Real estate prices: documentation of statistics
21.11.2024 valid documentation
Basic data of the statistics
Data description
The statistics on real estate prices describe the prices of single-family houses and single-family house plots and their quarterly and annual changes and price levels. Data on old single-family houses and single-family house plots are available with different classifications starting from 1985.
The price index of new single-family houses describes how much the price of building an average single-family house has developed. Data on new single-family houses on the level of the whole country are available starting from 2009.
The price index of new single-family houses describes how much the price of building an average single-family house has developed. Data on new single-family houses on the level of the whole country are available starting from 2009.
Statistical population
The population of the statistics on real estate prices comprises all real estate transactions made in Finland.
Statistical unit
The statistical unit for real estate prices is a single-family house and a single-family house plot. For the price index of new single-family houses the statistical unit is a new single-family house.
Unit of measure
The measurement units used in the statistics are the index point figure, percentage change, price per square metre in euros, floor area in square metres and data on the number of transactions.
Base period
For old single-family houses and plots three base periods are used in the statistics: 2020=100, 2015=100, 2010=100 and 1985=100. The base year 2010 and 2022 is used for the price index of new single-family houses.
Reference period
In quarterly statistics the reference period is a quarter and in annual statistics a calendar year.
Reference area
Real estate prices are published on the level of the whole country, excluding Åland.
Sector coverage
The price statistics on old single-family houses and single-family house plots are based on the National Land Survey’s purchase price register which contains all real estate transactions. However, the statistics do not include single-family houses located on rented plots.
The data for new single-family houses are based on the Building Cost Index and the development of prices of professional and own-account construction. Prices are measured by means of materials, wages and salaries, and prefabricated houses, and connection and official charges.
The data for new single-family houses are based on the Building Cost Index and the development of prices of professional and own-account construction. Prices are measured by means of materials, wages and salaries, and prefabricated houses, and connection and official charges.
Time coverage
Data on old single-family houses and plots are available with different classifications starting from 1985.
Data on new single-family houses on the level of the whole country are available starting from 2009.
Data on new single-family houses on the level of the whole country are available starting from 2009.
Frequency of dissemination
The statistics on real estate prices are published quarterly approximately 10 weeks from the end of a quarter. Annual data are released in connection with the publication for the last quarter. The released data are final data.
Concepts
Average area
The area of one-dwelling houses refers to floor area (m²) and the area of one-dwelling house plots to the total area of the plot.
Market price
The general actual selling price, or the price where supply and demand meet.
Nominal price index
Describes the change in prices relative to the base time period of the index (cf. real price index).
One-dwelling house plot
A real property whose use purpose is a residential building and has no buildings. The real estate is not situated in a shore plan area either. If the real estate is in a town plan area it is also required that the nature of the plan is a residential detached house area.
One-dwelling house real estate
A real property whose use purpose is a residential building area and which has only housing buildings and ancillary buildings, and it is not located in the shore plan area. If the real estate is in a building plan or town plan area it is also required that the nature of the plan is a residential building or detached house area.
Plot for detached houses
In the real estate price statistics plots for detached houses or unbuilt plots for detached houses are defined on the basis of the land register with the following conditions: The purpose of use of the real estate is a residential building plot and it has no buildings. The real estate must neither be situated in a shore plan area. If the real estate is in a building plan or town plan area it is also required that the quality of the plan is residential detached area, the register has information about the permitted building volume and the building efficiency coefficient is under 0.5. In sparsely-populated areas the last condition cannot be checked because the quality of the plan and the permitted building volume have not been defined in the plan areas in question.
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 estate
A real estate is a unit of ownership in a land or water area entered as real estate in the real estate register. Buildings and fixtures owned by the owner of a real estate and located on it belong to the real estate.
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.
Accuracy, reliability and timeliness
Overall accuracy
When viewing regional price indices of old single-family houses and plots, attention should be paid to the number of transactions in the area. If only a few transactions are made in the area, a few deviating cases can have a significant effect on the development of the index in the area. Then it would be advisable to examine longer term development instead of quarterly changes. It should also be noted that the statistics do not include single-family houses on rented plots.
