Publication:
Estimating House Prices in Emerging Markets and Developing Economies: A Big Data Approach

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dc.contributor.authorBehr, Daniela M.
dc.contributor.authorChen, Lixue
dc.contributor.authorGoel, Ankita
dc.contributor.authorHaider, Khondoker Tanveer
dc.contributor.authorSingh, Sandeep
dc.contributor.authorZaman, Asad
dc.date.accessioned2023-02-14T18:02:59Z
dc.date.accessioned2023-03-06T15:56:24Z
dc.date.available2023-02-14T18:02:59Z
dc.date.available2023-03-06T15:56:24Z
dc.date.issued2023-02
dc.description.abstractDespite the relevance of house prices for a variety of stakeholders as well as for macroeconomic and monetary policy making, reliable, publicly available house price data are largely absent in emerging markets and developing economies. Filling this void, this paper presents a systematic approach to collecting, analyzing, and assessing private property prices in emerging markets and developing economies. The paper uses data scraped from five countries’ largest real estate websites where private properties are listed for sale, to obtain price data and property attributes to establish a comprehensive data set that allows for both intra- and inter-country comparison of residential property prices. It then outlines the usability of these data by employing random forest estimation to predict the price of a standard housing unit—the basic house price—that is comparable across countries. While this approach is also applicable to filling wide data gaps in the provision of private property prices in developed economies, the paper focuses on how this approach can be applied to emerging markets and developing economies, where private property price data are particularly scarce.en
dc.identifierhttp://documents.worldbank.org/curated/en/099902502072329449/IDU0a13494320191f04f1508b99027642b859647
dc.identifier.doi10.1596/1813-9450-10301
dc.identifier.urihttps://hdl.handle.net/10986/39421
dc.languageEnglish
dc.language.isoen
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Papers;10301
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectEMERGING MARKET HOUSING PRICES
dc.subjectWEB SCRAPING DATA
dc.subjectRANDOM FOREST
dc.subjectMACHINE LEARNING
dc.subjectRESIDENTIAL REAL ESTATE COMPARISON
dc.subjectREAL ESTATE DATA COLLECTION
dc.titleEstimating House Prices in Emerging Markets and Developing Economiesen
dc.title.subtitleA Big Data Approachen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleEstimating House Prices in Emerging Markets and Developing Economies: A Big Data Approach
okr.date.disclosure2023-02-07
okr.date.doiregistration2025-04-10T11:21:56.910410Z
okr.date.lastmodified2023-02-07T00:00:00Zen
okr.doctypeWorking Papers
okr.doctypeWorking Papers::Policy Research Working Papers
okr.docurlhttp://documents.worldbank.org/curated/en/099902502072329449/IDU0a13494320191f04f1508b99027642b859647
okr.guid099902502072329449
okr.identifier.doi10.1596/1813-9450-10301
okr.identifier.externaldocumentumIDU-a1349432-191f-4f15-8b99-27642b859647
okr.identifier.internaldocumentum33997514
okr.identifier.reportWPS10301
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/099902502072329449/pdf/IDU0a13494320191f04f1508b99027642b859647.pdfen
okr.topicMacroeconomics and Economic Growth::Inflation
okr.topicPoverty Reduction::Poverty Monitoring & Analysis
okr.topicSocial Development::Poverty and Social Impact Analysis
okr.topicPrivate Sector Development::Emerging Markets
okr.unitIFC
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