1.1. Contact organisation
Statistical Office of the Slovak Republic
1.2. Contact organisation unit
Business Statistics Directorate / Agricultural Statistics Department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Statistical Office of the Slovak Republic
Lamačská cesta 3/C
P.O.BOX 17
840 05 Bratislava 45
Slovak Republic
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
17 February 2025
2.2. Metadata last posted
6 March 2025
2.3. Metadata last update
17 February 2025
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures 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 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 2019/2020 (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) 2021/2286.
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 gross margin (SGM) (until 2007) or 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 gross margin or the standard output of the holding.
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 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- 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 “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings;
- for the module “Orchards”: apples area by age of plantation and density of trees.
3.5. Statistical unit
See sub-category below.
3.5.1. Definition of agricultural holding
The agricultural holding is 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: Growing of non-perennial crops.
- A.01.2: Growing of perennial crops.
- A.01.3: Plant propagation.
- A.01.4: Animal production.
- A.01.5: Mixed farming or.
- 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
No3.6.2. Population covered by the data sent to Eurostat for the modules “Labour force and other gainful activities”, “Rural development” and “Machinery and equipment”
The same population of agricultural holdings defined in item 3.6.1.
3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”
Restricted from publication
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
The subset of agricultural holdings defined in item 3.6.2 with irrigable area.
3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
The subset of agricultural holdings defined in item 3.6.2 with arable land and/or with some elements of ecological focus areas (terraces, field margins, agroforestry, etc.) or drainage.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
The subset of agricultural holdings defined in item 3.6.2, with any of the individual orchard variables that meet the threshold specified in Article 7(5) of Regulation (EU) 2018/1091.
3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Restricted from publication
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 productionThe location where all agricultural activities are situated
The majority of the area of the holding
The most important parcel by physical size
The residence of the farmer (manager) not further than 5 km straight from the farm
3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Farm structure statistics in our country cover the period from 2001 onwards. Older time series are described in the previous quality reports (national methodological reports).
3.9. Base period
The 2023 data are processed (by Eurostat) with 2020 standard output coefficients (calculated as a 5-year average of the period 2018-2022). 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 12-month period for the land variables ending on 31 October within the reference year 2023. 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.
5.2. Reference period for variables on irrigation and soil management practices
The 12-month period ending on 31 October within the reference year 2023.
5.3. Reference day for variables on livestock and animal housing
The reference day 31 October within the reference year 2023 for the livestock variables. Not applicable for the animal housing variables for 2023.
5.4. Reference period for variables on manure management
The manure management variables are not applicable for 2023.
5.5. Reference period for variables on labour force
The 12-month period ending on 31 October within the reference year 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2023.
5.7. Reference day for all other variables
The reference day 31 October within the reference year 2023.
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
Act No 540/2001 on State Statistics (section 16);
Decree of the Statistical Office No 292/2020, which issues the Program of state statistical surveys for the years 2021-2023.
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
2002 for the Act No 540/2001 on State Statistics;
2021 for the Decree of the Statistical Office No 292/2020.
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
The Statistical Office of the Slovak Republic is the central state administration body for state statistics; it is responsible for its development, production and dissemination. It is established a Coordination Council for State Statistics to ensure the performance of the tasks related to the official state statistics. The members of the Coordination Council shall be representatives of all bodies carrying out state statistics. The Chairperson of the Coordination Council shall be the President of the Statistical Office. Other bodies carrying out state statistics shall perform the tasks of state statistics to the extent resulting for them from the programme of state statistical surveys. In the production of state statistics, another body carrying out state statistics shall be guided by the methodological instructions of the Statistical Office of the Slovak Republic.
To the extent necessary to achieve the statistical purpose and within the scope of its subject matter competence, the body carrying out state statistics shall have the right of access to data from all administrative data sources. The administrator of the administrative data source shall provide the data from the administrative data source to the bodies carrying out state statistics without delay and free of charge in electronic form and in the required structure on the basis of a written request. The administrator of the administrative data source shall provide metadata for the data provided together with the data from the administrative data source.
Furthermore, there was concluded the agreement between the Statistical Office of the Slovak Republic and other state organisations in order to secure the mutual data exchange.
7.1. Confidentiality - policy
Data protection is governed by the following legislative act, internal directives (SME) and methodological direction (MET) of the Statistical Office of the SR:
- Act No 540/2001 on State Statistics (sections 29-33);
- SME-1/2021 - Protection of personal data within the scope of the Statistical Office of the Slovak Republic;
- SME-1/2015 - Protection of confidential statistical data
- MET-7/2023 - Protection of confidential statistical data.
