Consumer price index

Name: Consumer price index
Topic: Prices and price indices

Division for Price Statistics

National level only

The survey is conducted monthly and is published on the 10th of each month, approximately 10 days after the reference month.

The Harmonized Index of Consumer Prices (HICP) for Norway is reported to EUROSTAT every month.

Collected and revised data are stored securely by Statistics Norway in compliance with applicable legislation on data processing.

Statistics Norway can grant access to the source data (de-identified or anonymised microdata) on which the statistics are based, for researchers and public authorities for the purposes of preparing statistical results and analyses. Access can be granted upon application and subject to conditions. Refer to the details about this at Access to data from Statistics Norway.

The purpose of the CPI is to measure the actual price development of goods and services demanded by private households.

The survey was established in 1960 and replaced the Cost of Living Index, which had been published since 1914. In 1999 the process of revision and the methods of calculations were modernised and improved, and the classification of consumption was changed to Classification of individual consumption by purpose (COICOP).

In 2005 the sub-index for food and non-alcoholic beverages was improved, which resulted in a sub-index exclusively based on the use of electronic scanner data. In 2011, the National Accounts data were introduced as a weighting source, and replaced the Household Budget Survey which had been used since 1960. The price reference month changed from July to December. From 2016, the classification of consumption was extended and are now named ECOICOP (European Classification of Individual Consumption by Purpose). Additionally, the classification by delivery sector was revised in that year.

The Harmonized index of consumer prices (HICP)

The primary purpose of the statistics is international comparisons of price developments.

In 1991 the Treaty on European Union (the "Maastricht Treaty") laid down various convergence criteria that increased the demands for comparable price indices. An international cooperation started in 1993 where the objectives were to obtain comparable measures of price development. HICP was first published in 1997. HICPs are produced in all Member States in addition to Iceland, Switzerland and Norway.

The Norwegian HICP is founded on the Norwegian CPI for which the process of editing and the methods of calculations were modernized and improved in 1999. See the history of the CPI in the section above.

The CPI has its most advanced users in the public sector (ministries, the Central Bank of Norway) and in the financial sector. Labour organisations and employers' federations are other important users. The CPI is widely used to index payments such as different contracts. Within Statistics Norway the CPI is an important input to the National Accounts. It is also used as a deflator for the index of Retail Sales. Primary data is also used in analysis and research within Statistics Norway.

The Harmonized index of consumer prices (HICP)

The Central European Bank is the most frequent user of the HICP. The Eurozone index is used as a main indicator for monetary policy management for the Euro-zone. Statistics Norway reports the Norwegian HICP to Eurostat on a monthly basis, and the Norwegian publication of the HICP is considered preliminary until the Eurostat publication.

No external users have access to statistics before they are released at 8 a.m. on ssb.no after at least three months’ advance notice in the release calendar. This is one of the most important principles in Statistics Norway for ensuring the equal treatment of users.

Some data are collected from the Construction Cost Index for Residential Buildings, the price indices for business activities (car rental, other transport services and legal activities) and from the Wage Statistics. The CPI is an important input to the National Accounts. It is also used as a deflator for the index of Retail Sales.

The Harmonized index of consumer prices (HICP)

The traditional CPI is the foundation of the HICP.

The statistics are developed, produced and disseminated pursuant to Act no. 32 of 21 June 2019 relating to official statistics and Statistics Norway (the Statistics Act).

With the exception of the computation of the owner-occupied housing consumption, the CPI generally follows the same legislation as the Harmonized Index of Consumer Prices (HICP). More about EUROSTATS regulations: Legislation related to the HICP (ec.europa.eu)

The population is defined as all goods and services offered to households in Norway. Prices and expenditure shares of a sample of products and services are being measured. Expenditure shares (weights) are based on data obtained from the National accounts, while prices are collected each month from a representative sample of retail and service outlets.

This sample is selected from all outlets in Statistics Norway's Business Register defined as the industries 45, 47, 55, 56, 77, 95 and 96 (SIC07 -The Standard Industrial Classification). In addition, prices are collected with unequal frequency from different outlets or parties (including households) mainly on services within the industries 35, 49, 50, 51, 53, 60, 61, 65, 66, 69, 77, 79, 85, 86, 88, 90, 91 and 93. Household samples are selected from the "Central Population Register".

