|Adjustments||Not Seasonally Adjusted|
|Source||Ministère des Transports, de l'Equipement, du Tourisme et de la Mer|
|Release||Construction Permits and Starts|
|Non-residential Building Permits||Mar 2019||3,460||3,498||Ths. sq. m, NSA||Monthly|
|Non-residential Housing Starts||Mar 2019||2,601||2,120||Ths. sq. m, NSA||Monthly|
|Dwelling Stocks||2018||36,330||35,944||Ths. #||Annual|
|House Price Index||2018 Q4||107.4||108||Index 2015Q1=100, NSA||Quarterly|
|House Price Index for Existing Homes||2018 Q4||107.6||106.7||Index 2015Q1=100, SA||Quarterly|
|House Price Index for New Homes||2018 Q4||110.19||108.04||Index 2015=100, NSA||Quarterly|
|House Price Value for New Homes||2018 Q4||273,359||259,307||EUR, NSA||Quarterly|
|Building Permits||Oct 2017||47,129||49,330||Number, NSA||Monthly|
|Housing Starts||Oct 2017||35,297||33,614||#, NSA||Monthly|
|Residential Building Permits||Oct 2017||44,208||45,494||Number, NSA||Monthly|
|Residential Housing Starts||Oct 2017||32,394||31,434||Number, NSA||Monthly|
The results are published from the database Sit @ del2. It gathers information on building permits (permits) and housing starts provided by the department and ministry by local collectors. The results are expressed according to the date on which the event (authorization, open yard, etc.) is registered in the database Sit @ del2. These figures differentiate between new construction (completely new buildings) and construction on existing buildings (changes to existing housing or building additional housing adjacent to an existing building). The figures include the total number of housing units divided between ordinary and residential homes. In ordinary homes, a distinction is made between individual dwellings (pure and grouped) and collective dwellings. The housing residences (homes for the elderly, students, tourism, etc.) are characterized by the provision of individualized services (recreation, food, care or otherwise) in addition to lodging. Homes or hotels that comprise only rooms and common services are not classified as homes but as local hotel accomodations.
The methodology of statistical information on building permits and housing starts has changed since the April 2009 release of the series. Now, the series are released by date according to the date on which the event (authorization, open yard, etc.) is registered in the database Sit @ del2. See below for more information on the methodology of the series.
The methodological changes described below apply to all historical data, including the early periods before the change in methodology, because the historical data were recalculated. The changes during the month (at the time of the data release) on permits already published (included on statistics for months or years earlier) are grouped in a new series called "patches" available on the website SOeS. This monthly series is like any other. This series includes cancellations and deviations (positive or negative) due to such modification to permits. Cancellations are also subject to a separate series. With this new method of accounting for cancellations and changes to permits, data at the time of release are not altered after publication each month. In the past, data were corrected during the following months. Consequently, annual data at the time of release account for the published data throughout the 12 months of the year (or 12 months 'rolling'). The new series' that distinguish new construction and building on existing permits allows the source to take better account of certain transactions, such as some pardons.
The results of authorizations are final.
The "Other" category includes starts of retirement homes, homes on military bases, and residences in convents, etc.
Moody's Analytics seasonally adjusts and annualizes total residences (HSQSTRRESUM.IFRA). The adjustment was done using U.S. Census Bureau's X-12 ARIMA. The data is annualized by multiplying the seasonally adjusted monthly value by 12. The period from April-1982 to December-1985 was estimated by Moody's Analytics. The values from INSEE for this period are extremely volatile and do not match periods prior or post. The estimates were derived by dividing the last month in the quarter by 3 and interpolating the intervening months using a liner spline.