1.1. Contact organisation
Statistical Office of the Republic of Slovenia
1.2. Contact organisation unit
Department for Agriculture, Forestry, Fishery and Hunting
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Litostrojska 54
1000 Ljubljana
Slovenia
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
30 May 2024
2.2. Metadata last posted
30 May 2024
2.3. Metadata last update
31 May 2024
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of agricultural holdings and manager of the agricultural holding and information on their land and livestock. They also describe production methods, rural development measures, labour force and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the structure and state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
3.2. Classification system
Data are arranged in tables using many classifications. Please find below information on most classifications.
The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2018/1874.
The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard output (SO) (from 2010 onward) which is calculated for each crop and animal. The farm type is determined by the relative contribution of the different productions to the total standard output of the holding (COMMISSION IMPLEMENTING REGULATION (EU) 2015/220 of 3 February 2015 laying down rules for the application of Council Regulation (EC) No 1217/2009 setting up a network for the collection of accountancy data on the incomes and business operation of agricultural holdings in the European Union).
The territorial classification uses the NUTS classification to break down the regional data. The regional data is available at NUTS level 2.
3.3. Coverage - sector
The statistics cover agricultural holdings undertaking agricultural activities as listed in item 3.5 below and meeting the minimum coverage requirements (thresholds) as listed in item 3.6 below.
3.4. Statistical concepts and definitions
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2019/2020 are set in Commission Implementing Regulation (EU) 2018/1874.
The following groups of variables are collected in 2020:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module "Animal housing and rural development module": animal housing, nutrient use and manure on the farm, manure application techniques, facilities for manure.
3.5. Statistical unit
See sub-category below.
3.5.1. Definition of agricultural holding
In accordance with Regulation (EC) No 1091/2018 the ‘farm’ or ‘agricultural holding’ means a single unit, both technically and economically, that has a single management and that undertakes economic activities in agriculture in accordance with Regulation (EC) No 1893/2006 belonging to groups A.01.1, A.01.2, A.01.3, A.01.4, A.01.5 or to the ‘maintenance of agricultural land in good agricultural and environmental condition’ of group A.01.6 within the economic territory of the Union, either as its primary or secondary activity. Regarding activities of class A.01.49, only the activities ‘Raising and breeding of semi-domesticated or other live animals’ (with the exception of raising of insects) and ‘Bee-keeping and production of honey and beeswax’ are included.
3.6. Statistical population
See sub-categories below.
3.6.1. Population covered by the core data sent to Eurostat (main frame and if applicable frame extension)
The thresholds of agricultural holdings are available in the annex.
Annexes:
3.6.1. Thresholds of agricultural holdings
3.6.1.1. Raised thresholds compared to Regulation (EU) 2018/1091
No3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
Yes3.6.2. Population covered by the data sent to Eurostat for the modules “Labour force and other gainful activities”, “Rural development” and “Machinery and equipment”
The subset of population of agricultural holdings defined in item 3.6.1 which falls in the main frame i.e. above at least one of the thresholds set in Regulation (EU) 2018/1091.
The above answer holds for the modules ‘Labour force and other gainful activities’ and ‘Rural development’. The module ‘Machinery and equipment’ is not collected in 2020.
3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”
The subset of the population of agricultural holdings defined in item 3.6.2 with at least one of the following: bovine animals, pigs, sheep, goats, poultry.
There were 25 farms who were later on discovered that did not have animals, but had other data, so we left them in a subset population.
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
Not applicable for 2019/2020.
3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
Not applicable for 2019/2020.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
Not applicable for 2019/2020.
3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Not applicable for 2019/2020.
3.7. Reference area
See sub-categories below.
3.7.1. Geographical area covered
The entire territory of the country.
3.7.2. Inclusion of special territories
Not applicable.
3.7.3. Criteria used to establish the geographical location of the holding
The main building for production3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Integrated Farm Statistics cover the period from 2020 onwards. Older (before 2020) time series on Farm structure statistics are described in the previous quality reports (national methodological reports).
3.9. Base period
The 2020 data are processed (by Eurostat) with 2017 standard output coefficients (calculated as a 5-year average of the period 2015-2019). For more information, you can consult the definition of the standard output.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land refers to the reference year 2020. In the case of successive crops from the same piece of land, the land use refers to a crop that is harvested during the reference year, regardless of when the crop in question is sown.
Reference period was from 1.1.2020 till 31.12.2020.
5.2. Reference period for variables on irrigation and soil management practices
Reference period was from 1.1.2020 till 31.12.2020.
5.3. Reference day for variables on livestock and animal housing
The reference day within the reference year 2020 (1 st of February 2020).
5.4. Reference period for variables on manure management
The 12-month period ending on 1 December 2020. The variables on manure management refer to a 12-month period including the reference day used for livestock and animal housing.
5.5. Reference period for variables on labour force
The 12-month period ending on 1 December 2020.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2020.
5.7. Reference day for all other variables
Not relevant.
6.1. Institutional Mandate - legal acts and other agreements
See sub-categories below.
6.1.1. National legal acts and other agreements
Legal act6.1.2. Name of national legal acts and other agreements
The National Statistics Act and the annual work programmes.
6.1.3. Link to national legal acts and other agreements
6.1.4. Year of entry into force of national legal acts and other agreements
1995
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
The Statistical Office of the Republic of Slovenia is only responsible institution for data on integrated farm statistics.
7.1. Confidentiality - policy
The National Statistics respect statistical confidentiality.
The National Statistics Act (hereinafter the ZDSta) stipulates within fundamental principles of national statistics in Article 2 that “national statistics shall be implemented on the principles of … confidentiality …”. The principle is concretized in further provisions of the ZDSta, while for explanation one can turn to some international documents. The United Nations Resolution on Fundamental Principles of Official Statistics (adopted by the UN Statistical Commission in 1994 and confirmed by the UN General Assembly on 29 January 2014) determines in Principle 6 that “individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes”. The explanation of the resolution is that reliable official statistics is based on the trust of the public and its good will to provide timely and accurate data that are requested. Such cooperation is only possible if statistical confidentiality is respected. In a similar way this principle is concretized in the European Statistics Code of Practice (adopted by the European Statistical System Committee on 28 September 2011), which determines that “the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and its use only for statistical purposes must be absolutely guaranteed“. And last but not least, item (e) of Article 2 of Regulation (EC) No. 223/2009 on European Statistics determines statistical confidentiality as “the protection of confidential data related to single statistical units which are obtained directly for statistical purposes or indirectly from administrative or other sources and implying the prohibition of use for non-statistical purposes of the data obtained and of their unlawful disclosure”.
