Arbeitspapier
Learning from man or machine: Spatial aggregation and house price prediction
House prices vary with location. At the same time the border between two neighboring housing markets tends to be fuzzy. When we seek to explain or predict house prices we need to correct for spatial price variation. A much used way is to include neighborhood dummy variables. In general, it is not clear how to choose a spatial subdivision in the vast space of all possible spatial aggregations. We take a biologically inspired approach, where different spatial aggregations mutate and recombine according to their explanatory power in a standard hedonic housing market model. We find that the genetic algorithm consistently finds aggregations that outperform conventional aggregation both in and out of sample. A comparison of best aggregations of different runs of the genetic algorithm shows that even though they converge to a similar high explanatory power, they tend to be genetically and economically different. Differences tend to be largely confined to areas with few housing market transactions.
- Sprache
-
Englisch
- ISBN
-
978-82-7490-268-8
- Erschienen in
-
Series: Centre for Land Tenure Studies Working Paper ; No. 4/18
- Klassifikation
-
Wirtschaft
Neural Networks and Related Topics
Urban, Rural, Regional, Real Estate, and Transportation Economics: Housing Demand
Housing Supply and Markets
- Thema
-
House price prediction
Machine learning
Genetic algorithm
Spatial aggregation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Sommervoll, Dag Einar
Sommervoll, Åvald
- Ereignis
-
Veröffentlichung
- (wer)
-
Norwegian University of Life Sciences (NMBU), Centre for Land Tenure Studies (CLTS)
- (wo)
-
Ås
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Sommervoll, Dag Einar
- Sommervoll, Åvald
- Norwegian University of Life Sciences (NMBU), Centre for Land Tenure Studies (CLTS)
Entstanden
- 2018
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