Statistics Lithuania

Agricultural, Environmental and Energy Statistics Division

29 Gedimino Ave.

LT-01500 Vilnius, Lithuania

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 regional data is available at NUTS level 2.

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 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 subset of population of agricultural holdings defined in item 3.6.1 which falls in the main frame i.e. above at least one of the thresholds set in Regulation (EU) 2018/1091.

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.

If during the AC 2020 it was clarified that some farms had no animals of the above mentioned species at the time of the census, these farms were monitored comprehensively anyway and all collected data of these farms for this module were sent to Eurostat.

See sub-categories below.

The entire territory of the country.

Not applicable

Not available

Farm structure statistics in our country cover the period from 2003 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 reference year 2020 or 12-month period ending on 1 June 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  1 June within the reference year 2020.

The reference day is 1 June within the reference year 2020.

The 12-month period ending on 1 June 2020. This period includes the reference day used for livestock and animal housing.

The 12-month period ending on 1 June within the reference year 2020.

The three-year period ending on 31 December 2020.

The reference day 1 June within the reference year 2020.

See sub-categories below.

Law on official statistics

Official Statistics Programme 2020, Part I, which includes the statistical surveys conducted by Statistics Lithuania and other bodies managing official statistics.

Law on official statistics

Official Statistics Programme 2020 (in Lithuanian only)

Law on official statistics - 12 October 1993, as last amended on 29 September 2020.

Official Statistics Programme 2020 - 2020

In Article 5 of the Law on Official Statistics it is stated that in implementing the Official Statistics Programme, the bodies managing official statistics shall have the right to obtain free of charge from the sources of official statistics referred to in Article 10 of this Law required statistical data, including personal data, which cover also special categories of personal data, and data which allow direct or indirect identification, also to combine them with other statistical data.

In Article 10 it is stated that sources of official statistics shall be as follows: 1) statistical data provided by or collected from respondents; 2) administrative data; 3) data of legal or natural persons lawfully obtained by the bodies managing official statistics and accessible to the public and/or data accumulated and managed by legal persons; 4) statistical data of international organisations lawfully obtained by the bodies managing official statistics.

The exchange of statistical data required for the implementation of the Official Statistics Program is also defined in Article 13 of the Law on Official Statistics.

In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees confidentiality of the data submitted by respondents (households, enterprises, institutions, organisations and other statistical units), as defined in the Confidentiality Policy Guidelines of Statistics Lithuania.

See sub-categories below.

See sub-categories below.

If there was any confidential information in aggregated data, special symbols were inserted instead of the exact value. Symbol  "•" was inserted if:

• statistical information was prepared using data obtained from less than of three respondents;
• statistical data from one respondent represent more than 70 per cent of the total volume of statistical indicator;
• aggregated statistical data of two respondents represent more than 85 per cent of the volume of whole statistical indicator.

See sub-categories below.

Statistics Lithuania actually provides access to microdata for scientific purposes.

Confidential statistical data may be provided for use for scientific purposes if scientific institutions ensure the protection of the data in the way that it is not possible to directly identify respondents.

Statistical information is published on the Official Statistics Portal according to the Official Statistics Calendar.

Official Statistics Calendar

Statistical information is prepared and disseminated under the principle of impartiality and objectivity, i.e. in a systematic, reliable and unbiased manner, following professional and ethical standards (the European Statistics Code of Practice), and the policies and practices followed are transparent to users and survey respondents.

All users have equal access to statistical information. All statistical information is published at the same time – at 9 a.m. on the day of publication of statistical information as indicated in the calendar on the Official Statistics Portal. Relevant statistical information is sent automatically to news subscribers.

