9076_om_not-searchable
/en/inntekt-og-forbruk/statistikker/fbu/arkiv
9076_om
statistikk
2008-09-04T10:00:00.000Z
Income and consumption
en
false

Survey of consumer expenditure2005-2007

Content

About the statistics

Definitions

Name and topic

Name: Survey of consumer expenditure
Topic: Income and consumption

Responsible division

Division for Income and social welfare statistics

Definitions of the main concepts and variables

Total consumption expenditure . Total consumption expenditure consists of payments by the household during the accounting period (converted to figures for the whole year). Some expenses, such as housing expenses, purchase of durable consumer goods (cars, electrical household appliances, etc.), expensive clothing, package tours etc. have been recorded by means of interviews. Consumption expenditure for durable consumer goods corresponds to the difference between expense in connection with the purchase of new goods and income resulting from any sale (or trade-in) of old goods. For this reason certain tables present negative figures, for instance for the commodity group purchase of transport equipment.

Total consumption expenditure does not include expenses for direct taxes, social security contributions, gifts given away, investments in real property (such as the purchase of a dwelling and expenses for the building and extension of existing building), contractual savings (e.g. pension contribution, loan instalments, life insurance premium, etc.).

In addition to payments, total consumption expenditure includes the value of consumption of self-produced commodities and gifts received. The value of self-produced commodities and gifts received is estimated according to retail prices.

Income . The information is taken from tax assessment registers. Income is calculated as pensionable earnings - assessed taxes + tax deductions.

From 1996 is the income, and from 1998 is education taken from the incomeregister.

Expenses for housing, power and fuel include expenses related to the households permanent dwelling as well as to holiday houses. Dwellings are assessed for tax purposes using one of two methods, either per cent assessment or account assessment. For households having their own per cent assessed dwelling, expenses include interest on loans for the dwelling, repairs and maintenance, insurance, water rates and various other expenses. For dwellings assessed according to accounts, the housing expenses comprise stipulated annual rent according to the last tax assessment. For households with a rented dwelling, the housing expenses include rent and interest on loans for housing deposits. From 1996 has Statistics Norway introduced a new classification of consumption - COICOP (Classification of individual Consumption by Purpose). For households having their own per cent assessed dwelling, the expenses up till the introduction of COICOP has been defined as expenses including interest on loans for the dwelling, repairs and maintenance, insurance, water rates and various other expenses. After introduction of COICOP, interest is no longer considered as consumption. For owners of this kind of dwelling there will be imputed a rent, which is added as housing expense.

The value of a free dwelling corresponds to the amount assessed at the latest tax assessment. Expenses for holiday houses include any interest on loans, insurance and other costs. For households having rented a holiday house, this expense is included. Expenses for maintenance comprise purchase of commodities, wages and salaries and other expenses in connection with maintenance of the households own dwelling, rented dwelling and holiday house.

Household . A household consists of all persons living in the same dwelling and eating at least one meal together per day. Persons who are temporarily absent due to school; vacation, admission to hospital, military service etc. are included.

Main income earner . The person who contributes most to the financial support of the household.

Age . A persons age equals the difference between the year of the households participation in the survey and the year the person was born.

Type of household . Couples comprise both married and non-married cohabiting couples, and have been classified in age groups on the basis of the age of the older person. Child means an unmarried person living with one or both parents/guardians. The groups couples without children, couples with children and mother or father with children comprise no persons other than those mentioned.

Standard classifications

Region

The various regions consist of the following counties

Østlandet: Oslo, Akershus, Østfold, Hedmark, Oppland,

Buskerud, Vestfold and Telemark

Agder and Rogaland: Aust-Agder, Vest-Agder and Rogaland

Vestlandet: Hordaland, Sogn og Fjordane, Møre og Romsdal

Trøndelag: Sør-Trøndelag and Nord-Trøndelag

Nord-Norge: Nordland, Troms and Finnmark

From 1997 the various regions consist of the following counties

Østlandet and Akershus: Oslo and Akershus

Hedmark and Oppland Hedmark and Oppland

Sørøstlandet: Østfold, Buskerud, Vestfold and Telemark

Agder and Rogaland Aust-Agder, Vest-Agder and Rogaland

Vestlandet Hordaland, Sogn og Fjordane, Møre og Romsdal

Trøndelag Sør-Trøndelag and Nord-Trøndelag

Nord-Norge Nordland, Troms and Finnmark

Area of residence. Areas are delimited on the basis of Statistics Norways Standard Classification of Municipalities, 1985 (SNS No. 4), according to classification codes for population density.

