Households' assets: documentation of statistics
Basic data of the statistics
Information is published at the household and personal level. The household level information comprehensively describes the amount of real and financial assets and the demographic distribution of wealth. At personal level, information is published only about publicly traded shares and mutual funds.
The frame population includes all private households and their members living permanently in Finland at the end of the statistical reference year (31.12.).
The household-dwelling population is formed by all persons living permanently at dwellings. Good two per cent of the entire population are excluded from the statistics. They include persons without a postal address, the institutional population (e.g. long-term residents of old people's homes, care institutions, prisons or hospitals), persons permanently resident abroad and persons temporarily resident in Finland. Conscripts are regarded as part of the population in these statistics.
Unit of measure
Asset items missing entirely in the 2019 wealth survey are cash and valuables. In 1987 to 2004, data on valuables were included as interview data. The 2009 and 2013 surveys do not contain data on savings and investment insurances.
Register based statistics about the publicly traded shares and mutual funds of persons include shares listed in Finland, mutual funds and foreign collective investment vehicles, and, as of 2020, equity savings accounts.
Frequency of dissemination
The formation of disposable money income can be described as follows:
+ wages and salaries
+ entrepreneurial income
+ property income (without imputed rent)
= factor income
+ current transfers received (without imputed rent)
= gross money income
– current transfers paid
= disposable money income
When current transfers paid are deducted from gross money income, the remaining income is the household's disposable money income.
The primary income concept used in the income distribution statistics is household's disposable money income according to international recommendations, in which case sales profits and taxes paid on them do not belong to the scope of the income concept. Following international recommendations, they are treated as a memorandum item outside the income concept.
The concept of disposable money income in the total statistics on income distribution differs from disposable money income in the income distribution statistics. As a conceptual difference, the income concept of the total statistics on income distribution includes taxable realised capital gains. For practical reasons, the total statistics on income distribution do not include the majority of interest income and current transfers received and paid between households (e.g. child maintenance support). Real property tax is not deducted in the total statistics on income distribution either.
Excluded from the household population are those living permanently abroad and the institutional population (such as long-term residents of old-age homes, care institutions, prisons or hospitals).
The corresponding register-based information is household-dwelling unit. A household-dwelling unit is formed of persons living permanently in the same dwelling or address. More than one household may belong to the same household-dwelling unit. The concept of household-dwelling unit is used in register-based statistics in place of the household concept.
Although income is the main criterion determining the reference person, in some cases (e.g. entrepreneur households) the activity of the whole household is taken into account. Households of pensioner parents with children (including those over the age of consent) are also special cases where the parent with the higher income is selected as the reference person if the combined incomes of the parents clearly exceed those of a child.
Accuracy, reliability and timeliness
The sample data of the statistics on households' assets, from which comprehensive data on households' net wealth are published at set intervals, are based on a representative sample survey. The reliability of the sample data is essentially affected by the unit non-response due to the fact that some households refuse to or do not take part in the survey for some other reason. It can be concluded from the structure of non-response whether it has been distributed unevenly or randomly. The non-response of the survey is examined in more detail in the quality description of the income distribution statistics.
Efforts have been made to compare the results of the wealth survey by type of wealth with external sources. Some of the data are available not only as a sample but also as total data, in which case comparisons have been made with the key figures of the so-called household-dwelling population. Such data include investment funds, quoted shares, bonds and unquoted shares. Comparisons have also been made with financial accounts, asset balances and statistics on indebtedness. In the pricing of dwellings, prices per square metre have been compared with the data of the statistics on prices of dwellings and the real estate purchase price statistics. The estimates of the wealth survey can deviate significantly from the comparison sources due to differences in methodology and coverage. The data are not directly comparable with, for example, the asset balance data. Further information about the comparisons is available from Statistics Finland.
Comparability - geographical
In addition to data collection methods, the comparison between the countries in the euro area is affected by differences in the characteristics of the household population and the distribution of ownership of different types of assets. For example, the size distribution of households differs considerably from one country to another. One of the main phenomena behind the differences between countries is the relative share of owner-occupiers in the population. For example, in Germany and Austria fewer than 50 per cent of households live in a dwelling they own. The corresponding share is over 80 per cent in Croatia, Lithuania, Hungary, Malta and Slovakia. Further information on the comparability of the results between countries is available in the methodological report published on the ECB's web pages.
Comparability - over time
The value of dwellings has been estimated separately for dwellings in housing companies and real estates by means of prices per square metre. For some dwellings in housing companies, purchase prices have been obtained from information collected by the Tax Administration for asset transfer tax calculation purposes, and they have been raised by house type and area with the indices of the statistics on prices of dwellings in housing companies to the level of the statistical reference year. Part of the price data has been calculated based on the average prices per square metre collected by the Tax Administration. Real estates have been priced based on the average prices per square metre calculated from the basic data of the real estate purchase price statistics. Other than own permanent residential real estate properties have been drawn from the data describing buildings and dwellings in the Population Information System.
