Hellenic Statistical Authority (ELSTAT) 

Agriculture Livestock Fishery and Environment Statistics Division / Structure of Agricultural and Livestock Holdings Section

Pireos 46 & Eponiton Str.,18510 – Piraeus, P.O.Box 80847 

The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock, and employment. There are also more detailed data on labour force, rural development measures and the impact of agriculture on the environment, especially animal housing and manure management.

The data are used by public, researchers, farmers and policymakers to better understand the state of the farming sector and its impact on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.

The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.

The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.

Data are arranged in tables using several classifications. Please find below information on most classifications.

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

The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard 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.

The statistics cover agricultural holdings undertaking agricultural activities as defined in item 3.5 below and meeting the minimum coverage requirements (thresholds) as listed in item 3.6 below.

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 2020 are set in Commission Implementing Regulation (EU) 2018/1874.

The following groups of variables are collected in 2020:

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

See sub-category below.

The agricultural holding is a single unit, both technically and economically, that has a single management and that undertakes economic activities in agriculture in accordance with Regulation (EC) No 1893/2006 belonging to groups:

- A.01.1: Growing of non-perennial crops

- A.01.2: Growing of perennial crops

- A.01.3: Plant propagation

- A.01.4: Animal production

- A.01.5: Mixed farming or

- The “maintenance of agricultural land in good agricultural and environmental condition” of group A.01.6 within the economic territory of the Union, either as its primary or secondary activity.

Regarding activities of class A.01.49, only the activities “Raising and breeding of semi-domesticated or other live animals” (with the exception of raising of insects) and “Bee-keeping and production of honey and beeswax” are included.

See sub-categories below.

The thresholds of agricultural holdings are available in the annex.

The same population of agricultural holdings defined in item 3.6.1

The above answer holds for the modules ‘Labour force and other gainful activities’ and ‘Rural development’. The module ‘Machinery and equipment’ is not collected in 2020.

The same population of agricultural holdings defined in item 3.6.2.

See sub-categories below.

The entire territory of the country.

Mount Athos

Not available

Farm structure statistics for Greece cover the period from 1983 onwards. Older time series are described in the previous quality reports (national methodological reports).

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, please 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) or number of hives (for bees), labour force in persons or AWU (annual working units) or full-time working days, standard output in Euro, places for animal housing etc.) and
• the number of agricultural holdings having these characteristics.

See sub-categories below.

The use of land refers to the reference year 2019/2020 and more specifically to the period 01/10/2019-30/09/2020. 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.

The 12-month period ending on 30/09/2020 within the reference year 2019/2020.

The reference day 01/11/2020 within the reference year 2019/2020.

The 12-month period ending on 01/11/2020. This period includes the reference day used for livestock and animal housing.

The 12-month period ending on 30/09/2020 within the reference year 2019/2020.

The three-year period ending on 31/12/2020.

The reference day 30/09/2020 within the reference year 2019/2020.

See sub-categories below.

1. Greek Statistical Law No 3832/2010, as in force

2. Regulation on the Operation and Administration of the Hellenic Statistical Authority (ELSTAT), 2012 (Government Gazette 2390/B/28.08.2012)

3. Regulation on the Statistical Obligations of the agencies of the Hellenic Statistical System (Government Gazette 4083/Β/20.12.2016)

4. Law No 4772/2021 Conducting General Censuses for the year 2021 by the Hellenic Statistical Authority, emergency measures for counteracting the consequences of COVID-19 pandemic, emergency fiscal and tax measures (Government Gazette 17/A/05-02-2021)

1. LAW no: 3832, 9 March 2010

2. Regulation on the Operation and Administration of the Hellenic Statistical Authority

3. Regulation on the Statistical Obligations of the Agencies of the Hellenic Statistical System

4. ΝΟΜΟΣ ΥΠ’ ΑΡΙΘΜ. 4772

Each act/agreement enters into force on the respective date of issue.

