1.1. Contact organisation
Statistical Service of Cyprus (CYSTAT)
1.2. Contact organisation unit
Agricultural Statistics Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Statistical Service of Cyprus
Michael Karaoli street
1444 Nicosia
Cyprus
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
10 April 2025
2.2. Metadata last posted
5 May 2025
2.3. Metadata last update
10 April 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.
Note that the Republic of Cyprus is designated as one region at NUTS levels 1, 2 and 3.
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": oranges area, small citrus fruit area, olives 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 establishing the statistical classification of economic activities NACE Rev. 2. The agricultural holdings belong to NACE 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”
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 3.6.1 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 3.6.1 with arable land. Please note that exceptions may apply in the cases where the holding does not have arable land but maintains ecological focus areas under the provisions of Article 46 of Regulation (EU) No 1307/2013 or the holding has utilised agricultural areas which are subject to drainage.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
The subset of agricultural holdings defined in item 3.6.1, 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
Republic of Cyprus.
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 most important parcel by economic 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 Cyprus cover the period from 2003 onwards. The data collections for previous periods are described in separate 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
Land characteristics refer to areas used in the 12-month reference period of 1 September 2022 to 31 August 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
For variables on irrigation and soil management practices, the 12-month reference period is 1 September 2022 to 31 August 2023.
5.3. Reference day for variables on livestock and animal housing
For livestock variables, the reference day is 31 December 2023.
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 of 1 September 2022 - 31 August 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 is 31 December 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
The Official Statistics Law of 2021 (Law No. 25(I)/2021) provides the legal basis for the development, production and dissemination of official statistics in Cyprus. Its provisions are in line with Regulation (EC) No 223/2009 on European Statistics, with an emphasis on its latest amendment by Regulation (EU) 2015/759. Article 3 of the national Official Statistics Law (Law No. 25(I)/2021) defines the functions of the Statistical Service of Cyprus regarding the production and dissemination of official statistics. Moreover, Article 13, explicitly stipulates the mandate for data collection and introduces a mandatory response to statistical inquiries by stipulating the obligation of respondents to reply to surveys and provide the data required. This relates not only to national but also to European statistics which, by virtue of Article 8 of the said Law, are incorporated in the annual and multiannual programmes of work without any further procedure.
6.1.3. Link to national legal acts and other agreements
Official Statistics Law of 2021
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
Not applicable. The IFS microdata are transmitted only to Eurostat and are not shared or exchanged between any agencies.
7.1. Confidentiality - policy
Official statistics are released in accordance to all confidentiality provisions of the following:
- National Official Statistics Law No. 25(I) of 2021 (especially Article 16 on statistical confidentiality).
- Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality).
- European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
- CYSTAT's "Guidelines for the Protection of Confidential Data" (only in Greek).
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
The treatment of confidential data is regulated by CYSTAT's "Guidelines for the Protection of Confidential Data" (only in Greek). The rules and measures provided shall apply, in order to ensure that confidential data are exclusively used for statistical purposes and to prevent their unlawful disclosure.
IFS data are sent through eDAMIS encrypted. The summary tables that are disseminated show only aggregates for the whole country and no microdata are included in order to ensure confidentiality. In the detailed tables disseminated in the web portal of CYSTAT, confidentiality rules apply. If the aggregated data correspond to 3 or less holdings, then data are suppressed and flagged as confidential and are included only in the totals in order to prevent their unlawful disclosure. Also, secondary confidentiality treatment applies, where needed, in order to ensure that the primary confidentiality cells cannot be estimated with the help of the other non-confidential cells.
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
Recoding of variablesRemoval of variables
Reduction of information
Merging categories
7.2.2.3. Description of methodology
Statistical microdata from CYSTAT’s surveys are accessible for scientific research purposes only and under strict provisions as described below:
In general, access to confidential data collected by the Statistical Service directly from the statistical units, which only allow for indirect identification of the statistical units, shall be granted by permission of the Director, provided that the said data are necessary for specific scientific, research programmes in Cyprus or abroad, the results of which do not disclose specific statistical units and are not to be used for commercial purposes.
