Harmonised index of consumer prices (HICP) (prc_hicp)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Statistical Office of the Republic of Slovenia — SURS

Time Dimension: 2020-A0

Data Provider: SI1

Data Flow: HICP_NES_A

Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)

For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT


1. Contact Top
1.1. Contact organisation

Statistical Office of the Republic of Slovenia — SURS

1.2. Contact organisation unit

Price Statistics Section, webpage


1.5. Contact mail address

Statistical Office of the Republic of Slovenia

Litostrojska cesta 54
SI-1000 Ljubljana

2. Metadata update Top
2.1. Metadata last certified 31/07/2020
2.2. Metadata last posted 31/07/2020
2.3. Metadata last update 31/07/2020

3. Statistical presentation Top
3.1. Data description

The harmonised index of consumer prices (HICP) is a consumer price index (CPI) that is calculated according to a common approach. It measures the change over time of the prices of consumer goods and services acquired by households. Because of the common methodology, the HICPs of the countries and European aggregates can be directly compared.

3.2. Classification system

European classification of individual consumption according to purpose (ECOICOP)

3.3. Coverage - sector

The HICP covers the final monetary consumption expenditure of the household sector.

3.4. Statistical concepts and definitions

The main statistical variables are price indices.

3.5. Statistical unit

The basic unit of statistical observation are prices for consumer products.

3.6. Statistical population

3.6.1. Statistical target population

The target statistical universe is the 'household final monetary consumption expenditure' (HFMCE) on the economic territory of the country by both resident and non-resident households... The household sector to which the definition refers includes all individuals or groups of individuals irrespective of, in particular, the type of area in which they live, their position in the income distribution and their nationality or residence status. These definitions follow the national accounts concepts in the European System of Accounts.

3.6.2. Coverage error population

There are no deviations from the target population.

3.7. Reference area

3.7.1. Geographical coverage

The HICP refers to the economic territory of a Member State as defined by ESA2010.

3.7.2. Coverage error regions

The economic territory of Slovenia is the same as the geographic territory on which Slovenian government institutions conduct administrative control. The HICP covers the entire area of the country.

3.8. Coverage - Time

3.8.1. Start of time series

In accordance with Council Regulation (EC) No 1687/98, each Member State is required to produce a harmonised index of consumer prices (HICP) starting in January 1997.

3.8.2. Start of time series - national specifics

 The production of HICP started in 2001. From 1997 to 2000, the data for CPI and HICP are considered as equal.

 See the HICP database

3.9. Base period


4. Unit of measure Top

The following units are used:

  • Index point
  • Percentage change on the same period of the previous year (rates);
  • Percentage change on the previous period (rates);
  • Percentage share of the total (weights).

5. Reference Period Top

HICP is a monthly statistics.

6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

Harmonised Indices of Consumer Prices (HICPs) are harmonised inflation figures required under the Treaty on the Functioning of the European Union. Council Regulation (EC) No 2016/792 of 11 May 2016 (OJ L 135) sets the legal basis for establishing a harmonised methodology for the compilation of the HICP, the MUICP and the EICP.
The Commission has brought forward detailed Regulations establishing the specific rules governing the production of harmonised indices.


  • Initial implementing measures (1749/1996)
  • Sub-indices (2214/1996)
  • Weights (2454/1997)-repealed
  • Coverage of goods and services (1687/1998)
  • Geographic and population coverage (1688/1998)
  • Treatment of tariffs (2646/1998)
  • Treatment of insurance (1617/1999)
  • Revised sub-indices (1749/1999)
  • Treatment of products in the health, education and social protection sectors (2166/1999)
  • Timing of entering purchaser prices (2601/2000)
  • Treatment of price reductions (2602/2000)
  • Treatment of service charges (1920/2001)
  • Minimum standards for revisions (1921/2001)
  • Common index reference period (1708/2005)
  • Temporal coverage of price collection (701/2006)
  • Sampling (1334/2007)
  • Seasonal products (330/2009)
  • Weights (1114/2010)
  • Owner-occupied housing (93/2013)
  • Common index reference period (2015/2010)


All relevant regulations as well as further methodological details can be found in the HICP section on Eurostat's website under Methodology => Legislation.

6.2. Institutional Mandate - data sharing

Data are sent to Eurostat via eDAMIS following a predetermined timetable.