For data producing agencies that are part of the Hellenic Statistical System (ELSS), issues pertaining to the development, production and dissemination of statistics, are arranged by agency and laid down in form of memoranda of cooperation and written agreements between ELSTAT and the agencies (Regulation on the Statistical Obligations of the agencies of the Hellenic Statistical System (Government Gazette 4083/Β/20.12.2016).

Data producing agencies, that are not part of the Hellenic Statistical System, are subject to the provisions mentioned in section 6.1.5.

The issues concerning the observance of statistical confidentiality by the Hellenic Statistical Authority (ELSTAT) are arranged by articles 7, 8 and 9 of the Law 3832/2010 as in force, by Articles 8, 10 and 11(2) of the Regulation on Statistical Obligations of the agencies of the Hellenic Statistical System and by Articles 10 and 15 of the Regulation on the Operation and Administration of ELSTAT.

More precisely ELSTAT disseminates the statistics in compliance with the statistical principles of the European Statistics Code of Practice and in particular with the principle of statistical confidentiality: http://www.statistics.gr/en/statistical-confidentiality?inheritRedirect=true

Protection of personal data

ELSTAT abides by the commitments and obligations arising from the applicable EU and national legislation on the protection of the individual from the processing of personal data and the relevant decisions, guidelines and regulatory acts of the Hellenic Data Protection Authority.

Pursuant to the Regulation on the protection of natural persons with regard to the processing of personal data [Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 (General Data Protection Regulation - GDPR)], ELSTAT implements the appropriate technical and organisational measures for ensuring adequate level of security against risks for the personal data it collects and has access to, in the context of carrying out its tasks, in order to meet the requirements of this Regulation and to protect these personal data from any unauthorised access or illegal processing.

The personal data collected by ELSTAT are used exclusively for purposes related to the conduct of surveys and the production of relevant statistics. Only ELSTAT has access to the data. The controller is the person appointed by law pursuant to the relevant provisions concerning the Legal Entities of Public Law and the Independent Authorities. The data are stored in the databases of ELSTAT for as long as required by the relevant legislation.

Legal basis of the processing: Article 6, para 1(c) and 1(d) of the General Data Protection Regulation (GDPR)

https://www.statistics.gr/el/privacy-info

See sub-categories below.

See sub-categories below.

The above procedures are implemented using the free version of τ-argus software v4.1.0 distributed by Statistics Netherlands, therefore the identification of confidential cells and their suppression (primary and secondary) is automated.

To ensure adherence to the confidentiality provisions set out in section 7.1 Confidentiality – policy, prior to their publication ΙFS data are subject to the following procedures:

• Microaggregation at NUTS3 level,
• Primary cell suppression on the aggregated data, using a minimum frequency/threshold less than three (3), according to the recommendations of the Statistical Confidentiality Committee (SCC) of ELSS, and
• secondary cell suppression with full singleton handling, using Optimal Salazar solution.

See sub-categories below.

ELSTAT may grant researchers conducting statistical analyses for scientific purposes access to data that enable the indirect identification of the statistical units concerned, but only after a favorable recommendation by the Statistical Confidentiality Committee (SCC) operating within the ELSS.  The access is granted provided the following conditions are satisfied:

a) an appropriate request together with a detailed research proposal in conformity with current scientific standards have been submitted;

b) the research proposal indicates in sufficient detail the set of data to be accessed, the methods of analyzing them, and the time needed for the research;

c) a contract specifying the conditions for access, the obligations of the researchers, the measures for respecting the confidentiality of statistical data and the sanctions in case of breach of these obligations has been signed by the individual researcher, by his/her institution, or by the organization commissioning the research, as the case may be, and by ELSTAT.

Users can request access to microdata by submitting an application to the Hellenic Statistical Authority, Statistical Information and Publications Division, 46, Pireos & Eponiton Str, P.O.Box 80847, GR-18510, Piraeus (tel (30)213-1352022, FAX: (30)213-1352312, e-mail: data.dissem@statistics.gr.

Yes

There is a press release calendar, planned during the previous calendar year, that also concerns data releases (https://www.statistics.gr/en/calendar#62022).

