Effectiveness comparison of the residential property mass appraisal methodologies in the USA
Purpose - Quite a few statistical and artificial neural network (ANN) models have been developed for the mass appraisal of the real estate by the municipalities. The purpose of this paper is to report the results of a research conducted to compare the prediction accuracy of the three most used model...
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| Veröffentlicht in: | International journal of housing markets and analysis 2011-08, Vol.4 (3), p.224-243 |
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| container_title | International journal of housing markets and analysis |
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| creator | Chun Lin, Chung Mohan, Satish B. |
| description | Purpose - Quite a few statistical and artificial neural network (ANN) models have been developed for the mass appraisal of the real estate by the municipalities. The purpose of this paper is to report the results of a research conducted to compare the prediction accuracy of the three most used models: multiple regression model, additive nonparametric regression, and ANN.Design methodology approach - The three models were developed using the housing database of a town with 33,342 residential houses. In this database, the cutoff point for higher priced homes was $88 per square foot of living area.Findings - The research confirmed that using statistical and ANN models are reliable and cost-effective methods for mass appraisal of residential housing.Originality value - It was found that any of the three models can be used, with similar accuracy, for lower and medium-priced houses, but the ANN is considerably more accurate for higher priced houses. |
| doi_str_mv | 10.1108/17538271111153013 |
| format | Article |
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The purpose of this paper is to report the results of a research conducted to compare the prediction accuracy of the three most used models: multiple regression model, additive nonparametric regression, and ANN.Design methodology approach - The three models were developed using the housing database of a town with 33,342 residential houses. In this database, the cutoff point for higher priced homes was $88 per square foot of living area.Findings - The research confirmed that using statistical and ANN models are reliable and cost-effective methods for mass appraisal of residential housing.Originality value - It was found that any of the three models can be used, with similar accuracy, for lower and medium-priced houses, but the ANN is considerably more accurate for higher priced houses.</description><identifier>ISSN: 1753-8270</identifier><identifier>EISSN: 1753-8289</identifier><identifier>DOI: 10.1108/17538271111153013</identifier><language>eng</language><publisher>Bingley: Emerald Group Publishing Limited</publisher><subject>Accuracy ; Brain ; Housing ; Housing prices ; Human error ; Neural networks ; Neurons ; Real estate appraisal ; Residential areas ; Studies ; Variables</subject><ispartof>International journal of housing markets and analysis, 2011-08, Vol.4 (3), p.224-243</ispartof><rights>Emerald Group Publishing Limited</rights><rights>Copyright Emerald Group Publishing Limited 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c350t-c3cbe22c4a7e8627e276eb3587840a88ccf28889986ebd0f24b19e0a1198e0d93</citedby><cites>FETCH-LOGICAL-c350t-c3cbe22c4a7e8627e276eb3587840a88ccf28889986ebd0f24b19e0a1198e0d93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/17538271111153013/full/pdf$$EPDF$$P50$$Gemerald$$H</linktopdf><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/17538271111153013/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,776,780,961,11614,21674,27901,27902,52661,52664,53219,53347</link.rule.ids></links><search><creatorcontrib>Chun Lin, Chung</creatorcontrib><creatorcontrib>Mohan, Satish B.</creatorcontrib><title>Effectiveness comparison of the residential property mass appraisal methodologies in the USA</title><title>International journal of housing markets and analysis</title><description>Purpose - Quite a few statistical and artificial neural network (ANN) models have been developed for the mass appraisal of the real estate by the municipalities. The purpose of this paper is to report the results of a research conducted to compare the prediction accuracy of the three most used models: multiple regression model, additive nonparametric regression, and ANN.Design methodology approach - The three models were developed using the housing database of a town with 33,342 residential houses. In this database, the cutoff point for higher priced homes was $88 per square foot of living area.Findings - The research confirmed that using statistical and ANN models are reliable and cost-effective methods for mass appraisal of residential housing.Originality value - It was found that any of the three models can be used, with similar accuracy, for lower and medium-priced houses, but the ANN is considerably more accurate for higher priced houses.</description><subject>Accuracy</subject><subject>Brain</subject><subject>Housing</subject><subject>Housing prices</subject><subject>Human error</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Real estate appraisal</subject><subject>Residential areas</subject><subject>Studies</subject><subject>Variables</subject><issn>1753-8270</issn><issn>1753-8289</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kE1LAzEQhoMoWKs_wNvi2Wo-upvZYyn1AwoetDdhSbMTm7K7iclW6L83taKgdA4zw8vzzgxDyCWjN4xRuGUyF8Al20UuKBNHZLDTRsChPP7pJT0lZzGuKS0gBz4grzNjUPf2AzuMMdOu9SrY6LrMmaxfYRYw2hq73qom88F5DP02a1VilfdB2Zj0FvuVq13j3izGzHZfxsXz5JycGNVEvPiuQ7K4m71MH0bzp_vH6WQ-0iKnfcp6iZzrsZIIBZfIZYFLkYOEMVUAWhsOAGUJSa6p4eMlK5EqxkpAWpdiSK72c9OB7xuMfbV2m9CllRWA4EIWgiWI7SEdXIwBTeWDbVXYVoxWux9W_36YPNd7D7YYVFP_Wv6ila9NwukB_OCGT7KrgAU</recordid><startdate>20110809</startdate><enddate>20110809</enddate><creator>Chun Lin, Chung</creator><creator>Mohan, Satish B.</creator><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DPSOV</scope><scope>DWQXO</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K6~</scope><scope>KC-</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M2L</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope></search><sort><creationdate>20110809</creationdate><title>Effectiveness comparison of the residential property mass appraisal methodologies in the USA</title><author>Chun Lin, Chung ; 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| identifier | ISSN: 1753-8270 |
| ispartof | International journal of housing markets and analysis, 2011-08, Vol.4 (3), p.224-243 |
| issn | 1753-8270 1753-8289 |
| language | eng |
| recordid | cdi_emerald_primary_10_1108_17538271111153013 |
| source | Emerald Journals; Standard: Emerald eJournal Premier Collection |
| subjects | Accuracy Brain Housing Housing prices Human error Neural networks Neurons Real estate appraisal Residential areas Studies Variables |
| title | Effectiveness comparison of the residential property mass appraisal methodologies in the USA |
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