Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
National Accounts division is responsible for compilation of annual and quarterly main aggregates of NA (basic and detailed breakdowns of main NA aggregates).
Methodology and Data Science group is responsible for seasonal adjustment of all required quarterly NA data.
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
State Data Agency (Statistics Lithuania), 29 Gedimino Ave., LT-01500 Vilnius, Lithuania
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
5 January 2026
2.2. Metadata last posted
5 January 2026
2.3. Metadata last update
5 January 2026
3.1. Data description
This metadata is associated with the following tables in Eurobase:
Capital stocks by industry and by detailed asset type (nama_10_nfa_st)
Capital stocks by sector and by detailed asset type (nama_10_nfa_bs)
Capital formation by industry and by detailed asset type (nama_10_a64_p5)
Quarterly and annual gross fixed capital formation by main asset type (namq_10_an6 and nama_10_an6)
National accounts data concern all data produced and disseminated for an economy according to the definitions and guidelines of the European System of Accounts (ESA 2010).
Lithuania provides to Eurostat all mandatory data required by the ESA 2010 transmission programme and some information on voluntary basis for tables nama_10_nfa_stand nama_10_a64_p5 ( e.g. type of asset by A*21 - AN.11321 Computer hardware, AN.11322 Telecommunications equipment, AN.1139 + AN.114 Other machinery and equipment + weapon systems, AN.1171 Research and development, AN.1173 Computer software and databases).
Lithuanian data, which is published in Eurobase, can be found in national Database of Indicatorsunder database tree Economy and finance (macroeconomics) (>National Accounts (ESA 2010)).
The associated transmission programme (Annex B) defines compulsory data. Data are compiled at the level of the total economy at industry and institutional sector level and by asset breakdowns. The classifications applied are described below.
Economic activity
ESA 2010 uses aggregation levels of the NACE Rev.2 classification to define industry breakdowns (NACE stands for Nomenclature générale des Activités économiques dans les Communautés Européennes). NACE Rev.2 is a classification of economic activities widely used in statistics and in other domains. Requirements for the transmission of NACE Rev.2 series have been specified in the Commission Regulation (EC) No 715/2010 of 10 August 2010.
Lithuanian classification of Economic Activities (EVRK Rev 2) is a national version of the Statistical Classification of Economic Activities in the European Community (NACE). The periodicity of update of the classification directly depends on the periodicity of update of NACE.
Asset types
Asset types for non-financial fixed assets are classified according to ESA 2010 (Table 7.1 and Chapter 23).
Institutional sector
Breakdowns by institutional sector include total economy (S.1), non-financial corporations (S.11), financial corporations (S.12), general government (S.13), households (S.14), and non-profit institutions serving households (S.15).
More details and specific information can be found in relevant metadata file (link in concept 3.1).
3.3. Coverage - sector
The ESA 2010 transmission programme, as outlined in annex B of EU regulation 2023/734, which amended the European system of regional and national accounts (ESA 2010), defines the datasets that national statistical authorities of the EU countries have to transmit to Eurostat for the compilation of the European accounts.
For capital stocks, gross capital formation, gross fixed capital formation, consumption of fixed capital and balance sheets, countries are required to transmit annual data. Balance sheets are broken down by asset group and by institutional sector; the other variables are broken down by asset group and NACE industry (various levels). Quarterly data for gross fixed capital formation is also transmitted.
More information about each data set can be found in relevant metadata file (see links in concept 3.1).
3.4. Statistical concepts and definitions
These data sets require the understanding of various technical concepts, e.g. asset, fixed assets, (produced and non-produced) non-financial assets, fixed capital, capital stock (gross and net), consumption of fixed capital, gross capital formation, and gross fixed capital formation.
Lithuania applies concepts and definitions of ESA 2010 .
3.5. Statistical unit
According to the ESA 2010 guidelines, in national accounts two types of units and two corresponding ways of subdividing the economy are used: (a) institutional unit; (b) local kind-of-activity unit (local KAU). The first type is used for describing income, expenditure and financial flows as well as balance sheets. The second type of units is used for the description of production processes, for input-output analysis and for regional analysis.
An institutional unit is an economic entity characterised by decision-making autonomy in the exercise of its principal function. A resident unit is regarded as constituting an institutional unit in the economic territory where it has its centre of predominant economic interest if it has decision-making autonomy and either keeps a complete set of accounts, or is able to compile a complete set of accounts.
