Statistics Austria

Directorate Spatial Statistics

Agriculture and Forestry, VIS 

Statistics Austria

Directorate Spatial Statistics

Guglgasse 13

1110 Vienna

Austria 

The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.

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

The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 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 many classifications. Please find below information on most classifications.

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

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 manure management":  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 subset of the population of agricultural holdings defined in item 3.6.2 with at least one of the following: bovine animals, pigs, sheep, goats, poultry.

See sub-categories below.

The entire territory of the country.

Not applicable

Not available

Farm structure statistics in our country cover the period from 1970 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, you can consult the definition of the standard output.

Two kinds of units are generally used:

• the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
• the number of agricultural holdings having these characteristics.

See sub-categories below.

The use of land refers to the 12-month period ending on 31 December within the reference year 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 31 December within the reference year 2020.

The reference day 1 April within the reference year 2020.

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

The 12-month period ending on 31 December within the reference year 2020.

The three-year period ending on 31 December 2020.

The reference day 1 March within the reference year 2020.

See sub-categories below.

National IFS-Regulation 2020: 279. Verordnung der Bundesministerin für Nachhaltigkeit und Tourismus betreffend die Statistik über die Struktur der landwirtschaftlichen Betriebe im Jahr 2020 (Agrarstrukturstatistik-Verordnung 2020)

Federal Statistics Act 2000: Bundesgesetz über die Bundesstatistik (Bundesstatistikgesetz 2000)

National IFS-Regulation 2020:  (BGBl. II No 279/2019)

Federal Statistics Act 2000: BGBl. I No 163/1999, as last amended by BGBl. I Nr. 136/2001, BGBl. I Nr. 71/2003,  BGBl. I Nr. 92/2007,  BGBl. I Nr. 125/2009, BGBl. I Nr. 111/2010, BGBl. I Nr. 40/2014, BGBl. I Nr. 30/2018, BGBl. I Nr. 32/2018 and BGBl. I Nr. 205/2021.

National IFS-Regulation 2020:  2019

Federal Statistics Act 2000:  2000

Under the Federal Statistics Act 2000 (BGBl. I No 163/1999, as last amended by BGBl. I Nr. 136/2001, BGBl. I Nr. 71/2003,  BGBl. I Nr. 92/2007,  BGBl. I Nr. 125/2009, BGBl. I Nr. 111/2010, BGBl. I Nr. 40/2014, BGBl. I Nr. 30/2018, BGBl. I Nr. 32/2018 and BGBl. I Nr. 205/2021), Statistics Austria is required to use the available administrative data instead of information obtained using its own questionnaires, so as to minimise the respondents' workload.

On the other hand there is an obligation on the holders of administrative data to cooperate. According to Regulation BGBl. II No 279/2019 § 10.
(1) Area characteristics pursuant to § 4 par. 2 fig. 3, which are recorded within the scope of the multiple application area, shall be transferred directly to the electronic questionnaire.
(2) Pursuant to § 4 par. 2 fig. 2 to 8, the holders of administrative data shall, at the request of the Federal Agency, transmit the data to the Federal Agency electronically free of charge within four weeks.

National level: The legal base for statistical confidentiality is:

• The general obligation to publish statistics and the strict fulfilment of statistical confidentiality is regulated by the “Federal Statistics Act 2000” ("Bundesstatistikgesetz 2000") in the current version. It contains provisions governing data protection. The surveyed data are subject of confidentiality (§ 17 Federal Statistics Act – Statistical Confidentiality) and will be treated in the strictest confidence; a forwarding of data to third parties is permitted only under the legal bases mentioned conditions (e.g. the transmission of data to the LFBIS: see above- administrative and financial provisions).  

• The protection of personal data is covered by the “Data Protection Act 2000” ("Datenschutzgesetz 2000", in the current version).

See also http://www.statistik.at/web_en/about_us/responsibilities_and_principles/confidentiality/index.html

EU level:  Regulation (EC) No 2223/2009 on European statistics.

