1. THE INTEREST RATE SPREAD AND REAL ESTATE RETURNS ---- EVIDENCE FROM HONG KONG Yishuang Xu* Department of Real Estate and Construction The University of Hong Kong June 2010

2. MOTIVATIONS The role of interest rate spread Expected inflation? Proxy of interest rate? Anonymous macro-economic factor?

3. THEORETICAL BACKGROUND Expectation Theory ---- the term structure of interest rate Expected Rental Income Growth Model

4. DERIVATION OF THE MODEL Based on Gordon Growth Model, we further assume that the required rate of return ( i ) would change with constant growth ( G ) as well, then we get the variant of GGM : Here, P = price of asset, R = income of asset, g=expected income growth, i=required rate of return, G = the growth of required rate of return (1)

5. HOW TO FIND OUT “G” Required rate of return ( I ) = cost of capital = risk-free return rate =yield of government bond growth of igrowth of bond yield is equal to spread of bond yield (S) = longest-period bond yield (i t ) – shortest-period bond yield (i 0 ) (2) ≈

6. THE MODEL OF EXPECTED EARNINGS GROWTH Combining equation (1) and (2), we can get the model for capturing the expected income growth of certain asset as followed: Where P, R 0 and g refer to the price, income and expected income growth of the asset while I and S t represent the 1-year T-bill yield and the spread between t- year and 1-year T-bill yield.

7. SIMULATIONS OF THE MODEL Real estate return v.s. interest rate spread Simulation1 st 2 nd 3 rd 4 th 5 th 6 th Correlation-0.4614-0.5074-0.4191-0.5292-0.4470-0.4739

8. SIMULATIONS OF THE MODEL Real estate return v.s. interest rate Simulation1 st 2 nd 3 rd 4 th 5 th 6 th Correlation-0.5205-0.3650-0.4321-0.5603-0.5650-0.4887

9. SIMULATIONS OF THE MODEL Real estate return v.s. derived expected earnings growth Simulation1 st 2 nd 3 rd 4 th 5 th 6 th Correlation0.9999

10. SIMULATIONS OF THE MODEL Real estate return v.s. rental changes Simulation1 st 2 nd 3 rd 4 th 5 th 6 th Correlation0.9987 0.99950.99850.99870.9989

11. EMPIRICAL RESEARCH DESIGN 1. To estimate the changes of rental index 2. To test the relationship between real estate return and other independent variables

12. ESTIMATION OF RENT CHANGES Estimates of rent dynamics beta Property sector ConstantGDPd(GDP)d(UNE)d(INT-INF) Office-0.0328420.000000101 ** -0.0000000752-2.616805 *** -0.112462 Residential-0.0068560.0000000166-0.0000000704-2.287231 *** 0.933575 Retail-0.0029930.0000000091 6 0.0000000674-0.973431 *** -0.096567 Industrial-0.014130.000000038-0.000000017-1.365563 *** -0.422221 *, **, *** are 10, 5, and 1% significance levels, heteroscedastic-consistent (robust-White) standard errors are in parentheses. With the estimated beta values, we further estimate the rent changes ( ∆ lnR 0t ) without error. Thus the multi-co-linearity between rent and price movements can be eliminated and the newly estimated rent changes series are used in the empirical test for the relationship between property return and macroeconomic factors.

13. EMPIRICAL MODEL H 0 : the property price changes are significantly related to the interest rate spread; H 1 : the property price changes cannot be found related to the interest rates spread. HYPOTHESES:

14. DESCRIPTIONS OF VARIABLES Descriptions of the Variables in the Empirical Model CategoriesUnit of measureDescriptions Dependent Variable PtPt indexPrice index Independent Variables R 0t indexRental index gtgt percentagethe derived expected earnings growth of the property ItIt percentagethe yield rate of one-year exchange fund notes StSt percentagethe yield spread between one- year and ten-year exchange fund notes INF t percentagethe percentage change of the CPI composite GDP t million HKDlevel data of GDP

15. EMPIRICAL RESULTS AND INTERPRETATIONS sector expected earnings growth Interest Rate Interest Rate Spread Spot Rental office34.15 *** -25.43 *** -65.40 *** 0.90 *** residential39.76 *** -40.08 *** -87.23 *** 0.70 *** retail30.76 *** -35.43 *** -64.14 *** 0.88 ** industrial28.60 ** -18.03 ** -24.60 ** 0.73 * Notes: *, **, *** is significance at 10%,5% and 1% level respectively.

16. CONCLUSIONS AND IMPLICATIONS to find out the fundamental macroeconomic drivers that systematically influence the real estate returns based on a theoretical model to address the investors’ expectations, both on future inflation and asset earning changes, into the pricing of real estate the results have important implications for dynamic asset allocation and pricing strategies that involve the predictability of real estate returns based on macroeconomic data

17. THANK YOU