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)Secondary confidentiality rules
7.2.1.2. Methods to protect data in confidential cells
Cell suppression (Completely suppress the value of some cells)7.2.1.3. Description of rules and methods
When ensuring the protection of confidential statistical data in tables with aggregated data, the SO SR applies in all cases the minimum frequency rule with a set value equal to 3. The cell is confidential when the frequency of respondents is less than 3.
The secondary confidentiality is applied to protect primary confidential data. We consider the secondary confidential data to be those data which can indirectly identify the primary confidential data based on the calculation of the value of the variable. For the purposes of identification and protection of the confidential data, we used the tools such as τ-ARGUS, MS Excel or MS Access.
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
The Act on State Statistics does not allow an access to confidential data for usual users. The Statistical Office of the SR may provide confidential data for scientific purposes to legal persons, who carry out scientific research as their basic mission and are able to ensure conditions for the data protection.
Data are provided in the form:
a) complete confidential data; those are provided only to the state authorities (for example ministries, national banks, etc.) based on the mutual contract and within the data exchange through the secured FTP server;
b) anonymised data which do not allow direct identification of legal or physical persons; to other organisations than the state authorities.
8.1. Release calendar
There is a release calendar of publications for Integrated Farm Statistics. There is no release calendar for datasets.
8.2. Release calendar access
8.3. Release policy - user access
Policy on dissemination of the statistical information of the Statistical Office of the Slovak Republic (hereinafter referred to as “Policy on dissemination”) is a fundamental document in the field of statistical information dissemination. It represents a set of principles applied by the Statistical Office of the SR in dissemination of the statistical information.
The Policy on dissemination is defined in accordance with the Act on State Statistics, the development strategy of the Statistical Office of the SR, the information dissemination strategy of Eurostat and European Statistics Code of Practice.
The principles of dissemination policy are reflected in the Principles of Publication and Provision of Statistical Information, which establish binding principles and procedures for the publication and provision of statistical information and the compilation of the Catalogue of Publications, taking into account existing requirements of the quality management system of the Statistical Office. The main principles of the dissemination policy are: we guarantee equal access to statistical information for all users. We provide standard statistical information free of charge. We publish timely statistical information according to the time schedule / calendar of the first issue. Only statistical criteria are decisive for the assessment of objectivity.
We have sole responsibility for deciding on statistical methods, standards and procedures, as well as on the content and timing of the publication of statistical information. We guarantee the protection of confidential data provided by survey units. Confidential data shall be provided exclusively under the conditions laid down by the Act on State Statistics in a form that does not allow direct or indirect identification of reporting agents. We communicate with users about the value of statistical information. The same principles apply to the publication of IFS 2023 data.
8.3.1. Use of quality rating system
No8.3.1.1. Description of the quality rating system
Not applicable.
The frequency of dissemination of the agricultural census data is every 10 years. Every 3-4 years are disseminated the data on farm structural survey / integrated farm survey which are not collected on the census basis.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
No10.1.2. Link to news releases
Not applicable.
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
Yes, in English also10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
We are going to publish 2 publications (planned in October 2025):
1) Farms in Slovakia in the year 2023 – Basic indicators (Results of the Integrated farm statistics 2023)
2) Farms in Slovakia in the year 2023 – Typology (Results of the Integrated farm statistics 2023)
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
For the period 1 January 2023 - 20 January 2025, there has been the following number of accesses:
- Počet fariem podľa typu a triedy ekonomickej veľkosti [pl3803rr]: 100
Number of farms by type and economic size of unit [pl3803rr] (EN version): 10
- Počet fariem podľa veľkosti obhospodarovanej pôdy [pl3804rr]: 77
Classification of farms by size of cultivated agricultural land [pl3804rr] (EN version): 13
- Triedenie fariem podľa počtu zvierat k 31.10. [pl3805rr]: 76
Classification of farms by number of animals as of 31.10. [pl3805rr] (EN version): 10
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
General website to Datacube: / (EN version)
Go to:
- 4 - Odvetvové štatistiky / 4 - Sector Statistics.
- 4. 1 - Poľnohospodárstvo, lesníctvo a rybárstvo / 4.1 - Agriculture, Forestry, Fisheries.
- Počet fariem podľa typu a triedy ekonomickej veľkosti [pl3803rr] Number of farms by type and economic size of unit (EN version).
- Počet fariem podľa veľkosti obhospodarovanej pôdy [pl3804rr] Classification of farms by size of cultivated agricultural land (EN version).
- Triedenie fariem podľa počtu zvierat k 31.10. [pl3805rr] Classification of farms by number of animals as of 31.10. (EN version).
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
No10.6.3. Title, publisher, year and link to national reference metadata
Not applicable.
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
Not available.