The President and Prime Minister of the Republic of Lithuania, their advisers, the Ministers of Finance, Economy and Innovation, as well as Social Security and Labour or their authorized persons, as well as, in exceptional cases, external experts and researchers have the right to receive early statistical information. The specified persons are entitled to receive statistical reports on GDP, inflation, employment and unemployment and other particularly relevant statistical reports one day prior to the publication of this statistical information on the Official Statistics Portal. Before exercising the right of early receipt of statistical information, a person shall sign an undertaking not to disseminate the statistical information received before it has been officially published.

Statistical information is published following the Official Statistics Dissemination Policy Guidelines and Statistical Information Dissemination and Communication Rules of Statistics Lithuania approved by Order No DĮ-176 of 2 July 2021 of the Director General of Statistics Lithuania.

The methodology is described in the EU Handbook

Data are disseminated at the national level every 3-4 years.

See sub-categories below.

Preliminary results of the Farm Sructure Survey

See sub-categories below.

Results of the Agricultural Census 2020 (edition 2022), Statistics Lithuania, was published in 2022. 

See sub-categories below.

We do not monitor and record the number of consultations of data tables in the field of farm structure.

https://osp.stat.gov.lt/statistiniu-rodikliu-analize#/ (Agriculture, hunting, forestry and fishing -> Agriculture -> Farming structure and agricultural censuses).
The page of Database of Indicators is for viewing and analyzing statistical information. For more information on the Indicators Database, see the Database of Indicators User Guide.

See sub-category below.

Not available.

Not requested.

See sub-categories below.

Not requested.

Farming structure and agricultural census indicators, Statistics Lithuania, metadata are published at Farming structure and agricultural census indicators.

Not applicable.

Not applicable.

The quality report is delivered to Eurostat.

See sub-categories below.

Quality of statistical information and its production process is ensured by the provisions of the European Statistics Code of Practice and ESS Quality Assurance Framework.

In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. The main trends in activity of Statistics Lithuania aimed at quality management and continuous development in the institution are established in the Quality Policy.

Monitoring of the quality indicators of statistical processes and their results and self-evaluation of statistical survey managers is regularly carried out in order to identify areas which need improvement and to promptly eliminate shortcomings.

More information on assurance of quality of statistical information and its preparation is published in the Quality Management section on the Statistics Lithuania website.

Validation rules will be improved.

The quality of the statistical results meets the requirements of accuracy, timeliness and punctuality, comparability and consistency. 

In 2019, the review of the Agricultural Census 2020 statistical forms was carried out, recommendations received have been implemented.

Quality of the obtained statistics is analysed during the evaluation of the indicators. Outstanding values of indicators are identified and analysed. In case of significant deviations, the data provider is contacted and the reasons for the deviation are clarified.

At the micro level, data are compared with the data of declarations of agricultural and other areas, the Farm Animal Register, Database of the State Social Insurance Fund Board, other agricultural statistical surveys (crop production, animal production, etc.). Differences, if significant, are identified and farms are contacted. Differences are mainly due to inconsistencies in definitions and methodological provisions.

Additional quality control of statistics is performed at the macro level. Results of the calculation are compared with the results of the previous Farm Structure Surveys, Agricultural Censuses and other agricultural statistical surveys (crop, animal, etc.). Results of the calculation are also compared with administrative data: the Register of Agricultural and Rural Business (Holdings' Register). If significant differences in indicators are identified, microdata are analysed in more detail.

Quality of the statistical information has not been affected by COVID-19.

The main users of statistical information are state and municipal institutions and establishments, international organizations, the media, representatives of business and science, students whose needs are met without violating the principle of confidentiality.

Core structural data as well as data for modules ‘Labour force and other gainful activities’, ‘Rural development’ and ‘Animal housing and manure management’ were collected according to Regulation (EU) 2018/1091 of the European Parliament and of the Council of 18 July 2018 on integrated farm statistics and repealing Regulations (EC) No 1166/2008 and (EU) No 1337/2011.

Also, some data for national needs were collected:

• data on having a loan to acquire capital
• data on direct sales (do the direct sales to consumers account for more than 50% of the total sales?)
• data on irrigation
• data on soil cover in winter
• data on tillage methods
• data on use of renewable energy sources (equipment)

There is no information about unmet user needs.

