Producer price index for industrial production (PPI)


  1. Contact
  2. Metadata update
  3. Statistical presentation
  4. Measurement unit(s)

  5. Reference period
  6. Institutional mandate
  7. Confidentiality
  8. Release policy
  9. Frequency of dissemination
  10. Accessibility and clarity
  11. Methodological documentation

  12. Quality management
  13. Relevance
  14. Accuracy and reliability
  15. Timeliness and punctuality
  16. Coherence and comparability
  17. Coherence
  18. Response burden

  19. Data revision

  20. Statistical processing
  21. Comments and other information

1 Contact
1.1 Contact organisation

Statistics Lithuania

1.2 Contact organisation unit

Price Statistics Division

1.3 Contact name

Regina Burneikienė

1.4 Contact person function

Chief Specialist

1.5 Contact mail address

29 Gedimino Ave., LT-01500 Vilnius, Lithuania

1.6 Contact email address

1.7 Contact phone number

+370 5 236 4732

1.8 Contact fax number

+370 5 236 4666

2 Metadata update
2.1 Metadata last certified


2.2 Metadata last posted 2020-11-11
2.3 Metadata last update 2020-11-10
3 Statistical presentation

Description of statistical information (main characteristics, purpose)

The objective of the statistical survey on prices for producer products – to collect statistical data about prices of representative products and to calculate the PPI for different periods on the basis of that statistical data, i.e. to calculate the overall change in prices for Lithuanian industrial production sold over a certain period of time. The PPI is used to calculate various indicators at constant prices, to analyse the economic development and evaluate inflation processes in the industrial sector.


Classifications(s), classification system

National version (EVRK Rev. 2) of the Statistical Classification of Economic Activities in the European Community (NACE Rev. 2);

Classification of Products and Services (PGPK 2016);

Nomenclature of Countries and Territories

3.3 Sector coverage

Mining and quarrying, manufacturing, electricity, gas, steam and air conditioning supply, water supply, sewerage, waste management and remediation activities (EVRK Rev. 2, sections B–E).

3.4 Statistical concepts and definitions

Producer price index (PPI) is a relative indicator reflecting the overall change in prices for industrial products manufactured by Lithuanian producers over a certain period of time.

Price index is a relative statistical indicator showing the price change over a certain period of time.

Index reference period is the reference period with the index equated to 100 points. Having the time series of price indices, calculated with a single index reference period, it is possible to determine the PPI for different periods.

Price reference period is a reference period based on the price level in which the overall change in prices is measured.

Weight reference period is the reference period the data of which are used for calculating index weights.

Weight is the volume of products of a certain classification level, compared to the volume of higher-level products in the weight reference period in value terms. The higher the weight, the stronger the effect of change in prices for industrial products of a certain classification level on the change in prices for industrial products of the higher classification level.

3.5 Statistical unit


3.6 Statistical population

Selected enterprises selected of various forms of ownership engaged in industrial activities. Enterprises are chosen with a record of stable production and large share of sales in the respective PGPK 2016 product heading.. 

3.7 Reference area

The entire territory of the country.

3.8 Time coverage

Since January 1992.

3.9 Base period



Measurement unit(s)


Weights and rates of change in prices are expressed in per cent.

5 Reference period


6 Institutional mandate
6.1 Legal acts and other agreements

Council Regulation (EC) No 1165/98 of 19 May 1998 concerning short-term statistics (OJ 2004, special edition, volume 20, p. 291), as last amended by Commission Regulation (EU) No 461/2012 of 31 May 2012 (OJ 2012 L 142, p. 26).


Data sharing and exchange

7 Confidentiality

Confidentiality policy

In the process of statistical data collection, processing and analysis and dissemination of statistical information, Statistics Lithuania fully guarantees the 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.

7.2 Confidentiality - data treatment

Description of Statistical Disclosure Control Methods, approved by Order No DĮ-124 of 27 May 2008 of the Director General of Statistics Lithuania.

Integrated Statistical Information System Data Security Regulations and Rules for the Secure Management of Electronic Information in the Integrated Statistical Information System, approved by Order No DĮ-240 of 16 September 2020 of the Director General of Statistics Lithuania.