In the dissemination of the IFS 2020 data, the deepest regional breakdown is the LAU 2 - level.

See sub-categories below.

See sub-categories below.

In the dissemination of the IFS 2020 data, the deepest regional breakdown is the LAU 2 - level. In the database, there is a restriction of the combination of variables in more detailed spatial levels.

See sub-categories below.

Not applicable

There is a publication calendar for all statistical areas; an individual publication calendar for the Integrated Agricultural Statistics does not exist.

A release calendar as well as a press calendar is on the homepage of Statistics Austria at http://www.statistik.at/web_en/about_us/calendar/index.html  

• No prior access before official data release.
• The "Federal Statistics Act 2000" ("Bundesstatistikgesetz 2000" in the current version) explicitly states in §30 (3) the obligation of Statistics Austria to inform without delay the Federal Ministry responsible for the subject matter concerned about the results of statistical surveys and to publish them simultaneously.
• The data are transmitted to Eurostat according to the release calendar of Eurostat.

Not applicable

every 3-4 years

See sub-categories below.

General: www.statistik.at/web_de/presse/index.html

Press release preliminary information  
The most important data were available in the form of a press release containing preliminary national information on September 22, 2021. The press release was made available on the Internet at www.statistik.at, www.statistik.at/web_de/presse/index.html. 

Press release final data 
Final data were available in the form of a press release containing final national information in May 2022. The press release was made available on the Internet at www.statistik.at/web_de/presse/index.html.

See sub-categories below.

FSS (Agrarstrukturerhebung) 2010, Statistics Austria, 05/2013:  http://www.statistik.at/wcm/idc/idcplg?IdcService=GET_NATIVE_FILE&RevisionSelectionMethod=LatestReleased&dDocName=071011

FSS (Agrarstrukturerhebung) 2016, Statistics Austria, 02/2018:  http://www.statistik.at/wcm/idc/idcplg?IdcService=GET_NATIVE_FILE&RevisionSelectionMethod=LatestReleased&dDocName=116146

The reports concerning the IFS 2020 are not yet available and will be provided under: http://www.statistik.at/web_de/services/publikationen/8/index.html  

Statistical Yearbook of Austria: Various Statistics Austria publications contain contributions setting out the results of the IFS/FSS.

See sub-categories below.

STATcube is available online at www.statcube.com.  

A subscription provides access to more detailed data and additional features not available with the free guest access. This Guest access can be used to assess whether the purchase of a subscription is worthwhile. The database includes features which can only be fully accessed by subscribers (labelled with the tag [partly ABO]) and other features only accessible to subscribers (labelled with the tag [ABO]). Please note: the abbreviation "ABO" stands for the German translation of the term "subscription".

See sub-category below.

Not available

Not requested.

See sub-categories below.

Not requested.

Standard documentation; meta-information      
(Definitions, explanatory notes, methods, quality)           
Concepts, definitions and explanations relating to the information on the IFS 2020, plus notes on the methods used and on quality, will be available September 2022 free of charge, in a standardised form, at http://www.statistik.at/web_de/dokumentationen/Land-undForstwirtschaft/index.html. 

Not applicable

not applicable

See 10.6 Documentation on methodology

See sub-categories below.

Statistics Austria has its own internal quality management department.

Reports are not only based on best practices, but also on the results of regular (quality) meetings amongst decision-making bodies and users.

A commitment to quality of Statistics Austria is available under http://www.statistik.at/web_en/about_us/responsibilities_and_principles/commitment_to_quality/index.html

Not available.

Not available.

