Livestock and meat (apro_mt)

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

Compiling agency: Statistical Office of the Republic of Serbia (SORS)


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

Statistical Office of the Republic of Serbia (SORS)
1.2. Contact organisation unit

Agriculture and Forestry Division - Unit for livestock and fishery statistics
1.5. Contact mail address

5 Milana Rakica, Belgrade


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.

Survey on agriculture production - animal production (SP1) is the main survey for providing data on livestock number (cattle, pigs, sheep, goats and poultry) as on 1 December and also basis for providing data on  GIP meat forecast,  slaughter out of slaughterhouses in monthly and annual periodicity, production of milk, eggs-total, eggs for consumption, wool and honey as well as data on use of milk on the holdings and production of milk products. Although the number of pigs in the Republic of Serbia is no longer 3 million or more, SORS continued to provide number of pigs in a semi-annual periodicity by conducting the May/June Survey on the number of pigs (SP2) as on 23 May, as well as forecast of GIP of pig meat based on these results.

This quality report covers the year 2019 and all the quality indicators already reported for year 2016 on the statistical processes used to meet the Regulation (EC) No 1165/2008.The deadline for submission is on 1 July 2020.
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 applicable.


3. Statistical processing Top
3.1. Source data

Information requested in the metadata files on statistical processes.
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

01/12

01/12

01/12

01/12
November/ December - Regional

01/12

01/12

01/12

01/12
May/June

 

 23/5

  
3.3. Data collection

See item 3.3.1.
3.3.1. Production of estimates

See items 3.3.1.1 and 3.3.1.2.
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
Models
Other
Other slaughtering covered by the GIP forecast


Additional comments (on the GIP forecast)

GIP forecast is providing by applying the calculated coefficient to the latest number of a certain category of livestock species (for cattle: calves and young catlle, cows, heifers, bulls and bullock; for pigs: pigs with a live weight of less than 20kg, pigs with a live weight of 20kg or more but less than 50kg, pigs with a live weight of 50kg and over; for sheep: lambs and other sheep). Coefficient is calculated for each category as the ratio of realized gross domestic production and the number of a certain category in previous years (three-year average).

The forecast is provided for the required categories in the appropriate periodicals, in accordance with Regulation (EC) No 1165/2008.
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)
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)

Estimation of monthly slaughtering  out of slaughterhouses is provided as the difference between three-year average of total slaughtering  and slaughtering  in slaughterhouses, for the certain category, in the reference month. 

Structure of slaughtering out of slaughterhouses by months and categories is obtained by regular annual  Survey on agriculture production-animal production and implemented on total slaughtering out of slaughterhouses. Monthly data on slaughtering in slaughterhouses are provided from administrative  source - record of Ministry of Agriculture, Forestry and Water Management (MoA), Veterinary administration.

 
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

See items 5.1.1, 5.1.2 and 5.1.3.
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		 Slaughtering - Bovines
Slaughtering - Pigs
Slaughtering - Sheep and goats		 Livestock - Bovines
Livestock - Pigs
Livestock - Sheep and goats
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

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Pigs

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Sheep and goats

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Slaughtering

Bovines

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Pigs

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Sheep and goats

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Poultry

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

GIP forecast

Bovines

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Pigs

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Sheep and goats

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals

Other slaughtering

 The main data users are MoA and other ministries, the Chamber of Commerce, other institutions and individuals
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)?