The average prices of the statistics vary differently from the price index, because the price index takes into account changes in the distribution and their effects on prices regarding the characteristics of single-family houses and plots sold at different points in time, such as year of completion, floor area and location. The price index and average prices are both, depending on the situation, usable indicators.
The price index endeavours to measure as accurately as possible how much more/less an average single-family house or plot 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.
The average prices of the statistics vary differently from the price index, because the price index takes into account changes in the distribution and their effects on prices regarding the characteristics of single-family houses and plots sold at different points in time, such as year of completion, floor area and location. The price index and average prices are both, depending on the situation, usable indicators.
The price index endeavours to measure as accurately as possible how much more/less an average single-family house or plot 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.
Timeliness
The statistics on real estate prices are published quarterly approximately 7 weeks from the end of a quarter. Annual data are released in connection with the publication for the fourth quarter. The released data are final data.
Punctuality
The data have been published on the days indicated in the release calendar.
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 Whole country, Greater Helsinki, Rest of Finland and Satellite municipalities and the regional division based on population.
Comparability - over time
For old single-family houses and plots, data are available starting from 1995. Data on the index of real estate prices 1985=100 are available with a more detailed classification between 1985 and 2009. In addition, there is a long time series on the index of real estate prices 1985=100 on the level of the whole country, Greater Helsinki and the rest of Finland. This time series is always chained with the newest index, whereby 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 statistical model, review procedures, weight structure and classifications used in the calculation of old single-family houses and single-family house plots were renewed in 2017. The base year of the index was changed into 2015=100. Due to the changes, retrospectively calculated series for 2015 and 2016 differ from the previously published indices (2005=100 series, 1985=100 series).
In 2023, the weight structure, regional classification and base year used in the price index of old single-family houses were remodelled. The new base year is 2020=100. In addition, the calculation method of the index was reviewed so that the weights and the quality standardisation coefficients of the hedonic method will in future be updated yearly, which improves the quality of the index.
New categories in the regional classification are the six largest towns and the whole country exclusive of the six largest towns. The previously published base years (2015=100, 2010=100, 1985=100) for the index of old single-family houses and plots are continued by chaining them with changes according to the 2020=100 indices starting from the first quarter of 2023.
The product and weight structure was renewed in the price index of newly built single-family houses in 2023. The new base year is 2022=100. The new index is published on a more detailed level than before. The so-called prefabricated house index and its sub-indices are published especially as new.
The most significant change in the weight structure of the price index of newly built single-family houses can be seen in the clear growth in professional construction of single-family houses relative to own-account building.
The statistical model, review procedures, weight structure and classifications used in the calculation of old single-family houses and single-family house plots were renewed in 2017. The base year of the index was changed into 2015=100. Due to the changes, retrospectively calculated series for 2015 and 2016 differ from the previously published indices (2005=100 series, 1985=100 series).
In 2023, the weight structure, regional classification and base year used in the price index of old single-family houses were remodelled. The new base year is 2020=100. In addition, the calculation method of the index was reviewed so that the weights and the quality standardisation coefficients of the hedonic method will in future be updated yearly, which improves the quality of the index.
New categories in the regional classification are the six largest towns and the whole country exclusive of the six largest towns. The previously published base years (2015=100, 2010=100, 1985=100) for the index of old single-family houses and plots are continued by chaining them with changes according to the 2020=100 indices starting from the first quarter of 2023.
The product and weight structure was renewed in the price index of newly built single-family houses in 2023. The new base year is 2022=100. The new index is published on a more detailed level than before. The so-called prefabricated house index and its sub-indices are published especially as new.
The most significant change in the weight structure of the price index of newly built single-family houses can be seen in the clear growth in professional construction of single-family houses relative to own-account building.
Coherence - cross domain
The uniform regional classification and processing rules are applied as far as possible to the statistics on housing prices.
The National Land Survey of Finland publishes the purchase price statistics based on purchase price data. The main difference between the price index compiled by Statistics Finland and the National Land Survey’s purchase price statistics is that the purchase price statistics present primarily the distribution data of transactions and prices at a given period, while the price index focuses on measuring changes in prices from one period to another. The latter takes account of price differences caused by real estate properties sold in different periods and their effect is removed in the index calculation. The numbers released in the statistics differ for single-family house plots from the National Land Survey's purchase price register due to different selection rules.
