Crop production (apro

Crop production (apro_cp)

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

Compiling agency: Statistical Office of the Slovak Republic

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 Slovak Republic

1.2. Contact organisation unit

Department of the Agricultural Statistics

1.5. Contact mail address

Statistical Office of the Slovak Republic

Lamačská cesta 3/C

840 05 Bratislava

Slovak Republic

2. Statistical presentation

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2.1. Data description

Annual crop statistics provide statistics on the area under main arable crops, vegetables and permanent crops and production and yield levels. The statistics are collected from a wide variety of sources: surveys, administrative sources, experts and other data providers. The data collection covers early estimates (before the harvest) and the final data. Data are collected at regional level, the lowest level is NUTS 4.

2.2. Classification system

The national classifier - Hierarchical crop classification system

2.3. Coverage - sector

Growing of non-perennial crops, perennial crops and plant propagation (NACE A01.1-01.3)

2.4. Statistical concepts and definitions

See: Annual crop statistics Handbook

2.5. Statistical unit

Utilised agricultural area cultivated by an agricultural holding.

2.6. Statistical population

All agricultural holdings growing crops.

2.7. Reference area

The entire territory of the country.

2.8. Coverage - Time

Crop year.

2.9. Base period

Not applicable.

3. Statistical processing

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3.1. Source data

	Source 1	Source 2	Source 3	Source 4
Have new data sources been introduced since the previous quality report?	NO
If yes, which new data sources have been introduced since the previous quality report?
Type of source?
To which Table (Reg 543/2009) do they contribute?
Have some data sources been dropped since the previous quality report?	NO
Which data sources have been dropped since the previous quality report?
Type of source?
Why have they been dropped?
Additional comments

Data sources: Please indicate the data sources which were used for the reference year on which is reported

Type

Name(s) of the sources

If other type, which kind of data source?

Table 1: Crops from arable land

Early estimates for areas

Census
Survey

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Pol 6-01 - Questionnaire on estimated yields on selected crop as of 20th of June

Pol 8-01 - Questionnaire on estimated yields on selected crop as of 15th of August

Pol 9-01 - Questionnaire on estimated yields on selected crop as of 15th of September

Final area under cultivation

Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Production

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Yield

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops

Census

Poľ 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Osev 3-01 - Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Table 2: Vegetables, melons and strawberries

Early estimates for harvested areas

Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Final harvested area

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Production

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops

Census

Poľ 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Osev 3-01 - Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Table 3: Permanent crops

Early estimates for production area

Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Final production area

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Production

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Non-existing and non-significant crops

Census

Pol 18-01 (part of survey) - Annual questionnaire on crop production and livestock numbers (cenzus on utilized agricultural areas)

Table 4: Agricultural land use

Main area

Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Non-existing and non-significant crops

Census

Osev 3-01- Questionnaire on sown areas by agricultural crops as of 20 May (cenzus - sown areas)

Total number of different data sources

Additional comments

Data source for the humidity	Put x, if used
Surveyed: farmers report the humidity
Surveyed: farmers convert the production/yield into standard humidity
Surveyed: whole sale purchasers report the humidity
Surveyed: whole sale purchasers convert the production/yield into standard humidity
Surveyed by experts (e.g. test areas harvested and measured)
Estimated by experts
Other type	X
If other type, please explain	Slovak Technical Standard for humidity of crops wich in most cases is equal to Eurostat standards
Additional information

Which method is used for calculating the yield for main arable crops?	Production divided by sown area production divided by harvested area
If another method, describe it.	For the purposes of yield estimation we calculate the yield by using the sown area. For the purposes of the definitive yield we calculate the yield by using the harvested area.