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Quality guidelinesDesignated quality manager, quality unit and/or senior level committee
Compliance monitoring
External review or audit
Certification
11.1.3. Description of the quality management system and procedures
The SO SR management commits to follow the Quality Policy based on requirements of users of statistics, on rules, principles, recommendations and requirements of the ISO 9001 standard for Quality Management Systems.
For the successful implementation of this commitment, the management of the SO SR will ensure the following tasks:
- to set-up and maintain the Quality Policy and Quality Objectives of the SO SR;
- to ensure permanent maintenance and periodic review of the efficiency and effectiveness of the Integrated Quality Management System implemented in order to achieve these objectives;
- to ensure availability of all necessary resources;
- to make decisions on activities for improving the Quality Management System.
11.1.4. Improvements in quality procedures
The improvement in the quality procedures is managed in compliance with the Code of Practice for the European Statistics.
11.2. Quality management - assessment
Based on the last evaluation of the quality management system, we can state that the quality management system is functional and effective from the point of view of 2023 with deviations that they have no impact on the system as a whole. SO SR provides resources for the functionality and development of the system of quality management in the required structure and in a sufficient time horizon.
In order to manage the situation caused by decisions in the external environment (limited amount of funds from the state budget and increased demands, especially from key customers and data suppliers), as well as by large-scale unwanted events (a huge increase in energy prices), the SO SR has identified these threats and taken steps to minimise their impacts. The SO SR will continue to implement the adopted measures in order to minimise possible risks and threats of a possible adverse reaction from customers and other key stakeholders.
12.1. Relevance - User Needs
The results of the IFS 2023 are very important for the following users:
- DG AGRI - the collection of the structural data will contribute to the improvement of the decision-making process concerning the Common Agricultural Policy (CAP) and its future development. This data collection will also provide the framework for harmonised, comparable and coherent agricultural statistics in the EU;
- Ministry of Agriculture and Rural Development of the Slovak Republic - the data are necessary for the main agricultural policy maker at the national level, who needs to be informed about the recent development in the agricultural sector and for the purposes of the FADN;
- agricultural professional associations - the data will contribute to a better information as regards their members, which are the subject of this survey;
- research and development institutions in the agricultural sector - the data will serve as a basis for scientific purposes.
12.1.1. Main groups of variables collected only for national purposes
No variables collected only for national purposes in IFS 2023.
12.1.2. Unmet user needs
All user needs are met.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
The Statistical Office of the SR conducts surveys on a regular basis focused on the key customers, where the aim is concentrated on their satisfaction with the released products and data. Based on the results of these surveys, we take follow-up measures in the area of content and quality of published data.
12.2.1. User satisfaction survey
Yes12.2.2. Year of user satisfaction survey
2022
12.2.3. Satisfaction level
Satisfied12.3. Completeness
Information on not collected, not-significant and not-existent variables is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
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 on Eurostat’s website, at the webiste: Circabc Europa website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
We do not have cases where estimated RSEs are above the thresholds.
13.2.3. Reference on method of estimation
The relative standard error (RSE) is the standard error divided by the point estimate, multiplied by 100. The RSEs were calculated using the SURVEYMEANS procedure in SAS.
13.2.4. Impact of sampling error on data quality
None13.3. 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 on Eurostat’s website: Circabc Europa website.
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.
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)
Below thresholds during the reference periodTemporarily out of production during the reference period
Ceased activities
Duplicate units
13.3.1.1.2. Actions to minimize the over-coverage error
Removal of ineligible units from the records, leaving unchanged the weights for the other units13.3.1.1.3. 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
1.48%
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)
Other13.3.1.3.3. Actions to minimise the under-coverage error
In the case of self-sufficient farms, we strived for obtaining more information from local authorities and administrative sources before IFS 2023 data collection.
13.3.1.3.4. Additional information under-coverage error
As regards the types of holdings belonging to the population of the core but not included in the frame, there were the farms that refused to submit a questionnaire or could not be contacted due to inaccuracies in their addresses.
13.3.1.4. Misclassification error
No13.3.1.4.1. Actions to minimise the misclassification error
Not applicable.
13.3.1.5. Contact error
Yes13.3.1.5.1. Actions to minimise the contact error
See the point 13.3.1.3.3.