The Harmonized index of consumer prices (HICP)

The sample of goods and services is nearly fully harmonized with the CPI sample. The cost for owner-occupied housing consumption (that consists of about 14 per cent of the CPI) is not included in the HICP. In addition games of chance and life insurance are not included. Due to the restribution of the weights of these omitted areas, the absolute weights at the detailed level differ between the CPI and the HICP.

The CPI (and the HICP) is based on the following sources: Electronic questionnaires, electronic data from firms and dwellings, turnover information from Statistics Norway's Business Register, commodity trade statistics, and budget shares from the household budget survey.

A sample of about 650 goods and services is selected. In addition, scanner data is used as the sole data source for food and beverages, as well as non-food goods from supermarkets, pharmaceutical products, fuel, and specific consumption categories such as clothing and equipment for sports and outdoor recreation.

Representative goods and services in the sample are selected based on information from the annual Survey of consumer expenditure and branch information. The sample of goods and services is basically kept constant, but is regularly updated when new important products enter the market while outdated products are removed.

Prices are collected from a sample of outlets, households and municipalities. The outlets comprise a panel sample, with one sixth of the outlets being replaced each year. The sample consists of approximately 2 000 firms.

The outlets/firms are selected from Statistics Norway's Business Register in proportion to the firms turnover, i.e. large firms have a bigger probability of being chosen. The selection is made after stratifying the population by industry and region. The probability to be selected is proportional to the size of the turnover. The sample is selected in such a way that it has minimal overlap with the sample of companies in the Index of wholesale and retail sales.

The sample of households for the survey of rents amounts to 2 500 tenants based on the Rental market survey.

The sampling plan for the food and non-alcoholic beverages index is based on the population in the Central Register of Establishments and Enterprises (CRE) defined as the industries in 47.11 and 47.12. The draft population consists of companies belonging to the major supermarket chains and their associated kiosk chains, provided that they can deliver scanner data. Parts of the sample are replaced each year to ensure a representative sample.

The main part of the prices are collected by means of electronical questionnaires, which are sent to the outlets the 10th of each month, and returned to Statistics Norway the first working day after the 15th. Statistics Norway also receives electronic scanner data from companies in the grocery retail, pharmacy, sports, clothing, and gas station sectors monthly.

Car prices are received electronically from the Norwegian Road Traffic Information Council. Data from Vinmonopolet (Norwegian state-owned alcoholic beverage retailer) is also received electronically. Electricity prices are collected from the internet. Rent data for rental properties is gathered using electronic forms and CATI (Computer Assisted Telephone Interview) directly from households.

On average, an outlet spends 90 minutes per year filling out forms in Altinn. This results in a total time usage of approximately 3 300 hours, or just under 520 workdays per year for the entire sample.

The task must be completed by each individual firm. Firms that fail to respond by the deadline will receive a "notice of fine". This is sent out approximately 3 business days after the deadline has passed. To avoid paying the fine, firms must submit completed forms to Statistics Norway within 6 to 7 days.

All forms undergo a review of administrative characteristics. This is followed by automated checks for data entry errors, duplicates, and observations with significant changes compared to the previous month. The price data is then sorted by item and region and further edited. Finally, prices are reviewed at both the item level and item group level. Generally, firms are not contacted during the editing process. Editing is defined here as checking, examining and amending data.

Indices at micro level are calculated for each commodity by an unweighted geometric mean. Aggregation to higher levels is done by the Laspeyre formula where the weights are based on consumption in households in National Accounts. The price reference period is December and short-term indices are chained to long-term indices where the index reference period 2015 = 100.

The CPI and the CPI-AET all-item indices are also presented with seasonally adjusted figures. X12-ARIMA is used for seasonality adjustment.

Employees of Statistics Norway have a duty of confidentiality.

Statistics Norway does not publish figures if there is a risk of the respondent’s contribution being identified. This means that, as a general rule, figures are not published if fewer than three units form the basis of a cell in a table or if the contribution of one or two respondents constitutes a very large part of the cell total.