There are no essential methodological changes in the determination of the value of owner-occupied dwellings between 2013, 2016 and 2019. The definition of ownership shares was revised in other dwellings in housing companies and in residential real estate in 2016, which increased the value of other dwellings in housing companies and lowered the value of other residential real estate. The corresponding revision was made retrospectively to the data for 2013.
In 1987 to 2004, data on the values of dwellings are the household's own estimates of the selling price of the dwelling. This may affect the comparability of the data especially for single-family houses.
Housing loans are register data based on the register data of the statistics on indebtedness. In the wealth survey (from 2009 onwards), only households that own their dwelling have housing loans.
Other debts have been formed with the help of both register and interview data. In addition to housing loans, data on other debts, such as study and business loans, are obtained from the register of the statistics on indebtedness.
Since 2012, the debt register has not included continuous credits, which are, for example, credit card credits, accounts with overdraft facilities, and other credits that consumers can use continuously within the credit limits without a separate decision to grant credit from the lender. The insufficient data were supplemented in 2013, 2016 and 2019 by asking the households in the interview about their amounts of credit card, charge card, part payment and other debts. As regards these data, it was checked that there were no overlaps in the data in the interview and register debts. In 2009, debt data were obtained comprehensively from registers and the data on debts for the year in question were formed altogether from registers.
The values of free-time residences were formed by pricing the free-time residences owned by private persons in Statistics Finland's statistics on buildings and free-time residences at the prices of the National Land Survey's real estate purchase price statistics. Free-time residences do not include dwellings owned abroad. Fewer free-time residences are obtained from register data than from interviews, which was the method used in 1987 to 2004. Thus, the data on free-time residences are not comparable between 1987 to 2004 and 2009 to 2019.
The value of transport equipment, such as the value of passenger cars, vans and motorcycles, is formed from the data in the vehicle register maintained by the Finnish Transport and Communications Agency (Traficom) and the Tax Administration's price quotes of vehicles, supplemented with prices of websites advertising vehicles for sale.
The vehicle price data are formed from asking prices calculated for taxation purposes. In 2016 and 2019, driven kilometres could also be used in pricing, and they were not used in 2013. Other vehicles consist of non-taxable vehicles in the vehicle register, such as mopeds, quad bikes, snowmobiles and trailers. These have been priced separately with the help of asking prices of websites advertising vehicles for sale. Ownership of boats is based on Traficom’s watercraft register and price data on the price data of websites advertising vehicles for sale. In 2013, 2016 and 2019, car holders were included, while in 2009 only owners were included. As a result, the share of households owning a car is smaller in 2009.
The values of forest land were estimated based on the forest property register administrated by Statistics Finland using the average comparison value of bare land by municipality. It does not reflect the real market value of forest land. Only land areas owned by natural persons are taken into account in the forest property register. Consequently, such property as forest land owned by an estate is excluded from the survey.
The values of farm land were estimated based on the forest property register administrated by Statistics Finland using both the sales prices by municipality and the average comparison value of bare land by municipality. In assets, the value of farm land is an estimate calculated based on purchase prices, which is considerably higher than the comparison value of taxation. In 1987 to 2004, the value of farm land is not included in assets.
No micro level source is available on households' assets in deposits, so the data on deposits at the household level have been collected in the wealth survey with interviews. Deposits in the statistical reference years 2013, 2016 and 2019 are based on household interview data from the third and fourth survey rounds of the interview for the income and living conditions survey in spring 2014, 2017 and 2020. The data were collected and formed divided into current accounts and savings and investment accounts. For the first and second survey rounds the data were modelled with predictive mean matching, combining the real donor method and regression model. The data for 2009 have been modelled from the 2004 data by statistical combining. The data for earlier years were collected with interviews.
The value of quoted shares was formed on the basis of data in the book-entry securities register and OMX price data. Only shares quoted on the Helsinki Stock Exchange are included in the data.
The value of unquoted shares, or the imputed net wealth of an unlisted limited company, was formed from the personal taxation data as the net wealth of the unlisted companies that paid dividends, which is determined based on the balance sheet of the company's most recently ended accounting period. Unquoted shares are known only for those who have received dividends from unlisted companies. The value of unquoted shares is not comparable between 1987 to 2004 and 2009 to 2019, because older data are based on interview data and they were nominal values.
The net wealth of business activities and groups is based on the personal taxation register as is the net wealth of unlisted companies. The net wealth of business activities refers to the net wealth of taxation for employers and own-account workers. The group's net wealth is net wealth as a partner in a general or limited partnership. Net wealth of business activities is included only in the data for 2013, 2016 and 2019. The group's net wealth is included from 2009 onwards.
