29.7.2022 valid documentation

Basic data of the statistics

Data description

The statistics on prices of dwellings in housing companies describe the unencumbered prices per square metre of old dwellings in housing companies, and monthly, quarterly and annual changes in them. For new dwellings data are published quarterly and annually. The statistics contain data classified by area and type of building for the examined period and for a longer time period. The purpose of the statistics is to provide information about price development and activity of the housing market.

Statistical population

The population of the statistics on prices of dwellings in housing companies comprises all transactions of dwellings in housing companies made in Finland.
 

Statistical unit

The statistical unit is a sold dwelling in a housing company.

Unit of measure

The measurement units used in the statistics are the index point figure, percentage change, price per square metre in euros and data on the number of transactions.

Base period

The following base periods are used in the statistics on old dwellings in housing companies: 1970=100, 1983=100, 2000=100, 2005=100, 2010=100, 2015=100 and 2020=100. The base year 2015 is used in the price index of new dwellings in housing companies.

Reference period

In monthly statistics the reference period is a calendar month, in quarterly statistics a quarter and in annual statistics a calendar year.

Reference area

Prices of dwellings in housing companies are published on the level of the whole country, excluding Åland.
 

Sector coverage

The statistics on the prices of old dwellings are based on the Tax Administration's data on dwellings and asset transfer tax statements. After the data are supplemented, the data include nearly all transactions of dwellings whose tenure is based on ownership of housing company shares. All transactions of housing company dwellings are not included immediately in the statistics, because the purchaser is allowed two months to pay the asset transfer tax. Supplementing of the data is also affected by the processing time of the data in the Tax Administration (insufficient data), whether the data have been reported on time and whether the electronic form has been used in the notification.

The statistics on prices of new dwellings are based on data collected from the largest real estate agents and building contractors. The data cover approximately 70 per cent of sold new dwellings. 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.

Time coverage

In terms of old dwellings, data compiled from the Tax Administration's asset transfer tax data are available on prices of dwellings in housing companies quarterly starting from 1987. Data provided by real estate agents are available for the period 1970 to 1986 with a less detailed regional classification than at present. For new dwellings, the time series have been calculated quarterly since 2005.

Frequency of dissemination

The statistics on prices of dwellings in housing companies are published monthly, quarterly and annually. Monthly data are released one month from the end of the statistical reference month and quarterly data are released simultaneously with the data for the last month of each quarter. The annual statistics are usually published in connection with the statistical release for the first quarter of the year following the statistical reference year.

Concepts

Dwelling

A dwelling refers to a room or a suite of rooms which is intended for year-round habitation; is furnished with a kitchen, kitchenette or cooking area; and has a floor area of at least 7 square metres. Every dwelling must have its own entrance. A single-family house may be entered through an enclosed porch or veranda. If a dwelling is entered through the premises of another dwelling, it is not regarded as a separate dwelling but instead those two constitute one dwelling.

First-time homebuyer

First-time dwelling transactions include those that are entitled to the exemption from asset transfer tax for first-time homebuyers (www.vero.fi).

Floor area

The floor area of a dwelling is measured from the inner surfaces of its walls. The figure includes the floor areas of the utility room, walk-in cupboard, bathroom, hobby room, sauna, washroom and dressing room, as well as the floor areas of rooms used for working unless used by hired employees.

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.

Hitas dwelling

Hitas is a regulation system for the price and quality level of dwellings built on rented plots owned by the City of Helsinki. Hitas dwellings refer to the dwellings subject to the regulation system in question.

Index

An index is a ratio describing the relative change in a variable (e.g. price, volume or value) compared to a certain base period (e.g. one year). The index point figure for each point in time tells what percentage the given examined variable is of its respective value or volume at the base point in time. The mean of the index point figures for the base period is 100.

Market price

The general actual selling price, or the price where supply and demand meet.

Monthly change

Monthly change is the relative change in the index from a time period one month earlier. The change is usually expressed as a percentage.

New dwelling

A new dwelling is completed in the statistical reference year or the year before it.

Nominal price index

Describes the change in prices relative to the base time period of the index (cf. real price index).

Number of rooms

The number of rooms is the number of rooms in a dwelling. Kitchen is not counted as a room. Dwellings with at least three rooms belong to the category 3h+.

Old dwelling

Old dwellings are other than new or unknown dwellings. (Unknown are those dwellings whose year of construction is not known.) (Cf. new dwelling.)

Point figure

Point figure is a change quantity used in price indices, which expresses the price, average price or index of the comparison period relative to the price, average price or index of the base period. The point figure of the base period is usually denoted by the number hundred. For example, if the point figure for a commodity at a certain point in time is 105.3, it means that the price of that commodity has risen by 5.3 per cent from the base period.

Price per square metre for a dwelling

The dwelling price statistics utilise the unencumbered price per square metre, which means that the loan portion is included in the price. The price concept published is price per square metre (€/m2).

Quarterly change

Quarterly change refers to the relative change in the index of the quarter compared with the index of the previous quarter. The change is usually expressed in percentages.

Real price

The price calculated with the prices of a certain base year, from which the effects of changes in the price level have been removed. In most cases the real price refers to the nominal price deflated with the Consumer Price Index.

Real price index

Indicates the change in real prices compared with the index base time period (e.g. 2000, 1983 or 1970). The real price index is derived by dividing the point figure of the nominal price index with the point figure of the Consumer Price Index of the corresponding time period and base year.

Transaction of shares in a housing corporation

A transaction of shares in a housing corporation refers to a sale of shares entitling ownership of a dwelling in a housing corporation, for which an asset transfer notification has been made to the Tax Administration.

