Farm structure (ef)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: Statistical Service of Cyprus (CYSTAT) 


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Statistical Service of Cyprus (CYSTAT) 

1.2. Contact organisation unit

Agricultural Statistics Unit

1.5. Contact mail address

Statistical Service of Cyprus

Michael Karaoli street

1444 Nicosia

Cyprus 


2. Metadata update Top
2.1. Metadata last certified 31/03/2022
2.2. Metadata last posted 31/03/2022
2.3. Metadata last update 04/08/2022


3. Statistical presentation Top
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 the general public, researchers, farmers and policy-makers to better understand the state of the agricultural sector and the impact of agriculture on the environment. The data follow up the developments 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 collection 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 the most important ones.

The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2018/1874.

The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard gross margin (SGM) (until 2007) or standard output (SO) (as from 2010 onwards) 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. Data for Cyprus is available at NUTS level 1. 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 2019/2020 are set in Commission Implementing Regulation (EU) 2018/1874.

The following groups of variables were collected in 2019/2020:

  • for core: location of the holding, the legal personality of the holding, manager, type of tenure of the utilized agricultural area, variables of land, organic farming, irrigation on the cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
  • for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
  • for the module "Rural development": support received by agricultural holdings through various rural development measures;
  • for the module "Animal housing and rural development module":  animal housing, nutrient use and manure on the farm, manure application techniques, facilities for manure.
3.5. Statistical unit

See sub-category below.

3.5.1. Definition of agricultural holding

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. They 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

- 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 covered are provided in the annex.



Annexes:
3.6.1. Thresholds of agricultural holdings
3.6.1.1. Raised thresholds compared to Regulation (EU) 2018/1091
No
3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
Yes
3.6.2. 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 as defined in item 3.6.1 is covered for the modules ‘Labour force and other gainful activities’ and ‘Rural development’. Data on the module ‘Machinery and equipment’ were not collected in 2020.

3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”

The same population of agricultural holdings as defined in item 3.6.2.

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 production
The 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. Older time series are described in the previous quality reports (national methodological reports).

3.9. Base period

The 2020 data are processed (by Eurostat) with 2017 standard output coefficients (calculated as a 5-year average of the period 2015-2019). For more information, you can consult the definition of the standard output.


4. Unit of measure Top

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 specific characteristics.


5. Reference Period Top

See sub-categories below.

5.1. Reference period for land variables

Land characteristics refer to areas used in the reference period of 1 September 2019 to 31 August 2020. In the case of successive crops from the same piece of land, the land use refers to a crop that is harvested during the reference year, regardless of when the crop in question is sown.

5.2. Reference period for variables on irrigation and soil management practices

The total irrigable area refers to areas used in the reference period of 1 September 2019 to 31 August 2020.

Reference period for other variables of irrigation and soil management practices is not applicable for 2019/2020.

5.3. Reference day for variables on livestock and animal housing

For variables on livestock and animal housing, the reference day is 31 December 2020.

5.4. Reference period for variables on manure management

The 12-month period ended on 31 December 2020. This period includes the reference day used for livestock and animal housing.

5.5. Reference period for variables on labour force

The 12-month period of 1 September 2019 - 31 August 2020.

5.6. Reference period for variables on rural development measures

The three-year period ending on 31 December 2020.

5.7. Reference day for all other variables

The reference day is 31 December 2020.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

See sub-categories below.

6.1.1. National legal acts and other agreements
Legal act
6.1.2. 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. This law specifies the tasks of the Statistical Service and defines its role and function as the agency responsible for the production of official statistics.

6.1.3. Link to national legal acts and other agreements

The link to The Official Statistics Law is provided below. 



Annexes:
Official Statistics Law of 2021
6.1.4. Year of entry into force of national legal acts and other agreements

The purpose of the new Law, which entered into force on the 18th of March 2021, was to review and modernize the legislation governing 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. The new law also attempted to include recommendations that were highlighted during the peer review process of the national statistical system, conducted in Cyprus in March 2015.

