables.

The detailed content of each table and the reference to its legal definition is provided in the table below.


Table 3.1: Data tables disseminated regarding animal production statistics



Legal basis

Legal reference

Data frequency



Poultry farming (apro_ec)


Poultry (annual data)







Poultry (monthly data) 

Reg. (EC) No 617/2008

Annex III


45 days



Hatcheries - poultry other than hens

Reg. (EC) No 617/2008

Annex IV


30 January next year



Hatcheries - hens


 Milk and milk products (apro_mk) 


Fat contents and protein contents (cow's milk) 

Dec. 97/80/EC

Table B


30 June next year



Milk collection (all milks) and dairy products obtained  



Cows'milk collection and products obtained (annual data) 





From apro_mk_colm


Cows'milk collection and products obtained (monthly data) 

Dec. 97/80/EC

Table A


45 days



Production and utilization of milk on the farm 

Dec. 97/80/EC

Table C


30 September next year


 Dairies structure - triennial (apro_mk_str) 


Milk collection - Distribution of enterprises by volume of annual collection  

Dec. 97/80/EC


Table D

every third year


30 September next year



 Milk collection - Distribution of collection centres by volume of annual collection

Table E


Milk treated - Distribution of enterprises by volume of annual production 

Table F


 Fresh products - Distribution of enterprises by volume of annual production

Table G1


Drinking milk - Distribution of enterprises by volume of annual production 

Table G2


Powdered dairy products - Distribution of enterprises by volume of annual production 

Table G3


Butter - Distribution of enterprises by volume of annual production 

Table G4


Cheese - Distribution of enterprises by volume of annual production

Table G5

 Livestock and meat (apro_mt) 

 Meat production (apro_mt_p) 


Meat production and foreign trade - weight - (monthly data) 

Reg. (EC) No 1165/2008



60 days



Meat production and foreign trade (annual data)  







Slaughtering, other than in slaughterhouses 

Reg. (EC) No 1165/2008



30 June next year



Meat production and foreign trade - head 

Reg. (EC) No 1165/2008



60 days



Production forecasts pig - head 

Reg. (EC) No 1165/2008



15 February,

15 September

15 September for 13 MSs


Production forecasts cattle, sheep and goat - head 

Reg. (EC) No 1165/2008



15 February,

15 September

September deadline for 12 MSs (bovine animals), 12 MSs(sheep) and 5 MSs (goats)


Meat balance sheet 

No longer updated





 Livestock (apro_mt_ls) 

apro_mt_lscatl (May-June)

Cattle population 

Reg. (EC) No 1165/2008



15 September

due by 12 MSs





Next year: 15 February (provisional) and 15 May (definitive)



Goat population 

Reg. (EC) No 1165/2008



Next year: 15 February (provisional) and 15 May (definitive)

due by 5 MSs



No longer updated



15 September

See farm structure survey results


Sheep population 

Reg. (EC) No 1165/2008



Next year: 15 February (provisional) and 15 May (definitive)

due by 13 MSs

apro_mt_lspig (May-June)

 Pig population

Reg. (EC) No 1165/2008



15 September

due by 12 MSs

apro_mt_lspig (November-December)


Reg. (EC) No 1165/2008



Next year: 15 February (provisional) and 15 May (definitive)


Structure of rearing (apro_mt_str) 





Structure of rearing 

No longer updated




See farm structure survey results

Regional Agriculture Statistics (agr_r) 


 Animal populations (December) by NUTS 2 regions

Reg. (EC) No 1165/2008



Next year: 15 February (provisional) and 15 May (definitive)

NUTS 2 regions (DE and UK NUTS1)


Production of cow's milk on farms by NUTS 2 regions (1 000 t) 

Dec. 97/80/EC



30 September next year

NUTS2 regions

3.2. Classification system

Some standard code lists cover the concepts over the domains. The list of items and their definition is in any case derived from the legislation, but the coding integrates different approaches. The following concepts have been integrated in a single list agriprod:

  • Live animals
  • Meat and meat products
  • Dairy and other animal products (except meat)

Some other classifications will be harmonised.

  • Activities (e.g. hatching of chicks by utility, cows’ milk collection)

A handbook on concepts and definitions used for animal production statistics is provided in Annex 1.

Regional data

The territorial classification of regional data (tables agr_r_milkpr and agr_r_animal) is broken down according to the NUTS classification for Member States and to Eurostat’s list of Statistical Regions for Candidate countries and EFTA countries.

