Publication:
Estimating of hedonic price models using robust regressions: Solving the outlier problem

dc.contributor.authorsÇaǧlayan E.
dc.date.accessioned2022-03-28T15:03:01Z
dc.date.accessioned2026-01-10T18:38:41Z
dc.date.available2022-03-28T15:03:01Z
dc.date.issued2013
dc.description.abstractThis paper analyses the hedonic price model for Istanbul real estate market, in order to determine the relationship between house prices and housing features by using OLS. Since the OLS suffers from heteroscedasticity, non-normality and outliers, we estimate the hedonic price model by using robust regression which is called L1 and M regressions to get rid of these problems of OLS. For the purpose of investigating the relation between house prices and features of houses in Istanbul, the survey data of and Člayan and Arikan's work (Quality and Quantity, 2011) were used. Results of the study indicate that while having a central heating system, natural gas, a certain level of security, garage and four faces, have an effect that increase house prices, being located in a site or on a street have a decreasing effect on the same. © International Economic Society.
dc.identifier.issn13071637
dc.identifier.urihttps://hdl.handle.net/11424/256914
dc.language.isoeng
dc.publisherInternational Economic Society
dc.relation.ispartofInternational Journal of Economic Perspectives
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectHedonic price model
dc.subjectOutlier
dc.subjectRobust regression
dc.titleEstimating of hedonic price models using robust regressions: Solving the outlier problem
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage20
oaire.citation.issue3
oaire.citation.startPage14
oaire.citation.titleInternational Journal of Economic Perspectives
oaire.citation.volume7

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