National institutions:

• Federal Chancellery (BKA)
• Federal Ministry of Agriculture, Forestry, Environment and Water (BMLFUW)
• Political Institutions (National Assembly, Federal Assembly, etc.)
• Austrian Chamber of Agriculture (LKÖ), Chambers of Agriculture on regional level
• Regional authorities (Provincial Government, municipalities)
• Statistics Austria (Output statistics and subsequently supply balance sheets; Economic Accounts for Agriculture (EAA) and subsequently National Accounts (NA); Environment and energy statistics)
• Austrian Institute of Economic Research (WIFO)
• Federal Institute of Agricultural Economics (AWI)
• Federal Institute for Less Favoured and Mountainous Areas (BABF)
• Agency for Health and Food Safety (AGES)
• Environment Agency Austria (UBA)

International institutions:

• European Commission (ESTAT, DG AGRI, DG CLIMA, JRC)
• Farm Accountancy Data Network (FADN)
• UNO (Food and Agriculture Organization of the United Nations (FAO))

Non-institutional users:

• Media
• Educational institutions (Agricultural colleges, universities)
• Research institutions (universities)
• Enterprises
• Non-Profit-Organisations
• General public

There is no monitoring of the requested topics (main groups of variables) according to the different data users and purposes.

In order to satisfy both national needs and various directives, the survey of the individual variables was more detailed for certain groups. Those variables were aggregated prior to transmission to Eurostat in line with the rules for the provision of IFS data (see Annex 12.1.1_national-variables_IFS2020AT). 

So far, all known and reasonable user needs are met. It has to be stated that this question is also a matter of cost/benefit consideration. 

Not applicable; User needs already can be brought forward in the course of the respective preparation of the legal basis. The most important data-users are heard in this process.

There are no dedicated procedures to measure user satisfaction in IFS.

not applicable

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.

The IFS2020 was carried out as a census. The relative standard errors are zero. There was no non-response adjustment and calibration. Please find the relative standard errors for the main variables in the annex.

There are no cases where estimated RSEs are above thresholds.

However, for the purpose of the IFS2020 we did not calculate the relative standard error. In our case is not applicable.

The Method used for estimation of relative standard errors would be the Horvitz-Thompson Estimator for stratified sampling:

Point estimates: The total of variable X is estimated as being the value of (a quantitative) variable X for holding j in province b and stratum h, n_bh the realised sample size and the number of holdings in the population.

Variance: The variance  of the point estimate   is given by  

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 virtually no under-coverage of agricultural holdings, because newly created holdings usually submit subsidy applications and their administrative data are used for inclusion in the Farm Register (or Agricultural and Forestry Register, AFR). Wrongly classified units can be ruled out due to the routine maintenance of the AFR with checks against various types of administrative data (applications for subsidies, social insurance information etc.).

Undercoverage is minimised via routine maintenance of the AFR with checks against various types of administrative data (applications for subsidies, social insurance information etc.).

New births, new units derived from split or units with outdated information and which became relevant were added to the frame during the survey period.

Not available

Not available

Contact error is minimised via routine maintenance of the AFR with checks against various types of administrative data (applications for subsidies, social insurance information etc.). 

In the case of undeliverable and returned survey documents, the correct addresses were researched and the documents were resent.

See sub-categories below.

There were no variables with high measurement errors.

Occasionally respondents transferred area data, which was not prefilled by administrative sources from their land register without considering diverging units of area.  E.g.: Other farmland (FA_OTH), Unutilised agricultural area (NUAA), Wooded areas (WA), Short rotation coppice areas (SRCAA), Other areas on the farms (FA9).

Measurement errors are minimised by offering appropriate information in the questionnaire to use the correct units of measurement. Errors that nevertheless occurred were discovered in the course of plausibility checks (e.g. checking the data against previous surveys). Impact of measurement errors on data quality can be assumed to be extremely low. 

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.

In the end (after urgency and administrative penalty proceedings), 341 units remained with their refusal to provide information. Their data could be imputed by using administrative or other data-sources (Internet etc.). As this number is very low and fairly equally distributed, no further analysis was made.

Item non-response rates were not calculated. Item non-response can virtually be excluded for the main variables, if not for most variables due to the measures mentioned above (electronic questionnaire with plausibility checks). Occasional imputations by enumerators cannot be quantified. In the hindsight it is difficult to quantify item non-response with regard to the costs and response-burden. 

