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.
Short-term Statistics Department, Industrial and Services Prices Section
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Postal address: H-1525 Budapest P.O.B. 51, Hungary
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
19 June 2025
2.2. Metadata last posted
19 June 2025
2.3. Metadata last update
19 June 2025
3.1. Data description
The purpose of the indicator is to measure the movements of the basic prices of products manufactured in industry at the first stage of sale. To calculate producer price indices, there is a need more specifically external and domestic sales prices. The industrial producer price index is an indicator measuring the monthly changes of sold products produced and the related services provided by producers. It is prepared broken down by non-domestic and domestic markets, by 4, 3 and 2-digit codes of NACE Rev.2 (“TEÁOR’08” in Hungarian), for the whole of industry as well as by main end-use groups (MIGs). The industrial producer price index (PPI) is the weighted average of domestic and non-domestic sales price indices.
ITO (The Hungarian acronym stands for Industrial Product Classification) is a classification by products in compliance with CPA 2008 down to 6-digit level.
3.3. Coverage - sector
The data collection covers Sections B to E38 of NACE Rev.2. Enterprises selected from branches of mining and quarrying, manufacturing, electricity, gas, steam and air conditioning supply, water collection, treatment and supply, and waste collection, treatment and disposal activities; materials recovery.
3.4. Statistical concepts and definitions
As regards the definitions of variables used in practice of the HCSO the Commission Implementing Regulation 2020/1197 is the standard source.
Industrial producer price indices: they reflect price movements of sold products and services produced/performed by enterprises classified into the industry. The indices are calculated by classes of the standard industrial classification of all economic activities (TEÁOR). The producer price indices (PPI) are computed as the weighted average of domestic and non-domestic output price indices at every aggregation level, it does not show the composition changes by destination of sales. The indices are aggregated by two-step Laspeyres weighting.
Price indices of domestic sales: indices calculated by base-year weighting from the net prices of products and services sold within the country. The observed price is a basic price, excluding value added tax and excise duty, and including price supplement belonging to turnover.
Price indices of non-domestic sales: indices calculated by base-year weighting from the prices of products sold in foreign trade directly, by means of consignees or by privity. The observed price is a price at frontier parity converted to HUF by the actual rate of exchange quoted by National Bank of Hungary at fulfilment.
End-use grouping: groups established from 4-digit branches in compliance with requirements of the European Union (MIGs: Main Industrial Groupings) since 2001. Accordingly, 4-digit branches of industry are classified into 3 main and further 4 sub-groups.
PPI is published on the following bases:
Previous month = 100
December of last year = 100
Corresponding period of the previous year = 100
Accumulated from the beginning of the year
Base year (2021) = 100
3.5. Statistical unit
Legal unit (considered as enterprise) and reported unit is also enterprise.
3.6. Statistical population
The target population consists of enterprises included in the industrial area from Section B to E of NACE Rev. 2. The sample of data suppliers reporting price statistics data consist of the representative enterprises of the Groups of NACE irrespective of the size groups regarding the number of employed persons. The number of possible data providers is approximately 9,000 enterprises.
3.7. Reference area
Territory of Hungary. The whole national territory is covered and the activities performed outside the national territory is not considered in this variable.
3.8. Coverage - Time
Data are available from 2000.
3.9. Base period
PPI data are monthly and refer to the base year 2021. The time series for the base year 2021 are calculated back to January 2000. The reference year is the average of the year 2021. The base and reference periods published at national level are the same as those reported to Eurostat.
Index
Month
6.1. Institutional Mandate - legal acts and other agreements
At European level:
Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics
Commission Implementing Regulation 2020/1197 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics (General Implementing Act)
All relevant regulations can be found in the STS section on Eurostat’s website under Statistics / Short-term business statistics / Legislation
Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics.
All data are transmitted monthly to Eurostat via Edamis.
HCSO makes available all the non-confidential data on its Dissemination database website, and according to agreement all non-confident data are transmitted monthly to National Bank of Hungary.