3.3. Coverage - sector

Statistics on livestock, on farm production, on other slaughtering and utilisation of milk cover agricultural holdings in Member States.
The minimal coverage for livestock sample surveys is of at least 95 % of the national population with reference to the last survey on the structure of agricultural holdings (FSS).

Livestock surveys may be conducted independently by livestock category or as a sub-set of items surveyed with a wider scope (livestock survey as a whole, farm production survey, annual census) or recorded with a wider objective in the case of registers (every animal owner). Depending on the design, some over-coverage can be observed.

Statistics on external trade in chicks are designed to reflect foreign trade in chicks from hatcheries with more than 1 000 incubation places.

Other animal production statistics cover EU plants whose activity is slaughtering, milk collection, milk product production or hatching fertilised eggs. The sample surveys must cover exhaustively dairies representing 95 % of the cows’ milk collected by Member States, the balance being represented by sampling or other sources. The methodological questionnaire collected from Member States reports whether a correction is applied for cross-border collection of milk from dairy farms in a country by dairy enterprise in a neighbour country.

See also Annex 1 for further explanations.

3.4. Statistical concepts and definitions

Among concepts used in animal production statistics (see Annex 1), some can be reported because of their specificity.

Gross indigenous production (GIP) is the number of animals slaughtered plus the balance of intra-Community and external trade for the same kind of live animals. GIP is thus the number of animals from a Member State (indigenous) apparently (gross) slaughtered or exported alive.

Slaughtering is measured through activity of slaughterhouses from 1 January 2009 (application of Regulation (EC) No 1165/2009), i.e. production of marketable meat for human consumption. Estimates of ‘other slaughtering’ can be added for a more accurate picture of meat production.

Livestock is accounted by categories that capture their rearing, either for fattening then slaughter, or for herd renewal, i.e. for breeding and/or milking.

Milk statistics are led by the concept of ‘national dairy’, i.e. the dairy sector is considered as a single process, which internal flows are not (intended to be) taken into account.

Use of raw milk is followed through production of its two main components, fat and protein content. Milk processed is thus accounted for as an aggregate of UWM (utilised whole milk, with the full content of fat and proteins) and USM (utilised skimmed milk, with the full content of proteins,without fat). As a process can produce skimmed milk further to the main (fat) product and, in such a case, USM can be negative. This is especially the case for cream and butter production.

Bovine animals are domestic animals of the species Bos taurus and Bubalus bubalis, including hybrids like Beefalo. Clarification on the implementation of this definition led to the integration of buffaloes and hybrids into the category 'bovine animals'.

Chickens means all animals of species Gallus gallus, including broilers and boiling hens. This concept was applied with Regulation (EC) No 1165/2008 on 1 January 2009.

Regional data

Region means a sub-division of a Member State territory. Depending on the statistics, 'region' refers to:

  • NUTS 2 for milk production (table agr_r_milkpr), the NUTS reference being the version applicable on the date of data transmission.
  • NUTS 2, except for DE and UK (NUTS1) for livestock statistics (table agr_r_animal).

For data on the structure of hatcheries, a particular region (the most important) can be considered as representative of the national data in BG, EL, LV and AT.

3.5. Statistical unit

Agricultural holdings are the statistical units for livestock surveys and animal production statistics at farm level (milk production and meat). Depending on the statistics collected, a more precise definition can be used, based on their activity or their structure, e.g. dairy farms producing raw milk, or farms with livestock or with sheep or goats.

Dairy enterprises -- undertakings of two types:

  • Collection centres collect milk or cream and transfer it in whole or in part to other enterprises without any processing. They are often defined as referred to in Article 2(2) of Council Directive 96/16/EC.
  • Dairies and agricultural holdings purchase milk or milk products from agricultural holdings or collection centres with a view to transforming them into milk products. They are often defined as referred to in Article 2(1) of Council Directive 96/16/EC.

Some enterprises process milk products obtained from a dairy as defined above, e.g. skimmed milk into milk powder or yogurt, and may appear to be excluded from the definition of dairy enterprises. Nevertheless, non-packed intermediate products are considered as raw products and such dairies are therefore covered as statistical units for the purpose of some statistics, whatever the enterprise supplying them.

Slaughterhouses are registered and approved establishments used for slaughtering and dressing animals whose meat is intended for human consumption. In countries in which ‘hygiene package’ is not fully implemented (slaughterhouses not registered or not approved by the EU can nevertheless produce for the local market) all slaughterhouses are covered.

