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UK commercial property forecasting: the devil is in the data

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  • Michael Ball
  • Sotiris Tsolacos

Abstract

The modelling of UK property markets using construction statistics faces considerable problems because of the way in which those statistics are drawn up. These difficulties are shown here to include data accuracy; the impact of large projects; the cost indices used to deflate current price data; missing information; the addition of unrecorded output and estimates that induce serial correlation. Such problems make the data relatively poor bases on which to formulate property market forecasts. Ex post forecasting analysis over two horizons showed that simple regression models, which include variables that affect development profitability, did not outperform ARIMA models, which are based solely on the construction statistics. The available floor-space data are also poor indicators of building supply. There seems to be a strong case for the government to improve the quality of the commercial supply data it provides.

Suggested Citation

  • Michael Ball & Sotiris Tsolacos, 2002. "UK commercial property forecasting: the devil is in the data," Journal of Property Research, Taylor & Francis Journals, vol. 19(1), pages 13-38.
    • Handle: RePEc:taf:jpropr:v:19:y:2002:i:1:p:13-38
    DOI: 10.1080/09599910110110699
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    Cited by:

    1. Allison M. Orr & Colin Jones, 2003. "The Analysis and Prediction of Urban Office Rents," Urban Studies, Urban Studies Journal Limited, vol. 40(11), pages 2255-2284, October.
    2. Patrick Mcallister & Graeme Newell & George Matysiak, 2008. "Agreement and Accuracy in Consensus Forecasts of the UK Commercial Property Market," Journal of Property Research, Taylor & Francis Journals, vol. 25(1), pages 1-22, June.
    3. Michael Ball, 2002. "Cultural Explanation of Regional Property Markets: A Critique," Urban Studies, Urban Studies Journal Limited, vol. 39(8), pages 1453-1469, July.
    4. Peter Öhman & Bo Söderberg & Ola Uhlin, 2011. "Accuracy of Swedish property appraisers’ forecasts of net operating income," Journal of Property Research, Taylor & Francis Journals, vol. 29(2), pages 103-122, November.
    5. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2012. "Examination of property forecasting models - accuracy and its improvement through combination forecasting," ERES eres2012_082, European Real Estate Society (ERES).

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