7.2. Confidentiality - data treatment
See sub-categories below.
7.2.1. Aggregated data
See sub-categories below.
7.2.1.1. Rules used to identify confidential cells
Threshold rule (The number of contributors is less than a pre-specified threshold)p% rule (A contributor is able to derive an estimate of some other contributor within p% of its true value)
Secondary confidentiality rules
7.2.1.2. Methods to protect data in confidential cells
Other7.2.1.3. Description of rules and methods
The confidentiality issue was determined by the methodologists on protection in SURS and methodologists for farm structure survey.
Regarding protection of final output tables, two confidentiality rules were applied:
- "Threshold rule" - the individual cell in the table is protected if there are fewer than "t" reporting units.
- "P% rule"
Additionally, secondary data protection was applied to all tables.
Researchers must sign the contract with SURS, where confidentiality rules are included. Results intended for the export are later on reviewed by SURS concerning the statistical confidentiality.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
No7.2.2.2. Methods of perturbation
None7.2.2.3. Description of methodology
In the Statistical Office of the Republic of Slovenia, dissemination of statistically protected micro-data and sensitive tables (from the point of view of statistical confidentiality) to researchers is organised through the function of the Data Protection Committee, the advisory body of the Director General, in compliance with the system of rules and procedures related to the dissemination of statistically protected micro-data to researchers, and the use of software for the statistical protection of data.
Micro-data are not disseminated.
The micro-data are available according to special conditions to researchers for research purposes. Basic instructions concerning the access and the use of statistically protected micro-data are available on the web page: http://www.stat.si/StatWeb/en/StaticPages/Index/For-Researchers
SURS decided that researchers could gain access to micro-data in "Eurofarm data-set" (without precise location of individual agricultural holding). There will also be a possibility to gain other data on individual holding that are not in the "Eurofarm data-set", but each request will be dealt with individually. Researchers must sign the contract with SURS, where confidentiality rules are included. Results intended for the export are later on reviewed by SURS concerning the statistical confidentiality.
8.1. Release calendar
Releases of the Statistical Office of the Republic of Slovenia become available on working days always at 10:30 am. The release calendar enables searching for the titles of already published and announced releases. The release calendar is prepared and published in advance (usually in November for the next year). This applies to all regular publications, including for Integrated Farm Statistics. For the Integrated Farm Statistics data the the following announcements have been announced and realised for Integrated Farm Statistics data so far: 29.3. 2021 first, basic provisional data, 13.10. 2021 more detailed basic provisional data and 18.3.2022 final basic data for 2020.
8.2. Release calendar access
The release calendar can be accessed via the website of the Statistical Office of the Republic of Slovenia. On the release calendar website, publications can be searched by title, topic, sub-theme, publication date or producer.
8.3. Release policy - user access
The Dissemination and Communication Policy of the Statistical Office of the Republic of Slovenia (SURS) informs the users about the diverse supply of data, products and services provided by SURS. Also presented are the principles and standards considered in data publication and communication with final users of these data. Together with the European Statistics Code of Practice, the policy described on official website is the basic guideline for all SURS’s employees. SURS follows it in daily activities of publishing the data and communicating with users as well as in making long-term decisions.
8.3.1. Use of quality rating system
Yes, another quality rating system8.3.1.1. Description of the quality rating system
The Statistical Office of the Republic of Slovenia draws attention to less reliable estimates by flagging them with a special sign. If the table contains estimated population totals of (continuous) variables, estimated averages of continuous variables or estimated ratios of population totals of (continuous) variables, publishing limitations are determined by the relative standard errors or the coefficients of variation (CV). In such cases it holds:
- If the coefficient of variation (CV) is 10% or below (CV <= 10%), the estimate is reliable enough and is published without limitations; between 10% and up to 30% (10% < CV <= 30%), the estimate is less reliable and is flagged for caution with letter M; over 30% (CV > 30%), the estimate is too unreliable to be published and therefore suppressed for use by letter N. For more, see the general methodological explanations Precision of statistical estimates.
Data on Integrated Farm Statistics (IFS) are disseminated at national level after each IFS reference year. This is every 3-4 years.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
For the reference year 2020 have been published three news releases: 29.3. 2021 first, basic provisional data, 13.10. 2021 more detailed basic provisional data, 18.3.2022 final basic data for 2020 and 21.7.2022 final labour force and manure management data.
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
No10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
For the reference year 2020 have been published three news releases:
First data of Agricultural Census, Slovenia, 2020, SURS, 29.3.2021 (https://www.stat.si/statweb/en/News/Index/9459),
In 2020, almost a quarter of all land in Slovenia was used for agricultural production, SURS, 13.10. 2021 (https://www.stat.si/statweb/en/News/Index/9883) and Agricultural holdings in Murska Sobota with the largest average utilised agricultural area, SURS, 18.3.2022 (https://www.stat.si/statweb/en/News/Index/10211).
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
Not available.
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
The online database SiStat is accessible to users.
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
Yes10.5. Dissemination format - other
Not available.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
See sub-categories below.
10.6.1. Metadata completeness - rate
Not requested.
10.6.2. Availability of national reference metadata
Yes10.6.3. Title, publisher, year and link to national reference metadata
FARM STRUCTURE SURVEY AND AGRICULTURAL CENSUS, SURS, 2021, https://www.stat.si/StatWeb/File/DocSysFile/8048/15-119-ME.pdf
10.6.4. Availability of national handbook on methodology
No10.6.5. Title, publisher, year and link to handbook
Not applicable.
10.6.6. Availability of national methodological papers
No10.6.7. Title, publisher, year and link to methodological papers
Not applicable.
