|Adjustments||Not Seasonally Adjusted|
|Building Completions||2019 Q3||49,748||54,024||#, SAAR||Quarterly|
|Building Permits||2019 Q3||2,392||2,871||Number, NSA||Quarterly|
|House Price Index||2019 Q3||798||781||1981=100, NSA||Quarterly|
|House Price Index for Existing Homes||2019 Q3||115.96||113.99||Index 2015=100, NSA||Quarterly|
|House Price Index for New Homes||2019 Q3||130.91||128.58||Index 2015=100, NSA||Quarterly|
|Non-residential Building Permits||2019 Q3||871||1,015||Number, NSA||Quarterly|
|Residential Building Permits||2019 Q3||1,521||1,856||Number, NSA||Quarterly|
|Residential Housing Starts||2019 Q3||8,896||12,644||#, NSA||Quarterly|
Real estate price index for one- and two-dwelling buildings for permanent living (1981=100) by region and period. Real estate price index estimates the price and value developments in the existing house stock.
One- or two-dwelling buildings for permanent dwelling include detached one- or two-dwelling buildings, terraced houses and linked buildings. Real estate with site leasehold rights are included.
The index is constructed out of house prices and the values from the Real Estate Tax Assessment Register.
The data used for a specific period is the sold properties for that specific period. The data set is not using a repeated sales method (matching real estate), but there is a possibility that a specific real estate made in t-1 also is included in the period t. For example: someone buys a real estate in January and is not satisfied and sells it in June. This real estate will be included in 1st quarter and 2nd quarter, but it is actually two purchases.
The source is not using information regarding the valuation banks and financial institutes uses when they issue loans in our calculations.
Additional information from the source:
The Real Estate Price Index for one- and two-dwelling houses estimates the changes in prices and values of all one- and two-dwelling houses. The Real Estate Price Index, unlike other indices and statistics on real estate, takes into consideration that houses sold might not be a random sample of all real estates and that the mix or composition of houses sold may vary from one year to the next.
To calculate the Real Estate Price Index, we use information from both the register of all real estate, one- and two-dwelling houses, as well as information of sold properties. Data from the two sources are divided into classes according to assessed value and region. Studies have shown that assessed value is an acceptable variable for classification. The purchase price mean is calculated for each cell (region and assessed value-class). A weighted mean of means is calculated. The weights are the number (or frequency) of real estates according to the register. The index is calculated as Laspeyres chain index and published as integer values only.
Subject to revisions