Livestock and meat (apro_mt)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: DS (Statistics Denmark)


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

DS (Statistics Denmark)
1.2. Contact organisation unit

Food Industries, Business Statistics
1.5. Contact mail address

Sejroegade 11, DK 2100 Copenhagen


2. Statistical presentation Top
2.1. Data description

The livestock and meat statistics are collected under Regulation (EC) No 1165/2008 since 2009. They cover slaughtering in slaughterhouses (monthly) and other slaughtering (annual), GIP (gross indigenous production) forecast (semi-annual or quarterly data), and livestock statistics (once or twice a year), including regional statistics (annual).This template lists the questions constituting the quality report required in Article 17 of EU Regulation N°1165/2008 on livestock and meat statistics.
This quality report covers the year 2019 and all the quality indicators already reported for years 2010, 2013 and 2016.
2.2. Classification system

Not requested for reference year 2019.
2.3. Coverage - sector

Not requested for reference year 2019.
2.4. Statistical concepts and definitions

Not requested for reference year 2019.
2.5. Statistical unit

Not requested for reference year 2019.
2.6. Statistical population

Not requested for reference year 2019.
2.7. Reference area

Not requested for reference year 2019.
2.8. Coverage - Time

Not requested for reference year 2019.
2.9. Base period

Not requested for reference year 2019.


3. Statistical processing Top
3.1. Source data

 

 

 
3.2. Frequency of data collection

See item 3.2.1.
3.2.1. Reference date of the statistics

Reference date of the statistics

Livestock statistics Bovines animal Pigs Sheep Goats
November/December

31/12 2019

01/01 2020

    
November/ December - Regional

31/12 2019

01/01 2020

    
May/June

30/6 2019

01/07 2019

  
3.3. Data collection

See item 3.3.1.
3.3.1. Production of estimates

Information requested in the metadata files on statistical processes.
3.3.1.1. Process for GIP forecast

Is the following information taken into account to produce the GIP forecast?

  Bovines Pigs Sheep and Goats
No forecast required for sheep and goats    
Extrapolation of known results on slaughtering
Expert assessment of the market
Expert assessment of the GIP by internal expert by external expert
by internal expert
Models Recent changes in the stocks (livestock for fattening) for the forecast for the short term
Recent changes in stocks (breeding animals) for the forecast for the longer term		 Recent changes in the stocks (livestock for fattening) for the forecast for the short term
Recent changes in stocks (breeding animals) for the forecast for the longer term
Other
Other slaughtering covered by the GIP forecast


Additional comments (on the GIP forecast)

Other slaughtering is negligible for both cattle and pigs
3.3.1.2. Process for estimate of other slaughtering

What significant source do you use to estimate other slaughtering?

 

Bovines

Pigs

 Sheep and Goats
Administrative information from veterinary service
Farm Survey
Consumer Survey
Coefficients based on ad hoc study
Year of calculation (Coefficients based on ad hoc study)

2015

2015
Discrepancy between slaughtering and estimated GIP (For instance, if overall GIP is directly estimated based on data at farm level)
Comprehensive study
Year of calculation (Comprehensive study)


Additional comments (on other slaughtering)

The other slaughtering of livestock in Denmark is negligible, but in connection with rebacering every five years, the data is reviewed.
3.4. Data validation

Not requested for reference year 2019.
3.5. Data compilation

Not requested for reference year 2019.
3.6. Adjustment

Not requested for reference year 2019.


4. Quality management Top
4.1. Quality assurance

Not requested for reference year 2019.
4.2. Quality management - assessment

Not requested for reference year 2019.


5. Relevance Top
5.1. Relevance - User Needs

The statistics are of great interest to EU, the Ministry og Environment and Food, The Danish Association of Slaughterhouses and others farmer´s organizations, but also students and interested people in general.
5.1.1. Main national users of the statistics on livestock and meat

The data produced under Regulation (EC) No 1165/2008 are used by the following users, in addition to being delivered to Eurostat:

  National accounts (National Accounts, including European Accounts of Agriculture) Supply balance sheets Gross nutrient balance
Main national users Livestock - Bovines
Livestock - Pigs
Livestock - Sheep and goats
Slaughtering - Bovines
Slaughtering - Pigs
Slaughtering - Sheep and goats
Slaughtering - Poultry
GIP forecast - Bovines
GIP forecast - Pigs
Other slaughtering		 Slaughtering - Bovines
Slaughtering - Pigs
Slaughtering - Sheep and goats
Slaughtering - Poultry
Other slaughtering		 Livestock - Bovines
Livestock - Pigs
5.1.2. Other Main national users of the statistics on livestock and meat

Other Main national users of the statistics on livestock and meat, please specify:

Livestock

Bovines

Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Pigs

Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Sheep and goats

 

Slaughtering

Bovines

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Pigs

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Sheep and goats

 Danish Agriculture & Food Council,which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Poultry

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

GIP forecast

Bovines

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Pigs

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations.

