Crop balance sheets (apro

Crop balance sheets (apro_cbs)

National Reference Metadata in ESS Standard for Crops Balance Sheet Quality Reports Structure (esqrsbs)

Compiling agency: Statistical Office of the Republic of Slovenia.

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

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1.1. Contact organisation

Statistical Office of the Republic of Slovenia.

1.2. Contact organisation unit

Agriculture, Forestry, Fishing and Hunting Statistics Section

1.5. Contact mail address

andraz.habjanic@gov.si

2. Statistical presentation

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2.1. Data description

Main characteristics

2.1.1. Describe shortly the main characteristics of the statistics

Crop Balances are standardized information for a calendar year on supply and demand for specific groups of agricultural products and refer to the country as a whole. Crop Balances for cereals cover supply and use of the main cereals (common wheat & spelt, durum wheat, barley and grain maize & corn-cob-mix) and main oilseeds (rape and turnip rape seeds, sunflower seeds and soya).

Reference period

2.1.2. Reference period of the data collection	2020
2.1.3. Is the reference period based on the calendar year starting January 1st and ending December 31st?	Yes
2.1.4. If No, please specify	/

National legislation

2.1.5. Is there a national legislation covering these statistics?	No
If Yes, please answer all the following questions.
2.1.6. Name of the national legislation	/
2.1.7. Link to the national legislation	/
2.1.8. Responsible organisation for the national legislation	/
2.1.9. Year of entry into force of the national legislation	/
2.1.10. Please indicate which variables required under EU legislation are not covered by national legislation, if any?	/
2.1.11. Please indicate which national definitions differ from those in the EU legislation, if any?	/
2.1.12. Is there a legal obligation for respondents to reply?	No

Additional comments on data description

2.2. Classification system

The classification system is described in the handbook.

2.3. Coverage - sector

Main cereals (common wheat & spelt, durum wheat, barley and grain maize & corn-cob-mix) and oilseeds (rape and turnip rape, sunflower, soya).

2.4. Statistical concepts and definitions

Statistical concepts and definitions are described in the handbook.

2.5. Statistical unit

[CBS] The whole chain from farms to users. (including traders, people in charge of stocks, a.s.o).

2.6. Statistical population

The balance sheets are prepared on the basis of the prescribed set of basic and processed agricultural products. The balance sheets thus cover all units that produce, import, export or consume selected group of agricultural products (basic data sources are statistical surveys of agricultural, industrial and external trade statistics).

2.7. Reference area

2.7.1 Geographical area covered	The entire territory of the country - NUTS0 Slovenia.
2.7.2 Which special Member State territories are included?	No territories outside the NUTS0 Slovenia border.

2.8. Coverage - Time

Calendar year 2020.

2.9. Base period

Not applicable

3. Statistical processing

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3.1. Source data

Data source details

	Crop statistics	Trade statistics	Stock estimates	Domestic use estimates
Census
Sample Survey
Administrive data source	x	x		x
Agro-economic model
Expert Estimates			x	x
Other sources

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.1 of the annexed Excel file
3.1.2 Name/Title	/
3.1.3 Name of Organisation responsible	/
3.1.4 Main scope	/
3.1.5 List used to build the frame	/
3.1.6 Any possible threshold values	/
3.1.7 Population size	/
3.1.8 Additional comments	For detailed data on crop and trade statistics please see the Quality reports for these two statistical domains. No specific (pilot) census has been carried out for the purpose of crop balances' compilation.

Sample Survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.1 of the annexed Excel file
3.1.9 Name/Title	Production of food products (IND-15/M).
3.1.10 Name of Organisation responsible	Statistical Office of the Republic of Slovenia.
3.1.11 Main scope	Business entities (enterprises) engaged in the production of food, beverages and animal feed.
3.1.12 List used to build the frame	IND-15/M is a monthly sample survey that primarily collects data from business entities involved in the production of food, beverages and animal feed (NACE clasiffication activities 10 and 11) and fictitious units (parts of enterprises or units in the composition, which are not registered in the bussiness register but perform activities 10 and 11 according to NACE clasiffication).
3.1.13 Any possible threshold values	Enterprises with a threshold of 20 employees are included in the adress book.
3.1.14 Population size	180 units.
3.1.15 Sample size	180 units.
3.1.16 Sampling basis	Other
3.1.17 If Other, please specify	Cut-off threshold.
3.1.18 Type of sample design	Other
3.1.19 If Other, please specify
3.1.20 If Stratified, number of strata
3.1.21 If Stratified, stratification criteria
3.1.22 If Other, please specify
3.1.23 Additional comments	The sampling unit, the observation unit and the reporting unit are enterprises and units in composition. The observation unit is the same as the sampling unit. In cases where the observed unit reports the data itself, the reporting unit is also the same as the observation unit. For the observed unit, however, another unit (for example, a parent unit or an accounting service) can report data, in this case the reporting unit is enterprise or unit in composition, regardless of the activity it performs. In address book of IND-15/M, most units are such that the sampling unit is the same as the observation unit and it also equals the reporting unit.

