Please use this identifier to cite or link to this item: https://doi.org/10.1080/15578771.2011.622353
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dc.titleModeling Sectoral Construction Demand and Its Relationship with Economic Indicators
dc.contributor.authorHua, G.B.
dc.date.accessioned2013-10-14T04:40:06Z
dc.date.available2013-10-14T04:40:06Z
dc.date.issued2012
dc.identifier.citationHua, G.B. (2012). Modeling Sectoral Construction Demand and Its Relationship with Economic Indicators. International Journal of Construction Education and Research 8 (3) : 223-240. ScholarBank@NUS Repository. <a href="https://doi.org/10.1080/15578771.2011.622353" target="_blank">https://doi.org/10.1080/15578771.2011.622353</a>
dc.identifier.issn15578771
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/45777
dc.description.abstractThe published literature abounds with evidence of a need to relate construction activities with the general economic environment. The effect of economic fluctuations has a major impact on the performance of the construction sector. Economic indicators, which are measures of national economic performance, may serve as viable input variables to model construction demand. The general groups of measures that are closely related to demand for residential, industrial and commercial building construction include national output, population and employment, government fiscal policies, national consumption, investment and savings, industry and commerce, balance of payments, money and interest rates, and prices and wages. Traditionally, in macroeconomic modelling studies, independent variables are selected systematically by satisfying two main criteria: economic significance and statistical adequacy. However, this has not been the case in construction demand modelling studies. There has yet to be an approach which includes variable selection as part of the whole modelling process. Therefore, a systematic approach is proposed and validating it entails comparing the results of the present study with those of a similar study. The main finding implies that carrying out the statistical variable selection is an important step in finalising the set of variables to be used in the modelling process. © 2012 Copyright Taylor and Francis Group, LLC.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/15578771.2011.622353
dc.sourceScopus
dc.subjectconstruction demand
dc.subjecteconomic indicators
dc.subjectmodelling
dc.subjectpercentage error
dc.subjectR-square
dc.subjectstepwise variable selection
dc.typeArticle
dc.contributor.departmentBUILDING
dc.description.doi10.1080/15578771.2011.622353
dc.description.sourcetitleInternational Journal of Construction Education and Research
dc.description.volume8
dc.description.issue3
dc.description.page223-240
dc.identifier.isiutNOT_IN_WOS
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