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: Hungarian Central Statistical Office

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

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1.1. Contact organisation

Hungarian Central Statistical Office

1.2. Contact organisation unit

Sectoral Statistics Department

1.5. Contact mail address

H-1525 Budapest, P.O.B. 51.

Hungary

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 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.

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?	Yes
If Yes, please answer all the following questions.
2.1.6. Name of the national legislation	The Act CLV of 2016 on Official Statistics provides the general regulatory framework of surveys implemented in Hungary. Surveys of the reference period are included in the yearly National Program of Statistical Data Collection (NPSDC) which is a Government Decree.
2.1.7. Link to the national legislation	https://www.ksh.hu/docs/hun/info/adatgyujtes/2020/KSH_AGY_2020.pdf
2.1.8. Responsible organisation for the national legislation	Hungarian Government
2.1.9. Year of entry into force of the national legislation	2020
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?	Yes

Additional comments on data description

2.2. Classification system

The classification system is described in the handbook.

2.3. Coverage - sector

Main cereals and oilseeds

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

All agricultural holdings growing crops and enterprises purchasing agricultural products from the producers for further processing or resale.

2.7. Reference area

2.7.1 Geographical area covered	The entire territory of the country.
2.7.2 Which special Member State territories are included?

2.8. Coverage - Time

2002-2020

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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092) December survey of key private holdings (Nr. 2219) See the CROPROD_ESQRSCP_A_HU_2019		Stock data for calendar year of the surveys Nr. 1092 (stock data of the farms) and 1099 (stock data of the enterprises purchasing agricultural products for processing and sale)	Producer’s commodity balances based on the data of survey Nr. 1092 and Nr. 1099
Sample Survey		Official national external trade statistic of HCSO Data sources are available: https://www.ksh.hu/apps/meta.objektum?p_lang=EN&p_menu_id=110&p_ot_id=100&p_obj_id=BFAA
Administrive data source	IACS
Agro-economic model
Expert Estimates				Hungarian Grain and Feed Association (processing of grain)
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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
3.1.3 Name of Organisation responsible	HCSO
3.1.4 Main scope	Budgetary and social security institutions, non-profit and economic organisations using land area
3.1.5 List used to build the frame	Business Register of the HCSO, Agricultural Census 2020, IACS
3.1.6 Any possible threshold values
3.1.7 Population size	8121
3.1.8 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 3.1 of the annexed Excel file
3.1.9 Name/Title
3.1.10 Name of Organisation responsible
3.1.11 Main scope
3.1.12 List used to build the frame
3.1.13 Any possible threshold values
3.1.14 Population size
3.1.15 Sample size
3.1.16 Sampling basis
3.1.17 If Other, please specify
3.1.18 Type of sample design
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

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	Integrated Administration and Control System (IACS)
3.1.25 Name of Organisation responsible	Hungarian State Treasury
3.1.26 Contact information (email and phone)
3.1.27 Main administrative scope	IACS is the most important system for the management and control of payments to farmers made by the Member States in application of the Common Agricultural Policy.
3.1.28 Geospatial Coverage	National
3.1.29 Update frequency	Continuous
3.1.30 Legal basis	Governement Decree No 311/2006 on Hungarian State Treasury Governement Decree No 328/2016 on the termination of the Agricultural and Rural Development Office and on the amendment of certain related government decrees
3.1.31 Are you able to access directly to the micro data?	No
3.1.32 Are you able to check the plausibility of the data, namely by contacting directly the units?	Yes
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?	Good
3.1.34 Please list the main differences between the administrative source and the statistical definitions and concepts	The administrative units are not holdings but just legal and natural persons.
3.1.35 Is a different threshold used in the administrative source and statistical data?	Yes
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	Hungarian Grain and Feed Association
3.1.47 Primary purpose	Market information from processors of grain
3.1.48 Legal basis
3.1.49 Update frequency	Annual
3.1.50 Expert data supplier	Producer organisation
3.1.51 If Other, please specify
3.1.52 How would you assess the quality of those data?
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

3.2. Frequency of data collection

Every year

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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
3.3.2 Methods of data collection	Electronic questionnaire
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)	https://www.ksh.hu/docs/hun/info/02osap/2020/kerdoiv/k201092.pdf
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
3.3.9 Methods of data collection
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

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	IACS
3.3.16 Extraction date	01.07.2020.
3.3.17 How easy is it to get access to the data?	Access granted upon a simple request
3.3.18 Data transfer method	Downloading data from Sharepoint server of Hungarian State Treasury.
3.3.19 Additional comments	From IACS we use the Single Area Payment Scheme data for the estimation of utilised agricultural area of private holdings.