7. Confidentiality Top
7.1. Confidentiality - policy

The legal basis for confidentiality treatment is based on Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on the transmission of data subject to statistical confidentiality to the Statistical Office of the European Communities and the National Statistics Act (OJ RS, No. 45/95 and 9/2001).

The National Statistics Act (hereinafter the ZDSta) stipulates within fundamental principles of national statistics in Article 2 that “national statistics shall be implemented on the principles of … confidentiality …”. The principle is concretised in further provisions of the ZDSta, while for explanation one can turn to some international documents. The United Nations Resolution on Fundamental Principles of Official Statistics (adopted by the UN Statistical Commission in 1994 and confirmed by the UN General Assembly on 29 January 2014) determines in Principle 6 that “individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes”. The explanation of the resolution is that reliable official statistics is based on the trust of the public and its good will to provide timely and accurate data that are requested. Such cooperation is only possible if statistical confidentiality is respected. In a similar way this principle is concretised in the European Statitstics Code of Practice (adopted by the European Statistical System Committee on 28 September 2011), which determines that “the privacy of data providers (households, enterprises, administrations and other respondents), the confidentiality of the information they provide and its use only for statistical purposes must be absolutely guaranteed“. And last but not least, item (e) of Article 2 of Regulation (EC) No. 223/2009 on European Statistics determines statistical confidentiality as “the protection of confidential data related to single statistical units which are obtained directly for statistical purposes or indirectly from administrative or other sources and implying the prohibition of use for non-statistical purposes of the data obtained and of their unlawful disclosure”. 

Statistical confidentiality as determined above is thus provided with the help of various legal, organisational and technological procedures that can be summarised in the following points:

  • Security of data and information
  • Use of data exclusively for statistical purposes
  • Statistical protection of the data transmitted to users
  • Secure management of data for research purposes
  • Educating and informing the employees about statistical confidentiality
7.2. Confidentiality - data treatment

Only indices where there is no confidentiality issue are published (at the Ecoicop level) and the average annual retail prices for some products and services. Confidential data are data at the level of each unit, the data on item weights and the most detailed descriptions of products and services.

8. Release policy Top

In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see point 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.

8.1. Release calendar

The release calendar is publicly available and published at the end of the year for the entire coming year.

The release of the HICP follows a preannounced calendar (which is the same as for the CPI). The all-items HICP and detailed HICPs (for 12 main ECOICOP groups) are available and first released on the last working day of the month to which they relate in a special publication called 'First Release' and at the same time data are also announced at a press conference. Later, within one week, data are transmitted to Eurostat.


8.2. Release calendar access

First data are published in accordance with the release calendar as First Release at 10:30 (local time) on the day of release.

SURS's advance release calendar is available on the website and can also be subscribed via email or RSS.

8.3. Release policy - user access

The release policy is oriented towards wide public. The release dates are published in advance and are listed in a release calendar. Besides the release calendar, informing public about dates of data releases, SURS also prepares press conferences (invitations are sent to journalists), usually on the day of the release of data on monthly inflation, i.e. on the last working day in the month. In addition to regular press conferences, SURS also organises additional press conferences on special events or releases of important analyses of statistical data. On the other hand, all subscribers to the news are informed about the release a week prior the data release.

There is no special or pre-access to data.

Statistical data can be obtained on Statistical Office's web pages: Prices and Inflation, and also via mail, phone, fax and e-mail, by ordering statistical publications and by visiting the Information Centre during office hours.

9. Frequency of dissemination Top


10. Accessibility and clarity Top

Harmonised consumer price indices are produced monthly. Dissemination policy and practice:

  • Electronic dissemination

- monthly: through E-mail, Twitter, RSS and via Edamis, users may also subscribe for automatic receiving of alert when a First Release is released,

- annually: Stat’o’book (Statistical overview of Slovenia).

  •  Paper dissemination

                - Stat’o’book and occasional publications such as Prices in Slovenia (published in 2012).

Dissemination languages are Slovenian and English.

10.1. Dissemination format - News release

Publication dates for CPI/HICP are set forth in advance. HICP data are just a small part of a news release, where the all-items HICP and detailed HICPs (for 12 main ECOICOP Divisions, plus special aggregates goods and services) are available to the public. The focus of the news release is on CPI.