9 months

Note: The User Satisfaction Survey is conducted every two years (last conducted in 2019) and refers to the users of all data and services provided by the SORS.
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)  898178
Pigs (under 3 million head)  2903007
Sheep (under 500 000 head)  
Goats (under 500 000 head)  191280
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

See items 6.2.1.1. and 6.2.1.2.
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 %)

2.98

2.66

3.5

6.73
 Livestock - Nov./Dec. Regional (in %)

RS11-11.89
RS12-5.02
RS21-4.80
RS22-6.04

RS11-11.33
RS12-4.47
RS21-4.40
RS22-5.04

RS11-17.17
RS12-9.39
RS21-4.51
RS22-7.00

RS11-31.46
RS12-12.26
RS21-12.12
RS22-10.41
 Livestock - May/June (in %)

 

3.18

   
 Assessment method For calculating estimates and standard errors Swedish ETOS based on software SAS was used For calculating estimates and standard errors Swedish ETOS based on software SAS was used For calculating estimates and standard errors Swedish ETOS based on software SAS was used For calculating estimates and standard errors Swedish ETOS based on software SAS was used 
 Further comment

Without data for RS23 (Region Kosovo i Metohija)

 Without data for RS23 (Region Kosovo i Metohija) Without data for RS23 (Region Kosovo i Metohija) Without data for RS23 (Region Kosovo i Metohija)

 

 Slaughtering statistics  Bovine animals  Pigs  Sheep  Goats  Poultry
 Slaughtering statistics (in %)

 

 

 

 

 
 Assessment method

 

 

        
 Further comment

 

Total slaughtering of livestock is a value estimated on the basis of annual calculations with the use of the available data on balance of live animals:

1. Animal heads at the beginning of year (number and weight, estimation based on results of the Farm Structure Survey 2018 and other available sources)

2. Livestock born (number, calculated by applying coefficients for EAA purposes: 0.80 calving per cow)

3. Import (number and weight, Customs Administration)

4. Export (number and weight, Customs Administration)

5. Total slaughtering (number and weight, estimated on the basis of the balance of live animals)

6. Perished (number, Survey on agriculture production – animal production, 2019) 

7. Animal heads at the end of year (number and weight, Survey on agriculture production – animal production, 2019).

The difference between total slaughtering and slaughtering in slaughterhouses represents slaughtering out of slaughterhouses.

 

  

Total slaughtering of livestock is a value estimated on the basis of annual calculations with the use of the available data on balance of live animals:

1. Animal heads at the beginning of year (number and weight, estimation based on results of the Farm Structure Survey 2018 and other available sources)

2. Livestock born (number, calculated by applying coefficients for EAA purposes: 16.38 piglets per sow)

3. Import (number and weight, Customs Administration)

4. Export (number and weight, Customs Administration)

5. Total slaughtering (number and weight, estimated on the basis of the balance of live animals)

6. Perished (number, Survey on agriculture production – animal production, 2019) 

7. Animal heads at the end of year (number and weight, Survey on agriculture production – animal production, 2019).

The difference between total slaughtering and slaughtering in slaughterhouses represents slaughtering out of slaughterhouses.

 

  

Total slaughtering of livestock is a value estimated on the basis of annual calculations with the use of the available data on balance of live animals:

1. Animal heads at the beginning of year (number and weight, estimation based on results of the Farm Structure Survey 2018 and other available sources)

2. Livestock born (number, calculated by applying coefficients for EAA purposes: 1.30 lambs per breeding sheep)

3. Import (number and weight, Customs Administration)

4. Export (number and weight, Customs Administration)

5. Total slaughtering (number and weight, estimated on the basis of the balance of live animals)

6. Perished (number, Survey on agriculture production – animal production, 2019) 

7. Animal heads at the end of year (number and weight, Survey on agriculture production – animal production, 2019).

The difference between total slaughtering and slaughtering in slaughterhouses represents slaughtering out of slaughterhouses.

 

  

Total slaughtering of livestock is a value estimated on the basis of annual calculations with the use of the available data on balance of live animals:

1. Animal heads at the beginning of year (number and weight, estimation based on results of the Farm Structure Survey 2018 and other available sources)

2. Livestock born (number, calculated by applying coefficients for EAA purposes: 1.90 kids per breeding goat)

3. Import (number and weight, Customs Administration)

4. Export (number and weight, Customs Administration)

5. Total slaughtering (number and weight, estimated on the basis of the balance of live animals)

6. Perished (number, Survey on agriculture production – animal production, 2019) 

7. Animal heads at the end of year (number and weight, Survey on agriculture production – animal production, 2019).

The difference between total slaughtering and slaughtering in slaughterhouses represents slaughtering out of slaughterhouses.