From 1997 are Area of residence delimited on the basis of Statistics Norways Standard Classification of Municipalities, 1994 (NOS C 192), according to classification codes for population density.

The following classification is used

Oslo, Bergen, Trondheim

Densely populated areas except Oslo, Bergen, Trondheim comprise municipalities except Oslo, Bergen and Trondheim, where 50 per cent of the population or more live in densely populated areas.

Sparsely populated areas comprise municipalities where less than 50 per cent of the population live in densely populated areas.

A densely populated area is an area with at least 200 inhabitants as of 1 November 1980, or 3. November 1990 after 1997 and where the distance to the nearest house is less than 50 metres. A cluster of houses located more than 50 metres from a densely built-up area is, however, regarded as a part of the densely populated area if the house cluster naturally belongs to the densely built-up area.

Classification of expenditure. The most detailed classification in the publication contains 470 categories of commodities and services. These categories are aggregated to various levels 150, 37 and 9 commodity and service categories.

After 1996 will the survey be published with the new classification - COICOP (Classification of Individual Consumption by Purpose). The classification will make international comparison easier. The classification has 12 main groups, and the distribution of commodity and services are subordinated some new principles.

Ownership of durable goods. The percentages of households with certain durable goods comprise households which own the goods, but not households which only have the goods at their disposal.

Administrative information

Regional level

Results are on national level, but there are tables on regions and areas of residence

Frequency and timeliness

Annual in the periode 1974-2009. It was not conducted surveys in 2010 and 2011. After this it will be conducted larger periodic surveys by various intervals. The first if these was done in 2012.

International reporting

Eurostat

Microdata

In addition to a database containing raw data from interview and account books, results from the processing routine will also be stored on a household level.

Files with recoded variables are also made.

Background

Background and purpose

The principal aim of the survey has been to provide a detailed description of the consumption of private households in order to update the weight used in calculating the consumer price index. It will increasingly be used in the measurement of social development and economic living condition

Since 1974 Statistics Norway has carried out annual surveys of consumer expenditure with out major changes. Before 1974, nation-wide surveys were carried out in 1958, 1967 and 1973. After 2009 it has been carried out a major survey in 2012.

Users and applications

The most important users of results from the survey are Division of Economic Indicators, Division of National Accounts, Division of Environmental Statistics and Division of Microeconometrics Research.

Results from the survey are used by researchers at the Institute for Nutrition Research, the University of Oslo and the National Nutrition Council.

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 08:00 am. Prior to this, a minimum of three months' advance notice is given in the Statistics Release Calendar. This is one of Statistics Norway’s key principles for ensuring that all users are treated equally.

Coherence with other statistics

The most detailed classification in the publication contains 470 categories of commodities and services. These categories are aggregated to various levels 150, 37 and 9 commodity and service categories.

See UN. Department of economic and social affairs. Statistical office A System of national accounts. New York, 1968.

From 1996-1998 the results will also be published by COICOP-HBS (Classification of Individual Consumption by Purpose - Household Budget Survey) UN Statistical commission, March 1999. Konsumgrupperinger i offisiell statistikk

Legal authority

Voluntary basis

EEA reference

Not relevant

Production

Population

Not relevant

Data sources and sampling

Data sources are representative sample surveys and attached information from registers on income and education.

The survey is based on personal interviews and detailed accounting in a representative sample of private households based on drawn persons from 0 to 79 years of age (0-84 years in 2012). In 2012 the samle was 7000 housholds. Earlier the sample was annually 2 200 persons. Institutional households such as hospitals, boarding houses etc. were not included.

Collection of data, editing and estimations

Personal interviews computer assisted personal interview and a paper- and a internetbased booklet for detailed accounting for a period of 14-days.

Seasonal adjustment

Not relevant

Confidentiality

SN has worked out guidelines for coupling of different data sources for statistical purposes. The guidelines are based on SNs authorisation given by the Data Inspectorate for person registers, and the Statistics Act. According to these guidelines responses given in surveys can only serve for the purpose of making statistics. i.e. information concerning groups of people will be given, not for individuals. When survey data files are coupled to registers, encryption techniques are used in order to ensure that it is impossible to identify persons from the survey or register information in the coupled data file.

Comparability over time and space

Not relevant

Accuracy and reliability

Sources of error and uncertainty

Measurement and processing errors

Both in total counts and sample surveys erratic responses may occur. Errors may arise both in the collection as well as in the data revision process. PC's are used in the collection of data in the SLC. The interviewer reads the questions from the screen, and registers the answers directly into the data programme. An important advantage by using PC-based registering is that pre-programmed skipping of questions is employed in order to avoid placing questions to respondents for whom certain questions are inappropriate.

