Crop production (apro_cp)

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

Compiling agency: Statistics Iceland


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Statistics Iceland
1.2. Contact organisation unit

Business trends and structure
1.5. Contact mail address

Borgartun 21a, 150 Reykjavik, Iceland


2. Statistical presentation Top
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 mostly at national level but for some crops also regional data exist (NUTS1/2).
2.2. Classification system

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 Top
3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous quality report?  YES      
If yes, which new data sources have been introduced since the previous quality report?

Subsidies data. New agricultural negociations of the state with farmers associacion had a new set of subsidies for area with harvested crops.

Statistics Iceland has access to detailed data for these payments with area and tonnage included.
Type of source? Administrative data
To which Table (Reg 543/2009) do they contribute? Table1
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

these new administrative data can be sused for both table 1 and 2


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 Other  
Final area under cultivation Administrative data
Production Expert estimate
Yield Other
Non-existing and non-significant crops Expert estimate
Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Other
Final harvested area Census
Production Census

Other vegetables than potatoes, carrots and swedes are estmated with data from wholesale companies.
Non-existing and non-significant crops Expert estimate

No permanent crops above significant level in Iceland
Table 3: Permanent crops      
Early estimates for production area Expert estimate
Final production area Expert estimate
Production Expert estimate
Non-existing and non-significant crops Expert estimate
Table 4: Agricultural land use      
Main area Survey
Non-existing and non-significant crops Expert estimate
Total number of different data sources

3

Census

expert estimate

Wholesale reports

  
Additional comments

Data source for the humidity

Put x, if used

Surveyed: farmers report the humidity

 x

Surveyed: farmers convert the production/yield into standard humidity     

 x

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

 

If other type, please explain

 

Additional information

 
   


Which method is used for calculating the yield for main arable crops? another method
If another method, describe it.




 
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

Subsidies data
Planning (month-month/year)

 november 2022 (for year 2022)
Preparation (month-month/year)

February 2023 (for crop year 2022)
Data collection (month-month/year)

Farmers deliver the data in november-january, Statistics iceland receive the data in january-february
Quality control (month-month/year)

February-June 2023 (for crop year 2022)
Data analysis (month-month/year)

February-March 2023 (for crop year 2022)
Dissemination (month-month/year)

February-March 2023 (for crop year 2022)
If there were delays, what were the reasons?

Forgetful farmers, busy administrator






 
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).
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)

october 2022, holdings are checked with tax register which arrive in october every 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
Which survey method was used?
If 'other', please specify
Please provide a link to the questionnaire
Data entry method, if paper questionnaires?


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

Tax records

subsidies data
Description

National tax records

Subsidies data for crops.
Data owner (organisation)

Iceland revenue and customs

Ministry of Industries and Innovation
Update frequency Once per year or more often Once per year or more often
Reference date (month/year)

december 2022

december 2022
Legal basis

Tax laws

subsidies law
Reporting unit
Identification variable (e.g. address, unique code, etc.)

Agricultural holding

Agricultural holding
Percentage of mismatches (%)

less than 3% estimated

less than 3% estimated
How were the mismatches handled?

Statistics Iceland tries to identify holdings based on adress, person identification and location

Statistics Iceland tries to identify holdings based on adress, person identification and location
Degree of coverage (holdings, e.g. 80%)

over 95% (est.)

over 95% (est.)
Degree of completeness (variables, e.g. 60%)

over 95% (est.)

over 95% (est.)
If not complete, which other sources were used ?
Were the data used for sample frame? Directly for estimates Validation
Data used for other purposes, which?
Which variables were taken from administrative sources?

Values.

Area and tonnage
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)?

No detailed information between individual crop types


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

Permanent crops
Data owner (organisation)

Statistics Iceland
Update frequency (e.g. 1 year or 6 months) Yearly
Reference date (Month/Year  e.g. 1/22 - 8/22)

12/22
Legal basis
Use purpose of the estimates?

Confirm that premanent crop production is (still) below threshold
What kind of expertise the experts have?

Msc in agricultural science.
What kind of estimation methods were used?

Argus eyes on news and social media regarding premanent crops, social contacts within the agricultural sector.
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation? NO
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? Manual
What do they target?
Is the data cross-validated against an other dataset? YES
If yes, which kind of dataset?
If other, please describe

Crop data are cross checked with wholesale records.






 
3.5. Data compilation

Not Applicable.
3.6. Adjustment

Not applicable.


4. Quality management Top
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 Stable Stable Stable
Is there a quality management process in place for crop statistics? NO        
If, yes, what are the components?        
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? Increase of resources        
If, other, please specify        
Additional comments

New agricultural contract between farmers and state dictate increased and in many instances new area subsidies. Which demands area measurements and crop reports.