Not applicable.

Since 2005, user opinion surveys have been conducted on a regular basis. Official Statistics Portal traffic is monitored, website visitor opinion polls, general opinion poll on the products and services of Statistics Lithuania, target user group opinion polls and other surveys are conducted.

In 2007, the compilation of a user satisfaction index was launched. The said surveys are aimed at the assessment of the overall demand for and necessity of statistical information in general and specific statistical indicators in particular.

More information on user opinion surveys and results thereof are published in the User Surveys section on the Statistics Lithuania website.

However, user satisfaction survey regarding AC 2020 was not conducted.

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.

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

The precision requirements set in the Regulation (EU) 2018/1091 are all met. 

However, there are two indicators whose RSEs are high:

1. F0000_T0000T (Fruits, berries, nuts and citrus fruits (excluding grapes and strawberries)), LT01, LAFO, RSE= 7.57%
2. A4000_LSU (Sheep and goats), LT01, LAFO, RSE= 9.95%

There is a small amount of farms with fruit and berries as well as with sheep and goats in this NUTS region (LT01) of Lithuania. Area of fruits and berries and number of sheep and goats are relatively small as well.  However, a sample design is one for all indicators of a certain module and a small amount of farmers (respondents) leads to higher RSEs.

In the future, more farms with areas of fruit and berries as well as more farms with sheep and goats will be selected to the sample with a selection probability equal to 1.

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 frame extension, for which core data are sent to Eurostat. 

Core indicators were surveyed as a census. Therefore, ineligible units were just not taken into account when calculating totals. No re-weighting was used.

The modules were surveyed through a sample, but ineligible units were also not taken into account and weights of all units were recalculated considering the corrected population.

Not requested.

See sub-categories below.

Under-coverage is very low (less than 1 %)

The population was checked via various administrative data sources.

It was tried to survey all holdings belonging to the population. However, in some cases new births and new units derived from split may have not been included to the population. This could have happened if a new farm appeared after the public procurement procedure, when lists of farms already were delivered to subcontractor which was responsible for census fieldwork.  

There were several misclassification errors caused by change of municipality by units during the period between the moment of the sampling design and the reference period. Some of these changes were incorrect, therefore they were not taken into account and these units were left in the previous strata. But some of changes were addressed and municipality as well as strata was changed. Misclassification of units' size was not addressed. 

Misclassification errors are estimated to be minimal.

Some farmers and family farms were not surveyed, as were not found by the interviewers, because some addresses were incorrect or some people did not live all the time at the place they were searched (only seasonally, temporarily). Contact errors counted 2.8 %.

If the farmer was not found in his registration address, another address from the IACS Crop Declaration Database was taken if it was possible and the interviewers had to contact the farmer on the new address.

Incorrect phone numbers were corrected by updating them with the information taken from the IACS, telecommunication companies and other statistical surveys. Also, Statistics Lithuania has received e-mails (e-mails were taken from the IACS, other governmental institutions), therefore it was possible for the interviewers to contact farmers by e-mail.

See sub-categories below.

Most questions in the questionnaire were clear for the farmers or clarified by the interviewers. However, some errors occurred.

Mainly characteristics from module Animal housing and manure management were caused measurement errors:

- MAHM 008 “Dairy cows always outdoors”. A big amount of cows was indicated by farmers as always outdoors. Data were corrected by contacting farmers repeatedly.

- MAHM 047 „Net export of slurry/liquid manure from the farm“ and MAHM 048 „Net export of solid manure from the farm“. The main reason - holders do not have information about these quantities. The data were checked using the number of livestock and manure coefficients.  In some cases, farmers were contacted repeatedly.  

MAHM 047 “Organic and waste-based fertilisers other than manure used on the agricultural holding “. There were a lot of cases, when farmers filled in the amount of solid manure. Data were corrected by contacting farmers repeatedly.