A local KAU groups all the parts of an institutional unit in its capacity as producer which are located in a single site or in closely located sites, and which contribute to the performance of an activity at the class level (four digits) of the NACE Rev. 2.
An institutional unit comprises one or more local KAUs; a local KAU belongs to one and only one institutional unit.
Lithuanian national accounts are based on institutional units, which correspond to concept of enterprise in Lithuania. The Kind-of-activity units (KAUs) are made only out of the biggest enterprises that carry out several activities, and which have an impact on the total results.
The Statistical Register of Economic Entities (SREE) is the main tool to carry out statistical surveys. This register is maintained by Statistics Lithuania. It includes information about all types of units from the administrative Register of Legal Entities determining their active/inactive status. The SREE is the base for statistical units, sample frames, business demography and for serving user needs. For statistical purposes the Register, apart from the administrative part of information from administrative registers of units, includes a statistical part of information as well.
3.6. Statistical population
The national accounts population of a Lithuania consists of all resident statistical units. A unit is a resident unit of a country when it has a centre of predominant economic interest on the economic territory of that country, that is, when it engages for an extended period (one year or more) in economic activities on this territory.
Lithuanian national accounts are exhaustive. This means that all resident statistical units are covered directly through data sources (surveys/administrative data) or through inclusion of exhaustiveness adjustments.
3.7. Reference area
The reference area in Lithuanian national accounts is the economic territory of Republic of Lithuania.
3.8. Coverage - Time
The length of time series of the Lithuanian data starts from 1995. The time series at current prices, replacement costs and chain-linked volumes are available starting 1995 until the most recent year; the data at previous year’s prices are available starting 1996.
3.9. Base period
The concept of 'base period' is not applied in national accounts. Instead, for some national accounts variables the concepts of previous year prices and chain-linked volumes are applied, as stipulated in Regulation (EU) 2023/734. Expressing variables at the prices of the previous year allows the calculation of volume indices between the current time period and the previous year. After a reference period is chosen as a benchmark, volume indices can be chain-linked and then applied to variables at current prices of the benchmark year. This generates volume estimates for any period of observation.
Lithuania currently uses 2021as reference year for the compilation of chain-linked volumes.
Data on gross fixed capital formation and consumption of fixed capital are available in current prices, prices of previous year, and in chain-linked volumes, in millions of euro.
Data on capital stocks are available in gross and net terms at current replacement costs and the previous year's replacement costs at the end of the year, in millions of euro.
Data on balance sheets are available only in current prices, in millions of euro.
Lithuania adopted the euro as its national currency on 1 January 2015. NA data in national currency that Lithuania transmits to Eurostat correspond to nationally published figures. These series are converted into euros using the irrevocably fixed exchange rate and are published on Eurobase as Euro series (CP MEUR). The litas (former national currency) was pegged to the euro at a rate of 3.4528 to 1 on 2 February 2002 and litas became part of the ERM (European Exchange Rate Mechanism) II on 28 June 2004. This exchange rate did not change until Lithuania joined the euro area on 1 January 2015. The series at national currency and euro coincide from 2003 onwards but differ for earlier years due to market exchange rate movements.
The usual reference period to be used for presenting national accounts data is the calendar year for annual data and the quarter for quarterly data.
Two basic kinds of information are recorded: flows and stocks. Flows refer to actions and effects of events that take place within a given period of time (year or quarter), while stocks refer to positions at a point of time (usually the beginning or end of a year or quarter).
In the case of stock, which refer to positions at a point of time, recording time is the end of the accounting period of t-1. The closing stock of t-1 concerns the opening stock of t.
Lithuania uses the approach for reference period described above (concept 3.9).
6.1. Institutional Mandate - legal acts and other agreements
Stocks of fixed assets, gross fixed capital formation, consumption of fixed capital, balance sheets data are based on national accounts which are compiled in accordance with a methodology on common standards, definitions, classifications and accounting rules laid down in Annex A and in respect of the time limits set out in Annex B of the EU regulation 2023/734, which amended the European system of regional and national accounts (ESA 2010). Data on Research and development was added in Commission Delegated Regulation (EU) 2015/1365.