Changes that may occur, regarding either delays or ad-hoc press releases are communicated through ELSTAT webpage ( https://www.statistics.gr/en/news-announcements)

ELSTAT publishes sets of tables containing aggregated data, usually at the level of NUTS3, at its official webpage along with the respective metadata (https://www.statistics.gr/en/statistics/agr). Both data and metadata are accessible by anyone and free of charge.

For IFS data, the variables included represent the main crop/livestock/labour force categories and classifications.

The methodology is described in the Integrated Farm Statistics Manual, 2020 edition

Every three years for sample survey data and every 10 years for census survey data.

See sub-categories below.

https://www.statistics.gr/en/news-announcements

See sub-categories below.

• Greece in figures, ELSTAT, Quarterly publication since 2015, link: https://www.statistics.gr/en/greece-in-figures
• Farm Structure Survey, ELSTAT, 2013, link: Press Release FARM STRUCTURE SURVEY, YEAR 2013
• Farm Structure Survey, ELSTAT, 2016, link: PRESS RELEASE FARM STRUCTURE SURVEY, 2016

See sub-categories below.

2661 consultations in 2021, including consultations of metadata

https://www.statistics.gr/en/statistics/agr

See sub-category below.

Not available

Not requested.

See sub-categories below.

Not requested.

• Single Integrated Metadata Structure (SIMS v2.0) Farm Structure Survey 2007, ELSTAT 
• Single Integrated Metadata Structure (SIMS v2.0) Agricultural and Livestock Census 2009, ELSTAT 
• Single Integrated Metadata Structure (SIMS v2.0) Farm Survey Structure 2013, ELSTAT 
• Single Integrated Metadata Structure (SIMS v2.0) Farm Survey Structure 2016, ELSTAT 

Not applicable

Not applicable

The following quality reports are also made available:

• Summary quality report for users, Farm Structure Survey, Year 2016
• User oriented quality report, Farm Structure Survey, Years 2003, 2005, 2007, 2013,
• User oriented quality report, Agricultural Census, Year 2009
• Metadata in Euro-SDMX format (ESMS), Farm Survey Structure, 2003, 2005, 2007
• Metadata in Euro-SDMX format (ESMS), Agricultural and Livestock Census, 2009
• Single Integrated Metadata Structure (SIMS), Agricultural and Livestock Census, 2009
• Single Integrated Metadata Structure (SIMS), Farm Structure Survey, Years 2007, 2013, 2016

The NMR is not made directly available to the public through the ELSTAT web page (the SIMS and Euro-SDMX reports are provided instead).

However, the NMR, after validation, could also be made available after submitting an application to: http://www.statistics.gr/en/provision-of-statistical-data

See sub-categories below.

ELSTAT aims at ensuring and continuously improving the quality of the produced statistics and maintaining users’ confidence in these statistics. These goals are achieved, as described in the Quality Policy of ELSTAT, through the following principles:

• Safeguard and substantiate the operational independence of ELSTAT
• Produce timely and relevant statistics using scientifically sound methods
• Establish and maintain users’ confidence in the reliability of the statistics
• Safeguard the confidence of the statistical units who provide their confidential information for the production of the statistics

These quality objectives are achieved by incorporating the guidelines listed above in all the stages of collection, production and dissemination of the statistics.

The Census data collection was done by electronic self-census of the owner or manager of the agricultural holding, or by personal interview and registration of the data by the Enumerator, when the self-census was not possible, by taking all the necessary public health protection measures.

The Enumerators before undertaking the collection of the Census data attended a relevant seminar by the Census Supervisors for the correct completion of the questionnaire. A Work Team, consisting of competent employees of ELSTAT and the Heads of its two General Directorates, coordinated the work of organising, conducting, processing data, exporting and disseminating the results of the Census, providing relevant instructions and guidelines on various issues concerning the procedures and the output, including on quality issues.

Improvement measures are taken, where appropriate, on the basis of the evaluation of the statistical results of a survey, which takes place after its completion.

