Crop production (apro_cp)

Crop production (apro_cp)

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

Compiling agency: Central Statistical Bureau of Latvia

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

1. Contact

1.1. Contact organisation

Central Statistical Bureau of Latvia

1.2. Contact organisation unit

Agricultural Statistics Section, Agricultural and Environment Statistics Department of the CSB of Latvia

1.5. Contact mail address

Central Statistical Bureau of Latvia, Lacplesa street 1, Riga, LV-1301

2. Statistical presentation

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

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

Administrative data

Integrated Administration and Control Systems (IACS)

Final area under cultivation

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Production

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Yield

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Non-existing and non-significant crops

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Table 2: Vegetables, melons and strawberries

Early estimates for harvested areas

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Final harvested area

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Production

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Non-existing and non-significant crops

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Table 3: Permanent crops

Early estimates for production area

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Final production area

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Production

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Non-existing and non-significant crops

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Table 4: Agricultural land use

Main area

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Non-existing and non-significant crops

Survey

Sample survey on areas, harvested production and average yield of agricultural crops

Total number of different data sources

2

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	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?	production divided by harvested area
If another method, describe it.	For national needs - reference is the sown 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	Sample survey on areas, harvested production and average yield of agricultural crops
Planning (month-month/year)	10-12/2021
Preparation (month-month/year)	08-09/2022
Data collection (month-month/year)	10-11/2022
Quality control (month-month/year)	11-12/2022
Data analysis (month-month/year)	01-04/2023
Dissemination (month-month/year)	01-09/2023
If there were delays, what were the reasons?	No delays

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)?	YES
In case yes, how do they differ? ( list all items and explanations)		Onions (V4210) include shallots (V4220) Cherries (F1240) include sour (F1241) and sweet (F1242) cherries
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).	Before selection of holdings, when creating the population frame, holdings with crop standard output (SO) >= EUR 1500 are included. In addition, it is planned to add to the results estimated areas of agricultural crops in holdings with crop SO < EUR 1500. As the result, requirements stipulated in Art.3.2. of Regulation (EC) No 543/2009 are taken into account
Is the data collection based on holdings?	YES
If yes, how the holdings were identified?	Unique statistical farm identifier
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)	08/2022
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	Sample survey on areas, harvested production and average yield of agricultural crops
Which survey method was used?	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent Telephone interview, paper questionnaire Telephone interview, electronic questionnaire Face-to-face interview
If 'other', please specify
Please provide a link to the questionnaire	https://www.csp.gov.lv/lv/katalogs?catalog_vid_1%5B0%5D=247&catalog_vid_1%5B1%5D=247
Data entry method, if paper questionnaires?	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	(Integrated Administration and control System (IACS))
Description	(Data on the declared sown area of agricultural crops)
Data owner (organisation)	(Rural Support Service)
Update frequency	Once per year or more often
Reference date (month/year)	(June/2022)
Legal basis	(Agreement between CSB and Rural Support Service on exchange of information)
Reporting unit	(area of crop, ha)
Identification variable (e.g. address, unique code, etc.)	(Unique code of the crop)
Percentage of mismatches (%)	(not applicable)
How were the mismatches handled?	(not applicable)
Degree of coverage (holdings, e.g. 80%)	(78%)
Degree of completeness (variables, e.g. 60%)	(100%)
If not complete, which other sources were used ?	(not applicable)
Were the data used for sample frame?	Sample frame Validation Directly for estimates Other
Data used for other purposes, which?	(For recalculation of economic size of agricultural holdings, as a pre-print for Crop Production Survey)
Which variables were taken from administrative sources?	(All variables in ha for making early estimates)
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation?	NO
Please describe the differences	(not applicable)
What measures were taken to eliminate the differences?	(not applicable)
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?	(no any other data source available for making early estimates)
What were the possible limitations, drawbacks of using the data from administrative source(s)?	(no any other data source available for making early estimates)

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 Other
Is the data cross-validated against an other dataset?	YES
If yes, which kind of dataset?	Previous results Other dataset
If other, please describe	IACS

3.5. Data compilation

Not Applicable.