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.1
3.1.24 Name/Title	/
3.1.25 Name of Organisation responsible	/
3.1.26 Contact information (email and phone)	/
3.1.27 Main administrative scope	/
3.1.28 Geospatial Coverage
3.1.29 Update frequency
3.1.30 Legal basis	/
3.1.31 Are you able to access directly to the micro data?
3.1.32 Are you able to check the plausibility of the data, namely by contacting directly the units?
3.1.33 How would you assess the proximity of the definitions and concepts (including statistical units) used in the administrative source with those required in the EU regulation?
3.1.34 Please list the main differences between the administrative source and the statistical definitions and concepts	/
3.1.35 Is a different threshold used in the administrative source and statistical data?
3.1.36 If Yes, please specify	/
3.1.37 Additional comments	/

Agro-economic model

If there are different models used, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.38 Name/Title	/
3.1.39 Primary purpose	/
3.1.40 Legal basis	/
3.1.41 Update frequency
3.1.42 Expert data supplier
3.1.43 If Other, please specify	/
3.1.44 How would you assess the quality of those data?
3.1.45 Additional comments	/

Experts

If there is more than one Expert source, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.46 Name/Title	Stock estimates and domestic use estimates.
3.1.47 Primary purpose	For losses validation and for consumption validation.
3.1.48 Legal basis	Not applicable
3.1.49 Update frequency	Less frequent
3.1.50 Expert data supplier	Producer organisation Scientific organisation Other
3.1.51 If Other, please specify	Farmers.
3.1.52 How would you assess the quality of those data?	Good
3.1.53 Additional comments	/

Other sources

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.54 Name/Title	/
3.1.55 Name of Organisation	/
3.1.56 Primary purpose	/
3.1.57 Data type
3.1.58 If Other, please specify	/
3.1.59 How would you assess the quality of those data?
3.1.60 Additional comments	/

Annexes:
Additional sample survey used for balance compilation is explained - Agricultural Institute of Slovenia.

3.2. Frequency of data collection

Monthly (IND-15/M). Other sources annually.

3.3. Data collection

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.3 of the annexed Excel file
3.3.1 Name/Title	/
3.3.2 Methods of data collection
3.3.3 If Other, please specify	/
3.3.4 If face-to-face or telephone interview, which method is used?
3.3.5 Data entry method, if paper questionnaires?
3.3.6 Please annex the questionnaire used (if very long: please provide the hyperlink)	/
3.3.7 Additional comments	/

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.3 of the annexed Excel file
3.3.8 Name/Title	Stock estimates and domestic use estimates.
3.3.9 Methods of data collection	Electronic questionnaire
3.3.10 If Other, please specify	/
3.3.11 If face-to-face or telephone interview, which method is used?
3.3.12 Data entry method, if paper questionnaires?
3.3.13 Please annex the questionnaire used (if very long: please provide the hyperlink)	/
3.3.14 Additional comments	Survey questionnaire via computer.

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.3 of the annexed Excel file
3.3.15 Name/Title	/
3.3.16 Extraction date	/
3.3.17 How easy is it to get access to the data?
3.3.18 Data transfer method	/
3.3.19 Additional comments	/

Experts

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.3 of the annexed Excel file
3.3.20 Name/Title	/
3.3.21 Methods of data collection	/
3.3.22 Additional comments	/

Annexes:
Short questionnaire on stocks and domestic use of oilseeds.

3.4. Data validation

3.4.1 Which kind of data validation measures are in place?	Manual
3.4.2 What do they target?	Other
3.4.3 If Other, please specify	For crop balances, qualitative techniques are used, such as expectations, interviews, data coetc. No quantitative techniques are provided because crop balance is just one result which derives from different data inputs. Therefore, there are no possibilities to compare different results. They target misleading results.

3.5. Data compilation

3.5.1 Describe the data compilation process	The majority of the data collection is done by downloading from the internet (official SURS website). Some data content or estimation data are collected by SURS directly, by request. Agricultural Institute of Slovenia has collected some of the missing data by survey questionnaire on stocks and domestic use of oilseeds and added some expert estimates for selected data categories.
3.5.2 Additional comments	/

3.6. Adjustment

4. Quality management

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Crop balances (main cereals and oilseeds) have been compiled for the first time as pilot data collections for the calendar year 2017. Methodology has been checked, valuated and upgraded in 2018 and 2019, epsecially for the Crop Balance for oilseeds. The management system has not yet been established and used in the organisation.