The quality assessment procedures include:

• Evaluation of the statistical procedures and output of every statistical survey/work, on the basis of CoP principles and best practices in the European Statistical System;
• Participation in the Peer Reviews, which are periodically conducted throughout the European Statistical System;
• Evaluation of the implementation of CoP principles 1 - 6 in the ELSS by the Good Practice Advisory Committee, which is an independent advisory committee, whose members are selected from among experts with exceptional skills and national and/or international experience in matters relating to the CoP.

The main users of IFS data are:

• Private consulting companies that require the full array of IFS variables to identify sectors and regions eligible for funding under the various development initiatives.
• Ministry of Rural Development and Food and Ministry of Environment and Climate Change, requires various IFS data for policy planning and assessment reasons

There are no characteristics that are surveyed only for national purposes.

All user needs are met

Not applicable

Users' Satisfaction Survey, conducted using an online questionnaire.

2019 (the survey is running since 2011-2012)

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

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

See categories below.

See sub-categories below.

Please find the relative standard errors for the main variables in the annex.

In the extended sampling frame, the information used for stratification was not entirely accurate and as a result, the variances and sampling errors of the obtained estimations were larger than those expected from accurate stratification information. So, the benefits of precision due to stratification have been reduced.

In addition, the sampling frame included sample units that do not belong to the target population, such as units that no longer exist or units that are not within the survey scope.

The main consequence of ineligible units included in the sampling frame is that the actual sample size gets diminished as those units are discarded. So the estimation efficiency is reduced.

See annex 

See sub-categories below.

See sub-categories below.

The over-coverage rate is available in the annex. The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat. 

Not available

Not requested.

See sub-categories below.

There is no information in order to access the under coverage rate 

Updating the Farm Register of ELSTAT by administrative sources and agricultural and livestock surveys minimizes the under-coverage error.  

Not available

Misclassification errors create inaccurate stratification information of holdings and this reduces the benefits of stratification sampling and increases the relative standard errors of the estimates. 

Updating the Farm Register of ELSTAT by administrative sources and agricultural and livestock surveys minimizes the misclassification error.

There were cases that holdings were not possible to conduct them due to inaccurate address information from the Farm Register.

In these cases the initial sample was reduced and  additionally their eligibility status was unknown.

In the data process the eligibility status of the these “unknown” units was estimated by using information of the rest units in the same stratum.

The above contact errors increase the sampling errors and may create bias because it is not possible to conduct these “problematic” units.

Updating the Farm Register of ELSTAT by administrative sources and agricultural and livestock surveys minimizes the contact error.

See sub-categories below.

The interview was conducted with the owner or the manager of the holding. However, if the owner or the manager was found temporarily absent then the required information could be retrieved by interviewing another member of the holder’s family or from an employee with knowledge (e.g. foreman) of the holding.

The most common problematic questions/characteristics identified during the quality control of the data were the following:

• Location of the holding
• Kitchen gardens vs outdoor fresh vegetables,
• Permanent grassland vs common land, in some cases difficult to discern,
• Manure export/import
• Manure application techniques
• Manure storage

The estimation of the extra variability due to measurement errors can be done by comparing primary data of the survey with primary data of other source of statistical information, for the same reference period. 

See sub-categories below.

The unit non-response rate is in the annex of item 13.3.1.1. The unit non-response rate is unweighted.
The unit non-response rate is calculated as the share of eligible non-respondent holdings to the eligible holdings.  The eligible holdings include those holdings with unknown eligibility status which are imputed or re-weighted for (therefore considered eligible).
The unit non-response rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.

From the data of the frame extension, it was observed that the non-respondent sampling units are in their majority very small agricultural holdings. The weighted average of utilized agricultural area is 0.53 hectares

Item non response does not exist because item non-response controls were incorporated in the web questionnaire demanding complete sets of answers.

Not applicable

By applying sampling weighting adjustment, the bias due to non-response has been reduced.  However this extra weighting increases the variance and thus the sampling errors.  

See sub-categories below.