The National Land Survey of Finland publishes the purchase price statistics based on purchase price data. The main difference between the price index compiled by Statistics Finland and the National Land Survey’s purchase price statistics is that the purchase price statistics present primarily the distribution data of transactions and prices at a given period, while the price index focuses on measuring changes in prices from one period to another. The latter takes account of price differences caused by real estate properties sold in different periods and their effect is removed in the index calculation. The numbers released in the statistics differ for single-family house plots from the National Land Survey's purchase price register due to different selection rules.
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
Data on old single-family houses and plots differ from each other as concerns regional classifications, for example. Due to the small number of plot observations, population categories were combined compared to the categories of single-family houses: there are four population categories in the statistics on single-family houses and three in the statistics on plots.
Source data and data collections
Source data
The statistics on real estate prices are based on the transaction prices in the National Land Survey's purchase price register. In addition, background information is searched for the transaction price data from the Digital and Population Data Services Agency’s Building and Dwelling Register.
For the price index for newly built single-family houses, prices are collected on materials, prefabricated houses, and connection and official charges, and on planning and monitoring costs. The data are supplied by Rakennustutkimus RTS Oy. In addition, the price index uses the building cost index of residential detached houses and the volume index of newbuilding for detached houses.
For the price index for newly built single-family houses, prices are collected on materials, prefabricated houses, and connection and official charges, and on planning and monitoring costs. The data are supplied by Rakennustutkimus RTS Oy. In addition, the price index uses the building cost index of residential detached houses and the volume index of newbuilding for detached houses.
Data collection
The National Land Survey delivers the data to Statistics Finland quarterly.
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Frequency of data collection
The transaction prices in the National Land Survey's purchase price register are submitted to Statistics Finland quarterly.
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Methods
Data compilation
Old single-family houses and plots
The data of the statistics on real estate prices are formed from the purchase price register of the National Land Survey by including transactions of single-family houses and single-family plots. Real estate transactions are linked to the Digital and Population Data Services Agency’s Building and Dwelling Register. 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 the data are processed, the lowest level indices or micro indices are calculated. The micro index has two different parts, price change unadjusted for quality and a quality adjustment factor. Price change unadjusted for quality is the geometric mean of the prices per square metre of the previous year's micro category divided by the geometric mean of the prices per square metre of the previous quarter. Because this change also includes changes caused by qualitative changes in transactions, a quality adjustment factor must be included.
In practice, the quality adjustment factor is the ratio of the geometric means of the present period calculated with the regression model and the observation-specific forecast prices of the previous year in the micro category. The regression model produces a forecast price for an observation with certain characteristics in the base year (or in other words for the price comparison period). When the forecast price is calculated both with the characteristics of the present time and with the features of the previous period, the ratio of the mean of these prediction prices in the micro category indicates the price change in the micro category due to differences in the characteristics. When the geometric mean price of the previous period is adjusted with this ratio, a quality-adjusted price change is obtained from the previous period to the current period.
Index is calculated with Log-Laspeyres index formula. Distribution figures, lower quartiles, medians and upper quartiles are also calculated for both prices and floor areas. In addition, average prices and average areas are calculated. Average prices are calculated as an arithmetic mean weighted by the floor areas of the quarter.
Finally, the indices of old base years are chained forward. It should be noted in the chaining of old series that methodological changes are big and have a clear effect on the obtained results. If we look at annual changes in the 1985=100 series in 2016 to 2017, we obtain different results compared to the annual changes in the 2015=100 series.
New single-family houses
The data of Rakennustutkimus RTS Oy used in the calculation of the price index for newly built single-family houses for the share of own-account construction are processed and entered into the production system. After this, the data of the volume index of newbuilding and the building cost index are retrieved.
The price index is calculated with Laspeyres' index formula by weighting together micro indices calculated for different building modes and constructors: on-site or prefabricated, professional or own-account construction.
