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Data Uncertainty in Real Estate Forecasting

Author

Listed:
  • Patrick McAllister

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

  • Paul Kennedy

    (INVESCO Real Estate)

Abstract

The rapid expansion of the TMT sector in the late 1990s and more recent growing regulatory and corporate focus on business continuity and security have raised the profile of data centres. Data centres offer a unique blend of occupational, physical and technological characteristics compared to conventional real estate assets. Limited trading and heterogeneity of data centres also causes higher levels of appraisal uncertainty. In practice, the application of conventional discounted cash flow approaches requires information about a wide range of inputs that is difficult to derive from limited market signals or estimate analytically. This paper outlines an approach that uses pricing signals from similar traded cash flows is proposed. Based upon 'the law of one price', the method draws upon the premise that two identical future cash flows must have the same value now. Given the difficulties of estimating exit values, an alternative is that the expected cash flows of data centre are analysed over the life cycle of the building, with corporate bond yields used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds. Although there are rarely assets that have identical cash flows and some approximation is necessary, the level of appraiser subjectivity is dramatically reduced.

Suggested Citation

  • Patrick McAllister & Paul Kennedy, 2007. "Data Uncertainty in Real Estate Forecasting," Real Estate & Planning Working Papers rep-wp2007-06, Henley Business School, University of Reading.
  • Handle: RePEc:rdg:repxwp:rep-wp2007-06
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    File URL: http://www.henley.reading.ac.uk/rep/fulltxt/0607.pdf
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    Cited by:

    1. 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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