Harmonised index of consumer prices (HICP) (prc_hicp)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Italian National Institute of Statistics


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)
 



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1. Contact Top
1.1. Contact organisation

Italian National Institute of Statistics

1.2. Contact organisation unit

Integrated System on Economic Conditions and Consumer prices Unit

1.5. Contact mail address

Via C. Balbo, 16
00184 Roma
ITALY


2. Metadata update Top
2.1. Metadata last certified 12/07/2023
2.2. Metadata last posted 12/07/2023
2.3. Metadata last update 12/07/2023


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 harmonised approach. It measures the change over time of the prices of consumer goods and services acquired by households (inflation).

Due to 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

None.

3.7. Reference area

3.7.1. Geographical coverage

The HICP refers to the economic territory of a country as referred to in paragraph 2.05 of Annex A to ESA 2010, with the exception that the extraterritorial enclaves situated within the boundaries of a Member State or a country are included and the territorial enclaves situated in the rest of the world are excluded.

3.7.2. Coverage error regions

The Italian HICP covers all purchases by both resident and non-resident households within the economic territory of the country.

The economic territory of Italy is as defined in ESA 2010, except that the extraterritorial enclaves situated within the boundaries are included and the territorial enclaves situated in the rest of the world are excluded. The Republic of San Marino and the Vatican State are not covered.

In 2023 for almost the 50% of the basket the territorial coverage could be considered complete. It is referred to all the products in the basket which prices are collected a) centrally by Istat, b) through scanner data, c) receiving data from big providers and d) through administrative data.

For the remaining 51.5% of the basket, all Italian regions are covered in the following terms. Prices are collected in 79 towns (19 regional chief towns, 59 provincial chief towns and 1 municipality with more than 30,000 inhabitants) - which participate in the indices calculation of all items included in the basket - and in other 12 municipalities participating in the survey only for a subset of products which includes local tariffs (water supply, solid waste, sewerage collection, urban transport, taxi, car transfer ownership, canteens in schools, public day nursery, etc.) and some local services (building worker, football matches, cinema, theatre shows, secondary school education, canteens in universities etc.).

The coverage of the index, in terms of resident population of the provinces of the 79 towns taking part in the survey, is 82.9%. Considering also the 12 municipalities that participate only partially to the survey, the coverage, measured in terms of provincial resident population, rises to 90.0%.

3.8. Coverage - Time

3.8.1. Start of time series

The HICP series started in January 1997.

3.8.2. Start of time series - national specifics

See the HICP database

3.9. Base period

2015=100


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. Regulation (EU) 2016/792 of the European Parliament and the Council of 11 May 2016 (OJ L 135) sets the legal basis for establishing a harmonised methodology for the compilation of the HICP and the HICP-CT.

This regulation is implemented by Commission Regulation (EU) 2020/1148 of 31 July 2020.

Further documentation, can be found in Eurostat’s website - HICP dedicated section, namely recommendations on specific topics, under the methodology page, and guidelines, under the quality page.

6.2. Institutional Mandate - data sharing

The Legislative Decree No 322 of 6 September 1989 contains provisions on data sharing and coordination within SISTAN: according to the article No 6 Statistical Offices, under the coordination of Istat, shall cooperate with other authorities for the execution of the surveys provided for in the National Statistical Programme.

Directives issued by COMSTAT have further strengthened these provisions. In addition, Istat has developed statistical information systems utilized throughout SISTAN for sharing data. Istat also cooperates closely with agencies that do not belong to SISTAN through specific data sharing protocols and agreements.

Istat is part of the European Statistical System and coordinates and shares data with the Commission (Eurostat) and the others national statistical institutes and other national authorities responsible in each Member State for the development, production and dissemination of European Statistics.


7. Confidentiality Top
7.1. Confidentiality - policy

Regulation (EU) No 2015/759 of the European Parliament and of the Council of 29 April 2015 amending Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
Istat is obliged by law to respect the principle of statistical confidentiality (Article 9 of Legislative Decree No 322/89) upon which the National Statistical System is founded with regard to data collected during its own surveys. These data, therefore, are used exclusively for statistical purposes and may not be divulged to any party – public or private – outside the National Statistical System, or otherwise published or divulged, except in aggregate form and in such a way that it is impossible to identify the person to whom the data apply.
The compliance with the statistical confidentiality parties an aspect  of the broader principle of personal data protection as provided for by the Ethical code of conduct concerning the protection of personal data (Legislative Decree No 196/03) and specifically Annex A3, 'Ethical code for the processing of personal data for statistical purposes within Sistan'.

7.2. Confidentiality - data treatment

In order to make statistical confidentiality and protection of personal data effective, Istat is currently taking appropriate organisational, logistical, methodological and statistical measures in accordance with internationally established standards.

To meet the demand of detailed statistical information, Istat has developed a system of products and services to access and release of microdata - data on individual units of analysis.