In general it is obvious that the risk of non-response tends to be higher in the context of variables,

• which might be considered to be more confidential by the respondents or
• which can obviously and hardly be cross-checked.

Examples for variables with potential item non-response :

• Other farmland (FA_OTH)
• Unutilised agricultural area (NUAA)
• Wooded areas (WA)
• Other areas on the farms (FA9)
• Other gainful activities related to provision of health, social or educational services (OGA_HSES)
• Other gainful activities related to handicraft (OGA_HC)
• Other gainful activities related to processing of farm products (OGA_FPRDPRC)
• Other gainful activities related to production of renewable energy (OGA_NRGRPRD)
• Other gainful activities related to wood processing (OGA_WPRC)
• Other gainful activities related to agricultural contractual work (using production means of the holding) (OGA_ACW)
• Other gainful activities related to non-agricultural contractual work (using production means of the holding) (OGA_NACW)
• Other gainful activities related to forestry (OGA_FOR)
• Other gainful activities directly related to the agricultural holding n.e.c. (OGA_AGRHLD)
• Family members of holder-manager of the sole holder holding, who are working on the agricultural holding and have other gainful activities (not related to the agricultural holding) as their main activity (MOGA_FAM_NRH)
• Family members of holder-manager of the sole holder holding, who are working on the agricultural holding and have other gainful activities (not related to the agricultural holding) as their secondary activity (SOGA_FAM_NRH)

Item non-response is minimised by the electronic questionnaire, which was designed in such a way that it could only be sent once the compulsory fields had been correctly completed. To prevent individual pages of the questionnaire being inadvertently missed out, a marker was placed on each page of the internet questionnaire which had to be set to signify that the page had been completed. There were also cross-checks between dependent items in the questionnaire (e.g. livestock - manure). This range of well-targeted measures made it possible to reduce the item non-response rate. In the paper-based questionnaires in previous surveys, variables frequently came back uncompleted.       

In addition, various tests and monitoring measures were carried out during the plausibility checks. Missing data could be imputed after contacting the respondents again or by using other data-sources (internet etc.).

See sub-categories below.

Not available.

The data sets were checked for missing, incorrect or implausible information, using an extensive plausibility application. The corrections were made by the members of Statistics Austria's project team, who were specially trained and authorised to process and rectify the data sets.

Missing or incorrect entries were completed from other data sources wherever available (e.g. administrative data from IACS or ÖPUL, information on areas or „safety-plan-measures“from the social insurance for farmers) to avoid burdening the respondents. The forestry yearbook, containing the areas of Austria’s largest forestry holdings, was another means of checking data. If these sources were not exhaustive, individual items from the 2010, 2013 or 2016 FSS were used, wherever possible, to check and/or supplement the data. Where this did not provide clarity, individual holdings had to be contacted by telephone.

Moreover, the nil returns were examined. If, for example, administrative information on the holding was available, the nil return was rejected and the holding was surveyed again. This was done in close collaboration with staff dealing with the Farm Register (or Agricultural and Forestry Register, AFR), as the information from the nil returns (business closure, leasing etc.) were used for updating the registers.

Not applicable

See sub-categories below.

9 months; last day of the reference period: 31 December 2020; day of publication of first results: 22 September 2021. 

17 Months; last day of the reference period: 31 December 2020; day of publication of final results: May 2022. 

See sub-categories below.

See sub-categories below.

Not requested.

The planned national publication is scheduled for several steps or partial reports in the period May and June 2022. At the time no delay can be given in the course of the National Reference Metadata in Single Integrated Metadata Structure (SIMS).

See sub-categories below.

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

See sub-categories below.

Concerning the data-subset relevant for Eurostat the definition of the holding is consistent with the definition fixed in Regulation (EU) 2018/1091.  According to the national regulation, statistical units include forestry holdings with at least three hectares of wooded area. These holdings, which only are relevant due to their wooded areas, are included in the national results but not in the dataset delivered to Eurostat.

