|Unit||Index 2015Q1=100, NSA|
|Adjustments||Not Seasonally Adjusted|
|Source||French National Institute of Statistics and Economic studies (insee)|
|Release||House Price Index (Existing Homes) - Initial and Detailed Release|
|Dwelling Stocks||2019||36,609||36,247||Ths. #||Annual|
|Non-residential Building Permits||Oct 2019||3,541||3,285||Ths. sq. m, NSA||Monthly|
|Non-residential Housing Starts||Oct 2019||2,566||2,431||Ths. sq. m, NSA||Monthly|
|Building Permits||Sep 2019||40,025||32,449||#, NSA||Monthly|
|House Price Index||2019 Q3||110.7||107.8||Index 2015Q1=100, NSA||Quarterly|
|House Price Index for Existing Homes||2019 Q3||109.4||108.4||Index 2015Q1=100, SA||Quarterly|
|House Price Value for New Homes||2019 Q3||278,193||277,171||EUR, NSA||Quarterly|
|Housing Starts||Sep 2019||32,360||23,225||#, NSA||Monthly|
|Residential Building Permits||Sep 2019||37,285||30,134||#, NSA||Monthly|
|Residential Housing Starts||Sep 2019||30,762||22,156||#, NSA||Monthly|
|House Price Index for New Homes||2019 Q2||111.98||109.8||Index 2015=100, NSA||Quarterly|
For France, this house price index is a transaction price index measuring pure price changes between two consecutive quarters for dwellings sold. Quarterly from 1994.
The Paris Notaries Services manages a real estate database specifically for Ille-de-France. The source reports average sales price for houses for the region Ile-de-France and its departments. The departments that are included in the data set are Paris, Hauts-de-Siene, Siene-Saint-Dennis, Val-de-Marne, Seine-et-Marne, Yvelines, Essone, and Val-d’oise.
For a given quarter, the index is calculated as the weighted mean of the following two indices:
The Notaires - INSEE second-hand housing price index is based on a methodology validated by the Scientific Board of the Notaires-INSEE indices (Conseil scientifique des indices Notaires-Insee - CSIN). The new housing price index is based on an econometric model linking the new housing price logarithm to different variables that characterise the property: its type (house or apartment), its physical characteristics (floor space, number of rooms) and the geographic characteristics of the municipality in which it is located (size of the urban unit, ZEAT , coastal municipalities, winter sports and mountaineering resorts, etc.). This econometric model (in this case a hedonic model) is estimated over two consecutive quarters. There is also a time dummy variable among the explanatory variables which is used to adjust the average change in transaction prices between the two quarters, all other things being equal (i.e. with constant dwelling characteristics). The quarterly change in the index is obtained from the exponential of the coefficient associated with the time dummy. The model is said to be of “adjacent periods” as it is based on the price transition between two consecutive periods.
The housing price index for quarter Q of year Y is calculated in two steps: 1) weighted mean of the new and second-hand housing price indices, base 100 in Q4 of year Y-1; 2) chain-linking of the index to obtain an index expressed in base 100, as an annual average for 2010. The weightings of each of the two indices correspond to the respective share of new and second-hand housing in household expenditure on the purchase of dwellings in the course of year Y-2. This expenditure is obtained from the housing accounts published by the Observation and Statistics Service (Service de l’Observation et des Statistiques - SOeS) of the Ministry for Ecology, Sustainable Development, Transport and Housing.
Since October 2018, the source has advanced the base year to 2015=100.