1.1. Contact organisation
Statistical Office of the Republic of Serbia
1.2. Contact organisation unit
Division for Farm Structure Surveys and Statistical Farm Register
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
5 Milana Rakica St., 11000 Belgrade, Serbia
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
9 July 2026
2.2. Metadata last posted
3 August 2026
2.3. Metadata last update
9 July 2026
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of farms.
The main features of agricultural holdings: holding’s identification data, total area of agricultural holding and agricultural land categories of use, data on labour force and data on number of livestock are collected by the complete coverage of observation units. The data on organic farming are taken over from the administrative source – the records of the Ministry of Agriculture, Forestry and Water Management. The data on other features (irrigation of land under crops, types of keeping animals, soil management practices, use of fertilisers, agricultural buildings, machinery and equipment) are sample collected.
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 applied instruments, coverage, features and the standardisation of concepts and definitions are all in compliance with Regulation (EU) 2018/1091 of the European Parliament and of the Council of 18 July 2018 on integrated farm statistics, and Eurostat methodology.
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 “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, pears area, peaches area, nectarines area, apricots area, grapes for table use area, each one 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
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”
Labour force and other gainful activities and Machinery and equipment: The same population of agricultural holdings defined in item 3.6.1.
Rural development: Not applicable. The rural development measures addressed in this module are governed by EU policies and funding and therefore, they do not apply to Serbia.
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 area.
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: apples, pears, peaches, nectarines, apricots and grapes for table use.
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 majority of the area of the holding
3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Farm structure statistics in our country cover the period from 2012 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
Agricultural year from 1 October 2022 to 30 September 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 30 September within the reference year 2023.
5.3. Reference day for variables on livestock and animal housing
The reference day is 30 September 2023 for livestock variables.
The animal housing variables are not applicable 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 30 September within the reference year 2023.
5.6. Reference period for variables on rural development measures
Not applicable for Serbia. The rural development measures are governed by EU policies and funding.
5.7. Reference day for all other variables
The reference day is 30 September 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
Law on 2023 Census of Agriculture (Official Gazette of the RS, No. 76/21)
6.1.3. Link to national legal acts and other agreements
Law on 2023 Census of Agriculture
6.1.4. Year of entry into force of national legal acts and other agreements
2021
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
According to the signed Cooperation Agreement with the Ministry of Agriculture, Forestry and Water Management, the Ministry is obliged to provide data necessary to SORS.
7.1. Confidentiality - policy
Articles 23 and 24 of the Law on 2023 Census of Agriculture:
Article 23 - Usage of data collected through the Census
The data collected through the Census shall be used for statistical purposes only and shall not be ceded by the Statistical Office of the Republic of Serbia to other physical persons or legal entities.
The data collected through the Census may not be used for the purpose of determining obligations of civil persons and agricultural holdings, or as a proof for practising rights of civil persons and agricultural holdings.
The Statistical Office of the Republic of Serbia may use the data collected through the Census for establishing, keeping and updating statistical registers, in accordance with the Official Statistics Law and the law stipulating the protection of personal data.
For the purpose of using the census data for scientific and research purposes, the Statistical Office of the Republic of Serbia shall create a special database.
Article 24 - Protection of data collected through the Census
The Statistical Office of the Republic of Serbia is obligated to undertake all prescribed administrative, technical and organizational measures required for the protection of data collected through the Census against illegal access, publication or use, in accordance with the law regulating the domain of information safety.
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)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
For the protection of final output tables, an individual cell in the table is protected if there are fewer than 3 reporting units at the settlement level.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
Not applicable7.2.2.2. Methods of perturbation
None7.2.2.3. Description of methodology
Not applicable.
8.1. Release calendar
The Statistical Office of the Republic of Serbia publishes the release calendar on its official website.
The census was conducted as part of the IPA 2018 project. Due to its postponement from 2021 to 2023 because of COVID-19, the timeline for all activities was delayed, and the publication of special studies during the project's duration was uncertain.
Subsequently, the project was extended, and the publication of special publications took place in 2025 before the end of the project. Due to frequent changes in the schedule and dissemination deadlines, only the brochure announcing the agricultural census results was included in this calendar.
The first results were published in January 2024.