Sheep and goats

 

Other slaughtering

 Danish Agriculture & Food Council, which represents the farming and food industry of Denmark including businesses, trade and farmer's associations
5.1.3. Main international users of the statistics on livestock and meat

Does the department in charge of livestock and meat statistics provide data to the following international organisations at their request?

DG Agriculture and Rural Development YES
Other EU institutions YES
FAO YES
Other international ‘governmental’ organisation YES
5.2. Relevance - User Satisfaction

See item 5.2.1.
5.2.1. User satisfaction survey

User satisfaction survey

  Answer
Have you already carried out a survey on user satisfaction?
If yes, how long ago (months)?
If yes, are the results available to the public?
5.3. Completeness

Not requested for reference year 2019.
5.3.1. Data completeness - rate

Not requested for reference year 2019.


6. Accuracy and reliability Top
6.1. Accuracy - overall

See items 6.1.1. and 6.1.2.
6.1.1. Thresholds and legal derogation

Thresholds and legal derogation (Article 4 of regulation N°1165/2008)

Livestock statistics Total number of animals if under the legal threshold in December 2019 (Number of Head)
Bovine animals (under 1.5 million head)  
Pigs (under 3 million head)  
Sheep (under 500 000 head)

138.007 (the number on the 20 November 2019 according to The Central Husbandry Register (CHR)).
Goats (under 500 000 head)

18.800 (the number on the 20 November 2019 according to The Central Husbandry Register (CHR)).
6.1.2. Quality control survey

Quality control survey

Quality control survey (livestock statistics)
Quality control survey (meat statistics)
6.2. Sampling error

See items 6.2.1.1. and 6.2.1.2.
6.2.1. Sampling error - indicators

Information requested in the metadata files on statistical processes.
6.2.1.1. Coefficient of variation achieved for the main variables (only for sample survey)

Coefficient of variation achieved for the main variables (only for sample survey)

 Livestock statistics  Bovine animals  Pigs  Sheep  Goats
 Livestock - Nov./Dec. (in %)  

0.4

    
 Livestock - Nov./Dec. Regional (in %)  

From 1.3 to 7.2 dependt on region.

    
 Livestock - May/June (in %)  

0.4

   
 Assessment method  

SAS, Clan

    
 Further comment

For the cattle survey are used administrative data (registers).

The stock of cattle is estimated on the basis on data from the Central Register of Livestock (an administrative register). The Central Register of Livestock is maintained by the Ministry of Food, Agriculture and Fishery and the Cattle Database is maintained by the Agricultural Advisory Centre and the Danish Association of Cattle Breeders. 

 

      

 

 Slaughtering statistics  Bovine animals  Pigs  Sheep  Goats  Poultry
 Slaughtering statistics (in %)          
 Assessment method          
 Further comment

Using administrative registers.

Using administrative registers.

Using administrative registers.

  

Using administrative registers.
6.2.1.2. Sampling rate

Sampling rate

  Non-relevant * 1. Frame (Number of units) 2. Sample size (Number of units) Sampling rate ((2/1) x 100%)
Slaughterhouses
Cattle farms
Pig farms

3059 farms with pigs (1. Januar 2020)

1852

61
Sheep farms
Goat farms
Animal farms **


* If the main information is drawn from a census, a register or a source other than a survey, the first column is ticked ** Animal farms: if the survey is designed for all livestock together
6.3. Non-sampling error

See item 6.3.2.1.
6.3.1. Coverage error

Information requested in the metadata files on statistical processes.
6.3.1.1. Over-coverage - rate

Information requested in the metadata files on statistical processes.
6.3.1.2. Common units - proportion

Not requested for reference year 2019.
6.3.1.3. Coverage error for each process

Information requested in the metadata files on statistical processes.
6.3.2. Measurement error

Information requested in the metadata files on statistical processes.
6.3.2.1. Checklist on measurement errors

Whereas coherence refers to the data disseminated, the measurement errors refer to the data collection.