10.2. Dissemination format - Publications

Data on HICP are a part of First release of Consumer price indices and of some other publications.


10.3. Dissemination format - online database

HICP database are available on http://ec.europa.eu/eurostat/web/hicp/data/database.

10.4. Dissemination format - microdata access

Micro-data are not disseminated.

SURS grants special access (i.e. access to microdata) mostly to researchers and institutions, but strictly on the basis of a special protocol: http://www.stat.si/StatWeb/en/StaticPages/Index/For-Researchers.

10.5. Dissemination format - other

Non applicable.

10.6. Documentation on methodology

The HICP Methodological Manual provides the reference methodology for the production of HICP. (https://ec.europa.eu/eurostat/web/products-manuals-and-guidelines/-/KS-GQ-17-015)

10.6.1. Documentation on methodology - national specifics

A description of the methodology and sources used to compile the HICP are published on Statistical Office's website: www.stat.si/StatWeb/ under the Methodology tab.

This document is updated and published in February each year and refers to the current year.

10.7. Quality management - documentation

Annual quality reports for the survey CPI and HICP are available on https://www.stat.si/StatWeb/File/DocSysFile/9991


11. Quality management Top

European statistics code of practice: http://ec.europa.eu/eurostat/web/quality/european-statistics-code-of-practice

11.1. Quality assurance

11.1.1. Quality management - Compliance Monitoring

Compliance Monitoring

11.1.2. Quality assurance - national specifics

Guidelines for quality assurance were updated in 2017. They are divided into eight fields: analysis of needs and requests, survey design and preparation, selection of observation units, data collection, data processing, data analysis, data dissemination, and documentation and evaluation of surveys. These Guidelines stand for all SURS’s Divisions, including HICP.

Annual quality report and standard quality reports for the CPI and HICP survey are published on our website (only annual reports are available in English).

In a case of deviations data are checked manually. We have contacts with price collectors on regular basis.  In addition, each collector’s work is supposed to be checked in the field 1-2 times per year to ensure that central office guidance is being followed. Many stages of the production process are automated in order to reduce human error. In case the price controller decides that price collector’s explanation is not enough, it is demanded of the price collector to check eg. the price again and report it to the section.

11.2. Quality management - assessment

11.2.1. Compliance monitoring - last report and main results

Compliance Monitoring

11.2.2. Quality assessment - national specifics

HICP indices are produced in compliance with HICP methodological requirements and standards. The HICP process is still being developed (new data sources and related adaptation of methodology).

12. Relevance Top
12.1. Relevance - User Needs

In addition to being a general measure of inflation, the HICP is also used in the areas of:

  • wages, social benefit and contract indexation;
  • economic forecasting and analysis;
  • measuring specific price trends;
  • accounting purposes and deflating other series;
  • inflation targeting by central banks;
  • cross-country economic comparisons.


The euro area (evolving composition) index is used by the European Central Bank (ECB) as the main indicator for monetary policy management. The ECB and the European Commission's Directorate-General for Economic and Financial Affairs (DG ECFIN) use the HICP for assessing price stability and price convergence required for entry into European Monetary Union.

Other users include: National Central Banks, financial institutions, economic analysts, the media and the public at large.

12.1.1. User Needs - national specifics

HICP is a general measure of inflation in cross-country economic comparisons, used mostly by financial institutions for monetary policy (ECB, National Bank, etc.), European and international organisations (Eurostat, IMF, OECD, ILO), the national government, ministries, agencies, many sections within SURS, media, news agencies, enterprises and public as well.

12.2. Relevance - User Satisfaction

Systematic information on user satisfaction is not available. User satisfaction is measured indirectly through numerous e-mail and telephone requests for HICP data, even though the SURS website is the main dissemination channel.

Users' opinions and needs are also monitored by the exchange of views within the Price Statistics Advisory Committee. The principle users are asked about their needs, wishes and interests at the regular meetings.

Board of users is represented in the advisory committee. The Statistical Advisory Committee (for prices) is composed of outside members and SURS members. The outside members are representatives of relevant ministries, Bank of Slovenia, IER (Institute for Economic Research), FURS (Financial Administration of the Republic of Slovenia), ZPS (Slovene Consumers' Association), GURS (Surveying and Mapping Authority of the Republic of Slovenia), the Slovenian Chamber of Commerce, the EIPF Economic Institute, UMAR Institute of Macroeconomic Analysis and Development, the Faculty of Economics Ljubljana and Maribor, ZSSS (the Association of Free Trade Unions of Slovenia), ZDS (Association of Employers of Slovenia) and others.