        






 
4.2. Quality management - assessment

See the European level Quality Report.


5. Relevance Top
5.1. Relevance - User Needs

Are there known unmet user needs? YES
Describe the unmet needs

There is demand for more accurate area data.
Does the Regulation 543/2009 meet the national data needs? NO
Does the ESS agreement meet the national needs?
If not, which additional data are collected?

More detailed crop data.
Additional comments






 
5.2. Relevance - User Satisfaction

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

There is demand for more accurate area data.






 
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 Top
6.1. Accuracy - overall

See the European level Quality Report.

Hard to estimate due to low population in census (less than 50 farms)

 
6.2. Sampling error

Sampling method and sampling error

  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

No sampling error, Total census used biannually
Sampling basis?
If 'other', please specify
Sampling method?
If stratified, number of strata?
If stratified, stratification basis?
If 'other', please specify
Size of total population
Size of sample
Which methods were used to assess the sampling error? 
If other, which?
Which methods were used to derive the extrapolation factor? 
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas
If the results were compared with other sources, please describe the results
Which were the main sources of errors?


Sampling error - indicators


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
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 %)
Additional comments            




 
6.3. Non-sampling error

Not applicable.
6.3.1. Coverage error

Over-coverage - rate


Common units - proportion


  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
Error type
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




 
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
Was the questionnaire based on usual concepts for respondents?
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?
Preparatory (field) testing of the questionnaire?
Number of units participating in the tests? 
Explanatory notes/handbook for surveyors/respondents? 
On-line FAQ or Hot-line support for surveyors/respondents?
Were pre-filled questionnaires used?
Percentage of pre-filled questions out of total number of questions
Were some actions taken for reducing the measurement error or to correct the statistics?
If yes, describe the actions and their impact






 
6.3.3. Non response error

Unit non-response - rate


Item non-response - rate


  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name
Unit level non-response rate (in %)
Item level non-response rate (in %)              
               - Min% / item
               - Max% / item
               - Overall%
Was the non-response been treated ?
Which actions were taken to reduce the impact of non-response?
Which items had a high item-level non-response rate? 
Which methods were used for handling missing data?
(several answers allowed)
In case of imputation which was the basis?
In case of imputation, which was the imputation rate (%)?
Estimated degree of bias caused by non-response?
Which tools were used for correcting the data?
Which organisation did the corrections?
Additional comments




 
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 Top
7.1. Timeliness

Time lag - first result

First results for crops usually available in March, year n+1


Time lag - final result

Final results available in May year n+1


  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?

2

0

2

0

0

2

1

0

2
How many of them are forecasts (releases before the harvest)?

0

0

0
When was the first  forecasting published for the crop year on which is reported? (day/month/year)
When were the final results published for the crop year on which is reported? (day/month/year) 01/05/2023 01/05/2023 01/05/2023 01/05/2023
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 Top
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


  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
8.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?  None
If others, which?
If no comparisons have been made, why not?


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

no vines
Olive trees

Not applicable.
If there were considerable differences, which factors explain them?  





 
8.4. Coherence - sub annual and annual statistics

Not applicable.

Not relevant
8.5. Coherence - National Accounts

Not applicable.

Not relevant
8.6. Coherence - internal

Not applicable.

Not relevant


9. Accessibility and clarity Top

See points 9.1, 9.2, 9.3, 9.5 and 9.6
9.1. Dissemination format - News release

Availability Links
NO






 
9.2. Dissemination format - Publications

  Availability Links
Publications None
Publications in English






 
9.3. Dissemination format - online database

Data tables - consultations

Not relevant


  Availability Links
On-line database accessible to users
Website





 
9.4. Dissemination format - microdata access

Availability Links
YES






 
9.5. Dissemination format - other

Not applicable.

Crop statistics Availability Links
Free/against payment access policy Free https://px.hagstofa.is/pxis/pxweb/is/Atvinnuvegir/Atvinnuvegir__landbunadur__landbufe/LAN10103.px
Additional comments  
9.6. Documentation on methodology

  Availability Links
Methodological report None
Quality Report
Metadata
Additional comments  






 
9.7. Quality management - documentation

Not applicable.

See chapter 3 
9.7.1. Metadata completeness - rate

Not applicable.

Not relevant
9.7.2. Metadata - consultations

Not applicable.

Not relevant


10. Cost and Burden Top

Efficiency gains if compared to the previous quality report?
If other, which?
Burden reduction measures since the previous reference year  More user-friendly questionnaires
Multiple use of the collected data
If other, which?






 


11. Confidentiality Top
Restricted from publication
11.1. Confidentiality - policy
Restricted from publication
11.2. Confidentiality - data treatment
Restricted from publication


12. Comment Top

no comments


Related metadata Top


Annexes Top