10.7. Quality management - documentation
Quality reports are prepared for national users and contain reference metadata and a detailed overview of quality components of the statistical survey (relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability, and coherence) together with the values of quality indicators. National Quality report for 2020 IFS data will be prepared in the year 2022. Document on quality report is published on the web page: http://www.stat.si/statweb/en/Methods/QuestionnairesMethodologicalExplanationsQualityReports
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Training coursesUse of best practices
Quality guidelines
Compliance monitoring
11.1.3. Description of the quality management system and procedures
The Statistical Office of the Republic of Slovenia operates on the basis of the National Statistics Act and Regulation (EC) No. 223/2009 on European statistics; in performing its tasks it follows the general principles of quality management, the European Statistics Code of Practice and the Fundamental Principles of Official Statistics. In line with the stated, SURS declares that it takes into account the following principles: professional independence, process orientation, quality of products and services, planning of improvements, stimulating working environment for employees, data providers-friendly official statistics, user-oriented official statistics. The principles are more in detail presented in the Quality Statement of the Statistical Office of the Republic of Slovenia.
The quality of statistical data used to be dealt with mostly in connection with data accuracy in the narrow sense (as coherence between statistical data and exact values). In the last decade the statistical profession has made great progress towards broader understanding of the quality of statistical data. Quality is now dealt with in terms of different quality dimensions: relevance, accuracy of estimates, timeliness and punctuality of publication, accessibility and clarity of information, comparability of statistics and coherence of results.
SURS regularly publishes reports on the quality of statistical surveys, which contain detailed descriptions of individual statistical surveys regarding all quality dimensions. Quality reports also contain the values of quality indicators, i.e. numerical values of achieved quality levels for individual quality components.
11.1.4. Improvements in quality procedures
Not available.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
The purpose of publishing the data on the structure of agricultural holdings in Slovenia is to present the structure of agricultural production, machinery and equipment and labour input, and the data on agricultural holdings that are comparable with the data of other EU Member States. Published key statistics are: Area and structure of agricultural and other land used on agricultural holdings, Area and structure of arable land, permanent grassland and permanent crops, Number and structure of livestock on agricultural holdings, Structure of the labour force on agricultural holdings and the scope of work in gainful activities on agricultural holdings, Livestock units (LSU), Economic size of agricultural holdings, Production type of agricultural holdings.
The key users of data are: Public sector, Business entities, Science, research and education, General public, Foreign users, Internal users.
12.1.1. Main groups of variables collected only for national purposes
National needs are discussed with main users represented in the Agricultural, Forestry and Fishery Statistics Committee, which is an advisory body of SURS.
Some of the characteristics were added to the questionnaire for national purposes only:
- some categories of livestock and crops are more detailed than needed in Eurofarm dataset;
- number of vines in vineyards – needed for calculation of production;
- cutting timber on family farms was implemented in FSS due to national needs.
12.1.2. Unmet user needs
User needs have been thoroughly evaluated and respected in the development/design/implementation of the product/service/system. Through extensive user research, feedback analysis, and a user-centric approach. We had several meetings with main users, where all the needs were addressed.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
SURS measured general user satisfaction. SURS measured general user satisfaction for the last time in 2021. Respondents assessed general satisfaction with SURS with the average score of 8.3 (on a scale from 1 – disagree completely to 10 – agree completely).
12.2.1. User satisfaction survey
Yes12.2.2. Year of user satisfaction survey
2021
12.2.3. Satisfaction level
Satisfied12.3. Completeness
Information on low- and zero prevalence variables is available on: Eurostat's website
12.3.1. Data completeness - rate
Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.
13.1. Accuracy - overall
See categories below.
13.2. Sampling error
See sub-categories below.
13.2.1. Sampling error - indicators
Please find the relative standard errors for the main variables in the annex.
Annexes:
13.2.1 Relative Standard Errors
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
There are no cases where estimated RSEs are above thresholds.
13.2.3. Reference on method of estimation
The method for estimation of RSEs was SAS PROC SURVEYMEANS procedure. We calculated standard errors and coefficients of variation, by using general SAS programs that are used in most of the SURS surveys.
13.2.4. Impact of sampling error on data quality
Moderate13.3. Non-sampling error
See sub-categories below.
13.3.1. Coverage error
See sub-categories below.
13.3.1.1. Over-coverage - rate
The over-coverage rate is available in the annex. The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
Annexes:
13.3.1.1. Over-coverage rate and Unit non-response rate
13.3.1.1.1. Types of holdings included in the frame but not belonging to the population of the core (main frame and if applicable frame extension)
None13.3.1.1.2. Actions to minimize the over-coverage error
Maintain of ineligible units in the records, recalculating weights of all units by considering the corrected population13.3.1.1.3. Additional information over-coverage error
Not available.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under-coverage error
See sub-categories below.
13.3.1.3.1. Under-coverage rate
Since we have quality administrative sources, we estimate that there is no under-coverage.
13.3.1.3.2. Types of holdings belonging to the population of the core but not included in the frame (main frame and if applicable frame extension)
None13.3.1.3.3. Actions to minimise the under-coverage error
Good and up to date administrative sources are available.
13.3.1.3.4. Additional information under-coverage error
Not available.
13.3.1.4. Misclassification error
Yes13.3.1.4.1. Actions to minimise the misclassification error
Misclassification was detected, but with such minor influence, so no action was performed.
13.3.1.5. Contact error
Yes13.3.1.5.1. Actions to minimise the contact error
The use of administrative data.
13.3.1.6. Impact of coverage error on data quality
Low13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
Characteristics that caused high measurement errors
We are aware of measurement errors and we try to avoid this kind of errors by training interviewers, supervisors, by data checking and validation process. Where inconsistency or extreme values were discovered, the data were checked with possible administrative data or there was also a “call-back” to the farmers, and the data were checked again. So extreme values of variables were checked and corrected if necessary. Since the data was inserted directly into the data entry program (controls were included), there was likely to have less mistakes caused by interviewer.