Type of building

A classification for different types of dwellings. For example, blocks of flats, attached houses, detached houses. The dwelling price statistics utilise the categories blocks of flats and attached houses. The data on attached houses also include detached houses with shares in a housing corporation.

Type of financing

A classification describing the financing source of a dwelling or real estate.

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.

Weight structure

Describes what meaning each sub-index (commodity, employee group, etc.) belonging to the index has for total index.

Accuracy, reliability and timeliness

Overall accuracy

The results of the statistics describe the housing company share market relatively reliably. However, the number of transactions included in the statistics should be taken into consideration. If only a few transactions have been made, a couple of deviating cases may affect the average price for an area significantly. Therefore, the development of prices should always be examined in the longer term and not only for a certain time period. Attention should be paid to this when viewing the data on both the postal code level and the less detailed level.

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).

Timeliness

The statistics on prices of dwellings in housing companies are published monthly, quarterly and annually. Monthly data are released one month from the end of the statistical reference month and quarterly data are released simultaneously with the data for the last month of each quarter. The annual statistics are generally published in connection with the statistical release for the first quarter of the year following it.

Punctuality

The data are published on the days indicated in the release calendar. The release of the statistics on prices of old dwellings in housing companies had to be temporarily suspended from October 2019 to February 2020 due to changes in the asset transfer tax.

Data revision - practice

Monthly and quarterly data are updated retrospectively in connection with each release so that the final data for the statistical year are usually published with the data for the first quarter of the year following it.

Comparability

Comparability - geographical

The statistics are produced using the major regions according to the EU's regional classification system, NUTS2 (classification that entered into force on 11 July 2003), where Northern Finland and Eastern Finland are separate areas. In addition, the classification used is the whole country, Greater Helsinki, rest of Finland excluding Greater Helsinki, six largest cities, rest of Finland excluding six largest cities and satellite municipalities. In the statistics on prices of old dwellings in housing companies, data are also published by region according to the NUTS3 division of regions valid in 2015. The prices per square metre published annually by municipality are published using the municipal classification of 2020.

Comparability - over time

In terms of old dwellings, data compiled from the Tax Administration’s asset transfer tax data are available on prices of dwellings in housing companies quarterly starting from the year 1987. Data provided by real estate agents are available for the period 1970 to 1986 with a less detailed regional classification. For new dwellings, the time series have been calculated quarterly since 2005.

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

The uniform regional classification and processing rules are applied as far as possible to the statistics on housing prices.

Coherence - sub-annual and annual statistics

The data of the quarterly and annual releases are consistent with each other. Annual data are averages of the data for the quarters of the year in question.

Coherence - internal

The statistics on prices of old and new dwellings are internally as uniform as possible. The statistics differ from one another in terms of classifications, the classification of prices of new dwellings in housing companies is less detailed than that of old dwellings in housing companies due to small numbers of observations.
 

Source data and data collections

Source data

Old dwellings: The data of the price statistics are based on the Tax Administration's data on dwellings and asset transfer tax statements. Additionally, the Tax Administration’s Register of Real Estate Property and Statistics Finland’s data on the dwelling stock that are based on the Digital and Population Data Services Agency’s Register of Buildings and Dwellings are also used for the statistics. The monthly numbers of old dwellings in housing companies sold through real estate agents are based on the data from the price monitoring service of the Central Federation of Finnish Real Estate Agencies.

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.

Data collection

Data for Statistics Finland's own data collection is gathered by email and through the browser service.

Frequency of data collection

The data for the statistics on the prices of new dwellings in housing companies are collected quarterly from construction enterprises. The Tax Administration delivers to Statistics Finland data on dwellings and asset transfer taxes on a monthly basis as agreed. The Central Federation of Finnish Real Estate Agencies supplies the price monitoring service data monthly upon agreement.

Methods

Data compilation

Processing and calculation of data on the statistics on prices of old dwellings in housing companies

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.

Data validation

The data are checked on every calculation round by examining the most significant changes and deviating observations.

Seasonal adjustment

Seasonal adjustment is not used in the statistics on prices of dwellings in housing companies.

Documentation on methodology

The statistics on prices of dwellings in housing companies describe the unencumbered prices per square metre of dwellings in housing companies and changes in them. The statistics include both unencumbered prices per square metre calculated as averages directly from the data and the price index for dwellings in housing companies that describes the change in prices.

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

Statistics Finland

Contact organisation unit

Social Statistics

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 legislation

The 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 data materials are protected at all stages of processing with the necessary physical and technical solutions. Unit-specific data of the calculation data must be kept undisclosed. Data are handled only by persons who need the data in their work.

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).

Release policy

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

Data sharing

The data of the statistics are published on the home page of the statistics according to the release calendar.

Other

In addition to the statistics on prices of dwellings in housing companies, Statistics Finland releases data on the price development of single-family houses and single-family house plots in the quarterly statistics on real estate prices. The prices of dwellings in housing companies and single-family houses are included in the owner-occupied housing price indices delivered to Eurostat (Council Regulation (EU) No. 93/2013). The owner-occupied housing price indices are published on Eurostat's website http://ec.europa.eu/eurostat/web/housing-price-statistics

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.

Quality assessment

The data are checked before the statistics are calculated and the observations with clearly deviating prices or areas or otherwise deficient are removed from the calculations.

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 assurance

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)

User access

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 

Unless otherwise separately stated in connection with the product, data or service concerned, Statistics Finland is the producer of the data and the owner of the copyright. The terms of use for statistical data.

Data on owner-occupied housing price indices are delivered to Eurostat at the delivery times defined by Eurostat, which are slightly under three months from the end of the reference quarter.

Statistical experts

Petri Kettunen
Statistician
029 551 3558

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