Article 3 of the National Official Statistics Law, No. 25(I) of 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 programs of work without any further procedure.

6.1.5. Legal obligations for respondents
Yes
6.2. Institutional Mandate - data sharing

Official statistics compiled by the Statistical Service and the other national authorities on the basis of data resulting from a survey or from other sources shall be published in such a manner as to render impossible the direct or indirect disclosure of the identity of the persons who provided the data or the statistical units to which the data relate.


7. Confidentiality Top
7.1. Confidentiality - policy

Official statistics are released in accordance with the confidentiality provisions laid down in the following:

  • Official Statistics Law of 2021 (Law No. 25(I)/2021), Article 16 on protection of confidential data.
  • Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendment (especially Chapter 5 on statistical confidentiality).
  • European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
  • CYSTAT's internal Code of Practice for the Collection, Publication, and Storage of Statistical Data.
7.2. Confidentiality - data treatment

See sub-categories below.

7.2.1. Aggregated data

See sub-categories below.

7.2.1.1. Rules used to identify confidential cells
Threshold rule (The number of contributors is less than a pre-specified threshold)
Secondary confidentiality rules
7.2.1.2. Methods to protect data in confidential cells
Cell suppression (Completely suppress the value of some cells)
7.2.1.3. Description of rules and methods

The treatment of confidential data is regulated by CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data. 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.

Eurofarm data are sent through Edamis encrypted. The summary tables show only aggregates for the whole country and no microdata are included in order to ensure confidentiality.

7.2.2. Microdata

See sub-categories below.

7.2.2.1. Use of EU methodology for microdata dissemination
Yes
7.2.2.2. Methods of perturbation
None
7.2.2.3. Description of methodology

The methodology is described in the dedicated section of Eurostat's website: https://ec.europa.eu/eurostat/web/microdata

 


8. Release policy Top
8.1. Release calendar

CYSTAT has rendered its website as the main tool for the dissemination of statistical information. CYSTAT΄s website is available to everyone with Internet access, 24 hours/day, 7 days/week.

CYSTAT publishes on its website two types of release calendar: A weekly release calendar, which contains the dates of the announcements of the Statistical Service which are scheduled to be released in the following week, and a quarterly release calendar.

The statistical data are available in tables and publications, under various statistical subthemes, that users can either view or download. In addition, all released announcements can be found on the "Release Calendar" web page and also in the corresponding statistical subtheme.

CYSTAT΄s website is available in both Greek and English and all information and services are available free of charge. It is updated at 12:00 noon every working day.

8.2. Release calendar access

Access to the release calendar can be found below.



Annexes:
Announcements
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 website which offers the same conditions to everyone and is updated at the same time every working day. All users have equal access to statistical releases at the same time.

8.3.1. Use of quality rating system
No
8.3.1.1. Description of the quality rating system

Not applicable.


9. Frequency of dissemination Top

Summary tables of the results of the Farm Structure Surveys are disseminated every 3-4 years. The results of the Census of Agriculture 2020 are scheduled to be uploaded on the website by the end of 2022. 


10. Accessibility and clarity Top
10.1. Dissemination format - News release

See sub-categories below.

10.1.1. Publication of news releases
Yes
10.1.2. Link to news releases

A news release accompanies the results of the Census of Agriculture 2020 and the link is provided below:

https://www.cystat.gov.cy/en/PressRelease?id=68214

 

 

10.2. Dissemination format - Publications

See sub-categories below.

10.2.1. Production of paper publications
No
10.2.2. Production of on-line publications
Yes, in English also
10.2.3. Title, publisher, year and link

Title: CENSUS OF AGRICULTURE - SUMMARY TABLES, 2020

Publisher: Statistical Service of Cyprus

Year: 2023

Link: https://www.cystat.gov.cy/en/KeyFiguresList?s=28

Title: CENSUS OF AGRICULTURE - DETAILED TABLES, 2020

Publisher: Statistical Service of Cyprus

Year: 2023

Link: https://www.cystat.gov.cy/en/KeyFiguresList?s=28

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
No
10.3.3. Link to online database

Not applicable.