| Eurofarm variable | Variable description | Difficulties |
|---|---|---|
| A_3_3_1 | More than 50% of production self-consumed by the holder | Very difficult to assess for farmers - subjective estimation. |
| A_3_3_2 | More than 50% of sales are direct sales | Very difficult to assess for farmers - subjective estimation. |
| B_5_3 | Other land | Respondents' inability to provide accurate answers. |
| E_1_x | Farm work for each of the persons (AWU) | Sensitivity of the characteristic and subjective estimation. |
| F_2_1 | Importance of other gainful activities directly related to the holding | Sensitivity of the characteristic. Also quite difficult to assess for farmers - subjective estimation. |
| M_6_5_1 | Broadcast application of manure with no incorporation | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_5_2 | Broadcast application of manure with incorporation within 4 hours | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_5_3 | Broadcast application of manure with incorporation after 4 hours | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_6_1 | Bandspread application of manure with trailing hose | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_6_2 | Bandspread application of manure with trailing shoe | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_7_1 | Injection of manure on a shallow or open slot | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_6_7_2 | Injection of manure on a deep or closed slot | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_1_1 | Tillage: conventional | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_1_2 | Tillage: conservation | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_1_3 | Tillage: zero | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_2_1_1 | Soil cover: normal winter crop | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_2_1_2 | Soil cover: cover or intermediate crop | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_2_1_3 | Soil cover: plant residues | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_2_1_4 | Soil cover: bare soil | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
| M_2_1_5 | Outdoor arable land areas which are covered by multi-annual plants | New variable, introduced in 2016 and since it is not based on the area of crop (reported in IACS), it is quite difficult to assess for farmers. |
13.3.2.2. Causes of measurement errors
Complexity of variables13.3.2.3. Actions to minimise the measurement error
Training of enumerators13.3.2.4. Impact of measurement error on data quality
Moderate13.3.2.5. Additional information measurement error
Not available
13.3.3. Non response error
See sub-categories below.
13.3.3.1. Unit non-response - rate
The unit non-response rate is in the annex of item 13.3.1.1. The unit non-response rate is unweighted.
The unit non-response rate is calculated as the share of eligible non-respondent holdings to the eligible holdings. The eligible holdings include those holdings with unknown eligibility status which are imputed or re-weighted for (therefore considered eligible).
The unit non-response rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.3.1.1. Reasons for unit non-response
Failure to make contact with the unitRefusal to participate
Inability to participate (e.g. illness, absence)
13.3.3.1.2. Actions to minimise or address unit non-response
Follow-up interviewsReminders
Imputation
Weighting
13.3.3.1.3. Unit non-response analysis
By comparing the variables of respondents and non-respondents available in the sampling frame and with available administrative sources.
13.3.3.2. Item non-response - rate
No item non-response was detected, since CORE variables were collected mostly through administrative sources, and also with CATI, where application was strict (all the questions had to be answered and filled).
If there were minor casses, then they would be dealt with imputations.
13.3.3.2.1. Variables with the highest item non-response rate
Not applicable.
13.3.3.2.2. Reasons for item non-response
Not applicable13.3.3.2.3. Actions to minimise or address item non-response
Imputation13.3.3.3. Impact of non-response error on data quality
Moderate13.3.3.4. Additional information non-response error
Not available.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
CodingImputation methods
Data processing
13.3.4.2. Imputation methods
Mean imputationRandom hot deck imputation
Sequential hot deck imputation
Nearest neighbour imputation
13.3.4.3. Actions to correct or minimise processing errors
Application is used for imputations, so every step is defined and repeatable.
13.3.4.4. Tools and staff authorised to make corrections
There was only one person authorised to perform data processing. For data preparation also one IT staff was involved.
Special program, developed in SURS was used to perform imputations.
13.3.4.5. Impact of processing error on data quality
Moderate13.3.4.6. Additional information processing error
Not available.
13.3.5. Model assumption error
A model was used to asses labour input for holder-manager. The data on labour input was collected for cca. 17% of all agricultural holdings, and for all other the labour input was done with the model (it was based on gender, employment status, education, age, location).
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
The time lag of first results (months from 31 December 2020 to the day of the first release of first results) was 3 months.
14.1.2. Time lag - final result
The time lag of final results (months from 31 December 2020 to the day of the release of final results) was 18 months for core data and 21 months for module data.
14.2. Punctuality
See sub-categories below.
14.2.1. Punctuality - delivery and publication
See sub-categories below.
14.2.1.1. Punctuality - delivery
Not requested.
14.2.1.2. Punctuality - publication
The actual publication date coincides with the target date for data publication.
15.1. Comparability - geographical
See sub-categories below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable, because there are no mirror flows in Integrated Farm Statistics.
15.1.2. Definition of agricultural holding
See sub-categories below.
15.1.2.1. Deviations from Regulation (EU) 2018/1091
Data on agricultural holdings collected and sent to Eurostat had the same definition than in Regulation (EU) 2018/1091.
15.1.2.2. Reasons for deviations
Not applicable.
15.1.3. Thresholds of agricultural holdings
See sub-categories below.
15.1.3.1. Proofs that the EU coverage requirements are met
Since the IFS thresholds from Annex II of Regulation (EU) 2018/1091 were quite high for our country, we extended the frame, where also very small farms were surveyed. For that reason it is no doubt that EU coverage requirements are met.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
National threshold contains all the area as the IFS threshold except vineyard area. Concerning the vineyard area, national threshold is 0.3 ha and the IFS is 0.1 ha. For that reason some 3.000 agricultural holding were added to population.
National threshold for animal data collection is 2 LSU (including equidae), IFS has 1.7 LSU. For that reason only few agricultural holdings were added to population.
On the other hand national threshold for UAA is 1 ha, but IFS threshold is 5 ha. When taking into consideration all agricultural holdings, some 18 000 are considered agricultural holdings on national level, but on the EU level they are under thresholds.
15.1.3.3. Reasons for differences
See point 15.1.3.2.
15.1.4. Definitions and classifications of variables
See sub-categories below.
15.1.4.1. Deviations from Regulation (EU) 2018/1091 and EU handbook
Definitions are the same, but national publication has some different classification, due to a lower disaggregation of arable land and livestock categories.
The thresholds used to include holdings for national dissemination are different than the EU ones. Also LSU coefficients for national dissemination are different.
The thresholds for national dissemination are:
1. a) at least one hectare of utilised agricultural area, or
2. b) less than 1 hectare of utilised agricultural area, but:
- at least 0.1 hectare of utilised agricultural area and 0.9 hectare of forest, or
- at least 0.3 hectares of vineyards and/or orchards, or
- two or more livestock units (LSU), or
- 0.15 to 0.3 hectare of vineyards/orchards and 1 or 2 LSU, or
- more than 50 beehives, or
- are market producers of vegetables, herbs, strawberries, mushrooms, flowers or ornamental plants.
The thresholds for EU dissemination are presented in the annex to item 3.6.1 of the quality report.