Slaughtering:

Young cattle and calves recorded separately
Goats actually recorded
Carcass weight recorded fully compliant (Compliant with Regulation (EC) No 1165/2008)
Even for poultry
Poultry slaughtering recorded in tonnes and head
6.3.3. Non response error

Information requested in the metadata files on statistical processes.
6.3.3.1. Unit non-response - rate

Information requested in the metadata files on statistical processes.
6.3.3.2. Item non-response - rate

Information requested in the metadata files on statistical processes.
6.3.4. Processing error

Information requested in the metadata files on statistical processes.
6.3.4.1. Imputation - rate

Information requested in the metadata files on statistical processes.
6.3.5. Model assumption error

Not requested for reference year 2019.
6.4. Seasonal adjustment

Not requested for reference year 2019.
6.5. Data revision - policy

Information requested in the metadata files on statistical processes.
6.6. Data revision - practice

Not requested for reference year 2019.
6.6.1. Data revision - average size

Not requested for reference year 2019.


7. Timeliness and punctuality Top
7.1. Timeliness

Information requested in the metadata files on statistical processes.
7.1.1. Time lag - first result

Information requested in the metadata files on statistical processes.
7.1.2. Time lag - final result

Information requested in the metadata files on statistical processes.
7.2. Punctuality

Normally are these statistics published without delay, reference to the announced time of publication in the release calendar.

 
7.2.1. Punctuality - delivery and publication

Information requested in the metadata files on statistical processes.


8. Coherence and comparability Top
8.1. Comparability - geographical

See items 8.1.2 to 8.1.15.
8.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested for reference year 2019.
8.1.2. Comparability – geographical Calves

Is there any difference between the above referred definitions based on the animals age and/or intended use with the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition

'There are no information about which cattle is destined to used for slaughtering, as the population of cattle is estimated on the basis on administrative register.


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 Yes

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 Calves and young cattle for slaughter is estimatet as 60,000 heifers + (("Bulls and bullocks under ½ -1 year" + "Bulls and bullocks ½-1 year")) - 6.000 Male). 60.000 heifers are expected to be slaughter before they are 1 year. 6.000 Male is the expected breeding bulls.

Frequency of the revision of the values

Please specify the last time that this value was updated?

 31. December 2018

Main source used

Please define the data source used for the data

 'The Central Register of Livestock (an administrative register), which is maintained by the Ministry og Food, Agriculture and Fishery and the Cattle Database is maintained by the Agricultural Advisory Centre and the Danish Association of Cattle Breeders and the Slaughtering statistics.

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.3. Comparability – geographical Bulls

Is there any difference between the above referred definitions based on the castration status of the animals and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition?(Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.4. Comparability – geographical Buffaloes

Is there any difference between the accounting of buffaloes in the different age bovine animal categories and the above referred classes?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.5. Comparability – geographical Cows

Is there any difference between the above referred definitions based on the animals age and/or purpose and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.6. Comparability – geographical Heifers

Is there any difference between the above referred definitions based on the age and/or the intended use and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition

'There are no information about which cattle is destined to used for slaughtering, as the population of cattle is estimated on the basis on administrative register.


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 'Heifers is "Heifers 2 years and over". Heifters for slaughter is estimated as 20,000 heifters. Other Heifers is Heifers 2 years and over - 20,000 heifters. This is estimatie on the basis of the meat statistic 2011 and 2012 together with external expert support. 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 2013

Main source used

Please define the data source used for the data

 'The Central Register of Livestock (an administrative register), which is maintained by the Ministry og Food, Agriculture and Fishery and the Cattle Database is maintained by the Agricultural Advisory Centre and the Danish Association of Cattle Breeders and the Slaughtering statistics.

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.7. Comparability – geographical Lambs

Is there any difference between the above referred definitions based on the age and/or the purpose and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition

'Lambs (Slaughtering statistics) is define as Male or female under 18 months old.


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 'Not relevant for Denmark
8.1.8. Comparability – geographical Goats

Is there any difference between the above referred definitions based on the animals status and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 'Administrative information about slaughtering at slaughterhouses from the Ministry of Food, Agriculture and Fisheries is used. Here is the age under 18 months old.

Any further comments, please provide them here

 
8.1.9. Comparability – geographical Piglets

Is there any difference between the above referred definitions based on the weight and the one used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition

'In the Danish questionnaire for the pig survey there are ask for the number of pigs in the following categories of pigs:" Piglets" and "Weaners under 50 kilo". To meet the categorie in the EU legislation there is done some estimation before sending data to EUROSTAT: "piglets" + 1/3 of "Weaners under 50 kilo".


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 'To meet the categorie in the EU legislation there is done some estimation before sending data to EUROSTAT: "piglets" + 1/3 of "Weaners under 50 kilo".

Frequency of the revision of the values

Please specify the last time that this value was updated?