In order to minimise processing errors, data collection and processing were automated to the extent possible. Specifically, a CAI approach was adopted, using a web questionnaire incorporating as many logical and quality controls, as possible. Correction of the remaining processing errors, was attempted by imputation.

Corrections can only be made by authorized staff of ELSTAT.

Not available

Not available

See sub-categories below.

Not applicable.

The final results will be published in the second half of 2022. The time lag will be around 20 months compared to the end of the reference year.

See sub-categories below.

See sub-categories below.

Not requested.

For the publication time of the main national data tables and corresponding metadata, please see the annex of item 18.

See sub-categories below.

Not applicable, because there are no mirror flows in Integrated Farm Statistics.

See sub-categories below.

No

Not applicable

See sub-categories below.

It is calculated and verified that the EU coverage requirements are met. Numeric proof is provided in the table below:

Both national and data sent to Eurostat are collected using the same thresholds

Not applicable

See sub-categories below.

There is a difference in the way equidae are handled. Whereas in Regulation (EU) 2018/1091 equidae are under Other animals n.e.c., in Greece we retained the representation adopted till 2016, two, additional, separate categories for Horses - mules, and Donkeys. Nevertheless, equidae are reported to Eurostat under Other animals n.e.c..

The information is available in the annex. 
The number of working hours and days in a year for a full-time job correspond to one annual working unit (AWU) in the country. One annual work unit corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis. Annual working units are used to calculate the farm work on the agricultural holdings.

The information is available in the annex of item 15.1.4.1.1. 

The information is available in the annex of item 15.1.4.1.1. 

The LSU coefficients used, are those set in Regulation (EU) 2018/1091.

Whereas in Regulation (EU) 2018/1091 equidae are under Other animals n.e.c., in the Greek questionnaire there are two, additional, separate categories for Horses - mules, and Donkeys. Nevertheless, equidae are reported to Eurostat, according to the Regulation, under Other animals n.e.c..

Greece deviates from Regulation (EU) 2018/1091, as far as the collection and publication of data on equidae are concerned, for reasons of comparability with previous surveys and because horses, mules and donkeys are considered traditional animals for Greek agriculture. 

See sub-categories below.

No

Not applicable

Not applicable

Common lands were recorded as common land units, meaning virtual entities, one for each NUTS3 region, created for the purposes of data collection and recording, consisting of the utilised agricultural area used by agricultural holdings of that region, but not belonging directly to them.

The common land data were obtained from the Payment and Control Agency for Guidance and Guarantee Community Aid (OPEKEPE) which, in turn, has collected the data from the applicants for the Community Aid (farm holders), under its competence as the Integrated Administration and Control System (IACS) operator.

Common land is reported as assigned to 52 special/virtual 'common land agricultural holdings' which represent the 52 NUTS 3 regions of the country. Two NUTS3 regions don’t have any common land, so 50 units were submitted.

Special units were recorded in the dataset, and considered as agricultural holdings with activity 'providing grassland for feeding livestock' (NACE 68.20).

Not applicable

See sub-categories below.

No

Not applicable

Not applicable

See sub-categories below.

Siince 1999, so the lenght of comparable time series is seven (7).

See sub-categories below.

Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However even if our country raises fur animals, holdings with only fur animals are not included in our data collection because they do not meet the thresholds. The thresholds for animals are expressed in livestock units (LSU) and fur animals are not associated LSU coefficients. We did not add thresholds related to fur animals; there is no reason for it (fur animals do not contribute towards 98% of the total LSU).

See sub-categories below.

The threshold for “Greenhouses, regardless of the production type, ownership or the location of the holding” was revised from 0.05 ha to 0.01 ha, in conformance to Regulation (EU) 2018/1091.

See sub-categories below.

Not applicable

See sub-categories below.

Legal personality of the agricultural holding

In IFS, there is a new class (“shared ownership”) for the legal personality of the holding compared to FSS 2016, which trigger fluctuations of holdings in the classes of sole holder holdings and group holdings. Nevertheless, common holdings are rather uncommon in Greece, so this change is not expected to have an effect on data comparability.

Other livestock n.e.c.