Aggregated PPI data, along with other data, are sent monthly to the OECD by User Relations Department of HCSO.
7.1. Confidentiality - policy
At European level:
Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics
Commission Implementing Regulation 2020/1197 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics. (General Implementing Act)
All relevant regulations can be found in the STS section on Eurostat’s website under Statistics / Short-term business statistics / Legislation
HCSO ensures confidentiality for all the data reported by data providers and the exclusive use of the data for statistical purposes. We disseminate only aggregated data in full compliance with the rules of confidentiality. Individual data, as well as aggregated data consisting of fewer than 3 enterprises are regarded as confidential and therefore not published. Researchers have access to de-identified data sets and to anonymised micro data for scientific purposes with appropriate legal and methodological guaranties in place. As for the employees, they can work with datasets in their competence with registered and controlled access rights. For details see Information on confidentiality for data providers on the website of HCSO.
8.1. Release calendar
All of the features of dissemination activity are consistent with the Dissemination and Communication Policy of Hungarian Central Statistical Office. In the elaboration of this document the
(Since the last update of Dissemination Policy of HCSO a new statistical law has been adopted in Hungary and the European Statistical law has been amended, but the changes do not affect the principals of Dissemination Policy.)
HCSO has a public Dissemination calendar that contains the dissemination dates of all First releases. The public dissemination calendar (Catalogue) on the website of HCSO provided information not only the first releases but the analyses, methodological publications, promotional publications, reports, statistical reflections, yearbooks and pocketbooks. Both calendars are prepared in line with the annual dissemination programme.
8.2. Release calendar access
A public dissemination calendar of the first releases is accessible and it can be downloaded in Excel format by everyone via the website of HCSO. It provides information about publish date, the date of any modification, the title of publication, the reference period or date and the date of inclusion in the database.
8.3. Release policy - user access
The release calendar and the first releases are open for everybody via the website of HCSO. First releases and the related databases are published at 8:30 a. m. on the day provided in the Dissemination calendar. Certain first releases are sent to the members of the government and the president of the National Bank of Hungary at 5 p. m. on the day prior to the publication after closing the Budapest Stock Exchange. Within the given ministry and the National Bank of Hungary responsible use of our data is ensured by strict rules.
Monthly
10.1. Dissemination format - News release
First release about industrial producer price index is published regularly every month. It can be found on HCSO’s website. The publication shows among others
Price indices of domestic and non-domestic output and producer based on the same period of the previous year
Changing of prices concern end-use groups
Industrial producer price index, Export output price index, Domestic manufacturing price index and Domestic electricity, gas, steam and air conditioning supply price index, monthly average of year 2021 = 100
Domestic, Export and Total industrial producer price index, the same period of previous year = 100
10.2. Dissemination format - Publications
There are numerous publications with data of industrial producer price index, for example:
Statistical report: Economy and society is an on-line comprehensive publication every month, contains data about industrial producer price indices
Statistical Pocket-book of Hungary is an annual publication
Statistical Yearbook of Hungary is an annual publication
In HCSO the following four data access channels are available only for researchers for scientific purposes. The HCSO performs a researcher accreditation procedure for all data requests for these four data access channels.
The HCSO offers access to deidentified microdata sets for scientific purposes in the safe environment of the Safe Centre operated by the HCSO in Budapest.
The offers access to deidentified microdata sets for scientific purposes in the safe environment of the remote access points operated by the HCSO under the same access conditions as the Safe Centre access.
For scientific purposes, the HCSO produces the requested research outputs inside its own safe environment based on the specifications/syntax files provided by the researcher.
By using this data access channel, the HCSO provides anonymised microdata sets for the researcher for scientific purposes.
10.5. Dissemination format - other
STADAT (the acronym stands for statistical data), which involves mostly time series can be found on the HCSOs website. STADAT includes plenty of data in pre-made tables about numerous topics, with methodological notes. The tables can be downloaded but the user cannot transform them. (While working with the dissemination database the user can assemble a cross table, elements to the table columns and rows can be added as well as filters can be applied).