8 Release policy
8.1 Release calendar

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


Link to the release calendar

Official Statistics Calendar


Release procedure

Statistical information is published following the Official Statistics Dissemination Policy Guidelines and Statistical Information Preparation and Dissemination Rules (only in Lithuanian).

9 Frequency of dissemination


10 Accessibility and clarity
10.1 News release

Information is published in a news release on rates of change in prices for industrial production sold – on the 7th working day after the end of the reference month.



Lithuania in Figures, Statistical Yearbook of Lithuania. 



Database of Indicators (Economy and finance -> Price indices, changes and prices -> Producer price index, price changes and index weights)


Access to micro data

Microdata are available and provided for scientific purposes according to the provisions set in the Description of Procedures for the Provision of Confidential Statistical Data for Scientific Purposes. More information is available on the Official Statistics Portal, at Data for scientific purposes.

Public data files: users are also provided with opportunity to access public files with statistical data on observation units. More information is available on the Official Statistics Portal, at Public data files.

10.5 Other


Methodological documentation

Price indices, changes and prices

12 Quality management
12.1 Quality assurance

The 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 the areas which need improvement and to promptly eliminate the shortcomings.

12.2 Quality assessment

Statistical results quality is in line with the criteria of accuracy, timeliness and punctuality, compatibility and coherence producer prices in the reference month are compared with the previous month, the corresponding month of the previous year, and December of the previous year. If outliers are obtained, primary statistical price data are once again clarified with enterprises.

Statistical survey managers periodically perform self-assessment – to evaluate statistical survey processes; moreover, statistical questionnaire control testing is performed.

The collection and compilation of statistical information was not affected by COVID-19

13 Relevance
13.1 User needs

The main users are the Bank of Lithuania, Eurostat, state and municipal institutions and agencies, international organisations, the media, business and research communities, students, whose needs are satisfied without a breach of the confidentiality principle.

13.2 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 surveys and their results is available in section User surveys on the Statistics Lithuania website.


Completeness of statistical information

The PPI is published the EVRK Rev.2 section, 2-digit level and by Main Industrial Groupings (MIG) at the national level by markets: all-items, Lithuanian, non Lithuanian, (Euro area, non Euro area).


Data completeness - rate

100 per cent of information produced in accordance with the Official Statistics Programme Part I part I is published.

14 Accuracy and reliability
14.1 Overall accuracy

A purposive sampling method is applied to the selection of product categories (codes). The product categories (codes) at the PGPK 10-digit level are selected. The amount of such industrial production sold accounts for a large part (more than 50 per cent) of production of a corresponding economic activity. The PPI results received are analysed, looking for errors which may affect the final results. Monthly price changes are calculated; closer attention is paid to those producer price changes which are - 10 and -–10 per cent, as well as those prices which changed due to quality, the change of the season. Moreover, special attention is paid to those price changes which had the largest impact on the general change in the PPI.


Sampling error


Non-sampling error


Non-response error

Unit non-response rate

Response rate – 100 per cent.

2020 yr. months
1 2 3 4 5 6 7 8 9 10 11 12

Item non-response rate

Statistical units does not submitted the prices, %

of which

due to seasonality

due to other reasons


































15 Timeliness and punctuality


The PPI is published on the 7th working day after the end of the reference month. When there is no possibility to publish statistical information according to the terms of an approved release calendar, the users are informed in advance by indicating the reason of delay and new date of publication.



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.


Percentage of statistical information released on time

100 per cent

16 Coherence and comparability

Geographical comparability

The PPI can be partly comparable with the PPIs calculated by other EU countries because the provisions of the regulation provided in Point 6.1 apply.


Comparability over time

The calculation of PPIs for mining and quarrying and manufacturing (EVRK Rev. 1.1, sections C and D) was launched in 1992. From 1996, the calculation of PPIs for electricity, gas and water supply (EVRK Rev. 1.1, section E) and a general index for sections C–E was launched. The use of the Laspeyres formula for the calculation of price indices was launched; prices were used VAT and excise excluded. The PPI time series for 1998–2002 have been recalculated. From 2009, Statistics Lithuania has been publishing the PPI and price changes based on a new revision of EVRK (EVRK Rev. 2).