As part of the release of microdata, Istat offers a research data centre: ADELE Laboratory (Laboratory for Elementary Data Analysis), a 'secure' site accessible by researchers and academics enabling them to conduct their own statistical analyses on microdata from the Institute's surveys in compliance with legislation concerning the confidentiality of personal data.

The list of Istat surveys is available on line.

In addition, the section promoting information exchange and collaboration between Istat and scientific societies (in Italian language) is dedicated to researchers in order to contribute to the development of knowledge and to enhance the scientific debate in the national community.

Istat, moreover, participates in IDEM, the Italian federation of authentication and authorization infrastructures, and EduRoam that makes it easier and safer to access the web and the wi-fi network provided by its member organisations.


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 Protocol on impartial access to Eurostat data for users.

8.1. Release calendar

The HICP is released according to Eurostat’s Release calendar.

The calendar is publically available and published at the end of the year for the full following year.

8.2. Release calendar access

Istat website: Release calendar 2023.

8.3. Release policy - user access

In line with the Legislative Decree No 322/1989 (Article 15, paragraph 1[g] – requirement to publish and disseminate data) and the Italian Statistics Code of Practice (issued by the Comstat - Policy-making and Co-ordinating Committee for Statistical information - under Directive no. 10/2010 in full accordance with the European Statistics Code of Practice), Istat disseminates statistics, mainly on Istat’s website, (see item 10 - ‘Dissemination format’) 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 Carta dei servizi della Diffusione (Charter of Dissemination Services).


9. Frequency of dissemination Top

Monthly


10. Accessibility and clarity Top

The frequency of dissemination is bi-monthly. In facts, the consumer price indices release occurs in two successive time instants according to a different mode of data release: initially, as provisional estimate and afterwards, as a final data.

The dissemination of provisional estimates of the Italian HICP and CPIs occurs at the end of the reference month. The dissemination of final data of the indices is no later than the middle of the month following the reference one.

There is no paper dissemination. Generally speaking, ISTAT has considerably decreased paper dissemination in the last years. All releases and publications, excluding a limited number of them, are only released on ISTAT website.

 

10.1. Dissemination format - News release

Press releases on-line.

10.2. Dissemination format - Publications

The HICPs for the 12 ECOICOP Divisions and the total are published in time series tables attached to Press release.

10.3. Dissemination format - online database

Italian HICP indices, with a level of detail of the ECOICOP-HICP product classes and by special aggregates and Italian HICP-CT indices, with a level of detail of ECOICOP divisions, are published in I.Stat, the warehouse of statistics produced by Istat, inside the theme Prices.

10.4. Dissemination format - microdata access

None.

10.5. Dissemination format - other

See also Istat’s CPIs section website.

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

Methodological notes on the Italian HICP and national CPIs are published in:

10.7. Quality management - documentation

See Eurostat's Compliance Monitoring Reports of 2007, 2014, 2018 and follow-up report of 2022.


11. Quality management Top

In order to ensure the quality of the index, self-assessment procedure is carried out for the Survey of on Consumer Prices. This procedure is inside the quality assessment framework (internal audit and self-assessment of statistical products and processes) implemented by ISTAT, starting from January 2012. This framework is based on a combination of both internal audit and self-assessment procedures and is aimed at verifying the compliance of statistical processes and products to the principles stated in ISTAT Quality Guidelines for Statistical Processes (see the attached file). It allows for the identification of strengths and weaknesses in statistical processes and, meanwhile, for defining improvement actions. The quality assessment is carried out by a team of internal experts or auditors, in case of audit and by the survey manager, in case of self-assessment. In the last case the results are revised by an internal expert or reviewer. The assessment activity results in the definition of a list of improvement actions for each process under review. After top management approval, they are to be implemented in order to overcome the identified weaknesses and lead to quality improvements. The main improvement actions identified are categorised as follows:

  • 'internal' improvement actions: to be implemented through resources available within the department or direction in charge of the assessed survey;
  • 'system' improvement actions: their implementation is linked to the development of ISTAT's strategic projects; an example is the creation of common infrastructures such as the new centralised data acquisition systems;
  • 'Collaborative' improvement actions: their implementation is linked to the collaboration among different actors; this is the case of methodological actions, IT actions or others.

Every year, about 14 processes, are subjected to evaluation. At the moment, quality reports and results of audit and self-assessment procedures are not made available to users.

Concerning Italian HICP, ISTAT central office has a higher degree of control over the operations of the index at all levels with respect to the quality of the index results. As described below, ISTAT staff can monitoring all phases of price collection, product replacement and quality adjustment procedures, editing and index calculation at all level.

In particular, the staff of the Municipal Statistical Offices (MOSs) participating on the survey have an important role, above all, in the first phases of the production process; in their work, they follow the guidelines provided by ISTAT with periodical training and a continuous real-time support.

