Logit regression of rehousing
This topic discusses the estimation of the rehousing behaviour and relocation decisions of households in layer 3 of the Ruimtescanner XL.
The general framework will be the maximum likelihood estimation, or more specifically the logit regression of household i moving or not moving to location j
This study focuses on preferred residential density, and direct neighbourhood characteristics and their interaction with household characteristics as a further refinement to Tigris that models LMS-zonal preferences. It is likely that we'll take such zonal preference per household type (or household i) as exogenous, which incorporates preferences such as inter-zonal accessibility.
Relevant characteristics related to household i
- agegroup of oldest household member ( <65, >=65)
- number of persons (1, 2, 3+)
- number of working (0, 1+)
- household income category (1, 2, 3).
- original location before relocation (related to RIN i.e. Buurt-id)
Relevant characteristics related to j
- j=0 is the don't move choice: is this j the don't move choice?
- overall zonal attractiveness of j (as determined by Pearl).
- price of j (NVM only, or also WOZ?).
- waiting time
Location factors, relevant for both the origin of i and j, connected through RIN.
- structure factors:
- type: appt, terras-housing, (semi-) detachted, bungalow.
- density indicator: (see conceptual model: buildingarea / groundarea, floorarea / appt., appt. / building)
- environment factors:
- neighbourhood characteristics (typically within 1km range).
i.e.:
- average WOZ < 300m.
- parks > 1ha,
- horeca,
- supermarkt/levenmiddelen,
- distance to 3rd closest primary school
- neighbourhood characteristics (typically within 1km range).
i.e.:
Relevant characteristics related to the combination of i and j.
- distance i → j as an indicator for transition costs.
- difference of location factor values between origin i
- relative attractiveness of the Tigris-zone for actor i.
- relative attractiveness of any of the j characteristics for any of the i types.