Statistics Norway can make exceptions to the general rule if deemed necessary to meet the requirements of the EEA agreement, if the respondent is a public authority, if the respondent has consented to this, or when the information disclosed is openly accessible to the public.

More information can be found on Statistics Norway’s website under Methods in official statistics, in the ‘Confidentiality’ section.

The CPI all-item index goes back to 1865. For the period 1865-1900 it was based on the price index for private consumption from the National Accounts. Furthermore, the cost-of-living index for the City of Oslo, calculated by the Oslo Municipal Statistical Office, was used for the period 1901-1913. In the period 1914-1959 it was based on Statistics Norway's Cost of Living Index. Since 1959, the CPI has been applicable.

Series are primarily published down to the 4-digit ECOICOP level. A selection of indices is also published at the 5-digit ECOICOP level, along with several detailed product groups and representative items. For the published indices grouped by ECOICOP, the series go back to January 1979. Additionally, a number of derived series are published, including the CPI adjusted for tax changes and excluding energy products (CPI-ATE) and the CPI grouped by delivery sector. These series have different starting points.

The Harmonized index of consumer prices (HICP)

Statistics Norway publishes index numbers, monthly changes, and 12-month changes for Norway every month, in addition to the annual growth rate and weights. Eurostat (ec.europa.eu) publishes aggregated data for Norway and other European countries, as well as weighted numbers for the EU, EEA, and the Eurozone. The all-item indices for each country is available back to January 1996.

The questionnaires are formed in such a way that the reported price for the last month is listed. This method is done to ensure that the prices of the same goods are given. However, outlets may of consideration of convenience copy the previous month's prices instead of the correct prices when filling out the questionnaires. The most obvious cases of this kind are revealed in manual checks carried out when receiving the questionnaires. When a good or service is no longer sold, the outlets are instructed to find a replacement and mark it in the questionnaire. If outlets report a price of the replacement without marking it, the difference in price between the old product and the replacement will incorrectly be registered as a price change of the old product. The extent of this error is unknown.

Non-response : Each month around 85 to 90 per cent of firms respond. After follow-up reminders, the response rate increases to around 95 percent. Total and partial missing prices are imputed. There are four different algorithms used in estimating missing prices. Imputed prices are either based on the price changes or average prices of the same product in the region or the country as a whole.

Skewness : The sample of goods and services are updated once a year, where new products are introduced and replace old products. The sample of households in the household budget survey is also changed once a year to make the sample of households more representative. In the sample of outlets/ firms, one sixth of the samples are changed each year. Statistics Norway has not done any calculations on the skewness in the Norwegian CPI. International surveys indicate that the sample of goods and services is the source of the largest skewness.

Traditionally non-sampling errors in the CPI are divided into three main types of measurement errors;

a) Income effects that influence consumer behavior over time;

Over time, households experience changes in income, which in turn impact the expenditure shares on various goods and services. To be able to set proper weights in CPI, in each period, the weights in the CPI should reflect the expenditure shares. Therefore the weights are updated yearly. There have not been any calculations done to measure errors caused by non-representative weights.

b) Price effects caused by changes in relative prices;

The price relationship between different goods and services changes over time. This also affects household consumption shares and causes the same measurement issues as income effects.

c) The unsatisfactory treatment of quality changes;

Statistics Norway has not conducted separate calculations of the significance of these measurement errors in the Norwegian CPI. Analyses conducted in the USA, Canada, Sweden, and the UK estimate that the total measurement error falls within the range of 0.4 to 1.1 percent, measured as an annual growth rate. However, these figures come with a high degree of uncertainty. Overall, it is reasonable to assume that the Norwegian CPI overestimates the development of living costs, but the level is most likely well below one percent when measured as an annual change.

HICP numbers are revisable.

For monthly and quarterly figures, there are often significant seasonal variations that make it difficult to directly interpret the development from one period to another. To facilitate the interpretation of such time series, many datasets are seasonally adjusted using X-12-ARIMA or other seasonal adjustment tools.

For more information on seasonal adjustment: Documentation of seasonal adjustment in Statistics Norway.