The mutual agreements between Statistics Lithuania and administrative data providers (e.g. The Bank of Lithuania, Ministry of Finance) are signed and updated every year.
6.2. Institutional Mandate - data sharing
Lithuanian national accounts data are used by different national and international organizations, policy makers, analysts. All data presented in the national Database of indicators are accessible to everyone.
Data are transmitted via Eurostat to other international organisations as Statistics Lithuania is part of the European Statistical System and coordinates and shares data with the Commission (Eurostat).
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
In the process of statistical data collection, processing and analysis and dissemination of statistical information, the State Data Agency 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 the State Data Agency.
7.2. Confidentiality - data treatment
Lithuanian guidance on confidential data treatment is presented in:
The Statistical Disclosure Control Manual, approved by Order No DĮ-26 of 19 January 2024 of the Director General of the State Data Agency.
The State Data Governance Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the State Data Governance Information System, approved by Order No DĮ-202 of 27 August 2021 of the Director General of Statistics Lithuania.
Lithuania transmits capital formation and stocks data to Eurostat at a highly aggregated level, therefore, these data are not classified as confidential.
8.1. Release calendar
Statistical information is published in accordance with an approved release calendar placed on the Official Statistics Portal of Lithuania. Release calendar is usually approved around mid-December for the following year. Any amendments to release calendar are approved by the order of Director General of State Data Agency as soon as they are known.
The advance release calendar includes events such as news releases, publications, indicators database.
8.2. Release calendar access
Approved release calendar of Statistics Lithuania is available on the website. Search by area “Economy and finance (macroeconomics)”, topic “National accounts” and sub-theme are available for selection.
8.3. Release policy - user access
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.
Statistical information is published following the Official Statistics Dissemination Policy Guidelines and the Rules for Information Dissemination and Communication of the State Data Agency, approved by Order No DĮ-221 of 14 October 2025 of the Director General of the State Data Agency.
Annual data: gross fixed capital formation, capital stocks, consumption of fixed capital, and balance sheets.
10.1. Dissemination format - News release
No specific news release related to capital formation and stocks data.
10.2. Dissemination format - Publications
No specific publications related to capital formation and stocks data.
10.3. Dissemination format - online database
Lithuanian national accounts data are available to users in Database of Indicators. All statistical data are available by entering navigation tree under ‘Economy and finance (macroeconomics)‘ and then by selecting navigation tree ‘National accounts (ESA 2010)’.
10.4. Dissemination format - microdata access
Not applicable.
10.5. Dissemination format - other
Information on national accounts may be posted using social media.
Statistics Lithuania uses of social media of Facebook, Twitter, WordPress, YouTube.
Statistics Lithuania publishes some national metadata documentation on the Official Statistics Portal under ‘Metadata’.
10.7. Quality management - documentation
The importance of national accounts requires that documentation should be available on the procedures applied for quality management and quality assessment. Examples of such documentation are national accounts quality reports, quality studies and reports on revision analysis.
The quality (accuracy/consistency) checks carried out by Eurostat on the received country data are described in a validation handbook. From 2017 onwards also annual quality reports are available. They describe several dimensions of the quality of countries' national accounts data transmissions.
GNI Inventories contain very relevant information on the quality of the data underlying the GNI data transmitted by countries to Eurostat. GNI Inventories contain sections on the estimation of capital stocks, consumption of fixed capital, gross fixed capital formation and balance sheets.
Chapter 1 of the Lithuanian GNI Inventory is available in CIRCABC webpage. The full GNI Inventory is not publicly available.
11.1. Quality assurance
Quality is assured by strict application of ESA 2010 concepts and by thorough validation of the data delivered by countries.
In 2007, a quality management system, conforming to the requirements of the international quality management system standard ISO 9001, was introduced at Statistics Lithuania. 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 State Data Agency website.
The ESA 2010 Regulation stipulates that the quality of national and regional accounts data sent to Eurostat are to be assessed according to the quality criteria set out by the Regulation on European statistics (Regulation (EC) No 223/2009). The modalities, structure and assessment indicators of the quality assessment process are set out in a Commission implementing act (Regulation (EU) 2016/2304).
Each year, in accordance with Article 4(2) of the ESA 2010 Regulation, Member States report on the quality of national and regional accounts data sent to Eurostat. Based on their national quality reports, Eurostat prepares an overall assessment in accordance with Article 4(4).
