{"id":{"repo_id":"auckland-ms","oai_identifier":"oai:researchspace.auckland.ac.nz:2292/72936"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-ms/oai:researchspace.auckland.ac.nz:2292/72936","repository":{"repo_id":"auckland-ms","name":"University of Auckland","base_url":"https://researchspace.auckland.ac.nz/server/oai/request"},"display":{"title":"Predicting House Sale Prices in Newly Developed Suburbs Without Historical Sales","abstract":"There is a recent trend of housing developers designing masterplan suburbs based on new urbanist principles to solve the housing crisis all around the world. The aim of this study is to anticipate the value of housing features in recently developed suburbs using a Bayesian approach, and investigate the price premiums of masterplan suburbs in the Auckland housing market. We present the Standard House Configuration Model, where housing feature impacts are analyzed relative to the configuration of a standard house for easy interpretation. The benefit of using a Bayesian approach is that we describe housing feature impacts using highest density intervals, which more closely resemble the intuitive understanding of probability intervals than statistical confidence intervals. Our case study on the newly developed suburbs of Fairview Heights, Oteha, Stonefields, Long Bay, Flat Bush, Silverdale, and Hobsonville in Auckland, New Zealand, demonstrates that the posterior distributions from our model effectively capture the complex relationship between housing features and sale price (R2 value of 91.5%). From analyzing the seven newly developed suburbs in Auckland, New Zealand, we find evidence that masterplan suburbs have higher price premiums than traditional suburbs. Our model estimates that masterplan suburbs offer a 17.47% to 20.16% price premium compared to non-masterplan suburbs. The proposed model is cross-validated on four recently developed suburbs in Auckland. For comparable suburbs, our model is able to make reasonably accurate price predictions without using any historical sale records from the target suburb. This indicates that the insights into housing feature impacts are applicable to other new suburbs still in the planning stage and, therefore, have the potential to support future suburb developments.","abstract_html":"There is a recent trend of housing developers designing masterplan suburbs based on new urbanist principles to solve the housing crisis all around the world. The aim of this study is to anticipate the value of housing features in recently developed suburbs using a Bayesian approach, and investigate the price premiums of masterplan suburbs in the Auckland housing market. We present the Standard House Configuration Model, where housing feature impacts are analyzed relative to the configuration of a standard house for easy interpretation. The benefit of using a Bayesian approach is that we describe housing feature impacts using highest density intervals, which more closely resemble the intuitive understanding of probability intervals than statistical confidence intervals. Our case study on the newly developed suburbs of Fairview Heights, Oteha, Stonefields, Long Bay, Flat Bush, Silverdale, and Hobsonville in Auckland, New Zealand, demonstrates that the posterior distributions from our model effectively capture the complex relationship between housing features and sale price (R2 value of 91.5%). From analyzing the seven newly developed suburbs in Auckland, New Zealand, we find evidence that masterplan suburbs have higher price premiums than traditional suburbs. Our model estimates that masterplan suburbs offer a 17.47% to 20.16% price premium compared to non-masterplan suburbs. The proposed model is cross-validated on four recently developed suburbs in Auckland. For comparable suburbs, our model is able to make reasonably accurate price predictions without using any historical sale records from the target suburb. This indicates that the insights into housing feature impacts are applicable to other new suburbs still in the planning stage and, therefore, have the potential to support future suburb developments.","abstract_has_math":false,"creators":["Lin, Christina Yin-Chieh"],"institution":"ResearchSpace@Auckland","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Kempa-Liehr, Andreas","Mason, Andrew"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-24T01:05:11Z","subjects":["Machine Learning","Property Development"],"languages":[],"rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"rights_urls":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2292/72936","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kempa-Liehr, Andreas","Mason, Andrew"]},{"key":"dc:creator","label":"Author","values":["Lin, Christina Yin-Chieh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-16T22:25:13Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-07-16T22:25:13Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:publisher","label":"Institution","values":["ResearchSpace@Auckland"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["PhD"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Auckland"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Machine