Home > Statistics > Rents of dwellings > 2017 > Quality Description Definitions: Rents of Dwellings

Quality Description Definitions: Rents of Dwellings

• 1. Relevance
• 2. Methodological description
• 3. Correctness and accuracy of the data
• 4. Timeliness and promptness of the published data
• 5. Accessibility and transparency of the data
• 6. Comparability of the statistics
• 7. Coherence and consistency

1. Relevance

1.1 Information content and purpose of use

The annual statistics on rents describe the level of rents in the rental dwelling stock and changes in rents on the annual level. The statistics contain data on rents classified by area, type of financing, number of rooms and year of construction. The statistics also release data on new tenancies.

The purpose of the statistics on rents is to provide information about the development of the rental market to all those monitoring the rental market.

1.2. Concepts, classifications and data

The data and the data suppliers

The data for the statistics on rents derive from the interview data collected in connection with the Labour Force Survey and from the Social Insurance Institution's register of housing allowances. In addition, Statistics Finland’s data on the dwelling stock, derived from the Population Register Centre’s Register of Buildings and Dwellings, as well as data on migration and on the population structure are also utilised in the compilation of the annual statistics.

Used concepts:

Rent: Statistics Finland's concept of rent includes separately paid water charges and heating costs. Compensations for the use of facilities, such as a sauna or laundry room, are not included in the rent figures. The concept of rent in the statistics is also exclusive of electricity and Internet charges. In case the charges above are directly included in the rent paid by the tenant, they are taken into the calculation of the average rent, because these items cannot be easily separated from rents. The statistics release information about both the average rent per square metre of the dwelling (EUR/m2/month) and the total rents of an average dwelling per month. The average rents per square metre and total rents reported in the statistics are geometric averages.

Number of rooms: A room is defined as a space with one or more windows that has a floor area of at least seven square metres and a mean height of at least two metres. A hall, porch, bed recess or the like is not regarded as a room. Kitchen is not included in the number of rooms. Dwellings with at least three rooms are classified into room number category 3+.

ARA rental dwelling: the rent is determined by the regulations of the Act on the Use, Assignment and Redemption of State-subsidised (ARAVA) Rental Dwellings and Buildings and the Act on Interest Subsidy for Rental Housing Loans and Right of Occupancy Housing Loans. The prime cost principle is applied to the determination of rents of dwellings. Dwellings built with interest subsidy are included in ARA dwellings in the rent statistics.

Non-subsidised rental dwelling: the rent is determined by market demand.

New tenancy: In the annual rent statistics, a new tenancy is one started during the statistical reference year.

Distribution parameters:

Lower quartile = 25% of the observations remain below when the observations are arranged in size order.

Median = Middle observation when the observations are arranged in size order.

Upper quartile = 75% of the observations remain below when the observations are arranged in size order.

Classifications :

Regional division: Regional classifications of different levels are used in the statistics. The most detailed classification level is the sub-area classification of urban areas, which is based on the postcode classification according to price level and location. In addition to municipalities, regions and major regions (NUTS 2011), the statistics use diverse area combinations: such as Greater Helsinki, satellite municipalities around Greater Helsinki, and the classification according to the population. The Greater Helsinki area includes Helsinki, Espoo, Vantaa and Kauniainen. The satellite municipalities are Hyvinkää, Järvenpää, Kerava, Kirkkonummi, Nurmijärvi, Riihimäki, Sipoo, Tuusula and Vihti. A detailed regional classification can be found on the homepage of the statistics under Classifications.

2. Methodological description

Calculation of average rents per square metre

The average rents of rental dwellings per square metre describe the current rent level in dwellings of different size and type. Because the calculation is based on exhaustive register data with respect of the recipients of housing allowance and on interview data as concerns other rented dwellings, the observations are weighted by stratum weights in the calculation of average rents.

The calculation is performed in two stages. First, geometric average prices are calculated for most detailed classification levels, such as non-subsidised one-room flats in Helsinki sub-area 1 (centre). After this, averages are calculated for higher area levels using the value weights derived from the rent framework.

Calculation of changes

The annual change in rents is calculated from average rents for two successive years. There may be structural changes between different time points in the rented dwellings included in the statistics. Owing to the comprehensiveness of the data, a possible structural change in the rented dwellings included in the statistics can, however, be interpreted as a real structural change in the rental dwelling stock.