Meetings are held every year and a half. All users of our data are invited. Its instructions are not strictly binding, but statistical advisory committees have a significant impact on the development of national statistics in Slovenia at expert level and in cooperation of institutions in common efforts to provide quality, timely and relevant statistics.  We often ask their opinion on cancellation of individual surveys and major revisions. We inform them about all major methodological changes we are planning to perform.

In addition, there is the Methodological Council, which is meant for professional discussion of outstanding issues, methodological changes, carrying out surveys, strategy, etc., and it consists of experts from various fields. For major changes proper material must be prepared and Council’s guidelines, recommendations and conclusions are binding.


12.3. Completeness

All statistics that are required by international standards are calculated. HICP covers all the groups and subgroups of the ECOICOP classification whose share in total consumption is greater than 0.1%. Indices at the 5-digit level are produced.

13. Accuracy Top
13.1. Accuracy - overall

The accuracy of source data is monitored by assessing the methodological soundness of price and weight sources and the adherence to the methodological recommendations. The goods and services selected for the basket are those that are most important to the customers; have a significant share in total consumption; best reflect the changes of prices of related products. All methodology recommendations are taken into account. Prices are collected in outlets, craftsmen, supermarkets, etc., in four big cities in the country and some other cities, some of them also via the internet and by phone. They reflect the price situation for the whole country. Scanner Data (for the first two ECOICOP Divisions) are obtained from the biggest supermarket chains (covering the whole country).

Weights are based on the data from NA on the structure of household final consumption expenditure.

The outlets from which prices are collected are chosen to represent the existing trade and service network and are based usually on the following criteria: turnover, representativeness and coverage of availability of goods and services included in HICP's basket. Scaner Data are gained from the biggest supermarket chains in the country.  

Private households are included irrespective of their income. The domestic concept is in force.

13.2. Sampling error

The survey is not based on a random sample, so we can not use the "classic" approaches to assess the sampling error. The methodology for calculating the precision of consumer price indices is not yet completely developed because of the complexity of sample design.

13.3. Non-sampling error

Non-sampling errors are not quantified.


SURS tries to reduce non-sampling errors through continuous methodological improvements and survey process improvements.

- Survey data: a new data collection application running on PC tablets for survey data was introduced (2016), meaning less possibility of input errors.

- Scanner data: SURS’s application META SOP (SAS) for logic controls and data management is in force as well as visual inspection of indices (2018).

14. Timeliness and punctuality Top
14.1. Timeliness

The full set of HICPs is published each month according to a pre-announced schedule, usually between 15 and 18 days after the end of the reference month. Each year, the January news release is published at the end of February to allow for the annual update of the weights of individual product groups and the relative country weights of Members States in the country-group aggregates.

The euro area flash estimate is published on the last working day of the reference month or shortly after that.

14.2. Punctuality

Since the March 1997, launch of the HICP release, the HICP for the country groups aggregates has always been published on the pre-announced release dates.

15. Coherence and comparability Top
15.1. Comparability - geographical

HICPs across Member States are comparable. Any differences at all levels of detail should only reflect differences in price changes or expenditure patterns.

To this end, definitions and classifications have been harmonised in a series of legal acts. The HICP is produced according to these minimum standards that may be applied with some flexibility as long as they result in an index that is estimated to differ systematically by less than or equal to 0.1 percentage points on average over one year against the previous year from an index compiled following the minimum standards (Article 4 of Council and Parliament Regulation (EU) 2016/792).

15.2. Comparability - over time

HICP data are fully comparable over time. There have been several improvements in methodology since the HICP was introduced with the aim of improving reliability and comparability of the HICP.

There were no breaks in the HICP series despite some significant changes, such as New seasonal regulation (in 2011), Ecoicop classification (in 2017) and Scaner Data (in 2018).

15.3. Coherence - cross domain

There are no considerable differences between CPI and HICP, except that HICP is based on the domestic concept of consumption, while national CPI is based on the national concept of consumption. This difference between the two is in weights.