The in-depth reengineering of the local consumer price survey IT environment (based on a centralised relational database that stores all the survey data; a data collection application, running on PC Tablets; a control and correction application which allows to perform checks and editing on micro data directly on the database and makes available several sets of indicators to monitor data quality) has greatly improved the quality of indices data and reduced the non-sampling errors.

In order to guarantee the quality (accuracy) of Italian HICP and CPIs, a complex system of actions and editing procedures, aimed at non-sampling error handling, is applied:

  • preventive actions, aimed to reduce the error probability, consist of training activities periodically arranged for price collectors and local responsible of the survey of MOSs and updating training for all staff at central level. The training of price collectors regards all activities connected to price collection (timing, product replacements and microdata editing practices, among others) and the training of the MOS staffs concerns activities connected to the management and the quality monitoring of the daily work carried out by collectors and to the data editing. The training of ISTAT staff regards all aspects of production process of consumer price indices. ISTAT staff has a crucial role of support and guidance of all staff involved in the local collection;
  • checks under production process, in order to identify and correct errors when they arise, are carried out by mean of the software ‘desktop’ (named P1J) installed on Tablets which provides a set of automatic checks on imputed data, aiding price collectors to detect and avoid possible mistakes and to validate prices. These automatic checks are based on tolerance range of price change (comparison of the currently observed price quote with the previously observed one) and are set independently for group of products, taking into account if products are seasonal or have volatile prices etc.
  • assessment actions, aimed to measure the non-sampling error level contained in produced data, are carried out by mean of the editing application (named P2O) which is used by MOS and ISTAT staff and which provides complex checks on quality of:
    • the process of price collection per each municipality;
    • the collected data per each municipality (check on the general state of the survey for each municipality and automatic identification of errors in the micro data, using a set of indicators which can be calculated with different periodicity during the month).

 



Annexes:
ISTAT Quality Guidelines for Statistical Processes
11.1. Quality assurance

11.1.1. Quality management - Compliance Monitoring

Compliance Monitoring

11.1.2. Quality assurance - national specifics

Statistical practice used to compile HICP is compliant with HICP methodological requirements and good practices in the field of CPIs Data production process and data quality are regularly carried out both by Istat and Municipal Offices of Statistics (MOS) that are officially in charge of local data collection.

Monitoring activity is carried out using different indicators regarding outlet selection, price collection schedule and quality of collected data (temporary non-collection rate by different reasons – outlet closing, missing items etc; replacement item rate, temporary price reduction rate).

At first stage, data quality is monitored by MOS. At a second stage, Istat carries out a complete check on the entire data-set collected both by MOS and at central level (about 393,000 prices are monthly collected by MOS).

Istat regularly provides data collectors with training interventions geared towards acquiring appropriate skills for carrying out collection activity.

11.2. Quality management - assessment

11.2.1. Compliance monitoring - last report and main results

See Eurostat's Compliance Monitoring Report of 2007, 2014, 2018 and 2022 follow-up.

11.2.2. Quality assessment - national specifics

The quality of the HICP can be assessed high. Its concepts and methodology has been developed according harmonised standards. HICP accuracy is considerably improved following changes introduced in the data collection and data editing processes. The main users consider HICP sufficiently accurate for their purposes. It is disseminated following a pre-announced timetable.

The quality assessment is firstly carried out through periodic internal audit.


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

The HICP is mainly used for measuring price trends, economic forecasting and analysis, accounting purpose and deflating series and inflation targeting.
The main users include European Central Bank, European Commission, Bank of Italy, Finance and Economy Ministry, Economic Development Ministry, universities, public and private research institutes, trade associations, National Accounts Division and other Istat sections; media and public at large.

12.2. Relevance - User Satisfaction

No information.

12.3. Completeness

Concerning the Italian HICP and HICP-CT, ECOICOP indices at 5th digit level are produced monthly and published on Istat website (starting from the 4th digit level).


13. Accuracy Top
13.1. Accuracy - overall

The accuracy of HICP can be assessed high. The accuracy of data source is monitored by assessing the methodological soundness of prices and weights sources and the adherence to the harmonised methodology. Price collection assure good coverage and timeliness. Outlets, where price are collected, are selected to represent the Italian trade and services network. All the private household in the economic territory are covered.

No systematic error affects the estimates.

In the last years, there were no revisions of the released data.

13.2. Sampling error

The HICP sampling error is not quantified because a non-probability sampling is used. Sampling errors are reduced using a large amount of consumer prices; furthermore, in order to minimise the variance of the all-items index, a representative number of prices for each item category is collected. 

13.3. Non-sampling error

The HICP non-sampling errors are not quantified. They are considerably reduced in the last years with the in-depth reengineering of the whole Consumer Price survey IT environment. The new IT architecture is based on:

  • A centralised relational database that stores all the survey data;
  • A new data collection application, running on Tablets;
  • A new control and correction application which allows to perform checks and editing on micro data directly on the database and makes available several sets of indicators to monitor data quality.


