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Aibinu, A A, Ling, F Y Y and Ofori, G (2011) Structural equation modelling of organizational justice and cooperative behaviour in the construction project claims process: contractors' perspectives. Construction Management and Economics, 29(05), 463–81.
Gambatese, J A and Hallowell, M (2011) Factors that influence the development and diffusion of technical innovations in the construction industry. Construction Management and Economics, 29(05), 507–17.
Jarkas, A and Horner, M (2011) Revisiting the applicability of learning curve theory to formwork labour productivity. Construction Management and Economics, 29(05), 483–93.
Kim, Y W, Han, S, Shin, S and Choi, K (2011) A case study of activity‐based costing in allocating rebar fabrication costs to projects. Construction Management and Economics, 29(05), 449–61.
Liou, F m, Yang, C h, Chen, B and Chen, W (2011) Identifying the Pareto‐front approximation for negotiations of BOT contracts with a multi‐objective genetic algorithm. Construction Management and Economics, 29(05), 535–48.
Pemsel, S and Widén, K (2011) Bridging boundaries between organizations in construction. Construction Management and Economics, 29(05), 495–506.
Shah, R K and Dawood, N (2011) An innovative approach for generation of a time location plan in road construction projects. Construction Management and Economics, 29(05), 435–48.
Thomas Ng, S, Fan, R Y C and Wong, J M W (2011) An econometric model for forecasting private construction investment in Hong Kong. Construction Management and Economics, 29(05), 519–34.
- Type: Journal Article
- Keywords: private construction investment; vector error correction model; regression analysis; stationarity
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/01446193.2011.570356
- Abstract:
Acknowledging the importance of the private construction market and a close linkage between private construction investment, public sector output and general economic conditions, there is a strong motivation to develop reliable models to forecast private construction investment. Based on the Hong Kong scenario, two modelling approaches, namely the vector error correction (VEC) and the multiple regression models are developed and compared for their modelling accuracy and ability to handle non?stationary time series data. The result suggests that private construction investment in Hong Kong can be predicted by reference to public investment in construction, gross domestic product (GDP) and unemployment rate. All in all, the VEC model is considered more accurate and robust in handling non?stationary data. Through the VEC model, it is possible to confirm that the crowding?in effect of public work programmes, though minimal, is discernible in private construction investment in Hong Kong. Yet private construction investment is more sensitive to general economic conditions, as represented by GDP and unemployment rate. The GDP could represent the ability of investors to pay for construction items, while the unemployment rate is used as a proxy for the willingness of end?users to purchase the construction items. The models proposed should help policy and decision makers formulate suitable policies and strategies to sustain the construction industry in the medium to long run.