Hatcheries are establishments for incubating eggs, hatching and supplying chicks.

For some animal production statistics, the statistical units are not explicitly defined, i.e. they refer to all enterprises. This is the case for statistics on the trade in chicks and this used to be the case for slaughtering statistics. Indirectly, the statistical units are the reporting enterprises dealing with one of parameters to be measured by the statistics.

3.6. Statistical population

The statistical population is the framework of the statistical units in the reference Member State or country for the reference period.

Nevertheless, data collection may be organised in a different way by a respondent other than the statistical unit. For instance, milk delivered by farms to dairies is accounted for by both units, and can be obtained more easily from dairies, of which there are fewer.

For monthly milk statistics, the population covers the dairies collecting cows’ milk. The quantity of milk products processed is therefore underestimated compared to national production.

3.7. Reference area

The reference area is the territory of the Member States as defined by Decision 91/450/EEC [1]. For non-EU countries, territory follows the definition agreed bi-laterally with Eurostat.

[1] Commission Decision of 26 July 1991 defining the territory of Member States for the purposes of implementing Article 1 of Council Directive 89/130/EEC, Euratom on the harmonisation of the compilation of gross national product at market prices. OJ L 240, 29.8.1991, pp. 36-40.

3.8. Coverage - Time

Data are presented in chronological series for each country and for the EU. The period covered varies according to the country, depending on the date of accession to the EU. They are available at least for the EU Member States, depending on the date they became members of the EEC or EU, from legislation to repeal of the legal text and insofar as Member States comply with legislation.

Statistics are available, at least partly, since reference years 1960 (milk statistics), 1964 (meat statistics) and 1970 (livestock statistics and statistics on eggs for hatching and chicks) for the countries that were Member States at this time.

Further time periods may be available if collected on a volunteer basis, especially:

  • Data collected under a gentlemen’s agreement
  • Data collected for accessing and acceding countries
  • Data collected under other specific agreements

The production forecast cover four or six quarters for pigs, three or four semesters for bovine animals, and two or zero semester for sheep and goat, depending on the size of the national livestock. At the end of September, year N, the forecast must be available up to the end of: - year N+1 for bovine animals and - first half of year N+1 for pigs. At the end of February, the forecast regarding sheep and goats must be available up to the end of the year for the countries with significant production.

3.9. Base period

Not applicable.

4. Unit of measure Top

The units of measure are

  • for livestock and gross indigenous production

1000 heads

  • for slaughtering

1000 tonnes (carcass weight), 1000 heads

  • for milk statistics
    except for fat and protein content

1000 tonnes
tonnes or percentage

  • for chicks and eggs

1000 units

5. Reference Period Top

For non-cumulative variables such as stock or inventory variables, the reference date is

  • a given day during the period displayed in ‘Month’ for livestock (tables such as apro_mt_ls*),
  • on 31 December of the year indicated in ‘Time’ for annual and less frequent data (apro_ec_lshen, apro_ec_strpoul, apro_ec_strhen, tables like apro_mk_str* and like apro_mt_str*).

For cumulative variables such as production or flows, the reference periods are:

  • the calendar month for data in tables apro_mk_colm apro_mt_pwgtm, apro_mt_pheadm and apro_ec_poulm,
  • the calendar quarter for GIP forecast for pigmeat in table apro_mt_ppighq,
  • the calendar semester for other GIP forecast for meat in table apro_mt_pcatlhs,
  • the calendar year for all other animal production statistics.

6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

The legal acts currently applicable are:

  • Regulation (EC) No 1165/2008 of the European Parliament and of the Council of 19 November 2008 concerning livestock and meat statistics and repealing Council Directives 93/23/EEC, 93/24/EEC and 93/25/EEC. OJ L 321, 1.12.2008, p. 1–13.
    Germany and Bulgaria were granted derogations from the application of this Regulation until 1 January 2010 or, in the case of statistics on sheep and goats, until 1 January 2011 (Commission Decision 2010/323/EU).
  • Directive 96/16/EC of 19 March 1996 on statistical surveys of milk and milk products. OJ L 78, 28.3.1996, p. 27–29.
  • Decision 97/80/EC of 18 December 1996 laying down provisions for the implementation of Council Directive 96/16/EC on statistical surveys of milk and milk products. OJ L 24, 25.1.1997, p. 26–49.
  • Commission Regulation (EC) No 617/2008 of 27 June 2008 laying down detailed rules for eggs for hatching and farmyard poultry chicks (OJ L 168, 28.6.2008, p. 5–16) implementing Regulation (EC) No 1234/2007.