Data transmission to Eurostat each month. The transmission is carried out in SDMX format via eDAMIS system. SDMX Converter 4.5.0 version is used for the transformation.
Additional methodological comments can be found in STADAT system and in dissemination database.
10.7. Quality management - documentation
User-oriented quality reports on statistical domains are prepared in the framework of methodological documentation and are published as metainformation on the HCSO website: Methodological documentation .
An internal HCSO regulation is in place regarding the preparation of producer-oriented quality reports for each statistical domain on a yearly basis.
In case of some statistical domains – concerning first releases – quality check is carried out and documented each month for the management of HCSO. However, this report is not published.
11.1. Quality assurance
The HCSO Quality Policy lays out the principles and commitments related to the quality of statistics. The document is consistent with the goals set out in the Mission and Vision statements and with the principles of the European Statistics Code of Practice and is publicly available on the HCSO website.
Quality Guidelines are meant to ensure the quality of the statistical processes. The document has been in place since 2007 (1st revision in 2009, 2nd revision in 2014 and 3rd revision is currently ongoing). The latest version (2014) is available on the HCSO website.
Procedures are in place in order to ensure updated documentation on product quality. (See above about Quality Documentation in 10.7) Apart from the internal reports, quality reports are regularly provided to Eurostat as well.
11.2. Quality management - assessment
Commission Implementing Regulation 2020/1197 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics concerning short term statistics. (General Implementing Act)
The average response rate is 98,7% in 2024, which is outstanding achievement. The content and coverage of collected data meet the requirements. For the accuracy HCSO operates electronic data collection and data entry system in which three-stage data correction system works.
The day of the publication of data is specified in dissemination calendar and the deadline has been always kept. The data transmission to the international organisations has been also done in time.
The wide range of the turnover data is available on the website of HCSO in dissemination databases and in “STADAT” system, as well as First Releases are published regularly on the HSCO’s website.
There are not known serious quality problems in the industrial turnover. HCSO is committed to develop the quality and ensure the credibility of statistics.
12.1. Relevance - User Needs
The concepts and methods are based on European legislation. The most important foreign users are mostly international organisations (e.g. Eurostat, OECD, and UN). The principal domestic users are the National Central Bank of Hungary, Ministries and contracting parties. The production of industry is needed for calculating GDP; therefore, the National Accounts department is the relevant internal user.
12.2. Relevance - User Satisfaction
Not available.
12.3. Completeness
The scope and the level of detail meet the requirements. Due to demands of domestic users and the other departments of HCSO, the coverage is extended E38 divisions of NACE Rev. 2. The time series without break starts form 2009. Historical time series of the 2000-2008 period were recalculated in accordance with this new classification, so the time series can be considered continuous from 2000.
13.1. Accuracy - overall
At the beginning of the sampling procedure HCSO gets in touch with the possible data providers and discuss them about the reporting activity. Because of the regular contact the average response rate is over 97.5%. There is negligible bias because some enterprises goes bankrupt over the given year and their data are estimated till the end of the year if necessary and cannot be deleted from the sample.
No sampling error calculation is made because judgemental sampling is used. In price indices the risks in not having a probability sample are relatively low.
To avoid the other errors, at the beginning of the sampling procedure the statisticians check the data providers by current information from the Registration Court and get in touch with the possible data providers to discuss their reporting activity and the products to be designated.
Another cause of an error (first of all non-sampling error) is that the sample is built up from two-year data.
The data are generally considered to be final at first released, no first estimation and second estimation are made.
Missing responses are requested by telephone/e-mail contacts. If necessary, prices are checked by phone/e-mail with the contact person of the reporting enterprise.
13.2. Sampling error
First the commodities (product groups) are selected in the 4-digit classes by judgmental sampling (the most important groups) then the main producers (enterprises) of the selected commodities, and finally in these enterprises the particular price-representing products by also judgmental selection. Random sampling is not used, but observed sample is revised in each year.
