Forecasting supply of commercial office buildings using polynomial distributed lag model

Chun-pong Sing, Peter E D Love, Xiangyu Wang, Jim Smith

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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.
Original languageEnglish
Title of host publicationProceedings of the Construction, Building and Real Estate Conference
EditorsD Kashiwagi, K Sullivan
Place of PublicationTempe, Arizona
PublisherArizona State University
Pages1353-1360
Number of pages8
ISBN (Print)9781842198407
Publication statusPublished - 2012
EventConstruction, Building and Real Estate Conference: COBRA 2012 - Las Vegas, Nevada, United States
Duration: 11 Sep 201213 Sep 2012

Conference

ConferenceConstruction, Building and Real Estate Conference
CountryUnited States
CityNevada
Period11/09/1213/09/12

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  • Cite this

    Sing, C., Love, P. E. D., Wang, X., & Smith, J. (2012). Forecasting supply of commercial office buildings using polynomial distributed lag model. In D. Kashiwagi, & K. Sullivan (Eds.), Proceedings of the Construction, Building and Real Estate Conference (pp. 1353-1360). Tempe, Arizona : Arizona State University.