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	Grinding data from Hungarian Grain and Feed Association
3.3.21 Methods of data collection	Information of the millers, grain processors
3.3.22 Additional comments

3.4. Data validation

3.4.1 Which kind of data validation measures are in place?	Manual Automatic
3.4.2 What do they target?	Completeness Outliers Aggregates Consistency
3.4.3 If Other, please specify

3.5. Data compilation

3.5.1 Describe the data compilation process	Full-scope survey is applied in case of agricultural enterprises and key private holdings. Imputation is not applied for primary data. For the estimation of other private holdings (excluding from the 'key private holding' category) we use the Single Area Payment Scheme data from IACS.
3.5.2 Additional comments

3.6. Adjustment

Not applied

4. Quality management

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4.1. Quality assurance

4.1.1 Is there a quality management system used in the organisation?	Yes
4.1.2 If yes, how is it implemented?	Internal quality report is made annually by statistical domain. It contains detailed information about the quality of statistical products. It helps to evaluate the quality of the statistical products according to the quality components accepted in the HCSO. Furthermore it helps to define the quality improvement measures.
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?	Further automation
4.1.6 If Other, please specify
4.1.7 Additional comments

4.2. Quality management - assessment

Development since the last quality report

4.2.1 Overall quality	Improvement
4.2.2 Relevance	Improvement
4.2.3 Accuracy and reliability	Improvement
4.2.4 Timeliness and punctuality	Stable
4.2.5 Comparability	Stable
4.2.6 Coherence	Improvement
4.2.7 Additional comments

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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	All required data has been completed.
5.1.2 Please specify any plans to satisfy needs more completely in the future
5.1.3 Additional comments

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	Data sets are complete.
5.3.2 If not complete, which characteristics are missing?
5.3.3 Additional comments

6. Accuracy and reliability

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See sections below.

6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Good
6.1.2 What are the main factors lowering the accuracy?	Measurement error Non-response error
6.1.3 If Other, please specify
6.1.4 Additional comments

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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
Over-coverage
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope?	No
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?	No
6.3.1.5 Over-coverage - rate
6.3.1.6 Impact on the data quality	None
Under-coverage
6.3.1.7 Does the sample frame include all units falling within the scope of this survey?	No
6.3.1.8 If Not, which units are not included?	Coverage of the used agricultural area is not complete. Imputation of missing agricultural area is based on administrative data.
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
Misclassification
6.3.1.11 Impact on the data quality
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
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
Misclassification
6.3.1.24 Impact on the data quality
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	IACS
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?	Yes
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?	No
6.3.1.31 Over-coverage - rate
6.3.1.32 Impact on the data quality	None
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?	No
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	None
Misclassification
6.3.1.37 Impact on the data quality
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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
6.3.2.2 Is the questionnaire based on usual concepts for respondents?	Yes
6.3.2.3 Number of censuses already performed with the current questionnaire?	4
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?	Yes
6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?	Yes
6.3.2.8 Are there pre-filled questions?	Yes
6.3.2.9 Percentage of pre-filled questions out of total number of questions	[0-100] 10
6.3.2.10 Other actions taken for reducing the measurement error?	Supervisors at the regional departments checked the questionnaires.
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
6.3.2.13 Is the questionnaire based on usual concepts for respondents?
6.3.2.14 Number of surveys already performed with the current questionnaire?
6.3.2.15 Preparatory testing of the questionnaire?
6.3.2.16 Number of units participating in the tests?
6.3.2.17 Explanatory notes/handbook for surveyors/respondents?
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?
6.3.2.19 Are there pre-filled questions?
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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
6.3.3.2 Unit non-response - rate	2%
6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context?	Very low
6.3.3.4 Measures taken for minimising the unit non-response	Follow-up interviews Reminders
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate	Because the data collection was done via internet validation rules were run during field work. The program did not allow to save the questionnares with missing required items, therefore nonresponse item inside the filled part of questionnares did not occur.
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	Production, utilisation and net income of the crop products, vegetables, grass and reed (Nr.1092)
6.3.4.2 Imputation - rate	Not applicable
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

Not applicable.

