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dc.contributor.authorZhang, Xin
dc.contributor.authorGeltner, David M
dc.contributor.authorde Neufville, Richard L
dc.date.accessioned2018-05-17T17:23:46Z
dc.date.available2018-05-17T17:23:46Z
dc.date.issued2018-03
dc.identifier.issn0895-5638
dc.identifier.issn1573-045X
dc.identifier.urihttp://hdl.handle.net/1721.1/115429
dc.description.abstractThis paper reports on the current state of a project to develop a system dynamics (SD) model for urban housing markets in China, aimed at facilitating policy analysis and supporting practical educational tools that might reach large numbers of potential entrepreneurs in China. Although numerous academic papers have applied SD models to real estate markets over the past generation, the technique remains relatively unknown and little used both in the academic economics literature and, more to the point, among practitioners and educators in the real estate community. Yet SD has the potential to address key needs among these constituencies, and extend and complement upon traditional economic methods. SD models are focused on modeling market transitions toward long-run equilibria, facilitating the study of the details of causality and the dynamic path of the market and features that are prominent in the history of housing markets in emerging markets. Different from intensive data-driven economic models, SD models are structural-based operational models that can more easily accommodate the actual non-market features and unique institutional components of these emerging real estate markets, where long-range historical data are not readily available. SD can provide intuitive and transparent model structures that should be able to improve pedagogy for educating large numbers of potential real estate entrepreneurs particularly in emerging market countries. For demonstration, in the present paper we choose to focus on the China-specific features of ‘speculative demand’ and ‘land financing scheme’, and use the newly developed SD model to explore the effects of land supply, “command-and-control” versus “market-driven” policies for housing in China. It is important to note, however, that while we chose China for the purposes of our study, the same technique can be applied to any emerging real estate market. Moreover, our research here can be seen as a stepping stone: Before a generalized SD model for emerging markets can be developed, it is both reasonable and appropriate to construct a model that is constrained to a manageable subset of the overall market space. Keywords: Chinese housing market; System dynamics analysis; Housing system; Housing price simulation; Housing bubbleen_US
dc.publisherSpringer USen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s11146-017-9650-zen_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceSpringer USen_US
dc.titleSystem Dynamics Modeling of Chinese Urban Housing Markets for Pedagogical and Policy Analysis Purposesen_US
dc.typeArticleen_US
dc.identifier.citationZhang, Xin et al. “System Dynamics Modeling of Chinese Urban Housing Markets for Pedagogical and Policy Analysis Purposes.” The Journal of Real Estate Finance and Economics (March 2018): 1-26 © 2018 The Authorsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Real Estateen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planningen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.mitauthorZhang, Xin
dc.contributor.mitauthorGeltner, David M
dc.contributor.mitauthorde Neufville, Richard L
dc.relation.journalJournal of Real Estate Finance and Economicsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-03-15T04:35:23Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.orderedauthorsZhang, Xin; Geltner, David; de Neufville, Richarden_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-7653-7080
dc.identifier.orcidhttps://orcid.org/0000-0002-1024-7555
dc.identifier.orcidhttps://orcid.org/0000-0002-4851-812X
mit.licensePUBLISHER_CCen_US


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