In FSS 2016, deer were included in this class, but in IFS they are classified separately.

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

Deer breeding, is very rare in Greece, so the respective change will not affect the data series.

Equidae, even though still handled, in the questionnaire, as they were in 2016, they are reported according to Regulation (EU) 2018/1091. This could induce a break in the time series, however, despite the fact that equidae are significant from a tradition point of view, their numbers are not significant enough to cause a break.

Livestock units

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

Poultry, other than chicken, are not very common in Greece. The change of the respective LSU coefficients is not expected to have an impact on the time series.

Organic animals

While in FSS only fully compliant (certified converted) animals were included, in IFS both animals under conversion and fully converted are to be included.

This change is capable of introducing a break in the organic livestock time series. Nevertheless, the respective change in animals’ heads is not large enough to warrant a break in the time series.

See sub-categories below.

The reference period for the manure management variables changed between 2016 and 2020. In 2020 it was the 12-month reference period ending on 01/11/2020. For 2016, the reference period for “other characteristics” was the period from 1^st October 2015 until 30 September 2016.

See sub-categories below.

Not applicable

the comparison of 2020 figures versus 2016, revealed some interesting trends, here pointed out:

Livestock data

Male bovine animals 2 years old or older; Increase of livestock due to increased subsidies, reduced possibility of loses to wild animals and increased demand for bovine meat. Also, intense interest in buffalo meat and buffalo related meat and dairy products

Heifers & dairy cows: the existing negative trend has been accelerated due to low priced imports from neighbouring countries 

Rabbits: Financial difficulty faced by small holdings. Mainly traced to the cost of fodder that accounts for about 70% of the total production cost and is imported thus having a high price. This is combined with a low market penetration of the product, possibly due to the lack of marketing (rabbit meat is usually sold as is, scarcely ever undergoing processing), and large imports, mostly from Italy, at very competitive prices.

Crops data

common wheat and spelt outdoor / durum wheat / rye and winter cereal mixtures/ oats and spring cereal mixtures / rice outdoor: Increased cultivation costs (e.g. compared to forage plants) yielding low prof its and rather labour intensive. Non subsidised.

seeds and seedlings: the sharp increase from 2016 is due in anticipation of the restoration of fresh vegetables' cultivation to its pre-COVID levels. 

nuts outdoor: increased thanks to low production costs and high produce price

leguminous plants harvested green ( increased from 2016) / green maize (decreased from 2016): special subsidy regime for forage plants

Tobacco outdoor recorded a sharp decline from 2016, on te contrary Aromatic medicinal and culinary plants increased their area: this was due to moving towards alternative cultivation such aromatic plants ( e.g. lavender) for which there are subsidisation support schemes in pace.

Permanent agricultural grassland not in use - outdoor - eligible for financial support:  The increase is mainly due to the reduction of arable land due to the change of the definition for "Pastures and meadow s not used for productive purposes, eligible for subsidies".

Nurseries - outdoor: Reduction resulting from the reduction of the respective productive cultivation (wines, orchards etc) due to high production costs and low produce prices.

Flowers and ornamental plants: increased demand for small ornamental shrubs mainly for export.

Unutilised agricultural area: Such areas are gradually removed from the Registry as their owners become inactive and their successors cannot be traced.

permanent crops - under glass: sharp increase from 2016 due to introduction of new high-valued tropical species/fruits following a south-European wide trend.

See sub-categories below.

Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.

Not applicable, because Integrated Farm Statistics have no relevance for national accounts.

See sub-categories below.

IFS 2020 microdata were compared to relevant agricultural surveys, as well as to corresponding IACS data whenever a full match could be secured between an IFS and an IACS holding, on the basis of the holder’s personal data. The results indicated differences in several cases, triggering corrective actions.

See sub-categories below.

