Type: Project Other Data - July 19, 2022, 9:54 a.m.
This file contains several indicators:
- number of advertisements for buying dwellings scraped from web portals in the period of February to April 2022. The advertisements are aggregated at LAU2 level, and they are unique and avoid counting multiple instances of the same advertisement across time.
-number of advertisements for renting dwellings scraped from web portals in the period of February to April 2022. The advertisements are aggregated at LAU2 level, and they are unique and avoid counting multiple instances of the same advertisement across time.
-advertised price of real estate. The data measures the average price of buying a property in €/sqm per LAU2 unit computed from web scraped data obtained from online portals. All typologies are included (multifamily / single family, new / old)
-advertised price of rental. The data measures the average price of renting a property in €/sqm per LAU2 unit computed from web scraped data obtained from online portals. All typologies are included (multifamily / single family, new / old)
-number of valid scraped advertisements for multifamily dwellings (apartments) aggregated at LAU2 level. It includes both rental and buying advertisements and requires homogenising the housing typologies, which are slightly different in each country.
-number of valid scraped advertisements for single family dwellings (single houses) aggregated at LAU2 level. It includes both rental and buying advertisements and requires homogenising the housing typologies, which are slightly different in each country.
-composite indicator on affordability of buying a dwelling. The indicator is calculated as the average price per sqm in each LAU2 over the monthly income measured as PPP in the NUTS3 region in which the advertisement is located. The resulting figure is the number of months of income required to buy a sqm (or room in Newry-Dundalk case study) of dwelling.
-composite indicator on affordability of renting a dwelling. The indicator is calculated as the average price per sqm in each LAU2 over the monthly income measured as PPP in the NUTS3 region in which the advertisement is located. The resulting figure is the number of months of income required to rent a sqm (or room in Newry-Dundalk case study) of dwelling.
-quotient between the average buying price over the average rental price in each LAU2 unit, both prices are calculated in previous indicators. It is available only in LAU2 units where both valid buying and renting advertisements exist. Higher values indicate that buying is proportionally more expensive that renting; thus, renting might be a better option. Lower values indicate the opposite.
-average length of the scraped advertisements. It is computed by counting how many times each advertisement appears during the 12 weeks we have scraped data (so it takes a value from 1 to 12). Afterwards, we apply the Inverse Distance Weight (IDW) methodology from ArcGIS toolbox to compute a surface grid to extrapolate the advertisement length in the whole region analysed.
The collected advertisements are cleaned according to the methodology explained in the technical annex. For some LAU2 units, no valid advertisements are found. The list of valid advertisements is used in all subsequent indicators.