Annual CPI and HICP indices by months, 2019


CPI 101,1 101,2 101,6 101,7 101,4 101,8 102,0 102,3 101,7 101,4 101,4 101,8 101,6
HICP 101,2 101,3 101,6 101,8 101,6 101,9 102,0 102,4 101,7 101,5 101,4 102 101,7
15.4. Coherence - internal

The HICPs are internally coherent. Higher level aggregations are derived from detailed indices according to well-defined procedures.

16. Cost and Burden Top

Not available

17. Data revision Top
17.1. Data revision - policy

The HICP series, including back data, is revisable at any point in time under the terms set in Commission Regulation (EC) No 1921/2001 of 28 September 2001. The published HICP data may be revised for corrections, and new or improved information.

17.1.1. Data revision - policy - national specifics

Methodological explanation on revision of statistical data is available on http://www.stat.si/dokument/5299/RevisionOfStatisticalDataMEgeneral.pdf

Major changes in methodology are announced in advance, while information on minor methodological changes is provided in methodological explanations and on Statistical Office's website ttp://www.stat.si/StatWeb/en/home.

17.2. Data revision - practice

In general, monthly indices are not subject to revision. The data are final when first released and if subsequently an error is found, a correction of the First Release is made and users are informed. At the same time, if necessary, the corrected data are transmitted to Eurostat. 

There were two unplanned revisions (June 2013 and December 2019). The main reason were mistakes discovered subsequently (an error at input data-human error) which had an impact on lower Ecoicop levels and on Total Index as well. When discovered, the entered data were corrected, indices recalculated and the First Release revised. There were no impact on previously published figures.


18. Statistical processing Top
18.1. Source data

18.1.1. Weights

Weights used for index calculation in an individual year are based on national accounts data on household final consumption expenditure. These data are checked and updated with data from other statistical and non-statistical sources. The main source for calculating weights is national accounts data (t-2) which are the basis for determining weights at 2nd, 3rd, 4th  and in some cases at 5-digit sub-class ECOICOP level, while for lower levels mostly data collected with the household budget surveys (HBS) are used. Weights are changed every year. All weights are reviewed (sublevels included) every year and updated when required. Compilation at elementary aggregate level

Below the level of ECOICOP class we use detailed weights to aggregate item indices to ECOICOP classes. Within item indices we use either regional stratum weights for locally collected items or regional and/or provider/supplier stratum weights for centrally collected items. This applies to ECOICOP 03-12. For food, beverages and tobacco (ECOICOP 01 and 02) at elementary aggregate levels weights are based on the ratio of retailers’ turnover (t-1). The lowest level with explicit weights is the unofficial COICOP 6-digit level (elementary aggregate), eg. Telecom operators, Financial services, Retailers’ Scanner data on turnover.

For some groups, weights are additionally checked with data from other sources (energy, trade) and, if necessary, corrected (alcoholic beverages, tobacco, cars, fuels, energy). The main reason is that data gained from the HBS are not entirely dependable and complete. Since those groups are very important, data are checked and, if necessary, corrected.

The main source for weights is National accounts data. Weights are additionally updated with data from other sources, i.e. surveys conducted by SURS (retail trade statistics, energy statistics, transport statistics, etc.). These additional sources enable the distribution of weights to aggregate levels with better precision and therefore better quality of weights for the goods and services.

All weights are reviewed every year and updated when required.

For locally collected items, the regional stratum weights for localities are largely derived from the number of people living in each region. For centrally collected items, when one price is valid for the whole county (e.g. newspapers, fuels, etc.), no weights are required. For other centrally collected items, regional weights are derived from population and turnover data along with information from other sources (e.g. providers of goods/services and research agencies, etc.).

Outlets are implicitly weighted via the sampling frame used, i.e. the bigger the market share (turnover) of a retail chain of outlets, the more branches of that chain are sampled. Information for this comes from a retail sales survey. Where no turnover data exist for a particular product or type of outlet, outlets are equally weighted.

For item weights, the main source of information is detailed HBS data. In those cases where the HBS is not so detailed, this information is also supplemented with information from other sources, e.g. providers of goods/services (travel agencies, providers of mobile phone services, financial services, internet, profit rents, number of beds in hotels, etc.), economic and market analyses and other surveys conducted by SURS.

