Harmonised index of consumer prices (HICP) (prc_hicp)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Statistics Finland (SF)

Time Dimension: 2020-A0

Data Provider: FI1

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

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1. Contact Top
1.1. Contact organisation

Statistics Finland (SF)

1.2. Contact organisation unit

Social Statistics / Consumers and livelihood

1.5. Contact mail address

Street address: Työpajankatu 13, 00580 Helsinki, FINLAND
Postal address: FI-00022 Statistics FINLAND


2. Metadata update Top
2.1. Metadata last certified 12/11/2020
2.2. Metadata last posted 22/01/2021
2.3. Metadata last update 31/01/2020


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

-

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

All major regions are covered. Cross-border purchases are currently not treated in line with the HICP recommendation.

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

See the HICP database

January 1996

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. 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.

Regulations:

  • 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

Not available


7. Confidentiality Top
7.1. Confidentiality - policy

Statistics Act (Finland), section 10. defines followingly "When data collected for statistical purposes are being combined, stored, destroyed or otherwise processed it shall be ensured that no person’s protection of private life or personal data, or business or professional secret shall be endangered."

In practice this means that all item level information (weights, prices, descriptions) are treated as confidential.

 



Annexes:
Statistics Act
7.2. Confidentiality - data treatment

The data is confidential until it is published on the internet. The use of data is restricted by usage rights. All persons employed by Statistics Finland have signed a pledge of secrecy, where they have obliged to keep secret the data prescribed as confidential by virtue of the Statistics Act or the Act on the Openness of Government Activities. The access to the data is limited to the certain part of the staff of Statistics Finland.

List of person with rights to the data before the publication is updated by secretary of Price Statistics unit and confirmed by the Director of Economic and Environmental Statistics.

Confidentiality of data collected for statistical purposes is decreed in the Act on the Openness of Government Activities (621/1999) chapter 6, section 16-17.

European Statistics Code of Practice  has been implemented to the production of HICP/CPI.



Annexes:
Act on the Openness of Government Activities


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

confirmed every autumn in connection with the planning of activities. The release calendar for the coming year is made available to users in December.

 

8.2. Release calendar access

Statistics Finland publishes the annual release calendar on the web-page.



Annexes:
The release calendar
8.3. Release policy - user access

Upublication dates. The release calendar of statistics contains information on the timing of the future releases. The calendar also contains direct links to the already published statistical releases and publications. The statistics are released on the web site of Statistics Finland on a pre-determined date given on release calendar.


9. Frequency of dissemination Top

Monthly


10. Accessibility and clarity Top

HICP is published mainly via internet-page. Statistics home page contains information on

  • the monthly publications,
  • the handbook for users,
  • the weight structure for current year,
  • the description of the statistics and
  • the description of the methods.

It also contains direct links to the StatFin-database service where the monthly indices are published. with two decimals. HICP release is published in Finnish, Swedish and English.


Access to the micro-data is very limited meaning that a user needs a licence in order to use colelcted data. If the licence is granted by the reserach services, the data is first anonymized so that no outlet names nor specific information of collected items are given. In addition, the delivered micro data is limited to the information concerning only the prices, the package size and information of the price type (normal, sales prices or new product offer.) More information of the practices in research services is available in the web page Charging basis and prices. 

 



Annexes:
home page of CPI
Online database
Charging basis and prices
10.1. Dissemination format - News release

A shorter press release for CPI and HICP is issued each time results are published. The press release is a summary of the changes in consumer prices. Intention is that release provides information on the most remarkable changes in CPI and HICP. 

A longer press release is issued once a year describing changes made in the beginning of statistical year : changes in the data collection  (new and vanishing products), methodological changes etc.

Information on the press releases is shared just after the release is published for the press via email as a RSS-feed.

Twitter is used in sharing the information for the greater audience. Official tweets are done under @tilastokeskus- user id.



Annexes:
RSS-feed
10.2. Dissemination format - Publications

Consumer Price Index and HICP-monthly results are published on the consumer price index homepage at www.stat.fi >> Key Figures >> Inflation.

