Publicação
Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area
| Resumo: | Sales and rental prices were analysed at parish level using random forest regression for the Lisbon Metropolitan Area. Three dependent variables (new sales, new rents, and all rents) and a set of independent variables/associated factors were used, including location, building/dwelling characteristics, socioeconomic features, and tourism. This geographically-based approach aims not to predict housing prices, but to identify relevant factors associated with sales/rents, ranking their importance. The temporal dimension is also explored by comparing new and all existing rents. The results revealed similarities and differences between housing submarkets. New sales and new rents had similar spatial patterns and dynamics but were different from that of all rents, with different regulations over time. Strong associations were found between the dependent variables and the population's social status and urban quality. However, while location was more strongly related to new sales and new rents, revealing a greater dependence on the current dynamics of the housing market, socioeconomic features were more closely related to all rents, expressing the urban and demographic dynamics of recent decades. Different associated factors prevail inside and outside the Lisbon municipality. The results contribute to a better understanding of housing submarkets and the relationships between sales/rents and associated factors. |
|---|---|
| Autores principais: | Leal, Miguel |
| Outros Autores: | Carreiras, Marina; Alves, Sónia |
| Assunto: | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1865920812666585088 |
|---|---|
| author | Leal, Miguel |
| author2 | Carreiras, Marina Alves, Sónia |
| author2_role | author author |
| author_facet | Leal, Miguel Leal, Miguel Carreiras, Marina Alves, Sónia Carreiras, Marina Alves, Sónia |
| author_role | author |
| contributor_name_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Leal, Miguel\"},{\"Person.name\":\"Carreiras, Marina\"},{\"Person.name\":\"Alves, Sónia\",\"Person.identifier.orcid\":\"0000-0003-1231-8588\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Leal, Miguel Carreiras, Marina Alves, Sónia |
| datacite.date.Accepted.fl_str_mv | 2025-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2025-01-15T16:21:24Z |
| datacite.date.embargoed.fl_str_mv | 2025-01-15T16:21:24Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| datacite.titles.title.fl_str_mv | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| dc.contributor.none.fl_str_mv | Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Leal, Miguel Carreiras, Marina Alves, Sónia |
| dc.date.Accepted.fl_str_mv | 2025-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2025-01-15T16:21:24Z |
| dc.date.embargoed.fl_str_mv | 2025-01-15T16:21:24Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/97228 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Elsevier |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| dc.title.fl_str_mv | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Sales and rental prices were analysed at parish level using random forest regression for the Lisbon Metropolitan Area. Three dependent variables (new sales, new rents, and all rents) and a set of independent variables/associated factors were used, including location, building/dwelling characteristics, socioeconomic features, and tourism. This geographically-based approach aims not to predict housing prices, but to identify relevant factors associated with sales/rents, ranking their importance. The temporal dimension is also explored by comparing new and all existing rents. The results revealed similarities and differences between housing submarkets. New sales and new rents had similar spatial patterns and dynamics but were different from that of all rents, with different regulations over time. Strong associations were found between the dependent variables and the population's social status and urban quality. However, while location was more strongly related to new sales and new rents, revealing a greater dependence on the current dynamics of the housing market, socioeconomic features were more closely related to all rents, expressing the urban and demographic dynamics of recent decades. Different associated factors prevail inside and outside the Lisbon municipality. The results contribute to a better understanding of housing submarkets and the relationships between sales/rents and associated factors. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/fce1987d-850d-4c8c-83da-d35ab6467566/download |
| funding.funder.alternateName_str_mv | FCT FCT FCT FCT FCT |
| funding.funder.identifier_str_mv | http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 http://doi.org/10.13039/501100001871 |
| funding.funder.name_str_mv | Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia Fundação para a Ciência e a Tecnologia |
| funding.name_str_mv | DL 57/2016 6817 - DCRRNI ID 6817 - DCRRNI ID 6817 - DCRRNI ID |
| id | ul_831e2e2dfd33b11f7eb18cebfafa29d7 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/97228 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/97228 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Leal, Miguel Carreiras, Marina Alves, Sónia Alves, Sónia https://www.ciencia-id.pt/C615-9715-565A C615-9715-565A http://orcid.org/0000-0003-1231-8588 0000-0003-1231-8588 |
| publishDate | 2025 |
| publisher.none.fl_str_mv | Elsevier |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engElsevierpt_PTSales and rental prices were analysed at parish level using random forest regression for the Lisbon Metropolitan Area. Three dependent variables (new sales, new rents, and all rents) and a set of independent variables/associated factors were used, including location, building/dwelling characteristics, socioeconomic features, and tourism. This geographically-based approach aims not to predict housing prices, but to identify relevant factors associated with sales/rents, ranking their importance. The temporal dimension is also explored by comparing new and all existing rents. The results revealed similarities and differences between housing submarkets. New sales and new rents had similar spatial patterns and dynamics but were different from that of all rents, with different regulations over time. Strong associations were found between the dependent variables and the population's social status and urban quality. However, while location was more strongly related to new sales and new rents, revealing a greater dependence on the current dynamics of the housing market, socioeconomic features were more closely related to all rents, expressing the urban and demographic dynamics of recent decades. Different associated factors prevail inside and outside the Lisbon municipality. The results contribute to a better understanding of housing submarkets and the relationships between sales/rents and associated factors.application/pdfpt_PTDecoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan AreaLeal, MiguelCarreiras, MarinaPersonalAlves, SóniaDSpacehttp://dspace.org/items/f9e6d203-ff2c-47ea-81d1-35fb22aec7f1DSpacehttp://dspace.org/items/f9e6d203-ff2c-47ea-81d1-35fb22aec7f1AlvesSóniaCiência IDhttps://www.ciencia-id.ptC615-9715-565AORCIDhttp://orcid.org0000-0003-1231-8588Researcher IDhttps://www.researcherid.comAAN-4439-2021Scopus Author IDhttps://www.scopus.com56125008200Scopus Author IDhttps://www.scopus.com56125008200HostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptISSNIsPartOf0264-2751DOIIsPartOf10.1016/j.cities.2024.1056312025-01-15T16:21:24Z20252025-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/97228http://purl.org/coar/access_right/c_abf2open accessHousingReal estateSales pricesRental pricesRandom forestMachine learning12654880 bytesFundação para a Ciência e a TecnologiaImigração, Território e Estratégias de Habitação - Imigração, gentrificação e produção de cidade: Um estudo da situação na Área Metropolitana de Lisboa de Maruna Gaboleira CarreirasCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaNot AvailableDL 57/2016Crossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaInterdisciplinary Centre of Social Sciences6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaCentre of Geographical Studies6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871Fundação para a Ciência e a TecnologiaLaboratory for Sustainable Land Use and Ecosystem Services6817 - DCRRNI IDCrossref Funder IDhttp://doi.org/10.13039/501100001871literaturehttp://purl.org/coar/resource_type/c_6501journal article2025http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/fce1987d-850d-4c8c-83da-d35ab6467566/downloadCities158119 |
| spellingShingle | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area Leal, Miguel Housing Real estate Sales prices Rental prices Random forest Machine learning Leal, Miguel Housing Real estate Sales prices Rental prices Random forest Machine learning |
| status | SINGLETON |
| subject.fl_str_mv | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| title | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| title_full | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| title_fullStr | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| title_full_unstemmed | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| title_short | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| title_sort | Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: a random forest approach for the Lisbon Metropolitan Area |
| topic | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| topic_facet | Housing Real estate Sales prices Rental prices Random forest Machine learning |
| url | http://hdl.handle.net/10400.5/97228 |
| visible | 1 |