For ECOICOP 01 and 02 (Scanner Data) elementary aggregate levels weights are based on the ratio of retailers’ turnover (t-1). Compilation of sub-index weights.

Weights are derived from National Accounts (t-2) up to 4th and in some cases up to the 5-digit sub-class ECOICOP level while for lower levels mostly data collected with the most recent Household budget surveys are used.

For some groups, weights are additionally checked with data from other sources (energy, trade) and, if necessary, corrected. The main reason is that data gained from the HBS are not entirely dependable and complete. Since those groups are very important, data are checked and, if necessary, corrected. We consider data from other sources, i.e. surveys conducted by SURS (retail trade statistics, energy statistics, transport statistics, etc.). These additional sources enable the distribution of weights to aggregate levels with better precision and therefore better quality of weights for the goods and services.

Sub-index level weights which are adjusted are: 021 Alcohol (Survey on trade), 022 Tobacco (Survey on trade), 0453 Liquid fuels (Survey on energy), 0711 Motor cars (Slovenian Chamber of Commerce), 0722 Fuels and lubricants for personal transport equipment (Survey on energy), 125 Insurance (Survey on insurance). Reference period higher levels

The reference year is t-2 (i.e. 2018), prices updated to December t-1 (i.e. 2019). Weights - plausibility checking

Weights are obtained from National Accounts for higher ECPOCOP levels  and are complemented with HBS data on lower level (elementary aggregat level). These data are checked and updated with data from other statistical and non-statistical sources. Neverthelessl the main source for calculating weights is national accounts data (t-2).  Weights are changed every year. Weights are price-updated to December prices (t-1).

Weights for important and sensitive groups (critical weights like Motor cars, Fuels and lubricants for personal transport equipment) are additionally reviewed and updated every year with data t-1.

Since 2018, a new data source (retailers’ turnover from Scanner Data) is taken into account (this applies to lower levels of aggregation). All weights are reviewed (sublevels included) every year and updated when required.

18.1.2. Prices

SURS has mixed approach regarding price collection:

  • prices are collected directly in the field or via telephone, emails, catalogues, the internet,
  • in electronic form,
  • by web-scraping,
  • by scanner data. Data Source - overview  

The main sources of price data used to compile the HICP are survey data and scanner data. Scanner data - general information

Scanner Data are received from Supermarkets and serve as:

  • the only source for index computation for Ecoicop Divisions 01 and 02 (using new methodology). The share of supermarket data represents about 75% of the grocery market (ECOICOP 01) and 70% (ECOICOP 02 - Alcohol). Market shares (2015) were calculated as the enterprise’s turnover as a share of turnover of all enterprises registered in Retail sale in non-specialized stores with food, beverages or tobacco predominating.
  • for Ecoicop 03, 05, 06, 09, 07 and 12 Scanner data serve as a source for price observation, but just in a function of imitating field collection (compliments traditional stores). Bulk web scraping - general information

SURS performs bulk webscraping but only a limited number of data enter index production - for now we just mimic traditional price collection.

We scrape data from the biggest domestic stores selling computers, computer equipment and package holiday providers (where access is not rejected).

18.1.3. Sampling design and procedure Sampling design: regions - general information

For the purpose of collecting data on prices, the country is divided into four parts ('regions'). Within 'regions', the largest city with surroundings is chosen for price collection (i.e. Ljubljana, Maribor, Koper and Novo mesto). Some prices are collected in other big cities, too, or centrally by the section, so that practically the entire territory of Slovenia is covered. Besides that, Scanner Data are obtained from the biggest supermarket chains (covering the whole country). Sampling design: outlets - general information

Outlets in each location are firstly selected on the basis of the turnover data from retail trade statistics as well as from information from the business register and other sources. Then the outlet sample is further augmented by price collectors’ experience and knowledge of the local market. We monitor prices in different types of outlets: markets, specialized stores, discounters and craftsmen. From 2018, we exclude market stalls, fish shops, butcheries, bakeries (they are not important in consumers‘ shopping habits, at least not in a significant scale). Sampling design: products - newly significant goods and services

The list of newly introduced goods and services in 2020 consists of: Smart watch, Power bank, Electric scooter and Video On Demand Streaming Services.

18.2. Frequency of data collection

Price data is collected every month.