10.4. Dissemination format - microdata access

See sub-category below.

10.4.1. Accessibility of microdata
Yes
10.5. 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
No
10.6.3. Title, publisher, year and link to national reference metadata

Not applicable.

10.6.4. Availability of national handbook on methodology
No
10.6.5. Title, publisher, year and link to handbook

Not applicable.

10.6.6. Availability of national methodological papers
No
10.6.7. Title, publisher, year and link to methodological papers

Not applicable.

10.7. Quality management - documentation

Not available. 


11. Quality management Top
11.1. Quality assurance

See sub-categories below.

11.1.1. Quality management system
Yes
11.1.2. Quality assurance and assessment procedures
Use of best practices
Quality 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.

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 statistics are assessed as being of very good quality.


12. Relevance Top
12.1. Relevance - User Needs

Data are used by Eurostat, the Ministry of Agriculture, Rural Development and Environment, the United Nations, FAO, media, researchers, scientists, enterprises, individuals, trade unions, National Accounts.

12.1.1. Main groups of variables collected only for national purposes

The data collection is organized in line with Regulation (EU) 2018/1091 and the questionnaire included all the characteristics set out by the Regulation.

Some characteristics were added to the questionnaire which are not mentioned in Regulation (EU) 2018/1091 but are 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 (kolocasi), 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, but is not specific to particular statistical products. Hence, it does not allow for adequate conclusions to be made with regard to the agricultural census.

12.2.1. User satisfaction survey
No
12.2.2. Year of user satisfaction survey

Not applicable.

12.2.3. Satisfaction level
Not applicable
12.3. Completeness

Information on low- and zero prevalence variables is available on: Eurostat's website.

12.3.1. Data completeness - rate

Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.


13. Accuracy Top
13.1. Accuracy - overall

See categories below.

13.2. Sampling error

See sub-categories below.

13.2.1. Sampling error - indicators

The relative standard errors for the main variables are included in the annex.



Annexes:
13.2.1 Relative Standard Errors
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091

The core and modules data collection for the year 2020 was carried out as a Census, therefore there are no cases where the estimated RSEs are above thresholds.

13.2.3. Methodology used to calculate relative standard errors

The core and modules data collection for the year 2020 was carried out as a Census and no adjustments or calibration was needed.

13.2.4. Impact of sampling error on data quality
None
13.3. 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 provided in the annex. The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat. 



Annexes:
13.3.1.1. Over-coverage rate and Unit non-response rate
13.3.1.1.1. Types of holdings included in the frame but not belonging to the population of the core (main frame and if applicable frame extension)
Below thresholds during the reference period
Temporarily out of production during the reference period
Ceased activities
Duplicate units
13.3.1.1.2. Actions to minimize the over-coverage error
Other
13.3.1.1.3. Additional information over-coverage error

Since core and modules data collection was carried out as a census, no weights were used and all ineligible holdings were removed from the Agricultural Register. 

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 undercoverage rate is 0.7%.

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 births
New 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 farm register in those cases where the cause of the error is fully clarified. Coverage and other errors were minimized 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 minimizing such errors. 

13.3.1.3.4. Additional information under-coverage error

Not available.

13.3.1.4. Misclassification error
No
13.3.1.4.1. Actions to minimise the misclassification error

Not applicable.

13.3.1.5. Contact error
Yes
13.3.1.5.1. 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 Census of Agriculture 2020, and, in many cases, by re-contacting the holder by telephone. The need for such corrections was minimal. Information on holders who were unable to be reached was also gathered by contacting local authorities, follow-up visits, and telephone interviews were carried out during the data collection process. 

The analytical checking process in conjunction with the intensive call-back strategy minimised almost entirely missing and inaccurate data as well as the number of missing cases.

