Prices of dwellings in housing companies: documentation of statistics
Basic data of the statistics
Unit of measure
The statistics on prices of new dwellings are based on data collected from the largest real estate agents and building contractors. The data can be revised if Statistics Finland receives information on a significant number of transactions after the release time.
The statistics on prices of dwellings in housing companies cover only dwelling transactions in housing company shares. Statistics Finland publishes a separate price index on prices of single-family houses, which is published quarterly in the statistics on real estate prices. Data on real estate transaction prices by municipality are available from the National Board of Survey.
Frequency of dissemination
The following are not counted in the dwelling's floor area: garage, cellar, sauna facilities in an unfurnished basement, unheated storage space, balcony, porch, veranda and attic space unless used as a living space.
The floor area of a freetime residence refers to its gross floor area.
A government-subsidised dwelling is a dwelling produced with government ARAVA loans, in which the rent is determined by the cost correlation principle. Most of government-subsidised dwellings are owned by municipalities.
Non-subsidised dwellings are other than government-subsidised dwellings.
Accuracy, reliability and timeliness
Quarterly data are statistically more reliable than monthly data and contain more detailed information by area.
Cases with missing information about transaction price or floor area, or with exceptionally high or low price due to a contract within the family or an error in data entry are not accepted into the price statistics. The acceptable ranges of prices for different areas are defined annually.
The price indices of old and new dwellings in housing companies and the published prices per square metre include dwellings on both own plots and rented plots. The price indices and prices per square metre of old dwellings in housing companies do not include price controlled HITAS dwellings.
Prices per square metre for new dwellings in housing companies are published separately for dwellings located on rented plot and own plot and the ownership form of plot is taken into consideration in the quality standardisation of the index.
Because the price index takes into account changes in the distribution of year of completion, floor area and location of dwellings sold at different points in time, and their effects on prices, the average prices of the statistics vary differently from the price index. The price index and average prices are both usable indicators, depending on the situation.
The price index aims to measure as accurately as possible how much more/less an average dwelling in a housing company costs now than it did before. The average price, in turn, describes the prevailing price level for sold dwellings without considering whether they are older, newer, larger or smaller than dwellings sold before. More information about the key figures of the statistics is given in the Tieto&trendit blog (In Finnish).
Data revision - practice
Comparability - geographical
Comparability - over time
Chained old index series are published in the statistics for different base years. The weight structure and regional classifications of the base year in question are used during each base year.When the base year changes, old time series are always chained with the newest index, where by the changes in the index correspond to the changes in the newest index. In connection with changing the base year, the methodological changes made are also reflected in the annual changes of the long time series.
The price statistics on old dwellings were revised in 2022. In the revision, the price review and data procedures were updated and the calculation methods of the price index and prices per square metre were renewed. The new base year 2020 was introduced in the statistics. The results differ from those published previously due to the changes mentioned above.
The price statistics on new dwellings were revised in 2020. In the revision, the data were supplemented retrospectively with new information, the price review and data procedures were updated, the calculation methods of the price index and prices per square metre were renewed and the publication level of the statistics was specified so that data are published in the following for the biggest towns as well. The new base year 2015 was introduced in the statistics. The results differ from those published previously due to the changes mentioned above.
In 2019, the reporting of the asset transfer tax was changed. In connection with the change in the asset transfer tax, the Tax Administration's data on dwellings (data on changes in ownership of dwellings in housing companies) were introduced in 2020 for old dwellings in housing companies in addition to the asset transfer tax statements that were previously in use. Due to the change in data, the number of sales published in the statistics and their accumulations are not comparable with earlier years starting from 2019 Q4.
Coherence - cross domain
Coherence - sub-annual and annual statistics
Coherence - internal
Source data and data collections
New dwellings: The data of the price statistics are based on the price monitoring data of the Central Federation of Finnish Real Estate Agencies, as well as data from Statistics Finland's own data collecting. The data include information on transactions in new dwellings reported by the largest real estate agents and building contractors. The monthly statistics do not contain information on new dwellings due to the scarcity of statistical data.
Frequency of data collection
The data of the statistics on prices of old dwellings in housing companies are formed by combining the Tax Administration's data on dwellings and asset transfer tax statements into one transaction concerning a dwelling. The obtained data are then combined with register data from the real estate database and the building and dwelling production database in order to obtain characteristics data. After this the regional classification is added to the data. The validation of the data is performed by adding price limits to the data and by adding so-called deletion codes to deviating observations by floor area, year of construction and area. The data are then saved into the production database.
After this, the parameters of the present time, that is, averages for all variables of the regression model are calculated from the data: age, floor area and area. The parameters are calculated on the lowest level of the classification, i.e. area/type of building/number of rooms. The calculated parameters are placed in the regression model and the forecast prices according to the model are calculated for the present time and the base period.
The effect of each variable is calculated by deducting from the forecast price of the base period the forecst price of the present period.
