Real estate prices: documentation of statistics
Basic data of the statistics
Data description
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
Statistical unit
Unit of measure
Base period
Reference period
Reference area
Sector coverage
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 new single-family houses on the level of the whole country are available starting from 2009.
Frequency of dissemination
Concepts
Average area
Market price
Nominal price index
One-dwelling house plot
One-dwelling house real estate
Plot for detached houses
Quarterly change
Real estate
Real price
Real price index
Accuracy, reliability and timeliness
Overall accuracy
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
Punctuality
Comparability
Comparability - geographical
Comparability - over time
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).
For new single-family houses, data are available from 1995 onwards.
Coherence - cross domain
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
Coherence - internal
Source data and data collections
Source data
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
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Frequency of data collection
Rakennustutkimus RTS Oy supplies the data to Statistics Finland quarterly.
Methods
Data compilation
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 current quarter'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 period 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), in this case for 2015. 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.
When micro indices have been calculated from the previous quarter to the present quarter, these are used to chain the index forward for each micro area of the previous quarter. Micro indices are aggregated according to the index classification using value share weights as weights. After this, quarterly and annual changes and, if necessary, annual averages are calculated for the indices. 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
Documentation on methodology
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
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 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 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
Data sharing
Other
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
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
Quality assessment
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.