Innhold over kalkulator
Consumer price index
Updated: 10 June 2022
Next update: 11 July 2022
|Index||Monthly change (per cent)||12-month rate (per cent)|
|May 2022||April 2022 - May 2022||May 2021 - May 2022|
|CPI All-item index||121.5||0.2||5.7|
|Food and non-alcoholic beverages||110.4||0.4||2.6|
|Alcoholic beverages and tobacco||114.7||0.2||2.9|
|Clothing and footwear||101.8||1.2||2.5|
|Housing, water, electricity, gas and other fuels||128.2||-1.0||8.0|
|Furnishings, household equipment and routine maintenance||128.0||2.2||8.9|
|Recreation and culture||124.6||1.0||3.8|
|Restaurants and hotels||126.6||1.1||7.7|
|Miscellaneous goods and services||116.5||0.1||2.4|
|CPI-ATE All-item index||117.2||0.4||3.4|
|CPI by delivery sector|
|Services where labor dominates||122.8||0.3||3.2|
Calculate the price change
The latest available figures are for May 2022. Figures for June are released around July 10.
About the statistics
The CPI describes the development in consumer prices for goods and services purchased by private households in Norway, and is a common measure of inflation. The CPI adjusted for tax changes and excluding energy products (CPI-ATE) is a measurement of the underlying growth in consumer prices.
Price refers to actual retail price of goods and services offered to households. This means prices including indirect taxes, fees and subsidies. Discount and sale prices are registered.
Price reference month defines the time of reference for new weights, updated sample and base prices used for calcultaion in the following year.
Budget shares are proportional to the consumption of a certain good and consumption in total in households. Expenditure shares are obtained from the consumtion in houshold in National Accounts.
A Laspeyre price index is a price index where the base-period weights remain fixed. A chained Laspeyres price index is an index linked by Laspeyres indices with different sets of weights. New sets of weights are incorporated into the index every year. A Paasche price index also uses fixed weights but, unlike the Laspeyre price index, the weights are from actual current period. A pure Paasche price index is not used in the CPI
A Fisher price index is a geometric mean of a Laspeyre and Paasche price index. The Fisher price index is used in the CPI for the index of motor vehicles and indices of alcoholic beverages sold through the State wine and liquor monopoly.
ECOICOP (European Classification of individual consumption by purpose) is a consumer classification developed by UN and EUROSTAT. The classification criteria is the end purpose of the consumption.
Imputed price is a price estimated for a missing price based on other price observations of the same products.
CPI-AE (CPI excluding energy products) is an indicator where the price material and the weight of the energy Products (i.e.: electricity, heat energy, liquid and solid fuels together with motor oil, petrol and diesel) are taken out. Other computations are identical with the computation process of the CPI.
CPI-AEL (CPI excluding electrisity) is an indicator where the price material and the weight of the electricity including grid rent is excluded. Other computations are identical with the computation process of the CPI.
CPI-AT (CPI adjusted for tax changes) is an indicator where the weights and the calculations are identical to the CPI. The CPI-AT is also based on actual, observed prices, but those are adjusted for real changes in taxes. The CPI-AT takes into account the following taxes:
1. Value added tax
2. Alcohol tax
3. Tobacco tax
4. Petrol tax
5. Diesel tax
6. Electricity tax
7. Taxes on mineral products
8. Chocolate tax
9. Tax on non-alcoholic beverages
10. Sugar tax
11. Tax on disposable beverage packing
12. Aviation tax - Terminal and security charge
13. Purchase tax on vehicles, weight tax
14. Purchase tax on vehicles, piston displacement tax
15. Purchase tax on vehicles, motor effect tax
CPI-ATE (CPI adjusted for tax changes and excluding energy products) is an indicator that is built upon the main components of CPI-AE and CPI-AT.
Seasonal goods are products that are only or to a small extent available at certain times of the year. Examples are fruit, vegetables and certain clothing products. Observed prices are used in season while out of season the prices are in most cases estimated.
Name: Consumer price index
Topic: Prices and price indices
Division for Price Statistics
National level only
Published the 10th of the month, around 10 days after the current month.
Harmonized Indices of Consumer Prices for Norway are reportedly monthly to EUROSTAT.
Data at micro level, information about sample units, population, and catalogues are stored in Oracle databases.
The CPI measures the actual changes in the prices for household goods and services including charges and fees. 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. From 2011 National Account data are the main weigh source and replaced the Household Budget Survey which had been used since 1960. The price reference month is 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). In addition the classification of indices grouped by delivery sector is revised.
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.
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.