In order to understand the reasons behind the differences between IFS and the Annual Crop Survey (ACS), the following general remarks need to be considered:
Annual crops statistics (ACS) is conducted by the Ministry of Rural Development and Food (MRDF) according to Regulation (EC) 543/2009. The methodology described in the Regulation differs from that of IFS. Examples of methodological
differences include:
a. ACS data are not collected through a survey, but are obtained primarily from the regional Directorates of Agricultural Economy and Veterinary, of the country and are based on experts’ opinions. This raises the issue of accuracy/subjectivity of the estimations and according to the relevant metadata, there has not been a peer-review carried out for ACS.
b. In ACS, utilised agricultural area (UAA) is counted more than once in the case of successive crops, leading to higher values of the related variables being reported by the ACS compared to the IFS.
c. There are differences between the definitions for some of the examined variables, according to the EC regulations relevant for the ACS and the IFS.
d. Regarding animal related variables, ACS and IFS use different reference dates.
e. Data validation and cross-checking with external sources, namely ELSTAT-FSS/IFS and Payment and Cont rol Agency for Guidance and Guarantee Community Aid (OPEKEPE)-IACS, is reported by the MRDF however the relevant procedures are not documented and the results are not provided in the metadata.

The data are internally consistent. This is ensured by the application of a wide range of validation rules.

See sub-categories below.

There was co-ordination with the Livestock Surveys of year 2020.

Reduced burden to both the respondents and the ELSTAT, as a result of adopting the CAI methodology. Significant efficiency gains for data verification and validation with direct, positive consequences on data quality.

See sub-categories below.

12

5

2

8

The revision policy of the Hellenic Statistical Authority (ELSTAT) defines standard rules and principles for data revisions, in accordance with the European Statistics Code of Practice and the principles for a common revision policy for European Statistics contained in the Annex of the European Statistical System (ESS) guidelines on revision policy. For more details: ELSTAT Revision Policy

No data revisions. 

Not requested.

See sub-categories below.

See sub-categories below.

Agricultural Register of ELSTAT

See sub-categories below.

Not applicable for 2019/2020.

Not applicable for 2019/2020.

Not applicable for 2019/2020.

See sub-categories below.

The sampling method used is the one stage stratified sampling with survey units the agricultural and live-stock holdings of Farm Register of ELSTAT. Apart from size and location, the farm’s typology (according to Regulation (EC) 1242/2008) was used as stratification criteria.  

Take-all strata are the strata with large scale holdings that present high population variance for the main variables. The boundaries of the size classes were determined by applying the Rule of Cumulative Root.

The sample size was determined so that the relative standard errors of the estimates of the main variables would not exceed 5% at the whole Country.

See sub-categories below.

Not applicable

Not applicable

Not applicable

See sub-categories below.

Not applicable

Not applicable

Not applicable

See sub-categories below.

Not applicable

Not applicable

Not applicable

SPSS

See sub-categories below.

The information is available on Eurostat's website.

See the attached Excel file in the Annex.

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

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

See sub-categories below.

For transcribed versions of the web questionnaire in Greek and English, see the pdf files in the Annexes.

See sub-categories below.

Custom Oracle SQL based applications, developed in house, and Microsoft Excel

See details on the methods used to derive the extrapolation factors (18.5.2) in the Annex

For the sampling survey on frame extension, only item-imputation was implemented on 63 holdings for the core variables from the corresponding administrative data of IACS. The item imputation rate is 63/7194=0.87%

Covered under Data compilation.

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

See sub-categories below.

ACS - Anual crops statistics

CAP – Common Agricultural Policy

CAI - Computer assisted instruction

CAPI –  Computer Assisted Personal Interview

CATI – Computer Assisted Telephone Interview

CAWI – Computer Assisted Web Interview

ELSTAT - Hellenic Statistical Authority

ESS - European Statistical System

FSS – Farm Structure Survey

IACS – Integrated Administration and Control System

IFS – Integrated Farm Statistics

LSU – Livestock units

MRDF - Ministry of Rural Development and Food

NACE – Nomenclature of Economic Activities

NMR - National Methodological Report

NUTS – Nomenclature of territorial units for statistics

PAPI – Paper and Pencil Interview

SO – Standard output

UAA – Utilised agricultural area

No additional comments.