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Panel Data Modelling of Prime Office Rents: A Study of 12 Major European Markets

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  • Fotis Mouzakis
  • David Richards

Abstract

A significant amount of real estate research has been directed towards developing empirical models explaining rental growth. This paper develops an error correction mechanism (ECM) model which is built on the general theoretical formulation of the Hendershott et a.l (2002a). Income, as measured by local market services output, is used as a key determinant of office demand. A total office stock variable is also used which is derived from the cumulated level of development completions. The model is estimated empirically for 12 office market locations across Europe using panel data techniques and the full sequence of panel model selection tests. The approach allows the behaviour of different markets to be readily compared and contrasted, and provides inferences about intra‐market dependence and the comparative speed of adjustment towards long‐run equilibrium. The study also compares the short‐term predictive performance of the proposed model to a number of alternatives which has been covered in the literature, including a‐theoretical models. The results offer some support for the proposed model for predicting short‐term rental movements.

Suggested Citation

  • Fotis Mouzakis & David Richards, 2007. "Panel Data Modelling of Prime Office Rents: A Study of 12 Major European Markets," Journal of Property Research, Taylor & Francis Journals, vol. 24(1), pages 31-53, February.
    • Handle: RePEc:taf:jpropr:v:24:y:2007:i:1:p:31-53
    DOI: 10.1080/09599910701297713
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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. Patric H. Hendershott & Bryan D. MacGregor & Raymond Y.C. Tse, 2002. "Estimation of the Rental Adjustment Process," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(2), pages 165-183.
    3. Grenadier Steven R., 1995. "Local and National Determinants of Office Vacancies," Journal of Urban Economics, Elsevier, vol. 37(1), pages 57-71, January.
    4. Inder, Brett, 1993. "Estimating long-run relationships in economics : A comparison of different approaches," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 53-68.
    5. Paul Levine & Fotis Mouzakis & Ron Smith, 1998. "Prices and quantities in the arms trade," Defence and Peace Economics, Taylor & Francis Journals, vol. 9(3), pages 223-236.
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    Cited by:

    1. Nowak Krzysztof, 2020. "Hidden Vacancy Rate as a Part of Office Market Dynamics in Selected Polish Cities," Real Estate Management and Valuation, Sciendo, vol. 28(1), pages 1-12, March.
    2. Dimitrios Papastamos & Fotis Mouzakis & Simon Stevenson, 2014. "Rationality and Momentum in Real Estate Investment Forecasts," Real Estate & Planning Working Papers rep-wp2014-07, Henley Business School, University of Reading.
    3. Patric Hendershott & Maarten Jennen & Bryan MacGregor, 2013. "Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail," The Journal of Real Estate Finance and Economics, Springer, vol. 47(4), pages 659-687, November.
    4. Catherine Bruneau & Souad Cherfouh, 2015. "Long-run equilibrium for the Greater Paris office market and short-run adjustments," Journal of Property Research, Taylor & Francis Journals, vol. 32(4), pages 301-323, December.
    5. John McCartney, 2012. "Short and long-run rent adjustment in the Dublin office market," Journal of Property Research, Taylor & Francis Journals, vol. 29(3), pages 201-226, April.

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