Learning","Property Development"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2292/72936"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["There is a recent trend of housing developers designing masterplan suburbs based on new urbanist principles to solve the housing crisis all around the world. The aim of this study is to anticipate the value of housing features in recently developed suburbs using a Bayesian approach, and investigate the price premiums of masterplan suburbs in the Auckland housing market. We present the Standard House Configuration Model, where housing feature impacts are analyzed relative to the configuration of a standard house for easy interpretation. The benefit of using a Bayesian approach is that we describe housing feature impacts using highest density intervals, which more closely resemble the intuitive understanding of probability intervals than statistical confidence intervals. Our case study on the newly developed suburbs of Fairview Heights, Oteha, Stonefields, Long Bay, Flat Bush, Silverdale, and Hobsonville in Auckland, New Zealand, demonstrates that the posterior distributions from our model effectively capture the complex relationship between housing features and sale price (R2 value of 91.5%). From analyzing the seven newly developed suburbs in Auckland, New Zealand, we find evidence that masterplan suburbs have higher price premiums than traditional suburbs. Our model estimates that masterplan suburbs offer a 17.47% to 20.16% price premium compared to non-masterplan suburbs. The proposed model is cross-validated on four recently developed suburbs in Auckland. For comparable suburbs, our model is able to make reasonably accurate price predictions without using any historical sale records from the target suburb. This indicates that the insights into housing feature impacts are applicable to other new suburbs still in the planning stage and, therefore, have the potential to support future suburb developments."]},{"key":"dc:title","label":"Title","values":["Predicting House Sale Prices in Newly Developed Suburbs Without Historical Sales"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kempa-Liehr, Andreas","Mason, Andrew"],"dc:creator":["Lin, Christina Yin-Chieh"],"dc:date.accessioned":["2025-07-16T22:25:13Z"],"dc:date.available":["2025-07-16T22:25:13Z"],"dc:date.issued":["2025"],"dc:description.abstract":["There is a recent trend of housing developers designing masterplan suburbs based on new urbanist principles to solve the housing crisis all around the world. The aim of this study is to anticipate the value of housing features in recently developed suburbs using a Bayesian approach, and investigate the price premiums of masterplan suburbs in the Auckland housing market. We present the Standard House Configuration Model, where housing feature impacts are analyzed relative to the configuration of a standard house for easy interpretation. The benefit of using a Bayesian approach is that we describe housing feature impacts using highest density intervals, which more closely resemble the intuitive understanding of probability intervals than statistical confidence intervals. Our case study on the newly developed suburbs of Fairview Heights, Oteha, Stonefields, Long Bay, Flat Bush, Silverdale, and Hobsonville in Auckland, New Zealand, demonstrates that the posterior distributions from our model effectively capture the complex relationship between housing features and sale price (R2 value of 91.5%). From analyzing the seven newly developed suburbs in Auckland, New Zealand, we find evidence that masterplan suburbs have higher price premiums than traditional suburbs. Our model estimates that masterplan suburbs offer a 17.47% to 20.16% price premium compared to non-masterplan suburbs. The proposed model is cross-validated on four recently developed suburbs in Auckland. For comparable suburbs, our model is able to make reasonably accurate price predictions without using any historical sale records from the target suburb. This indicates that the insights into housing feature impacts are applicable to other new suburbs still in the planning stage and, therefore, have the potential to support future suburb developments."],"dc:identifier.uri":["https://hdl.handle.net/2292/72936"],"dc:publisher":["ResearchSpace@Auckland"],"dc:rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"dc:rights.uri":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"dc:subject":["Machine Learning","Property Development"],"dc:title":["Predicting House Sale Prices in Newly Developed Suburbs Without Historical Sales"],"dc:type":["Thesis"],"thesis:degree_discipline":["Engineering"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["PhD"],"thesis:institution_name":["The University of Auckland"]},"updated_at":"2026-07-24T01:05:11Z"}