Abstract
In Singapore, the construction sector’s share in GDP has steadily climbed from 5.4 per cent in 1989 to 7.1 per cent in 1995. Its output has been growing at 11.9 per cent per annum since 1989. A growing outward trend has been the ‘regionalisation’ of the local construction industry with the result that there has been an increase in construction firms competing for projects abroad. Contracts won abroad will bring in export earnings to the economy that can offset, in part, the leakage due to imports of foreign services and building materials. With the maturing of Singapore’s economy, we shall see increasing refurbishment and restoration work in the future. As construction output is a derived demand, it also reflects the importance of inter-sectoral linkages and associative growth. This notion is supported by the high percentage which capital formation in construction contributes to the Gross Fixed Capital Formation (GFCF) in Singapore.
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References
Bergstrom, A.R. (1967), The Construction and Use of Economic Models, London, English Universities Press.
Bon, R. (1989), ‘Direct and Indirect Resource Utilisation by the Construction Sector: The Case of the USA since World War II’, Habitat International, 12(1), 49–74.
DiPasquale, D. and W.C. Wheaton (1995), Urban Economics and Real Estate Markets, Englewood Cliffs, NJ, Prentice Hall.
Garson, G.D. (1991), ‘Interpreting Neural-Network Connection Weights’, AI Expert, 6, 47–51.
Goh, B.H. (1996), ‘Residential Construction Demand Forecasting Using Economic Indicators: A Comparative Study of Artificial Neural Networks and Multiple Regression’, Construction Management & Economics, 14(1), 25–34.
Hebb, D.O. (1949), The Organisation of Behavior, New York, Wiley.
Hecht-Nielsen, R. (1989), ‘Theory of the Backpropagation Neural Network’, Proceedings of the International Joint Conference on Neural Networks, 1, 593–611, New York, IEEE Press. Hillebrandt, P. (1984), Analysis of the British Construction Industry, London, Macmillan.
Hirshleifer, J. (1958), ‘On the Optimal Investment Decision’, Journal of Political Economy, 66(4), 329–52.
Hodgkin, A.L. and A.F. Huxley (1952), ‘A Quantitative Description of Membrane Current and its Application to Conduction and Excitation in Nerve’, Journal of Physiology, 117, 500–44.
Hopfield, J.J. (1982), ‘Neural Networks and Physical Systems with Emergent Collective Computational Abilities’, Proceedings of the National Academy of Sciences, 79, 2554–58.
Jacobs, R.A., M.I. Jordan, S.J. Nowlan and G.E. Hinton (1991), ‘Adaptive Mixtures of Local Experts’, Neural Computation, 3, 79–87.
Koh, A.M.M. (1987), An Econometric Model for Forecasting Industrial Space Demand in Singapore, Unpublished PhD dissertation, University of Georgia, USA.
Matyas, J. (1965), ‘Random Optimization’, Automation and Remote Control, 26, 246–53.
Minsky, M. and S. Papert (1969), Perceptrons: An Introduction to Computational Geometry, Cambridge, MA, MIT Press.
Ofori, G. (1988), ‘Construction Industry and Economic Growth in Singapore’, Construction Management and Economics, 6, 57–70.
Ofori, G. (1993), Managing Construction Industry Development: Lessons from Singapore’s Experience, Singapore, Singapore University Press, NUS.
Rosenblatt, F. (1958), ‘The Perceptron: A Probabilistic Model for Information Storage and Organisation in the Brain’, Psychological Review, 65(6), 386–408.
Samad, T. (1988), ‘Backpropagation is Significantly Faster if the Expected Value of the Source Unit is Used for Update’, International Neural Network Society Conference Abstracts.
Tan, W. (1989), Subsector Fluctuations in Construction, Occasional Paper No. 1, Construction Management and Economics Research Unit, School of Building and Estate Management, National University of Singapore, Singapore.
Tang, J.C.S., P. Karasudhi and P. Tachopiyagoon (1990), ‘Thai Construction Industry: Demand and Projection’, Construction Management & Economics, 8, 249–57.
Turin, D.A. (1973), The Construction Industry: its Economic Significance and its Role in Development, London, University College London.
Widrow, B. and M.E. Hoff (1960), ‘Adaptive Switching Circuits’, IRE WESCON Convention Record, New York, 96–104.
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© 2003 Applied Econometrics Association
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Tan, F., Ofori, G. (2003). Estimating Construction Demand in Singapore: Potential of Neural Networks. In: Thalmann, P., Zarin-Nejadan, M. (eds) Construction and Real Estate Dynamics. Applied Econometrics Association Series. Palgrave Macmillan, London. https://doi.org/10.1057/9780230001190_4
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DOI: https://doi.org/10.1057/9780230001190_4
Publisher Name: Palgrave Macmillan, London
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