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    Forecasting Supply of Commerical Office Buildings Using Polynomial Distributed Lag Model

    Access Status
    Fulltext not available
    Authors
    Sing, Michael
    Love, Peter
    Wang, Xiangyu
    Smith, J.
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Sing, M. and Love, P. and Wang, X. and Smith, J. 2012. Forecasting Supply of Commerical Office Buildings Using Polynomial Distributed Lag Model, in Chynoweth, P. (ed), RICS COBRA 2012 The Construction, Building and Real Estate Research Conference of the Royal Institution of Chartered Surveyors, Sep 10-13 2012. Las Vegas, Nevada: RICS 2012.
    Source Title
    Proceedings of RICS COBRA 2012 The Construction, Building and Real Estate Research Conference of the Royal Institution of Chartered Surveyors
    Source Conference
    RICS COBRA 2012 The Construction, Building and Real Estate Research Conference of the Royal Institution of Chartered Surveyors
    ISBN
    978-1-84219-840-7
    School
    Department of Construction Management
    URI
    http://hdl.handle.net/20.500.11937/14135
    Collection
    • Curtin Research Publications
    Abstract

    Forecasting the supply of commercial office buildings is critical for the economic development. Using the data from Hong Kong, the major factors influencing the supply of commercial office buildings such as gross domestic product, property prices, vacancy rates, interest rate are examined. Unlike the investment in financial assets, commercial office building developments are characterized by a time lag from the decision to build until their completion. The lead-lag structure of these major factors in determining the supply of office buildings is identified. Using the technique of polynomial distributed lag, the lead-lag model is simulated, and provides a reliable forecast on the supply of office buildings. Considering the prevailing shortage of commercial office buildings as result of economic growth in Asia, the forecasts derived from the model are deemed to be useful for economists and property analysts to facilitate their investment decision-making in the future.

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