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
Measurement errors may concern the employment characteristics of farms. These are mainly items related to:
1) hours worked related to the CORE: WH_MAN_AWU_PC - Working hours by farm manager - % band Annual work units (AWU)
2) hours worked related to the module LAFO:
- WH_HLD_AWU_PC - Working hours by holder - % band Annual work unit (AWU),
- FLF_D_RFAM_M_XX - Family farm labour force directly employed by the farm on a regular basis - Male - % band Annual work unit (AWU),
- FLF_D_RFAM_F_XX - Family farm labour force directly employed by the farm on a regular basis - Female - % band Annual work unit (AWU),
- FLF_D_RNFAM_M_XX - Non-family farm labour force, directly employed by the farm on a regular basis - Male - % band Annual work unit (AWU), and
- FLF_D_RNFAM_F_XX - Non-family farm labour force, directly employed by the farm on a regular basis - Female) - % band Annual work units (AWU)
3) the variables concerning the irrigation on the farm measured in m3.
13.3.2.2. Causes of measurement errors
Respondents’ inability to provide accurate answers13.3.2.3. Actions to minimise the measurement error
Explanatory notes or handbooks for enumerators or respondentsTraining of enumerators
Other
13.3.2.4. Impact of measurement error on data quality
Unknown13.3.2.5. Additional information measurement error
We tried to eliminate the measurement errors by using the controls in software during the data processing and direct data validation with the survey units, which was extremely demanding. The controls built directly into the electronic questionnaire made it possible to alert the respondent to an existing irregularity when filling out the questionnaire and, in the event of a fundamental error, did not allow the respondent to submit such questionnaire.
The elimination of such errors was secured in two ways. In the first place, we embedded control algorithms to the software for recording data in order to detect the most important errors arising from relationships between workers on the farm. During the creation of the file for Eurostat, we built in further algorithms in order to help detect also other possible errors.
All data errors have been corrected, but the error rate cannot be documented.
13.3.3. Non response error
See sub-categories below.
13.3.3.1. Unit non-response - rate
See 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
13.3.3.1.3. Unit non-response analysis
We analysed variables such as agricultural area and number of animals based on available data. As regards the unit non-response, the highest rate of non-response (3.24%) concerned the small and very small (family) farms.
13.3.3.2. Item non-response - rate
We do not calculate the item non-response rates. We tried to collect all the data concerning all pertinent variables that the survey units could provide us.
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
Follow-up interviewsReminders
Imputation
13.3.3.3. Impact of non-response error on data quality
Low13.3.3.4. Additional information non-response error
Not available.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
Data processing13.3.4.2. Imputation methods
Previous data for the same unitOther
13.3.4.3. Actions to correct or minimise processing errors
During the data processing, we used the built-in checks and after data uploading we compared the data to available registers. Identified errors during processing have been removed.
13.3.4.4. Tools and staff authorised to make corrections
As regards making corrections, authorisation for this activity was given to experts responsible for the IFS 2023 at the Agricultural Statistics Department and the authorised staff at the regional offices. We did not use the software solutions for the error corrections. We corrected errors manually.
13.3.4.5. Impact of processing error on data quality
Low13.3.4.6. Additional information processing error
As regards the other imputation methods, we used the data from the official registers - farm animal central register, orchards register, vineyards register, register of organic producers and IACS.
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
There will be no preliminary data (first results) published, only the final data.
14.1.2. Time lag - final result
The final data will be published in October 2025, that is 22 months after the reference period. In case of favourable validation process, this period may be shortened. The datasets, mentioned in the section 10.3.1, will be updated together with the publications.
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
x days for the publication of the publication "Farms in Slovakia in the year 2023 – Basic indicators (Results of the Integrated farm statistics 2023)"
x days for the publication of the publication "Farms in Slovakia in the year 2023 – Typology (Results of the Integrated farm statistics 2023)"
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
For the purpose of the IFS 2023 we used the same definition as defined in the 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
| Total | Covered by the thresholds | Attained coverage | Minimum requested coverage | |
|---|---|---|---|---|
| 1 | 2 | 3=2*100/1 | 4 | |
| UAA excluding kitchen gardens | 1 824 625 | 1 807 874 | 99.1% | 98% |
| LSU | 532 576 | 532 203 | 99.9% | 98% |
We confirm that the national thresholds respect the IFS thresholds from Annex II of Regulation (EU) 2018/1091.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
No differences.
15.1.3.3. Reasons for differences
Not applicable.
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
There are no deviations in definitions and classification of variables compared to Regulation (EU) 2018/1091, Commission Implementing Regulation (EU) 2021/2286 and EU handbook.
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 on Eurostat’s website, at the link: Circabc Europa website.
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.
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
See item 15.1.4.1.1.
15.1.4.1.3. AWU for workers of certain age groups
See item 15.1.4.1.1.
15.1.4.1.4. Livestock coefficients
For the purpose of the IFS 2023 we used the same livestock coefficients as the ones set in the Regulation (EU) 2018/1091.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
There are no differences between the types of livestock we included under the heading “Other livestock n.e.c.” and the types of livestock that should be included according to the EU handbook.