Length of comparable time series

Since January 1998.

17 Coherence

Cross-domain coherence


Internal coherence

Elementary price indices are consistently aggregated to higher-level price indices and all-items PPI according to established procedures.


Response burden

The average time spent by a respondent on the filling in of statistical questionnaire KA-09 (annual) – 2 hour, KA-08 (monthly) – 30 min.


Data revision


Revision policy

The revision policy of Statistics Lithuania is provided in the document General Principles behind the Performance, Analysis and Announcement of Revisions of Statistical Indicators.


Revision practice

Revisions are conducted in accordance with an approved statistical information revision calendar.

The PPI for the reference month may be revised due to the correction of statistical data submitted by enterprises. The PPI the reference month is provisional. In the publication of statistical information for the reference month, PPIs for the reference month are provisional, for the previous month – revised.


Average of the change obtained during the revision

In 2017, the average of the change in both the monthly and the annual PPI stood at 0.1 percentage points.

20 Statistical processing

Statistical data source

Sources of weights – statistical data of the Industry Statistics Division on the amount of industrial production sold in value terms, VAT and excises excluded. Enterprises selected for the survey provide statistical data on prices for industrial products sold on the Lithuanian and non-Lithuanian market on a monthly basis. Such statistical data serve as a basis for the calculation of PPIs and their changes.


Periodicity of statistical data collection



Statistical data collection

Statistical data on the annual sales volume of representative industrial products in value terms are received from a statistical questionnaire KA-09 (annual). The specialists of the Price Statistics Division collect data, perform control and correct the errors detected. The specialists of the regional data preparation divisions of Statistics Lithuania collect statistical data on prices for representative industrial products through statistical questionnaire KA-08 (monthly).

Reporting methods: electronic statistical data preparation and transfer system e-Statistics, by fax, email. Statistical questionnaire (only in Lithuanian)


Statistical data validation

Statistical data control requirements are provided in a survey programming technical specification. Error protocol is formed from the errors detected, which contains error code, error text, error attribute indicating whether the error must be corrected or may be ignored. Errors may be logical and arithmetical; they may have been made by the respondent or during the data entry or processing stages.

To ensure statistical data quality, primary database check is run additionally (secondary editing, statistical data validation).

The error protocol, statistical data completeness and reliability are checked, links between indicators are analysed. Statistical data are corrected according to error types (errors that must be corrected or may be ignored).

20.5 Data compilation

The PPI is calculated from the lowest level, i.e. representative products, to the highest level, i.e. the all-items PPI. In calculating the PPI, the Laspeyres formula is applied. The lowest-level price indices are then aggregated to higher-level price indices according to EVRK Rev. 2 levels: divisions (2-digit level),  sections (1-letter level), all-items PPI, and by Main Industrial Groupings at the national level. Fixed base weights are used for aggregation. PPIs for the reference year are linked to the PPIs for the previous year using a chain-linking method.

 Compilation of the producer price index for industrial production methodology.

20.6 Adjustment

The specialists of the Price Statistics Division are responsible for price adjustment. Primary price data are adjusted because of changes in the quality of representative products. If the quality of the replacement product significantly differs from that of the replaced one, the assessment of the impact of the change in quality on the increase or decrease in the price has to be made, and the price is recalculated. To maintain comparability between the price of the replaced and replacing product, the price of the replaced product in the previous month is adjusted by eliminating the impact of the change in quality. In order to reduce the number of items adjusted in terms of quality, products are grouped into product segments taking into account the purpose of use. Quality adjustment may be done by several methods: expert judgment, option pricing, bridged overlap, quantity adjustment.  Price indices are not seasonally adjusted. Missing prices are estimated.


Comments and other information

Producer Price Index Manual: Theory and Practice, 2004 (ILO, IMF, OECD, UNECE and World Bank);

Handbook on Industrial Producer Price Indices (PPI): Methodologies and Working Papers, 2012;

IMF Special Data Dissemination Standard (SDDS)