Table 1: List of livestock unit coefficients (LSU) used in Slovenia, by years
|
|
2000 |
2003 |
2005 |
2007 |
2010 |
2013 |
2016 |
2020 |
| CATTLE |
|
|
|
|
|
|
|
|
| Young cattle under 1 year |
|
|
|
|
|
|
|
|
| Calves for slaughter (young bulls) |
0.15 |
0.15 |
0.15 |
0.285 |
0.2836 |
0.2826 |
0.2831 |
0.2864 |
| Calves for slaughter (young heifers) |
0.15 |
0.15 |
0.15 |
0.289 |
0.2885 |
0.2880 |
0.2881 |
0.2918 |
| Calves for fattening (young bulls) |
0.3 |
0.3 |
0.3 |
0.285 |
0.2836 |
0.2826 |
0.2831 |
0.2864 |
| Calves for fattening (young heifers) |
0.3 |
0.3 |
0.3 |
0.289 |
0.2885 |
0.2880 |
0.2881 |
0.2918 |
| Young cattle, 1 to 2 years |
|
|
|
|
|
|
|
|
| Breeding heifers |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
| Heifers for fattening |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
| Bulls, oxen |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
| Cattle over 2 years old |
|
|
|
|
|
|
|
|
| Breeding heifers |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Heifers for fattening |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Dairy cows |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Suckling cows |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Bulls for breeding |
1.4 |
1.4 |
1.4 |
1.065 |
1 |
1 |
1 |
1 |
| Bulls and oxen for fattening |
1 |
1 |
1 |
1.065 |
1 |
1 |
1 |
1 |
| PIGS |
|
|
|
|
|
|
|
|
| Piglets under 20 kg, suckling |
0.02 |
0.008 |
0.008 |
0.008 |
0.008 |
0.008 |
0.008 |
0.008 |
| Piglets under 20 kg, other |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
|
|
| Pigs under 30 kg |
|
|
|
|
|
|
|
0.02 |
| Fattening pigs, ower 30 kg |
|
|
|
|
|
|
|
0.19 |
| Young pigs, 20 to 50 kg |
0.07 |
0.07 |
0.07 |
0.07 |
0.07 |
0.07 |
0.07 |
|
| Fattening pigs, 50 to 80 kg |
0.13 |
0.13 |
0.13 |
0.13 |
0.13 |
0.13 |
0.13 |
|
| Fattening pigs, 80 to 110 kg |
0.19 |
0.19 |
0.19 |
0.19 |
0.19 |
0.19 |
0.19 |
|
| Fattening pigs, 110 kg or over |
0.24 |
0.24 |
0.24 |
0.24 |
0.24 |
0.24 |
0.24 |
|
| Breeding pigs (50 kilograms or over) |
|
|
|
|
|
|
|
|
| Boars |
0.34 |
0.34 |
0.34 |
0.34 |
0.34 |
0.34 |
0.34 |
0.34 |
| Gilts not yet mated |
0.2 |
0.2 |
0.2 |
0.2 |
0.2 |
0.2 |
0.2 |
|
| Gilts mated for the first time |
0.23 |
0.23 |
0.23 |
0.23 |
0.23 |
0.23 |
0.23 |
|
| Sows not yet mated |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
|
| Mated sows |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
0.32 |
|
| Breeding sows (also gilts) |
|
|
|
|
|
|
|
0.32 |
| POULTRY |
|
|
|
|
|
|
|
|
| Layers |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
| Chickens for fattening |
0.0025 |
0.0025 |
0.0025 |
0.0025 |
0.0025 |
0.0025 |
0.0025 |
0.0025 |
| Other hens (cocks, spring chickens) |
0.005 |
0.005 |
0.005 |
0.005 |
0.005 |
0.005 |
0.005 |
0.005 |
| Turkeys |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
0.02 |
| Geese and ganders |
0.01 |
0.01 |
0.01 |
0.01 |
0.01 |
0.01 |
0.01 |
0.01 |
| Ducks and drakes |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
0.004 |
| Guinea fowl |
0.0035 |
0.0035 |
0.0035 |
0.0035 |
0.0035 |
0.0035 |
0.0035 |
0.0035 |
| Ostriches |
0.25 |
0.25 |
0.25 |
0.25 |
0.25 |
0.25 |
0.25 |
0.25 |
| Quails |
0.0003 |
0.0003 |
0.0003 |
0.0003 |
0.0003 |
0.0003 |
0.0003 |
0.0003 |
| Other poultry |
0.003 |
0.003 |
0.003 |
0.003 |
0.003 |
0.003 |
0.003 |
0.003 |
| RABBITS |
|
|
|
|
|
|
|
|
| Breeding rabbits, females |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
| Breeding rabbits, males |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
0.006 |
| Rabbits for fattening |
0.0024 |
0.0024 |
0.0024 |
0.0024 |
0.0024 |
0.0024 |
0.0024 |
0.0024 |
| HORSES |
|
|
|
|
|
|
|
|
| Foals, under 1 year |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
| Young horses (1 – 3 years old) |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Mares and fillies in foal |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Stallions and draught horses |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| Ponies |
/ |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
0.5 |
| Other horses |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
| SHEEP |
|
|
|
|
|
|
|
|
| Lambs and young sheep |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| Breeding sheep: |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
| Milk ewe lambs put to the ram for the first time |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Other ewe lams put to the ram for the first time |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Milk ewes that have already lambed |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Other ewes that have already lambed |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Rams |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
| Barren sheep |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
| GOATS |
|
|
|
|
|
|
|
|
| Goatlings and young goats |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| Breeding goats: |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
| Milk goats mated for the first time |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Other goats mated for the first time |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Milk goats that have already kidded |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| Other goats that have already kidded |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
/ |
/ |
/ |
| He-goats |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
0.15 |
| Barren goats |
0.11 |
0 |
0 |
0 |
0.14 |
0.14 |
0.14 |
0.14 |
| HONEY BEE COLONIES |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| FALLOW DEER |
0.1 |
0.1 |
0.1 |
0.1 |
0.1 |
0.1 |
0.1 |
0.1 |
| ORDINARY DEER |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
0.14 |
| LAME |
/ |
/ |
/ |
/ |
0.25 |
/ |
/ |
/ |
| CHINCHILLAS |
/ |
/ |
/ |
/ |
0.001 |
/ |
/ |
/ |
In 2020, there are no holdings in the classes FARM_SPOU (Manager is spouse of holder), FARM_HLD_SPOUFAM (Holder is co-manager with spouse or family member), FARM_FAM (Manager is member of holder's family) and FARM_NFAM (Manager is not member of holder's family) as these are included in the class FARM_HLD (Holder is single manager). Please see item 15.1.4.2 for the reason.