10.3. Dissemination format - online database

Statfin-database service provides tables where user may extract the results as a timeline. Accuracy of the tables differs a bit depending of the lenght of the timeline. The latest information is published in tables

  • 11xb Consumer Price Index 2015=100  and
  • 11xh Harmonised Index of Consumer Prices (HICP) and Harmonised Index of Consumer Prices at Constant Taxes (HICP-CT) 2015=100
  • 11xu Special Aggregates 2015=100

 

Database service provides also tables for

  • Cost-of-living index that dates back to 1914
  • Average prices of liquid fuels, 

 



Annexes:
The link to the online database
10.4. Dissemination format - microdata access

Due to the Statistics Act, micro data may be used for scientific purposes but only in an anonymised form and according to the general policy regarding confidentiality.

Hence, access to the micro-data is limited and user need to apply for a licence in order to be able to explore micro data and individual observations. If/when the licence is granted, data is anonymized so that no outlet names nor product details are given. In addition, information concerning the collected prices is limited to price, package size and information of price type (normal, sales prices or new product offer.) More information about service practices is available on web page.



Annexes:
Research data
Application for a license to use statistical data
10.5. Dissemination format - other

The results of the HICP, as well as results for the EU-Member states at a finer level of detail, are available on the homepage of the Statistical office of the European Union (Eurostat).

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 papers on the Consumer price index. CPI, and HICP are published in the following publications:

  • Consumer Price Index 2015=100 Handbook for users
  • basic concepts and definitions are availabe on statistics homepage
  • research studies are published in web-page "Methodological development work" 


Annexes:
Handbook
Definitions
Methodological development work in CPI
10.7. Quality management - documentation

CPI-RELEASE contains overall information on the quality management. Quality and Methodology Information-chapter gives an overview notes that are not specific to each release of data. They pull together qualitative information on the six Eurostat criteria of quality (relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability and coherence) and address relevant Key Quality Measures. They also provide a summary of methods used to compile outputs and describe the methods' impact on the quality of estimates produced.

Compliance Monitoring report for 2012 is available in Eurostat's web-page



Annexes:
HICP methodology -- see Compliance Monitoring Reports


11. Quality management Top

See CPI 2015=100 Handbook for users: http://www.stat.fi/tup/julkaisut/tiedostot/julkaisuluettelo/yksk39c_201500_2016_16193_net.pdf

and descriptions in chapter 18.4 Data Validation

 

 



Annexes:
CPI 2015=100 Handbook for users -- see chapter 18.4 Data validation
11.1. Quality assurance

11.1.1. Quality management - Compliance Monitoring

Compliance Monitoring

11.1.2. Quality assurance - national specifics

11.2. Quality management - assessment

11.2.1. Compliance monitoring - last report and main results

Compliance Monitoring

11.2.2. Quality assessment - national specifics

Same QA methods are used for national CPI as for HICP.

Special importance is attached to the transparency of data collection and computation methods. The concepts and methods of the HICP are developed according to international standards and they rely on the experiences of all EU member states in the field of consumer price statistics. Improving the quality and the comparability of the HICP is a permanent process.


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 used nationally by various user groups especially for the following three purposes:

  • Inflation measure;
  • Convergence criteria;
  • Indexation of financial instruments by using the HICP as a compensation
  • benchmark.

However, there is only limited use as compensation benchmark at the national level of
the HICP.

Main users of the HICP are Bank of Finland and Government authorities.

12.2. Relevance - User Satisfaction

The meetings of national group of CPI Experts are arranged twice a year. The group of CPI/HICP expert consists of representatives from Ministry of Finance, banking sector, research institutes and Finance Finland. The group of CPI/HICP expert provides user feedback and perspective to the utility of the information. This feedback is valuable especially when the aim is to improve CPI and HICP coverage, methods etc. The Group has no direct influence on the HICP, it may only share remarks of the interest group.