Under the provisions of the Official Statistics Law, CYSTAT may release microdata for the sole use of scientific research. Applicants have to submit the request form "APPLICATION FOR DATA FOR RESEARCH PURPOSES" giving thorough information on the project for which microdata are needed.
The application is evaluated by CYSTAT’s Confidentiality Committee and if the application is approved, a charge is fixed according to the volume and time consumed for preparation of the data. Microdata may then be released after an anonymisation process which ensures no direct identification of the statistical units but, at the same time, ensures usability of the data.
To safeguard statistical confidentiality, before being released the microdata undergo various methods of perturbation, such as recoding of variables, removal of variables, reduction of information and merging categories. More specifically, variables that are directly traceable to individual holdings or holders (e.g. identification number of the holding, details on the location of the holding) are either recoded or removed. Other variables on crops and animals are aggregated to a less detailed level, while certain variables (e.g. age of holders and family members) are merged into broader categories.
8.1. Release calendar
In the framework of its mission, CYSTAT provides high-quality statistical information, through the web portal and social media, with the use of statistical products such as announcements, interactive tables, predefined tables, metadata, infographics and publications. The principles and the legal framework governing the dissemination of official statistical data are defined and explained in the document “Dissemination Policy”. The means of dissemination, the main statistical products and the services provided to the users, are also presented. Additionally, the document describes the procedures for data revision and error treatment.
At national level, a release calendar with preliminary dates for the next four months is published at the web portal of the Statistical Service. Announcements are confirmed on the Friday preceding their release. Notifications about the dissemination of statistics are published in the release calendar, which is available on the web portal. The annual release calendar, announced during the 4th quarter of the year, includes provisional dates of publication for the following year, which are finalised the week before publication.
8.2. Release calendar access
The release calendar published at national level can be found at Announcement List.
8.3. Release policy - user access
As provided in Article 4(1) of the Official Statistics Law (Law No. 25(I)/2021) regarding the principle of impartiality, statistics are disseminated in such a way that all users have equal and simultaneous access to the data. CYSTAT΄s main channel for dissemination of statistics is the web portal, which offers the same conditions to everyone and is updated at the same time every working day (12:00 noon). No privileged pre-release access is granted.
In addition to the annual release calendar, users are informed of the various statistical releases through the “Alert” service provided by CYSTAT.
8.3.1. Use of quality rating system
No8.3.1.1. Description of the quality rating system
Not applicable.
Summary and detailed tables of the results of Farm Statistics are disseminated every 3-4 years.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
A news release will accompany the results of the IFS 2023 when finalised.
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
No10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
The results of the IFS 2023 are expected to be uploaded on the web portal of CYSTAT by the end of 2025.
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
Not applicable.
10.3.2. Accessibility of online database
No10.3.3. Link to online database
Not applicable.
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
Use of best practicesQuality guidelines
Compliance monitoring
11.1.3. Description of the quality management system and procedures
Statistics are produced in accordance with the provisions of the European Statistics Code of Practice and in line with the statistical principles governing its implementation.
Furthermore, CYSTAT has set its strategic goal to provide high-quality statistical information in an objective, transparent, reliable and timely manner. CYSTAT considers quality to be its main advantage in a world experiencing a growing trend of instant information which often lacks the necessary proof of quality. In order to realise strategic goals it is imperative to establish policies which ensure that an organisation is moving towards the right direction. For this reason, CYSTAT has established the "Quality Policy" which forms the basis of all statistical activities and leads towards continuous improvement of its statistical output.
In the case of IFS 2023, revisions will be made, if necessary.
11.1.4. Improvements in quality procedures
No further planned improvements at the moment.
11.2. Quality management - assessment
The quality of statistics is assessed according to the following quality criteria: relevance, accuracy, timeliness, punctuality, accessibility and clarity, coherence and comparability. The quality indicators are assessed taking into account Eurostat's defined methodology and recommendations. On the basis of the above criteria, the IFS 2023 results are assessed as being of very good quality.