14. Timeliness and punctuality Top
14.1. Timeliness

The full set of HICPs is published each month according to Eurostat’s Release calendar, usually between 15 and 18 days after the end of the reference month.

Each year, the January release is published at the end of February to allow for the annual update of the weights, both 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 dates announced in Eurostat’s Release calendar.


15. Coherence and comparability Top
15.1. Comparability - geographical

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

To this end, concepts and methods have been harmonised by means of legislation. HICPs that deviate from these concepts and methods are deemed comparable if 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 (Article 4 of Council and Parliament Regulation (EU) 2016/792).

15.2. Comparability - over time

Data on Italian HICP are available with reference period 2015=100 starting from January 2001 onward.

A set of monthly HICP series for the period 2001-2015 using 2005 as reference base year are also available; a set of monthly HICP series for the period 1997-2000, using 1996 as reference base year, are available at request.

15.3. Coherence - cross domain

ISTAT produces three different Consumer price indices, based on the same survey:

  • Consumer price index for the whole nation (NIC Index);
  • Harmonised index of consumer prices (HICP Index);
  • Consumer price index for blue- and white-collar worker households (FOI Index).

Differences between the HICP and the national CPIs:

  • As HICP, national CPI NIC refers to the entire population present in the country and implements the domestic concept, whereas the national CPI FOI refers to a subpopulation residing in the country and implements the “resident concept”;
  • National CPIs refer to household final consumption. So, for Health and Education and some Social protection expenditure, they use gross prices (i.e. the total prices of products, whether fully or partially paid by households), whereas the HICP uses net prices (prices actually paid by households);
  • National CPIs do not take into account temporary price reductions (i.e. sales);
  • National CPIs include in their scope Games of chance;

Concerning pharmaceutical products and some medical and paramedical services, contributions to the NHS are not used for national CPIs calculation (whereas they are included in HICP).

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 under the terms set in Articles 17-20 of Commission Implementing Regulation (EU) 2020/1148.

17.1.1. Data revision - policy - national specifics

In case of mistakes, ex-post changes in the HICP series, index levels, rates of change or weights that has been made publicly available, are implemented. Revisions due to mistakes are communicated to users as soon as possible.

Revised figures are released to the public accompanied by explanatory information made available on the ISTAT web site and in the different statistical products (mainly press releases and I.Stat data warehouse) they are marked with a flag. The revision marks, shown on the occasion of the release of the revised figures, are removed the following month.

Information at the level of detail necessary to assess the impact and the HICP series concerned before the release of revisions on the grounds of mistakes and the actions taken to prevent similar future occurrences are always provided to the Commission (EUROSTAT).

The methodological-technical changes and the updating of statistical standards (Article 6 Changes in the system of harmonised rules of Commission Regulation No 1921/2001), which are generally implemented in occasion of annual rebasing of the indices, do not entail revisions on previously released data.

17.2. Data revision - practice

The first data dissemination concerns provisional data for the latest month. These are confirmed or revised to the final figures within the second week of the following month.
Other major revisions are generally released with explanatory notes in the press release. Methodological changes are explained with the first release of data affected by such changes.  


18. Statistical processing Top
18.1. Source data

18.1.1. Weights

At the highest level of aggregation, weights are based on annual NA expenditure data which refers to a domestic concept of consumption.

Since 2021 basket, to take into account the changed consumption expenditure deriving from the health emergency due to Covid-19, for the estimation of the weighting coefficients, it was decided to use the most recent National Accounts data available. This choice was confirmed for the 2023 basket as well and therefore the reference expenditures are provisional data relating to year 2022.

Since the COVID-19 pandemic had a significant impact on the consumption expenditure of households who adjusted their consumption habits to the new circumstances, for the estimation of the weighting coefficients for 2022 indices, it was decided to use the most recent National Accounts data available, i.e. the provisional data relating to year 2021.

NA data concerns about 60 consumption expenditure aggregates, classified according to COICOP (as for food, the NA expenditure aggregates are provided at the class level; for non-food products the expenditure data are generally less detailed). NA data are reconciled with the coverage of the HICP by excluding imputed rents, consumption of self-produced goods, FISIM, and expenditure for games of chance; the data necessary for this task are produced by NA (in some cases, this information is provided to Consumer Prices Unit, but it is not disseminated).

In order to estimate weights for the lower level of the ECOICOP classification, NA data are broken down using more detailed information from other auxiliary sources (internal and external) and generally referred to year 2021. At the end of this process, weights are estimated for more than 400 product aggregates in which the final consumption is partitioned.

Secondary sources of information are, generally, updated annually. In some limited number of cases, secondary sources of information are updated less than annually.