13.3.1.6. Impact of coverage error on data quality
Low
13.3.2. Measurement error

See sub-categories below.

13.3.2.1. List of variables mostly affected by measurement errors

When cases of measurement errors were found, they were corrected at the very moment they were found, therefore by the end of the Census the measurement errors in the data were minimized.

13.3.2.2. Causes of measurement errors
Not applicable
13.3.2.3. Actions to minimise the measurement error
Pre-testing questionnaire
Explanatory notes or handbooks for enumerators or respondents
Training of enumerators
13.3.2.4. Impact of measurement error on data quality
Low
13.3.2.5. Additional information measurement error

Not available.

13.3.3. Non response error

See sub-categories below.

13.3.3.1. Unit non-response - rate

The unit non-response rate is provided in the annex under item 13.3.1.1The 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 that 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 participate
Inability 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 interviews
Reminders
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 applicable
13.3.3.2.3. Actions to minimise or address item non-response
None
13.3.3.3. Impact of non-response error on data quality
None
13.3.3.4. 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 entry
13.3.4.2. Imputation methods
None
13.3.4.3. Actions to correct or minimise processing errors

Data collection and data entry were organized in such a way as to take place almost simultaneously. 

Processing errors were not an issue because of two main reasons:

  • several checks were made by area supervisors on the paper questionnaires before the data entry process
  • the data entry program was designed in such a way as to identify any possible errors (consistency, value, range, arithmetic, etc.) that the questionnaires might have. The errors that were made during the data entry process (typing errors) were easily corrected through the re-typing of the correct data.

By the end of the survey and the finalization of the data, all errors were eliminated. 

13.3.4.4. Tools and staff authorised to make corrections

As mentioned in 13.3.4.3. several checks were made by area 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.

13.3.4.5. Impact of processing error on data quality
None
13.3.4.6. Additional information processing error

Not available.

13.3.5. Model assumption error

Not applicable.


14. Timeliness and punctuality Top
14.1. Timeliness

See sub-categories below.

14.1.1. Time lag - first result

Cystat did not publish the first results for the Census of Agriculture 2020. Final results have been published on Cystat's website with a time lag of 30 months after the end of the survey reference year (December 2020 - June 2023). 

14.1.2. Time lag - final result

The final results were sent to Eurostat by the end of March 2022.

Summary tables with summary and detailed results of the Census of Agriculture 2020 have been published on Cystat's website with a time lag of 30 months after the end of the survey reference year (December 2020 - June 2023). 

14.2. Punctuality

See sub-categories below.

14.2.1. Punctuality - delivery and publication

See sub-categories below.

14.2.1.1. Punctuality - delivery

The data are provided to Eurostat by 31 March 2022, within the deadline specified in Regulation (EU) 2018/1091.

14.2.1.2. Punctuality - publication

Not applicable.


15. Coherence and comparability Top
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 100% of the total utilized agricultural area (excluding kitchen gardens) and 100% 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

Not applicable.

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) 2018/1874, 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 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.

The information is available in the annex.



Annexes:
15.1.4.1.1. AWU
15.1.4.1.2. Point chosen in the Annual work unit (AWU) percentage band to calculate the AWU of holders, managers, family and non-family regular workers

The information is available in the annex under item 15.1.4.1.1. 

15.1.4.1.3. AWU for workers of certain age groups

The information is available in the annex under 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

Data is collected, sent to Eurostat, and published in compliance with 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 exists
15.1.6.1. Collection of common land data
Yes
15.1.6.2. 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
Surveys
15.1.6.5. 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 2020 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 NUTS1,2 and 3 levels.

15.2. Comparability - over time

See sub-categories below.

15.2.1. Length of comparable time series

The number of reference periods is 1.

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 changes
15.2.2.2. Description of changes

Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However, in Cyprus, there are no fur animals.

15.2.3. Thresholds of agricultural holdings

See sub-categories below.