12.1. Relevance - User Needs
Data are used by Eurostat, the United Nations, FAO, the Ministry of Agriculture, Rural Development and Environment, the Agricultural Research Institute, media, trade unions, farmers' organisations, enterprises and individuals.
12.1.1. Main groups of variables collected only for national purposes
The data collection is organised in line with Regulation (EU) 2018/1091 and the questionnaire included all the characteristics set out by the Regulation.
Some additional characteristics were included in the questionnaire which were necessary for national purposes. These were the following:
1) first name and surname, personal identification code, and contact details of the holders;
2) detailed data on agricultural crops were recorded with respect to the different local authorities where the actual areas were located;
3) areas were recorded with regard to the production of lentils, chick peas, cowpeas, haricot beans, louvana, beetroot, dasheen (kolokasi), groundnuts, sesame, pome fruits by type (apples, pears, etc.), stone fruits by type (peaches, plums, cherries, etc.), tropical fruits by type (bananas, avocados, etc.), nuts by type (almonds, walnuts, etc.), carobs and citrus fruits by type (oranges, lemons, etc.);
4) number of trees for all permanent crops.
12.1.2. Unmet user needs
To the best of our knowledge, all major user needs were met.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
A user satisfaction survey is carried out on an annual basis since 2008 (with the exception of 2010, 2013 and 2020) but is not specific to IFS. It does not allow for adequate conclusions to be made with regard to the farm statistics. The results of the surveys are available on CYSTAT’s web portal at Cystat website. Overall, there is a high level of satisfaction of the users of statistical data published by CYSTAT.
12.2.1. User satisfaction survey
No12.2.2. Year of user satisfaction survey
Not applicable.
12.2.3. Satisfaction level
Not applicable12.3. 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 europa.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
The cases where precision requirements are applicable are set in Annex V of the Regulation (EU) 2018/1091. For all applicable cases, the estimated relative standard errors (RSEs) are below the thresholds stipulated in Annex V except for one case, which occurs for CORE, LAFO, RDEV and MMEQ.
The concerned variable whose relative standard error is high, is A3120_LSU (Breeding sows, live weight 50 kg or over - LSU) with RSE=9.81%. There was an increase in the variability of the characteristics following the changes from the updating of the sampling frame based on the results of the Census 2020. The main reason is that in year 2023 when the sample was drawn the sampling frame included sample units that did not belong to the target population (units that no longer exist or units that are not within the survey scope) and consequently, the actual sample size was smaller since the ineligible holdings included were not surveyed.
To address this issue in the future, a larger sample will be drawn from the agricultural register and all holdings with pigs will be selected in the sample with a selection probability equal to 1. This action should lower the RSEs.
13.2.3. Reference on method of estimation
No adjustments or calibration was needed. Coefficients of Variation (Relative Standard Errors) were calculated using the functions e.svydesign and svystatTM of the R package ReGenesees.
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 europa.
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
Other13.3.1.1.3. Additional information over-coverage error
All ineligible units were removed from the records and the weights of other units were recalculated by considering the corrected population.
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
The under-coverage rate was reduced to 0% following mitigation measures.
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 birthsNew units derived from split
13.3.1.3.3. Actions to minimise the under-coverage error
Coverage errors are taken into account for purposes of updating the Agricultural Register in those cases where the cause of the error is fully clarified. Coverage and other errors were minimised during the multi-stage checking process that took place concurrently with data collection and data entry. Furthermore, the large volume of information that was already available in the Agricultural Register assisted in minimising such errors.
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
Contact errors were assessed by checking the data reported against the prior information available in the existing Agricultural Register, which is of fundamental importance to the Integrated Farm Statistics 2023 and, in many cases, by re-contacting the holder. The need for such corrections was minimal. Information on holders who were unable to be reached was also gathered by contacting local authorities and then follow-up visits and telephone interviews were carried out. The analytical checking process in conjunction with the intensive call-back strategy minimised missing and inaccurate data as well as the number of non-response cases.
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
No specific variables can be listed.