3.6. Adjustment

Not applicable.

4. Quality management

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?	YES
If, yes, what are the components?	Activities of the Total Quality Management Systen: to identify statistical and organizational processes and develop their descriptions in compliance with requirements of the quality management system. Components are fundamental processes such as project preparation, data collection, data processing, data analysis, data dissemination and support processes as metadata and documentation of processes. Quality Management System is maintained and updated electronically in QPR portal
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?	Systematic validation improvements Further automation Quality report
If, other, please specify
Additional comments	In order to facilitate correct interpretation of data and to foster dialogue with data users, the CSB develops a unified quality report standard where different data preparation aspects are described in detail: legal basis, methodology, sample design and sample size, data collection and processing methods, definitions etc. (available in Latvian and for internal use). Data entry system for respondents with improved validation rules has been worked out. Starting from 2021, insted of ADS, metadata will be maintained and published on the OS portal according to a common standard(SMS 2.0).

4.2. Quality management - assessment

See the European level Quality Report.

5. Relevance

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?	YES
If yes, how satisfied the users were?	Satisfied
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

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	Sample survey on areas, harvested production and average yield of agricultural crops
Sampling basis?	List
If 'other', please specify
Sampling method?	Stratified
If stratified, number of strata?	36
If stratified, stratification basis?	Location Size Specialisation
If 'other', please specify
Size of total population	23923
Size of sample	3486
Which methods were used to assess the sampling error?	Relative standard error
If other, which?
Which methods were used to derive the extrapolation factor?	Basic weight Non-response Wrong classification
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas	The relative standard error (percentage) is defined as the standard error divided by the estimated value. The total estimated value is the sum of two estimates, where the first comes from sample (holdings with crop standard output (SO) >= EUR 1500) and the second estimated correspond to unobserved population (holdings with crop SO < EUR 1500). RSE=sqrt(estimate of sampling variance)/the total estimated value The estimate of sampling variance is done by the ultimate cluster method (Hansen, Hurwitz and Madow, 1953) and residual estimation from the regression model to take weight calibration into account. The R procedure "vardom" from the package "vardpoor" (Breidaks and Liberts, 2014) is used for the variance estimation.
If the results were compared with other sources, please describe the results
Which were the main sources of errors?	Non-response and over coverage

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	Sample survey on areas, harvested production and average yield of agricultural crops
Cereals for the production of grain (in %)	0.7
Dried pulses and protein crops (in %)	2.9
Root crops (in %)	4.2
Oilseeds (in %)	0.8
Other industrial crops (included all industrial crops besides oilseeds) (in %)	4.3
Plants harvested green from arable land (in %)	3.8
Total vegetables, melons and strawberries (in %)	3.4
Cultivated mushrooms (in %)
Total permanent crops (in %)	6.4
Fruit trees (in %)	9.3
Berries (in %)	9.7
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

3.6 %

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	Sample survey on areas, harvested production and average yield of agricultural crops.
Error type	Over-coverage
Degree of bias caused by coverage errors	Unknown
What were the reasons for coverage errors?	Divergence between the frame population and the target population occurs becausethere are holdings, which do not grow defined crop, during the survey it is found that agricultural land of the holding is sold or rented out.
Which actions were taken for reducing the error or to correct the statistics?	Regular updating of Statistical Farm register and only holdings with crop areas are included in the frame.
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	Sample survey on areas, harvested production and average yield of agricultural crops
Was the questionnaire based on usual concepts for respondents?	YES
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?	18
Preparatory (field) testing of the questionnaire?	NO
Number of units participating in the tests?
Explanatory notes/handbook for surveyors/respondents?	YES
On-line FAQ or Hot-line support for surveyors/respondents?	YES
Were pre-filled questionnaires used?	NO
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?	YES
If yes, describe the actions and their impact	Method of data collection is improved giving possibilities for respondents to apply method of filling- in questionnaire electronically via application ISDAVS CASIS, where automatic data control takes place and it facilitates receiving of correct data from respondents. The errors attributable to the interviewer are reduced by adequate training.