 



Annexes:
Users of statistical data ever more active
12.3. Completeness

HICP indices are produced for all 5-digit eCOICOP-levels for Eurostat. eCoicop indices at 6- and 7-digit level are produced for national purposes.

Regarding ECOICOP sub-indices, especially at 5-digit level, certain indices are not provided because 

  • they are not included in the coverage of the HICP, OR
  • they were excluded for conceptual reasons (e.g. life insurance) OR
  • the degree of methodological harmonisation is not yet sufficient OR
  • because their consumption expenditure of the private household sector in Finland is very low.


13. Accuracy Top
13.1. Accuracy - overall

Some  commodity level accuracy figures have been calculated and the results are taken into account when deciding the number of price observations for each commodity. The bias in weights is the bias due to the small samples in HBS, specially for region Åland.

The Consumer Price Index is always based on some kind of a sample of the products and services available to consumers. The randomness of the samples is reduced by the fact that the statistics are based on a panels. The use of panel ensures that the produced price changes are accurate enough.

Following sources for bias may be identified:

  1. substitution bias:
    • The Laspeyres fixed-weight index formula does not include any change in consumption due to a change in relative prices. For example, if the price of chicken drops in proportion to beef, the demand for chicken will rise as the demand for beef falls. An index that uses the weights of the comparison period does not take this into account.
    • The magnitude of the substitution bias depends on the households’ reaction to the change in prices and the magnitude of the price changes. The less frequent the adjustment in the index weight structure, the greater the substitution bias.
    • The substitution bias is not estimated as being very significant at the overall index level.

  2. bias caused by new products:
    • A Consumer Price Index using comparison period weights may be particularly prone to bias when new products, such as consumer electronics, enter the market. If prices fall abruptly and this causes a great rise in demand, a fixed-weight index is not, perhaps, capable of taking this into account sufficiently quickly. In such cases, a single product may have a noticeable effect on the year-on-year change in the Consumer Price Index.
    • new products are included in the index once a year as weights are updated or when it is necessary to replace vanishing products with new one. Thus new products will probably not form an essential source of bias

  3. bias arising from the outlet sample:
    • The sample of outlets in the Consumer Price Index is checked and updated annually. Within a year, the selected outlets will remain the same through-out the index calculation If households start to favour a certain type of outlet, such as big hypermarkets instead of smaller shops, this can be a potential source of bias if the price development of products differ in different types of outlets.
    • this bias is not likely to be considerable as more and more transaction data (scanner-data) is introduced to the production of HICP/CPI.
    • Also the outlet sample is revised and updated annually. The significance of the bias arising from the retail outlet sample is not likely to be very high in the Finnish Consumer Price Index, which draws on quite a large number of outlets (around 2,000) in proportion to the country’s size. Moreover, outlets that close down are replaced with new ones, taking into account the market situation of the collection area. A change of a collection outlet does not cause a change in the index

  4. bias caused by quality change:
    • Any changes in the quality of goods and services are carefully examined when products are replaced due to the removal from the outlet’s selection OR due to the fact that product is outdated and need to be replaced by a new model that better represents the product group in question. 
13.2. Sampling error

  The item sample is formed utilising statistics on retail trade sales, the Household Budget Survey and other sources. The main sampling methods are:

  • Selection of the most sold products in terms of sales value (e.g. daily consumer goods).
  • Purposive sampling based on expert views in the ab-sence of comprehensive sales data (e.g. optical industry products and restaurant food)
  • Probability proportional to size (PPS) sampling, stratified by product and focusing on high sales values1 (e.g. magazines )
  • Other methods (e.g. cluster sampling by brand and price group for new cars). 
  • OR no sampling that is the case when complete scanner-datasets are obtained in price collection 

The outlets from which the data for the Consumer Price Index are collected are selected to represent the structure of retail trade as closely as possible with regard to the size of central retail corporations and outlets. The aim is to take regional differences into as well.

Statistics Finland’s Register of Enterprises and Establishments is used as the sampling frame. The outlets included in the collection are randomly sampled from the frame  ensuring that different size categories are represented. 