The database with final results is available as of June 2024.
8.2. Release calendar access
8.3. Release policy - user access
The results are published on the SORS website, according to the publishing and dissemination policies.
In the case of the first and final results of the 2023 agricultural census, the main stakeholders were invited to a press conference.
8.3.1. Use of quality rating system
Yes, the EU quality rating system8.3.1.1. Description of the quality rating system
The quality rating system is compatible with one described in the EU handbook.
Data dissemination does not follow a consistent frequency, given that SORS conducted the agricultural census in 2012 and 2023, and the farm structure survey in 2018.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
Yes, but not in English10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
Brochure - 2023 Census of Agriculture
The publications (only in Serbian) can be found below.
- Organising agricultural production through agricultural cooperatives, SORS, 2025
- Structure, economic strength and market activity of agricultural holdings in the Republic of Serbia according to the 2023 agricultural census results, SORS, 2025
- Fruit growing and structure of orchards in the Republic of Serbia according to the 2023 agricultural census results, SORS, 2025
- Gender representation on agricultural holdings in the Republic of Serbia according to the 2023 agricultural census results, SORS, 2025
- Livestock breeding in the Republic of Serbia according to the 2023 agricultural census results, SORS, 2025
- Structural changes in the field of agriculture and the impact of economic growth, SORS, 2025
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
Online database ('Agriculture, forestry and fishery' → 'Census of Agriculture/agricultural census')
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
No10.5. Dissemination format - other
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
10.6.4. Availability of national handbook on methodology
Yes10.6.5. Title, publisher, year and link to handbook
Methodological guidelines, SORS, 2023
10.6.6. Availability of national methodological papers
Yes10.6.7. Title, publisher, year and link to methodological papers
Methodological guidelines, SORS, 2023
10.7. Quality management - documentation
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Use of best practicesQuality guidelines
Peer review
11.1.3. Description of the quality management system and procedures
The quality management system of SORS relies on the mission and vision of the Official Statistics of the Republic of Serbia, as well as on the European Statistics Code of Practice, which represents the Common Quality Framework of the European Statistical System (ESS). The quality management system is available on this page.
The quality strategy is the output of the project 'IPA 2014 Multi-beneficiary statistical cooperation programme' and is also available on this page.
11.1.4. Improvements in quality procedures
No ongoing or planned improvements in quality procedures.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
Census data will be used for statistical analyses to enable relevant decision-making, which is required to support agricultural production and development. The main stakeholder, the Ministry of Agriculture, Forestry and Water Management, is using this data for the development of its Agriculture Strategy 2025-2034.
12.1.1. Needs at national level
National needs are discussed with main stakeholders, primarily representatives from the MOAFW.
Certain categories of livestock and crops have been taken into account in greater detail than required by Regulation (EU) 2018/1091, specifically to provide a basis for validating other annual statistical surveys. For example, data on the total area under fruit cultivation were collected for all fruit species grown in the country - including those for which the regulation does not mandate data on orchard density or plantation age. Similarly, within the livestock category of sows weighing 50 kg or more, the data include both sows and young female heads. This comprehensive breakdown of the regulatory categories into more detailed subcategories is best illustrated in the questionnaire.
The registration ID number from the administrative register is also added for updating SFR and using administrative data in the future.
12.1.2. Unmet user needs
The main users of agricultural statistics - MOAFW, other government institutions, and public authorities - were consulted during the preparation of the questionnaire, and their suggestions and needs were taken into consideration when deciding which variables should be included in addition to those required by Regulation (EU) 2018/1091. Therefore, no unmet needs have been identified among these main users. Regarding other users (farmers and farmers’ associations, research institutions and universities, professional associations, and NGOs), no information is available on potential unmet needs.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
SORS conducts a general User Satisfaction Survey every second year (the last survey was conducted in June-July 2023).
The User Satisfaction Survey obtains information about the needs of users, their satisfaction with data and services, as well as information about the quality of data and services.
In addition to this survey, SORS continuously analyses user requests, media publications and web analytics.