4.1. Quality assurance

4.1.1 Is there a quality management system used in the organisation?	No
4.1.2 If yes, how is it implemented?	/
4.1.3 Has a peer review been carried out?	No
4.1.4 If Yes, which were the main conclusions?	/
4.1.5 What quality improvements are foreseen?	Improve data validation
4.1.6 If Other, please specify	/
4.1.7 Additional comments	Management system will presumably be established with the completion of grant project, once the Crop balances' methodology will be finalized. Verification of some estimates with sample surveys (share of losses on agricultural holdings) and identification of additional data collection on stocks is presumably to be done in the near future.

4.2. Quality management - assessment

Development since the last quality report

4.2.1 Overall quality	Stable
4.2.2 Relevance	Stable
4.2.3 Accuracy and reliability	Stable
4.2.4 Timeliness and punctuality	Stable
4.2.5 Comparability	Stable
4.2.6 Coherence	Stable
4.2.7 Additional comments	Crop balances have been compiled as pilot data collections in 2017, and verified and methodologically upgraded (Crop Balance for oilseeds) in 2018 and 2019. They represent data improvement but will be further methodologically upgraded in the near future, if improved administrative data sources or estimation methods will be identified.

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5. Relevance

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5.1. Relevance - User Needs

5.1.1 If certain user needs are not met, please specify which and why	/
5.1.2 Please specify any plans to satisfy needs more completely in the future	/
5.1.3 Additional comments	Collected data on main cereals and oilseeds balance sheets will serve as data platform for further agricultural policy decision making and will also provide basis for further detailed experts’ analysis and modeling, definitions of agricultural indicators and international reporting.

5.2. Relevance - User Satisfaction

5.2.1 Has a user satisfaction survey been conducted?	No
If Yes, please answer all the following questions
5.2.2 Year of the user satisfaction survey	/
5.2.3 How satisfied were the users?
5.2.4 Additional comments	/

5.3. Completeness

5.3.1 Data completeness - rate	Crop balances (main cereals and oilseeds) have been compiled for the first time as pilot data collections for the calendar year 2017. Their methodology has been verified and upgraded in 2018 and 2019 (Crop Balance for oilseeds); it will be further upgraded if additional adminstrative data sources and estimation methods will be identified.
5.3.2 If not complete, which characteristics are missing?	/
5.3.3 Additional comments	Crop balances have been compiled as pilot data collections and later methodologically upgraded.

6. Accuracy and reliability

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6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Good
6.1.2 What are the main factors lowering the accuracy?	Other
6.1.3 If Other, please specify	/
6.1.4 Additional comments	Crop balances have been compiled as pilot data collections for 2017 calendar year and further upgraded in 2018 and 2019 (Crop Balance for oilseeds).

6.2. Sampling error

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.2 of the annexed Excel file
6.2.1 Name/Title	/
6.2.2 Methods used to assess the sampling error
6.2.3 If Other, please specify	/
6.2.4 Methods used to derive the extrapolation factor
6.2.5 If Other, please specify	/
6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas	/
6.2.7 Sampling error - indicators	Please provide the coefficients of variation in table 6.2 of the annexed Excel file
6.2.8 Additional comments	/

6.3. Non-sampling error

See sections below.

6.3.1. Coverage error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.1 Name/Title	/
Over-coverage
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope?
6.3.1.3 What methods are used to detect the out-of scope units?	/
6.3.1.4 Does the sample frame include units that do not exist in practice?
6.3.1.5 Over-coverage - rate	/
6.3.1.6 Impact on the data quality	Unknown
Under-coverage
6.3.1.7 Does the sample frame include all units falling within the scope of this survey?
6.3.1.8 If Not, which units are not included?	/
6.3.1.9 How large do you estimate the proportion of those units? (%)	[0-100]
6.3.1.10 Impact on the data quality	Unknown
Misclassification
6.3.1.11 Impact on the data quality	Unknown
Common units
6.3.1.12 Common units - proportion	/
6.3.1.13 Additional comments	/