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

Not applicable.

6.6. Data revision - practice

6.6.1 Data revision - average size	0
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?	Not applicable.
7.1.2 When were the final results for the reference period published?	Producer’s commodity balances and consolidated balance sheets data were published on 15^th October 2021.
7.1.3 Reasons for possible long production times?

7.2. Punctuality

7.2.1 Were data released nationally according to a pre-announced schedule (Release Calendar)?	Yes
7.2.2 If Yes, were data released on the target date?	Yes
7.2.3 If No, reasons for delays?
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	19 periods (2002-2020)
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?	None
8.3.2 If Other, please specify
8.3.3 Describe briefly the results of comparisons
8.3.4 If no comparisons have been made, explain why	Outside of HCSO other data sources are not available.
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?
9.2.3 Do you produce an electronic publication?	Yes
9.2.4 If Yes, is there an English version?	Yes
9.2.5 Please provide a link	https://www.ksh.hu/stadat_files/mez/en/mez0021.html

9.3. Dissemination format - online database

9.3.1 Data tables - consultations	Not available.
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

Not available.

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	For the better understanding of data the HCSO publishes the documentation of many different statistical domains including EAA documentation. It comprises the definitions of concepts, the data sources used in a statistical domain, the methods applied, data quality aspects, the most frequently used classifications and other metadata. Metadata and documentations are permanently updated in accordance with changes. Statistical domains: main metadata of statistics (purpose, content, legal base, data production methodology, data quality, concepts, classifications, data sources, forms of publications) Concepts and definitions: glossary of statistics, explanation of and cross-references between concepts, changes of definitions over time Classifications: main classifications used in statistics, their structure, with explanation of items, tables of correspondence between different classifications and the different versions of each classification Data sources: registers, data surveys, and data received from other sources, serving as a basis for producing statistics. - Data collections: most important metadata of data collections and surveys, which are the data sources of a statistical domain (enactor, frequency, scope of data suppliers, deadline for data receipt, etc.). Statistical data collections ordered by the HCSO are listed here. - Administrative data sources: description of administrative data sources used as data sources for a statistical domain (data provider, frequency, scope of data, etc.). Administrative data: data generated during the implementation of the statutory administrative tasks of the administrative organization (e.g. public registers). Administrative data received by the HCSO are displayed here. - Non-administrative data sources: description of non-administrative data sources forming the data source of the statistical domain (data provider, frequency, scope of data, etc). Data sources not required by law or created for non-administrative purposes as well as statistical data collections ordered by organizations of the official statistical service other than the HCSO if these are taken over by the HCSO are displayed here. - Registers: descriptions of HCSO registers and attributes of register units serving as a basis for a statistical domain
9.7.2 Metadata - consultations	Not available.
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	On-line surveys Further automation Increased use of administrative data
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report	More user-friendly questionnaires
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?
11.1.3 Describe the data confidentiality policy in place	The protection of personal data and the publicity of data of public interest are regulated by the following Acts in Hungary: - Act CLV of 2016 on Official statistics, - Act CXII of 2011 on Informational Self-Determination and on Freedom of Information. Besides the above mentioned legal acts, internal regulations on confidentiality exist within the HCSO. On the top of the regulations concerning data protection stands the Confidentiality Policy of the HCSO, which contains the most important principles regarding statistical confidentiality. The HCSO Regulation on Data Protection sets forth more detailed rules and as a framework regulation is complemented by several other internal regulations. The access to statistical data is regulated in a separate internal regulation (Regulation 18/2014 on the rules of data access) which contains the rules on the six data access channels of the HCSO. In virtue of the Act CXII of 2011 on Informational Self-Determination and on Freedom of Information and the Act XLVI CLV of 2016 on Official statistics all individual data are qualified as confidential and are treated as such. Survey data are validated and checked exclusively by the staff of HCSO and enumerators are responsible for preventing unauthorized access to the completed questionnaires. Confidentiality Policy of the HCSO: http://www.ksh.hu/docs/bemutatkozas/eng/avpol_web_eng.pdf HCSO Regulation on Data Protection: http://www.ksh.hu/docs/szolgaltatasok/adatigenyles/hcso_regulation_on_data_protection.pdf

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	Only non-confidential data are disseminated.
11.2.2 Additional comments

12. Comment

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Related metadata

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Annexes

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CropsBS-Annex
CropsBS_Annex_HU