Formation of the framework for rent statistics

The framework for the rental dwelling stock used in the calculation of the annual statistics is formed from the Population Register Centre’s Building and Dwelling Register. All dwellings in permanent use that are not institutional dwellings (halls of residence, services flats and old people's homes) and that tenants occupy on the basis of a rental agreement are selected from the register. New tenancies in the framework are defined by means of the Population Register Centre's data on population structure.

Correction of rents in the register of housing allowances by means of data on population structure

The rent data in the Social Security Institution’s register of housing allowances are checked by means of the data on the population in the data on population structure. The rent is revised to correspond to the actual total rent of the dwelling. This correction measure has been done in the annual statistics on rents since the statistics for 2011:

3. Correctness and accuracy of the data

3.1. Reliability of the statistics

When considering the reliability of the statistics, attention must be paid to the fact that combining the register of housing allowances to the Register of Buildings and Dwellings is not always without its problems, especially as concerns pensioners and students (students do not necessarily register their student flats as their place of residence, etc.). In addition, all the data of the Population Information System and the register of housing allowances are not necessarily up-to-date. The register of housing allowances provides information about rents in dwellings of those receiving housing allowance. The register covers all dwellings receiving housing allowance. The rent level of other rented dwellings is estimated based on data on around 15,000 interviews. To ensure the reliability of the statistics, average rents per square metre and dispersion figures are not published in categories with fewer than 20 observations. The statistics make use of limits on rent per square metre based on the distribution, by which cases clearly deviating from the market level and errors in data are removed.

The register of housing allowances provides information about rents in dwellings of those receiving housing allowance. The register covers all dwellings receiving housing allowance. The rent level of other rented dwellings is estimated based on data on around 15,000 interviews.

To ensure the reliability of the statistics, average rents per square metre and dispersion figures are not published in categories with fewer than 20 observations. The statistics make use of limits on rent per square metre based on the distribution, by which cases clearly deviating from the market level and errors in data are removed.

3.2. Accuracy of the statistics

Cases with missing information about rent or floor area, or with exceptionally high or low rent due to contract within family or error in data entry are not accepted into the statistics. The acceptable ranges of rents per square metre by area are defined yearly. The definition is made based on the distribution of rents so that clearly erroneous cases are first removed from the data. After that, the limits in euros are defined, below which five per cent of the data and above which two per cent of the data remain. The observations falling below and above these limits are removed based on these limits that are determined yearly.

4. Timeliness and promptness of the published data

The annual rent statistics are published yearly at the beginning of March following the statistical reference year and the published data are final.

5. Accessibility and transparency of the data

This publication describes the rent level and changes in rents during the year preceding the time of publication. The latest data release from the statistics and a pdf version of the publication are published on Statistics Finland’s website on the publication date of the annual statistics on rents.

6. Comparability of the statistics

6.1. Comparability with other data

In addition to the annual statistics on rents, Statistics Finland publishes quarterly data on rents. The compilation of the annual statistics deviates in certain respects from that of the quarterly statistics. The clearest difference between the two sets of statistics is that in addition to interview data, the annual statistics also utilise data from the register of housing allowances, which are not used in the quarterly statistics. Thus, the basis of the data for the annual statistics is considerably broader than that of the quarterly statistics.

When these statistics are compared with data from other producers, the source of the basic data should be considered. The data in the annual statistics on rents are based on the Social Insurance Institution's register of housing allowances. Therefore, the statistics include a very comprehensive sample of the rental dwelling stock in the whole country.

6.2. Comparability over time

Because of comparability, the average rents for 2011 were also calculated with the same method as rents for 2012. The average rents for 2011 calculated in this new way can be found in the StatFin database service.

Students were transferred to the general housing allowance scheme in August 2017. The change is visible in the housing allowance data in that the separate group students was removed and all housing allowance customers are now classified either as recipients of general housing allowance or of housing allowance for pensioners. In the previous housing allowance data of the annual statistics, the data on students and their treatment differed from the data of recipients of general housing allowance. The above-mentioned standardisation of the data and treatment may have an effect on the comparability of the annual rent statistics of 2017 with the statistics of 2016. The effects are assessed to be minor and local.

7. Coherence and consistency

In addition to Statistics Finland's statistics on rents, KTI Finland publishes rent data for the largest towns two times per year. These rent data are based on the rents of non-subsidised rental dwellings owned by towns, non-profit corporations and insurance companies. Statistics Finland publishes annual and quarterly statistics on rents.

Source: Rents of dwellings, Statistics Finland

Inquiries: Martti Korhonen 029 551 3451, Outi Hautamäki 029 551 3228, asuminen.hinnat@stat.fi

Director in charge: Sami Saarikivi

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Updated 8.3.2018