15.1.4.1.1. The number of working hours and days in a year corresponding to a full-time job
The information is available in the annex.
The number of working hours and days in a year for a full-time job correspond to one annual working unit (AWU) in the country. One annual work unit corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis. Annual working units are used to calculate the farm work on the agricultural holdings. One AWU is considered as 1800 working hours.
Annexes:
15.1.4.1.1. AWU
15.1.4.1.2. Point chosen in the Annual work unit (AWU) percentage band to calculate the AWU of holders, managers, family and non-family regular workers
The information is available in the annex of item 15.1.4.1.1.
National publication for AWU is calculated on exact working hours per year and not size classes.
15.1.4.1.3. AWU for workers of certain age groups
The information is available in the annex of item 15.1.4.1.1.
15.1.4.1.4. Livestock coefficients
In Slovenia we are using different LSU coefficients for national data dissemination. The coefficients used are listed in our metadata information on website: https://www.stat.si/statweb/File/DocSysFile/8048/15-119-ME.pdf.
Also see 15.1.4.1.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
Included are Equidae, breeding rabbits, lama and alpaca.
15.1.4.2. Reasons for deviations
Definitions are the same, but classifications are not, since some categories in IFS are grouped, and in national publications they are not.
In 2020, the classes FARM_HLD (Holder is single manager), FARM_SPOU (Manager is spouse of holder), FARM_HLD_SPOUFAM (Holder is co-manager with spouse or family member), FARM_FAM (Manager is member of holder's family) and FARM_NFAM (Manager is not member of holder's family) are all grouped under the class FARM_HLD (Holder is single manager). According to the new administrative rules in Slovenia, the person reported as being the holder of the farm is also considered to be responsible for farm management.
The thresholds used to include holdings for the national dissemination are different than the thresholds for EU dissemination, because it was decided at national level to keep the same thresholds for 2000, 2010 and 2020 as much as possible due to time comparison.
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
Not applicable.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land exists15.1.6.1. Collection of common land data
Yes15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Common land is included in the land of agricultural holdings based on a statistical model.15.1.6.4. Source of collected data on common land
Administrative sources15.1.6.5. Description of methods to record data on common land
We use administrative data of the Ministry of Agriculture, Forestry and Food. Common land is included in the land use data of the agricultural holdings making use of the common land - “In proportion to the use by each holding".
The area of common land was not double counted, because the data on common land were gathered from administrative data, and divided in proportion to each holding (on the basis of the LSU). Holders reported land use without common land.
The area of common land consists only of pastures (rough grazing).
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
Not applicable.
15.1.7. National standards and rules for certification of organic products
See sub-categories below.
15.1.7.1. Deviations from Council Regulation (EC) No 834/2007
There are no differences detected.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
Not applicable.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
The results are comparable for years 2000, 2003, 2007, 2010, 2013, 2016 and for this year (2020).
15.2.2. Definition of agricultural holding
See sub-categories below.
15.2.2.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series15.2.2.2. Description of changes
Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However our country does not raise fur animals.
15.2.3. Thresholds of agricultural holdings
See sub-categories below.
15.2.3.1. Changes in the thresholds of holdings for which core data are sent to Eurostat since the last data transmission
There have been sufficient changes to warrant the designation of a break in series15.2.3.2. Description of changes
The national threshold is not the same as the IFS threshold, therefore frame extention was made.
Due to different threshold some 3.000 AH were added to the population (the reason is lower threshold for vineyard area).
15.2.4. Geographical coverage
See sub-categories below.
15.2.4.1. Change in the geographical coverage since the last data transmission to Eurostat
There have been no changes15.2.4.2. Description of changes
Not applicable.
15.2.5. Definitions and classifications of variables
See sub-categories below.
15.2.5.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series15.2.5.2. Description of changes
Legal personality of the agricultural holding
In IFS, the legal provisions foresee a new class (“shared ownership”) for the legal personality of the holding compared to FSS 2016. This new class (FARM_HLD_SPOUFAM - Holder is co-manager with spouse or a family member) was not collected due to national situation.
In 2016, the holder was not always the manager. However this changed in 2020, when the person reported as being the holder of the farm is also considered to be responsible for farm management. Therefore, while the 2016 data distinguish between the categories "Holder is single manager", "Manager is spouse of holder", "Manager is member of holder's family" and "Manager is not member of holder's family" , in 2020 all such holdings are grouped under the class "Holder is single manager".
Other livestock n.e.c.
In FSS 2016, deer were included in this class, but in IFS they are classified separately.
Also in FSS 2016, there was a class for the collection of equidae. That has been dropped and equidae are included in IFS in "other livestock n.e.c."
Livestock units
In FSS 2016, turkeys, ducks, geese, ostriches and other poultry were considered each one in a separate class with a coefficient of 0.03 for all the classes except for ostriches (coefficient 0.035). In IFS 2020, the coefficients were adjusted accordingly, with turkeys remaining at 0.03, ostriches remaining at 0.35, ducks adjusted to 0.01, geese adjusted to 0.02 and other poultry fowls n.e.c. adjusted to 0.001.
Organic animals
While in FSS only fully compliant (certified converted) animals were included, in IFS both animals under conversion and fully converted are to be included.
15.2.6. Reference periods/days
See sub-categories below.
15.2.6.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series15.2.6.2. Description of changes
In previous FSS 2016 reference period for labour force was 12 months ending on 31 May of reference year, but for IFS 2020 the data was collected in December 2020, looking 1 year before 1 December.
In previous FSS 2016 reference period for livestock was 1 June. For AC 2020 it was 1 February.
In previous FSS 2016 reference period for land variables was 12 months ending on 1 June 2016 while in IFS 2020, it ended on 31 December 2020.
In previous FSS 2016 reference period for rural development variables was 36 months ending on 1 June 2016 while in IFS 2020, it ended on 31 December 2020.
15.2.7. Common land
See sub-categories below.
15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no changes15.2.7.2. Description of changes
Not applicable.
15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat
Some statistics have such small area or small number (occurrence) that there are not easy for the trends to be very big. Also some animals can variate from one category to another in four years time. Also the reason is, due to subsidy reason (administrative support) for farms.