It is not possible to use any of the statistical sampling methods for selecting specialised stores for the price collection, so Statistics Finland’s interviewers choose suitable outlets from their area according to specified criteria and by drawing on their knowledge of the area.

No item sampling, nor outlet sampling is used in cases where the scanner-data is obtained. This covers following commodity groups:Food, alcoholic beverages, pharmaceutical products and wireless telephone services

Various sampling methods are used to create a commodity- and an outlet specific samples, thus a sampling error cannot be formally calculated nor estimated although there are sampling-related errors. It can be assumed that the monthly development of prices is reflected very accurately in both the overall index and aggregated sub-indices using this non-random procedure.

To keep the unknown sampling error as low as possible, scanner-data is increasingly utilised nowadays . 

13.3. Non-sampling error

Non-sampling errors are not quantified in HICP construction. Continuously improving the methodology is however intended to reduce non-sampling errors to a minimum.

  • non-response error is very low because respondents are reminded of their obligation to reply to the questionnaire or give needed information


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 comparability over time is ensured. There are not any statistical breaks in the HICP series due to changes in the methods.

Changes in the consumption and shopping habits are incorporated every year.

 

15.3. Coherence - cross domain

  1. Methodology: No methodological differences. Same methodology is used for CPI as for HICP
  2. The territorial and population coverage: Same coverage in both statistics
  3. Product coverage; Coverage is same expect in cases of following commodities
    1. owner-occupation,
    2. games of chance,
    3. interests on consumption and other credits,
    4. fire insurance on owner-occupied dwellings,
    5. the vehicle tax and fishing and hunting fees.
  4. Differences in the treatment of product groups: All product groups are treated similarly

 

 

 

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

The national CPI  is not revisable statistics.

17.2. Data revision - practice

In principle, national CPI is not revisable. In the past 10 years, HICP has not been revised ever.

 


18. Statistical processing Top
18.1. Source data

18.1.1. Weights

The weight structure of the Consumer Price Index is based on the data in the private consumption expenditure of National Accounts dating back two years. The figures on private consumption expenditure in National Accounts are based on the latest Household Budget Survey. National Accounts data on consumption expenditure is available at 5-digit coicop level. Where the National Accounts’ division of consumption items is not accurate enough, the weight of the sum level is divided into sub-items, primarily with the help of sales data and other statistics provided by Statistics Finland or other public authorities, such as The Finnish Institute for Health and Welfare, The Finnish Transport and Communications Agency and the Bank of Finland.  In addition, other sources are used when defining the weights for sub-items. The auxiliary sources are e.g. Household Budget Survey for the definition of sub-items.

Expenditure on narcotics and prostitution are removed from the private consumption expenditure in National Accounts for the Consumer Price Index. In addition, the consumption expenditure of non-profit institutions is removed from the private  consumption  expenditure  in  National  Accounts  and  the  consumption  expenditure  of  foreigners  in  Finland is added to it.

The  overall  consumption  calculated  from  National  Accounts  is  adjusted  with  a  separate  method  for  calculating  weights  for  the  housing  commodity  group.  Vehicle tax and interest on consumer credits are added to the value weight of the Consumer Price Index. In addition, compensations paid are deducted from the value weight of  insurance  premiums and health care fees,  and  the  difference  in  the  measurement  of  financial  services,  as  well  as  addition  of  the  acquisition  costs  of  motor  vehicles  are  taken  into  consideration. After this, the value weights are price-updated to the level  of  the  calculation  year  with  commodity-specific  price indices. Weights are produced for all 480 (approx) items in the basket.

