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

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

Introduction Investigate 56 A-REIT M&A announcements 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)

Prior literature (All REIT-REIT) AuthorStudy period # sampleCARs (%)Event days Allen & Sirmans (1987) *[-1,0] Campbell et al., (1998) [-1,+1] Sahin (2005) *[-1,+1] Eichholtz & Kok (2008) [-1,+1] Keisers (2009) [-1,+1] Campbell et al., (2009) [-1,+1] * Denotes statistical significance

Prior literature (Pub v Private) AuthorStudy period # Sample TypeCARs (%)Event days Campbell et al., (2001) Pub-pub Pub-private -0.6* +1.9* [-1,+1] Campbell et al., (2005) Pub-private+1.52*[-1,+1] Keisers (2009) Pub-pub Pub-private -0.76* [-1,+1] Campbell et al., (2009) Pub-pub Pub-private -0.95* +1.1* [-1,+1] * Denotes statistical significance

Prior literature (method of payment) AuthorStudy period # Sample TypeCARs (%) Event days Campbell et al., (2001) Scrip (Pub-pub) Scrip (Pub-priv) -0.6* +2.2* [-1,+1] Campbell et al., (2005) (pub-priv) 49 4 Scrip/combo Cash [-1,+1] Eichholtz & Kok (2008) Scrip/combo Cash [-1,+1] Ratcliffe et al., (2009) (Aust data) Scrip/combo Cash +1.55* [-1,+1] Campbell et al., (2009) Scrip/combo Cash +0.81* [-1,+1] * Denotes statistical significance

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

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:

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.

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:

Data Successful A-REIT M&A’s bidders were identified from the Connect 4 Takeovers Database from Jan 1996 to Dec 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.

Announcement of 56 M&As by Year Year# announceYear# announce Total56

Descriptive stats All Obs (n = 56)MeanMedianMaxMinS.D. Mkt Value of Bidder ($M) Value of Acquisition ($M) Relative Size of Acquisition Public-Public (n = 44)MeanMedianMaxMinS.D. Mkt Value of Bidder ($M) Value of Acquisition ($M) Relative Size of Acquisition Public-Private (n = 12)MeanMedianMaxMinS.D. Mkt Value of Bidder ($M) Value of Acquisition ($M) Relative Size of Acquisition Means TestDiff in meansp-value Mkt Value of Bidder (0.030)** Value of Acquisition633.11(0.109) Relative Size of Acquisition-0.146(0.389)

Panel A: A-REIT Bidders Total sample (n = 56)Cash (n = 30)_____Combination (n = 26) IntervalCARpValueCARpValueCARpValue [-2,+2]0.880%(0.015)**0.321%(0.622)1.231%(0.016)** [-1,+1]0.966%(0.001)***0.174%(0.707)1.463%(0.001)*** Panel B: Public-Public Total sample (n = 44)Cash (n = 21)_____Combination (n = 23) IntervalCARpValueCARpValueCARpValue [-2,+2]0.326%(0.079)*-0.345%(0.840)0.714%(0.030)** [-1,+1]0.457%(0.017)**-0.286%(0.776)0.947%(0.002)*** Panel C: Public-Private Total sample (n = 12)Cash (n = 9)______Combination (n = 3) IntervalCARpValueCARpValueCARpValue [-2,+2]2.914%(0.060)*1.876%(0.228)5.196%(0.272) [-1,+1]2.834%(0.022)**1.246%(0.262)5.419%(0.349) Event study results ***, **, * statistical significance at 1%, 5% & 10% level

Results – regression model Panel APanel B No. of Obs Variable56(p-value)54^(p-value) Intercept0.100(0.049)**0.027(0.193) RELSIZE0.003(0.689)-0.006(0.232) LEV-0.181(0.050)**-0.079(0.125) MOP-0.022(0.179)-0.021(0.034)** PUBLIC-0.043(0.116)-0.005(0.435) BVMV-0.029(0.019)**-0.022(0.042)** HHPROP0.033(0.088)*0.028(0.033)** R2R Adjusted R White Test46.007(0.006)39.260(0.035) Jarque-Bera (0.000)3.358(0.187) Ramsey Reset25.402(0.123)22.166(0.020) Values corrected for hetroskedasticity. ^ Reported figures corrected for outliers. ***, **, * show statistical significance at the 1%, 5% and 10% level respectively.

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