The data of the statistics on real estate prices are formed from the purchase price register of the National Land Survey by including transactions of single-family houses and single-family plots. Real estate transactions are linked to the Digital and Population Data Services Agency’s Building and Dwelling Register. 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 the data are processed, the lowest level indices or micro indices are calculated. The micro index has two different parts, price change unadjusted for quality and a quality adjustment factor. Price change unadjusted for quality is the geometric mean of the prices per square metre of the previous year's micro category divided by the geometric mean of the prices per square metre of the previous quarter. Because this change also includes changes caused by qualitative changes in transactions, a quality adjustment factor must be included.
In practice, the quality adjustment factor is the ratio of the geometric means of the present period calculated with the regression model and the observation-specific forecast prices of the previous year in the micro category. The regression model produces a forecast price for an observation with certain characteristics in the base year (or in other words for the price comparison period). When the forecast price is calculated both with the characteristics of the present time and with the features of the previous period, the ratio of the mean of these prediction prices in the micro category indicates the price change in the micro category due to differences in the characteristics. When the geometric mean price of the previous period is adjusted with this ratio, a quality-adjusted price change is obtained from the previous period to the current period.
Index is calculated with Log-Laspeyres index formula. Distribution figures, lower quartiles, medians and upper quartiles are also calculated for both prices and floor areas. In addition, average prices and average areas are calculated. Average prices are calculated as an arithmetic mean weighted by the floor areas of the quarter.
Finally, the indices of old base years are chained forward. It should be noted in the chaining of old series that methodological changes are big and have a clear effect on the obtained results. If we look at annual changes in the 1985=100 series in 2016 to 2017, we obtain different results compared to the annual changes in the 2015=100 series.
New single-family houses
The data of Rakennustutkimus RTS Oy used in the calculation of the price index for newly built single-family houses for the share of own-account construction are processed and entered into the production system. After this, the data of the volume index of newbuilding and the building cost index are retrieved.
The price index is calculated with Laspeyres' index formula by weighting together micro indices calculated for different building modes and constructors: on-site or prefabricated, professional or own-account construction.
Data validation
The data are checked in every calculation round by going through the most significant changes and deviating observations.
Documentation on methodology
Indices of real estate prices are indices standardised for quality based on hedonistic regression analysis. Indices standardised for quality describe pure price change, that is, the effect on prices of qualitative differences of single-family houses/single-family house plots sold at different periods is removed. Before index calculation, the data have been limited so that included are single-family house plots of size 450 to 20,000 m² (town plan) and of size 1,000 to 20,000 m² (other than town plan) and single-family houses with a floor area of 40 to 440 m². In addition, clearly deviating price observations are removed from the calculation based on annually updated price limits. Indices are calculated according to the classification of area and population as fixed-weight Log-Laspeyres index. Weights of the 2015=100 series are based on the data of the register of buildings and dwellings for 2015.
The statistical model, review procedures, weight structure and classifications used in the calculation of old single-family houses and single-family house plots were renewed in 2017. In addition, the new base year 2015=100 was taken into use.
In the index regression models, the explanatory factors are in the model of single-family houses the house's age, the square of age, abutting a shoreline, floor area and in Greater Helsinki the distance to Helsinki and elsewhere in the country the distance to a big, medium size and small town. The model renewed in 2017 takes better into account the distance of the real estate to town or municipality centres.
In the regression model of plots, the explanatory factors are the quality of the plot plan (town/master, sparsely populated), nature of conveyance (municipality/other), abutting a shoreline, size of the plot, plot efficiency, and in Greater Helsinki the distance to Helsinki and elsewhere in the country the distance to a big, medium size and small town. In addition, the plot model takes into account the effect of the plot area separately in town plan area vs. other area. The model renewed in 2017 takes better into consideration the distance of the plot, plot efficiency and the quality of the plan in the plot area.
In the renewed statistics, plots located in a master plan area are also included, while before they were excluded from the statistics. Observations are not limited based on the distance of the municipality/Centre for Economic Development, Transport and the Environment or building efficiency, as in previous statistics. Changes in data limitations have a lowering effect on plots’ prices per square metre.
In the renewal of 2017, the area classification and the classification based on population were also updated. In the classification based on population, the key change is that Kuopio moved to the category of over 100,000 inhabitants.