After this, weighted arithmetic means according to the desired classifications are calculated both from the price ratios (p1/p0) and the influencing factors. The final index adjusted for quality is calculated by multiplying all geometric means mentioned in the previous section with each other. Data on the value of the building stock are used in the weighting for each micro area. Finally, quarterly and annual changes are calculated. Further information under 10.6 Documentation on methodology.
Processing and calculation of data on the statistics on prices of new dwellings in housing companies.
The coordinates and the required regional classifications are combined with the data of the statistics on prices of new dwellings in housing companies. Validation is carried out in the same way as in old dwellings in housing companies.
The calculation is performed by first forming the variables of the regression model of the base period (previous year) and the regression model for them. After this, corresponding data are formed for the comparison period. Price changes on the lowest level are calculated and weighted together with the value shares of new dwellings sold in the basic and comparison periods. After this, the calculated index is chained to the 2015=100 index series. Quarterly and annual changes are calculated.
Documentation on methodology
Based on the total number of actual transaction prices, the price index aims at answering the question how much more or less a typical dwelling in a housing company now costs compared with before. Because the composition of dwellings sold at different times is not the same, monitoring average price changes is not sufficient. For example, the relative shares of different types of dwellings among sold dwellings may vary from quarter to quarter. When calculating the index, the so-called hedonic method is used, where the aim is to separate the genuine price development from price changes caused by dwelling characteristics at different points in time with the help of data classification and regression analysis.
Classification: Because the location, type of building and number of rooms are the most important price determinants, the composition of sold dwellings is first standardised by classifying these variables. The regional classification has been constructed so as to be geographically meaningful and as homogeneous as possible in respect of price levels of dwellings. In the regional classification, the largest towns have been divided into several sub-areas and smaller municipalities, where only few transactions take place, have been combined. Within areas, dwellings in a housing company are divided by type of building into two categories: blocks of flats and terraced and single-family houses. Dwellings in blocks of flats have been classified further by the number of rooms into one-room dwellings, two-room dwellings and dwellings with three or more rooms. Terraced houses have been divided by the number of rooms into two categories: dwellings with fewer than three rooms and dwellings with at least three rooms.
Regression model and quality adjustment: The used classification does not, however, homogenise the data sufficiently, because inside a class, dwellings differ from another in terms of precise location, floor area, year of completion, and so on. The price data on old dwellings contain data on the year of completion, floor area, and location of the dwelling on the postal code level. The price data of new dwellings include information on the area, ownership form of plot (whether the dwelling is located on own or rented plot) and location of the dwelling. With the help of the regression model, these data are used to quality adjust for changes in the composition of the data between the base and reference periods.
An example of quality adjustment: during the statistical quarter the dwellings sold in a certain area have, on average, a larger floor area than the dwellings in the base period. In the quality adjustment, the index is revised upwards as otherwise the lower price per square metre caused by the larger floor area would erroneously be interpreted as a drop in prices. If there is no difference in the floor areas of the dwellings sold during the statistical quarter compared to the base period, no quality adjustment is needed.
The index point figure for the whole country is derived by aggregating the index class-specific price changes and the quality adjustments with Törnqvist index formula.Quality standardised price changes are weighted together with the value shares of dwellings sold in the base and comparison periods.The weights for old dwellings are derived as value-shares of the stock of dwellings in housing companies. The base period is the previous year and the actual index series is calculated by chaining the index into a time series where the base year is 2015=100 for new dwellings in housing companies and 2020=100 for old dwellings in housing companies.
Principles and outlines
Contact organisation unit
Legal acts and other agreements
The compilation of statistics is guided by the Statistics Act. The Statistics Act contains provisions on collection of data, processing of data and the obligation to provide data. Besides the Statistics Act, the Data Protection Act and the Act on the Openness of Government Activities are applied to processing of data when producing statistics.
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 legislationThe prices of dwellings in housing companies and single-family houses are included in the owner-occupied housing price indices delivered to Eurostat (Commission Regulation (EU) No. 93/2013). The compilation of price indices is directed by the Handbook on Residential Property Prices Indices (RPPIs).
The price indices of dwellings in housing companies and single-family houses function as source data for the national Consumer Price Index. The Consumer Price Index is based on the ILO Labour Statistics Convention No. 160.
Confidentiality - policy
The data protection of data collected for statistical purposes is guaranteed in accordance with the requirements of the Statistics Act (280/2004), the Act on the Openness of Government Activities (621/1999), the EU's General Data Protection Regulation (EU) 2016/679 and the Data Protection Act (1050/2018). The data materials are protected at all stages of processing with the necessary physical and technical solutions. Statistics Finland has compiled detailed directions and instructions for confidential processing of the data. Employees have access only to the data essential for their duties. The premises where unit-level data are processed are not accessible to outsiders. Members of the personnel have signed a pledge of secrecy upon entering the service. Violation of data protection is punishable.
Further information: Data protection | Statistics Finland (stat.fi)
Confidentiality - data treatment
The use of data is restricted by usage rights. The phases of the statistical production process produce an end result that does not enable identification of individual data producers. All employees have signed a pledge of secrecy, where they have obliged to keep secret the data prescribed as confidential by virtue of the Statistics Act or the Act on the Openness of Government Activities. The data of the statistics are published on a less detailed level, so the data protection of individual respondents is not endangered.