The sample choosing is based on a non-probabilistic sampling method therefore no sampling error, confidence interval or CV is calculated.
The industrial producer price index (PPI) is prepared broken down by non-domestic and domestic markets, by 4, 3 and 2-digit codes of NACE Rev.2 (“TEÁOR’08” in Hungarian), for the whole industry as well as by main end-use groups (MIGs). PPI data are not separated into retail trade or wholesale trade price indices. Sample sizes: more than 5300 product prices were collected from about 1330 enterprises.
Aggregation structure: Commodity indices are aggregated by industry and by end-use as well (EU: Main Industrial Groupings).
13.3. Non-sampling error
In 2024 the coverage of the main aggregates by NACE were:
B: 67.71% (mining and quarrying),
C: 99.32% (manufacturing),
D: 78.54% (electricity, gas, steam, air conditioning),
E: 93.45% (water supply, sewerage, waste management, and remediation activities).
The total coverage was 93.45% in 2024.
The coverage by end-use groups of the producer branches of domestic industry were:
IA: 78.56% (energy and intermediate producer branches),
IB: 98.38% (capital producer branches),
IC: 99.78% (consumer goods producer branches).
The total coverage was: 83.00% in 2024.
No under-coverage is calculated.
Over-coverage: In special cases the branch classification of some data providers is temporarily removed from industry branches.
Multiple listings: There are no multiple listings due to the registration number of the enterprises.
Data are collected by electronic questionnaires. All data arrive via an electronic data collection system (ELEKTRA) and are transferred automatically into Integrated Data Entry and Validation System (ADÉL). The provided data are checked by the responsible specialist statisticians. They can also provide feedback for the data providers, and ask for corrections in case of errors.
Data editing is carried out at the level of elementary indices; if a given elementary index (i.e. the absolute value of the price change compared to the previous month) exceeds a pre-defined value (e.g.: ± 20%) the electronic data processing program automatically warns the expert who is responsible for the specific product.
Owing to the solid contact with data providers average response rate is over 98.7%, except for some special situations (e. g. eliminated company, etc.) basically all data are provided. Weighted unit response rate cannot be calculated because our method does not distinguish data providers. Unweighted unit response rate was between 97.5% and 99.5%, the average was 98.7% in 2024. No item non-response rate is calculated because the ELEKTRA system does not allow data providers to submit data if any record of the questionnaire is empty. Data are checked constantly during the receipt process. If any mistake occurs, the respondent is asked to fix it, therefore editing and imputation errors are negligible. If the enterprise is under bankruptcy or liquidation proceedings and cannot provide prices for the given month, the last month price data are imputed (in non-domestic direction this is adjusted by the average exchange rate changes of the actual month). The number of imputed questionnaires for 2024 were between 7 and 32, the average was 16. The average imputation rate is 1.3%.
Models are not used. No modelling errors are calculated.
14.1. Timeliness
Data of index of industrial producer price are published not later than 30 days after the end of the reference month following the EBS regulation.
14.2. Punctuality
The publications agree with the dissemination calendar. There are no time lags.
15.1. Comparability - geographical
Over the data collection and calculation domestic and non-domestic markets are interpreted according to territory of Hungary. The whole country is treated in a uniform manner in statistical point of view. The same statistical concepts can be applied all of the territory. All data sources coverage fully the regions. There are no difficulties concerning the geographical comparability.
15.2. Comparability - over time
The time series of PPI were continuous from 1999, when “TEÁOR’98” (which fully conforms to NACE Rev.1) was introduced, until the end of 2008. After the introduction of “TEÁOR’98” the time series remained comparable at 2-digit and higher levels from 1992 but there are some discrepancies between the nomenclatures at 3- and 4-digit levels. In order to compute long time series annually re-weighted price indices are linked together without any adjustment; otherwise said chain indices are calculated. Since 2009 the index calculation has been based on “TEÁOR’08”, which conforms to NACE Rev.2. Historical time series of the 2000-2008 period were recalculated in accordance with this new classification, so the time series can be considered continuous from 2000. The change in the base year 2015 and then 2021 did not affect the comparability of the data, because the indices were recalculated for the base year 2015 and in 2024 for the base year 2021 up to January 2000.