13.3.2.2. Causes of measurement errors
Complexity of variablesSensitivity of variables
Respondents’ inability to provide accurate answers
13.3.2.3. Actions to minimise the measurement error
Explanatory notes or handbooks for enumerators or respondentsTraining of enumerators
13.3.2.4. Impact of measurement error on data quality
Low13.3.2.5. Additional information measurement error
When cases of measurement errors were found, they were corrected at the very moment they were found, therefore by the end of the survey the measurement errors in the data were minimised.
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
Refusal to participateInability to participate (e.g. illness, absence)
Inability to communicate (e.g. language barriers)
13.3.3.1.2. Actions to minimise or address unit non-response
Follow-up interviewsReminders
Legal actions
13.3.3.1.3. Unit non-response analysis
Since the non-response rate was minimal, there was no need to carry out a non-response analysis.
13.3.3.2. Item non-response - rate
Non-response in the sense of only partially completed questionnaires was non-existent.
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
Data entry13.3.4.2. Imputation methods
None13.3.4.3. Actions to correct or minimise processing errors
Data collection and data entry were organised in such a way as to take place almost simultaneously.
Processing errors were not an issue because of two main reasons:
- exhaustive checks were performed by field supervisors on the paper questionnaires before the data entry process,
- the data entry programme was designed in such a way as to identify any possible errors (consistency, value, range, arithmetic, etc.) contained in the questionnaires. The typing errors that might have occurred during the data entry process were easily identified and corrected.
By the end of the survey and the finalisation of the data, errors were eliminated to the minimum.
13.3.4.4. Tools and staff authorised to make corrections
As mentioned in 13.3.4.3. several checks were made by field supervisors on the paper questionnaires before starting the data entry process.
The data entry software was designed by the National Coordinator and an officer from the Data Processing Unit of the Statistical Service of Cyprus using Microsoft Office Access. The data entry program itself was designed in a way so as to identify any possible errors (consistency, value, range, arithmetic, etc.) that the questionnaires might have, as well as typing errors. The data entry was monitored and checked daily for any errors, missing items, changes, and inaccuracies. When the validation of microdata started, a team of 3 persons was formed in order to check and correct any other processing errors and finally validate all microdata. The team consisted of the National Coordinator and a Statistics Officer, who are permanent employees of CYSTAT and a Statistics Research Assistant who is employed under a short-term contract agreement.
13.3.4.5. Impact of processing error on data quality
None13.3.4.6. Additional information processing error
Not available.
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
CYSTAT will not be publishing first results for the IFS 2023.
14.1.2. Time lag - final result
Summary tables with detailed results of the IFS 2023 will be published on CYSTAT's web portal with a time lag of 24 months after the end of the survey reference year (by December 2025).
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 results of the IFS 2023 are expected to be uploaded on the web portal of CYSTAT by the end of 2025.
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
There are no deviations from Regulation (EU) 2018/1091 regarding the definition of agricultural holding.
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
Cyprus lowered the thresholds compared to the EU Regulation thresholds and covered at least 98% of the total utilised agricultural area (excluding kitchen gardens) and at least 98% of the livestock units in the country.
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
The same definitions and classification of variables as included in Regulation (EU) 2018/1091, Commission Implementing Regulation (EU) 2021/2286 and EU handbook were applied; therefore there are no deviations.
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.
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
Cyprus uses the LSU coefficients set out in 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 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 exist from the reference periods/days set in Regulation (EU) 2018/1091.
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
Surveys15.1.6.5. Description of methods to record data on common land
The common land is recorded proportionally to the use by each holding based on their livestock units. The area of common land used by a specific holding is included in the UAA of this holding.
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
No particular problems in the collection of data on common land were faced, since hectares of utilised agricultural area used by a holding on which common rights apply are minimal in Cyprus. Please also note that based on the results of IFS 2023, common land is non-significant.
15.1.7. National standards and rules for certification of organic products
See sub-categories below.
15.1.7.1. Deviations from Council Regulation (EC) No 834/2007
There are no 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. Cyprus is one region at NUTS levels 1, 2 and 3.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
The number of reference periods is 2: 2020 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 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
Not applicable.
15.2.5. Definitions and classifications of variables
See sub-categories below.