The following agreements are also applicable:

  • Agreement on the European Economic Area (OJ No L 1, 3.1.1994, p. 3; and EFTA States’ official gazettes), Annex XXI, regarding milk statistics
  • Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics

Finally some former legal texts and agreements were previously applied. When feasible, Eurostat ‘aligns’ the time series, possibly with an indication for breaks (flag ‘b’); otherwise, the series looks incomplete. In some cases, entire tables are no longer updated.

Regional data

Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS).  OJ L 154, 21.6.2003, p. 1-41; (Consolidate version - 07/02/2011). 

6.2. Institutional Mandate - data sharing

Not applicable.

7. Confidentiality Top
7.1. Confidentiality - policy

Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

A confidentiality charter for animal production statistics has been adopted in 2016 (Confidentiality Charter - Animal production statistics.pdf) and should lead to disseminate more EU totals from 2018 on.

7.2. Confidentiality - data treatment

Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

A confidentiality flag is 'computed' for each aggregate. By default, if one or more components are confidential the aggregate is also flagged as confidential. Implementation of the confidentiality charter is based on the set of methods agreed and refer to the number of cells, the possible dominance of some of them and the logical links between the values with the same table or in different tables.

8. Release policy Top
8.1. Release calendar

Data are disseminated as soon as they are available.

8.2. Release calendar access

Not available.

8.3. Release policy - user access

In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see item 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.

9. Frequency of dissemination Top

Data dissemination usually follows data collection by a few days. Frequency is thus the same in both cases for a given data set.
For most of the data collected, collection frequency is the time granularity of the data, i.e. monthly data are collected monthly and annual data annually.
Annual totals provided in tables apro_mk_cola, apro_mt_pann and apro_ec_poula are disseminated at the same time as data for December.
GIP forecasts for meat are collected twice a year or, for countries with a limited livestock population, annually.
Data on the structure of dairy enterprises are collected every third year.

10. Accessibility and clarity Top
10.1. Dissemination format - News release

News releases on-line.

10.2. Dissemination format - Publications


Publications available in pdf format are accessible on Eurostat's website (Statistics / Agriculture and fisheries / Agriculture / Publications). Eurostat has published in 2016 the Eurostat regional yearbook 2016

The Directorate General on Agriculture and Rural Development (DG-AGRI) publishes regularly a Short-term outlook.

Statistics Explained

Statistics Explained is an official Eurostat website presenting many statistical topics in an easily understandable way. Together, the articles make up an encyclopaedia of European statistics, completed by a statistical glossary clarifying all terms used and by numerous links to further information and the very latest data and metadata, a portal for occasional and regular users alike.

Animal production articles:

The page which provides a clickable list of all articles in Statistics Explained on agriculture, can be accessed under the following link:

The Eurostat statistics are widely re-disseminated. For improving the market transparency, the EU Milk Market Observatory provides for instance statistics on milk production.

10.3. Dissemination format - online database

The data on animal production statistics may be found on the Eurostat’s dissemination database under the link: and under the following paths: Statistics / Agriculture and Fisheries / Agriculture / Data / Database / (+) Agriculture / (+) Agricultural products / (+) Milk and milk products, or (+) Poultry farming, or (+) Animal production and for regional agricultural statistics: Statistics / Agriculture and fisheries / Data / Database / (+) Agriculture / (+) Regional agriculture statistics / (+) Animal populations, or (+) Production of cows' milk on farms.

This channel displays all the public Animal Production results.

10.4. Dissemination format - microdata access

Not applicable.

10.5. Dissemination format - other

Eurostat uses to provide regularly two summary reports as MS Excel files to interested users, on slaughtering and on cows'milk collection.

These files provide a sub-set of the results as in the dissemination database at the relevant date and therefore this way of dissemination is going to disappear.

Confidentiality is especially an issue for milk statistics due to the dominant contribution of the largest enterprises in the national totals, and especially for some products (e.g. dairy powders). Further investigations are currently conducted in order to improve the dissemination of the EU results without threatening statistical confidentiality.

10.6. Documentation on methodology

Public documentation on methodology and legislation is available on-line at" target="_blank.

10.7. Quality management - documentation

Member States provide Eurostat with a report on the quality of the data transmitted every third year under the current legislation on livestock and meat, and for the first time for reference year 2010.