15.3. Coherence - cross domain
The non-domestic output price index is occasionally compared with the export-import price index (XMPI) and the indicators of exchange rate movements of HUF in the reference period. These indices examine similar price movements but from different points of view (e.g. they are calculated according to different nomenclatures and for different purposes). Comparison between them is practically limited: for the calculation of the XMPI individual price surveys are made of products sold on different export markets even if the sold products are the same. In case of the PPI the main purpose of observing non-domestic output price is to observe the position of Hungarian producers in external markets, therefore the PPI survey takes into account the average price of identical products even if they are sold in different countries. Methodology to calculate an exact and precise comparison is not available for now.
15.4. Coherence - internal
Commodity indices are aggregated by industry by 4, 3 and 2-digit codes of NACE Rev.2 (TEÁOR’08 in Hungarian), and by main end-use groups as well (Main Industrial Groupings (MIGs)). Motion of these aggregates are comparable considering that although related aggregates move together in tendency, but their rate can be different because of distinct composition.
Cost (NSI hours per year in 2024): 7866
Burden (Respondents hours per year in 2024): 9713
17.1. Data revision - policy
A revision in official statistics is defined as any change in a value of a statistic released to the public. The fundamental aim of revision is to improve data quality and thereby to be more accurate when reflecting the reality.
HCSO published its renewed revision policy in 2018. The revision policy is in line with the following conceptual frameworks:
finally, the HCSO takes into consideration the deadlines of mandatory international data transmissions and publication
HCSO considers any change in the value of already published data as data revision. Revisions take place for a number of distinct reasons, which tend to break into four groups:
incorporation of better source data (e.g. replacement of first/provisional estimates based on expert judgements, or as a result of benchmarking)
capturing routine recalculations (e.g. updating the base period)
reflection of improved methodology (e.g. changes in concepts, definitions or classifications)
correction of errors
Consider the various causes of revisions and the different frequencies of publications, the HCSO – in correspondence with international guidelines – distinguishes the following types of revisions:
Routine revisions: routine revisions are changes in published data which are related to the regular statistical business process. Routine revisions mainly occur when the incorporation of late information (new or the correction of already obtained) modifies the already published results or in the case of benchmarking. Routine revisions are conducted periodically, according to a schedule drawn up in advance. With some sets of statistics (e.g. in foreign trade), a number of revisions are needed to obtain final results, while in other cases the provisional results are replaced by final data in the course of one single revision. Routine revisions barely affect the applied methodology, and only a few periods (some months or quarters) back in time are revised and longer revisions take place at a lower frequency, e.g. annually.
Major/methodological revisions: Major revisions are changes in published data, often substantial, which are due to changes in definitions, classifications and methodologies. Updating of the weights of the base year of an index series, the availability of a new structural source that is only collected at long intervals (5 to 10 years), such as the census, and the entry into force of a new legal act may also cause major revisions.
Major revisions are planned very well in advance and users are informed beforehand on the forthcoming major revisions. They are less frequent than routine revisions and occur only every 5 to 10 years. Since major revisions affect a large part of the time series and sometimes even the complete time series, it is necessary to backcast time series, otherwise major revisions would produce breaks and inconsistencies in them.
Unplanned revisions: Unplanned or unscheduled revisions are those that are not foreseen (as opposed to planned revisions), because they are a result of unforeseeable events and therefore it is usually not possible to pre-announced them in advance. As unscheduled revisions can undermine confidence in the quality of official statistics, HCSO is committed to avoiding as much as possible unscheduled revisions and to limit them to the case of important errors (whose correction results in significant improvement regarding data quality). Unscheduled revisions are communicated to the users in a transparent manner.