12.2.1. User satisfaction survey
Yes12.2.2. Year of user satisfaction survey
Results of the User satisfaction survey, 2023
12.2.3. Satisfaction level
Highly 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 link: CircaBC website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
A part of relative standard errors computed by Eurostat exceeded the precision thresholds laid down in Regulation (EU) 2018/1091. The relative standard errors computed by Eurostat do not account for the effect of calibration on variance. Calibration was carried out at the national level, with the aim of ensuring that the estimated number of agricultural holdings exhibiting a given characteristic was consistent with the corresponding agricultural census totals. For example, in the case of irrigation, the calibration was designed to align the estimated number of holdings with irrigation with the Census figures.
For future survey rounds, the plan is to improve the selection of auxiliary variables used in the calibration process, as well as to carefully assess the territorial levels at which calibration is performed, in order to further improve the quality and accuracy of the estimates.
13.2.3. Reference on method of estimation
We used Eurostat's variance estimation method for the computation of the relative standard errors. The method is based on the ultimate cluster approximation. It accounts for the sampling design and for the presence of unequal weights within strata, however it does not account for the effect of calibration residuals on the estimated variance. For the description of the method, see the IFS 2023 Handbook, chapter “4.Data processing”, sub-chapter “4.6. Calculation of weights, variance estimation and quality rating system”, section "TOTALS OF CONTINUOUS VARIABLES", sub-section "Variance estimation in IFS".
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, at the link: CircaBC.
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
Merged to another unit
Duplicate units
13.3.1.1.2. Actions to minimize the over-coverage error
None13.3.1.1.3. Additional information over-coverage error
Not available.
13.3.1.2. Common units - proportion
The share of holdings from the administrative sources that matched the total number of holdings in the frame is 65%.
13.3.1.3. Under-coverage error
See sub-categories below.
13.3.1.3.1. Under-coverage rate
The under-coverage rate estimated from the Post-Enumeration Survey (PES) is 11%. This estimate refers only to the household sector, as the PES frame was based on the Population Census 2022 results. The share of the weighted households covered by the PES in the total number of agricultural holdings amounts to 85%.
For the legal entities sector, the under-coverage rate could not be estimated. However, since all available administrative registers were used to construct the agricultural census frame, under-coverage in this sector is considered negligible.
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)
New births13.3.1.3.3. Actions to minimise the under-coverage error
Using all available registries to create the framework.
Using information from Population Census 2022 to detect potentially new agricultural holdings.
13.3.1.3.4. Additional information under-coverage error
Not available.
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
Regularly update Statistical Farm Register with information obtained from all available administrative sources and field checks.
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
Not available.
13.3.2.2. Causes of measurement errors
Complexity of variables13.3.2.3. Actions to minimise the measurement error
Pre-testing questionnaireOn-line FAQ or Hot-line support for enumerators or respondents
Training of enumerators
13.3.2.4. Impact of measurement error on data quality
None13.3.2.5. Additional information measurement error
During the training of interviewers and controllers, more attention was paid to characteristics that were previously found to be difficult to understand. For these same characteristics, logic controls were also enforced during data entry and the subsequent validation process. If inconsistencies or extreme values were discovered, the data were checked against information from the agricultural census (e.g., through correlation with other variables) and re-verified with farmers via a 'call-back'. This process ensured that extreme values were checked and corrected as necessary.
Since the data were entered directly into a program with built-in controls, it is likely that fewer mistakes occurred due to interviewer error.
A Post-Enumeration Survey (PES) was conducted in January 2024, and the PES report can be found in the annex.
Annexes:
13.3.2.5. Post-Enumeration Survey report
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
Reminders13.3.3.1.3. Unit non-response analysis
For unit non-response, a comparison with information in the SFR and administrative sources was performed. The conclusion is that these non-responding units are neither legal units nor do they have a major contribution to the main variables (UAA, LSU). Furthermore, no such non-responding units were found registered in administrative registers.
13.3.3.2. Item non-response - rate
The electronic questionnaire did not allow item non-response.
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
None13.3.3.3. Impact of non-response error on data quality
None13.3.3.4. Additional information non-response error
Not available.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
None13.3.4.2. Imputation methods
None13.3.4.3. Actions to correct or minimise processing errors
Not applicable.
