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)

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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