For some items, weights are available at a more detailed level, as so called internal weights. For example, 12.7.0.1.1 Redemption of documents, are considered as one item. In this case internal weights are available for each document included in price collection. Internal weights are defined also for commodities:

Weights are updated annually concerning the 4- and 5-digit eCoicop-classes. In the more detailed level, 6- and 7-digit eCoicop weights are updated once a year or every third year concerning the 03.1.2 Garments, 03.1.3 Other articles of clothing and clothing accessories, 03.2.1 Shoes and other footwear, 05.1.1 Furniture and furnishings, 05.5.2 Small tools and miscellaneous accessories, 05.6.1 Non-durable household goods, 06.1.2 Other medical products, 06.1.3 Therapeutic appliances and equipment, 06.2.3 Paramedical services, 07.2.1 Spare parts and accessories for personal transport equipment, 09.1.4 Recording media, 09.3 Other recreational items and equipment, gardens and pets, 09.4 Recreational and cultural services, 09.5 Newspapers, books and stationery, 09.6 Package holidays, 11.1 Catering services, 11.2 Accommodation services, 12.1 Personal care and 12.7.Other services.

When scanner data is available, weights are updated either annually (pharmaceutical products, alcoholic beverages) or monthly (food, daily durables, wireless telephone services). This distinction depends on the calculation method in use. 

When using scanner data, retailer-specific weights are also applied in the calculation of indices, if appropriate. These weights are checked and updated annually. 

Regional weights are updated after the latest results are received from HBS. Exception to this are the regional weights for the rents that are updated annually.

18.1.1.1. Compilation at elementary aggregate level

The weights of the 4- and 5-digit level are acquired from National Accounts. These levels are further divided into sub-classes, primarily with the help of the sales data and other statistical information produced by other statistics such as Bank of Finland’s statistics, housing statistics, financing statistics and Household Budget Survey.

The lowest aggregation level where explicit weights are introduced, is 7-digit COICOP. Below the 7-digit coicop some commodities may contain more specified weights:item-specific /retailer-specific/customer-type/regional weights/service-provider specific or size of family weights. One example of the item specific internal weights is the Local bus journeys (Passenger transport by road) where prices are collected concerning the one-way-ticket, monthly season ticket, annual season ticket etc. These internal weighting information are obtained from e.g. sales data provided by companies or service providers. The updating of internal weights varies: some weights are updated annually and some weights are updated less frequently (e.g. every fifth year). 

Main data sources that are used for the weights are explained in chapter 18.1.1.

HBS is used for the regional 4-digit ecoicop-weights.

Business Register or sales data of central corporations are mainly used for the retailer-specific weights.

18.1.1.2. Compilation of sub-index weights.

The overall consumption calculated from National Accounts is adjusted with a separate methods for calculating weights for the housing commodity group. Vehicle tax and interest on consumer credits are added to the value weight of the Consumer Price Index. In addition, compensations paid are deducted from the value weight of  insurance  premiums and health care,  and  the  difference  in  the  measurement  of  financial  services,  as  well  as  addition  of  the  acquisition  costs  of  motor  vehicles  are  taken  into  consideration.  

Sources for the weights are the latest HBS, statistical information produced by other statistics, Bank of Finland statistics, sales data of central corporations, etc.

18.1.1.3. Reference period higher levels

Every year, the weighting pattern for the HICP is updated based on national accounts data up to the year before last (t-2) and then adjusted to the price development up to December of the previous year (t-1).

18.1.1.4. Weights - plausibility checking

The original, elementary aggregate weights are calculated from collected data by dividing the the 4-digit coicop weights obtained from National Accounts. Information that is utilised for defining the distribution of the lower levels are other sources of information, such as scanner data and other types of salesdata, other statistics and similar kind of information.

Price-updating is done by multiplication of original weight and its price relative. Then these different structures are compared in the weight period. In this comparison, the impact of inflation is inspected in weight structures. If the price development is not constant in elementary product groups, it may change the distribution in weight shares in COICOP divisions and subclasses.

Then these next year period weights are compared to current year weights. For example, the 2019 price-updated weights were compared to 2018 price-updated weights. By comparing these two years, the changes in CPI weight structure can be analyzed and checked.