15.1.4.2. Reasons for deviations
Not applicable.
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
We used the same reference periods/days as the ones set up in the Regulation (EU) 2018/1091.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land does not exist15.1.6.1. Collection of common land data
Not applicable15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Not applicable15.1.6.4. Source of collected data on common land
Not applicable15.1.6.5. Description of methods to record data on common land
Not applicable.
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
No deviations in the national standards and rules for certification of organic products from Council Regulation (EC) No 834/2007
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
There are no differences in the methods used across regions within the country.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
The data are comparable since 2010, the change in the threshold values in 2020 and after will not significantly affect comparability.
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 no changes15.2.2.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
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 no changes15.2.3.2. Description of changes
Not applicable.
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
no changes
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 no changes15.2.5.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
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 no changes15.2.6.2. Description of changes
Not applicable.
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
here below are some explanations on the evolution of IFS2023 data compared to IFS2020
Crop production
As regards the crop production, the sown/harvest area of the crops differs from year to year taking into account the climatic conditions in the previous years and the current year and the actual price level of the individual crop.
a) C1120T- Durum wheat, the significant increase is in line with the crop production statistics for year 2023, the climatic conditions are changing in favor of this type of crop, which is also interesting from the financial side for farmers.
b) C1400T – Oats, the significant decrease is in line with the crop production statistics for year 2023.
c) C1500T – Grain maize, the significant decrease is in line with the crop production statistics for year 2023.
d) P1000T – Peas, the significant increase is in line with the crop production statistics for year 2023.
e) I1190T - Other oil seed crops, the significant decrease is in line with the crop production statistics for year 2023.
f) ARA99T – other arable land crops – significant increase relates to the introducing of the buffer strips as an official measure for farmers within the “Greening of the agricultural policy” into the financial aid for farmers
g) Q0000T – fallow land – the same case as in the case ARA99T, fallow lands were in 2023 financially compensated with comparison with the situation in year 2020.
h) W1110T + W1120T, W1190T, W1200T – the total area of vineyards is decreasing and this fact is in compliance with crop statistics 2023. We can confirm increase of the area of grapes for table use. The shift between the areas of the PDO/PGI on the one side and other wines n.e.c. on the other side could be possible, as a result of the cost optimalisation and decreasing of the administration burden connected with the registration of these type of wines. This shift between two above mentioned wine type areas can be confirmed after IFS2026, during which we will examine the actual situation in this area using the connection with the vineyard’s module.
i) FA9 – other land, we can confirm the increase of this variable, as a result of building of the new farm buildings (storage houses, manure dumps, stables etc.) supported by the Rural Development Program and on the other hand, increase of the long term unutilized agricultural area which can be subsequently changed to another type of area.
j) As regards the animal production, the total decrease of animal production in Slovakia, mainly in the sector of pigs due to the African swine fever and in poultry sector due to the Bird flu, some of producents officially ended up their activities.
k) Other gainful activities – we confirm the decrease between two IFS surveys.
The analysis of holdings breakdown by UAA in 2023 showed an increase of share of higher UAA classes compared to 2020, this is due to the combined effect of smaller holdings that ceased their activities and the concentration: it is expected this trend to continue in the next years as a result of the economic strength of the larger farms, which can buy up the land from the smaller ones.
With respect to the number of holdings broken down by SO EURO class, they can be dragged similar comments as per UAA breakdown. Another important aspect plays role in this case and it is that larger farms can diversify their activities into more areas. Some of their activities are heading to the areas with the higher SO coefficients (specialized crop production or animal production), while the smaller farmers usually concentrate their activities into the smaller number of areas with the lower SO coefficient or they can be active in production of the products with high SO coefficients, but the volume of production is very low due to their capacity
With respect to the farm typology breakdown evolutio, in 2023 there was an increase of the FT15 and FT16. In Slovakia there is is a low percentage of the farms which are specialist for horticulture or specialist for permanent crops.
Data on Labour force
From 2020 to 2023, the share of holdings run by younger manager has slightly increased. This increase is a consequence of the subsidy policy and the scheme from the Rural Development Program. There is a measure in the Rural Development Program which is aiming at the young farmers, so they are eligible to receive financial support. The goal of this measure is to ensure “smooth” transition of farming to the younger farmers, as the current age structure of Slovak farmers is not very favorable.
15.2.9. Maintain of statistical identifiers over time
Partially15.3. 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
We made the analysis where we compared the results from IFS 2023 with the annual crop statistics and animal production statistics. The results of the analysis confirm the coherence between the statistical surveys conducted in the crop, animal and farm structural sectors.
