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dc.contributor.authorFagereng, Andreas
dc.contributor.authorHolm, Martin Blomhoff
dc.contributor.authorTorstensen, Kjersti Næss
dc.date.accessioned2022-02-07T13:44:55Z
dc.date.available2022-02-07T13:44:55Z
dc.date.created2020-12-14T20:41:06Z
dc.date.issued2020
dc.identifier.citationJournal of Economic and Social Measurement, 2020, vol. 45, no. 1, pp. 65-81,en_US
dc.identifier.issn0747-9662
dc.identifier.urihttps://hdl.handle.net/11250/2977541
dc.descriptionNote: [1] The article should not be reported as representing the views of Statistics Norway or Norges Bank. The views expressed are those of the authors and do not necessarily reflect those of Statistics Norway or Norges Bank.en_US
dc.description.abstractWe provide a new estimate of household-level housing wealth in Norway between 1993 and 2015 using an ensemble machine learning method on housing transaction data. The new housing wealth measure is an improvement over existing data sources for two reasons. First, the model outperforms previously applied regression models in out-of-sample prediction precision. Second, we extend the sample of estimated housing wealth by including cooperative units, non-id apartments, and cabins.en_US
dc.language.isoengen_US
dc.publisherIOS Pressen_US
dc.subjectMachine learningen_US
dc.subjectHousing wealthen_US
dc.subjectHouse pricesen_US
dc.titleHousing wealth in Norway, 1993–2015en_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber65-81en_US
dc.source.volume45en_US
dc.source.journalJournal of Economic and Social Measurementen_US
dc.source.issue1en_US
dc.identifier.doi10.3233/JEM-200471
dc.identifier.cristin1859741
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode1


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