15.2.5.1. Changes since the last data transmission to Eurostat
There have been 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
2023 vs 2020, trends on number of holdings
CY data for IFS 2023 were fully comparable with 2020 data because the country provided survey data for holdings from both main frame and frame extension.
With the perspective of the number of holdings by legal form, there was an increase of holdings where the manager is spouse of the holder (FARM_SPOU) and where the manager is member of the holder's family (FARM_FAM) at the expenses of holdings where the holder is the single manager (FARM_HLD) and where the holder is co-manager with the spouse or family member (FARM_HLD_SPOUFAM).
The share of farms with legal personality also increased.
Trends on crops products
- C1300T, C1400T, C1600T + C1700T + C1900T, there is a decreasing trend in the cultivation of barley, oats, triticale and other cereals not elsewhere classified which is also consistent with the annual crop statistics and the areas reported in the IACS register (sorghum is not significant for Cyprus).
- Q0000T, fallow land is decreasing in Cyprus and this is also consistent with the annual crop statistics and the areas reported in the IACS register.
- K0000T, there was a huge increase in kitchen gardens in the Census 2020 due to the change in the threshold. After three years with the carrying out of IFS 2023, the calculation of the coverage errors showed that some of the ineligible holdings were those that remained with only kitchen gardens. Since, by definition, holdings having only kitchen gardens (no market activity) are excluded from the frame, they were not surveyed and were removed from the agricultural register; hence, this explains the large decrease in the area of kitchen gardens in 2023.
- UAAT_IB, there is a decrease in the irrigable area and this is mainly attributed to the fact that the source of irrigation of some holdings is the underground water (perforation), from rivers/dams or from public piped distribution networks. The drought of recent years affected water availability both in rivers and underground and holdings were no longer able to have access to irrigation water. Additionally, after comparisons between the results of the Census 2020 and the IFS 2023, the biggest discrepancies in the irrigable areas of the holdings were observed in holdings cultivating mostly cereals and fodder crops. The majority of these holdings were using water from supply networks and as the cost of water increased, they stopped irrigating their crops, since cereals and fodder crops do not necessarily need to be irrigated
Trends on livestock products
- A2120, there is a decrease in the number of male bovine animals, 1 to less than 2 years old, but to a smaller scale. The decrease is also consistent with the decrease in the data reported in the annual livestock statistics.
- A2230, there is an increase in the number of heifers, 2 years old and over, but to a smaller scale. The increase is also consistent with the increase in the data reported in the annual livestock statistics.
Trends on other gainful activities and labour force
- For OGA_HLD_NRH, in general, other gainful activities of the holders, either related or not related to the agricultural holding, decreased by more than 20% compared to the year 2020. This is mainly due to age, as people grow older or experience health problems.
- For MOGA_FAM_NRH, family members, as they grow older, they retire from their main occupation; therefore, a decrease in the number of family members having other gainful activity not related to the agricultural holding as their main occupation is observed.
- For SOGA_FAM_NRH, as the cost of living in Cyprus rises, many persons tend to engage in secondary gainful activities for extra income. This explains the increase observed in secondary other gainful activities of the holders’ family members.
- The total labour force (holder, manager, family members, regular and non-regular employees) shows a slight increase compared to year 2020. It seems that the labour input to the farms provided by the holders and family members is decreasing and, consequently, a larger number of workers (regular and non) is hired to work in the farms.
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
Comparisons were performed between the results of IFS 2023 and those of the annual crop and animal production statistics. Where significant deviations and discrepancies were identified, further investigations were performed, and the reason was sought. Where necessary, appropriate corrections/amendments were made.
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 ORGANIC CROP PRODUCTION
ARA, PECR and UAAXK0000 appear to be remarkably lower in IFS 2023 compared to crops statistics. The above results are obtained from two different sources with different methodology and definitions.
The IFS 2023 results are provided by CYSTAT and are obtained through a sample survey based on the provisions of Regulation (EU) 2018/1091 on integrated farm statistics and the relevant EU guidelines.
The production and transmission of the organic farming data are the responsibility of the Department of Agriculture of the Ministry of Agriculture, Rural Development and the Environment and are obtained using different sources and methodology. With the introduction of the SAIO Regulation, CYSTAT will take over the responsibility of producing organic farming statistics and this will improve data coherence.