15.2.3.1. Changes in the thresholds of holdings for which core data are sent to Eurostat since the last data transmission
There have been sufficient changes to warrant the designation of a break in series
15.2.3.2. Description of changes

The main differences in the thresholds concern only the area variables.

In the Census of 2020, agricultural holdings were considered and surveyed only if they had utilized agricultural area equal or greater than two decares (0.2 ha) or if they had at least one hundred square meters (100m²=0.01 ha) of greenhouse or at least one decare (0.1 ha) of vineyards or at least one hundred square meters (100m²=0.01 ha) mushrooms.

Instead, in the Farm Structure Survey of 2016 agricultural holdings were considered and surveyed only if they had utilized agricultural area equal to or greater than one decare (1 decare = 0.1 ha) or if they had at least half decare (0.05 ha) of greenhouse.

Consequently, several main variables were affected by the change, especially the number of holdings and the labour force.

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 changes
15.2.4.2. Description of changes

Not applicable.

15.2.5. Definitions and classifications of variables

See sub-categories below.

15.2.5.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series
15.2.5.2. Description of changes

Legal personality of the agricultural holding

In IFS 2020, there is a new class (“shared ownership”) for the legal personality of the holding compared to FSS 2016, which triggers fluctuations of holdings in the classes of sole holder holdings. However, the impact was minimal.

Other livestock n.e.c.

In FSS 2016, deer were included in this class, but in IFS 2020 they are classified separately. This does not change the data for Cyprus since the variable for deer does not exist.

Also in FSS 2016, there was a class for the collection of equidae. That has been dropped and equidae are included in IFS 2020 in "other livestock n.e.c."

Livestock units

In FSS 2016, turkeys, ducks, geese, ostriches, and other poultry were each considered in a separate class with a coefficient of 0.03 for all the classes except for ostriches (coefficient 0.035). In IFS 2020, the coefficients were adjusted accordingly, with turkeys remaining at 0.03, ostriches remaining at 0.35, ducks adjusted to 0.01, geese adjusted to 0.02, and other poultry fowls n.e.c. adjusted to 0.001. 

Organic animals

While in FSS 2016 only fully compliant (certified converted) animals were included, in IFS 2020 both animals under conversion and fully converted were 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 sufficient changes to warrant the designation of a break in series
15.2.6.2. Description of changes

The main difference concerns the reference day for recording the livestock characteristics. In FSS 2016, the reference day was 1 October 2016, whereas in IFS 2020 the reference day was 31 December 2020.

The two different reference days have about a 3-month time lag between them, which implies there are several changes in the structure of the livestock units and the livestock numbers; hence there is a break in the series, and livestock data are not comparable with previous FSS results.  

Also, the reference period for manure management variables changed. The information collected for some variables in FSS 2016 refers to the reference period from 1 September 2015 to 31 August 2016, whereas in IFS 2020 the 12-month reference period was ending on 31 December 2020. 

15.2.7. Common land

See sub-categories below.

15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no changes
15.2.7.2. Description of changes

Not applicable.

15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat

Animal production statistics:

There is a break in the series since the reference day for livestock variables has changed from 1 October to 31 December. The main reason for the change in the reference day was to be comparable to the annual livestock statistics.

