Livestock and meat (apro_mt)

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

Compiling agency: MAA (Ministère de l'Agriculture et de l'Alimentation) Service de la Statisique et de la Prospective


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

MAA (Ministère de l'Agriculture et de l'Alimentation) Service de la Statisique et de la Prospective
1.2. Contact organisation unit

SSP/SDSAFA - Complexe d'enseignement agricole SDSAFA
1.5. Contact mail address

sdsafa.ssp.sg@agriculture.gouv.fr


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 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

31/12

01/11

01/11

01/11
November/ December - Regional

31/12

01/11

01/11

01/11
May/June

01/05

01/05

  
3.3. Data collection

See item 3.3.1.



Annexes:
questionnaire for pigs, sheeps and goats livestocks statistics
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 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
Production models (e.g. cycle of pig market)		 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
Production models (e.g. cycle of pig market)		 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
Production models (e.g. cycle of pig market)
Other
Other slaughtering covered by the GIP forecast


Additional comments (on the GIP forecast)

GIP bovines, sheep and goats forecast: We use a demographic model. With the numbers of each category of animals from livestock statistics of November and May, past years slaughtering and the trade data, we estimate the possible destination of each group of animals : livestock or slaughter. GIP pig forecast : We use a demographic model. We start with the number of pigs in thousands of heads observed with the may or november survey and we make them live and then die after having procreate or fatten during the year.
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)

Slaughterings performed outside slaughterhouses are no longer allowed in France.

That's why we no longer calculate estimations for that kind of slaughterings.
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 Slaughtering - Bovines
Slaughtering - Pigs
Slaughtering - Sheep and goats		 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

 Technical institutes, Professional organizations, students, 

Pigs

 Technical institutes, Professional organizations, students, 

Sheep and goats

 Technical institutes, Professional organizations, students, 

Slaughtering

Bovines

  Insee, Technical institutes, Professional organizations, students,..

PigsInsee, Technical institutes, Professional organizations, students,..

 Insee, Technical institutes, Professional organizations, students,..

Sheep and goats

 Insee, Technical institutes, Professional organizations, students,..

Poultry

  Insee, Technical institutes, Professional organizations, students,..

GIP forecast

Bovines

 Technical institutes, Professional organizations, 

Pigs

  Technical institutes, Professional organizations, 

Sheep and goats

  Technical institutes, Professional organizations, 

Other slaughtering

 
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 NO
Other EU institutions NO
FAO NO
Other international ‘governmental’ organisation NO
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)

Poultry monthly slaughterings

Legal threshold (tonne per year)

Chicken

600

Turkey

1000

Guinea fowl

100

Ducks

200

Goose

10

Rabbit

80

Pigeon

10

Quail

80

 

Livestock statistics Total number of animals if under the legal threshold in December 2015 (Number of Head)
Bovine animals (under 1.5 million head)  
Pigs (under 3 million head)  
Sheep (under 500 000 head)  
Goats (under 500 000 head)

 
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 %)

Livestock Bovine is drawn from a register.

There is no estimate

1,9

1,48

1,31
 Livestock - Nov./Dec. Regional (in %)

Idem

0,74 to 17,03

3,08 to 12,78

2,53 to 21,24
 Livestock - May/June (in %)

idem

 1,54

   
 Assessment method

idem

avec 

V2 : estimated variance
Pi_i : inclusion probability of farm i in the sample
Pi_j : inclusion probability of farm j in the sample
Pi_ij : inclusion probability of farms i and j together in the sample
y_i : variable total for farm i (for example number of pigs, goats...)
y_j : variable total for farm j (for example number of pigs, goats...) 

idem pigs

idem pigs
 Further comment

 SP6 : Data for May and December came from an administrative source, the Bdni.

Livestocks statistics are census data

SP3 : Sample survey for may and november data collection on pigs in France

The sampling designs for may and november statistics are two independant rotating panels. Each year, a fifth of each sample is renewed. The five first panels have been sampled in mai 2015 and in november 2015. Around 2,000 farms out of 12,000 farms are surveyed for  pig statistics of May. Around 3,800 farms out of 15,000 farms are surveyed for pig statistics of November.

SP4 : Sample survey for november data collection on sheeps in France

The sampling design is a rotating panel. Each year, a fifth of the sample is renewed. The five first panels have been sampled in november 2018.  Around 4,500 farms out of the 40,000 farms in the statistical universe are surveyed

SP5 : Sample survey for november data collection on goats in France

We use a stratified random sample design. About 2,100 farms out of the 8,500 farms in the statistical world are surveyed.

 

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

0

0

0

0

0
 Assessment method          
 Further comment

Slaughtering statistics are census data

Slaughtering statistics are census data

Slaughtering statistics are census data

Slaughtering statistics are census data

Slaughtering statistics are census data
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

166 000
Pig farms 29511 5896 21
Sheep farms

57997 units with lots of units below 10 sheep

4500

7.8
Goat farms

16052 units but with lots of units below 10 goats

2100

 20.4
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

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.

Non response rate : Bovines : 0 %

                              Pigs : 3 %

                              Sheep : 3 %

                              Goats : 3 %         

                              Poultry : 5 %
6.3.3.2. Item non-response - rate

Information requested in the metadata files on statistical processes.

 

Non response rate : Bovines : 0 %

                              Pigs : 1 %

                              Sheep : 1 %

                              Goats : 1 %         

                              Poultry : 3 %
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.

There is no imputation for monthly slaughterings surveys

 
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.

 

 

Data are revised each month from the beginning of the current year since late answers to monthly surveys are integrated.

 

 
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.

Bovines, pigs, sheep and goats : 20 of each month

Poultry : 25 of each month

 
7.1.2. Time lag - final result

Information requested in the metadata files on statistical processes.

There is no distinction between first and final results

 
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


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


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

 
8.1.14. 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

  2001

 2001

 1973

  2

Pigs

  2001

 2001

 1973

  2

Sheep and goats

  2001

 2001

 1973

  1

Slaughtering

 

 

 

Bovines

  2009  2000

 1975

  12

Pigs

  2009  2000

 1975

  12

Sheep and goats

  2009  2000

 1975

  12

Poultry

  2009

 2001

 1994

  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.

 

Slaughterings data are published each month on line : https://agreste.agriculture.gouv.fr/agreste-web/

 
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.

The ministry of Agriculture's department in charge of meats as well as regional statistical services receive individual slaughterings data every month.  

 
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)

Livestock Pigs - Nov

3620

10

1

36 620

Livestock Pigs -May

2466

10

1

24 660

Livestock Sheep Nov

3686

10

 

1

36 860

Livestock Goats Nov

2090

10

1

20 900

 

Monthly Slaugterings in slaughterhouses

375

30

12

135 000
         
         
         
         
         


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
questionnaire for livestocks pigs, sheep and goats surveys
SP1 : Slaughterings (except poultry)
SP2 : Poultry' slaughterings
SP3 : Sample survey for May and November data collection on pigs
SP4 : Sample survey for November data collection on sheeps in France
SP5 : Sample survey on goats in France
SP6 : Use of an exhautive administrative data source (BDNI) for may and december cattle numbers