Every year, not later than 31 May, Lithuania provides Eurostat with the completed quality report. The quality report on national and regional accounts contains quantitative indicators and qualitative descriptions of the quality of the data sent the previous year. These reports are not published nationally.
Lithuania also provides to Eurostat the yearly Report on quality of GNI data and the GNI questionnaire. Report is not available to the users. The structure and format of the GNI Questionnaires and Reports on Quality is approved each year by the GNI Expert Group.
11.2. Quality management - assessment
ESA 2010 data transmissions are subject to regular quality assessment reviews. Article 4 of Regulation (EU) No 549/2013 (ESA 2010 Regulation) specifies that the data covered by that Regulation is subject to the quality criteria, namely relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability and coherence, as set out in Article 12(1) of Regulation (EC) No 223/2009 of the European Parliament and of the Council.
Member States are to provide the Commission with a report on the quality of the transmitted data on national and regional accounts. The modalities, structure, periodicity and assessment indicators of the quality reports on data transmitted have been specified in a Commission Implementing Regulation 2016/2304 of 19 December 2016. The implementation of the quality reporting and assessment exercise started in 2017 and is carried out annually. As part of the annual exercise, Eurostat assesses the results, prepares and publishes an overall assessment based on the national quality reports and other available information.
See also section 11.1.
The quality of information is analysed during the estimation of indicators. Additional quality control of statistical data is performed at the macro level. Statistical indicator estimates are compared with the estimates of the previous periods and the data from other relevant statistical surveys and administrative sources.
Eurostat periodically checks the quality of the reported annual National Accounts data through the annual GNI questionnaires and the GNI quality reports. Eurostat also assesses countries' GNI Inventories of sources and methods, and the compliance of the compiled indicators with the requirements of EU legislation. GNI verification visits are carried out to gather additional information that is necessary to identify possible weaknesses in the statistical sources and methods used to calculate GNI and its components.
12.1. Relevance - User Needs
Users of annual national accounts data are typically interested in analysing structural changes in the economy from a medium-term perspective.
Data on gross fixed capital formation is used to compile stocks of fixed assets and balance sheets, which on its hand is very much used in economic and productivity analyses. Reliable measurement of productivity, in particular capital productivity, depends on accurate capital related data, including gross fixed capital formation.
The main users of statistical information on Lithuanian National Accounts are State and municipal authorities and agencies, international organisations, the media, research and business communities, students, whose needs are satisfied without a breach of the confidentiality principle.
12.2. Relevance - User Satisfaction
From 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 State Data Agency website.
12.3. Completeness
According to quality reports issued by Eurostat (see section 11.1 for more information) overall completeness of Lithuanian National Accounts data as required by ESA 2010 Transmission Programme was very high.
Lithuania provides all mandatory data required by TP and some information on voluntary basis.
13.1. Accuracy - overall
National accounts aggregates estimated in Lithuania are based on various data sources: large number of statistical surveys, administrative data, using direct and indirect estimation methods, benchmarking and extrapolations. The accuracy of NA aggregates largely depends on the quality of the different data sources used. Conceptual and exhaustiveness adjustments are made to the data coming from the different data sources to meet the requirements and definitions of ESA 2010.
The most accurate estimates are made after the balancing procedure of Supply-Use tables (transmitted at t+36 months after the reference period). The supply and use framework forms the basis for the balancing process by type of product and provides important indications as regards the consistency of the GDP production and expenditure approaches.
Accuracy of capital stock estimates is ensured through the application of the PIM method based on consistent GFCF time series by asset, sector and economic activity. The reliability of the estimates is monitored by regularly reviewing key model parameters, such as service lives, retirement and depreciation assumptions, and by comparing the results with available information from age structure surveys and administrative data sources.
13.2. Sampling error
Not applicable.
13.3. Non-sampling error
Not applicable.
14.1. Timeliness
Member States are required to transmit their data to Eurostat in compliance with the deadlines defined in the ESA 2010 transmission programme.
Lithuanian national accounts are sent to Eurostat respecting the deadlines specified in ESA 2010 data transmission programme.
Annual and quarterly NA data are disseminated nationally in timely matter according to approved release calendar (see sections 8.1-8.3 for more information).