With regards to the evolution of the number of holdings by LSU class, it was recorded an increase of holdings without LSU, and of those with LSU<5. The reason for those trends are evolving farms, since some are specialising, and the second reason in for including the vineyard threshold 0.1ha, since we have there cca. 5% increase of farmers who have only vineyard and nothing else.
15.2.9. Maintain of statistical identifiers over time
No15.3. Coherence - cross domain
See sub-categories below.
15.3.1. Coherence - sub annual and annual statistics
Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.
15.3.2. Coherence - National Accounts
Not applicable, because Integrated Farm Statistics have no relevance for national accounts.
15.3.3. Coherence at micro level with data collections in other domains in agriculture
See sub-categories below.
15.3.3.1. Analysis of coherence at micro level
Yes15.3.3.2. Results of analysis at micro level
The results of the 2020 were checked and compared with all the available administrative data. Actually a lot of administrative data was used directly from administrative sources. The results were checked partially also with other statistical data collections (Annual Crop Statistics, Animal Production Statistics).
15.3.4. Coherence at macro level with data collections in other domains in agriculture
See sub-categories below.
15.3.4.1. Analysis of coherence at macro level
Yes15.3.4.2. Results of analysis at macro level
The results of the 2020 were checked and compared with all the available administrative data, previous surveys and other surveys conducted by SURS. A comparison was made with other sources at macro-data level. The data is comparable and all minor differences can be explained.
All surveys in agricultural statistics department can be combined and compared between themselves.
Comparison to other statistical domains can be done on macro level.
15.4. Coherence - internal
The data are internally consistent. This is ensured by the application of a wide range of validation rules.
See sub-categories below.
16.1. Coordination of data collections in agricultural statistics
All agricultural statistics are produced in the same department and there is a good coordination of surveys to avoid situation that some farms have to answer multiple questionnaires with the same kind of questions (ex. a small part of data for annual crop statistics is retained from FSS).
16.2. Efficiency gains since the last data transmission to Eurostat
Further automationIncreased use of administrative data
16.2.1. Additional information efficiency gains
Not available.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Not relevant
16.3.2. Module ‘Labour force and other gainful activities‘
Not available
16.3.3. Module ‘Rural development’
Not applicable (use of administrative data source).
16.3.4. Module ‘Animal housing and manure management’
Not available.
16.3.5. Module ‘Irrigation’
Not applicable for 2019/2020.
16.3.6. Module ‘Soil management practices’
Not applicable for 2019/2020.
16.3.7. Module ‘Machinery and equipment’
Not applicable for 2019/2020.
16.3.8. Module ‘Orchard’
Not applicable for 2019/2020.
16.3.9. Module ‘Vineyard’
Not applicable for 2019/2020.
17.1. Data revision - policy
SURS has a data revision policy and a scheduled revision program of the preliminary form to final which is published on the website.
17.2. Data revision - practice
The revision policy for the 2020 agricultural census data was reasoned with the program of the data dissemination form from preliminary to final data.
17.2.1. Data revision - average size
Not requested.
Annexes:
18. Timetable of statistical process
18.1. Source data
See sub-categories below.
18.1.1. Sampling design & Procedure frame
See sub-categories below.
18.1.1.1. Type of frame
List frame18.1.1.2. Name of frame
The Statistical Farm Register.
18.1.1.3. Update frequency
Annual18.1.2. Core data collection on the main frame
See sub-categories below.
18.1.2.1. Coverage of agricultural holdings
Census18.1.2.2. Sampling design
Not applicable for 2020.
18.1.2.2.1. Name of sampling design
Not applicable18.1.2.2.2. Stratification criteria
Not applicable18.1.2.2.3. Use of systematic sampling
Not applicable18.1.2.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.2.2.5. Method of determination of the overall sample size
Not applicable for 2020.
18.1.2.2.6. Method of allocation of the overall sample size
Not applicable18.1.3. Core data collection on the frame extension
See sub-categories below.
18.1.3.1. Coverage of agricultural holdings
Census18.1.3.2. Sampling design
Not applicable.
18.1.3.2.1. Name of sampling design
Not applicable18.1.3.2.2. Stratification criteria
Not applicable18.1.3.2.3. Use of systematic sampling
Not applicable18.1.3.2.4. Full coverage strata
Not applicable.
18.1.3.2.5. Method of determination of the overall sample size
Not applicable.
18.1.3.2.6. Method of allocation of the overall sample size
Not applicable18.1.4. Module “Labour force and other gainful activities”
See sub-categories below.
18.1.4.1. Coverage of agricultural holdings
Sample18.1.4.2. Sampling design
Stratification was made based on NUTS2 level, four size classes of agricultural holdings +agricultural enterprises.
18.1.4.2.1. Name of sampling design
Stratified one-stage random sampling18.1.4.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.4.2.3. Use of systematic sampling
Yes18.1.4.2.4. Full coverage strata
Full coverage strata are agricultural enterprises, and big family farms in Slovenia.
18.1.4.2.5. Method of determination of the overall sample size
The sample size was determined by making experimental samples different sizes and estimating differente response rate. Then RSE was calcualted on different variables.
18.1.4.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable18.1.5. Module “Rural development”
See sub-categories below.
18.1.5.1. Coverage of agricultural holdings
Census18.1.5.2. Sampling design
Not applicable.
18.1.5.2.1. Name of sampling design
Not applicable18.1.5.2.2. Stratification criteria
Not applicable18.1.5.2.3. Use of systematic sampling
Not applicable18.1.5.2.4. Full coverage strata
Not applicable.
18.1.5.2.5. Method of determination of the overall sample size
Not applicable.
18.1.5.2.6. Method of allocation of the overall sample size
Not applicable18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.6. Module “Animal housing and manure management module”
See sub-categories below.
18.1.6.1. Coverage of agricultural holdings
Sample18.1.6.2. Sampling design
Stratification was made based on NUTS2 level, four size classes of agricultural holdings +agricultural enterprises.
18.1.6.2.1. Name of sampling design
Stratified one-stage random sampling18.1.6.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.6.2.3. Use of systematic sampling
Yes18.1.6.2.4. Full coverage strata
Full coverage strata are agricultural enterprises, and big family farms in Slovenia.
18.1.6.2.5. Method of determination of the overall sample size
The sample size was determined by making experimental samples different sizes and estimating differente response rate. Then RSE was calcualted on different variables.
18.1.6.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.7. Module ‘Irrigation’
See sub-categories below.