Crops production statistics:
- C1110T, there is an increasing trend in the cultivation of common wheat and spelt, which is also consistent with the annual crop statistics data.
- C1200T, there is a decreasing trend for rye, since farmers prefer the cultivation of other types of cereals (e.g., common wheat), with the exception of FSS 2016 where the hectares for cultivating rye seem to have been overestimated.
- G1000T, there is an increasing trend in the cultivation of temporary grasses and grazings. 
- G2000T, there is an increasing trend in the cultivation of leguminous plants harvested green. 
- land variables, there have been changes in the thresholds to warrant the designation of a break in the series and this was also mentioned in the NMR. In the Census of 2020, agricultural holdings were considered and surveyed only if they had utilized agricultural area equal to or greater than two decares (0.2 ha) or if they had at least one hundred square meters (100m²=0.01 ha) of greenhouse or at least one decare (0.1 ha) of vineyards or at least one hundred square meters (100m²=0.01 ha) mushrooms, whereas, in previous Farm Structure Surveys, agricultural holdings were considered and surveyed only if they had utilized agricultural area equal or greater than one decare (1 decare = 0.1 ha) or if they had at least half decare (0.05 ha) of the greenhouse. Consequently, some main variables were affected by the change and K0000T (kitchen gardens) was one of them, which explains the very large increase.
- MOGA_NFAM_RH and SOGA_NFAM_RH are non-significant as indicated in the NSNE dataset.
- forest areas, there is a large decrease compared to the historical data and this is mainly attributed to the catastrophic fires that took place in
Cyprus (there is a fire in the forest almost every year) especially during 2016-2017 and 2020-2021. Consequently, all forest areas along with short
rotation coppice areas (SRCAA) have decreased through the years.
- The comparisons related to grapes for wine are somehow incorrect since in Cyprus quality wine is considered only in the case of grapes for wine
with protected designation of origin (PDO). Hence, in order to be correct, we would have to compare quality wine vs. W1110T and other wine
grapes vs. W1120T+W1190T (results for the year 2020 are similar to historical data).
- W1300T (grapes for raisins outdoor), there is an increase compared to the historical data from previous farm structure surveys. In 2020 there are twice the number compared to in 2016. Clearly, more farmers are interested in the cultivation of grapes for raisins.
- I5000T, the data from the Census of Agriculture 2020 showed an increase in the areas cultivated with aloe vera and roses for industrial use. Based on the information collected from the farmers in Cyprus, the processing of aloe vera for the production of medicinal products and the processing of roses for rose oil or rose water became very popular in recent years, which can explain the increase in cultivated areas.
- L0000T, comparing the historical data, there is an increasing trend; the FSS 2013 and FSS 2016 seem to have been underestimated.
- PECRS, the majority of the area concerning permanent crops under glass concerns loquats, dragon fruits, and passion fruits. The increase in the area of IFS 2020 can be attributed mainly to tropical fruits.
 
Rural Development Measures
The increase between 2016 and 2020 of the farms that have benefitted from rural development measures resulted mainly from the support of the agri_environment_climate measure (RDEV_28_10) and the payments to areas facing natural or other specific constraints (RDEV_31_13). This increase has also been crosschecked with the information received from the administrative source
15.2.9. Maintain of statistical identifiers over time
Partially
15.3. 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
Yes
15.3.3.2. Results of analysis at micro level

Comparisons were performed between the results of IFS 2020 with those of the annual crop and the 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
Yes
15.3.4.2. Results of analysis at macro level
Some explanations for the discrepancies between IFS and APRO are explained here:
- I0000 (industrial crops outdoor), the discrepancies are due to aromatic, medicinal, and culinary plants which are marked as NS in annual crop statistics, and no data are transmitted.
- K0000 (kitchen gardens outdoor), data for annual statistics are the result of FSS and are updated when the survey is completed; hence for the year 2020 revised data will have to be re-transmitted.
- P0000 (dry pulses and protein crops for the production of grain outdoor), data for annual crops statistics do not refer to all dry pulses cultivated in Cyprus because of the unavailability of annual information. Annual crop statistics data include only broadbeans, beans, cowpeas, lentils, chickpeas
and louvana.
- J0000 (permanent grassland outdoor), C0000 (cereals for the production of grain outdoor), C1110 (common wheat and spelt outdoor), C1300 (barley outdoor), T0000 (citrus fruit outdoor), Q0000 (fallow land outdoor), G1000 (temporary grasses and grazings outdoor), G2000 (leguminous plants harvested green outdoor), G3000 (green maize outdoor), G9900 (other plants harvested green from arable land n.e.c. outdoor), data for annual crops statistics are provisional for the year 2020 and final data will be re-transmitted.
- C1400 (oats and spring cereal mixtures outdoor), data for annual crop statistics are provisional for the year 2020, and final data will be retransmitted. However, the category in annual crops statistics includes only oats, since cereal mixtures are marked as non-significant, and is the result of the
annual sample survey.
 