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.14 Name/Title	/
Over-coverage
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope?
6.3.1.16 What methods are used to detect the out-of scope units?	/
6.3.1.17 Does the sample frame include units that do not exist in practice?
6.3.1.18 Over-coverage - rate	/
6.3.1.19 Impact on the data quality	Unknown
Under-coverage
6.3.1.20 Does the sample frame include all units falling within the scope of this survey?
6.3.1.21 If Not, which units are not included?	/
6.3.1.22 How large do you estimate the proportion of those units? (%)	[0-100]
6.3.1.23 Impact on the data quality	Unknown
Misclassification
6.3.1.24 Impact on the data quality	Unknown
Common units
6.3.1.25 Common units - proportion	/
6.3.1.26 Additional comments	/

Administrative data

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.27 Name/Title of the administrative source	/
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?
6.3.1.29 What methods are used to detect the out-of scope units?	/
6.3.1.30 Does the administrative source include units that do not exist in practice?
6.3.1.31 Over-coverage - rate	/
6.3.1.32 Impact on the data quality	Unknown
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?
6.3.1.34 If Not, which units are not included?	/
6.3.1.35 How large do you estimate the proportion of those units? (%)	[0-100]
6.3.1.36 Impact on the data quality	Unknown
Misclassification
6.3.1.37 Impact on the data quality	Unknown
6.3.1.38 Additional comments	/

6.3.2. Measurement error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.1 Name/Title	/
6.3.2.2 Is the questionnaire based on usual concepts for respondents?	No
6.3.2.3 Number of censuses already performed with the current questionnaire?	/
6.3.2.4 Preparatory testing of the questionnaire?	No
6.3.2.5 Number of units participating in the tests?	/
6.3.2.6 Explanatory notes/handbook for surveyors/respondents?	No
6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?	No
6.3.2.8 Are there pre-filled questions?	No
6.3.2.9 Percentage of pre-filled questions out of total number of questions	[0-100]
6.3.2.10 Other actions taken for reducing the measurement error?	/
6.3.2.11 Additional comments	/

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.12 Name/Title	Questionnaire on stocks and domestic use of oilseeds.
6.3.2.13 Is the questionnaire based on usual concepts for respondents?	No
6.3.2.14 Number of surveys already performed with the current questionnaire?	1
6.3.2.15 Preparatory testing of the questionnaire?	No
6.3.2.16 Number of units participating in the tests?	/
6.3.2.17 Explanatory notes/handbook for surveyors/respondents?	No
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?	No
6.3.2.19 Are there pre-filled questions?	No
6.3.2.20 Percentage of pre-filled questions out of total number of questions	[0-100]
6.3.2.21 Other actions taken for reducing the measurement error?	/
6.3.2.22 Additional comments	/

6.3.3. Non response error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.1 Name/Title of the survey	/
6.3.3.2 Unit non-response - rate	/
6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context?
6.3.3.4 Measures taken for minimising the unit non-response
6.3.3.5 If Other, please specify	/
6.3.3.6 Item non-response rate	/
6.3.3.7 Item non-response rate - Minimum	/
6.3.3.8 Item non-response rate - Maximum	/
6.3.3.9 Which items had a high item non-response rate?	/
6.3.3.10 Additional comments	/

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.11 Name/Title of the survey	/
6.3.3.12 Unit non-response - rate	/
6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context?
6.3.3.14 Measures taken for minimising the unit non-response
6.3.3.15 If Other, please specify	/
6.3.3.16 Item non-response rate	/
6.3.3.17 Item non-response rate - Minimum	/
6.3.3.18 Item non-response rate - Maximum	/
6.3.3.19 Which items had a high item non-response rate?	/
6.3.3.20 Additional comments	/

6.3.4. Processing error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.1 Name/Title	/
6.3.4.2 Imputation - rate	/
6.3.4.3 Imputation - basis
6.3.4.4 If Other, please specify	/
6.3.4.5 Additional comments	/

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.6 Name/Title	/
6.3.4.7 Imputation - rate	/
6.3.4.8 Imputation - basis
6.3.4.9 If Other, please specify	/
6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation?
6.3.4.11 Additional comments	/

6.3.5. Model assumption error

6.4. Seasonal adjustment

6.5. Data revision - policy

Types of data revisions in relation to planning:

a) Planned data revision is subject to the following reasons:
I. Due to the needs of users for timely information, data are published that meet the criteria of the quality of official statistical data, but do not meet the quality that can be met with additional statistical procedures. Final data are based on more complete answers about the phenomenon and/or analyses and are published later on;
II. Seasonal adjustment and/or elimination of calendar effects;
III. Change in methodology and classifications.

b) Unplanned data revision is not part of the regular statistical process. It appears due to unpredictable changes in the methodology, unpredictable emergence of new and better data, unpredictable changes regarding reporting units that transmit their data to the Office, unpredictable obstacles in data processing and publishing, and errors in data processing and publishing (e.g. a key unit corrects its data for the past few months, an unpredictable change in the administrative data source).