PC assisted interviewing gives the opportunity to monitor response consistency between the different questions directly. For every question a range of proper values are defined. In addition, error messages are programmed in order to alert the interviewer when typing values that not are consistent with previous responses.

We avoid entering invalid input and we achieve reduced non-response on certain questions by reduced risk for skipping questions that should have been raised.

Errors may occur when respondents give wrong answers. One reason is difficulties for the respondent to remember circumstances far behind in time. Additionally, questions may be misunderstood. When questions relate to issues people find complicated, we must expect that erratic responses may be found. Data collection errors may also come from questions respondents find sensitive. In such cases, respondents may intentionally reply incorrectly. Responses may also be influenced by what the respondent consider socially desirable.

Processing errors take place when there are discrepancies between the values registered and the values reported out of the process. Such errors may occur for instance by recoding. By means of various examinations, such errors are attempted to be identified and corrected.

When all errors as far as possible are corrected, experience indicate that statistical outcomes in most cases to a relatively little extent are affected by collection and processing errors. However, the effect of such errors may have importance in some cases, and every error will not necessarily be detected.

Non-response errors

The response percentage has varied from 54.8 per cent (1999) to 50 per cent (2007).

The non-respondents are not equally distributed among all the household groups. The rate of non-response varied according to area of residence, type of household and accounting period during the year. In order to right sample bias, corrections have been made for the non-response. Household groups with a high non-response rate are weighted relatively more in estimating average figures.

Sampling errors

Variance Several types of error are connected with the results from a sample survey. One type of error, called sampling variance, is caused by the act that the survey is based on a sample instead of a complete census of the population. The size of the sampling variance (the standard deviation) depends among other things on the size of the survey, the length of the registration period, and the way in which the sample has been drawn.

The Central Bureau of Statistics has not made exact calculations to compute estimates for the standard deviation of observed percentages. However, in table a the approximate size of standard deviation is given for observed percentages and various sample sizes.

Table a. Approximate size of standard deviation in per cent

Number of observations

Percentages

 

5 (95)

10 (90)

15 (85)

20 (80)

25 (75)

30 (70)

35 (65)

40 (60)

45 (55)

50 (50)

50

3.8

5.2

6.2

6.9

7.5

7.9

8.3

8.5

8.6

8.7

75

3.1

4.2

5.1

5.7

6.1

6.5

6.8

6.9

7.0

7.1

100

2.7

3.7

4.4

4.9

5.3

5.6

5.8

6.0

6.1

6.1

150

2.2

3.0

3.6

4.0

4.3

4.6

4.8

4.9

5.0

5.0

200

1.9

2.6

3.1

3.5

3.8

4.0

4.1

4.2

4.3

4.3

250

1.7

2.3

2.8

3.1

3.4

3.6

3.7

3.8

3.9

3.9

300

1.5

2.1

2.5

2.8

3.1

3.2

3.4

3.5

3.5

3.5

400

1.3

1.8

2.2

2.5

2.7

2.8

2.9

3.0

3.1

3.1

600

1.1

1.5

1.8

2.0

2.2

2.3

2.4

2.5

2.5

2.5

800

0.9

1.3

1.6

1.7

1.9

2.0

2.1

2.1

2.2

2.2

1 000

0.8

1.2

1.4

1.6

1.7

1.8

1.9

1.9

1.9

1.9

1 500

0.7

1.0

1.1

1.3

1.4

1.5

1.5

1.6

1.6

1.6

2 000

0.6

0.8

1.0

1.1

1.2

1.3

1.3

1.3

1.4

1.4

2 500

0.5

0.7

0.9

1.0

1.1

1.1

1.2

1.2

1.2

1.2

3 000

0.4

0.6

0.7

0.8

0.9

0.9

1.0

1.0

1.0

1.0

4 000

0.4

0.6

0.7

0.8

0.8

0.9

0.9

1.0

1.0

1.0

To illustrate the uncertainty associated with a percentage, one can use an interval to give the level of the true value of an estimated quantity (the value obtained if making observations on the whole population instead of observations based on a part of the population). Such intervals are called confidence intervals if constructed in a special way. In this connection one can use the following method. Let M be the estimated quantity, and S the estimate of standard deviation of M. The confidence interval will be an interval with limits (M-2S) and (M+2S).

This method will give, with approximately 95 per cent probability, an interval containing the true value.

The following example illustrates the use of table a for finding confidence intervals The estimate of standard deviation of 70 per cent, is 3.2 when the estimate is based on 300 observations. The confidence interval for the true value has limits 70±2*3.2, which means the interval is from 63.6 to 76.4 per cent.

Revision

Not relevant