In Finland, seasonal products are treated with class-confined seasonal weights. For example, strawberry is a seasonal product in Finland and its season is in July. The plausibility of price-updated seasonal weights is checked by tabulating weights by month. The aggregated lowest published levels of COICOP (in the case of Finland, COICOP5) are fixed for the whole year. In July, strawberry has its own weight and in other months its weight is divided to other COICOP6 groups. The COICOP5 weight remains constant.

18.1.2. Prices

The manual price collection includes on the one hand the regional price collection by price collectors in shops all over Finland and on the other hand the central price collection, which takes place mainly as a survey on the internet. The additional use of scanner data sources allows the statistical offices to increase the number of monthly price observations significantly. These datasets are processed centrally in CPI-team.

The prices for the Consumer Price Index are collected monthly between the 10th and 20th days of month. The reference point of time varies in the centralised collection (e.g. the monthly average price or the price halfway through the month). The prices for all the daily consumer goods are collected every month. The prices for seasonal products are collected when they are generally available (in-season) and when their sales volumes are sufficiently large.  For example, prices for cultivated strawberries are collected only in July. Scanner data often includes price observations from all month but in some cases from the first two or three weeks of a month.

18.1.2.1. Data Source - overview  

Main data sources are

  1. regional price collection performed by price collectors
  2. centralised data collection in the CPI-team
  3. scanner-data


Annexes:
The updated version of detailed structure

18.1.2.2. Scanner data - general information

Following scanner-datasets are used in the production:

  • 06.1.1.0 Pharmaceutical products covering sales of all pharmacies in Finland.
  • 02 Alcoholic beverages sold in Finland
  • 01 Food covering sales of every major retail chain
  • other daily products: 05.4.0.3, 05.5.2.2, 05.6.1.1, 05.6.1.2, 09.3.3.2, 09.3.4.2, 12.1.2.1, 12.1.3.1, 12.1.3.2, 12.3.2.2  -- 45% of the total market share

See excel file for the

  • 08.3.0.2 wireless telephone services and 08.3.0.3 Internet subscription charge>> operators provide information regarding total sales and number of subscriptions by each subsription
  • 07.3.1.1 / Short-distance train journeys and long-distance train journeys >> service provider delivers us average prices for the most common train journeys and gives regional sales values for the weights

 

 

18.1.2.3. Bulk web scraping - general information

This collection method is not in use in Finland.

18.1.3. Sampling design and procedure

18.1.3.1. Sampling design: regions - general information

The Consumer Price Index for the whole country is compiled from indices by major regions. Finland is divided to six regions in the NUTS2 regional division. Major regions are Uusimaa, Southern Finland, Eastern Finland, Western Finland, Northern Finland and Åland. The weights of the indices by major regions are formed directly from the Household Budget Survey having regional division at NUTS2 level. All regions are included in the sample

18.1.3.2. Sampling design: outlets - general information

In general, the outlet sample shall reflect consumer behaviour. For goods, different market shares of the outlet types are taken into account by explicit weighting. For price collection, the Finland is systematically divided in 6 regions. In every region, outlets (assigned to relevant outlet types) with a high relevance for private consumption are selected. No outlet category is excluded.

Following outlet types are distinquished:

  • mini-markets, supermarkets and hypermarkets for daily products collection;
  • department stores, specialist shops and other retail shops for consumer durables ,
  • internet trade and public or private service provider for other commodity groups.

Concerning the scanner-datasets (food, durables, operators), no commodity, outlet or regional sampling is done. Hence, all data is utilised when possible. 

18.1.3.3. Sampling design: products - newly significant goods and services

New, significant goods and services are added to the basket annually. New commodities are identified by a rolling series of commodity reviews conducted principally based on market sales information and SF household survey data together with personal experience of the monthly collection of prices. These reviews are supplemented by the proposals made by central office staff. All suggestions are investigated to identify availability, expenditure etc and final decisions are based on a number of factors, including:

  • Amount spent on a particular item or the group of items.
  • Ease of finding and pricing the product.
  • Availability throughout the year.
  • Variability of prices within a class.
  • Analysis of balance across the basket.