18.1.1.1. Compilation at elementary aggregate level

Generally, the lowest level of aggregation where explicit weights are introduced is the product aggregate level (8 digits level of the classification scheme for the Italian HICP). In a number of cases, however, product aggregate indices are calculated as the weighted arithmetic mean of product indices: in these cases explicit weights are defined corresponding to the 10 digits level of the classification.

The weights used below the sub-index level are estimated using information sources which are both internal to ISTAT - Household Budget Survey (HBS) and other Multipurpose surveys - and external.

HBS is used as a source for about 140 product aggregate weights (on a total of about 400).To estimate 2023 weights, provisional HBS data referred to year 2022 were used.

In almost all the cases, HBS data are used in combination with other sources.

With reference to the external sources, hereafter a list:

  • market research centres such as A.C. Nielsen-Italia for food and grocery, Sita-Ricerca for clothing and footwear, GFK for electronic products and major household electric appliances, IQVIA SOLUTIONS ITALY for pharmaceutical products;
  • trade associations like FEDERLEGNO for furniture, ANIE for household appliances, Unione Petrolifera for fuels, FIEG for newspapers and magazines, ANIA for insurance services, etc;
  • national authority and public bodies such as AAMS (Independent Administration of State Monopolies) for tobacco products; AIFA (Italian Medicines Agency) for pharmaceutical products; ACI for motor cars; Ministry of Transport and Infrastructures for some transport services – by road, by sea and inland waterway; ENAC (Italian Civil Aviation Authority) for air-fares; Communication Department of Ministry of Economic Development for postal services; AGCOM (Italian Communications Authority) for telephone services; ISMEA for food; Bank of Italy for financial services; Revenue Agency for Medical services, ARERA the Italian Regulatory Authority for Energy, Networks and Environment for Electricity and Gas.
  • companies such as ENEL (the largest electricity company in Italy) for electricity.

For the external sources, the reference period is 2021, with the exception of Sita-Ricerche (for clothing and footwear). IQVIA SOLUTIONS ITALY (for pharmaceutical products) and GFK (for electronics) for which 2022 data were available.   

Weights for regions are estimated using data on household final monetary consumption expenditure at regional level provided by National Accounts (year 2021) and HBS data (year 2022).

Generally speaking, there is not a system of weights for outlets (with the exception of the outlets of modern distribution for which scanner data concerning grocery products are available); product indices at town level are calculated through simple geometric mean, for the lack of information concerning turnover of each outlet for each product.

18.1.1.2. Compilation of sub-index weights

The weights of sub-indices, at three digits level, are obtained using publicly available NA data. As for the four digits level, more detailed information is generally needed (however this is not the case concerning the sub-indices of the Division 01 Food and non-alcoholic beverages, for which data released by NA are sufficiently detailed). To this aim other sources of information are used to breakdown NA expenditure data, both internal to ISTAT (HBS and other Multi-purpose surveys) and external.

With regards to weights from National Accounts, the table of final consumption expenditure of households - national annual data - on economic territory by COICOP is used. The NA data and the HBS data, expenditures used to breakdown NA aggregates, both refer to the year t-1 (2022).

In the 2023 HICP basket the largest increases concern the weights of Restaurants and hotels (+19.468 as parts for 1000), Housing, water, electricity, gas and other fuels (+8.307) and Recreation and culture (+6.507); the largest decreases relate to Food and non-alcoholic beverages (-13.594 as parts per 1000), Health (-4.098) and Alcoholic beverages, tobacco (-3.900).

18.1.1.3. Compilation of sub-index weights

The reference period of the data used for the calculation of the weights (national level) is t-1 for primary source (NA expenditure data) and for the mail secondary sources of information (HBS). Other auxiliary sources used to estimate weights at the lower level of classification are generally referred to year t-2.

18.1.1.4. Weights – plausibility checking

Below the 5-digit level of ECOICOP, data used to estimate weights are checked by analysing the consistency with the data of the previous years.

 

18.1.1.5. Price updating

The price-updating practice concerns the expenditures at the product aggregate level. For each product aggregate in the basket of the HICP, the estimated expenditure (referred to year t-1) is price-updated to December t-1 using the rate of change measured between the average of year t-1 (2022) and December t-1 (2022). If price indices are not available (as for the new product aggregates included in the basket in occasion of the rebasement of the index), the price-updating is carried out on the base of the rate of change of the index referred to the immediately upper aggregation level.

18.1.1.6. Compilation of total household final monetary consumption expenditure

The reference period of the primary source (NA expenditure data) is t-1 (provisional data). Therefore, no adjustment was necessary to ensure consistency with HFMCE.

18.1.2. Prices

Price collection is carried out using different sources of information: survey, scanner data (for grocery products excluding fresh food), webscraping and administrative data (for fuels, rents, tobacco).

In different cases, prices are also collected on the internet, but only for a limited number of product-offers.        