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 regular statistical surveys (crop production statistics) are carried out at the regional level. Holdings submit data for each district in which they perform farming activities separately, i.e., if holding carries out the agricultural production in more districts (districts can belong to different NUTS2), it must complete data for agricultural production separately for each district. In the IFS data are collected according to the specified predominant place in compliance with establishing the geographic location of the holding for transmission to Eurostat.
The main cross-domain differences for crops and animal statistics are due to different collecton date:
- data on the crop area wascollected as of 20th of May, the data in the IFS2023 was collected as of 30th of October.
- data from the IFS2023 report the results from the end of the October 2023, data on organic production are the results from the end of December 2022.
- data on the number of animals presents the situation in December, in the IFS it is the situation in October.
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
We analysed all agricultural statistical surveys and all available administrative data sources. We compiled the questionnaire of the IFS 2023 survey in such a way that respondents did not need fill in data which can be obtained from other sources.
16.2. Efficiency gains since the last data transmission to Eurostat
Increased use of administrative dataFurther training
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
1 hour 41 minutes for the whole questionnaire (the modules "Labour force and other gainful activities", "Irrigation", "Soil management practices" and "Machinery and equipment" are included).
16.3.2. Module ‘Labour force and other gainful activities‘
Not available (see the point 16.3.1 Core).
16.3.3. Module ‘Rural development’
Not relevant. The data for this module were taken from the administrative source (Agricultural Paying Agency).
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Not available (see the point 16.3.1 Core).
16.3.6. Module ‘Soil management practices’
Not available (see the point 16.3.1 Core).
16.3.7. Module ‘Machinery and equipment’
Not available (see the point 16.3.1 Core).
16.3.8. Module ‘Orchard’
Not relevant. The data for this module were taken from the administrative source (Central Control and Testing Institute in Agriculture).
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
The revision policy of the Statistical Office of the SR is governed by the internal directive SME-2/2021.
As regards Integrated Farm Statistics, in case of changes in concepts, methodologies, classifications, code lists or corrections of fundamental errors, extraordinary (major) revisions are carried out within the deadlines for regular publication of definitive data. For Integrated Farm statistics, we do not publish preliminary data. So, when some change needs to be done, it is carried out before the final data are published, i.e. after data validation and prior to publication.
If an error occurs after publication, we will correct the error in the publication and inform the public about the correction of the publication on our website, in the "News" section.
17.2. Data revision - practice
There are no revisions to report for the IFS 2023 data collection.
17.2.1. Data revision - average size
Not requested.
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 Farm Register.
18.1.1.3. Update frequency
Continuous18.1.2. Core data collection on the main frame
See sub-categories below.
18.1.2.1. Coverage of agricultural holdings
Sample18.1.2.2. Sampling design
The main frame was created by using multiple registers:
- datafile of holdings from the IFS 2020,
- new holdings identified during regular statistical surveys,
- new holdings from the register of organisations of the SO SR,
- new holdings from external registers:
- orchards register;
- vineyards register;
- farm animal central register;
- register of organic producers;
- IACS.
The total number of holdings which were identified initially or during the data collection which were meeting the thresholds and falling into main frame was 22 946.
We divided the holdings in the main frame into 2 groups:
- Farms of legal persons, registered natural persons and households with the UAA >= 5 ha were fully covered in the form of census.
- Households with the UAA less than 5 ha. For this group of the survey units we had decided to conduct the sample survey.
This approach was used for the core data collection as well as for the data collection in modules "Labour force and other gainful activities", "Rural development", "Irrigation", "Soil management practices", "Machinery and equipment" and "Orchard".
The sample selection was stratified at the level of NUTS 3, where every NUTS 3 region is the corresponding stratum.
18.1.2.2.1. Name of sampling design
Stratified one-stage random sampling18.1.2.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.2.2.3. Use of systematic sampling
No18.1.2.2.4. Full coverage strata
As regards the IFS 2023, our approach was as follows:
Farms of legal persons, registered natural persons and households with the UAA >= 5 ha were fully covered in the form of census.
This approach was used for the core data collection as well as for the data collection for the modules "Labour force and other gainful activities", "Rural development", "Irrigation", "Soil management practices", "Machinery and equipment" and "Orchard".
18.1.2.2.5. Method of determination of the overall sample size
The total number of holdings which were identified initially or during the data collection which were meeting the thresholds and falling into main frame was 22 946.
Farms of legal persons, registered natural persons and households with the UAA >= 5 ha were fully covered in the form of census.
We carried out a sample survey only on the households with the UAA less than 5 ha. The sample selection was stratified at the level of NUTS 3, where every NUTS 3 region is the corresponding stratum. The gross sample of the survey on households with the UAA less than 5 ha was 1 895 holdings.
