The predictive performance of multilevel models of housing sub-markets: A comparative analysis

Much of the housing sub-market literature has focused on establishing methods thatallow the partitioning of data into distinct market segments. This paper seeks tomove the focus on to the question of how best to model sub-markets once they havebeen identified. It focuses on evaluating the effectiven...

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Main Authors: Leishman, C., Costello, Greg, Rowley, Steven, Watkins, C.
Format: Journal Article
Published: Sage Publications Ltd. 2013
Online Access:http://hdl.handle.net/20.500.11937/41944
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author Leishman, C.
Costello, Greg
Rowley, Steven
Watkins, C.
author_facet Leishman, C.
Costello, Greg
Rowley, Steven
Watkins, C.
author_sort Leishman, C.
building Curtin Institutional Repository
collection Online Access
description Much of the housing sub-market literature has focused on establishing methods thatallow the partitioning of data into distinct market segments. This paper seeks tomove the focus on to the question of how best to model sub-markets once they havebeen identified. It focuses on evaluating the effectiveness of multilevel models as atechnique for modelling sub-markets. The paper uses data on housing transactionsfrom Perth, Western Australia, to develop and compare three competing sub-marketmodelling strategies. Model 1 consists of a city-wide ‘benchmark’; model 2 providesa series of sub-market-specific hedonic estimates (this is the ‘industry standard’) andmodels 3 and 4 provide two variants on the multilevel model (differentiated by variationin the degrees of spatial granularity embedded in the model structure). Theresults suggest that the more granular multilevel specification enhances empiricalperformance and reduces the incidence of non-random spatial errors.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T09:09:44Z
publishDate 2013
publisher Sage Publications Ltd.
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spelling curtin-20.500.11937-419442017-09-13T14:21:31Z The predictive performance of multilevel models of housing sub-markets: A comparative analysis Leishman, C. Costello, Greg Rowley, Steven Watkins, C. Much of the housing sub-market literature has focused on establishing methods thatallow the partitioning of data into distinct market segments. This paper seeks tomove the focus on to the question of how best to model sub-markets once they havebeen identified. It focuses on evaluating the effectiveness of multilevel models as atechnique for modelling sub-markets. The paper uses data on housing transactionsfrom Perth, Western Australia, to develop and compare three competing sub-marketmodelling strategies. Model 1 consists of a city-wide ‘benchmark’; model 2 providesa series of sub-market-specific hedonic estimates (this is the ‘industry standard’) andmodels 3 and 4 provide two variants on the multilevel model (differentiated by variationin the degrees of spatial granularity embedded in the model structure). Theresults suggest that the more granular multilevel specification enhances empiricalperformance and reduces the incidence of non-random spatial errors. 2013 Journal Article http://hdl.handle.net/20.500.11937/41944 10.1177/0042098012466603 Sage Publications Ltd. fulltext
spellingShingle Leishman, C.
Costello, Greg
Rowley, Steven
Watkins, C.
The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title_full The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title_fullStr The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title_full_unstemmed The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title_short The predictive performance of multilevel models of housing sub-markets: A comparative analysis
title_sort predictive performance of multilevel models of housing sub-markets: a comparative analysis
url http://hdl.handle.net/20.500.11937/41944