Member States send Eurostat an annual methodological questionnaire on milk statistics providing some quality indicators.

This information may be disseminated to the public once this is agreed with Member States.

11. Quality management Top
11.1. Quality assurance

Animal production statistics are subject to the general quality assurance framework of Eurostat, where domain-specific quality assurance activities (the use of best practices, quality reviews, self-assessments, compliance monitoring) are carried out systematically.

11.2. Quality management - assessment

Principal strengths of statistical output:

  • Long history and experience;
  • Legal basis;
  • Data collection based on common methodology and harmonised questionnaires;
  • Good knowledge of key users and their needs;
  • Sound monitoring of compliance with the requirements of data collection;
  • Close cooperation with data providers;
  • Share of best practices on data validation;
  • Good completeness of the data received;
  • Validation processes in place;
  • Detailed methodological information is available to the public;
  • Data is normally disseminated a few hours after being received;
  • Coherence analysis with other statistics is undertaken;
  • The statistical process is revised and improved according to emerging needs;
  • Innovative IT applications are used for data collection, validation and dissemination.

Principal weaknesses of the statistical output:

  • More information on profiles and specific needs of users would be useful;
  • Coordination with international organisations could be improved with a view to reducing the burden on respondents and further improve data coherence;
  • Timeliness of data delivered from certain countries could be improved;
  • More information on metadata and certain validation procedures at country level is needed;

There is still room for further automation of routine clerical operations such as data validation.

12. Relevance Top
12.1. Relevance - User Needs

The main users are other Directorates General of the European Commission (e.g. DG Agriculture and rural development and DG Health and Consumers). However, there are other major users such as other European institutions, national administration services, national statistical institutes, other international organisations, agro-industry, producer groups, research institutes, journalists, third countries and the public in general. The objectives of these users vary, but animal production statistics are especially useful for market management/monitoring, production forecasts and policy-making in agriculture and food.

12.2. Relevance - User Satisfaction

Key users are well known and their needs are met. In addition, specific questions from individual users are answered.
Eurostat conducts regular user surveys with a wider scope.

12.3. Completeness

Since 2010, completeness has been measured regularly and discussed during meetings of the Working Party on Annual Production Statistics. Meanwhile it has been regularly improved.

To reduce the burden on respondents, some statistics are collected less often in countries with limited importance in the EU-28 totals. Statistics on bovine population are due only once a year for the Member States where it is below 1.5 million head. Statistics on pig population are due only once a year for the Member States where it is below 3 million head. Statistics on sheep population are not expected from the Member States where it is below 500 000 head. Statistics on sheep population are not expected fromthe Member States where it is below 500 000 head.

Also some further data are not due and may appear to be missing, due to the ‘cube’ approach of the dissemination database (each selected code of a dimension is crossed with each selected code of each dimension).

Regional livestock population is not mandatory when it is under 75 000 bovine animals, 150 pigs, 100 000 sheep and 25 000 goats.

13. Accuracy Top
13.1. Accuracy - overall

Accuracy is normally accuracy displayed and reflects accuracy of computation. Nevertheless threshold for significance is half of the displayed unit. It means that '0.000' with flag 'n' is lower than 0.5 whereas 0.001 is lower than 0.0005. '0.000' without flag 'n' is a true zero, i.e. with full accuracy.

13.2. Sampling error

Regulation (EC) No 1165/2008 states that sampling errors for the results of each Member State shall not exceed (with a confidence interval of 68 %):

  • 1 % of the total number of bovine animals (5 % where the bovine animal population is below 1 000 000 head);
  • 1.5 % of the total number of cows (5 % where the cow population is below 500 000 head);
  • 2 % of the total number of pigs (5 % where the pig population is below 1 000 000 head); and
  • 2 % of the total number of sheep and goats (5 % where the sheep and goat population is below 1 000 000 head).

The Member States report to Eurostat on the actual accuracy but these national figures are not publishable.

Directive 96/16/EC states that the sampling error must not exceed 1 % of the total national [milk] collection (with a confidence interval of 68 %).

No quality criterion is defined in Regulation (EC) No 617/2008.

13.3. Non-sampling error

Measurement errors are due mainly to lack of harmonisation in statistical methods. For instance, when EU concepts do not fit with national concepts, there may be significant measurement errors. As well over-coverage (surveying units out of the statistical population) may be due to the same, when the harmonised definition of the statistical unit is not implemented. Data providers are expected to correct these deviations.