3.2. Frequency of data collection

	Source 1	Source 2	Source 3	Source 4	Source 5	Source 6	Source 7	Source 8	Source 9
Name of data source	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Planning (month-month/year)	February/2022	February/2022	February/2022	February/2022	November/2022
Preparation (month-month/year)	March-July/2022	March-July/2022	March-July/2022	March-July/2022	November/2022
Data collection (month-month/year)	May-June/2022	June/2022	August/2022	September/2022	January - February/2023
Quality control (month-month/year)	May-June/2022	June/2022	August/2022	September/2022	February/2023
Data analysis (month-month/year)	June/2022	June/2022	August/2022	September/2022	February/2023
Dissemination (month-month/year)	July/2022	July/2022	August/2022	September/2022	March/2023
If there were delays, what were the reasons?	No relevant	No relevant	No relevant	No relevant	No relevant

3.3. Data collection

Definitions	Question	In case yes, how do they differ?
Do national definitions differ from the definitions in Article 2 of Regulation (EC) No 543/2009?	NO
Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations?	NO
Are special estimation/calculation methods used for main crops from arable land?	NO
Are special estimation/calculation methods used for vegetables or strawberries?	NO
Are special estimation/calculation methods used for permanent crops for human consumption?	NO
Are special estimation/calculation methods used for main land use?	NO
Do national crop item definitions differ from the definitions in the Handbook (D-flagged data)?	NO
In case yes, how do they differ? ( list all items and explanations)
In case data are delivered for one of the items below, describe the crop species included in the item:

Population

Which measures were taken in order to make sure that the requirement stipulated in Art. 3.2 are met? (Statistics shall be representative of at least 95 % of the areas of each table in the Regulation).	We use different sources to make sure that the statistics is representative of at least 95% of each table in the Regulation, for example results from the Agricultural Census, data from IACS from Paying Agency, data from the Central Control and Testing Institute in Agriculture concerning the vineyards and orchards. Those mentioned sources are used to identify any survey unit which will be included into our surveys.
Is the data collection based on holdings?	YES
If yes, how the holdings were identified?	Identifier of the holder
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)	Monthly/per year
Was a threshold applied?	NO
If yes, size of the excluded area	Area excluded on the basis of the threshold in % of the total area for that crop
Cereals for the production of grain (in %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds) (in %)
Plants harvested green from arable land (in %)
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)

Survey method (only for census and surveys)

	Survey 1	Survey 2	Survey 3	Survey 4	Survey 5	Survey 6	Survey 7
Name of the survey	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Which survey method was used?	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent
If 'other', please specify
Please provide a link to the questionnaire	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Data entry method, if paper questionnaires?	Manual	Manual	Manual	Manual	Manual

Administrative data (This question block is only for administrative data)

	Admin source 1	Admin source 2	Admin source 3	Admin source 4	Admin source 5	Admin source 6
Name of the register
Description
Data owner (organisation)
Update frequency
Reference date (month/year)
Legal basis
Reporting unit
Identification variable (e.g. address, unique code, etc.)
Percentage of mismatches (%)
How were the mismatches handled?
Degree of coverage (holdings, e.g. 80%)
Degree of completeness (variables, e.g. 60%)
If not complete, which other sources were used ?
Were the data used for sample frame?
Data used for other purposes, which?
Which variables were taken from administrative sources?
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation?
Please describe the differences
What measures were taken to eliminate the differences?
How was the reliability, accuracy and coherence (comparison to other available data) of the data originated from administrative data source (ante- and/or ex-post) checked?
What were the possible limitations, drawbacks of using the data from administrative source(s)?

Expert estimations (This question block is only for expert estimates)

	Expert estimate 1	Expert estimate 2	Expert estimate 3	Expert estimate 4	Expert estimate 5	Expert estimate 6
Name of the estimation
Data owner (organisation)
Update frequency (e.g. 1 year or 6 months)
Reference date (Month/Year e.g. 1/22 - 8/22)
Legal basis
Use purpose of the estimates?
What kind of expertise the experts have?
What kind of estimation methods were used?
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation?
If yes, please describe the differences
What measures were taken to eliminate the differences?
How were the reliability, accuracy and coherence (comparison to other available data) of the data originated from experts' estimates (ante- and/or ex-post)checked?
What were the possible limitations, drawbacks of using the data from expert estimate(s)?
Additional comments

3.4. Data validation

Which kind of data validation measures are in place?	Automatic and Manual
What do they target?	Completeness Outliers Aggregate calculations
Is the data cross-validated against an other dataset?	NO
If yes, which kind of dataset?
If other, please describe

3.5. Data compilation

Not Applicable.