The holdings, which only are relevant due to their wooded areas and which do not necessarily meet the thresholds fixed in Regulation (EU) 2018/1091 are nevertheless collected and included in the national results for national reasons. 

See sub-categories below.

 As can be seen in the annex 3.6.1 Thresholds of agricultural holdings the thresholds of agricultural holdings applied are lower than those specified in Regulation (EU) 2018/1091.

UAA surveyed covers 98 % of the total UAA (excluding kitchen gardens) and the Livestock surveyed covers 99 % of the livestock units in Austria:

According to the national regulation, statistical units include forestry holdings with at least three hectares of wooded area. 

National importance of wooded area. 

See sub-categories below.

Definitions used in IFS 2020 are mainly based on the Commission Implementing Regulation (EU) 2018/1874. Furthermore, the guidelines according to the „ Integrated farm statistics manual” are implemented as far as possible. There are following differences: 

• % band Annual work unit (AWU): The number of hours for a „full-time employee“ was set 2000 hours per year (250 working days of eight hours), whereas the EU Regulation provides for only 1800 hours per year (225 working days of eight hours). As these are only guidelines, and as the European requirements are, according to experts, too low for Austria, the national Working Party of the Agricultural Statistics Advisory Committee decided to increase the number of hours as from the 1995 Farm Structure Survey. This deviation has not changed in time series and can mostly be attributed to specific national circumstances. The worktime percentage bands for the regularly employed labour force are calculated by using the working hours reported by the respondents. Apparent excessive amounts regarding the labour input (e.g. 100 %  in case of retired people or pupils and students) were reduced considering interacting factors.
• F3000T  Berries (excluding strawberries) - outdoor: Starting with the FSS 2016 elderberry (Sambucus nigra L.) was recorded under PECR9_H9000T Other permanent crops including other permanent crops for human consumption – outdoor to ensure a better coherence with crop statistics. Elderberries are used predominantly for industrial purposes.
• Other livestock n.e.c.

For details, see sub-categories below.

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 Livestock coefficients are consistent with those fixed in Regulation (EU) 2018/1091.

“Other livestock n.e.c.” includes rabbits for breeding.

The deviations concerning AWU are justified in the decision of the national Working Party of the Agricultural Statistics Advisory Committee to increase the number of hours. 

Rabbits were reported as NS, are not reported as a separate variable and are therefore subsumed under Other livestock n.e.c..

In general, minor discrepancies can theoretically occur, whenever the definitions between the statistical side and those of the administrative data diverge.

See sub-categories below.

No deviations.

Not applicable

Not applicable

Common land has been included in the FSS as special agricultural holdings (AGRARIAN COMMUNITIES) since 1993. The UAA of the common land is predominantly made up of grassland (99.9996%)

This approach (separate record) met the practice of the subsidy system where, common land units themselves, can apply for subsidies, are therefore part of administrative data and are treated like other farms. 

There were no particular questions and no separate questionnaire for common land units. The administrative data were provided within the questionnaire after transmission from IACS via web service interface.

In contrast to the surveys before the recorded common land units were not kept in the data set as separate individual holdings. Their UAA (non-material shares) was then assigned to the individual farms of the members of the agrarian community. In terms of tenure classification, these allocated areas are recorded as 'common land'.

We do not experience problems to collect data on common land.

See sub-categories below.

There are no deviations.

Not applicable

There are no differences in the methods used across regions within the country.

See sub-categories below.

1

See sub-categories below.

Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However, our country does not raise fur animals.

Common Land is now included in the land of agricultural holdings renting or being allotted the land based on written or oral agreements. Before that, the Common Land Units were counted as “normal” holdings (separate record). This approach met the practice of the subsidy system, where common land units themselves can apply for subsidies and are therefore part of administrative data. Furthermore, they fulfilled at least one condition for an agricultural holding: The maintenance of agricultural land in good agricultural and environmental condition (under 01.61 of NACE Rev. 2).