14. Timeliness and punctuality Top
14.1. Timeliness

Table 3.1. (see 3.1. data description) shows the deadlines for the various animal production statistical tables, given relative to the end of the reference period.
The actual timeliness (length of time between the event and availability of the statistical output) can be shorter than the legal timeliness if data are provided earlier. The time lag between the actual release date and the planned (agreed or legal) date is called punctuality.
The actual timeliness for EU-28 results depends on timeliness achieved among Member States. Time taken for data validation and dissemination by Eurostat is also taken into account.

14.2. Punctuality

Data are normally received within the legal deadlines. However, some countries may experience delays in sending their data to Eurostat due to exceptional circumstances.

15. Coherence and comparability Top
15.1. Comparability - geographical

Animal production statistics are mostly comparable over countries and regions with the following exceptions:

  • Gentlemen’s agreements may be agreed with only some countries
  • A derogation to EU statistical legislation may have been granted
  • The legislation itself provides for differentiated approaches for countries depending on their livestock population
  • Specific agreements with EEA countries and with the Swiss Confederation envisage limit application of the legislation and exceptions to the definitions

Other non-EU countries may partly implement EU legislation and some concepts may be irrelevant for them. Quality of the statistics is usually not at the same level as for statistics under EU legislation.

Comparability of regional data over time will be affected by breaks in the NUTS classification.

15.2. Comparability - over time

Animal production statistics are largely comparable over time, with the following exceptions:

  • Implementation of Regulation (EC) No 1165/2008 (see ASA-TE-696.Inventory_of_changes.rev1.doc )
  • Change of NUTS for regional statistics
  • Other changes in the methodology flagged with "b", indicating breaks in the time series
15.3. Coherence - cross domain

Most livestock categories are comparable with certain characteristics from the farm structure survey, but differences in the design of each survey (especially reference date and calibration method) may produce discrepancies in estimates.

15.4. Coherence - internal

Internal coherence is insured through pre-validation checks during the data collection and validation on the data received in Eurostat.

16. Cost and Burden Top

Permanent efforts are done to limit the burden on the respondents and, if relevant on the competent national authorities.

  • The design of Regulation (EC) No 1165/2008 makes optional the delivery of some data sets for the countries under a certain threshold. This approach by differentiate intensity of burden relatively to the policy interest is favoured in the new data collection (gentlemen's agreements). This might make difficult using the tables with national values due to the gaps.
  • Use of administrative sources is favoured (livestock statistics) when it is not the prefered data source (slaughtering).
  • Involvement of the respondents as data users (milk statistics) contributes to a balanced burden.
  • The supply balance sheets, requested previously at national level are now compiled , with few exceptions, at EU level.

17. Data revision Top
17.1. Data revision - policy

Data are revised if figures of higher quality become available.

In order to provide fresh statistics, Regulation (EC) No 1165/2008 foresees that provisional livestock statistics are delivered first (in February and September) and definitive results are provided later (in May and October).

17.2. Data revision - practice

Results can be corrected by the countries concerned during the months after data has been sent.

18. Statistical processing Top
18.1. Source data

The data sources may be sample surveys or censuses for milk and livestock statistics. Nevertheless administrative sources may be used for obtaining these results in order to limit burden on the respondents. This is especially the case for bovine livestock. The milk quota registers are used up to the end of the milk quota regime (April 2015).

See also Annex 3 for livestock and meat statistics.

18.2. Frequency of data collection

For most of the data collected, collection frequency is the time granularity of the data, i.e. monthly data are collected monthly and annual data annually.

Annual totals provided in tables apro_mk_cola, apro_mt_pann and apro_ec_poula are disseminated at the same time as the data from December.

GIP forecast for meat are collected twice a year or, for the countries with a limited livestock population, annually.

Data on the structure of dairy enterprises are collected every third year.

18.3. Data collection

Data and metadata transmission is executed in the same manner in all three sub-domains. The input consists of the national data which are ready for transmission and the output comprises the XML data files in eDAMIS servers.

CNAs transmit regional (where required) and national statistics to Eurostat exclusively via eDAMIS. The data comprise all variables listed in Chapter 2 heading 5 except those for which it is indicated that they are computed by Eurostat. The data comprise nine datasets on milk statistics, 16 datasets on livestock and meat production statistics and three datasets on poultry statistics, displayed in Table 2. Special notes about the transmission of some livestock and meat datasets are given in Table 3.