The statistics on housing prices comply with active data protection. The aim of data protection for the statistics on housing prices is that the sales price or rent of an individual dwelling or financial statement data of an individual housing company cannot be deduced from the figures published by Statistics Finland. Individual data suppliers cannot be identified from the published data.
In the statistics on housing prices, each area, number of rooms and type of building contains several observed events. If there are too few observations in a particular category, the data are suppressed. If necessary, protection is performed by means of subsidiary protection or a less detailed classification if the category has repeatedly observations that are suppressed.
The protection measures concern data at the lowest level. At the most detailed level, data are released on dwellings belonging to a certain category for the number of rooms and year of construction in a certain district or postal code area. Protection is performed according to the threshold value rule so that cells too small a number of observations are suppressed. In order not to reveal individual observations, parallel categories or a higher category are also suppressed where necessary (secondary protection).
Statistics Finland publishes new statistical data at 8 am on weekdays in its web service. The release times of statistics are given in advance in the release calendar available in the web service. The data are public after they have been updated in the web service.
Further information: Publication principles for statistics at Statistics Finland
In addition to the statistics on prices of dwellings in housing companies, Statistics Finland releases quarterly statistics on real estate prices on the price development of single-family houses. Besides the data published by Statistics Finland, real estate agents, credit institutions and banks also publish information concerning dwelling prices and their development.
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.
Seasonally adjusted data in statistics on economic trends become revised because of the calculation method used. Additional information on a new time series observation is exploited in model-based calculation methods and this is reflected as changes in previous releases. Revisions of the latest figures to be seasonally adjusted are elaborated on in the releases and quality reports of statistics.
A summary table of the revisions that have taken place is also published in connection with key statistics on economic trends and some annual statistics. The table shows how the data for the statistical reference periods have changed between the first and the most recent statistical release.The data on prices of old dwellings in housing companies become revised over the year so that the final data for the year are published in the release concerning the first quarter of the following year.
On average, the revision in the monthly statistics on prices of dwellings in housing companies amounts to 0.3 percentage points either way for the whole country. The revision is bigger for smaller geographical areas. On average, the revision in quarterly statistics amounts to 0.2 percentage points either way for the whole country. Due to the change in the asset transfer tax, data revisions may change starting from 2020.
When the quarterly statistics on old dwellings in housing companies are published, they cover approximately 80 to 90 per cent all transactions made in the latest quarter. The latest monthly statistics contain around 70 per cent of all transactions. Statistics Finland receives the rest of the data later on as they arrive at the Tax Administration.
The monthly data become revised during the following months so that the final data for the year are published in the release concerning the first quarter of the following year. Further information about data revisions can be found in separate tables.
It is not recommended to use the latest month’s number of transactions in old dwellings in housing companies when describing the activity of trading; it rather describes the reliability of the price index and price per square metre in the latest time period. If only a few transactions are known, a couple of deviating cases may affect significantly the average price for an area.
The numbers of transactions in the latest months should be examined over a longer period than one month. Particularly in summer months, the number of transactions in the latest release of the monthly statistics may remain lower than usual and become revised in the coming months.
When these statistics are compared with data from other producers, the source of the basic data should be considered. The data published by Statistics Finland on old dwellings in housing companies are based on the Tax Administration's data on dwellings (data on ownership of dwellings in housing companies) and asset transfer tax statements. The monthly data become revised during the following months so that the final data for the year are usually published in the release concerning the first quarter of the following year. The data for the annual statistics cover nearly all private transactions and the transactions carried out through real estate agents.
For example, the data published by the Central Federation of Finnish Real Estate Agencies are based on data on dwelling transactions reported by the largest real estate agents and building contractors. The data cover 70 to 80 per cent of transactions in old dwellings in housing companies, in addition to which the data contain reported data on real estate transactions and transactions in new dwellings. The price index of old dwellings in blocks of flats published by the Central Federation of Finnish Real Estate Agencies differs from that published by Statistics Finland, for example, as regards quality standardisation and the calculation method of the index. The aim of the price index published by Statistics Finland is to describe the price development of the entire dwelling stock, while the objective of the index of the Central Federation of Finnish Real Estate Agencies is to describe price changes in completed transactions.
Quality management requires comprehensive guidance of activities. The quality management framework of the field of statistics is the European Statistics Code of Practice (CoP). The frameworks complement each other. The quality criteria of Official Statistics of Finland are also compatible with the European Statistics Code of Practice.
Further information: Quality management | Statistics Finland (stat.fi)
Data are released to all users at the same time. Statistical data may only be handled at Statistics Finland and information on them may be given before release only by persons involved in the production of the statistics concerned or who need the data of the statistics concerned in their own work before the data are published.
Further information: Publication principles for statistics
Are you looking for previously published documentation?
The documentation released before 5.4.2022 can be found on the archive pages of the statistics.Go to the archive page