276756
/en/priser-og-prisindekser/statistikker/kpi/maaned
276756
statistikk
2017-11-10T08:00:00.000Z
Prices and price indices;Income and consumption
en
kpi, Consumer price index, CPI, inflation, price trends, price increases, CPI-ATE, price index adjustment, deflation, deflator, product groups (for example food, housing, transport), service groups (for example telecom services, hotels and restaurants)Consumer prices , Consumption, Income and consumption, Prices and price indices
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Consumer price index

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Key figures

1.2 %

year-to-year change CPI October 2017

Consumer Price Index (2015=100)
IndexMonthly change (per cent)12-month rate (per cent)
October 2017September 2017 - October 2017October 2016 - October 2017
CPI All-item index106.00.11.2
Food and non-alcoholic beverages102.90.3-1.2
Alcoholic beverages and tobacco105.4-0.21.7
Clothing and footwear107.5-0.1-0.9
Housing, water, electricity, gas and other fuels107.7-0.21.7
Furnishings, household equipment and routine maintenance103.90.6-2.8
Health103.80.10.9
Transport105.60.12.9
Communications105.80.20.8
Recreation and culture107.8-0.42.0
Education111.60.04.3
Restaurants and hotels107.40.13.2
Miscellaneous goods and services104.80.52.3
 
CPI-ATE All-item index105.20.31.1
 
CPI by delivery sector
Consumer goods105.7-0.30.1
Services106.20.32.4
Services where labor dominates106.4-0.12.1

See more tables on this subject

Table 1 
Consumer Price Index, historical indices from 1924 (2015=100)

