Agent-Based Modelling of House Price Evolution

Terence Bossomaier; Siti Amri; James Thompson

doi:10.1109/ALIFE.2007.367831

Agent-Based Modelling of House Price Evolution

Terence Bossomaier, Siti Amri, James Thompson

Research output: Book chapter/Published conference paper › Conference paper › peer-review

5 Citations (Scopus)

35 Downloads (Pure)

Abstract

Housing price growth is a complex mixture of external factors such as the growth of the economy, unemployment rates and the supply of land. It is also strongly dependent upon buyer and seller perceptions and attitudes, particularly during a boom period. External factors may be captured by a variety of methods, but the emergent price and sale volume resulting from human interactions is a problem in the dynamics of multiple cognitive agents. We describe a RePast model for house price growth using real-world GIS data with a fuzzy logic frameworkfor modelling agent behaviour.

Original language	English
Title of host publication	First ALife 07
Place of Publication	USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	463-467
Number of pages	5
ISBN (Electronic)	142440701X
DOIs	https://doi.org/10.1109/ALIFE.2007.367831
Publication status	Published - 2007
Event	IEEE Symposium of Artificial Life (ALife) - Honolulu, Hawaii, New Zealand Duration: 01 Apr 2007 → 05 Apr 2007

Conference

Conference	IEEE Symposium of Artificial Life (ALife)
Country/Territory	New Zealand
Period	01/04/07 → 05/04/07

Access to Document

10.1109/ALIFE.2007.367831

CSU289235Accepted author manuscript, 276 KB

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title = "Agent-Based Modelling of House Price Evolution",

abstract = "Housing price growth is a complex mixture of external factors such as the growth of the economy, unemployment rates and the supply of land. It is also strongly dependent upon buyer and seller perceptions and attitudes, particularly during a boom period. External factors may be captured by a variety of methods, but the emergent price and sale volume resulting from human interactions is a problem in the dynamics of multiple cognitive agents. We describe a RePast model for house price growth using real-world GIS data with a fuzzy logic frameworkfor modelling agent behaviour.",

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AB - Housing price growth is a complex mixture of external factors such as the growth of the economy, unemployment rates and the supply of land. It is also strongly dependent upon buyer and seller perceptions and attitudes, particularly during a boom period. External factors may be captured by a variety of methods, but the emergent price and sale volume resulting from human interactions is a problem in the dynamics of multiple cognitive agents. We describe a RePast model for house price growth using real-world GIS data with a fuzzy logic frameworkfor modelling agent behaviour.

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Agent-Based Modelling of House Price Evolution

Abstract

Conference

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