With exeption of the computation of the owner-occupied housing follow the CPI the same legislation as the Harmonized Indices of Consumer Prices (HICP). More about EUROSTATS regulations: Legislation related to the HICP
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 CPI 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 only data source for food and beverages together with non-food goods from supermarkets, pharmaceutical goods, fuel and within specific consumption groups in clothing and equipment for sport and open-air recreation
Representative goods and services in the sample are selected based on information from the annual household budget survey 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 where one sixth of the outlets are replaced each year. The sample amounts to about 2 000 firms. The sample of households for the survey of rents amounts to 2 500 tenants based on the Rental market survey. 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 does not overlap the sample of the Index of Retail Sales.
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 grocery firms, retail pharmacies, sports and clothing dealer's and petrol stations monthly. Car prices and price information on alcoholic beverages are received electronically. Tariffs on electricity are collected from the Internet. Rentals for tenants are collected by means of electronic questionnaires andCATI- Computer Assisted Telephone Interview - directly from households.
An outlet uses an average 90 minutes to fill out the questionnaires throughout the year, which means that the sample of outlets uses in total about 3 300 hours or less than 520 days of work each year.
Individual firms fill out the questionnaires. Firms who fail to comply receive a "notice of fine". To avoid paying the fine, firms must submit completed forms to Statistics Norway within 6 to 7 days.
After checking the questionnaires, the prices are thereafter put through tests, which identifies duplicates and observations with large price changes from the previous month. The price material are then sorted by item and region and further edited. Finally, prices are controlled at item level and item group level. Generally firms are not contacted during the editing process.
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 all-item index is also presented with seasonally adjusted figures, applying the X12ARIMA method.
Data collected from firms and households are subject to secrecy and are to be kept or destroyed in a secure manner. Any use of the data must be in accordance with the rules set out by the Data Inspectorate.
The All-item index goes back to 1865. In the period 1865-1900 it was based on the price index for private consumption from the National Accounts . In the period 1901-1913 it was based on the Cost of Living Index of Oslo, calculated by a local statistical office in Oslo. In the period 1914-1959 it was based on Statistics Norway's Cost of Living Index.
Statistics Norway publishes indices at ECOICOP class level. There are also certain indices at sub-class level and indices at consumption segment and item level published each month. The indices published are available from January 1979. In addition derived series are published, among these are, CPI adjusted for tax-changes (CPI-AT), CPI excluding energy Products (CPI-AE) and CPI grouped by delivery sector. These series have different starting points.
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 goes out of the market, 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. The response increases to about 95 per cent after the process of reminding. 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 which influences consumer behaviour through time;
Households through time face changes in income, which also affect the expenditure shares of different 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 changes also the expenditure share of households and causes the same measurement challenge as the income effects.
c) The unsatisfactory treatment of quality changes;
Statistics Norway has not accomplished separate calculations of these measurement errors in the Norwegian CPI. Calculation of measurement errors and analyses done in USA, Canada, Sweden and Great Britain estimate the measurement errors somewhere between 0.4 to 1.1 per cent measured as annual growth rate. However there are uncertainties in these estimates. Its likely to assume that the Norwegian CPI overestimates the development in the cost of living, but the level is likely to be less than one per cent measured as annual change.
General information on seasonal adjustment
Monthly and quarterly time series are often characterized by considerable seasonal variations, which might complicate their interpretation. Such time series are therefore subjected to a process of seasonal adjustment in order to remove the effects of these seasonal fluctuations. Once data have been adjusted for seasonal effects by X-12-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.
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 is an adjustment for variations caused by calendar effects and outliers.
There are no pre-treatment of raw data.
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.
Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.
Model selection is automatic using established procedures in the seasonal adjustment tool.
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 in use.
Choice of seasonal adjustment approach
Consistency between raw and seasonally adjusted data
In some series, consistency between raw and seasonally adjusted series is imposed.
Do not apply any constraint.
Consistency between aggregate/definition of seasonally adjusted data
In some series, consistency between seasonally adjusted totals and the aggregate is imposed. 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 performed if all time series, including aggregates, are seasonally adjusted on an individual basis. Indirect seasonal adjustment is performed 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 the period to be used in estimating the model and the correction factors. Correction factors are the factors used in the pre-treatment and seasonal adjustment of the series.
For the CPI and the CPI-ATE the time series from 1985 and 1995 respectively, are used.
General revision policy
Seasonally adjusted data may change due to a revision of the unadjusted (raw) data or the addition of new data. Such changes are called revisions, 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 the CPI-ATE are revised back 4 years; before that the seasonal adjusted figures are final.
Evaluation of seasonally adjustment 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.
Unadjusted data and seasonally adjusted data are available.
Index series are published in the StatBank.