 

  

Total slaughtering of livestock is a value estimated on the basis of annual calculations with the use of the available data on balance of live animals:

1. Animal heads at the beginning of year (estimation based on results of the Farm Structure Survey 2018 and other available sources)

2. Livestock born (estimated number on the basis of results of Survey on agriculture production – Animal production, 2019 and annual data on activity of hatcheries)

3. Import (number and weight, Customs Administration)

4. Export (number and weight, Customs Administration)

5. Total slaughtering (number and weight, estimated on the basis of the balance of live animals)

6. Perished (number, Survey on agriculture production – animal production, 2019) 

7. Animal heads at the end of year (number and weight, Survey on agriculture production – animal production, 2019).

The difference between total slaughtering and slaughtering in slaughterhouses represents slaughtering out of slaughterhouses.

 
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

164151

4595

2.80
Pig farms

336375

7850

2.33
Sheep farms

145234

3277

2.57
Goat farms

56129

1329

2.37
Animal farms **

474351

11152

2.35


* 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

See item 6.3.2.1.
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

Information requested in the metadata files on statistical processes.
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


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

 
8.1.3. 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


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

 
8.1.7. 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


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

 
8.1.8. 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

 

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


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

 
8.1.10. 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

According to the national classification (NC),   female heads that have farrowed or are covered but not for first time (sows, NC)  and female heads that have been set aside for breeding but have not yet farrowed or are covered for the first time (gilts, NC) are observed separatly in the frame of  female breeding heads weighing 50 kg or more (sows, EU). Although there is a slight difference in definition, data for national needs can be easily transformed into data for the categories listed in Annex II Regulation (EC) No 1165/2008 for the purpose of data transmission to Eurostat.


Geographical correction

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

 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?

Data according to the national clasification are transformed as follows: covered sows + gilts covered for the first time = covered sows (EU); gilts covered for the first time = covered sows for the first time (EU); sows - covered sows +gilts - gilts covered for the first time = other sows (EU); gilts – gilts covered for the first time = gilts not yet covered (EU).

This calculation is applied before data transmission to Eurostat.

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

Regarding carcasses poultry, according to national definition  liver, gizzard, neck, feet and head are included as edible parts. This is the only difference in relation to the EU definition of the term “carcass”; therefore for the purpose of data envisaged to be sent to Eurostat, net weight is recalculated as “65% chicken”.


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?

The correction is performed by applying a coefficient 0.65 to the gross weight of slaughtered poultry.  

Frequency of the revision of the values

Please specify the last time that this value was updated?

The correction is carried out in monthly periodicity, before  transmission of data on slaughtering in slaughterhouses to Eurostat. Having in mind the reference year of this report, the last correction was made on the day of sending these data for December 2019 to Eurostat (27 January 2020).

Main source used

Please define the data source used for the data

 Record of MoA on slaughtering in slaughterhouses (administrative source)

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

 
8.1.14. 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

  2006

 2004

 1947

  1

Pigs

  2006

 2004

 1947

  2

Sheep and goats

  2006

 2004

 1947

  1

Slaughtering

 

 

 

Bovines

  2011  2008

 1952

  12

Pigs

  2008  1952

 

  12

Sheep and goats

  2008  1952

 

  12

Poultry

  2008

 

 1991

  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)

SP1 (Survey on agriculture production - animal production, 2019)

  9142  20  1 182840

SP2 (Survey on the number of pigs, 2019)

  4747  5  1 23735


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

No comment


Related metadata Top


Annexes Top
SP1:Survey on agriculture production – animal production (December survey on livestock number for all types of animal)
SP2: Survey on the number of pigs (May/June sample survey)
SP3:Slaughtering in slaughterhouses (administrative source, record of the MoA - Veterinary Administration)