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

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  • Heng Jiang
  • Chunlu Liu

Abstract

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.

Suggested Citation

  • Heng Jiang & Chunlu Liu, 2014. "A panel vector error correction approach to forecasting demand in regional construction markets," Construction Management and Economics, Taylor & Francis Journals, vol. 32(12), pages 1205-1221, December.
  • Handle: RePEc:taf:conmgt:v:32:y:2014:i:12:p:1205-1221
    DOI: 10.1080/01446193.2014.977800
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    Cited by:

    1. Wesam Salah Alaloul & Muhammad Ali Musarat & Muhammad Babar Ali Rabbani & Qaiser Iqbal & Ahsen Maqsoom & Waqas Farooq, 2021. "Construction Sector Contribution to Economic Stability: Malaysian GDP Distribution," Sustainability, MDPI, vol. 13(9), pages 1-26, April.
    2. Eka Sudarmaji & Noer Azam Achsani & Yandra Arkeman & Idqan Fahmi, 2021. "Can Energy Intensity Impede the CO2 Emissions in Indonesia? LMDI-Decomposition Index and ARDL: Comparison between Indonesia and ASEAN Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 308-318.
    3. Ma, Le & Liu, Henry J. & Edwards, David J. & Sing, Michael C.P., 2021. "Housing price dynamics on residential construction: A case study of the Australian property sector," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 525-532.
    4. Antti Kurvinen & Arto Saari & Juhani Heljo & Eero Nippala, 2021. "Modeling Building Stock Development," Sustainability, MDPI, vol. 13(2), pages 1-17, January.
    5. Douglas Mugabe & Levan Elbakidze & Tim Carr, 2021. "All the DUCs in a Row: Natural Gas Production in U.S," The Energy Journal, , vol. 42(3), pages 113-132, May.
    6. Ogunlesi, Ayodeji, 2018. "Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis," MPRA Paper 90202, University Library of Munich, Germany.
    7. Kunofiwa Tsaurai, 2017. "Foreign Direct Investment-Growth Nexus in Emerging Markets: does Human Capital Development Matter?," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 13(6), pages 174-189, DECEMBER.

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