 'Before 2005

Main source used

Please define the data source used for the data

 'The survey

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.10. Comparability – geographical Sows

Is there any difference between the above referred definitions based on the covered status of the animals and the ones used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.11. Comparability – geographical Slaughter units

Is there any difference between the above referred definitions based on the units provided by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.12. Comparability – geographical Carcasses

Is there any difference between the above referred definitions based on the animals carcass weight and the ones used by respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.13. Comparability – geographical Carcasses poultry

Is there any difference between the above referred definition and the one used by respondents in your Member State?


If yes, please describe briefly the difference in the definition

'There is used "70%" chicken (grill chichen).


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 'The number of slaughtering chicken is from administrativ information from veterinary service.The weight of the chicken is from adminstrativ farmregister, which almost all chickenfarmer has to used.

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

Data from slaughterhouses from administrativ veterinayr servide can mabey be used from 2021, however this needs to be investigated.

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.14. Comparability – geographical Slaughterhouse

Is there any difference between the above referred definition and the one used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.1.15. Comparability – geographical Gross indigenous production

Is there any difference between the above referred definition and the one used by the respondents in your Member State?


If yes, please describe briefly the difference in the definition


Geographical correction

Do you apply correction of your data in order to meet the EU definition? (Yes/No)

 

IF YES correction of your data is applied in order to meet the EU definition?

Value /Method of calculation

Briefly describe the value of the correction or of the coefficient?

 

Frequency of the revision of the values

Please specify the last time that this value was updated?

 

Main source used

Please define the data source used for the data

 

IF NO, correction of your data is not applied in order to meet the EU definition?

Is a standard operation procedure (SOP) envisaged to solve the above-mentioned differences?

Briefly describe if a correction will be implemented and if so when?

 

SOP to correct the differences is not envisaged

Please explain the reasons

 

Any further comments, please provide them here

 
8.2. Comparability - over time

See item 8.2.2.
8.2.1. Length of comparable time series

Not requested for reference year 2019. 
8.2.2. First year of availability of comparable data

First year when the statistics were produced with comparable figures for all, most or only the main variables (e.g. total numbers of animals):

 

All

Most

Main variables

Number of periods per year*

Livestock

 

 

Bovines

  2010

 2000

 1900

  4

Pigs

 2000

 1974

 1915

  4

Sheep and goats

  

 

 

  

Slaughtering

 

 

 

Bovines

  1945

1930érne

 1900  12

Pigs

  1945

1930érne 

 1900

  12

Sheep and goats

  1945

1930érne 

 1900

  12

Poultry

 1945

1930érne 

 1900  12

* Number of periods per year: according to the frequency of statistics, i.e. 12 for monthly data, 4 for quarterly data, 1 for annual data, etc.
8.3. Coherence - cross domain

Information requested in the metadata files on statistical processes.
8.4. Coherence - sub annual and annual statistics

Not requested for reference year 2019.
8.5. Coherence - National Accounts

Not requested for reference year 2019.
8.6. Coherence - internal

Information requested in the metadata files on statistical processes.


9. Accessibility and clarity Top
9.1. Dissemination format - News release

Not requested for reference year 2019.
9.2. Dissemination format - Publications

Information requested in the metadata files on statistical processes.
9.3. Dissemination format - online database

Information requested in the metadata files on statistical processes.
9.3.1. Data tables - consultations

Information requested in the metadata files on statistical processes.
9.4. Dissemination format - microdata access

Information requested in the metadata files on statistical processes.
9.5. Dissemination format - other

Information requested in the metadata files on statistical processes.
9.6. Documentation on methodology

Information requested in the metadata files on statistical processes.
9.7. Quality management - documentation

Information requested in the metadata files on statistical processes.
9.7.1. Metadata completeness - rate

Not requested for reference year 2019.
9.7.2. Metadata - consultations

Information requested in the metadata files on statistical processes.


10. Cost and Burden Top

See item 10.1.
10.1. Burden on the respondents

Estimated burden on the respondents (in hours and minutes) to statistical surveys on livestock and meat (administrative sources are excluded)

Label statistical survey The number of respondents (average) The average time spent by the respondents to provide information (in minutes) The number of occurrences of the statistical survey over the reference year The overall yearly burden on the respondents - TOTAL (in minutes)

Sample survey on pigs

1800

17

2

61200
         
         
         
         
         
         
         
         
         


11. Confidentiality Top
11.1. Confidentiality - policy

Information requested in the metadata files on statistical processes.
11.2. Confidentiality - data treatment

Information requested in the metadata files on statistical processes.


12. Comment Top


Related metadata Top


Annexes Top
SP1 : Sample survey on pigs
SP2 : Bovine register
SP3 : GIP pigs
SP4 : GIP cattle
SP5 : Slaughtering and other slaughtering