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	Sample survey on areas, harvested production and average yield of agricultural crops
Unit level non-response rate (in %)	1.6
Item level non-response rate (in %)
- Min% / item
- Max% / item
- Overall%
Was the non-response been treated ?	YES
Which actions were taken to reduce the impact of non-response?	Design weights were corrected by non-response effects and calibration
Which items had a high item-level non-response rate?	Not applicable
Which methods were used for handling missing data? (several answers allowed)	Follow-up interviews Reminders Imputations
In case of imputation which was the basis?	Imputation based on similar units Imputation based on other sources
In case of imputation, which was the imputation rate (%)?	1.3
Estimated degree of bias caused by non-response?	Unknown
Which tools were used for correcting the data?	application ISDAVS
Which organisation did the corrections?	CSB
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

7.1. Timeliness

Time lag - first result

Time lag - final result

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?

1

1

1

1

1

1

1

1

1

1

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

When was the first forecasting published for the crop year on which is reported? (day/month/year)

17/02/2023

31/03/2023

17/02/2023

17/02/2023

31/03/2023

31/03/2023

17/02/2023

31/03/2023

31/03/2023

31/03/2023

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

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

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?	Farm structure survey 2016 IACS
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			1.0%
Dried pulses and protein crops			1.7%
Root crops			11.5%
Oilseeds			0.1%
Other industrial crops (than oilseeds)
Plants harvested green			13.4%
Total vegetables, melons and strawberries
Vegetables and melons			6.9%
Strawberries			6.6%
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?			Data in ACS includes data on areas of kitchen gardens.Not all holdings apply for subsidies.

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

9.1. Dissemination format - News release

Availability	Links
YES	https://www.csb.gov.lv/en/statistics/statistics-by-theme/agriculture/crop/search-in-theme/2661-sown-area-and-harvested-production-agricultural

9.2. Dissemination format - Publications

	Availability	Links
Publications	Electronic	https://www.csb.gov.lv/lv/statistika/statistikas-temas/lauksaimnieciba/augkopiba/meklet-tema/424-latvijas-lauksaimnieciba-2023
Publications in English	Electronic	https://www.csb.gov.lv/en/statistics/statistics-by-theme/agriculture/crop/search-in-theme/424-agriculture-latvia-2023

9.3. Dissemination format - online database

Data tables - consultations

	Availability	Links
On-line database accessible to users	YES	http://data1.csb.gov.lv/pxweb/en/lauks/lauks__03Augk__ikgad/?rxid=d8284c56-0641-451c-8b70-b6297b58f464&tablelist=true
Website	English	https://www.csb.gov.lv/en/sakums

9.4. Dissemination format - microdata access

Availability	Links
NO

9.5. Dissemination format - other

9.6. Documentation on methodology

	Availability	Links
Methodological report
Quality Report	English	https://webgate.ec.europa.eu/estat/spe/metaconv/editMetadataFile.htm?metadataFileId=32131
Metadata	English	https://www.csb.gov.lv/en/statistics/statistics-by-theme/agriculture/crop/tables/metadata-sown-area-harvested-production-and-average-yield
Additional comments	Since 2017 Quality report is available only for internal use.

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

Efficiency gains if compared to the previous quality report?	Further automation Increased use of administrative data Staff further training
If other, which?	There is no efficiency gains into monetary terms due to increasing costs of services (rent costs, electricity, heating, computer rent etc.)
Burden reduction measures since the previous reference year	Less respondents Easier data transmission
If other, which?

11. Confidentiality

11.1. Confidentiality - policy

Restricted from publication

11.2. Confidentiality - data treatment

Restricted from publication

12. Comment

Descriptive text was added to the separate concept name

Related metadata

Annexes