Crop balance sheets (apro_cbs)

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

Compiling agency: Natural Recources Institute Finland (Luke)


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



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1. Contact Top
1.1. Contact organisation

Natural Recources Institute Finland (Luke)

1.2. Contact organisation unit

Statistical Services

1.5. Contact mail address

Latokartanonkaari 9

FI-00790 HELSINKI

Finland


2. Statistical presentation Top
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? 

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?


Additional comments on data description

2.2. Classification system

The classification system is based on handbook.

2.3. Coverage - sector

The balance calculation cover common wheat and spelt, durum wheat, barley, grain maize & corn-cob-mix, rape and turnip rape seeds, sunflower seed and soys

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

Trade and industry enterprises

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

Starting from year 2017-

2.9. Base period

Not applicable


3. Statistical processing Top
3.1. Source data

Data source details

 

Crop statistics

International rade statistics

Stock estimates

Domestic use estimates

Census

 

 

 x

Sample Survey

 x

 

 

 x

Administrive data source

 

 

 x

 x

Agro-economic model

 

 

 

 

Expert Estimates

 

 

 x

 x

Other sources

 

 x

 

 


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

A questionnaire is used to collect data from all cereal trade enterprises and all cereal-using enterprises

3.1.3 Name of Organisation responsible

Luke, Natural Resources Institute Finland

3.1.4 Main scope

Statistics on cereals purchased, used and stockpiled by industry and trade

Biannual statistics on the stocks of cereals, turnip rape and oilseed rape held by enterprises that buy and use cereals.

 

3.1.5 List used to build the frame

Business register

3.1.6 Any possible threshold values

Enterprises cover at least 97% of the use of cereals/tirnip rape and oilseed rape

3.1.7 Population size

Population covers at least 97% of the total use of the product

3.1.8 Additional comments

https://stat.luke.fi/en/statistics-on-cereals-purchased-used-and-stockpiled-by-industry-and-trade


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

Sample survey on crop production

3.1.10  Name of Organisation responsible

Luke, Natural Resources Institute Finland

3.1.11  Main scope

The statistics contain harvest data on Finland’s most important field crops

3.1.12  List used to build the frame

Agricultural and Horticultural Enterprise Register

3.1.13  Any possible threshold values

2000€  SO (Standard Output)

3.1.14  Population size

48000 farms

3.1.15  Sample size

6200 farms

3.1.16  Sampling basis

List

3.1.17  If Other, please specify

3.1.18  Type of sample design

Stratified

3.1.19 If Other, please specify

3.1.20 If Stratified, number of strata

3.1.21 If Stratified, stratification criteria

Unit location
Unit specialization

3.1.22 If Other, please specify

3.1.23 Additional comments

https://stat.luke.fi/en/crop-production-statistics


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

IACS

 

3.1.25 Name of Organisation responsible

Finnish Food Authority

 

3.1.26 Contact information (email and phone)

Tel +358 295 30 0400

 

3.1.27 Main administrative scope

 responsible for the use of agricultural aid and rural development funds of the European Union in Finland.

 

3.1.28 Geospatial Coverage

National

3.1.29 Update frequency

Annual

3.1.30 Legal basis

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?

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

A number of animals is taken from IACS to calculate the amount of grain used in farms for feed


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

3.1.47 Primary purpose

3.1.48 Legal basis

3.1.49 Update frequency

3.1.50 Expert data supplier

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

International Trade Statistics

3.1.55 Name of Organisation

Finnish Custom

3.1.56 Primary purpose

Import on export statistics

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

Statistics on cereals purchased, used and stockpiled by industry and trade

3.3.2 Methods of data collection

Postal 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?

Manual

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

Sample survey of crop production

3.3.9 Methods of data collection

Electronic questionnaire
Telephone interview

3.3.10 If Other, please specify

3.3.11 If face-to-face or telephone interview, which method is used?

Electronic questionnaire

3.3.12 Data entry method, if paper questionnaires?

3.3.13 Please annex the questionnaire used (if very long: please provide the hyperlink)

https://stat.luke.fi/sites/default/files/sato_2021_lomake.pdf

 

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

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

Research experts in Luke on animal feed

3.3.21 Methods of data collection

Interview

3.3.22 Additional comments



Annexes:
Enquiry to enterprices of purchases, use and stock of grain
3.4. Data validation

3.4.1 Which kind of data validation measures are in place?

Manual
None

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

not applicable

 

3.5.2 Additional comments

3.6. Adjustment

not applicable


4. Quality management Top
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?

The producers of Official Statistics of Finland have approved a common quality assurance in which they commit to common quality criteria and quality assurance measures. The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice. The good practices followed in the statistics are presented in Statistics Finland's Quality Guidelines for Official Statistics handbook.

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?

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

Stable

4.2.3 Accuracy and reliability

Improvement

4.2.4 Timeliness and punctuality

Stable

4.2.5 Comparability

Improvement

4.2.6 Coherence

Stable

4.2.7 Additional comments

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5. Relevance Top
5.1. Relevance - User Needs

5.1.1 If certain user needs are not met, please specify which and why

The calculation is based on calendar year but customers would prefere marketing year based balances. In national level some crops are not relevant (durum wheat, sunflower)

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

100%

5.3.2 If not complete, which characteristics are missing?

5.3.3 Additional comments


6. Accuracy and reliability Top
6.1. Accuracy - overall

6.1.1 How good is the accuracy?

Good

6.1.2 What are the main factors lowering the accuracy?

Coverage error
Non-response error
Model assumption error

6.1.3 If Other, please specify

6.1.4 Additional comments

I tried to remove 'non-response error' in 6.1.2. but I couldn't do it.