It was tried to correct these errors during data collection. Both, interviewers and farmers, were consulted by phone.

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 frame extension, for which core data are sent to Eurostat.

Farms which refused to render information or was not contacted due to other reasons were analysed and checked in the administrative data sources. 

Item non-response was not calculated. Only electronic questionnaires were used, some specific navigation was applied and answering of all relevant questions was mandatory.

Not applicable.

In order to avoid non-response as much as possible, an extensive census promotion campaign was conducted. Also, all farms received information letter with information about census, when, how and where they can provide their data.

See sub-categories below.

Data were imported from the electronic questionnaire to the database using a special computer program. Logical and arithmetical control was made. Data were compared with data from other statistical data sources (previous surveys on crop and animal production etc.). Thus, the probability of the processing errors was minimised as much as possible. Statistics Lithuania can assess that most processing errors were discovered.

The following computer programs were used to process and analyse the data received:

- ABBYY Form Filler 2.5 software was used for entering statistical data and to fill in the electronic questionnaire for agricultural companies and enterprises;

- ORBEON software was used for entering data for farmers' and family farms and transmitting these data via electronic statistical data preparation and transfer system e-Statistics for the Population to survey database;

- A special program created using ORACLE software was used for statistical data processing at Statistics Lithuania;

- Statistical program SAS was used for linking statistical data of several sources according to the selected criterion and for the calculation of derived statistical indicators;

- The results received were transferred into MS Office Excel worksheet tables. Excel was also used for the comparison of statistical AC 2020 data with statistical data of the previous year and the results of the previous FSS.

Corrections and imputations were made by employees of Agricultural, Environmental and Energy Statistics Division of Statistics Lithuania, which were responsible for the AC 2020.Corrections and imputations were made by employees of Agricultural and Environmental Statistics Division of Statistics Lithuania, which were responsible for the AC 2020.

Data available from the different data sources for those holdings which were not found or refused to answer to the questions were imputed into the AC 2020 database (prepared using ORACLE software). For the data imputations for non-response units, IACS Crop Declaration Database, Animal Register, State Social Insurance Fund Board Register were used. Also, the AC 2010, FSS 2013 and FSS 2016 data were used for imputation. Data were prepared for imputation using SAS software and Excel tables. All available statistical data were placed to one data file, this file was checked and automatically exported to the survey database (ORACLE). After that logical and arithmetical control was performed for entire AC 2020 database.

Not applicable.

See sub-categories below.

The first provisional results of the AC 2020 were published on 30 November 2021 in the Press release and in the Database of Indicators of Statistics Lithuania, i.e. 11 months from the reference period to the day of publication of first results.

The final AC 2020 results were published in 17 months from the reference period to the day of publication. First of all, the AC 2020 results were published in the online database (in May 2022). The online publication with the AC 2020 results was prepared and published later, in July 2022. 

See sub-categories below.

See sub-categories below.

Not requested.

First results were published according to approved release calendar. Also, we do not expect delays in dissemination of final results.

See sub-categories below.

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

See sub-categories below.

The definition of agricultural holdings is in accordance with Regulation (EU) 2018/1091. 

Not applicable.

See sub-categories below.

In order to achieve the requirement to cover 98% of the total utilised agricultural area (excluding kitchen gardens) and 98% of the livestock units in the country, the frame was extended. Therefore, the mentioned requirement is fulfilled. Approximately 99.0% of utilised agricultural area and 98.8 % of livestock units were covered.

There are no differences between the national threshold and the threshold of agricultural holdings used for the data sent to Eurostat.

Not applicable.

See sub-categories below.

There are no deviations from Regulation (EU) 2018/1091 and the EU handbook.

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 same LSU coefficients as the ones set in Regulation (EU) 2018/1091 are used.

There are no differences between the types of livestock that are included under the heading “Other livestock n.e.c.” and the types of livestock that should be included according to the EU handbook.

