A-REIT BIDDER RETURNS: An Evaluation of Public and Private Targets and Method of Payment

1. A-REIT BIDDER RETURNS: An Evaluation of Public and Private Targets and Method of Payment Chris Ratcliffe Bill Dimovski

2. Introduction • M&As one of few avenues to growth for A-REITs • Australia is one of the highest securitized property markets in the world • GFC saw market cap fall from A$135b in 2007 to A$46b Feb 2009, as at March 2011 A$79b • Chandler (2011) suggest increase M&A activity in future as market conditions improve

3. Introduction • Investigate 56 A-REIT M&A announcements 1996-2010 • Prior US REIT studies shown mixed results for bidders of public targets • +5.78% (Allen & Sirmans, 1987) • -1.21% (Sahin, 2005) • Private target → bidders earn CARs +1.52% (Campbell et al. 2005)

4. Prior literature (All REIT-REIT) * Denotes statistical significance

5. Prior literature (Pub v Private) * Denotes statistical significance

6. Prior literature (method of payment) * Denotes statistical significance

7. Event Study Method • We employed event study methodology as described by Brown and Warner (1985) • The market model was estimated for each company over a 120 day estimation period, OLS regression employed to determine the parameter estimations. • The following market model is employed: • To avoid the bias associated with the estimation of parameters using daily returns with infrequent trading we employ the Scholes and Williams (1977) adjusted beta method

8. Event Study Method • The abnormal return (AR) of the common stock in the event window [-20,+20] is calculated as: • The cumulative abnormal returns (CAR) for any interval during the event window:

9. Regression Method • Regression model was developed to examine the CARs [-1,+1] calculated above for acquirers. • Independent variables were selected on the basis of prior literature along with variables unique to the A-REIT structure.

10. Regression Method • RELSIZE – ln(price paid/bidder market capitalisation) • LEV – bidder financial leverage (financial debt/financial debt + equity) • MOP – method of payment, dummy variable 1 if cash used, otherwise 0 • PUBLIC – Type of target, dummy variable of 1 if the target is publicly listed, 0 otherwise • BVMV – Book-to-market ratio calculated as book value equity/market value equity • HHPROP – measure of focus/specialisation by property type, calculated as:

11. Data • Successful A-REIT M&A’s bidders were identified from the Connect 4 Takeovers Database from Jan 1996 to Dec 2010. • Daily share price data was obtained from Bloomberg. • Accounting data (leverage, specialisation) was collected from the Connect 4 Annual Reports collection and ASX. • A total of 56 transactions were identified.

12. Announcement of 56 M&As by Year

13. Descriptive stats

14. Event study results ***, **, * statistical significance at 1%, 5% & 10% level

15. Results – regression model Values corrected for hetroskedasticity. ^ Reported figures corrected for outliers. ***, **, * show statistical significance at the 1%, 5% and 10% level respectively.

16. Conclusion • Acquiring A-REITs enjoy positive & significant CARs • Choice of payment is important • Bidding A-REITs earn higher CARs when target is private • BVMV suggests investors penalise high BVMV A-REITs in a M&A due to their higher risk characteristics. • Specialisation has a positive impact on CARs