- N0000 (flowers and ornamental plants outdoor), data for annual crop statistics include production areas both outdoor and under glass or highly accessible cover and are also provisional for the year 2020. Final data will be re-transmitted
- I0000 (industrial crops outdoor), the discrepancies are due to aromatic, medicinal, and culinary plants which are marked as NS in annual crop statistics, and no data are transmitted.
- P0000 (dry pulses and protein crops for the production of grain outdoor), data for annual crops statistics do not refer to all dry pulses cultivated in Cyprus because of the unavailability of annual information. Annual statistics data include only broadbeans, beans, cowpeas, lentils, chickpeas and
louvana.
 
For A4200 (goats) the discrepancy on Animal Statistics is considered marginal. Data are obtained from two different sources, IFS 2020 vs. administrative data, hence a slight discrepancy is expected.
15.4. Coherence - internal

The data are internally consistent since a wide range of validation rules have been applied.


16. Cost and Burden Top

See sub-categories below.

16.1. Coordination of data collections in agricultural statistics

During the data collection of IFS 2020, no other annual surveys were conducted. The collection of all annual agricultural surveys has been postponed after the completion of the Census, in order to minimize the burden on the respondents. 

16.2. Efficiency gains since the last data transmission to Eurostat
None
16.2.1. Additional information efficiency gains

Not available.

16.3. Average duration of farm interview (in minutes)

See sub-categories below.

16.3.1. Core

Not 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’

Not available.


17. Data revision Top
17.1. Data revision - policy

CYSTAT's Revision Policy describes the general rules and principles governing the procedure of revising data published by CYSTAT.  As part of this policy, CYSTAT publishes a list of scheduled revisions on an annual basis, which can be found on the release calendar page (see attached link in 8.2.).

In the case of IFS 2020, revisions will be made, if necessary.



Annexes:
Revision Policy
17.2. Data revision - practice

Revisions are made, if necessary.

17.2.1. Data revision - average size

Not requested.


18. Statistical processing Top


Annexes:
18. Timetable of statistical process
18.1. Source data

See sub-categories below.

18.1.1. Population frame

See sub-categories below.

18.1.1.1. Type of frame
List frame
18.1.1.2. Name of frame

The Register of Agricultural and Livestock Holdings (Agricultural Register).

18.1.1.3. Update frequency
Continuous
18.1.2. Core data collection on the main frame

See sub-categories below.

18.1.2.1. Coverage of agricultural holdings
Census
18.1.2.2. Sampling design

Not applicable for 2019/2020.

18.1.2.2.1. Name of sampling design
Not applicable
18.1.2.2.2. Stratification criteria
Not applicable
18.1.2.2.3. Use of systematic sampling
Not applicable
18.1.2.2.4. Full coverage strata

Not applicable for 2019/2020.

18.1.2.2.5. Method of determination of the overall sample size

Not applicable for 2019/2020.

18.1.2.2.6. Method of allocation of the overall sample size
Not applicable
18.1.3. Core data collection on the frame extension

See sub-categories below.

18.1.3.1. Coverage of agricultural holdings
Census
18.1.3.2. Sampling design

Not applicable.

18.1.3.2.1. Name of sampling design
Not applicable
18.1.3.2.2. Stratification criteria
Not applicable
18.1.3.2.3. Use of systematic sampling
Not applicable
18.1.3.2.4. 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 applicable
18.1.4. Module “Labour force and other gainful activities”

See sub-categories below.

18.1.4.1. Coverage of agricultural holdings
Census
18.1.4.2. Sampling design

Not applicable.

18.1.4.2.1. Name of sampling design
Not applicable
18.1.4.2.2. Stratification criteria
Not applicable
18.1.4.2.3. Use of systematic sampling
Not applicable
18.1.4.2.4. 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 applicable
18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable
18.1.5. Module “Rural development”

See sub-categories below.

