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An Evaluation Of The Performance Of UK Real Estate Forecasters

Author

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  • Pat McAllister

    (Department of Real Estate & Planning, University of Reading)

  • Graeme Newell
  • George Matysiak

    (Department of Real Estate & Planning, University of Reading)

Abstract

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. It compares the performance of real estate forecasters with non-real estate forecasters. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters and a similar survey of macro-economic and capital market forecasters, these forecasts are compared with actual performance to assess a number of forecasting issues in the UK over 1999-2004, including forecast error, bias and consensus. The results suggest that both groups are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that forecasters display the characteristics associated with a consensus indicating herding.

Suggested Citation

  • Pat McAllister & Graeme Newell & George Matysiak, 2005. "An Evaluation Of The Performance Of UK Real Estate Forecasters," Real Estate & Planning Working Papers rep-wp2005-23, Henley Business School, University of Reading.
  • Handle: RePEc:rdg:repxwp:rep-wp2005-23
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    File URL: http://www.henley.reading.ac.uk/rep/fulltxt/2305.pdf
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    References listed on IDEAS

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    1. Russell Chaplin, 1999. "The predictability of real office rents," Journal of Property Research, Taylor & Francis Journals, vol. 16(1), pages 21-49, January.
    2. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
    3. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    4. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    5. Jim Clayton & David Geltner & Stanley W. Hamilton, 2001. "Smoothing in Commercial Property Valuations: Evidence from Individual Appraisals," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 29(3), pages 337-360, March.
    6. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    7. John Capstaff & Krishna Paudyal & William Rees, 1999. "The relative forecast accuracy of UK brokers," Accounting and Business Research, Taylor & Francis Journals, vol. 30(1), pages 3-16.
    8. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 293-318.
    9. Dean Croushore, 1997. "The Livingston Survey: still useful after all these years," Business Review, Federal Reserve Bank of Philadelphia, issue Mar, pages 15-27.
    10. Schnader, M. H. & Stekler, H. O., 1991. "Do consensus forecasts exist?," International Journal of Forecasting, Elsevier, vol. 7(2), pages 165-170, August.
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    Cited by:

    1. Dirk Brounen & Piet Eichholtz & David Ling, 2007. "Trading Intensity and Real Estate Performance," The Journal of Real Estate Finance and Economics, Springer, vol. 35(4), pages 449-474, November.

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