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Dynamic Interactions Between Private and Public Real Estate Markets: Some International Evidence

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Abstract

This study evaluates long-run relationships and short-run linkages between the private (unsecuritized) and the public (securitized) real estate markets of Australia, Netherlands, United Kingdom and the United States. Results indicate the existence of long-run relationships between the public and private real estate markets of each of the countries under consideration. This implies that for all countries, investors would not have realized long-term portfolio diversification benefits from allocating funds in both the private and public real estate markets since these assets are substitutable over the long run. Short-run analyses also reveal significant causal relationships between private and public markets of all countries under consideration. As expected, it was found that price discovery occurred in the public real estate market in that it leads but is not led by its private real estate market counterpart.

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Notes

  1. These markets were examined because they have both well-developed private and public real estate markets.

  2. It would be optimal to analyze the interrelationships between the private and public markets of several additional countries across the globe. However, data limitation of the private sector in particular limits our scope.

  3. For additional information on the NCREIF indices, please see the User’s Guide to NPI. http://www.ncreif.com/public_files/Users_Guide_to_NPI.pdf

  4. For additional information on the IPD indices, please see the IPD Index Guide. http://www.ipd.com/OurProducts/Indices/IPDIndexGuide/DownloadIPDIndexGuide/tabid/1737/Default.aspx

  5. For additional information on the FTSE EPRA/NAREIT indices, please see Ground Rules for the Management of the FTSE EPRA/NAREIT Global Real Estate Index Series. http://www.epra.com/media/FTSE_EPRA-NAREIT_Global_Real_Estate_Index_Ground_Rules_v4_2.pdf

  6. We acknowledge that there are inherent differences between the private and public real estate indices namely in terms of leverage and appraisal smoothing. However, following Tuluca et al. (2000) we have not degeared the REIT indices nor removed the effects of smoothing from the appraisal based indices since cointegration and subsequent causality test results should remain consistent regardless of these adjustments.

  7. For the KPSS test, the lag truncation parameter is set to 8 as it allows for an acceptable compromise between low power and size distortions [see for example Schlitzer (1995)].

  8. Let T=the number of usable observations, c=number of parameters estimated in each equation of the unrestricted system and let \( \sum u \) and \( \sum r \) be the variance/covariance matrices of the unrestricted and the restricted model respectively. Then the test statistic: \( \left( {T - c} \right)\left( {\log |\sum {r| - \log |\sum {u|} } } \right) \) can be compared to a χ 2 distribution with degrees of freedom equal to the number of restrictions in a system.

  9. It is important to note that in a system comprised of n variables, there can be at most n-1 , cointegrating vectors/relationships.

  10. Detailed descriptions of each of the model can be found in Johansen (1994).

  11. The calculations are available upon request but are not reported for brevity.

  12. The results of the λ Max tests are similar but are not reported for brevity purposes.

  13. To ensure that the frequency is indeed and undoubtedly playing a minor role, the analysis for the US and UK are conducted using quarterly frequency data. The results mirror those using annual frequency data. These results are not included for brevity purposes but are available upon request.

  14. As discussed earlier, the optimum lag length is computed by means of the likelihood ratio tests and then ensuring that the residuals are free from serial correlation as measured by the L-B-Q statistics.

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Authors and Affiliations

  1. Department of Finance and Economics,, Merrick School of Business, The University of Baltimore, 1420 N. Charles St, Baltimore, MD, 21201, USA

    Nafeesa Yunus

  2. Department of Finance and Business Law, Gazarian Real Estate, Center, Craig School of Business, California State University, Fresno, 5245 North Backer Avenue, PB7, Fresno, CA, 93740, USA

    J. Andrew Hansz

  3. Real Estate Investment Strategy,, Abu Dhabi Investment Authority, 211, Corniche, PO Box 3600, Abu Dhabi, United Arab Emirates

    Paul J. Kennedy

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  1. Nafeesa Yunus
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  2. J. Andrew Hansz
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Correspondence to Nafeesa Yunus.

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Yunus, N., Hansz, J.A. & Kennedy, P.J. Dynamic Interactions Between Private and Public Real Estate Markets: Some International Evidence. J Real Estate Finan Econ 45, 1021–1040 (2012). https://doi.org/10.1007/s11146-010-9297-5

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