HCSO makes its general and domain specific revision policies publicly available on its official website. HCSO applies the general policy’s principles to all of its statistics (including the STS data transmitted to the Eurostat). Although subject matter statistics may have specificities regarding their revision practices, they have to be fully compliant with the general principles.
HCSO notifies users about forthcoming revisions in time and indicates their date and time in the revision calendar.
17.2. Data revision - practice
Planned revision
There are no estimated or first released data. Data are released once for a period, these are definitive data. For this reason, MAR, RMAR or MR indicators cannot be calculated, so MAR = 0 RMAR= 0 and MR = 0. They are revised subsequently in exceptional cases only. There are no routine revision or revision calendar.
We perform larger revision in case of change in the nomenclatures used for the calculation of industrial producer price index (“TEÁOR”, “ITO”). The last grand revision took place in 2008 when “TEÁOR” and “ITO” changed. Since 2009, product classification is based on “ITO”, industrial classification is based on “TEÁOR’08”. Previous periods of 2000 were recalculated in accordance with “TEÁOR’08” classification, so the time series can be considered continuous from 2000. The next scheduled revision is expected in 2028 because of change to “TEÁOR’25” classification. This revision will expectedly affect the whole statistical domain. These major revisions do not cause time series breaks, because data are recalculated back until the date specified by law.
There is no benchmarking done with other statistics because of the differences in methodology.
Unplanned revisions:
Unplanned data revisions would only occur in exceptional cases, namely if an unforeseen event (data error, technical problem, etc.) necessitates a revision of the data. In that special case aggregates and components revised at the same time. Revised data are published on the KSH website with an attention note and resent to the necessary bodies (Eurostat, MNB). There was no non-scheduled revision last year in this statistical domain.
The revision practice has not been changed for a long time.
18.1. Source data
The scope of data suppliers reporting price statistics data is representative and independent of size groups regarding the number of employed persons. The data collection covers enterprises selected from branches of mining and quarrying, manufacturing, electricity, gas, steam and air conditioning supply, water collection, treatment and supply, and waste collection, treatment and disposal activities; materials recovery. In the ‘Monthly price survey of industrial products and services’ (questionnaire No. 1007) those economic units are observed which, according to the ’Annual production survey’ (questionnaire No. 1039) referring to two years prior to the reference year, had significant annual sales in the product groups dominating the total production value of the given section. The observed sample is revised in each year.
18.2. Frequency of data collection
Monthly
18.3. Data collection
Data collection is based on an online survey. The designing of the questionnaire including the set of control rules is the job of the statisticians, and the checking of the operation happens in close cooperation with IT department at the end of the previous year. The IT system sends an e-mail to data providers if a new questionnaire becomes accessible, or the deadline has expired. In case of non-response:
re-contact by phone
sending a warning message
fine as a final tool.
18.4. Data validation
Before data publication and transmission some indices are chosen at random. They are recalculated not only with the index computing software, but also with other tools. The values are compared. The total index has to be between the domestic and the non-domestic index, this is checked for every record. The data are transformed into SDMX form by SDMX Converter 4.5.0 program. Therefore, the validation takes into consideration the format and file structure (validation level 0) and inter-dataset checking happens (validation level 1).
18.5. Data compilation
For missing price observations in the reference month, the prices of the previous month are carried forward: in case of domestic sales the latest prices reported at the moment of sale; in case of non-domestic sales the latest sales prices corrected by the monthly average change of the exchange rate of HUF.
If the price change of a surveyed product is caused by quality change, then the product is considered to be a new product from the point of view of the price index calculation. To replace a product within a product group is possible in any month since no weights are used within the product group.
If a product is ceased to be produced then an appropriate replacement item is selected with the most similar specifications in terms of raw materials used for its production, construction, quality, technology, etc. The price for the new product selected to replace the product that drops out of production is first requested in the month when the respondent could supply price data for the product that falls out of production last time.