18.1.2.1. Data Source - overview  

The main sources of price data are:

  1. Survey data: traditional price collection and centralized price collection (which includes some web scraping);
  2. Administrative data (fuels, rents, tobacco). Administrative data are also collected directly by Istat;
  3. Scanner data (grocery products excluding fresh food).

 

 

18.1.2.2. Scanner data - general information

Since 2018, Istat has been using scanner data of grocery products (excluding fresh food) in the production process of the Italian HICP. Starting from January 2021 also the ECOICOP group 06.1.2 (Other medical products) is collected with scanner data.

In January 2023 Istat introduced scanner data to collect 19 further sub-indices ('aggregate of products') relating to packaged aged cheeses and fresh fruit and vegetables, previously collected with the local survey by municipal statistics offices. These new sub-indexes include only non-seasonal products sold in fixed-weight packages.

At present, scanner data feed the calculation of 103 sub-indices ('aggregate of products') belonging to six ECOICOP Divisions (01, 02, 05, 06, 09, 12).

The weight of scanner data on the HICP basket is 14.4%.

In 2023, scanner data for 4,283 outlets (4,007 in 2022) of the main 19 Retail Trade Chains covering the entire national territory are monthly collected by Istat on a weekly basis at item code level. The sample includes 483 hypermarkets, 1,577 supermarkets, 1,066 outlets with small sales areas (outlets with surface between 100 and 400 s.m.), 588 discounts and 569 specialist drugs).

Istat has increased the sample of outlets in the southern regions of the country where a greater number of missing outlets was observed in the previous years.

No increase in the number of retailers is planned for the time being.

Since 2020 the dynamic approach has been implemented to the selection of the elementary items. Since 2023 more than 20 million price quotes are collected each week to estimate inflation and the sample includes more than 12 million references each month.

Scanner data have replaced the traditional survey for all grocery products. Only for some products the prices are also collected by the municipal statistical offices (in dedicated shops such as pharmacies, perfumeries and pet shops). Weights for the integration of product aggregates indices of modern and traditional distribution, at the provincial level, are estimated from specialised sources.

18.1.2.3. Web scraping - general information

In 2022, web scraping is used to collect prices transport services by train, transport services by air, electricity in the liberalized market, town gas and food delivery.

As for transport services by train, web scraping procedures are currently used for scraping prices on the Trenitalia and Italo web sites (different macros have been developed to collect ticket prices by type of services).  

The prices for transport services by air are collected using web scraping procedures through the API’s available on Skyscanner’s web site. Several queries are launched to collect prices for national and international destinations with several lags between observation date and day of departure.

The prices of electricity in the liberalized market (in addition to the collection of prices in the administered market) are collected on the websites of the main regional providers.

Concerning town gas, web scraping is used to collect prices in the free market. 

For food delivery, prices are collected once a month on the website of one of the company more widespread on the national territory and refer to an order of standard meal with drink, delivered to the costumer's house (in the centre of the metropolitan areas). The sample includes 12 municipalities.

The API’s for the prices for transport services by air could be considered as a big data source in ISTAT, the same could not be said for the other goods and services whose prices are collected automatically from the internet. 

18.1.3. Sampling

18.1.3.1. Sampling design: locations for survey

All Italian regions are covered by the sample of outlets.

18.1.3.2. Sampling design: outlets

Regarding the traditional survey, the selection of outlets is based on a judgment sampling.

The survey is carried out at retail stores (shops, retail markets with fixed counters, discounts, etc.) or at artisans, freelancers, companies, agencies, hospitals, museums, outpatient clinics, sports centres, stadiums, cinemas, theatres, etc.

Concerning scanner data, the sample of outlets is a probability sample stratified according to provinces (107) and outlet-types (hypermarket, supermarket, outlets with surface between 100 and 400 s.m., discounts and specialist drugs). To select the sample, probabilities of selection are assigned to each outlet based on the corresponding turnover value. In 2022, the sample consists of about 4,000 outlets in more than 500 strata.

 

18.1.3.3. Sampling design: newly significant goods and services

Each year, both the goods and services in the basket are updated.

The review of the basket of products takes into account the changes in the household spending patterns and enriches, in some cases, the range of products which represent consolidated consumption.

For 2022, the main products added to the basket that represent the changes in the household spending patterns, are:

  • Desk chairs
  • Air fryers
  • Pulse Oximeter
  • Psychotherapy
  • Molecular test and Antigen test Covid 19
  • Serological antibody test Covid 19
  • Antigen self-test KIT Covid 19
  • Pokè bowls takeaway
  • Gymnastic mats and Streaming of audio content
  • Bread with other flours
  • Striped prawn
  • Artificial sugar substitutes
  • Town gas and natural gas - free market
  • Women's jeans
  • Children's shorts
  • Reading glasses without a prescription
  • Pet carrier.

On the other hand, Compact disk and Hoverboard have been removed from the basket. 

18.2. Frequency of data collection

Price data is collected every month.

