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Strategic asset allocation and the demand for real estate: international evidence

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Abstract

This paper analyzes the portfolio demand for real estate in a strategic asset allocation framework. We quantify the welfare losses from not including real estate in the traditional equity and bond portfolio for a typical investor. Previous studies have examined short-run and long-run optimal portfolio allocations for real estate in a North American setting. We employ forty-two real estate indices encompassing both developed and emerging economies, regions, and sectors. Our results show that in the short run, real estate is a desirable asset class for aggressive and conservative investors in all countries. At longer time horizons, real estate provides little diversification benefits in any of the eighteen sample countries. Thus, our study confirms North American results that real estate provides short run, but rather small long-run portfolio diversification benefits.

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Notes

  1. This section summarizes the Campbell et al. (2003) methodology in which real estate is now an additional asset class. Similarly, Umar (2017) used this approach to examine the benefits of adding conventional equities to a portfolio of Islamic equities.

  2. For a detailed description and derivation, please refer to Campbell et al. (2003).

  3. We computed confidence intervals to gauge the statistical significance of the parameter estimates by employing a bootstrapping procedure proposed by Mammen (1993). All our results presented in Tables 2 and 3 are significant at the 5% level. Confidence intervals are not be presented in the tables.

  4. Estimates of the estimated VAR model and residual correlations are available from the authors upon request.

  5. Dividend yield is a commonly used predictor variable in extant literature.

  6. We performed robustness checks for different values of these parameters. Our results show a qualitatively similar pattern for different values.

  7. 2 is the lowest level of risk aversion while 10 is the highest level of risk aversion.

  8. The welfare losses reported in Table 2 are point estimates that are subject to estimation uncertainty. To analyze the statistical significance of these estimates, we computed confidence intervals for each point estimate using a wild bootstrapping technique. Since all estimates in Tables 2 and 3 for varying degrees of risk aversion across all the 18 countries are significantly different form zero at the 5% significance level, confidence intervals are not presented in Tables 2 or 3. We report these results in Appendix A, Table 6. Furthermore, we report the total, myopic and hedge demand for each asset in the spirit of Campbell et al. (2003) in Appendix, Table 7.

  9. As mentioned earlier, we report the confidence intervals of the welfare losses in Appendix, Table 8. Furthermore, we report the total, myopic and hedge demand for each asset in the spirit of Campbell et al. (2003) in Appendix, Table 9.

  10. We are thankful for insightful suggestion of an anonymous referee for this analysis.

  11. As mentioned earlier, we report the confidence intervals of the welfare losses in Appendix, Table 10. Furthermore, we report the total, myopic and hedge demand for each asset in the spirit of Campbell et al. (2003) in Appendix, Table 11.

  12. E-Views allows five different trend assumptions in the VAR model and provides both trace and maximum Eigen value statistics. The various alternatives led to similar conclusions in all cases. At least two, and usually three cointegrating relationships exist among asset classes across the 18 countries. Since all cointegration test statistics are significant, only the Granger causality relationships are presented in Table 5. In our analysis, we chose the optimal lag length for both cointegration and Granger causality based on the Schwartz Information Criteria (SIC).

  13. However, for the US where there are three structural breaks and significant causality results that vary by subperiod, only an average across all four subperiods from 1997 to 2017 is presented to save space.

  14. Optimal lag lengths are presented in Table 5. Overall conclusions are not dependent upon lag length chosen, but the strength of Granger causality relationships can change considerably between different lag lengths.

  15. Although not the focus of this paper, international diversification across stock markets may prove more beneficial than international real estate diversification. To illustrate, US stock returns are not significantly cointegrated with stock return series in 8 of the other 17 countries: Germany, Japan, Philippines, Singapore, South Africa, Thailand, Belgium, and France. Similarly, for Chinese investors, diversification benefits might be possible because Chinese stock returns are not significantly cointegrated with returns in France, Germany, Italy, Spain, Sweden, UK, Philippines, Singapore, and Thailand.

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Funding

The authors received no external funding from any source for this study.

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Authors and Affiliations

  1. College of Business, Zayed University, PO Box 114534, Abu Dhabi, United Arab Emirates

    Zaghum Umar & Dennis Olson

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  1. Zaghum Umar
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  2. Dennis Olson
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Correspondence to Dennis Olson.

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Zaghum Umar declares that he has no conflict of interest regarding this paper, and Dennis Olson declares that he has no conflict of interest in regard to this paper.

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Appendix

Appendix

See Tables 6, 7, 8, 9 and 10, 11.

Table 6 Welfare losses for an investor in real estate, equities, and the benchmark asset
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Table 7 Asset demand for an investor with asset menu of real estate, equities, and the benchmark asset
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Table 8 Welfare losses for an investor in real estate, equities, government bonds, and the benchmark asset
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Table 9 Asset demand for an investor with asset menu of real estate, equities, government bonds, and the benchmark asset
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Table 10 Welfare losses for a US investor’s investment in global and local real estate indices, benchmark asset, equities, and government bonds
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Table 11 Asset demand for a US investor’s investment in global and local real estate indices, benchmark asset, equities, and government bonds
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Umar, Z., Olson, D. Strategic asset allocation and the demand for real estate: international evidence. Empir Econ 62, 2461–2513 (2022). https://doi.org/10.1007/s00181-021-02090-8

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