The total number of farms surveyed (1 895 plus the number of farms with legal persons farms, registered natural persons and households with the UAA >=5 ha) was 16 845 holdings.
This approach was used for the core data collection as well as for the data collection for modules "Labour force and other gainful activities", "Rural development", "Irrigation", "Soil management practices", "Machinery and equipment" and "Orchard".
18.1.2.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.3. Core data collection on the frame extension
See sub-categories below.
18.1.3.1. Coverage of agricultural holdings
Not applicable18.1.3.2. 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
See the point 18.1.2.2. Sampling design.
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
No18.1.4.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.4.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
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
Sample18.1.5.2. Sampling design
See the point 18.1.2.2. Sampling design.
18.1.5.2.1. Name of sampling design
Stratified one-stage random sampling18.1.5.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.5.2.3. Use of systematic sampling
No18.1.5.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.5.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
18.1.5.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.6. Module “Animal housing and manure management module”
Restricted from publication
18.1.6.1. Coverage of agricultural holdings
Restricted from publication
18.1.6.2. Sampling design
Restricted from publication
18.1.6.2.1. Name of sampling design
Restricted from publication
18.1.6.2.2. Stratification criteria
Restricted from publication
18.1.6.2.3. Use of systematic sampling
Restricted from publication
18.1.6.2.4. Full coverage strata
Restricted from publication
18.1.6.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.6.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.7. Module ‘Irrigation’
See sub-categories below.
18.1.7.1. Coverage of agricultural holdings
Sample18.1.7.2. Sampling design
See the point 18.1.2.2. Sampling design.
18.1.7.2.1. Name of sampling design
Stratified one-stage random sampling18.1.7.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.7.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
18.1.7.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.7.2.7. 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
Sample18.1.8.2. Sampling design
See the point 18.1.2.2 Sampling design.
18.1.8.2.1. Name of sampling design
Stratified one-stage random sampling18.1.8.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.8.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
18.1.8.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.8.2.7. 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
Sample18.1.9.2. Sampling design
See the point 18.1.2.2. Sampling design.
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.9.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
18.1.9.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.9.2.7. 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
Sample18.1.10.2. Sampling design
See the point 18.1.2.2. Sampling design.
18.1.10.2.1. Name of sampling design
Stratified one-stage random sampling18.1.10.2.2. Stratification criteria
Unit sizeUnit location
Unit legal status
18.1.10.2.3. Use of systematic sampling
No18.1.10.2.4. Full coverage strata
See the point 18.1.2.2.4. Full coverage strata.
18.1.10.2.5. Method of determination of the overall sample size
See the point 18.1.2.2.5. Method of determination of the overall sample size.
18.1.10.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.11. Module ‘Vineyard’
Restricted from publication
18.1.11.1. Coverage of agricultural holdings
Restricted from publication
18.1.11.2. Sampling design
Restricted from publication
18.1.11.2.1. Name of sampling design
Restricted from publication
18.1.11.2.2. Stratification criteria
Restricted from publication
18.1.11.2.3. Use of systematic sampling
Restricted from publication
18.1.11.2.4. Full coverage strata
Restricted from publication
18.1.11.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.11.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.12. Software tool used for sample selection
SAS.
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, at the link: Additional data - Eurostat (europa.eu).
18.1.13.2. Description and quality of the administrative sources
See the Excel file in the annex.
Annexes:
18.1.13.2. Description and quality of administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
None18.1.14. Innovative approaches
The information on the innovative approaches and the quality methods applied is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
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
Paper auto-questionnairePostal, non-electronic version
Telephone, non-electronic version
Telephone, electronic version
Use of Internet
18.3.2. Data entry method, if paper questionnaires
Manual18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3 Questionnaire in English
18.3.3 Questionnaire in Slovak
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Data format checksCompleteness checks
Range checks
Relational checks
Comparisons with previous rounds of the data collection
18.4.2. Staff involved in data validation
Staff from local departmentsStaff from central department
18.4.3. Tools used for data validation
We used the tools involved directly in the electronic data collection system (controls, control questions, colour highlighting, etc.) and the manual validation of the staff (at the headquarters and in the regional branches) directly participating in the IFS 2023. For this purpose we used the documents and datasets received from the Ministry of Agriculture of the Slovak Republic, Agricultural Paying Agency, State Veterinary and Food service, Central Control and Testing Institute in Agriculture and the data from the previous IFS and FSS surveys.
18.5. Data compilation
We worked with the final data file. This file was created by linking data from our questionnaire and the two administrative sources mentioned below, all based on a single ID number.