Data editing is carried out exclusively at the level of elementary indices, i.e. for prices of the surveyed products. If a given elementary index (i.e. the absolute value of the price change compared to the previous month) exceeds a pre-defined value (e.g.: ±20%), the electronic data processing programme automatically warns the expert who is responsible for that given product. Collected prices are also compared to the series of the prices of the same variety in the last 3-4 months. If necessary, reporting enterprises are contacted by phone to find out whether a real price change occurred in the reference period or some quality changes caused the price movement.
As a first step the computation of price relatives takes place by representative items for the reference month. Then the indices of commodity groups are determined as the arithmetical means of price relatives of the representative items, and the price indices of 4-digit branches are computed as the weighted arithmetical means of price indices of the commodity groups. Weights refer to the annual sales of industrial products and services of each commodity group in the year two years prior to the reference year in the respective sales direction. Weights are changed every year.
The PPI is the weighted average of the domestic and non-domestic price indices, it does not show the composition changes by destination of sales. The source of weights is the ‘Annual survey of industrial products’. The indices are aggregated by a two-step Laspeyres weighting.
The basic method used for the index calculation is Laspeyres with one-month overlap chain-linking method.
18.6. Adjustment
Data are not adjusted.
No further comments.
The purpose of the indicator is to measure the movements of the basic prices of products manufactured in industry at the first stage of sale. To calculate producer price indices, there is a need more specifically external and domestic sales prices. The industrial producer price index is an indicator measuring the monthly changes of sold products produced and the related services provided by producers. It is prepared broken down by non-domestic and domestic markets, by 4, 3 and 2-digit codes of NACE Rev.2 (“TEÁOR’08” in Hungarian), for the whole of industry as well as by main end-use groups (MIGs). The industrial producer price index (PPI) is the weighted average of domestic and non-domestic sales price indices.
19 June 2025
As regards the definitions of variables used in practice of the HCSO the Commission Implementing Regulation 2020/1197 is the standard source.
Industrial producer price indices: they reflect price movements of sold products and services produced/performed by enterprises classified into the industry. The indices are calculated by classes of the standard industrial classification of all economic activities (TEÁOR). The producer price indices (PPI) are computed as the weighted average of domestic and non-domestic output price indices at every aggregation level, it does not show the composition changes by destination of sales. The indices are aggregated by two-step Laspeyres weighting.
Price indices of domestic sales: indices calculated by base-year weighting from the net prices of products and services sold within the country. The observed price is a basic price, excluding value added tax and excise duty, and including price supplement belonging to turnover.
Price indices of non-domestic sales: indices calculated by base-year weighting from the prices of products sold in foreign trade directly, by means of consignees or by privity. The observed price is a price at frontier parity converted to HUF by the actual rate of exchange quoted by National Bank of Hungary at fulfilment.
End-use grouping: groups established from 4-digit branches in compliance with requirements of the European Union (MIGs: Main Industrial Groupings) since 2001. Accordingly, 4-digit branches of industry are classified into 3 main and further 4 sub-groups.
PPI is published on the following bases:
Previous month = 100
December of last year = 100
Corresponding period of the previous year = 100
Accumulated from the beginning of the year
Base year (2021) = 100
Legal unit (considered as enterprise) and reported unit is also enterprise.
The target population consists of enterprises included in the industrial area from Section B to E of NACE Rev. 2. The sample of data suppliers reporting price statistics data consist of the representative enterprises of the Groups of NACE irrespective of the size groups regarding the number of employed persons. The number of possible data providers is approximately 9,000 enterprises.
Territory of Hungary. The whole national territory is covered and the activities performed outside the national territory is not considered in this variable.
Month
At the beginning of the sampling procedure HCSO gets in touch with the possible data providers and discuss them about the reporting activity. Because of the regular contact the average response rate is over 97.5%. There is negligible bias because some enterprises goes bankrupt over the given year and their data are estimated till the end of the year if necessary and cannot be deleted from the sample.
No sampling error calculation is made because judgemental sampling is used. In price indices the risks in not having a probability sample are relatively low.
To avoid the other errors, at the beginning of the sampling procedure the statisticians check the data providers by current information from the Registration Court and get in touch with the possible data providers to discuss their reporting activity and the products to be designated.