3.6. Adjustment

Not applicable.

4. Quality management

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4.1. Quality assurance

	Completeness	Punctuality	Accuracy	Reliability	Overall quality
How would you describe the overall quality development since the previous quality report?	Stable	Stable	Improvement	Stable	Stable
Is there a quality management process in place for crop statistics?	YES
If, yes, what are the components?	communication with reporting units internal communication within Statistical Office of the SR controls in IT tools
Is there a quality report available?	NO
If yes, please provide a link(s)
To which data source(s) is it linked?
Has a peer-review been carried out for crop statistics?	NO
If, yes, which were the main conclusions?
What quality improvement measures are planned for the next 3 years?	Other
If, other, please specify	Use of administrative data
Additional comments

4.2. Quality management - assessment

See the European level Quality Report.

5. Relevance

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5.1. Relevance - User Needs

Are there known unmet user needs?	NO
Describe the unmet needs
Does the Regulation 543/2009 meet the national data needs?	YES
Does the ESS agreement meet the national needs?	YES
If not, which additional data are collected?
Additional comments

5.2. Relevance - User Satisfaction

Have any user satisfaction surveys been done?	NO
If yes, how satisfied the users were?
Additional comments

5.3. Completeness

See the European level Quality Report

5.3.1. Data completeness - rate

See the European level Quality Report

6. Accuracy and reliability

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6.1. Accuracy - overall

See the European level Quality Report.

6.2. Sampling error

Sampling method and sampling error

	Survey 1	Survey 2	Survey 3	Survey 4	Survey 5	Survey 6	Survey 7
Name		Pol 6-01	Pol 8-01	Pol 9-01
Sampling basis?		Area	Area	Area
If 'other', please specify
Sampling method?		Stratified	Stratified	Stratified
If stratified, number of strata?		8	8	8
If stratified, stratification basis?		Location	Location	Location
If 'other', please specify
Size of total population		6170	6170	6170
Size of sample		835	916	665
Which methods were used to assess the sampling error?		Relative standard error	Relative standard error	Relative standard error
If other, which?
Which methods were used to derive the extrapolation factor?		Basic weight	Basic weight	Basic weight
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas		We calculate the standard deviation. Weight: w_i= N_i/n_i Sum: sum(y) Average: y = sum/count Estimate total: sumweight Variance: s² = sum((y-y)²) / (n-1) h: h = (N²/n) (1-(n/N)) Estimate variance of total: ROZ = h * s² Standard error absolute: SE = sqrt(ROZ)	We calculate the standard deviation. Weight: w_i= N_i/n_i Sum: sum(y) Average: y = sum/count Estimate total: sumweight Variance: s² = sum((y-y)²) / (n-1) h: h = (N²/n) (1-(n/N)) Estimate variance of total: ROZ = h * s² Standard error absolute: SE = sqrt(ROZ)	We calculate the standard deviation. Weight: w_i= N_i/n_i Sum: sum(y) Average: y = sum/count Estimate total: sumweight Variance: s² = sum((y-y)²) / (n-1) h: h = (N²/n) (1-(n/N)) Estimate variance of total: ROZ = h * s² Standard error absolute: SE = sqrt(ROZ)
If the results were compared with other sources, please describe the results
Which were the main sources of errors?