Consumer Price Index, historical indices from 1924 (2015=100)1
Y-avg2JanFebMarAprMayJunJulAugSepOctNovDec
1Earlier indices are available in table 08184 in the StatBank
2Average of all monthly indices
2017.104.3104.7105.0105.2105.4105.8106.1105.3105.9106.0..
2016103.6101.5102.1102.5102.9103.2103.8104.5103.9104.2104.7104.9104.4
2015100.098.698.999.299.699.8100.1100.199.9100.6101.0101.3100.9
201497.996.697.197.397.797.897.598.397.998.598.698.698.6
201395.994.595.195.495.996.095.796.196.096.496.696.796.6
201293.993.294.294.194.294.293.793.392.993.994.394.494.7
201193.392.793.193.493.993.793.493.192.693.493.393.393.4
201092.190.992.092.592.792.292.191.691.492.092.192.393.3
200989.988.789.489.489.789.990.489.989.790.490.290.590.8
200888.086.787.287.287.287.287.487.988.089.389.689.189.0
200784.883.784.084.584.584.684.584.384.284.885.086.487.1
200684.282.783.483.684.384.384.283.983.985.185.285.184.7
200582.381.281.381.782.182.482.482.282.382.983.083.082.9
200481.080.480.580.981.081.181.181.080.881.381.581.581.4
200380.781.982.081.480.880.380.179.880.080.480.480.580.5
200278.778.078.178.478.578.778.778.678.378.879.179.480.0
200177.776.977.577.778.078.478.477.477.377.777.777.777.9
200075.574.574.874.975.175.275.675.375.376.076.076.476.3
199973.272.472.573.073.273.173.273.072.773.473.774.074.1
199871.570.771.071.471.471.371.571.571.371.971.972.072.1
199769.969.369.669.769.769.870.069.969.870.270.370.470.4
199668.267.367.467.767.968.068.168.368.368.668.968.868.8
199567.366.666.867.267.267.367.567.467.367.767.767.667.6
199465.764.965.165.465.565.565.765.865.866.266.266.266.2
199364.864.064.264.864.964.965.064.964.865.165.165.165.0
199263.462.462.663.163.363.463.563.663.463.763.863.863.8
199161.961.061.261.661.861.962.062.062.062.462.462.462.4
199059.958.658.859.559.559.659.859.959.860.460.960.960.7
198957.556.256.456.957.257.457.757.857.658.158.258.258.2
198855.053.553.854.654.754.855.155.155.155.855.855.855.8
198751.649.950.450.951.151.251.551.651.752.452.552.652.8
198647.445.645.846.146.446.547.347.847.948.648.849.049.2
198544.243.143.243.743.944.044.344.544.344.844.945.045.2
198441.940.740.941.441.641.641.842.042.042.342.542.642.8
198339.438.338.538.939.039.139.339.639.539.940.140.240.4
198236.334.835.035.635.735.836.136.736.737.037.337.537.7
198132.631.031.331.932.132.232.633.133.133.433.533.633.7
198028.726.927.427.828.028.328.729.029.229.529.729.930.1
197925.925.325.425.525.625.725.826.026.026.126.326.526.5
197824.723.924.024.324.424.424.624.924.925.225.325.325.3
197722.921.922.022.422.522.722.923.223.223.323.423.423.4
197621.020.120.220.520.720.821.121.321.321.321.321.421.5
197519.218.418.518.718.818.919.119.519.419.719.719.819.9
197417.216.516.616.817.016.917.017.217.317.517.617.717.9
197315.715.115.315.415.515.615.715.815.715.916.016.116.2
197214.614.214.214.314.414.414.614.714.814.914.915.015.0
197113.713.413.413.513.513.513.613.713.713.713.913.914.0
197012.812.412.512.612.612.712.712.912.913.013.113.213.3
196911.611.411.511.511.511.511.611.711.611.711.711.711.8
196811.311.111.111.211.211.211.211.311.311.311.411.411.4
196710.910.710.710.710.710.810.911.011.011.011.011.011.1
196610.410.210.210.310.310.310.310.510.510.510.610.610.6
196510.19.99.910.110.110.110.110.210.110.210.110.210.2
19649.79.49.59.59.69.69.69.79.89.99.89.99.9
19639.29.19.29.29.29.19.19.29.19.19.19.29.2
19628.98.78.78.88.98.98.99.09.09.19.09.09.1
19618.58.38.38.48.48.48.48.48.58.68.78.78.7
19608.38.38.38.38.38.38.38.38.38.38.38.38.3
19598.38.38.38.28.28.28.28.38.38.38.38.38.3
19588.17.87.87.98.08.18.18.28.28.38.28.28.2
19577.77.67.67.77.77.77.77.77.77.77.77.77.7
19567.57.27.37.37.47.67.67.77.67.57.57.57.6
19557.27.27.27.27.27.27.27.27.27.27.27.27.2
19547.16.96.97.07.07.17.17.37.37.37.27.27.2
19536.96.86.86.86.86.86.96.96.96.96.96.96.9
19526.76.56.66.66.66.66.76.86.86.96.96.96.8
19516.25.75.75.86.16.16.36.36.36.46.36.46.4
19505.35.15.15.15.25.35.35.35.35.45.55.65.6
19495.15.05.05.05.05.15.15.15.15.15.15.15.1
19485.15.05.15.15.15.15.15.15.05.05.05.05.0
19475.15.15.15.15.15.15.15.15.15.05.05.05.0
19465.15.05.05.05.05.05.05.15.15.15.15.15.1
19454.94.94.94.94.94.94.94.95.05.04.94.95.0
19444.94.84.84.84.94.94.94.94.94.94.94.94.9
19434.84.74.84.84.84.84.84.84.84.84.84.84.8
19424.74.64.64.64.64.64.74.74.74.74.74.74.7
19414.44.24.24.34.34.44.44.44.54.54.54.54.6
19403.73.43.43.63.63.63.63.73.74.04.04.04.1
19393.23.13.13.13.23.23.23.23.23.23.33.43.4
19383.23.23.23.23.23.23.23.23.23.13.13.13.1
19373.12.92.93.03.03.03.13.13.13.13.23.23.2
19362.92.92.92.92.92.92.92.92.92.92.92.92.9
19352.82.82.82.82.82.82.82.82.82.82.82.92.9
19342.82.72.72.72.72.72.72.82.82.82.82.82.8
19332.72.72.72.72.72.72.72.72.82.72.72.72.7
19322.82.82.82.82.82.82.82.82.82.82.82.82.8
19312.82.92.92.92.92.82.82.82.82.82.82.82.8
19303.03.03.03.03.03.03.03.03.03.02.92.92.9
19293.13.13.13.13.13.13.13.13.13.13.13.13.1
19283.23.33.33.23.23.23.23.33.23.13.13.13.1
19273.53.63.63.53.43.43.43.53.43.43.43.43.4
19263.84.04.03.93.93.83.83.83.83.73.73.73.6
19254.54.74.84.84.74.64.64.64.54.44.24.14.1
19244.44.14.24.34.34.34.44.44.54.64.64.64.7