Types of data revisions in relation to time of implementation:

a) Regular revisions: inclusion of a more complete/additional data source or a change in the data source, seasonal adjustment and/or elimination of calendar effects;

b) Occasional revisions are a consequence of including a new/more complete/additional data source that becomes the standard in later data releases or a consequence of an unpredictable obstacle in data processing and publishing, and change in methodology.

Types of data revisions in relation to the purpose:

a) Inclusion of a more complete/additional data source or a change in the data source;
b) Seasonal adjustment and/or elimination of calendar effects;
c) Transition to a new base period;
d) Improvement of methodology due to a change in the statistical method or a change in classifications, concepts and definitions;

e) Elimination or errors

More information about data revision at SORS is published on web site http://www.stat.si/StatWeb/en/mainnavigation/methods-and-classifications/methodological-explanations -> General methodological explanations -> Revision of statistical data.

6.6. Data revision - practice

6.6.1 Data revision - average size	/
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report?	No
6.6.3 What was the main reason for the revisions?	/
6.6.4 How do you evaluate the impact of the revisions?
6.6.5 Additional comments	/

7. Timeliness and punctuality

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7.1. Timeliness

7.1.1 When were the first results for the reference period published?	First results have not yet been published.
7.1.2 When were the final results for the reference period published?	/
7.1.3 Reasons for possible long production times?	Crop balances methodology has been updated in 2018 and 2019.

7.2. Punctuality

7.2.1 Were data released nationally according to a pre-announced schedule (Release Calendar)?	No
7.2.2 If Yes, were data released on the target date?
7.2.3 If No, reasons for delays?	Crop balances methodology will be further updated in 2022 and beyond if additional administrative data sources or estimation methods will be identified.
7.2.4 Number of days between the national release date of data and the target date	/

8. Coherence and comparability

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8.1. Comparability - geographical

To be assessed by Eurostat

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

8.2. Comparability - over time

8.2.1 Length of comparable time series	2017-2019.
8.2.2 Have there been major breaks in the time series?	No
8.2.3 If Yes, please specify the year of break and the reason	/
8.2.4 Additional comments	/

8.3. Coherence - cross domain

8.3.1 With which other national data sources have the data been compared?	Other
8.3.2 If Other, please specify	Other national supply balance sheets for cereals (total cereals balance sheet).
8.3.3 Describe briefly the results of comparisons	/
8.3.4 If no comparisons have been made, explain why	/
8.3.5 Additional comments	/

8.4. Coherence - sub annual and annual statistics

Not applicable

8.5. Coherence - National Accounts

Not applicable

8.6. Coherence - internal

Not applicable

9. Accessibility and clarity

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9.1. Dissemination format - News release

9.1.1 Do you publish a news release?	No
9.1.2 If Yes, please provide a link	/

9.2. Dissemination format - Publications

9.2.1 Do you produce a paper publication?	No
9.2.2 If Yes, is there an English version?	No
9.2.3 Do you produce an electronic publication?	No
9.2.4 If Yes, is there an English version?	No
9.2.5 Please provide a link	/

9.3. Dissemination format - online database

9.3.1 Data tables - consultations	Not yet.
9.3.2 Is an on-line database accessible to users?	No
9.3.3 Please provide a link	/

9.4. Dissemination format - microdata access

9.4.1 Are micro-data accessible to users?	No
9.4.2 Please provide a link	/

9.5. Dissemination format - other

Data have not yet been disseminated.

9.6. Documentation on methodology

9.6.1 Are national reference metadata files available?	No
9.6.2 Please provide a link	/
9.6.3 Are methodological papers available?	No
9.6.4 Please provide a link	/
9.6.5 Is a handbook available?	No
9.6.6 Please provide a link	/

9.7. Quality management - documentation

9.7.1 Metadata completeness - rate	After the final compilation of Crop balances detailed documentation will be prepared.
9.7.2 Metadata - consultations	/
9.7.3 Is a quality report available?	No
9.7.4 Please provide a link	/

10. Cost and Burden

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10.1 Efficiency gains if compared to the previous quality report	Increased use of administrative data
10.2 If Other, please specify	/
10.3 Burden reduction measures since the previous quality report	None
10.4 If Other, please specify	/

11. Confidentiality

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11.1. Confidentiality - policy

11.1.1 Are confidential data transmitted to Eurostat?	No
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009?	No
11.1.3 Describe the data confidentiality policy in place	/

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	/
11.2.2 Additional comments	/

12. Comment

Related metadata

Annexes