14.2. Punctuality
The punctuality of transmissions is usually very high and is reported in the annual ESA quality reports.
In Lithuania statistical information is published in accordance with an Official Statistics Calendar. In case of delay, users are notified in advance by indicating the reason and a new date of publication.
15.1. Comparability - geographical
The comparability is ensured by the application of common definitions (ESA 2010).
Lithuanian national accounts are produced according to requirements and definitions of ESA 2010. Lithuanian NA aggregates should be comparable with the same NA aggregates of other countries, which use the common definitions of ESA 2010 for production of their NA data. However full comparability cannot be always ensured, as different countries may use different methods and different data sources for estimation of NA aggregates.
15.2. Comparability - over time
By using a common framework, the ESA 2010, data can be comparable over time. In the case of fundamental changes to methods or classifications, revisions of long time series are performed, usually going far back into the past. If the series contain some break suggesting that some structural change occurred in the series at a certain point in time, a flag “B” is inserted in the first period (year/quarter) when it occurs.
The Lithuanian NA accounts data are comparable over time. The length of comparable time series is according to the requirements of ESA 2010 Transmission programme of data and depends on the corresponding data table.
The temporal breaks in time series can sometimes occur with the major or benchmark revisions of time series, changes in the classifications.
15.3. Coherence - cross domain
Within the system of national accounts there is full consistency between the domains: annual and quarterly national accounts, government accounts, sector accounts, financial accounts, regional accounts, supply and use tables. However, in practice full consistency may not always be possible and temporary discrepancies might occur. They are usually the result of vintage differences.
Primary statistics like structural business statistics (SBS), short term statistics (STS) and labour force statistics (LFS) are widely used as input for national accounts. However, there is no full consistency between these statistical domains and national accounts. Main reasons are differences in concepts/definitions and in coverage. Balance of payments is also used as an important source for national accounts. The definitions and coverage of balance of payments, as defined in the BPM6 manual, are fully harmonised with those in ESA 2010. Therefore, balance of payments variables are in principle fully coherent with the corresponding national accounts variables.
The compilation of fixed capital is consistent with the gross fixed capital formation in the national accounts. The types of assets by industry breakdown are identical to the breakdown of gross fixed capital formation and the breakdown by institutional sectors is identical to the institutional sector accounts.
The coherence of Lithuanian National Accounts data is very high in terms of internal consistency between and within the data tables, sub-annual and annual statistics, totals and sums of components.
Some differences between the tables during the year may occur due to vintage effect. This mainly concerns coherence with the general government accounts.
15.4. Coherence - internal
The internal coherence of the assessed Lithuanian data is very high, Lithuanian data are also coherent in terms of additivity of series. The internal coherence is checked between annual and quarterly NA data tables in respect to coherence within and between tables, totals and sum of components.
The internal coherence is fully ensured for net stocks at current prices between data in “Stocks of fixed assets” and “Balance sheet of non-financial assets” totals and sum of components.
The national accounts indicators are estimated using information from other statistical surveys, carried out by the Statistics Lithuania, and administrative data sources, so there is no additional statistical reporting burden on respondents.
17.1. Data revision - policy
In Lithuania the published national accounts aggregates can regularly be affected by the revisions. Two types of revisions are distinguished in national accounts practice: routine revisions and major/benchmark revisions. Regular update of data sources is a major cause of the routine revisions, while methodological provisions updates, improvement of estimation methods, emergence of new sources of information are the reasons for major revisions of National Accounts indicators.
Regarding revision policy implementation, the recommended harmonized revision policy is applied in Lithuania; some temporary inconsistencies can occur due to vintage effect.
Revision policy and its harmonization are also discussed in the Interinstitutional group on Macroeconomic statistics. This group is represented by experts from State Data Agency, the Ministry of Finance, the Bank of Lithuania, the State Tax Inspectorate, the Ministry of Economy and Innovation and National audit office of Lithuania (as an observer).
17.2. Data revision - practice
The revisions in Lithuania are usually scheduled and results are published in accordance to advance release calendar, indicating the length of time-series to be revised. In the case of unexpected non-scheduled revisions, the changes to release calendar are approved by the order of Director General of State Data Agency and users are informed about them.
The annual and quarterly data are revised and published once a year (usually in the first days of October). The routine annual revision of NA indicators usually affects time series up to the year t-4.
