Home > Statistics > Rents of dwellings > 2012 > 4th quarter > Quality Description: Rents of dwellings

Quality Description: Rents of dwellings

• 1. Relevance
• 2. Calculation method
• 3. Framework of quarterly statistics on rents
• 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

The quarterly statistics on rents describe quarterly and year-on-year levels and changes of rents for the rental dwelling stock. The statistics are published quarterly approximately five weeks after the end of the examined quarter.

1.2. Concepts, classifications and data

1.2.1 The data and the data suppliers

The statistics on rents are compiled from interview data collected in connection with the monthly Labour Force Survey, Statistics Finland’s data on the dwelling stock, obtained from the Building and Dwelling Register of the Population Register Centre, and data on migration and population structure. Around 1,500 persons are interviewed monthly. The sample for one survey month consists of five rotation groups which have entered the Labour Force Survey at different points of time. The target population of the survey month changes gradually so that one third of the respondents change monthly. The Population Register Centre's Register of Buildings and Dwellings forms the quarterly framework for rents. The framework is updated annually.

This publication of the quarterly statistics contains information on rents for the whole country, the Greater Helsinki Area, rest of the country, municipalities surrounding the Greater Helsinki Area and other largest municipalities. The Greater Helsinki Area comprises Helsinki, Espoo, Vantaa and Kauniainen. The surrounding municipalities are Hyvinkää, Järvenpää, Kerava, Kirkkkonummi, Nurmijärvi, Riihimäki, Sipoo, Tuusula and Vihti.

The interview data for these statistics have been collected, and the quarterly index calculated since the first quarter of 2003.

1.2.2 Concepts

In these statistics the concept of rent includes separately payable water and heating charges, but not compensations paid for the use of amenities such as sauna or laundry room. Telephone and electricity charges are also excluded. The published average rents have been calculated per square metre of dwelling per month (€/m2/kk).

The concept of number of rooms excludes kitchen. The room number category of 3h+ refers to dwellings with at least three rooms.

An Arava dwelling refers to a dwelling built with a government housing loan, whose rent is determined on the cost coverage principle. Most Arava dwellings are owned by local government. Non-subsidised dwellings are other than Arava dwellings or interest supported dwellings. Rental dwellings receiving interest support are now also classified under gowernment-subsidised dwellings in these statistics.

A new tenancy refers to a tenancy that has started within less than 12 months from the reference month of a Labour Force Survey interview. For example, in the interview data of December 2009, new tenancies mean those that commenced on or after 1 January 2009.

2. Calculation method

The calculation method used for these quarterly rent statistics is a combination of a traditional method based on classification and a regression analysis (hedonic method).

The data of the rent statistics are classified by area, type of financing, duration of tenancy and number of rooms. The classification is based on the NUTS2 regional division that entered into force in 2003. The data within the NUTS2 areas are classified by region and major town. Division in type of financing is made into non-subsidised and government subsidised tenancies. Non-subsidised tenancies are further classified into old and new tenancies. The formed categories are finally classified by number of rooms (1h, 2h, 3h+).

The used classification does not necessarily homogenise the data adequately, because dwellings within a category may deviate in respect of their microlocation, floor area, year of completion, etc. The available data contain information about dwelling location at the postal code level, as well as about dwelling age and floor area. With the regression model this information can be used to correct the average price of a given category in the comparison period so that the obtained average price adjusted for quality takes into account internal compositional changes in relevant variables between the base and comparison periods. The used regression model is of the following format:

Regression model

where subindex i refers to the estimation category, j to the observation number and k to the municipality or postal code area within the category. Ln(pij) is the logarithmic price per square meter for dwelling i in area j. Variables Aijk are microarea indicators (postal code areas with large towns and municipality indicators with combined areas). Kaksio (duplex) and kolmio (triplex) are room number indicators and rivitalo (terraced house) is house type indicator. The variable uusi (new) indicates new tenancies.

The index of rents is calculated with the following Laspeyres formula:

Laspeyres

where

is the average price standardised for quality for category i in the comparison period,

is the category-specific index calculation weight and

is the average base period price for category i. The average prices are geometric averages.

The weights of the index calculation have been determined using data on dwelling stock and on population structure. The weight is the summed-up floor area of rental dwellings in a category.

3. Framework of quarterly statistics on rents

Permanently occupied dwellings (excluding student dwellings, old people’s homes and sheltered accommodation) whose tenure status was given as ”rental dwelling” were drawn form the Population Register Centre’s 2005 Building and Dwelling Register. The total number of such dwellings drawn was 727,027, and they divided into government subsidised (Arava) dwelllings and non-subsidised dwellings as shown in the figure below:

Framework of quarterly statistics on rents

4. Timeliness and promptness of the published data

The annual rent statistics are published four times in a year and the published data are final.

5. Accessibility and transparency of the data

A latest data release from the statistics and an electronic pdf version of the publication will be published on Statistics Finland’s website on the publication date of the quarterly statistics on rents.

6. Comparability of the statistics

Besides quarterly, Statistics Finland also publishes statistics on rents annually. The compilation of the quarterly statistics deviates in certain respects from that of the annual 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 Housing Allowance Register, which are not used in the quarterly statistics. Thus, the basis of the data for the annual statistics is considerably broader than the one for the quarterly statistics.

7. Coherence and consistency

Statistics Finland publishes annual and quarterly statistics on rents.

Source: House Rents, Statistics Finland

Inquiries: Martti Korhonen 09 1734 3451, Tomi Martikainen 09 1734 3632, asuminen@stat.fi

Director in charge: Leena Storgårds

---

Updated 8.2.2013