Table 2 
The consumer price index adjusted for tax changes and excluding energy products, by ECOICOP. Monthly and 12 months changes

The consumer price index adjusted for tax changes and excluding energy products, by ECOICOP. Monthly and 12 months changes
Monthly change (per cent)12-month rate (per cent)
September 2016 - October 2016September 2017 - October 2017September 2016 - September 2017October 2016 - October 2017
CPI-ATE All-item index0.20.31.01.1
CPI-ATE Food and non-alcoholic beverages-0.40.3-1.9-1.2
CPI-ATE Alcoholic beverages and tobacco0.5-0.22.21.5
CPI-ATE Clothing and footwear2.1-0.11.2-0.9
CPI-ATE Housing, water, electricity, gas and other fuels0.20.21.81.8
CPI-ATE Furnishings, household equipment and routine maintenance0.60.6-2.8-2.8
CPI-ATE Health0.20.11.00.9
CPI-ATE Transport0.21.11.22.1
CPI-ATE Communications0.50.21.10.8
CPI-ATE Recreation and culture0.4-0.42.82.0
CPI-ATE Education0.00.04.34.3
CPI-ATE Restaurants and hotels0.20.13.33.2
CPI-ATE Miscellaneous goods and services-0.10.51.82.3

Table 3 
The consumer price index adjusted for tax changes and excluding energy products, by delivery sector. Monthly and 12 months changes

The consumer price index adjusted for tax changes and excluding energy products, by delivery sector. Monthly and 12 months changes
Monthly change (per cent)12-month rate (per cent)
September 2016 - October 2016September 2017 - October 2017September 2016 - September 2017October 2016 - October 2017
CPI-ATE All-item index0.20.31.01.1
CPI-ATE Consumer goods0.30.1-0.2-0.4
CPI-ATE Norwegian consumer goods0.20.5-1.1-0.9
CPI-ATE Norwegian goods excluding energy products0.20.5-1.1-0.9
CPI-ATE Norwegian agricultural products-0.70.1-2.2-1.5
CPI-ATE Norwegian goods excluding argricultural and energy products0.50.7-0.9-0.7
CPI-ATE Imported consumer goods0.3-0.10.2-0.2
CPI-ATE Imported agricultural products-1.50.4-2.5-0.6
CPI-ATE Imported goods excluding agricultural products0.50.00.4-0.1
CPI-ATE Services0.20.42.12.3
CPI-ATE Rent0.10.11.91.9
CPI-ATE Services excluding rent0.20.62.32.7
CPI-ATE Services where labor dominates0.10.02.32.2
CPI-ATE Services with other important price components0.20.92.33.0

Table 4 
Weights Consumer Price Index

Weights Consumer Price Index
Consumer Price Index (weights)
October 20161October 20171
1The weights are updated in January, and kept constant throughout the rest of the year.
Food and non-alcoholic beverages130.5129.7
Food114.7114.0
Bread and cereals14.114.0
Meat23.623.5
Fish and seafood6.66.6
Milk, cheese and eggs19.119.0
Oils and fats1.91.9
Fruit9.89.7
Vegetables10.110.0
Sugar, jam, honey, chocolate and confectionery16.416.2
Food products n.e.c.13.213.2
 
Non-alcoholic beverages15.815.7
Coffee, tea and cocoa4.44.5
Mineral waters, soft drinks, fruit and vegetable juices11.411.3
 
Alcoholic beverages and tobacco41.741.2
Alcoholic beverages25.024.1
Tobacco16.717.1
 
Clothing and footwear51.752.0
Clothing43.844.2
Footwear7.97.8
 
Housing, water, electricity, gas and other fuels229.8227.6
Actual rentals for housing45.645.7
Imputed rentals for housing133.0132.0
Maintenance and repair of the dwelling1.51.5
Water supply and miscellaneous services relating to the dwelling14.314.5
Electricity, gas and other fuels35.334.0
 
Furnishings, household equipment and routine maintenance66.667.3
Furniture and furnishings, carpets and other floor coverings25.124.7
Household textiles7.67.7
Household appliances9.79.9
Glassware, tableware and household utensils7.47.5
Tools and equipment for house and garden9.810.7
Goods and services for routine household maintenance7.06.8
 
Health31.832.4
Medical products, appliances and equipment14.214.4
Out-patient services16.917.3
 
Transport158.9158.8
Purchase of vehicles59.460.7
Operation of personal transport equipment66.964.2
Transport services32.633.9
 