See sub-categories below.

Due to raised thresholds concerning UAA very small units, which only have permanent grassland and a very limited market relevance, could be excluded.

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. 

Other livestock n.e.c.

In FSS 2016, deer were included in this class, but in IFS, they are classified separately.
Also in FSS 2016, there was a class for the collection of equidae. That has been dropped and equidae are included in IFS in "other livestock n.e.c."

Livestock units

In FSS 2016, turkeys, ducks, geese, ostriches and other poultry were considered each one in a separate class with a coefficient of 0.03 for all the classes except for ostriches (coefficient 0.035). In IFS 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 only fully compliant (certified converted) animals were included, in IFS both animals under conversion and fully converted are to be included.

See sub-categories below.

Reference day/period of "use of land variables": 

FSS2020: 12-month period ending on 31.12. Within the reference year.
FSS2016: 12-month period ending on 30.09. Within the reference year.

Reference period for variables on irrigation and soil management practices:

FSS2020: 12-month period ending on 31.12. Within the reference year.
FSS2016: 12-month period ending on 30.09. Within the reference year.

Reference day for variables on livestock and animal housing: no change

Reference period for variables on manure management: 

FSS2020: 12-month period ending on 31.12. Within the reference year.
FSS2016: 12-month period ending on 30.09. Within the reference year.

Reference period for variables on labour force and other gainful activities:

FSS2020: 12-month period ending on 31.12. Within the reference year.
FSS2016: 12-month period ending on 31.10. Within the reference year.

Reference period for variables on rural development measures: no change

Reference day for all other variables:

FSS2020: 1.3. within the reference year.
FSS2016: 31.10. within the reference year.

See sub-categories below.

In contrast to the surveys before the recorded common land units were not kept in the data set as separate individual holdings. Their UAA (non-material shares) was assigned to the individual farms of the members of the agrarian community. In terms of tenure classification these allocated areas are recorded as 'common land'.

The common land as individual units are therefore not included in the dataset. 

Evolution over time of holdings by classes of SO EUR 

Holdings breakdown by SO EUR shows that lower classes sharply decreased their share in 2020 versus 2016: the least productive holdings have been marked out by raising the threshold
for UAA, especially for greenland. See National Reference Metadata in Single Integrated Metadata Structure (SIMS) 15.2.3.2. Description of changes.

Evolution over time of Farm type classes weights 

A decrease of 16-General field cropping, partly caused by an increase of 15 Specialist cereals, oilseeds and protein crops and the fact, that the common land units were attributed to the related holdings and do not exist as own units anymore. If we remember correctly, the common land units, which do not have own LSU, were classified by Eurostat as 16-General field cropping in the past. Other effects are caused by higher thresholds of arable land (1 ha to 1.5 ha) and lower thresholds for vineyards (0,25 ha to 0,1 ha) which resulted in an increased share of 35-Specialist vineyards.

The decrease of 46- Specialist cattle — rearing and fattening could be partly caused by a shift towards 45-Specialist dairying. The decrease of 48- Sheep, goats and other grazing livestock is caused by altered (higher) thresholds on livestock (heads > 1,7 LSU) and a higher threshold on UAA and greenland (which resulted in a decrease of very small farms with this kind of livestock. The increase of 84-Various crops and livestock combined must be affected by units having Orchards and bees.

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.

Since the same data sources are in use, a deeper analysis does not make much sense. On the other hand, it is evident, that discrepancies can be caused by different reference days (livestock).

See sub-categories below.

IFS and ACS have some differences. 

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

See sub-categories below.

Double burden of very few farms occurred in the context of IFS and animal surveys. In the trade-off between the use of administrative data with a given reference date (1 April 2020) for all farms in the IFS and a double burden of some farms also chosen for the animal surveys the project team decided to run two separated surveys with an optimised use of administrative data and precisely tailored questionnaires. Another reason not to join the two surveys on the reference date of the animal survey in June or December is that time is rather short to survey all farms of the IFS and process the livestock data for the animal survey in time.   