The net asset values of unquoted shares, business activities and groups are values used in taxation and thus do not describe the actual market values.
Investments in mutual funds are based on the Tax Administration's annual tax return data, which have been raised from comparison values to current values by dividing them by 0.7. The data for 2013, 2016 an 2019 are more exhaustive than in the previous years because they include shares of foreign collective investment schemes.
Other financial assets cover bonds and participation certificates. The values of bonds are formed on the basis of the same book-entry securities data as quoted shares. The book-entry securities data do not include municipal and government bonds. Participation certificates have been calculated on the basis of interests or the number and market price of participation certificates for the most common participation certificates. The data are not comprehensive. In 2016, the number of households owning participation certificates is higher than before due to yield shares of cooperative banks.
Individual pension insurances have been estimated from the personal taxation register using the so-called perpetual inventory method. Individual pension insurance contributions (investments) and, respectively, pension payments received are available in the tax register from 1990 onwards. The values of individual pension insurances were derived cumulatively from these flow data by calculating a yield for the annual net investments (contributions-payments received) as interest on interest. Data have been produced yearly with the perpetual inventory method starting from the statistical reference year 2009. The data for 1987 to 2004 are interview data.
Data on savings and investment insurances are based on an interview. The data have been collected for the entire sample in the interview for the income and living conditions survey. Data on ownership are inquired on the individual level and value data on the household level. Data are not available for 2009 and 2013.
Employment pension assets are not included in the concept of wealth.
Assets in total (total assets, gross assets) refer to total real and financial assets before deducting debts. Real assets cover dwellings, transport equipment, fields, forests and net wealth of business activities and groups (business wealth). In 2013, 2016 an 2019, the net wealth of business activities and groups are included in real assets. There are no data on the net wealth of business activities in 2009. No data are available for the years 1987 to 2004 on the value of farm land or business wealth. There are no data on the value of forests for 1987 to 2004. For this reason, separate data have been formed in the data set and statistical tables, which do not include forests, fields and business wealth. The data for 1987 and 1988 do not include other housing wealth.
Net wealth is obtained by deducting the amount of housing, consumption, student and other loans from total assets. Separate data on net wealth not including forests, fields, business wealth and savings and investment insurances have also been formed.
Coherence - cross domain
The wealth survey is part of the ECB's Household Finance and Consumption Survey for the euro area (2009, 2013, 2016 an 2019). The concept of wealth and the classification of assets may differ from the ECB's definitions, as national statistics also aim to retain key time series.
Statistics Finland's annual statistics on indebtedness describe household-dwelling units' indebtedness. The statistics are based on total data, while the data of the wealth survey are based on a sample. The debt items derived from registers are the same in the statistics, but in the wealth survey their classification may differ (e.g. only owners of dwellings have housing loans). The wealth survey also contains supplementary interview data on debts and debt service expenses which are not included in the statistics on indebtedness. The wealth survey enables proportioning debts to assets, whereas in the statistics on indebtedness debts can only be proportioned to income.
Statistics Finland's financial accounts describe the financial assets of the sectors of the national economy at the macro level and starting from autumn 2014, data on real assets have also been published in connection with them. Due to conceptual differences and differences in definitions as well as different production methods, the estimates of total amounts of assets in the wealth survey cannot be directly compared with the household sector data of financial accounts.
Coherence - internal
Source data and data collections
A majority of the survey data derive from administrative registers and statistical registers. The register sources of the wealth survey are:
- The Population Information System of the Digital and Population Data Services Agency and Statistics Finland’s database on the population, buildings and dwellings in Finland
- Basic data of Statistics Finland's statistics on real estate prices, which are based on the transaction price data of the National Land Survey's register of real estate purchase prices
- The Tax Administration's tax database, real estate register, data collected for asset transfer tax calculation purposes, book-entry securities data, price quotes of vehicles, and inheritance and gift tax data
- Vehicle register and watercraft register (Traficom)
- The Social Insurance Institution of Finland's registers of pension insurance, health insurance compensation and rehabilitation, registers of child maintenance allowances, financial aid for students and housing allowances
- The National Institute for Health and Welfare's register of social assistance
- The register of pension contingency of the Finnish Centre for Pensions
- Statistics Finland’s Register of Completed Education and Degrees
- The State Treasury's database on the military injuries indemnity system
- The Education Fund's data files
- The farm register of the Information Centre of the Ministry of Agriculture and Forestry (TIKE)
- Statistics Finland's Business Register
- The Financial Supervision Authority's data (earnings-related unemployment allowances)
The sample in the wealth survey is the same as in the income distribution statistics. The sample is based on a rotating panel design. The households participate in the survey in four consecutive years, so the data for the statistical reference year consist of households that have been included in the sample for one to four rounds.