13.3.4.4. Tools and staff authorised to make corrections
The in-house-developed system IST (Integrated System for data collection and processing) was used as a correction tool. The corrections were defined by methodologists from the Agriculture, Forestry and Fishery department.
More information about IST can be found on this page.
13.3.4.5. Impact of processing error on data quality
None13.3.4.6. Additional information processing error
The in-house-developed system IST was used for data collection and processing, so every action was defined, stored, and repeatable.
Auto-correction was used only to correct typos during data entry if they were spotted during data validation with other available sources.
13.3.5. Model assumption error
The volume of water used for irrigation was estimated using a model. The module 'Irrigation' contained questions on areas under crops irrigated and the number of waterings during the reference period.
Based on this information and the standard amount of water per hectare for each crop, the total volume of water was calculated.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
January 2024, i.e. 1 month.
14.1.2. Time lag - final result
June 2024, i.e. 6 months.
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 for the brochure met the target date for data publication. However, for other publications, the punctuality cannot be assessed.
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
The national definition incorporates a physical threshold for family holdings, thereby also covering those family farms that are not engaged in market-oriented agricultural production but still meet the specified physical criteria.
15.1.2.2. Reasons for deviations
The domination of small family holdings in the country.
15.1.3. Thresholds of agricultural holdings
See sub-categories below.
15.1.3.1. Proofs that the EU coverage requirements are met
Lower threshold than set by Regulation (EU) 2018/1091.
Holdings with less than 0.5 hectares of UAA but exceeding the thresholds for specific crops listed in Annex II of Regulation (EU) 2018/1091 (e.g., aromatic, medicinal and culinary plants, flowers and ornamental plants, seeds and seedlings, nurseries, or orchards) are engaged in market production and are therefore included in the survey based on this criterion.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
No differences between the national thresholds and the thresholds used for the data sent to Eurostat.
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
No differences 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.
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
The same LSU coefficients as those set out in Regulation (EU) 2018/1091 were used.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
There are no differences between the types of livestock that are 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
No deviations.
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
The statistical model is based on the area of common land and the number of grazing animals recorded in holdings within each corresponding municipality. Different livestock species are represented by LSU.
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
We do not experience problems to collect data on common land.
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
No differences in methods across regions within the country.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
3 (2012, 2018, and 2023).
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
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However, even if our country raises fur animals, holdings with only fur animals are not included in our data collection because they do not meet the thresholds. We did not add thresholds related to fur animals; there is no reason for it (fur animals do not contribute towards 98% of the total LSU).
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
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, the thresholds in 2023 remained unchanged.
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
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, the geographical coverage in 2023 remained unchanged.
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
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, IFS 2023 introduced the following changes in definitions and classifications:
Legal personality of the agricultural holding
In IFS, there is a new class (“shared ownership”) for the legal personality of the holding compared to FSS 2016, which trigger fluctuations of holdings in the classes of sole holder holdings and group holdings.
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 2023, 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 no changes15.2.6.2. Description of changes
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, there are no changes in the IFS 2023 reference periods/days.
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
IFS 2023 is the first data collection conducted according to Regulation (EU) 2018/1091. Serbia did not conduct IFS 2020. Compared to FSS 2016, there are no changes in the IFS 2023 common land methodology.
15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat
Comparability between 2020 and 2023 could not be assessed due to the absence of 2020 data for Serbia. However, the 2023 data regarding legal personality has been thoroughly checked and confirmed.
15.2.9. Maintain of statistical identifiers over time
Yes15.3. 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
Data are compared with annual statistical surveys in agriculture on crop and livestock production. No major differences were found for UAA and its subcategories (arable land, permanent crops, etc.).
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
Coherence cross-domain: IFS vs CROP PRODUCTION (main area in 1000 ha) in relative terms
The discrepancies in results between the 2023 agricultural census and the regular annual survey on sown areas at the end of the spring sowing season are primarily due to different data collection methods. The agricultural census is conducted as a full enumeration, covering and surveying all agricultural holdings, whereas data in the regular annual survey are collected on a sample basis. The sample is designed to achieve an acceptable coefficient of variation (CV) for the main crops (those grown on the largest areas) that are the subject of quality reporting, such as wheat, maize, sugar beet, sunflower, and soybean. The quality and results of data for other crops primarily depend on their frequency of occurrence in a given territory, which leads to greater discrepancies in the results between the two surveys.