Sampling error - indicators

Not applicable

Coefficient of variation (CV) for the area (on the MS level)

	Survey 1	Survey 2	Survey 3	Survey 4	Survey 5	Survey 6	Survey 7
Name of the survey		Pol 6-01	Pol 8-01	Pol 9-01
Cereals for the production of grain (in %)		1,31	1,27	0,97
Dried pulses and protein crops (in %)
Root crops (in %)			1,28	1,24
Oilseeds (in %)		0,72	0,88	0,76
Other industrial crops (included all industrial crops besides oilseeds) (in %)
Plants harvested green from arable land (in %)				0,86
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)
Additional comments

6.3. Non-sampling error

6.3.1. Coverage error

Over-coverage - rate

Not applicable

Common units - proportion

Not applicable

	Data source 1	Data source 2	Data source 3	Data source 4	Data source 5	Data source 6	Data source 7	Data source 8	Data source 9
Name of the data source	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Error type	No error	No error	No error	No error	No error
Degree of bias caused by coverage errors
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments	Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.	Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.	Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.	Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.	Statistical Office of the SR (SO SR) administers the Farm register (RF), where all the relevant reporting units (RU) are recorded . RF is continuously updated according to information from the various sources (commercial register, trade register, paying agency, other surveys and so on.). In case that RU ceased their agricultural activity, it has obligation to report to the Statistical Office of the Slovak Republic, as well as information on potential successors (land sold, leased, etc.). SO SR immediately notes down the potential successor and updates its RF. Due to this fact, the fault of coverage (Coverage error) occurs only sporadically and has no effect on the quality of the survey.

6.3.2. Measurement error

	Data source 1	Data source 2	Data source 3	Data source 4	Data source 5	Data source 6	Data source 7	Data source 8	Data source 9
Name of the data source	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Was the questionnaire based on usual concepts for respondents?	YES	YES	YES	YES	YES
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?	26	26	26	26	26
Preparatory (field) testing of the questionnaire?	NO	NO	NO	NO	NO
Number of units participating in the tests?	0	0	0	0	0
Explanatory notes/handbook for surveyors/respondents?	YES	YES	YES	YES	YES
On-line FAQ or Hot-line support for surveyors/respondents?	NO	NO	NO	NO	NO
Were pre-filled questionnaires used?	NO	NO	NO	NO	NO
Percentage of pre-filled questions out of total number of questions	0	0	0	0	0
Were some actions taken for reducing the measurement error or to correct the statistics?	YES	YES	YES	YES	YES
If yes, describe the actions and their impact	telephone contact	telephone contact	telephone contact	telephone contact	telephone contact

6.3.3. Non response error

Unit non-response - rate

Not applicable

Item non-response - rate

Not applicable

	Survey 1	Survey 2	Survey 3	Survey 4	Survey 5	Survey 6	Survey 7
Name	Osev 3-01	Pol 6-01	Pol 8-01	Pol 9-01	Pol 18-01
Unit level non-response rate (in %)	1,28	0	0	0	1,50
Item level non-response rate (in %)
- Min% / item	0,10	0	0	0	0,10
- Max% / item	0,10	0	0	0	0,10
- Overall%	0,10	0	0	0	0,10
Was the non-response been treated ?	YES	NO	NO	NO	YES
Which actions were taken to reduce the impact of non-response?	Follow-up interviews	not relevant	not relevant	not relevant	Follow-up interviews
Which items had a high item-level non-response rate?	differently	not relevant	not relevant	not relevant	differently
Which methods were used for handling missing data? (several answers allowed)	Follow-up interviews Imputations				Follow-up interviews Imputations
In case of imputation which was the basis?	Imputation based on other sources				Imputation based on other sources
In case of imputation, which was the imputation rate (%)?	1,28	0	0	0	1,50
Estimated degree of bias caused by non-response?	None				None
Which tools were used for correcting the data?	None				None
Which organisation did the corrections?	None				None
Additional comments		In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops.	In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops.	In the year of survey all units reply in the census Osev 3-01. We use this opportunity to ask them also for estimation of their production as regards different crops

6.3.4. Processing error

Not applicable.