The last benchmark revision of NA indicators was performed in September 2024. For more information, please see the news release Annual aggregates of national accounts.
For the Relative Mean Absolute Revision of GDP and related indicators, please see nationally published metadata concept 17.2.1 Data revision - average size
See also section 17.1
18.1. Source data
National Accounts in Lithuania are estimated using various data sources: statistical surveys, administrative data, fiscal data. Some data sources are used for estimation of NA components, while others are used for verification purposes. Capital stock estimates are mainly based on national accounts data on GFCF, complemented by results from age structure surveys and administrative data sources.
The list of the main data sources broken down by three GDP approaches and GNI are presented in Chapter 1 of Lithuanian GNI Inventory (see section 1.9 Main data sources used). More detailed information about these main data sources is provided in GNI Inventory chapter 10, however it is not publicly available.
As for specific data sources for annual GDP and related aggregates (which are not available for quarterly estimates): there are many of them available only on annually basis, one of most important one is SBS data, the other ones are: Annual survey on earnings, Annual survey on trade and catering enterprises, HBS, Labour cost survey, Fuel and energy balances, Survey on education finance statistics, Investment survey, Research and experimental development surveys, Survey on education finance statistics, etc.
The quarterly estimates are compiled using multiple data sources such as output data, foreign trade statistics data on imports and exports, as well as from statistical questionnaires on enterprises’ production, agricultural statistics data. Intellectual property products estimation are based on forecasts produced using the IPP model.
18.2. Frequency of data collection
National accounts are usually compiled on an annual or quarterly basis from other primary statistics. The frequency of data collection of primary statistics varies according to the nature of the data source.
The Schedule of the exchange of information between the units inside Statistics Lithuania is approved by the Director General every year. This document specifies for every Statistics Lithuania unit what data, at which detail, when and to who has to be delivered.
Agreements between Statistics Lithuania and other administrative data providers (The Ministry of Finance, The Bank of Lithuania, Centre of Registers and other institutions) are also made. The agreements specify what data and at what level of detail should be provided, to whom, format and method of data provision, frequency and provision deadline of the data.
18.3. Data collection
National accounts departments typically do not collect data themselves but receive them from other departments or institutions.
The data collection in Lithuania is organised according to the schedule of the exchange of information between the units inside Statistics Lithuania and via signed agreements with external data providers. Please see section 18.2 for more information.
National accountants in Lithuania are often involved in advising on the contents of surveys, updates and development of the questionnaires of other units in Statistics Lithuania.
18.4. Data validation
The confrontation of data from different sources is an integral part of the national accounts compilation. Statistical data quality is ensured through data analysis, verification and validation of the data. Statistical data are compared with data from previous periods and with information from additional data sources. Analysis of the statistical data and identification of outliers are carried out. In the event of significant deviations, the reasons for the deviation are investigated and the errors identified are corrected.
For the validation of national accounts data, Lithuania also applies validation rules agreed with Eurostat and provides metadata to support the validation process with respect to revisions and outliers.
18.5. Data compilation
The Capital Stocks and Consumption of fixed capital (CFC) are assessed with the Perpetual Inventory Method (PIM) on the basis of information available on gross fixed capital formation (GFCF), prices relating to this investment and average economic life of different categories of fixed assets, based on the “Residual book-keeping value of fixed tangible and intangible assets distributed by vintage” surveys. Calculations of the gross and net capital stocks, also consumption of fixed capital include estimations by institutional sector, kind of activities, all types of producers (market, non-market and own final use) and have been grouped according to the branch of activities and fixed assets’ categories.
18.6. Adjustment
Annual data for gross fixed capital formation, capital stocks, consumption of fixed capital, and balance sheets is not seasonally adjusted. Quarterly data for gross fixed capital formation is adjusted for seasonal and calendar effects.
Economy and finance dedicated data and meta information can be found in Official Statistics Portal of Statistics Lithuania.
This metadata is associated with the following tables in Eurobase:
Capital stocks by industry and by detailed asset type (nama_10_nfa_st)
Capital stocks by sector and by detailed asset type (nama_10_nfa_bs)
Capital formation by industry and by detailed asset type (nama_10_a64_p5)
Quarterly and annual gross fixed capital formation by main asset type (namq_10_an6 and nama_10_an6)
National accounts data concern all data produced and disseminated for an economy according to the definitions and guidelines of the European System of Accounts (ESA 2010).