Communications24.923.0
Postal services0.80.7
Telephone equipment3.93.7
Telephone services20.318.6
 
Recreation and culture112.9115.2
Audio-visual, photographic and information processing equipment17.717.0
Other major durables for recreation and culture6.87.6
Other recreational items and equipment, gardens and pets19.920.2
Recreational and cultural services35.437.9
Newspapers, books and stationery17.217.3
Package holidays15.915.2
 
Education5.65.6
 
Restaurants and hotels56.657.7
Restaurant services51.252.6
Accommodation services5.35.2
 
Miscellaneous goods and services89.389.4
Personal care127.027.3
Personal effects n.e.c.14.74.6
Social protection119.419.5
Insurance117.117.1
Financial services n.e.c.113.913.5
Other services n.e.c.17.27.5

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.

Definitions

Definitions of the main concepts and variables

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 are taken out. 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 estimated.

Standard classifications

Two classifications are in use when calculating and later publishing the CPI, ECOICOP and classification by delivery sector are used. For further information about the classification: ECOICOP 

Administrative information

Name and topic

Name: Consumer price index
Topic: Prices and price indices

Next release

Responsible division

Division for Price Statistics

Regional level

National level only

Frequency and timeliness

Published the 10th of the month, around 1.4 weeks after the current month.

International reporting

Harmonized Indices of Consumer Prices for Norway are reportedly monthly to EUROSTAT.

Microdata

Data at micro level, information about sample units, population, and catalogues are stored in Oracle databases.

Background

Background and purpose

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.

Users and applications

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.

Equal treatment of users

No external users have access to the statistics and analyses before they are published and accessible simultaneously for all users on ssb.no at 8 am. Prior to this, a minimum of three months' advance notice is given inthe Statistics Release Calendar. For more information, go to: equality priciples

 

Coherence with other statistics

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.

Legal authority

The Statistics Act of June 16, 1989 number 54 , §§2-2 and 2-3.

EEA reference

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

 

Production

Population

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".

Data sources and sampling

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 of around 14 000 goods are used for the calculation of sub-index for food and non-alcoholic beverages.

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 2 200 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-alkoholic 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. An annual routine is established to avoid bias in the draft population. Parts of the sample are replaced each year to ensure a representative sample. The sample is drawn after proportional allocation by revenue stratified by chain profile, and in each stratum the companies are drawn randomly without replacement.

Another sampling methodology is used for sub-surveys directed towards municipalities.

Collection of data, editing and estimations

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, farmacies 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 and firms who fail to send in the forms are sent letters of reminder a week after the due data. Firms who fail to comply receive a "notice of fine" a week after the new deadline. 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.

Seasonal adjustment

The all-item index is also presented with seasonally adjusted figures, applying the X12ARIMA Method. For more information go to: About seasonal adjustment

Confidentiality

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.

Comparability over time and space

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.

Accuracy and reliability

Sources of error and uncertainty

The questionnaires are formed in such a way that reported prices in the last two months are 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.

Revision

Not relevant

About seasonal adjustment

General information on seasonal adjustment

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.

Why seasonally adjust these statistics?

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.

An indication of the seasonal pattern for the two all-item indices are shown below. The first table shows expected estimated correction factors for 2017 based on earlier data with the help of direct adjustment by X-12-ARIMA. Actual factors are not identified since these must be estimated when new data is available. The second table shows actual average of the seasonal adjustment factors for the period 2012-2016. Link to tables .

The tables show that the expected factors for 2017 are close to the average seasonal factors indicating a stabile seasonal pattern. The factors in the table are close to 100 indicating a low level of adjustment of the original series.

Pre-treatment

Pre-treatment routines/schemes

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

There are no pre-treatment of raw data.

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.

Model selection is automatic using 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 in use.

Seasonal adjustment

Choice of seasonal adjustment approach

X-12-ARIMA

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.

Audit procedures

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 to 2012; before 2012 the seasonal adjusted figures are final.

Quality of seasonal adjustment

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.

A table containing selected quality indicators for the seasonal adjustment is available here; Indicators of quality in seasonal adjusted figures.

For more information on the quality indicators in the table go to: Seasonal adjustment: General information.

 

Special cases

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.

Posting procedures

Data availability

Unadjusted data and seasonally adjusted data are available.

Press releases

Index series are published in the StatBank.

Relevant documentation

Contact

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