Once identified, the first step of introducing the item is to define a product specification and to decide the appropriate collection method.  If similar kinds of products are already collected, then the new items will be priced in outlets that are already part of the sample. Otherwise outlet is selected first from the Business register's list of outlets.

 

18.2. Frequency of data collection

Price data is collected every month.

18.3. Data collection

18.3.1. Price collection surveys

Consumer Price Index data is collected both centralised at Statistics Finland office and by Survey interviewers (price collectors). Complementary datasets, so called scanner-data, were implemented to the production of CPI in years 2017-2020.

Statistics Finland's interviewers collect altogether around 21 000 prices on nearly 470 commodities from approximately 2 200 outlets for the Consumer Price Index. To measure the price development, every month they collect the prices of the same products in the same outlets across the whole country, mostly using mobile data capture devices with integrated plausibility checks. Price collectors perform product replacement when a product is no more available in outlet. CPI-team decides replacement of an outlet and instructs price collectors when this change need to be carried out.

In addition, about 1000 items of prices are gathered by centralised collection. Centrally collected data contains prices that are collected either from internet pages, price lists or administrative web-pages. This centrally collected data is supplemented with several scanner-datasets having 1 000 to 6 mil. price observations by month. Amount of observations depends on the data in question. 

 

18.3.2. Timing of price collection

Prices are collected, in the field, between 10th and 20th of current month.

The price collection period is longer for products whose prices fluctuate considerably during the month. These are mainly centrally collected prices such electricity, clothing. Scanner-datasets cover in almost all cases all sales of a month. This means that data collection period is full set of days in the month. In some cases only first three weeks are contained in the scanner dataset.

18.4. Data validation

Plausibility checks are built into each stage of processing to prevent data entry errors by issuing warnings if implausible data are entered. Critical data that have been entered by price collectors must be confirmed and/or be specified by specially trained staff of the Statistical Offices. The most peculiar results after the calculation are checked by appropriately trained staff of the Statistical Offices

Data are fed through a series of automatic validation checks both out in the field and centrally. These are followed up with manual scrutiny of the data which can result in changes. Mostly the decisions are about whether or not to include a price quote in the compilation of the index. Based on the staff decision, observation is excluded or included in the calculation or staff can correct a quote.

A number of factors are used to highlight potentially incorrect prices such as price change, price range, correct entry of metadata including coding information. 

Scanner-datasets do not have similar kind of errors as traditionally collected data therefore it is taken as such.

18.4.1. Data validation - price data

There are different procedures to detect data entry errors.

  1. Price collectors have a mobile app that performs plausability checks at the same time as the  data is recorder to the application. If the warning or error-signal is received, price collector need to check the recording and correct it according to the instructions received from the app
  2. collected information is transmitted from the tablet to the central office after data collection period ends. As the data is updated to the database, several automatic checks are applied such as quantity and quality adjustment procedures, as well as treatment of missing prices.
  3. All observations that are collected by price collectors are re-checked at the central office with pre-defined common rules that belong to the  production system. Central staff executes these separeate check several times in a month and at least once before the Flash HICP calculation and HICP/HICP_CT calculation. This way critical data entries are once again confirmed. The decisions about whether or not to include a price quote in the compilation is mostly done by central staff.
  4. All centrally collected prices are validated at the moment of data is collected. Explicit quality adjustment methods are applied for durables. The most common methods are option pricing, supported judgmental quality
    adjustment, direct price comparison and bridged overlap.

CPI-team ensures the consistency of the price information. This is done with the checking lists and manually observing the observations. Detected errors are corrected immediately after they are discovered. Then, the indices
are recalculated and published.

 

18.5. Data compilation

18.5.1. Index formulae

The Finnish HICP is a Laspeyres type index covering the ECOICOP/HICP.