Not applicable.

See sub-categories below.

Data are collected, sent to Eurostat and published in compliance with the reference periods/days set in Regulation (EU) 2018/1091.

Not applicable.

Not applicable.

Not applicable.

Not applicable.

See sub-categories below.

There are no deviations in the national standards and rules for certification of organic products from Council Regulation (EC) No 834/2007.

Not applicable.

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

See sub-categories below.

Time series is comparable since 2003.

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 thresholds were changed to be in line with 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.

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.

Not applicable.

See sub-categories below.

Not applicable.

Common Polulation

From 2016 to 2020, the share of holdings with farm typology FT 16 and FT 61 increased. During last few years such a tendency is observed in Lithuania. More and more farms grow only crops (mainly cereals). Farms with dairy cows, sell their cows due to low purchase prices of milk. Moreover, dairy farms become crop farms. Data on crops were taken from IACS (questionnaires were prefilled), data on farm animals were taken from Animal register (number dairy cows was taken directly, without questioning).

As regards farm typology FT90, the main reason of decrease – most of farms were removed due to the threshold reasons.

As a consequence of a reduction of the number of farms with farm animals, the time manager dedicated to the holding decreased in 2020, compared to 2016. Managers of farms with farm animals usually dedicate more time to holding compared to crop farms.

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.

AC 2020 micro level data were compared to the Annual Crop Statistics 2020 data collection. No significant differences were found.

The comparison with Animal production statistics was not conducted due to the different reference dates.

See sub-categories below.

The information on the comparison between IFS2020 and Annual crops and Animal statistics is available here:

Coherence cross-domain: IFS vs MAIN AREA (ACS) in relative terms

Coherence cross-domain: IFS vs MAIN AREA in absolute terms

Coherence cross-domain: IFS vs CULTIVATED AREA  (ACS) in relative terms

Coherence cross-domain: IFS vs CULTIVATED AREA (ACS) in absolute terms

Livestock comparisons

A4100 (Sheep). The main reason for discrepancies is different reference day: 1 June 2020 in Census 2020; 31 December 2020 in animal production statistics. During the Census 2020, data about number of sheep kept in farms were taken from Animal Register without questioning farms. For animal production statistics needs, the question about sheep was in the survey questionnaire and Animal Register data were prefilled. However, in both cases (Census and the animal production statistics) results are very close to those received from Animal Register.
Another reason – different thresholds. However, in case of sheep, this reason had low influence, because keepers usually keep more than a few sheep and almost all farms which register their sheep are above the threshold (1,7 livestock units) (in case of animal production statistics – all farms with sheep are taken in to account).

A4200 (Goats). The discrepancies occurred due to two reasons: different thresholds of surveys and different reference day.
Different thresholds. In Lithuania a big number of farms keep 1 or 2 goats. In case of Census 2020, the same threshold (1,7 livestock units) was used and much more farms compared to farms with sheep were under the threshold. While in case of animal production statistics – all farms with goats are taken in to account. 

Different reference day: 1 June 2020 in Census 2020; 31 December 2020 in animal production statistics.

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

See sub-categories below.

In order to reduce costs, all holdings had the possibility to provide their data electronically. In order to reduce the burden, administrative data were used as much as possible. 

In case of all agricultural data collections data from administrative data sources are used directly or prefilled into questionnaires. In such a way the duplication of asking the same questions is avoided, because farmers have only look at prefilled numbers and approve their correctness. 

Statistics Lithuania pays a lot of attention to reducing the statistical reporting burden on respondents. Its obligations to implement the Law on Reducing the Administrative Burden of the Republic of Lithuania and to reduce the statistical reporting burden on the respondents are defined in the Respondents’ statistical reporting burden reduction policy.