The transmission means used is eDAMIS Web Forms (eWF). A specific form exists for each dataset, presented as a spreadsheet-like table on screen. According to usual eWF functionality, the form automatically retrieves from eDAMIS servers and displays the data transmitted for earlier reference periods. CNA staff type or import the statistics for the current reference period, and also for earlier periods if they wish. The form implements pre-validation, i.e. “real-time” validation.

If there are no critical errors and no basic errors without justification the data can be transferred to eDAMIS, where they are converted into XML files and are stored in eDAMIS’ servers.

When the data are transmitted the domain manager is automatically notified by eDAMIS.

Confidential data

Each data item is accompanied by a flag which shows whether the data is confidential or not.

Regarding milk statistics in particular, in 2010 14 countries flagged certain items as confidential since three or less dairy enterprises had a significant contribution to the production of milk or of milk products such as powered dairy products.

Monitoring of data transmission

The monitoring of data transmission starts at the time the collection takes place. Countries, which have not provided data one week after the end of the deadline, are notified with a reminder sent by the eDAMIS collection system automatically. Eurostat domain managers contact the data provider three weeks later. In case of non-response Eurostat contacts the data provider again before sending the formal reminder letter, which is the last step before starting an infringement procedure.

18.4. Data validation

1. Data validation in Member States

Data validation in Member States is known depending on their reporting.

  • For milk statistics, Member States validate the data collected from farms and dairies. Comparisons with data obtained from the same dairy/farm in previous collection rounds of the survey and with data from other surveys are usually carried out. Moreover, variables collected from dairies are compared with similar ones collected from farms. No more information about other validation performed by the Member States before data submission to Eurostat is available.
  • For livestock and meat statistics, the information about data validation is scarce. It covers all MSs with the exception of Austria since at the time of writing the present document no quality report was received from the country.
    Eleven CNAs report that they implement “real-time” validation of the data they collect, i.e. validation at the moment of collection. 22 CNAs mention explicitly that they validate the data: 18 compare the data with data for the same statistical units from earlier data collections, while 14 CNAs do other comparisons, which are not described. One CNA uses the results of a sample survey to check the data about slaughtering collected monthly from administrative sources.
    Reporting of the use of imputation, re-calibration or other correction / adjustment methods is connected explicitly with the treatment of non-response. It cannot therefore be known whether they are also used to correct other errors identified during validation. Re-calibration is used by eight CNAs, to treat non-response in livestock surveys. Imputation is employed by four CNAs in the case of monthly slaughtering statistics and by 14 CNAs for livestock statistics. The most usual imputation method is to take data for the same statistical unit from the previous data collection. A small number of CNAs use donor imputation or take data from other surveys or registers.
  • On eggs for hatching and chicks, no information is available about data validation performed by the Member States before data submission to Eurostat.

2. Validation rules agreed with Member States

The validation implemented by eWF in “real time”, as the user types the data, is known as “pre-validation” in the domain. There are two severity classes of validation rules:

Basic rule: a validation rule, which can be broken. However the CNA is required to provide a justification within the form for the violation of the rule;

Critical rule: a validation rule, which must be satisfied. As long as the form contains critical errors the functionality for transmitting the data to Eurostat is disabled.

Pre-validation of animal production statistics
Validation, level 0
It is checked that all mandatory cells contain information (data or flags) and that data types are valid. The only non-numerical value allowed in data cell in this domain is “NA” for cells for which data are not available. Flag “C” indicates confidentiality of the value. The flags that can be inserted in flag cells are pre-defined and available to the user as a drop-down list.
All data cells of all transmitted datasets are mandatory with few exceptions:

  • All data cells for regional data of countries with a single region,
  • Livestock statistics for the regions having fewer than 75 000 bovines, 150 000 pigs, 100 000 sheep or 25 000 goats, if these regions represent 5% or less of the national population of the relevant animals,
  • Data cells regarding optional items (Milk table B).

Validation, level 1
Validation of level 1 includes numerous rules specifying the allowed range of values for data cells and also certain rules for consistency between cells (mainly totals and sums of components).

3. Data validation - detection (Eurostat)

The first processing step is to validate the data and load them in the production system. The input to this process are the datasets received and the output are either the data loaded or validation reports and requests to the CNAs for feedback or revised data.

It is reminded to the reader that during data transmission eWF has performed a type of validation, the so-called “pre-validation” (see Data collection).

Data files are loaded and users can review the available information and the comments made by the CNAs and they can combine data from the available input files and create ad hoc data tables. Automated and non-automated validation is carried out with the tool.

