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The determinants of regional real estate returns in the United Kingdom: a vector error correction approach

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  • Daniel Kohlert

Abstract

This study provides a detailed analysis to regional office real estate markets in the United Kingdom. A vector error correction (VEC) approach is applied to a unique panel dataset that covers the time period from 1981 until 2004 and allows a disaggregation to the NUTS 2 level. Long‐run equilibrium relationships and short‐term corrections among total returns and the key macroeconomic variables gross domestic product (GDP), total investment and unemployment are captured. Different samples are used to control for the special role of the London market and to alleviate potential bias due to differences in the number of properties within regions. The results leave little ground for assuming that the economic variables have no impact on total office returns. They rather provide evidence that there are relatively strong long‐run relationships. The assumption is supported that the long‐run relationships are causal and running from the economic variables to total return. Furthermore, there is evidence for short‐term causal relationships between economic variables, in particular total investment, and total return, as well as for total returns adjusting to the long‐term disparities resulting from changes in the variables. Consequently, the economic variables do not only seem to provide short‐term information but also short‐term immediate effects on the movements of total returns. The character of the long‐term equilibrium and short‐term corrections, however, is not identical across samples while London indeed seems special.

Suggested Citation

  • Daniel Kohlert, 2010. "The determinants of regional real estate returns in the United Kingdom: a vector error correction approach," Journal of Property Research, Taylor & Francis Journals, vol. 27(1), pages 87-117, June.
  • Handle: RePEc:taf:jpropr:v:27:y:2010:i:1:p:87-117
    DOI: 10.1080/09599916.2010.500816
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    1. Karaman Örsal, Deniz Dilan & Droge, Bernd, 2014. "Panel cointegration testing in the presence of a time trend," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 377-390.
    2. Thrall, Grant Ian, 2002. "Business Geography and New Real Estate Market Analysis," OUP Catalogue, Oxford University Press, number 9780195076363, Decembrie.
    3. Peter Byrne & Stephen Lee, 2008. "Spatial Concentration in Institutional Industrial Real Estate Investment in the England and Wales," Real Estate & Planning Working Papers rep-wp2008-02, Henley Business School, University of Reading.
    4. William N. Goetzmann & Bradford Case & K. Geert Rouwenhorst, 1999. "Global Real Estate Markets: Cycles And Fundamentals," Yale School of Management Working Papers ysm116, Yale School of Management.
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    Cited by:

    1. Shizhen Wang & David Hartzell, 2021. "Real Estate Return in Hong Kong and its Determinants: A Dynamic Gordon Growth Model Analysis," International Real Estate Review, Global Social Science Institute, vol. 24(1), pages 113-138.
    2. Cohen Viktorija & Burinskas Arūnas, 2020. "The Evaluation of the Impact of Macroeconomic Indicators on the Performance of Listed Real Estate Companies and Reits," Ekonomika (Economics), Sciendo, vol. 99(1), pages 79-92, June.

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