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

Sample survey on Crop production

6.2.2 Methods used to assess the sampling error

Relative standard error

6.2.3 If Other, please specify

6.2.4 Methods used to derive the extrapolation factor

Basic weight
Non-response

6.2.5 If Other, please specify

6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas

The results were estimated with SAS software. Variances were estimated using the CLAN-macro developed by Statistics Sweden.

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

Statistics on cereals purchased, used and stockpiled by industry and trade

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?

The business register is used as a frame, and the register is updated every year

6.3.1.4 Does the sample frame include units that do not exist in practice?

6.3.1.5 Over-coverage - rate

There is no over- coverage

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?

Yes

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

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

Sample survey on Crop production

Over-coverage

6.3.1.15 Does the sample frame include wrongly classified units that are out of scope?

Yes

6.3.1.16 What methods are used to detect the out-of scope units?

Farm may have fininshed the farm keeping after the sample has drawn

6.3.1.17 Does the sample frame include units that do not exist in practice?

No

6.3.1.18 Over-coverage - rate

1%

6.3.1.19 Impact on the data quality

None

Under-coverage 

6.3.1.20 Does the sample frame include all units falling within the scope of this survey?

Yes

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 - number of animals, cultivated area of crops

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

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

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

6.3.2.2 Is the questionnaire based on usual concepts for respondents?

6.3.2.3 Number of censuses already performed with the current questionnaire?

6.3.2.4 Preparatory testing of the questionnaire?

6.3.2.5 Number of units participating in the tests? 

6.3.2.6 Explanatory notes/handbook for surveyors/respondents? 

6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?

6.3.2.8 Are there pre-filled questions?

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

Sample survey on crop production

6.3.2.13 Is the questionnaire based on usual concepts for respondents?

Yes

6.3.2.14 Number of surveys already performed with the current questionnaire?

26

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? 

Yes

6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?

Yes

6.3.2.19 Are there pre-filled questions?

Yes

6.3.2.20 Percentage of pre-filled questions out of total number of questions

16,6 %

6.3.2.21 Other actions taken for reducing the measurement error?

WEB- and CATI -survey included logical checks and min/max -checks

- above actions improved the quality of data (e.g. no outliers or extraordinary values)

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

Sample survey on crop production

6.3.3.12 Unit non-response - rate

15 %

6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context?

Low

6.3.3.14 Measures taken for minimising the unit non-response

Reminders

6.3.3.15 If Other, please specify

6.3.3.16 Item non-response rate

Non existent -

Due the controls and checks in WEB- and CATI -survey, the rate was non-existent.

6.3.3.17 Item non-response rate - Minimum

See 6.3.3.16

6.3.3.18 Item non-response rate - Maximum

See 6.3.3.16

6.3.3.19 Which items had a high item non-response rate? 

See 6.3.3.16

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

Sample survey on crop statistics

6.3.4.7 Imputation - rate

Imputation is not used

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

There were numerous controls and checks during the survey (WEB- and CATI -based survey).Checks and controls resulted in either a warning or an error notification (=error). Due this controls and checks data processing errors are extremely unlike.

6.3.5. Model assumption error
6.4. Seasonal adjustment

Not applicaple

6.5. Data revision - policy

Revision policy follows the national guidelines for Official Statistis of Finland (FOS). The OSF quality criteria are compatible with the quality criteria of the European Statistical System (ESS).

6.6. Data revision - practice

6.6.1 Data revision - average size

One year

 

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

Not yet known - new data production

 


7. Timeliness and punctuality Top
7.1. Timeliness

7.1.1 When were the first results for the reference period published?

N + 11 months

7.1.2 When were the final results for the reference period published?

N + 11 months

 

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)?

No

7.2.2 If Yes, were data released on the target date?

7.2.3 If No, reasons for delays?

No national publication yet

 

7.2.4 Number of days between the national release date of data and the target date


8. Coherence and comparability Top
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

4 years

 

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

Timeseries of four years

 

8.3. Coherence - cross domain

8.3.1 With which other national data sources have the data been compared?

Crop statistics
Trade Statistics
Other

8.3.2 If Other, please specify

Balance sheet for food commodities

8.3.3 Describe briefly the results of comparisons

Crop production and trade statistics have been used for estimates

 

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 Top
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?

No

9.2.4 If Yes, is there an English version?

9.2.5 Please provide a link

9.3. Dissemination format - online database

9.3.1 Data tables - consultations

0

 

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
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
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 Top

10.1 Efficiency gains if compared to the previous quality report

None

10.2 If Other, please specify

10.3 Burden reduction measures since the previous quality report

Multiple use of the collected data

10.4 If Other, please specify


11. Confidentiality Top
11.1. Confidentiality - policy

11.1.1 Are confidential data transmitted to Eurostat?

Yes

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

Less than 3 enterprises covers the figures

 

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination

The figures covers at least 3 enterprises

 

11.2.2 Additional comments


12. Comment Top


Related metadata Top


Annexes Top
CropsBS-Annex