For the IFS 2020, a web service interface was implemented to transfer IACS data directly into the questionnaire. This data transfer was possible as soon as the IACS data was available and was triggered the moment the IFS electronic questionnaire was opened.

See sub-categories below.

Respondents could voluntarily indicate in the questionnaire how much time it took them to complete it. However, no distinction was made between the individual parts (core/modules) of the questionnaire. The evaluation of this information yields a median of 60 minutes.

Not available

Not relevant, use of administrative data.

Not available

General principles relating to the data revision policy (available in German only) can be found at http://www.statistik.at/web_de/ueber_uns/aufgaben_und_grundsaetze/datenrevisionen/index.html.

In the course of the press release published on 22 September 2021, important preliminary key results made available on the internet were replaced with the publication of the final data. Beyond that, no further data revision is planned so far.

Not requested.

See sub-categories below.

See sub-categories below.

Statistical Farm Register

See sub-categories below.

Not applicable for 2019/2020.

Not applicable for 2019/2020.

Not applicable for 2019/2020.

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

See sub-categories below.

Not applicable

Not applicable

Not applicable

Not applicable

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 and the quality methods applied 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 3-4 years in-between.

See sub-categories below.

Please find the questionnaire in annex.

The Farm Structure Survey was held solely using an electronic questionnaire (e-Quest). The farmers were able to submit their return either directly at their computer (direct respondents, CAWI, 53%), at their competent chamber of agriculture (CAPI, 29%) or during a personal interview by telephone with staff of Statistics Austria (CATI, 18%) using the same electronic questionnaire. 

A dedicated free hotline was set up by Statistics Austria to answer any questions that arose during the survey phase. In addition, queries could be sent by e-mail to Agrarstrukturerhebung@statistik.gv.at.

See sub-categories below.

The data sets were checked for missing, incorrect or implausible information, using an extensive plausibility application. The program was developed in cooperation with the IT Dept. Care was taken to ensure that missing, incorrect and implausible entries were detected by the program and either highlighted or immediately corrected. The functionality of the plausibility program was first checked using fictitious holdings. The correction applications contained a number of deliberate errors in order to check whether the program would recognise and report them.

For the IFS 2020 about 85% of the questionnaires needed further checking due to information errors or "real" errors. This share was higher than in 2016 due to the variables concerning manure management practices. For each holding, all errors and information errors were listed and categorised. The errors detected (incorrect entries, missing or implausible data) had to be investigated and rectified by the processing team. Errors were eliminated and plausibility checks carried out repeatedly directly via the application. The staff themselves could correct logical obvious errors. Missing or incorrect entries were completed from other data sources wherever available (e.g. administrative data from IACS or ÖPUL, VIS, “total area information” from the social insurance for farmers) to avoid burdening the respondents. The forestry yearbook, containing the areas of Austria’s largest forestry holdings, was another means of checking data. If these sources were not exhaustive, individual items from the 2010, 2013 or 2016 Farm Structure Survey were used, wherever possible, to supplement and/or check the data. Where this did not provide clarity, individual holdings had to be contacted by telephone.

The IFS 2020 was conducted as a census. Data collected and administrative data were merged via the unique farm number/identifier.

The imputation-rate could be kept very low by the measures mentioned in 13.3.3.1.2. Actions to minimise or address unit non-response and 13.3.3.2.3. Actions to minimise or address item non-response. The imputation-rate cannot be quantified for single variables.

Covered under Data compilation.

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

See sub-categories below.

AFR – Agricultural Farm Register

AMA – Agrarmarkt Austria

CAP – Common Agricultural Policy

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

SO – Standard output

UAA – Utilised agricultural area

VIS – Veterinary Information System 

No additional comments.