Coherence cross-domain: IFS vs ANIMAL PRODUCTION (1000 heads) in relative terms
The discrepancy regarding A3100 (Live swine, domestic species) in the RS11 region is caused by a new business in the Belgrade region that started pig breeding, as well as a difference in reference dates. Specifically, the reference date for livestock numbers in the agricultural census is 30 September 2023, whereas the annual livestock survey numbers – exceptionally for 2023 – were estimated for 1 December 2023, according to the agricultural census and results from previous annual livestock surveys.
For A4200 (Live goats), the largest difference occurs in the number of goats under 1 year of age, while other categories, which fluctuate less, remain similar.
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 (Agricultural Department), and optimal coordination of surveys exists to avoid situations where some farms have to answer multiple questionnaires with the same or similar questions. Thus, the annual surveys on crop and livestock production, typically conducted in December, were not conducted in 2023. Furthermore, since organic production was taken from administrative sources, respondents did not have to complete those questions.
16.2. Efficiency gains since the last data transmission to Eurostat
Further automation16.2.1. Additional information efficiency gains
Not available.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Approximately 20 minutes.
16.3.2. Module ‘Labour force and other gainful activities‘
Approximately 10 minutes.
16.3.3. Module ‘Rural development’
Not relevant. The rural development measures addressed in this module are governed by EU policies and funding and therefore, they do not apply to Serbia.
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Approximately 10 minutes.
16.3.6. Module ‘Soil management practices’
Approximately 10 minutes.
16.3.7. Module ‘Machinery and equipment’
Approximately 15 minutes.
16.3.8. Module ‘Orchard’
Approximately 15 minutes.
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
17.2. Data revision - practice
Data revision is not planned so far.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
See sub-categories below.
18.1.1. Source data - frame population
See sub-categories below.
18.1.1.1. Type of frame
List frame18.1.1.2. Name of frame
Statistical Farm Register (SFR)
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.
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.
18.1.2.2.5. Method of determination of the overall sample size
Not applicable.
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
Census18.1.4.2. Sampling design
Not applicable.
18.1.4.2.1. Name of sampling design
Not applicable18.1.4.2.2. Stratification criteria
Not applicable18.1.4.2.3. Use of systematic sampling
Not applicable18.1.4.2.4. Full coverage strata
Not applicable.
18.1.4.2.5. Method of determination of the overall sample size
Not applicable.
18.1.4.2.6. Method of allocation of the overall sample size
Not applicable18.1.4.2.7. 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
Not applicable18.1.5.2. 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”
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
The sample frame consisted of all active agricultural holdings from the main and extended frames with data on UAA.
The sample frame was stratified and from each stratum, a simple random sample of agricultural holdings was selected. The location of the unit is defined according to the NUTS 3 classification.
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
Family holdings with irrigable area greater than or equal to 20 ha
Legal units
18.1.7.2.5. Method of determination of the overall sample size
The overall sample size was determined using Bethel algorithm, which is based on optimal allocation.
18.1.7.2.6. Method of allocation of the overall sample size
Neymann 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
The sample frame consisted of agricultural holdings with utilised arable land area belonging to the main or extended frame.
The sample frame was stratified and from each stratum, a simple random sample of agricultural holdings was selected. The location of the unit is defined according to the NUTS 2 classification.
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
Full coverage strata were determined using Hidiroglou algorithm. This algorithm uses an auxiliary variable (which is correlated with the study variable) to determine an optimum cut-off value for 'take-all' units. The purpose of this is to minimise the sample size while achieving a given precision for an estimate of the total at a specified level. In this module, the auxiliary variable was the utilised area of arable land, and the given precision was 5% at the region (NUTS 2) level. Strata that contained legal entities were also designated as full coverage.
18.1.8.2.5. Method of determination of the overall sample size
The overall sample size was determined using Bethel algorithm, which is based on optimal allocation.
18.1.8.2.6. Method of allocation of the overall sample size
Neymann 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
The sample frame consisted of all active agricultural holdings belonging to the main or extended frame, which had data for at least one variable needed for fulfilling precision requirements from Regulation (EU) 2018/1091 (Article 7).
