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Building cost index forecasting with time series analysis

Kibar, Mustafa Alptekin
Building cost indices are widely used in construction industry to measure the rate of change of building costs as a combination of labor and material costs. Cost index forecast is crucial for the two main parties of construction industry, contactor, and the client. Forecast information is used to increase the accuracy of estimate for the project cost to evaluate the bid price. The aim of this study is to develop time series models to forecast building cost indices in Turkey and United States. The models developed are compared with regression analysis and simple averaging models in terms of predictive accuracy. As a result of this study, time series models are selected as the most accurate models in predicting cost indices for both Turkey and United States. Future values of building cost indices can be predicted in adequate precision using time series models. This useful information can be used in tender process in estimation of project costs, which is one of the critical factors affecting the overall success of a construction project. Better cost estimates shall enable contractors to produce cash flow forecasts more acurately. Furthermore accurate prediction of future prices is very useful for owners in budget allocations; moreover can help investors to evaluate project alternatives adequately.