6.3.4.1. Imputation - rate

Not applicable.

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

Not applicable.

6.6.1. Data revision - average size

Not applicable.

7. Timeliness and punctuality

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7.1. Timeliness

Time lag - first result

First result - estimates of yield in the relevant year: 13 - 16 days

Time lag - final result

85 days

	Cereals	Dried pulses and protein crops	Root crops	Oilseeds	Other industrial crops	Plants harvested green	Vegetables and melons	Strawberries	Cultivated mushrooms	Fruit trees	Berries	Nut trees	Citrus fruit trees	Vineyards	Olive trees
How many main data releases there are yearly in the national crop statistics for the following types of crops?	5	3	4	5	2	3	0	2	1	1	1	1		2
How many of them are forecasts (releases before the harvest)?	3	3	2	3	0	1	2	0	0	1	1	1		0
When was the first forecasting published for the crop year on which is reported? (day/month/year)	07/07/2022	25/08/2022	25/08/2022	07/07/2022		30/09/2022
When were the final results published for the crop year on which is reported? (day/month/year)	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023	31/03/2023		31/03/2023
Additional comments

7.2. Punctuality

See the European level Quality Report

7.2.1. Punctuality - delivery and publication

See the European level Quality Report

8. Coherence and comparability

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8.1. Comparability - geographical

Not applicable.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

Length of comparable time series

Not applicable

	Crops from arable land (Table 1)	Vegetables, melons and strawberries (Table 2)	Permanent crops (Table 3)	Agricultural land use (Table 4)
Have there been major breaks in the time series in the previous 5 years?	NO	NO	NO	NO
If yes, to which were they related?
If other, which?
Which items were affected?
Year of break (number)
Impact on comparability
Additional comments

8.2.1. Length of comparable time series

Not applicable

8.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?
If others, which?
If no comparisons have been made, why not?	We made some basic frame comparisons with the data from IACS. However, the data from IACS is not definite, especially as regards kind of the crop. Therefore it is difficult to calculate the percentage of the compliance between our stastistical data and IACS data.

Differences between ACS and other data sources (%)

Results of comparisons	IFS 2020	Vineyard survey 2020	IACS	Other source(s)	In case of other sources, which?
Cereals
Dried pulses and protein crops
Root crops
Oilseeds
Other industrial crops (than oilseeds)
Plants harvested green
Total vegetables, melons and strawberries
Vegetables and melons
Strawberries
Cultivated mushrooms
Total permanent crops
Fruit trees		Not applicable.
Berries
Nut trees
Citrus fruit trees		Not applicable.
Vineyards
Olive trees		Not applicable.
If there were considerable differences, which factors explain them?

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

Availability	Links
NO

9.2. Dissemination format - Publications

	Availability	Links
Publications	Electronic Paper	Publications of the Catalogues
Publications in English	None

9.3. Dissemination format - online database

Data tables - consultations

Not applicable

	Availability	Links
On-line database accessible to users	YES	www.statistics.sk
Website	National language English	www.statistics.sk

9.4. Dissemination format - microdata access

Availability	Links
NO

9.5. Dissemination format - other

Free : Archív publikácií

9.6. Documentation on methodology

	Availability	Links
Methodological report	None
Quality Report	English	National quality report
Metadata	None
Additional comments

9.7. Quality management - documentation

Not applicable.

9.7.1. Metadata completeness - rate

Not applicable.

9.7.2. Metadata - consultations

Not applicable.

10. Cost and Burden

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Efficiency gains if compared to the previous quality report?	Further automation
If other, which?
Burden reduction measures since the previous reference year	Easier data transmission Multiple use of the collected data
If other, which?

11. Confidentiality

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11.1. Confidentiality - policy

Restricted from publication

11.2. Confidentiality - data treatment

Restricted from publication

12. Comment

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Related metadata

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Annexes

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