Validation, level 2 - detection of outliers

The automated validation is the detection of outliers in the received data. Time series are created by retrieving data from earlier reference periods. Each current value is considered an outlier when it is outside the interval (Q1 – 1.5*(Q3-Q1), Q3 + 1.5* (Q3-Q1)), where Q1 and Q3 denote the first and third quartiles respectively of the corresponding time series. This validation is applied to all cells of the received datasets. Outliers are not necessarily wrong data.

Validation, level 1 - consistency in the data file

Eurostat may implement additional validation rules to check the consistency of the outliers with current data from the same data file. The following types of additional checks are used:

- Aggregation of items: data items that represent category totals (e.g. total bovine animals) must be equal to the sum of the items representing the different categories, allowing for certain tolerance limits.

- Aggregation of regions: data items that represent regional totals (e.g. totals at country level) must be equal to the sum of items representing the corresponding sub-regions.

- Consistency of totals and partial components: sometimes not all categories corresponding to a particular total are collected (e.g. cows’ milk part of which is obtained from dairy cows’ milk, in Table C). In these cases the data items that represent category totals must be greater than or equal to the sum of the items representing the different categories.

- Sign of the values: all variables should be non-negative. Some variables however regarding milk production in Tables B and C are allowed to receive negative values (e.g. in Table B-Milk production, the variable ‘Input of skimmed milk (USM)’ can be by definition negative in case that the process produces skimmed milk (e.g. cream processing)).

- Consistency by size class: the average size class of milk collected and volume of milk treated or milk production in dairies enterprises is computed by size category and is checked whether it falls in specified ranges.

Validation, level 3 - comparison with other data sets

Eurostat may implement additional validation rules to check the consistency with related datasets. The following types of additional checks are used:

- Correspondence between variables from different data sets: same or similar variables from different datasets are compared (e.g. the quantities of products obtained in Table B-Milk Production should be equal to the ones reported in Table H-Milk Protein Contents).

- Consistency between variables from different data sets: related variables in different tables must be consistent. For example if Quantity of utilized product in Table B-Milk Production is zero (plus tolerance limits) then the Protein content of the same product in Table H-Milk Protein content must be less than 1000 (plus tolerance).

These checks are additional to the consistency checks already implemented in eWF. Since they are not applied to all data items they are not systematic and moreover they are not automated; the user chooses on which items to apply them and which rules to apply, based on intuition.

At the end of this step, validated data are forwarded for subsequent processing and production of EU statistics.

Validation of data compiled by Eurostat, after dissemination

Eurostat presents every year to the ‘Animal Production Statistics’ Working Partyp (WP) tables which summarize the data received from the CNAs since the previous WG meeting (Figure 10 Annex 1). More specifically, the tables present statistics produced on the basis of the received. The CNAs are asked to examine the results for their country. Whereas such validation is not powerful or fast, it is the only exhaustive validation covering efficiently every collected variable. Moreover, it provides Eurostat with the CNAs’ explicit approval of the results, which is stronger than an implicit non-rejection.

4. Data validation - correction (Eurostat)

Depending on the results of validation Eurostat may decide to reject the dataset (which is quite rare) or to request feedback from the CNA postponing loading in the production system. In either case it prepares an email to the registered data provider with a report of the validation findings.  

Validation of data compiled by Eurostat, after dissemination

The CNAs are asked to examine the disseminated results for their country and either to confirm that they are correct or to provide remarks and / or revised data if they identify errors.

18.5. Data compilation
  • Calculation of results for country aggregates (e.g. EU-28, EU-27, etc.)
  • Calculation of annual totals based on monthly values
  • Calculation of item aggregates
  • In table apro_ec_poulm, derived series are calculated from the primary data; from these it is possible to estimate numbers of birds and production (eggs) by applying coefficients.
18.6. Adjustment


19. Comment Top

The current description covers decades of methodology on statistics. It reflects especially the current design of animal production statistics. Usability of the data promotes continuity of the time series, which may downgrade interpretability of the statistics, especially considering the permanent improvement in the statistical production process. Eurostat expects having reached a satisfying trade-off. The data user is nevertheless invited referring to the relevant legislation applicable at the reference date for more accurate analysis involving long time series.

Related metadata Top
apro_mk_esqrs - Milk and milk products

Annexes Top
Annex 1: Handbook on definitions and concepts in animal production statistics
Annex 2: Methodology for animal production statistics
Annex 3: EU summary quality report 2010 (livestock and meat statistics)