Lithuania provides to Eurostat all mandatory data required by the ESA 2010 transmission programme and some information on voluntary basis for tables nama_10_nfa_stand nama_10_a64_p5 ( e.g. type of asset by A*21 - AN.11321 Computer hardware, AN.11322 Telecommunications equipment, AN.1139 + AN.114 Other machinery and equipment + weapon systems, AN.1171 Research and development, AN.1173 Computer software and databases).
Lithuanian data, which is published in Eurobase, can be found in national Database of Indicatorsunder database tree Economy and finance (macroeconomics) (>National Accounts (ESA 2010)).
5 January 2026
These data sets require the understanding of various technical concepts, e.g. asset, fixed assets, (produced and non-produced) non-financial assets, fixed capital, capital stock (gross and net), consumption of fixed capital, gross capital formation, and gross fixed capital formation.
Lithuania applies concepts and definitions of ESA 2010 .
According to the ESA 2010 guidelines, in national accounts two types of units and two corresponding ways of subdividing the economy are used: (a) institutional unit; (b) local kind-of-activity unit (local KAU). The first type is used for describing income, expenditure and financial flows as well as balance sheets. The second type of units is used for the description of production processes, for input-output analysis and for regional analysis.
An institutional unit is an economic entity characterised by decision-making autonomy in the exercise of its principal function. A resident unit is regarded as constituting an institutional unit in the economic territory where it has its centre of predominant economic interest if it has decision-making autonomy and either keeps a complete set of accounts, or is able to compile a complete set of accounts.
A local KAU groups all the parts of an institutional unit in its capacity as producer which are located in a single site or in closely located sites, and which contribute to the performance of an activity at the class level (four digits) of the NACE Rev. 2.
An institutional unit comprises one or more local KAUs; a local KAU belongs to one and only one institutional unit.
Lithuanian national accounts are based on institutional units, which correspond to concept of enterprise in Lithuania. The Kind-of-activity units (KAUs) are made only out of the biggest enterprises that carry out several activities, and which have an impact on the total results.
The Statistical Register of Economic Entities (SREE) is the main tool to carry out statistical surveys. This register is maintained by Statistics Lithuania. It includes information about all types of units from the administrative Register of Legal Entities determining their active/inactive status. The SREE is the base for statistical units, sample frames, business demography and for serving user needs. For statistical purposes the Register, apart from the administrative part of information from administrative registers of units, includes a statistical part of information as well.
The national accounts population of a Lithuania consists of all resident statistical units. A unit is a resident unit of a country when it has a centre of predominant economic interest on the economic territory of that country, that is, when it engages for an extended period (one year or more) in economic activities on this territory.
Lithuanian national accounts are exhaustive. This means that all resident statistical units are covered directly through data sources (surveys/administrative data) or through inclusion of exhaustiveness adjustments.
The reference area in Lithuanian national accounts is the economic territory of Republic of Lithuania.
The usual reference period to be used for presenting national accounts data is the calendar year for annual data and the quarter for quarterly data.
Two basic kinds of information are recorded: flows and stocks. Flows refer to actions and effects of events that take place within a given period of time (year or quarter), while stocks refer to positions at a point of time (usually the beginning or end of a year or quarter).
In the case of stock, which refer to positions at a point of time, recording time is the end of the accounting period of t-1. The closing stock of t-1 concerns the opening stock of t.
Lithuania uses the approach for reference period described above (concept 3.9).
National accounts aggregates estimated in Lithuania are based on various data sources: large number of statistical surveys, administrative data, using direct and indirect estimation methods, benchmarking and extrapolations. The accuracy of NA aggregates largely depends on the quality of the different data sources used. Conceptual and exhaustiveness adjustments are made to the data coming from the different data sources to meet the requirements and definitions of ESA 2010.
The most accurate estimates are made after the balancing procedure of Supply-Use tables (transmitted at t+36 months after the reference period). The supply and use framework forms the basis for the balancing process by type of product and provides important indications as regards the consistency of the GDP production and expenditure approaches.