18.3. Data collection

18.3.1. Price collection surveys

Price collectors collect prices by tablet computer (software based on Windows universal application). These data are sent by the http protocol to the SQL server at the central office. Data are reviewed once again and sent to Oracle where they are stored and prepared for further processing. The main difference between price collectors in the field and central price collectors is that in the central office prices are monitored on the internet; however, prices must be entered into the tablet, too. Three price collectors are in permanent employment, one is a contractor (organised by the Interviewing of People and Households Section). In each locality where prices are collected there is one price collector. Taking up their duties, new employees visit shops accompanied by someone experienced in this area (for some time).  But first of all, a tablet computer and its software used daily at work are presented. They also get all the necessary written instructions for price collection by tablet computer and clarifications concerning the functioning of the device. Additionally, we also organize 2-3 special meetings per year with price collectors, where the current problems in the field, new developments and new regulations from the harmonization process are discussed. Price collectors are experienced and in touch with the market. Their influence in outlet sampling, updating of the basket and marking the items for quality adjustments is significant.

Without taking into account prices for the first two Ecoicop Divisions, more than third of all prices are collected centrally via telephone, emails, catalogues, electronic form, scanner data and the internet; for newspapers and periodicals, post and telecommunication services, package holidays, accommodation services, electricity and fuel prices, prices for some medicaments and vehicles, bank services, municipal services, etc. Furthermore, scanner data are obtained from supermarket chains (covering household maintenance products, personal hygiene products, pets related products, etc.), so practically, by obtaining scanner data, more and more prices are collected centrally.

18.3.2. Timing of price collection

Data on prices are collected between the 1st and 25th day of each month.

18.4. Data validation

Different data sources have been checked separately. In the case of scanner data, the process fails (reports an error) at the entrance in case data arrive in a different standard, structure or date to which data relate. For traditionally collected prices the number of outlets and items has been checked. That number must be the same as predefined in the base period; the same applies to base prices. All collected prices are reviewed by price collectors before being sent to the central office; but initially, the first phase of control is incorporated in the tablet computer program for data entry and in the end all data are manually checked by a person in the unit. If there are doubts about the reliability of one or several prices, these prices are checked once again by contacting price collectors or, if necessary, checked directly in the field. There is no automatic rejection of observed prices in our validation process. Each case (problematic price) is considered individually and all modifications are done on the basis of relevant information. In addition, each collector's work is checked in the field 1-2 times per year to ensure that central office guidelines are being followed.

Testing the correctness and plausibility of outcomes is performed with several procedures; For Scanner data SURS’s application META SOP (SAS) for logic controls and data management is in force as well as visual inspection of indices.



18.4.1. Data validation - price data

Detecting data entry errors: We have several controls. 'Colour warnings' at price entry for monthly indices greater than 110 or smaller than 90. In the case of big discrepancies in price change (index greater than 300 or smaller than 50) additional confirmation of data entry is required. The price collector enters the type of data entry, e.g. number 2 stands for the same product–different price, besides that for data consistency an appropriate remark is chosen (price increase, decrease, discount, etc.), while at larger changes in prices the price collectors write additional notes when entering the price. In case the price controller decides that price collector explanation is not enough, it is demanded of the price collector to check the price again and report it to the section. For simpler data control (conducted by price collectors), the tablet computers’ application enables data to be displayed in Excel (sorting, comparing data, etc., in a way price collectors want). Price collectors can transmit data to the SQL server daily. So none of the collected prices that present a problem is eliminated automatically, but is treated individually and additional information on it is collected. In case the specification of the good or service is significantly changed, the section implements quality adjustment.

The monitoring of the consistency of the price information over time is integrated in the tablet's software. At each price entry in the tablet, a numeric remark describing product’s permanency is required: whether the product is the same as the previous month or it was replaced, etc. So we can monitor the product throughout the year. The consistency of the price information across similar products in the same period is monitored by visual inspection and information we receive. E.g.: Company X advertises 20% discount on items with brand Y. Those items are monitored in different outlets/cities, so 20% discount should be captured everywhere. 

In the case of extreme prices or price changes in Ecoicop 01 and 02 (Scanner data) extreme price changes are considered as outliers; for ECOICOP 03-12 price collectors check extreme price changes once again and if there is no acceptable explanation prices are being imputed (previous month’s data).