The data from the questionnaire are data which relates to the core and modules "Labour force and other gainful activities", "Irrigation", "Soil management practices" and "Machinery and equipment". The data for the module "Rural development" was extracted from the administrative source - IACS from the Agricultural Paying Agency. The data for the module "Orchard" was extracted from the administrative source - Orchards register which is administrated by the Central Control and Testing Institute in Agriculture.
For the part of the survey, which was based on the sample (the households with the UAA less than 5 ha), we used the one stage stratified random sampling. The sample was stratified at the level of the NUTS 3. The primary as well as the final weights were calculated based on this stratification.
18.5.1. Imputation - rate
| Code | Name | Imputation rate in % (unweighted) |
|---|---|---|
| UAAT | Utilised agricultural area - outdoor | 0.5 |
| ARAT | Arable land - outdoor | 0.3 |
| C0000T | Cereals for the production of grain (including seed) - outdoor | 0.3 |
| P0000T | Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses) - outdoor | 0.7 |
| R0000T | Root crops - outdoor | 0.1 |
| I0000T | Industrial crops - outdoor | 0.2 |
| I1100XI1150T | Oilseeds except cotton - outdoor | 0.2 |
| G0000T | Plants harvested green from arable land - outdoor | 0.5 |
| V0000_S0000T | Fresh vegetables (including melons) and strawberries - outdoor | 0.2 |
| Q0000T | Fallow land - outdoor | 0.7 |
| J0000T | Permanent grassland - outdoor | 0.9 |
| F0000T | Fruits, berries and nuts (excluding citrus fruits, grapes and strawberries) - outdoor | 0.8 |
| W1000T | Grapes - outdoor | 0.3 |
| A2010 | Bovine animals, less than 1 year old | 1.3 |
| A2020 | Bovine animals, 1 to less than 2 years old | 0.3 |
| A2120 | Male bovine animals, 1 to less than 2 years old | 0.5 |
| A2220 | Heifers, 1 to less than 2 years old | 0.2 |
| A2130 | Male bovine animals, 2 years old or over | 0.7 |
| A2230_2300 | Female bovine, 2 years old or over (including all cows) | 0.5 |
| A2230 | Heifers, 2 years old and over | 0.9 |
| A2300 | Cows | 0.5 |
| A2300F | Dairy cows | 0.5 |
| A2300G | Non dairy cows | 0.4 |
| A4100 | Sheep | 0.8 |
| A4200 | Goats | 1.8 |
| A3110 | Piglets, live weight under 20 kg | 0.0 |
| A3120 | Breeding sows, live weight 50 kg or over | 0.0 |
| A3130 | Other pigs | 0.1 |
| A5140 | Broilers | 0.0 |
| A5110O | Laying hens | 0.0 |
| A5000X5100 | Live poultry excluding chicken (species) | 0.0 |
| A5230 | Turkeys | 0.0 |
| A6710R | Bees (hives) | 0.0 |
18.5.2. Methods used to derive the extrapolation factor
Design weightCalibration
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
AWU – Annual Working Unit
CAP – Common Agricultural Policy
DG AGRI – Directorate-General for Agriculture and Rural Development
EU – European Union
FADN – Farm Accountancy Data Network
FSS – Farm Structure Survey
HA – Hectares
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
ISO – International Organization for Standardization
LAFO – Labour force and other gainful activities
LSU – Livestock unit
MET – Methodological direction
NUTS – Nomenclature of territorial units for statistics
RSE – Relative standard error
SGM – Standard Gross Margin
SME – Internal directives
SO – Standard output
SO SR – Statistical Office of the Slovak Republic
SR – Slovak Republic
UAA – Utilised agricultural area
19.2. Additional comments
No additional comments.
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures 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 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 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
17 February 2025
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 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- 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 “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings;
- for the module “Orchards”: apples area by age of plantation and density of trees.
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.
We worked with the final data file. This file was created by linking data from our questionnaire and the two administrative sources mentioned below, all based on a single ID number.
The data from the questionnaire are data which relates to the core and modules "Labour force and other gainful activities", "Irrigation", "Soil management practices" and "Machinery and equipment". The data for the module "Rural development" was extracted from the administrative source - IACS from the Agricultural Paying Agency. The data for the module "Orchard" was extracted from the administrative source - Orchards register which is administrated by the Central Control and Testing Institute in Agriculture.
For the part of the survey, which was based on the sample (the households with the UAA less than 5 ha), we used the one stage stratified random sampling. The sample was stratified at the level of the NUTS 3. The primary as well as the final weights were calculated based on this stratification.
See sub-categories below.
The frequency of dissemination of the agricultural census data is every 10 years. Every 3-4 years are disseminated the data on farm structural survey / integrated farm survey which are not collected on the census basis.
See sub-categories below.
See sub-categories below.
See sub-categories below.