18.1.7.1. Coverage of agricultural holdings
Not applicable18.1.7.2. Sampling design
Not applicable for 2019/2020.
18.1.7.2.1. Name of sampling design
Not applicable18.1.7.2.2. Stratification criteria
Not applicable18.1.7.2.3. Use of systematic sampling
Not applicable18.1.7.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.7.2.5. Method of determination of the overall sample size
Not applicable for 2019/2020.
18.1.7.2.6. Method of allocation of the overall sample size
Not applicable18.1.7.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.8. Module ‘Soil management practices’
See sub-categories below.
18.1.8.1. Coverage of agricultural holdings
Not applicable18.1.8.2. Sampling design
Not applicable for 2019/2020.
18.1.8.2.1. Name of sampling design
Not applicable18.1.8.2.2. Stratification criteria
Not applicable18.1.8.2.3. Use of systematic sampling
Not applicable18.1.8.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.8.2.5. Method of determination of the overall sample size
Not applicable for 2019/2020.
18.1.8.2.6. Method of allocation of the overall sample size
Not applicable18.1.8.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.9. Module ‘Machinery and equipment’
See sub-categories below.
18.1.9.1. Coverage of agricultural holdings
Not applicable18.1.9.2. Sampling design
Not applicable for 2019/2020.
18.1.9.2.1. Name of sampling design
Not applicable18.1.9.2.2. Stratification criteria
Not applicable18.1.9.2.3. Use of systematic sampling
Not applicable18.1.9.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.9.2.5. Method of determination of the overall sample size
Not applicable for 2019/2020.
18.1.9.2.6. Method of allocation of the overall sample size
Not applicable18.1.9.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.10. Module ‘Orchard’
See sub-categories below.
18.1.10.1. Coverage of agricultural holdings
Not applicable18.1.10.2. Sampling design
Not applicable for 2019/2020.
18.1.10.2.1. Name of sampling design
Not applicable18.1.10.2.2. Stratification criteria
Not applicable18.1.10.2.3. Use of systematic sampling
Not applicable18.1.10.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.10.2.5. Method of determination of the overall sample size
Not applicable for 2019/2020.
18.1.10.2.6. Method of allocation of the overall sample size
Not applicable18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.11. Module ‘Vineyard’
See sub-categories below.
18.1.11.1. Coverage of agricultural holdings
Not applicable18.1.11.2. Sampling design
Not applicable for 2019/2020.
18.1.11.2.1. Name of sampling design
Not applicable18.1.11.2.2. Stratification criteria
Not applicable18.1.11.2.3. Use of systematic sampling
Not applicable18.1.11.2.4. Full coverage strata
Not applicable for 2019/2020.
18.1.11.2.5. Method of determination of the overall sample size
Not applicable for 2019/2020.
18.1.11.2.6. Method of allocation of the overall sample size
Not applicable18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.12. Software tool used for sample selection
SAS programm.
18.1.13. Administrative sources
See sub-categories below.
18.1.13.1. Administrative sources used and the purposes of using them
The information is available on Eurostat's website.
18.1.13.2. Description and quality of the administrative sources
See the attached Excel file in the Annex.
Annexes:
18.1.13.2. Description and quality of the administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
Problems related to data quality of the sourceThe final validated data in the source would not be in time to meet statistical deadlines or would relate to a period which does not coincide with the reference period
18.1.14. Innovative approaches
The information on innovative approaches is available on Eurostat's website.
18.2. Frequency of data collection
The agricultural census is conducted every 10 years. The decennial agricultural census is complemented by sample or census-based data collections organised every 3-4 years in-between.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Postal, non-electronic versionTelephone, electronic version
Other
18.3.2. Data entry method, if paper questionnaires
Manual18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3. Agricultural census CORE
18.3.3. Agricultural census Labour force and livestock facilities
18.3.3. Agricultural census 2020_SI
18.3.3. Agricultural census labour force and livestock facilities_SI
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Data format checksCompleteness checks
Range checks
Relational checks
Data flagging
18.4.2. Staff involved in data validation
Staff from central department18.4.3. Tools used for data validation
The data were validated at the national level by using SAS programs and the application built by SURS.
18.5. Data compilation
The extrapolating factor was obtained based on the design weight and adjusted for non-response.
Weights were calculated as product of selection weight and non-response weight only. The sample survey for labour force module and module on animal housing was not calibrated to the number of agricultural holdings from the census core.
18.5.1. Imputation - rate
Agricultural census 2020 was mostly based on administrative sources and for that reason imputation rates are very difficult to calculate.
18.5.2. Methods used to derive the extrapolation factor
Design weightNon-response adjustment
18.6. Adjustment
Covered under Data compilation.
18.6.1. Seasonal adjustment
Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.
See sub-categories below.
19.1. List of abbreviations
CAP – Common Agricultural Policy
CAPI – Computer Assisted Personal Interview
CATI – Computer Assisted Telephone Interview
CAWI – Computer Assisted Web Interview
FSS – Farm Structure Survey
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LSU – Livestock units
NACE – Nomenclature of Economic Activities
NUTS – Nomenclature of territorial units for statistics
PAPI – Paper and Pencil Interview
SiStat - Statistical Office of the Republic of Slovenia
SO – Standard output
SURS - Statistical office of the Republic of Slovenia
UAA – Utilised agricultural area
19.2. Additional comments
No additional comments.
The data describe the structure of agricultural holdings providing the general characteristics of agricultural holdings and manager of the agricultural holding and information on their land and livestock. They also describe production methods, rural development measures, labour force and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the structure and state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
31 May 2024
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2019/2020 are set in Commission Implementing Regulation (EU) 2018/1874.
The following groups of variables are collected in 2020:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module "Animal housing and rural development module": animal housing, nutrient use and manure on the farm, manure application techniques, facilities for manure.
See sub-category below.
See sub-categories below.
See sub-categories below.
See sub-categories below.
See categories below.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
The extrapolating factor was obtained based on the design weight and adjusted for non-response.
Weights were calculated as product of selection weight and non-response weight only. The sample survey for labour force module and module on animal housing was not calibrated to the number of agricultural holdings from the census core.
See sub-categories below.
Data on Integrated Farm Statistics (IFS) are disseminated at national level after each IFS reference year. This is every 3-4 years.
See sub-categories below.
See sub-categories below.
See sub-categories below.