The sample frame was stratified and from each stratum, a simple random sample of agricultural holdings was selected. The location of the unit is defined according to the NUTS 3 classification.
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit locationUnit legal status
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
Full coverage strata, which contained enterprises, were determined using Hidiroglou algorithm. In this module, auxiliary variables were livestock and land variables, as listed in Regulation (EU) 2018/1091 (Article 7).
18.1.9.2.5. Method of determination of the overall sample size
The overall sample size was determined using Bethel algorithm, which is based on optimal allocation.
18.1.9.2.6. Method of allocation of the overall sample size
Neymann 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
The sample frame consisted of all active agricultural holdings belonging to the main or extended frame, which had data on apples, pears, peaches, nectarines, apricots and grapes for table use. Agricultural holdings with less than 0.1 ha of area of fruits or vineyards were excluded.
The sample frame was stratified and from each stratum, a simple random sample of agricultural holdings was selected. The location of the unit is defined according to the NUTS 2 classification.
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
Family holdings with area under apples, peaches or nectarines greater than 5 ha, or pears or apricots greater than 2 ha.
Legal entities.
Family holdings determined using Hidiroglou algorithm (auxiliary variable was grapes for table use and given precision was 4% at the national level).
18.1.10.2.5. Method of determination of the overall sample size
The overall sample size was determined using Bethel algorithm, which is based on optimal allocation.
18.1.10.2.6. Method of allocation of the overall sample size
Neymann 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 and ETOS (an upgraded version of CLAN). ETOS is based on SAS and is used to calculate specific indicators for household surveys, such as the Gini index in SILC.
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
Problems related to data quality of the source18.1.14. 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
Face-to-face, electronic versionUse of Internet
18.3.2. Data entry method, if paper questionnaires
Not applicable18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3 Questionnaire in English
18.3.3 Questionnaire in Serbian
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Completeness checksRelational checks
Comparisons with previous rounds of the data collection
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
Staff from central department18.4.3. Tools used for data validation
The in-house-developed system IST.
18.5. Data compilation
Weights were calculated by taking the inverse of the inclusion probabilities.
For calibration, totals obtained in the field after the 2023 agricultural census were used as auxiliary variables.
18.5.1. Imputation - rate
Not applicable.
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
CV – Coefficient of variation
ESS – European Statistical System
EU – European Union
FAQ – Frequently Asked Questions
FSS – Farm Structure Survey
IFS – Integrated Farm Statistics
IPA – Instrument for Pre-accession Assistance
IST – Integrated System for data collection and processing
LSU – Livestock unit
MOAFW – Ministry of Agriculture, Forestry and Water Management
NGO – Non-Governmental Organisation
NUTS – Nomenclature of territorial units for statistics
PES – Post-Enumeration Survey
SAS – Statistical Analysis System
SFR – Statistical Farm Register
SGM – Standard gross margin
SILC – Statistics on Income and Living Conditions
SO – Standard output
SORS – Statistical Office of the Republic of Serbia
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.
The main features of agricultural holdings: holding’s identification data, total area of agricultural holding and agricultural land categories of use, data on labour force and data on number of livestock are collected by the complete coverage of observation units. The data on organic farming are taken over from the administrative source – the records of the Ministry of Agriculture, Forestry and Water Management. The data on other features (irrigation of land under crops, types of keeping animals, soil management practices, use of fertilisers, agricultural buildings, machinery and equipment) are sample collected.
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 applied instruments, coverage, features and the standardisation of concepts and definitions are all in compliance with Regulation (EU) 2018/1091 of the European Parliament and of the Council of 18 July 2018 on integrated farm statistics, and Eurostat methodology.
9 July 2026
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 “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, pears area, peaches area, nectarines area, apricots area, grapes for table use area, each one 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.
Weights were calculated by taking the inverse of the inclusion probabilities.
For calibration, totals obtained in the field after the 2023 agricultural census were used as auxiliary variables.
See sub-categories below.
Data dissemination does not follow a consistent frequency, given that SORS conducted the agricultural census in 2012 and 2023, and the farm structure survey in 2018.
See sub-categories below.
See sub-categories below.
See sub-categories below.