The methodological description depicting the previously published series of the statistics can be read under the Methodological description section of the statistics.
The aim of the price index of new single-family houses is to follow the development of the prices of single-family housing construction. The index is formed by using the Building Cost Index and the indices describing professional and own-account construction. The sub-index describing construction of detached houses is derived from the Building Cost Index to the statistics. The price index for professional construction is a construction sale price index with variable weights and prices. For own-account construction, the development of total costs is followed from planning to yard work.
The index for newly built single-family houses is calculated according to the Laspeyres price index. In addition to the weight structure of the base year, the index calculation requires monthly price monitoring of selected commodities.
The weights of newly built single-family houses are formed for four components. The mode of building is a single-family house built on-site or from prefabricated elements and the constructor is a professional or own-account builder. The price index for newly built single-family houses is calculated by weighting these together.
The statistical model, review procedures, weight structure and classifications used in the calculation of old single-family houses and single-family house plots were renewed in 2017. In addition, the new base year 2015=100 was taken into use.
In the index regression models, the explanatory factors are in the model of single-family houses the house's age, the square of age, abutting a shoreline, floor area and in Greater Helsinki the distance to Helsinki and elsewhere in the country the distance to a big, medium size and small town. The model renewed in 2017 takes better into account the distance of the real estate to town or municipality centres.
In the regression model of plots, the explanatory factors are the quality of the plot plan (town/master, sparsely populated), nature of conveyance (municipality/other), abutting a shoreline, size of the plot, plot efficiency, and in Greater Helsinki the distance to Helsinki and elsewhere in the country the distance to a big, medium size and small town. In addition, the plot model takes into account the effect of the plot area separately in town plan area vs. other area. The model renewed in 2017 takes better into consideration the distance of the plot, plot efficiency and the quality of the plan in the plot area.
In the renewed statistics, plots located in a master plan area are also included, while before they were excluded from the statistics. Observations are not limited based on the distance of the municipality/Centre for Economic Development, Transport and the Environment or building efficiency, as in previous statistics. Changes in data limitations have a lowering effect on plots’ prices per square metre.
In the renewal of 2017, the area classification and the classification based on population were also updated. In the classification based on population, the key change is that Kuopio moved to the category of over 100,000 inhabitants.
The methodological description depicting the previously published series of the statistics can be read under the Methodological description section of the statistics.
The aim of the price index of new single-family houses is to follow the development of the prices of single-family housing construction. The index is formed by using the Building Cost Index and the indices describing professional and own-account construction. The sub-index describing construction of detached houses is derived from the Building Cost Index to the statistics. The price index for professional construction is a construction sale price index with variable weights and prices. For own-account construction, the development of total costs is followed from planning to yard work.
The index for newly built single-family houses is calculated according to the Laspeyres price index. In addition to the weight structure of the base year, the index calculation requires monthly price monitoring of selected commodities.
The weights of newly built single-family houses are formed for four components. The mode of building is a single-family house built on-site or from prefabricated elements and the constructor is a professional or own-account builder. The price index for newly built single-family houses is calculated by weighting these together.
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 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.
Release policy
The release calendar lists in advance all the statistical data and publications to be released over the year. Statistical releases can be found under statistics-specific releases. Statistical data are released at 8 am, unless otherwise indicated. The calendar is updated on weekdays. Statistics Finland's release calendar for the coming year is published every year in December.
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 quarterly statistics on real estate prices, Statistics Finland publishes monthly, quarterly and annual statistics on dwellings in housing companies. 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 owner-occupied housing price indices are published on Eurostat's website.
The National Land Survey also publishes data on real estate transactions. Price data on single-family houses are part of the indices of owner-occupied housing prices that Statistics Finland delivers to Eurostat.
The National Land Survey also publishes data on real estate transactions. Price data on single-family houses are part of the indices of owner-occupied housing prices that Statistics Finland delivers to Eurostat.
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.
Micro-data access
Unit-level data of the statistics are used only for producing the statistics and others than producers of statistics do not have access to unit-level data.
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.
Quality documentation
Earlier quality descriptions can be found here.
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.
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 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.