Unweighted Jevons is used mainly to aggregate price change of observations to elementary aggregate level. Only exception to this are the scanner-datasets, where all the observations are weighted and following formula is used:

  • pharmaceutical products -- Geometric Laspeyres (=log-Laspeyres)
  • alcoholic beverages -- Geometric Laspeyres
  • wireless telephone services and internet subscription fees -- Fisher
  • food, non-alcoholic beverages, daily products  -- Törnqvist

Use of log-Laspeyres, Fisher and Törnqvist are in line with the Regulation No 2016/79 because it does not restrict the use of these formulas.

The following number of decimals (behind per cent figures) is applied for

  • surveyed prices: 2
  • weights: exact
  • compilation: exact, no truncation or rounding
  • transmission of index figures: 10 decimals,
  • compilation of rates of change: 2 decimals (truncated)
  • transmission: exact
  • publication: 2

Official figures are always cut to two decimals, usually during the last step of calculation prior to publication. Year to year and monthly rates of change are calculated by using these published and therefore already cut figures.

 

18.5.2. Aggregation method

The price ratio by an item is calculated of the prices between the reference and the base period. The price base of the HICP is always the month of December of the year before the reference year (t–1).

Then an elementary index is computed based on the geometric average of the price ratios, so called Jevons, for each product type (coicop 7-digit) by region.

After this, the regional elementary aggregates are weighted to the higher levels of the index nomenclature using Laspeyres formula.

18.5.3. Chaining and linking method

 HICPs are chain-linked annually through the relevant December value (Laspeyres chain index concept).

The December of the previous year is the so-called chaining point for the Consumer Price Index. The point figure of the chaining month is carried forward with the calculated monthly change between the chaining point and the comparison month. This is done in every level of the index.

Splicing is not used for the time series of the Finnish HICP.

18.5.4. Quality adjustment

The Finnish price statistics uses the following quality adjustment methods:

  • Quantity adjustment (=Package Size Adjustment) can be used for any good where a change in size/ weight is relevant to the quality of the product and where we do not pre-specify a weight/volume - e.g. a kilo of apples. Adjusting the package size quantity is necessary when the quantity of a packaging unit has changed while holding its quality constant. It is crucial for the application of this method that the quantity directly and  proportionally affects the monetary value of the product. Thereby, also “hidden” price increases (through reduced quantities at the same price) are captured.
  • Hedonic regression is currently applied only to second hand cars. Hedonics are particularly applied to calculate the price increase of products which features and properties (=characteristics) has strong effect on the price. The hedonic quality adjustment is a statistical procedure which calculates by means of a regression the influence of individual product characteristics such as age, driven miles, etc.
  • Direct price comparison may be used for virtually any good or service. The direct price comparison can be applied if a replacement model of equivalent quality is available. It is an extreme of a quality adjustment method as the prices of both products are directly compared, hence the share of quality is zero percent and the price change fully enters the index calculation. Particularly for technical products it is precisely defined, for which characteristics of models explicit quality adjustment should not be applied.
  • Class mean imputation may be used for any good or service. Although the number of times this method is used varies year on year.
  • Judgmental quality adjustment: For some product changes, none of the previously mentioned methods is able to identify in which dimension the price difference between the replaced model and the new model is affected by quality differences. In this case, experts (CPI staff) are asked for a subjective judgment. Based on their experience (and specialist knowledge), they determine the share of the price difference due to quality differences.

Importance by prevalence of the method in use are in Finland: a) quantity adjustment B) direct comparison C) class mean imputation. Option costing and overlap pricing are used only occasionally.

18.5.5. Seasonal items - general information

Generally, if prices of seasonal items are missing due to out-of-seasonality then its weight is allocated to the other commodities in this specific 5-digit commodity group. This method is called class-confined weights.

Fish, fruits and vegetables are not treated seasonal at the moment in Finland because these are available in outlets during the whole year. Only seasonal product in 01.1  Food group / Fruits is strawberries. Most of the sales realises during the summer months in June, July and August. Reason to this is that these can be cultivated in Finland only on summer time. Share of the imported strawberries is still very low.

18.6. Adjustment

Not applicable.


19. Comment Top

None.

 


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Annexes Top
Updated version of the inventory