Use this URL to cite or link to this record in EThOS:
Title: Forecasting models of activity in industrial and commercial building
Author: Skinner, David
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 1999
Availability of Full Text:
Access through EThOS:
Access through Institution:
Despite its importance in national income, the level of activity in the construction sector has received little attention in the economics literature. The lack of studies attempting to forecast construction activity is surprising given that its volatility is often regarded as destabilising to the economy. Here, we model an important and growing component of construction, namely private industrial and commercial building. Construction activity is typically measured by output. To the extent that new construction output represents capital formation, output can be modelled as an investment problem. The theoretical investment literature is disparate and confusing but here, the leading models are presented in a unified framework in which the similarities and differences between them can be easily identified. We then go on to estimate a number of the models empirically. Some are econometric models consistent with traditional theories of investment. Others are based on vector autoregression (VAR) analysis which provides a largely statistical representation of a set of variables with minimum use of a priori restrictions but in which long-run relationships are preserved. The data required for model estimation is considerable and complicated by the effects of investment incentives embodied in the tax system. The forecasting performance of all the models is evaluated against forecasts generated by a benchmark model suggested by the data rather than by economic theory. In terms of forecasting performance, some of the investment models considered here are shown to be superior to the benchmark model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Economics & economic theory Economics Mathematical statistics Operations research Building