18.3. Data collection

18.3.1. Price collection surveys

Data contributing to the calculation of monthly consumer price indices are collected using different sources: the local survey, carried out by municipal statistics offices, under Istat supervision and coordination; the central survey carried out directly by Istat or through different data providers; the scanner data; the administrative sources.

18.3.2. Timing of price collection

The survey on consumer prices is carried out each month in the first fifteen working days.

18.4. Data validation

Data validation is carried out in two stages. First, data are validated at territorial level by MOSs. Second, Istat carries out validation data analysing different indicators available such as temporary non-collection rate, replacement item rate, temporary price reduction rate and price change rate for outlier or error detection.

For some group of goods and services, such as energy, outside sources are used to validate data.

As required by law, in each municipality, before publication, data are examined and validated by Municipal Commissions constituted by experts of economical bodies (Trade Unions, Trade Associations etc.).

18.4.1. Data validation - price data

With regards to editing practices, the use of Tablets for the local price collection provides the opportunity to validate collected prices in the field and to correct errors at the time of price collection (micro-editing). The software ‘desktop’ (named P1A) installed on Tablets provides a set of automatic checks on inputted data which aiding price collectors to detect and avoid possible mistakes and to validate prices. These automatic checks are based on tolerance range of price change (comparison of the currently observed price quote with the previously observed one). Ranges are set independently for group of products, taking into account if products are seasonal, if they have volatile prices etc. In details, the ranges are set as follows: Fresh fruit and vegetable, ± 50%; Fresh fish, ± 30%; Fuels ± 1%; Heating oil, Rent, Maintenance charges in multi-occupied buildings and all other products ± 8%. A further check is set for the quantity to which product price refers; it is based on a tolerance limit for quantity variation equal to 50%.

The described editing phase represents the first step of editing process. The next steps are carried out by mean of the editing application (named P2O) which is used by MOS and ISTAT staff and which provides complex checks on input data.

As for missing observations, quality checks are carried out on the basis of the information on price-loss causes reported by collectors. Particularly, each month MOS monitors:

  • the number of missing observations;
  • the correct applications by the collectors of the rules governing the substitution of product offers in case of permanent/temporary unavailability of prices;
  • the prices that do not exhibit any change for a long period.
18.5. Data compilation

18.5.1. Elementary price index formulae

Italian HICP is a Laspeyres-type index covering the ECOICOP.

In the Italian HICP, product aggregates are, within the consumption segments, the sample of products or group of products for which indices are calculated at national level. Particularly, product aggregates indices include stratification by regions and municipalities.

Product aggregates (for each region and municipality) can include one or more products: in the latter case, the product aggregate index is calculated using either the geometric or the weighted arithmetic mean (depending on the availability of the information needed to estimate weights).

It is worth noting that the computation of indices of the centrally collected products is based on a detailed stratification design which may include the territorial variables, (this is the case for example of fuels, electricity, building workers, some types of touristic services).

The number of decimals applied for the most part of price observations is equal to 2.

For fuels prices, the number of decimals applied is equal to 3; for tariffs and fees for gas, water supply and taxi, it is equal to 8; finally, for electricity tariffs, it is equal to 5.

With regard to compilation of HICP indices, at all level – from micro indices to all items index -, figures are with 6 decimal places.

Weights are per 1,000,000 (no decimal places)

Index figures are transmitted to EUROSTAT with 6 decimal places.

HICP indices (monthly and average index numbers) are published with 1 decimal place.

Rates of change are calculated using indices with 1 decimal place.

18.5.2. Aggregation of different data sources

In synthesis, the aggregation method consists of the following steps:

  1. Indices of the aggregate of products at the provincial level are calculated as the weighted arithmetic mean (or alternatively geometric mean) of micro-indices (indices of references);
  2. Indices of the product aggregates at the regional level are calculated as the weighted arithmetic mean of provincial indices (population weights).
  3. Indices of the product aggregates at the national level are calculated as the weighted arithmetic mean of regional indices (NA expenditure weights).
  4. Indices of the ECOICOP aggregates are calculated as the weighted arithmetic mean of the national aggregate of product aggregates indices (NA expenditure weights).

For grocery products (ex. fresh food), indices of the product aggregates at the provincial level are calculated using scanner data.  

In 2022, concerning 9 product aggregates (in ECOICOP Divisions 01, 06, 09 and 12), the corresponding provincial indices are calculated as the weighted arithmetic mean of 'scanner data' indices and 'traditionally collected prices' indices.

For the majority of the centrally collected price, the product aggregates indices are calculated at the national level as the weighted arithmetic mean of strata indices.

 

     

18.5.3. Chaining, linking and splicing methods

The chaining of the series is carried out by multiplying the monthly indices (base December t-1=100, 6 decimal places) of the current year for the index of December of the preceding year, expressed in reference base (2015=100, 6 decimal places).