More information can be found https://osp.stat.gov.lt/statistines-atskaitomybes-nastos-mazinimas

Statistics Lithuania make efforts to improve the AC 2020 efficiency. Firstly, agricultural companies and enterprises as well as farmers' and family farms had the possibility to fill in the electronic questionnaire by themselves and to transmit it via web data collection system. Secondly, the market research company collected data using portable computers, the software ORBEON was used for entering statistical data and data collection system e-Statistics for population was used for data transmission to the survey database. Variables on land areas and farm animals (pigs, poultry, rabbits, beehives) were prefilled in to the AC 2020 questionnaires. Moreover, a lot of variables, such as farm animals (cattle, sheep, goats) as well as all characteristics about support for rural development and organic farming were taken directly from administrative data sources without questioning the farmers. 

Also, such routine operations as data check were automated by introducing logical and arithmetical controls to data entry programs (both to the program created using ORBEON, ORACLE software and ABBYY Form Filler).

See sub-categories below.

The average duration of farm interview was 14 minutes for farmers’ and family farms and 69 minutes for agricultural companies and enterprises. There is no information about the separate duration for core and modules.

The average duration of farm interview was 14 minutes for farmers’ and family farms and 69 minutes for agricultural companies and enterprises. There is no information about the separate duration for core and modules.

Not relevant (data were collected from the administrative data source).

The average duration of farm interview was 14 minutes for farmers’ and family farms and 69 minutes for agricultural companies and enterprises. There is no information about the separate durations for core and modules.

The revision policy applied by Statistics Lithuania is described in the Description of Procedure for Performance, Analysis and Publication of Revisions of Statistical Information.

There are no planned revisions of published AC 2020 data. 

Final results are published and are not subject to subsequent revision. The exception is only in case of significant errors, changes in classifications, methodologies, new statistical data sources, etc.

Individual depersonalised data are validated by Statistics Lithuania and Eurostat using strict rules; later, aggregated data are checked again. AC 2020 data revision was not planned because data were carefully checked against administrative data sources and are consistent with validation rules. 

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.

The stratification variables were standard output and Local Administrative Units (municipalities). 

Within the full coverage strata were holdings: with a standard output of EUR 8 000 or more, i.e. y. belonging to economic size classes IV to XIV; certified organic farms; belonging to specific groups growing walnut, nursery, perennial plants for twining, weaving, flax, oilseeds, tobacco, hops, aromatic, medicinal and culinary plants, seed and seedling plants, other energy and industrial plants, fiber plants as well as farms where ostriches are kept.

The relevant analysis of FSS 2016 data was done for decision regarding the sample size.

See sub-categories below.

Not applicable.

Not applicable.

Not applicable.

See sub-categories below.

The stratification variables were standard output and Local Administrative Units (municipalities). Only the data of holdings that have cattle, pigs, sheep, goats or poultry are sent to Eurostat.

Within the full coverage strata were holdings: with a standard output of EUR 8 000 or more from livestock, certified organic livestock farms; belonging to specific group keeping ostriches.

The relevant analysis of FSS 2016 data was done for decision regarding the sample size.

The software tool used for sample selection was SAS.

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 3-4 years in-between.

See sub-categories below.

Please find the questionnaire in annex.

See sub-categories below.

During AC 2020 only electronic questionnaires were used. Validation rules were prepared and integrated into questionnaires. Moreover, additional validation rules were prepared for data processing software ORACLE. Also, some mistakes or inconsistencies were found during AC 2020 data comparison at macro level.

The weights of holdings in the module's sample were adjusted for non-response. Over–coverage holdings were not taken into account.

The unweighted unit imputation rate was 11 % in the population frame (17900 holdings were imputed).  For core variables unweighted imputation rate was the same as unit imputation rate. For variables in the sample-based module ‘Labour force and other gainful activities’, the unweighted imputation rate was 4,8 % in the gross sample size. For variables in the sample-based module ‘Animal housing and manure management’, the unweighted imputation rate was 3,5 % in the gross sample size.

Covered under Data compilation.

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

See sub-categories below.

AC - Agricultural Census

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

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