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A panel vector error correction approach to forecasting demand in regional construction markets

journal contribution
posted on 2014-01-01, 00:00 authored by Jason Jiang, Chunlu LiuChunlu Liu
Reliable forecasting as to the level of aggregate demand for construction is of vital importance to developers, builders and policymakers. Previous construction demand forecasting studies mainly focused on temporal estimating using national aggregate data. The construction market can be better represented by a group of interconnected regions or local markets rather than a national aggregate, and yet regional forecasting techniques have rarely been applied. Furthermore, limited research has applied regional variations in construction markets to construction demand modelling and forecasting. A new comprehensive method is used, a panel vector error correction approach, to forecast regional construction demand using Australia’s state-level data. The links between regional construction demand and general economic indicators are investigated by panel cointegration and causality analysis. The empirical results suggest that both long-run and causal links are found between regional construction demand and construction price, state income, population, unemployment rates and interest rates. The panel vector error correction model can provide reliable and robust forecasting with less than 10% of the mean absolute percentage error for a medium-term trend of regional construction demand and outperforms the conventional forecasting models (panel multiple regression and time series multiple regression model). The key macroeconomic factors of construction demand variations across regions in Australia are also presented. The findings and robust econometric techniques used are valuable to construction economists in examining future construction markets at a regional level.

History

Journal

Construction management and economics

Volume

32

Issue

12

Pagination

1205 - 1221

Publisher

Taylor & Francis

Location

Abingdon, England

ISSN

0144-6193

Language

eng

Publication classification

C Journal article; C1 Refereed article in a scholarly journal

Copyright notice

2014, Taylor & Francis