18.1.5.1. Coverage of agricultural holdings
Census
18.1.5.2. Sampling design

Not applicable.

18.1.5.2.1. Name of sampling design
Not applicable
18.1.5.2.2. Stratification criteria
Not applicable
18.1.5.2.3. Use of systematic sampling
Not applicable
18.1.5.2.4. 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 applicable
18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable
18.1.6. Module “Animal housing and manure management module”

See sub-categories below.

18.1.6.1. Coverage of agricultural holdings
Census
18.1.6.2. Sampling design

Not applicable.

18.1.6.2.1. Name of sampling design
Not applicable
18.1.6.2.2. Stratification criteria
Not applicable
18.1.6.2.3. Use of systematic sampling
Not applicable
18.1.6.2.4. Full coverage strata

Not applicable.

18.1.6.2.5. Method of determination of the overall sample size

Not applicable.

18.1.6.2.6. Method of allocation of the overall sample size
Not applicable
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable
18.1.12. Software tool used for sample selection

Not applicable.

18.1.13. Administrative sources

See sub-categories below.

18.1.13.1. Administrative sources used and the purposes of using them

The information is available on Eurostat's website.

18.1.13.2. Description and quality of the administrative sources

No administrative sources were used.

See the attached Excel file in the Annex.

18.1.13.3. Difficulties using additional administrative sources not currently used
None
18.1.14. Innovative approaches

The information on innovative approaches is available on Eurostat's website.

18.2. Frequency of data collection

The agricultural Census is conducted every 10 years. The decennial agricultural Census is complemented by sample or census-based data collections organised every 3-4 years in-between.

18.3. Data collection

See sub-categories below.

18.3.1. Methods of data collection
Face-to-face, non-electronic version
Telephone, non-electronic version
18.3.2. Data entry method, if paper questionnaires
Manual
18.3.3. Questionnaire

The questionnaire is provided in annex.



Annexes:
18.3.3. IFS QUESTIONNAIRE_EL
18.3.3. IFS QUESTIONNAIRE_EN
18.3.3. IFS 2020 SUPPLEMENTARY QUESTIONNAIRE_EN
18.3.3. IFS 2020 SUPPLEMENTARY QUESTIONNAIRE_EL
18.4. Data validation

See sub-categories below.

18.4.1. Type of validation checks
Data format checks
Completeness checks
Range checks
Relational checks
Data flagging
Comparisons with previous rounds of the data collection
18.4.2. Staff involved in data validation
Supervisors
Staff 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 made were identified at an early stage and the necessary clarifications were sought so that the degree of repetition of such errors would be minimized. Coverage checks were also made by contacting 5-10% of the respondents for whom a questionnaire was completed and ensuring that the questionnaire was filled out according to instructions, that is, during the personal visit or telephone call of the enumerator all questions were asked.  

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 checking by comparing all variables in relation to information available from previous surveys or other available information.

3. The data entry software was designed using Microsoft Office Access. The data entry program 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, changes, and inaccuracies. 

18.5. Data compilation

Not available.

18.5.1. Imputation - rate

Not applicable.

18.5.2. Methods used to derive the extrapolation factor
Not applicable
18.6. Adjustment

None.

18.6.1. Seasonal adjustment

Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.


19. Comment Top

See sub-categories below.

19.1. List of abbreviations

CAP – Common Agricultural Policy

CAPI –  Computer Assisted Personal Interview

CATI – Computer Assisted Telephone Interview

CAWI – Computer Assisted Web Interview

FSS – Farm Structure Survey

IACS – Integrated Administration and Control System

IFS – Integrated Farm Statistics

LSU – Livestock units

NACE – Nomenclature of Economic Activities

NUTS – Nomenclature of territorial units for statistics

PAPI – Paper and Pencil Interview

SO – Standard output

UAA – Utilised agricultural area

19.2. Additional comments

No additional comments.


Related metadata Top


Annexes Top