Another cause of an error (first of all non-sampling error) is that the sample is built up from two-year data.
The data are generally considered to be final at first released, no first estimation and second estimation are made.
Missing responses are requested by telephone/e-mail contacts. If necessary, prices are checked by phone/e-mail with the contact person of the reporting enterprise.
Index
For missing price observations in the reference month, the prices of the previous month are carried forward: in case of domestic sales the latest prices reported at the moment of sale; in case of non-domestic sales the latest sales prices corrected by the monthly average change of the exchange rate of HUF.
If the price change of a surveyed product is caused by quality change, then the product is considered to be a new product from the point of view of the price index calculation. To replace a product within a product group is possible in any month since no weights are used within the product group.
If a product is ceased to be produced then an appropriate replacement item is selected with the most similar specifications in terms of raw materials used for its production, construction, quality, technology, etc. The price for the new product selected to replace the product that drops out of production is first requested in the month when the respondent could supply price data for the product that falls out of production last time.
Data editing is carried out exclusively at the level of elementary indices, i.e. for prices of the surveyed products. If a given elementary index (i.e. the absolute value of the price change compared to the previous month) exceeds a pre-defined value (e.g.: ±20%), the electronic data processing programme automatically warns the expert who is responsible for that given product. Collected prices are also compared to the series of the prices of the same variety in the last 3-4 months. If necessary, reporting enterprises are contacted by phone to find out whether a real price change occurred in the reference period or some quality changes caused the price movement.
As a first step the computation of price relatives takes place by representative items for the reference month. Then the indices of commodity groups are determined as the arithmetical means of price relatives of the representative items, and the price indices of 4-digit branches are computed as the weighted arithmetical means of price indices of the commodity groups. Weights refer to the annual sales of industrial products and services of each commodity group in the year two years prior to the reference year in the respective sales direction. Weights are changed every year.
The PPI is the weighted average of the domestic and non-domestic price indices, it does not show the composition changes by destination of sales. The source of weights is the ‘Annual survey of industrial products’. The indices are aggregated by a two-step Laspeyres weighting.
The basic method used for the index calculation is Laspeyres with one-month overlap chain-linking method.
The scope of data suppliers reporting price statistics data is representative and independent of size groups regarding the number of employed persons. The data collection covers enterprises selected from branches of mining and quarrying, manufacturing, electricity, gas, steam and air conditioning supply, water collection, treatment and supply, and waste collection, treatment and disposal activities; materials recovery. In the ‘Monthly price survey of industrial products and services’ (questionnaire No. 1007) those economic units are observed which, according to the ’Annual production survey’ (questionnaire No. 1039) referring to two years prior to the reference year, had significant annual sales in the product groups dominating the total production value of the given section. The observed sample is revised in each year.
Monthly
Data of index of industrial producer price are published not later than 30 days after the end of the reference month following the EBS regulation.
Over the data collection and calculation domestic and non-domestic markets are interpreted according to territory of Hungary. The whole country is treated in a uniform manner in statistical point of view. The same statistical concepts can be applied all of the territory. All data sources coverage fully the regions. There are no difficulties concerning the geographical comparability.
The time series of PPI were continuous from 1999, when “TEÁOR’98” (which fully conforms to NACE Rev.1) was introduced, until the end of 2008. After the introduction of “TEÁOR’98” the time series remained comparable at 2-digit and higher levels from 1992 but there are some discrepancies between the nomenclatures at 3- and 4-digit levels. In order to compute long time series annually re-weighted price indices are linked together without any adjustment; otherwise said chain indices are calculated. Since 2009 the index calculation has been based on “TEÁOR’08”, which conforms to NACE Rev.2. Historical time series of the 2000-2008 period were recalculated in accordance with this new classification, so the time series can be considered continuous from 2000. The change in the base year 2015 and then 2021 did not affect the comparability of the data, because the indices were recalculated for the base year 2015 and in 2024 for the base year 2021 up to January 2000.