Coherence cross-domain: IFS vs ANIMAL PRODUCTION
Data for A3120 (breeding sows, live weight 50kg or over) are obtained from two different sources, IFS 2023 (sample survey) vs administrative data; hence, some discrepancies are expected. Furthermore, the administrative data collected cover the animal population from organised pig stalls, whereas IFS results include the number of animals from holdings with lower and different thresholds and the extrapolated number of holdings raising breeding sows is larger.
Data for both A4120 (other sheep) and A4220 (other goats) are obtained from two different sources, IFS 2023 (sample survey) vs administrative data; hence, some discrepancies are expected.
Coherence cross-domain: IFS vs ORGANIC ANIMAL PRODUCTION
The discrepancies for A2000_ORG, A2300F_ORG, A4100_ORG, A4200_ORG are due to the different sources with different methodology and definitions.
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
During the data collection of IFS 2023, no other annual sample surveys were conducted. The data collection of all other annual agricultural surveys has been postponed for after the completion of the IFS, in order to minimise the burden on the respondents.
16.2. Efficiency gains since the last data transmission to Eurostat
None16.2.1. Additional information efficiency gains
Not available.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Not available.
16.3.2. Module ‘Labour force and other gainful activities‘
Not available.
16.3.3. Module ‘Rural development’
Not available.
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Not available.
16.3.6. Module ‘Soil management practices’
Not available.
16.3.7. Module ‘Machinery and equipment’
Not available.
16.3.8. Module ‘Orchard’
Not available.
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
There is a formal revision policy at CYSTAT. CYSTAT publishes its Revision Policy on its web portal Revision Policy describing the general rules and principles governing the procedure of revising data published by CYSTAT. The policy is based on the guidelines of the European Statistical System (ESS) regarding revision policies for Principal European Economic Indicators, also taking into account the Quality Assurance Framework of the ESS and the European Statistics Code of Practice.
It is, however, worth noting that after IFS data are validated by Eurostat, they are considered final and are not revised. So far there has never been a need for a revision of the farm statistics data.
17.2. Data revision - practice
Revisions are made, if necessary.
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 Register of Agricultural and Livestock Holdings (Agricultural 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 IFS 2023 sample was selected with the method of one-stage stratified random sampling. The stratification variables were the Standard Output and the farm type of the holding. All holdings were divided into 6 groups according to their Standard Output as follows:
1st group: SO is greater than or equal to 0 euros and smaller than 2 000 euros
2nd group: SO is greater than or equal to 2 000 euros and smaller than 8 000 euros
3rd group: SO is greater than or equal to 8 000 euros and smaller than 25 000 euros
4th group: SO is greater than or equal to 25 000 euros and smaller than 100 000 euros
5th group: SO is greater than or equal to 100 000 euros and smaller than 500 000 euros
6th group: SO is greater than or equal to 500 000 euros
Then, the holdings were divided according to their typology (one level farm type).
18.1.2.2.1. Name of sampling design
Stratified one-stage random sampling18.1.2.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.2.2.3. Use of systematic sampling
No18.1.2.2.4. Full coverage strata
No strata were fully covered.
18.1.2.2.5. Method of determination of the overall sample size
The sample size was decided mainly on the basis of the relevant analysis of former farm statistics data. Financial and organisational possibilities were also considered.
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
Sample18.1.3.2. Sampling design
Same as the answer in 18.1.2.2.
18.1.3.2.1. Name of sampling design
Stratified one-stage random sampling18.1.3.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.3.2.3. Use of systematic sampling
No18.1.3.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.3.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
18.1.3.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.4. 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
Same as the answer in 18.1.2.2.
18.1.4.2.1. Name of sampling design
Stratified one-stage random sampling18.1.4.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.4.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
Same as the answer in 18.1.2.2.
18.1.5.2.1. Name of sampling design
Stratified one-stage random sampling18.1.5.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.5.2.3. Use of systematic sampling
No18.1.5.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.5.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
Same as the answer in 18.1.2.2.