Accuracy of capital stock estimates is ensured through the application of the PIM method based on consistent GFCF time series by asset, sector and economic activity. The reliability of the estimates is monitored by regularly reviewing key model parameters, such as service lives, retirement and depreciation assumptions, and by comparing the results with available information from age structure surveys and administrative data sources.
Data on gross fixed capital formation and consumption of fixed capital are available in current prices, prices of previous year, and in chain-linked volumes, in millions of euro.
Data on capital stocks are available in gross and net terms at current replacement costs and the previous year's replacement costs at the end of the year, in millions of euro.
Data on balance sheets are available only in current prices, in millions of euro.
Lithuania adopted the euro as its national currency on 1 January 2015. NA data in national currency that Lithuania transmits to Eurostat correspond to nationally published figures. These series are converted into euros using the irrevocably fixed exchange rate and are published on Eurobase as Euro series (CP MEUR). The litas (former national currency) was pegged to the euro at a rate of 3.4528 to 1 on 2 February 2002 and litas became part of the ERM (European Exchange Rate Mechanism) II on 28 June 2004. This exchange rate did not change until Lithuania joined the euro area on 1 January 2015. The series at national currency and euro coincide from 2003 onwards but differ for earlier years due to market exchange rate movements.
The Capital Stocks and Consumption of fixed capital (CFC) are assessed with the Perpetual Inventory Method (PIM) on the basis of information available on gross fixed capital formation (GFCF), prices relating to this investment and average economic life of different categories of fixed assets, based on the “Residual book-keeping value of fixed tangible and intangible assets distributed by vintage” surveys. Calculations of the gross and net capital stocks, also consumption of fixed capital include estimations by institutional sector, kind of activities, all types of producers (market, non-market and own final use) and have been grouped according to the branch of activities and fixed assets’ categories.
National Accounts in Lithuania are estimated using various data sources: statistical surveys, administrative data, fiscal data. Some data sources are used for estimation of NA components, while others are used for verification purposes. Capital stock estimates are mainly based on national accounts data on GFCF, complemented by results from age structure surveys and administrative data sources.
The list of the main data sources broken down by three GDP approaches and GNI are presented in Chapter 1 of Lithuanian GNI Inventory (see section 1.9 Main data sources used). More detailed information about these main data sources is provided in GNI Inventory chapter 10, however it is not publicly available.
As for specific data sources for annual GDP and related aggregates (which are not available for quarterly estimates): there are many of them available only on annually basis, one of most important one is SBS data, the other ones are: Annual survey on earnings, Annual survey on trade and catering enterprises, HBS, Labour cost survey, Fuel and energy balances, Survey on education finance statistics, Investment survey, Research and experimental development surveys, Survey on education finance statistics, etc.
The quarterly estimates are compiled using multiple data sources such as output data, foreign trade statistics data on imports and exports, as well as from statistical questionnaires on enterprises’ production, agricultural statistics data. Intellectual property products estimation are based on forecasts produced using the IPP model.
Annual data: gross fixed capital formation, capital stocks, consumption of fixed capital, and balance sheets.
Member States are required to transmit their data to Eurostat in compliance with the deadlines defined in the ESA 2010 transmission programme.
Lithuanian national accounts are sent to Eurostat respecting the deadlines specified in ESA 2010 data transmission programme.
Annual and quarterly NA data are disseminated nationally in timely matter according to approved release calendar (see sections 8.1-8.3 for more information).
The comparability is ensured by the application of common definitions (ESA 2010).
Lithuanian national accounts are produced according to requirements and definitions of ESA 2010. Lithuanian NA aggregates should be comparable with the same NA aggregates of other countries, which use the common definitions of ESA 2010 for production of their NA data. However full comparability cannot be always ensured, as different countries may use different methods and different data sources for estimation of NA aggregates.
By using a common framework, the ESA 2010, data can be comparable over time. In the case of fundamental changes to methods or classifications, revisions of long time series are performed, usually going far back into the past. If the series contain some break suggesting that some structural change occurred in the series at a certain point in time, a flag “B” is inserted in the first period (year/quarter) when it occurs.
The Lithuanian NA accounts data are comparable over time. The length of comparable time series is according to the requirements of ESA 2010 Transmission programme of data and depends on the corresponding data table.
The temporal breaks in time series can sometimes occur with the major or benchmark revisions of time series, changes in the classifications.