The Consumer Price Index (CPI) is an indicator build up of many different sub aggregates. Some of these sub aggregates show a clear seasonal pattern, for instance the price index of clothing and footwear where seasonal sales are common. To make the comparability with earlier periods easier, the figures are seasonally adjusted.

A seasonally adjusted CPI can be interpreted as one of many indicators trying to identify the underlying inflation in the original series.

Seasonally adjusted series

Seasonally adjusted series are only published for the CPI all-item index and the all-item index of CPI adjusted for tax changes and excluding energy products, CPI-ATE.

Pre-treatment routines/schemes

Pre-treatment is an adjustment for variations caused by calendar effects and outliers.

An adjustment for extreme values is made before seasonal adjustment is carried out.

Calendar adjustment

Calendar adjustment involves adjusting for the effects of working days/trading days and for moving holidays. Working days/trading days are adjustment for both the number of working days/trading days and for that the composition of days can vary from one month to another.

Not relevant for the CPI series.

Methods for trading/working day adjustment

Not relevant for the CPI series.

Correction for moving holidays

Not relevant for the CPI series.

National and EU/euro area calendars

Not relevant for the CPI series.

Treatment of outliers

Outliers, or extreme values, are abnormal values of the series .

Outliers are detected automatically by the seasonal adjustment tool. The outliers are removed before seasonal adjustment is carried out, and then reintroduced into the seasonally adjusted data.

Model selection

Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.

The model is automatically selected based on established procedures in the seasonal adjustment tool.

Decomposition scheme

The decomposition scheme specifies how the various components – basically trend-cycle, seasonal and irregular – combine to form the original series. The most frequently used decomposition schemes are the multiplicative, additive or log additive.

Multiplicative method is used.

Choice of seasonal adjustment approach

X-12-ARIMA

Consistency between raw and seasonally adjusted data

In some series, consistency between the raw and seasonally adjusted series is required.

No consistency conditions are imposed.

Consistency between aggregate/definition of seasonally adjusted data

In some series, consistency between seasonally adjusted totals and the aggregate is required. For some series there is also a special relationship between the different series, e.g. GDP which equals production minus intermediate consumption.

Not relevant for the CPI series, no adjustment of the aggregates.

Direct versus indirect approach

Direct seasonal adjustment is applied if all time series, including aggregates, are seasonally adjusted on an individual basis. Indirect seasonal adjustment is applied if the seasonally adjusted estimate for a time series is derived by combining the estimates for two or more directly adjusted series.

Direct approach is used.

Horizon for estimating the model and the correction factors

When performing seasonal adjustment of a time series, it is possible to choose which period will be used for estimating and calculating the correction factors. Correction factors refer to the factors used in the pre-treatment and seasonal adjustment of the series.

For the CPI and CPI-ATE, the time series starting from 2003 are used as the basis for calculation.

General revision policy

Seasonal adjustment can be changed when new observations are added or raw data is modified. This is called revision, and there are several ways to deal with the problem of revisions when publishing the seasonally adjusted statistics.

Seasonally adjusted data are revised each time it is published.

Comments : There is no revision in original series. For the seasonally adjusted series, new data can lead to revision in the seasonally adjusted series.

Concurrent versus current adjustment

The model, filters, outliers and regression parameters are re-identified and re-estimated continuously as new or revised data become available.

Horizon for published revisions

Both the CPI and CPI-ATE are updated for the past 4 years, meaning that the seasonally adjusted figures are final for periods more than 4 years ago.

Evaluation of seasonally adjusted data

Periodical evaluation using standard measures proposed by different seasonal adjustment tools.

Quality measures for seasonal adjustment

Additional specific tests are computed to complement the set of available diagnostics within the seasonal adjustment tool.

Seasonal adjustment of short time series

Both series are sufficiently long to perform an optimal seasonal adjustment.

Treatment of problematic series

None of the series are considered problematic.

Data availability

Unadjusted data and seasonally adjusted data are available.

Press releases

Index series are published in the Statbank.

Notat 2009/27 Dokumentasjon av sesongjustering i SSB (PDF)

EUROSTAT: Handbook on Seasonal Adjustment (ec.europa.eu)

US census: X-12-ARIMA-manual (census.gov)