18.1.7.2.1. Name of sampling design
Stratified one-stage random sampling18.1.7.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.7.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
Same as the answer in 18.1.2.2.
18.1.8.2.1. Name of sampling design
Stratified one-stage random sampling18.1.8.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.8.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
Same as the answer in 18.1.2.2.
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.9.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
Same as the answer in 18.1.2.2.
18.1.10.2.1. Name of sampling design
Stratified one-stage random sampling18.1.10.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.10.2.3. Use of systematic sampling
No18.1.10.2.4. Full coverage strata
Same as the answer in 18.1.2.2.4.
18.1.10.2.5. Method of determination of the overall sample size
Same as the answer in 18.1.2.2.5.
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
The sample for IFS 2023 was selected using the R software tool.
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
Agricultural censuses are conducted every 10 years and between agricultural censuses, 2 sample-based data collections are organised.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Face-to-face, non-electronic versionTelephone, non-electronic version
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 Greek
18.3.3 Questionnaire in English
18.3.3 Supplementary questionnaire in Greek
18.3.3 Supplementary questionnaire in English
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Data format checksCompleteness checks
Range checks
Relational checks
Data flagging
Comparisons with previous rounds of the data collection
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
SupervisorsStaff from local departments
Staff from central department
18.4.3. Tools used for data validation
A multilevel checking system of questionnaires was set up.
1. Supervisors had the responsibility of collecting and checking all questionnaires on a daily basis and handing them into the district officers on a weekly basis. The information contained in each questionnaire was checked for errors or inaccuracies including completeness, validations between related variables, acceptable ranges, summations, ratios, and rational checks. Any errors were identified at an early stage and the necessary clarifications were sought so that the degree of repetition of such errors would be minimised. Coverage checks were also made by contacting 5-10% of the respondents for whom a questionnaire was completed for ensuring that the questionnaire was filled out according to instructions provided by the Statistical Service to the enumerators.
2. Checking teams were also set up, working under the guidance and supervision of the district officers. These teams checked the questionnaires submitted by each supervisor and performed additional validations by comparing all variables in relation to information available from previous surveys or other sources.
3. The data entry software was designed using Microsoft Office Access. The data entry programme itself was built in a way so as to identify any possible errors (consistency, value, range, arithmetic, etc.) that the questionnaires may have, as well as errors made during the data entry process (typing errors). The data entry was checked daily for any errors, missing items, inaccuracies and inconsistencies.
18.5. Data compilation
Design weights were obtained by taking the inverse of the inclusion probabilities and are estimated by:
Whi = Nhi / nhi
where:
- Nhi is the total number of holdings in stratum i
- nhi is the number of holdings in the sample selected from stratum i
After the completion of the survey, the weights were recalculated.
18.5.1. Imputation - rate
Not applicable.
18.5.2. Methods used to derive the extrapolation factor
Design weight18.6. 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
CAPO – Cyprus Agricultural Payments Organization
CORE – General, crops and livestock variables of Annex III of Regulation (EU) 2018/1091
CYSTAT – Statistical Service of Cyprus
ESS – European Statistical System
EU – European Union
FAO – Food and Agriculture Organization of the United Nations
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LAFO – Labour force and other gainful activities
LSU – Livestock unit
MMEQ – Machinery and equipment module
NACE – Nomenclature of Economic Activities
NUTS – Nomenclature of territorial units for statistics
RDEV – Rural development
RSE – Relative standard error
SAIO – Statistics on agricultural inputs and outputs
SGM – Standard Gross Margin
SO – Standard output
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.
10 April 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": oranges area, small citrus fruit area, olives 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.
Design weights were obtained by taking the inverse of the inclusion probabilities and are estimated by:
Whi = Nhi / nhi
where:
- Nhi is the total number of holdings in stratum i
- nhi is the number of holdings in the sample selected from stratum i
After the completion of the survey, the weights were recalculated.
See sub-categories below.
Summary and detailed tables of the results of Farm Statistics are disseminated every 3-4 years.
See sub-categories below.
See sub-categories below.
See sub-categories below.