The chained indices are then rounded to the first decimal place.

18.5.4. Quality adjustment – Detailed information

For quality adjustment, as it is required by EC Regulation No 1334/2007 (repealed and replaced by Regulation (EU) 2020/1148), a case-by-case approach is adopted and therefore group of products by group of product.

In details, methods adopted to manage quality adjustment issues are:

Direct comparison:

  • for clothing and footwear, when the product offers in two consecutive months are evaluated comparable on the basis of criteria defined by ISTAT. In the month when the replacement is done, the elementary price is flagged, the reason of the replacement is ticked and the direct comparison is carried out directly by automatic procedures;
  • in some cases for processed or fresh food (for which prices are monthly collected) when, for a list of product defined by ISTAT, the change of the product offer is due exclusively to a change of brand, and therefore the product offers in two consecutive months are evaluated comparable. In the month when the replacement is done, the elementary price is flagged, the reason of the replacement is ticked and the data collector has to register the price of the product offer available in the previous month as the price of the previous month of the new product offer;
  • for products for which best seller approach is adopted such as electronic games, DVD movies;
  • for fresh food and fish, for which prices are collected twice a month, in the month when the replacement is done, the elementary price is flagged and the reason of the replacement is ticked (quantity collected or collection unit; brand and variety are not take into account). 
  • for most of the products for which prices are centrally collected by ISTAT, it allows direct comparison inside each specific stratum.

A combination of bridged overlap and class mean imputation:

  • in some cases for clothing and footwear, when the product offers in two consecutive months are evaluated not comparable on the basis of criteria defined by ISTAT. In the month when the replacement is done, the elementary price is flagged, the reason of the replacement is ticked and an automatic procedure estimates the price of the previous month of the new product offer in order to build the bridge between the two consecutive months. To calculate the price of the previous month, the rate of change m/m-1 of the geometric mean of the micro indices is used, within the same product of the basket in the same town, both of the product offers for which no replacements take place and for the product offers for which direct comparison was carried out. The information available within the same product, in the same town is used only if at least for the 50% of the sample for that specific product aggregate in that specific town, prices are collected for the same product offers of the previous month (indeed without replacements) or for product offers for which direct comparison was carried out. If the latter condition is not respected, the overlap approach is adopted.

Overlap:

  • for the other products, for which prices are collected monthly at territorial level (except clothing and footwear, products for which prices are collected centrally, fresh and processed food for which direct comparison is carried out). In the month when the replacement is done, if the data collector has collected the price of the previous month of the replacing product offer (or the seller is able to provide this information) this information is used and the elementary price is flagged. If the data collector has not collected the price of the previous month of the replacing product offer (and the seller is not able to provide this information), an automatic procedure estimates the price of the previous month of the new product offer using the current price of the replacing product offer (link-to-show-no-price-change). However, in order to avoid (when it is possible) the link-to-show-no-price-change, the software for the data collection allows ‘booking’ a product offer when the sampled product offer is on the way to exit the market.

Explicit quality change:

  • it is adopted only when the difference between a product offer in a month and a product offer in the following one, is due exclusively to packaging and the replacing product offer is actually new. In this case the data collector has to specify the reason of the replacement and to insert the information about the quantity of the new product offer; the elementary price registered is flagged. An automatic procedure calculates the price of the new product in the previous month taking into account the difference between the new and the old quantity collected. If the quantity increases or declines by 50% as compared to the previous month, the procedure estimates the price of the new product offer in the last month, calculating the cost of the new quantity on the base of the previous price. If the new one is different from the previous one of an amount that is more than 50%, the procedure calculates the price of the previous month of the new product offer as in the case of overlap when the link is built to show no price change). When the replacing product offer was already available in the previous month, the situation is ascribable to cases when it is adopted the overlap approach.

For the time being, no change has been implemented following the recommendations on bridged overlap. We plan to introduce the appropriate changes next year.

18.5.5. Seasonal items

Standards of the Commission Regulation No 330/2009 on treatment of seasonal items were adopted by the Italian HICP with the index of January 2011.

The implementation regulation entailed changes both in Italian HICP and national CPI compilation procedures (new standards were introduced for national CPI, too).

For the Italian HICP and national CPI compilation the following classes/groups fall under the scope of Commission Regulation No 330/2009 and then with Commission Implementing Regulation (EU) 2020/1148 of 31st July 2020 (that repealed Regulation 330/2009), where minimum standards are established to deal with seasonal products in the HICP:

  • 0.1.1.6 Fruit,
  • 01.1.7 Vegetables,
  • 0.3.1 Clothing,
  • 0.3.2 Footwear.

The class 0.1.1.3 Fish does not fall under the scope of the regulation: for the time being, according to the EC Regulation, quantitative evidences do not show seasonal behaviour in the products belonging to this class.

18.6. Adjustment

Not applicable.


19. Comment Top

None.


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