Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1080-8620.2004.00093.x
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dc.titleTransaction-based office price indexes: A spatiotemporal modeling approach
dc.contributor.authorTu, Y.
dc.contributor.authorYu, S.-M.
dc.contributor.authorSun, H.
dc.date.accessioned2013-10-14T05:12:57Z
dc.date.available2013-10-14T05:12:57Z
dc.date.issued2004
dc.identifier.citationTu, Y., Yu, S.-M., Sun, H. (2004). Transaction-based office price indexes: A spatiotemporal modeling approach. Real Estate Economics 32 (2) : 297-328. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1080-8620.2004.00093.x
dc.identifier.issn10808620
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/46296
dc.description.abstractThis study examines the potential of a two-order spatiotemporal autoregressive model with a Bayesian heteroskedasticity robust procedure in modeling stratatitled Singapore office unit transaction prices and in constructing transaction-based disaggregate office price indexes, The model reduces the problems caused by the infrequent trading of individual commercial properties. However, for those office properties that are located outside the CBD and also for those less frequently transacted, the power of the model in capturing these particular office buildings' price dynamics is limited. The significant differences of the office prices across the various office buildings and submarkets show that the model can capture the variation in office prices and track the timing of capital gains and losses that investors may accrue on spatially distributed office properties more accurately than hedonic or weighted least squares estimates.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1080-8620.2004.00093.x
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentREAL ESTATE
dc.description.doi10.1111/j.1080-8620.2004.00093.x
dc.description.sourcetitleReal Estate Economics
dc.description.volume32
dc.description.issue2
dc.description.page297-328
dc.identifier.isiut000221701100006
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