The sampling design is a two-phase stratified sampling. In the first phase, a so-called master sample is formed by selecting 50,000 target persons aged 16 or over by means of systematic sampling from Statistics Finland’s population database. The household-dwelling units of target persons included in the sample are formed by combining the persons living permanently at the same address with the target person with the help of the code for place of domicile. In the second phase, the actual sample for the income distribution statistics is selected from the master sample by strata. The probability of a household being included in the sample depends not only on the stratification criteria but also on the number of household members who are aged 16 or over.
The strata are created based on the tax data of the year preceding the statistical reference year. The strata are formed based on the household-dwelling unit’s income subject to state taxation and the socio-economic groups of the household members. The socio-economic groups formed based on the data from the tax register are wage and salary earners, farmers, other self-employed persons, pensioners and others. In defining the sample size by stratum, or in sample allocation, the special requirements of the income distribution survey are considered. The sampling design puts a relatively strong emphasis on persons of high income and as a result, on wealthy persons, which is an asset in the wealth survey. Entrepreneurs and those with high income have a higher probability than others of being included in the sample.
For the statistical reference year 2019, a supplementary sample was made for the sample for the first survey round, for which 500 households were drawn. An additional sample was needed, because due to the corona pandemic that started in spring 2020, the response rate for the first time was clearly lower than in the previous years. The reason for this may be not only the general fall in responsiveness, but also an interruption in trying to get face-to-face interviews from households that could not be reached by telephone because of the corona pandemic. An additional sample was selected to represent strata where the growth in non-response was particularly large and the numbers of observations were clearly lower than in the year before: self-employed persons, wage and salary earners with the lowest income and pensioners with the lowest income.
Frequency of data collection
Personal data on quoted shares and mutual funds of the dwelling population are collected annually from administrative files.
The general method for imputation was predictive mean matching, or the PMM method. The substitution of missing data is described in more detail below for each asset category.
Households and persons whose participation has been approved receive a weighting coefficient with which their data are raised to represent the data of the basic population. The weights are formed in the same way as in the income distribution statistics, that is, a preliminary correction for non-response by strata is made for the panel-specific design weights, and these weights are calibrated to external marginal distributions. The same data as in the income distribution statistics (weight variable YKOR) were used in calibrating the weights of the data of the 2019 wealth survey, supplemented by some asset data. The calibration data were:
- Area (the division of regions, in which Helsinki and other parts of the Helsinki Metropolitan area are shown separately; statistical groupings of municipalities)
- Size of municipality of residence
- Age and gender groups of members
- Level of education of persons aged 16 and over
- Total sums of the main income items: wages and salaries, entrepreneurial and property income, unemployment allowances (basic unemployment allowance and labour market allowance, earnings-related share), pensions, interest on housing and student loans, number of income recipients (earnings-related unemployment allowance, wage and salary income, pension income)
- number of persons belonging to low-income household-dwelling units in the household-dwelling population in the total statistics on income distribution (register-based income concept)
- number of persons owning investment funds and total value of investment funds
- number of persons owning quoted shares over the median of the population according to the conditional median, and
- total value of quoted shares
Principles and outlines
Contact organisation unit
Legal acts and other agreements
Statistics Finland compiles statistics in line with the EU’s regulations applicable to statistics, which steer the statistical agencies of all EU Member States.
Further information: Statistical legislation
Confidentiality - policy
Further information: Data protection | Statistics Finland (stat.fi)
Confidentiality - data treatment
Further information: Publication principles for statistics at Statistics Finland
National survey data have been formed from the basic data of the wealth survey for all years and they are released for research purposes. In addition, the ECB has formed research data also on the euro area data for researchers, and Finland's data for 2009, 2013, 2016 and 2019 are included. The data for 1998, 2009 and 2013 have also been delivered to the Luxembourg Wealth Study (LWS) database.
Accessibility and clarity
Statistical data are published as database tables in the StatFin database. The database is the primary publishing site of data, and new data are updated first there. When releasing statistical data, existing database tables can be updated with new data or completely new database tables can be published.
In addition to statistical data published in the StatFin database, a release on the key data is usually published in the web service. If the release contains data concerning several reference periods (e.g. monthly and annual data), a review bringing together these data is published in the web service. Database tables updated at the time of publication are listed both in the release and in the review. In some cases, statistical data can also be published as mere database releases in the StatFin database. No release or review is published in connection with these database releases.
Releases and database tables are published in three languages, in Finnish, Swedish and English. The language versions of releases may have more limited content than in Finnish.
Information about changes in the publication schedules of releases and database tables and about corrections are given as change releases in the web service.
Data revision - policy
Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions.
The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before.
Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data.
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