Scanner data: SURS’s application META SOP (SAS) is designed for logic controls and data management. it removes duplicates, zero values, detects outliers, etc. 


18.5. Data compilation

18.5.1. Index formulae

The Slovenian HICP is an annually chain linked Laspeyres-type index.

The price indices for elementary aggregates are calculated as a ratio of geometric mean prices.

The number of decimals applied at:

  • Price monitoring - as many decimals are considered as shown on the price lists. In low prices the calculation per unit takes into account a larger number of decimals. Almost all prices have been applied with 2 decimal places; some exceptions are petrol prices (3 decimals), electricity prices (5 decimals), etc.
  • Weights - no rounding or truncation is applied. For weights 7 decimals are applied and transmitted to Eurostat.
  • The compilation and transmission of index figures and rates of change - no rounding or truncation for weights is applied. In compilation and transmission to Eurostat 10 decimals are applied. Publication of index figures and rates of change - data are published to 1 decimal, except for the indices 2015 average, where two decimals are displayed.

For publication of index figures and rates of change rounding is used.

18.5.2. Aggregation method

The average national price of each non-food product or service is calculated with weighted arithmetic mean from previously calculated average prices in the locality. From average national prices in each current and base month (December of the previous year) we calculate individual index for each elementary aggregate.

Data from retailers’ databases (scanner data): From the monthly chain-linked EA indices per individual retailer we calculate an indiviudal index per elementary aggregate with weighted arithmetic mean. Weights of retailers represent the market share (turnover) of individual retailer per individual EA. From individual indices we calculate weighted arithmetic mean aggregate indices, i.e. indices of groups (by ECOICOP) and the total price index.

18.5.3. Chaining and linking method

At aggregated level annual chain-link method is used where December of the previous year is the linking month.

In 2001 the indices were chain linked through the new index base, i.e. 2000 (2000 average = 100), and a new method of calculation was introduced. In 2006 indices have been linked through a new index reference period 2005 (average 2005 = 100). Since 2016 indices were linked through the new index reference period year 2015 (average 2015 = 100).

The splicing in the time series is not used.

18.5.4. Quality adjustment

Explicit methods: Direct price comparison is used for clothing and footwear, books (the list of most read books is changed every month, since we monitor the major publishing house in the country, which publishes monthly the list of most sold, i.e. popular, books - Top 10 for adults and children/youth). DVDs and computer games are replaced on a monthly basis with more popular ones - direct comparison is used. As regards new cars, mixed/combined approaches are used; in the case of significant change, quality adjustment is made (mostly option pricing complemented with supported judgemental methods). For quantity adjustment, package size adjustment is used (e.g. medicaments). Option pricing is the most commonly used explicit method (a half of the price difference between the two models is attributed to the difference in quality). Sometimes, when other methods can't be applied, we change the base price of a replaced model with the replacement's base price (only if the December price of the replacement is known).

Implicit methods: The choice of a method also depends on the data available: overlap method for audio-video, photo equipmet (if data on prices in two consecutive periods are available). Bridge overlap method is applied in most cases when quality changes are detected. It’s applied for PCs, technical products, household appliances, audio-video goods and in a case of significant change in quality when no other useful information is available.


In 2019, the percentage of quality adjustments (ECOICOP 03-12) was 0.4%.


ECOICOP QA method (%)
Division Option pricing and mixed approaches Bridged overlap Package size adjustment Other
Base price change
03   0,01    0,11
04 0,09     0,43
05 0,06 0,30 0,004 0,21
06       0,23
07 0,18 0,06   0,25
08 0,40 2,51   0,40
09 0,10 0,30   0,40
11       0,10
12 0,02 0,04   0,16

18.5.5. Seasonal items - general information

Seasonal items are treated in accordance with Regulation 330/2009. A class-confined seasonal weights method is applied.

Product groups treated as seasonal are Fruit, Vegetables, Clothing, Footwear, Household appliances, Sport equipment, Recreational services and Package holidays.

For all the categories of seasonal items indices are calculated according to the CCSW method (seasonal weighting limited to individual classes). Weights of predefined seasonal products during their non-season are distributed to other products within the same class. During the year class weights remain the same while the product’s annual average weight is the same as its base weight.

18.6. Adjustment

Not applicable.

19. Comment Top


Related metadata Top

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