As safe as houses.
The article looks at trends in home prices around the world in 2019. Countries have different homes prices since they depend on local factors such as gross domestic product (GDP) growth, interest rates, rents and incomes. A machine-learning algorithm called a random forest has been used to examine t...
| Publicado en: | Economist Vol. 431; no. 9149; pp. 85 - 86 |
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| Formato: | Artículo |
| Publicado: |
Economist Newspaper Limited
6/29/2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=137313196&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 137313196 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00130613 ECO jtl: Economist issn: 00130613 maglogo: N pubinfo: dt: 6/29/2019 vid: 431 iid: 9149 pid: 161 pub: Economist Newspaper Limited artinfo: ui: 137313196 ppf: 85 ppct: 1 formats: tig: atl: As safe as houses. aug: su: Rental housing Housing market Home prices Gross domestic product Interest rates Machine learning Random forest algorithms sug: subj: Rental housing Housing market Lessors of Residential Buildings and Dwellings Lessors of residential buildings and dwellings (except social housing projects) Home prices Gross domestic product Interest rates Machine learning Random forest algorithms ab: The article looks at trends in home prices around the world in 2019. Countries have different homes prices since they depend on local factors such as gross domestic product (GDP) growth, interest rates, rents and incomes. A machine-learning algorithm called a random forest has been used to examine the impact of these variables. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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