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Forecasting UK commercial real estate cycle phases with leading indicators: a probit approach

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  • Alexandra Krystalogianni
  • George Matysiak
  • Sotiris Tsolacos
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    Abstract

    This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. Probit models are then estimated using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.

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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Economics.

    Volume (Year): 36 (2004)
    Issue (Month): 20 ()
    Pages: 2347-2356

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    Handle: RePEc:taf:applec:v:36:y:2004:i:20:p:2347-2356

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    1. King, R.G. & Plosser, C.I., 1989. "Real Business Cycles And The Test Of The Adelmans," RCER Working Papers 204, University of Rochester - Center for Economic Research (RCER).
    2. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    3. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    4. Arturo Estrella & Frederic S. Mishkin, 1995. "Predicting U.S. Recessions: Financial Variables as Leading Indicators," NBER Working Papers 5379, National Bureau of Economic Research, Inc.
    5. Lawrence J. Cristiano & Terry J. Fitzgerald, 1998. "The business cycle: it's still a puzzle," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q IV, pages 56-83.
    6. Bryan Boulier & H. O. Stekler, 2001. "The term spread as a cyclical indicator: a forecasting evaluation," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 403-409.
    7. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    8. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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    Cited by:
    1. Franz Fuerst, 2008. "Office Rent Determinants: a Hedonic Panel Analysis," Real Estate & Planning Working Papers rep-wp2008-12, Henley Business School, Reading University.
    2. Hyejung Moon & Jungick Lee, 2013. "Forecast evaluation of economic sentiment indicator for the Korean economy," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 180-190 Bank for International Settlements.

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