1. Are Real Estate Banks More Affected by Real Estate Market Dynamics? Evidence from the Main European Countries Lucia Gibilaro, University of Bergamo lucia.gibilaro@unibg.it Gianluca Mattarocci, University of Rome “Tor Vergata” gianluca.mattarocci@uniroma2.it gianluca.mattarocci@uniroma2.it Vienna – July 3 rd -6 th, 2013

2. Introduction Literature review Empirical analysis: Sample Methodology Results Conclusions Index

3. Introduction  The effect on the credit market could be driven by the increase of the collateral value of lending exposure and decrease the bank riskiness if the demand of the real estate financing does not change (Kiyotaki and Moore, 1997) while cause an increase of the probability of default of the bank if debtors increases their exposure due the lower cost of lending and the easier access to financing opportunities (Koetter and Poghosyan, 2010).  Studies on the main market players in the banking sector demonstrate that real estate banks could be more riskier respect to other banks (Blasko and Sinkey, 2006) even if results could change with the proxy used for evaluation the bank risk change (Giannotti, Gibilaro and Mattarocci, 2011) and the criterion for identifying the real estate banks (Eisenbeis et al. 1996).

4. Introduction Research questions: -What is the role of real estate market trends in explaining the higher or lower riskiness and profitability of banks? -Are real estate banks over-exposed to the real estate market trend?

5. Introduction Literature review Empirical analysis: Sample Methodology Results Conclusions Index

6. Literature review (1/2) Empirical evidences demonstrate that the market price of bank shares discount also the risk related to the real estate market trend and the sensitivity to the market could be different on the basis of some bank features (i.a. size) (i.a. Allen et al., 1995) Empirical evidences demonstrate that the real estate price dynamics affects the amount of lending offered by the banks even if the relationship could be more or less significant on the basis of the market analysed and the time horizon considered (i.a. Inoguchi, 2011). The characteristics of the bank could explain an higher or lower sensitivity to the real estate market dynamics and normally the effect is higher the worse are the bank fundamentals (i.a. Peek and Rosengren, 1994)

7. Literature review (2/2) Preliminary evidence proposed in literature demonstrates that real estate banks could be riskier respect to other banks (Blasko and Sinkey, 2006) but results are not always confirmed when the time horizon considered and the proxy selected for evaluation the bank risk change (Giannotti, Gibilaro and Mattarocci, 2011) or when we adopt a different criterion for identifying the real estate banks (Eisenbeis et al. 1996). Only few analyses proposed in literature consider the role of the real estate market trend in determining the risk and revenues of the banks (Igan and Pinheiro, 2010) and there are no studies that allow evaluating if a specialized real estate bank is more or less affected by the market trend with respect to all other banks.

8. Introduction Literature review Empirical analysis: Sample Methodology Results Conclusions Index

9. Empirical analysis: Sample Database: Bankscope Time horizon: 2007-2011 Frequency of data: yearly Real Estate Banks 20072008200920102011 Number 43161163162166 Total assets 3,239,729.83,977,323.43,238,684.73,476,400.44,467,402.4 Average Total Assets 75,342.5524,703.8719,869.2321,459.2627,075.17 Not Real Estate Banks 20072008200920102011 Number 940823822826822 Total assets 56,404,34270,861,97081,591,76196,917,431120,437,628 Average Total Assets 59,372.9985,170.6498,303.33116,207.95144,930.96 Following the approach proposed by Eisenbes and Kwast (1991), we classify in the year t a bank as a real estate bank if the role of real estate lending % Real Estateit is higher than 40%. Summary statistics on the two subsamples (REBs and not REBs) for each year are provided in table 1.

10. Empirical analysis: Methodology (1/2) Following the approach proposed by Blasko and Sinkey (2006), we compute a measure of the default risk for each bank in the sample using the following formula: The leverage measure is the ratio between the equity liabilities and total assets at time t for the bank i The TIER 1 capital requirement at time t for the bank i defined on the basis of the amount and quality of outstanding debt Return on Assets at time t for the bank i Return on Equity at time t for the bank i Net Interest Income with the respect to the overall income at time t for the bank i Loan loss provisions with respect to the overall loans at time t for the bank i Total of past due credits over 90 day with respect to the overall loans at time t for the bank i Amount of derivative exposure with respect to total assets at time t for the bank i Difference between rate-sensitive assets and rate sensitive liabilities with respect to total asset at time t for the bank i Left hand side variable Panel regression model

11. Empirical analysis: Methodology (2/2) (3) (4) (5) (6)

12. Empirical analysis: Results (1/3) REBsNot REBSKolmogorov Smirnov test MeanMedianDev.St.MeanMedianDev.St.ValueTest 15.053.5234.846.533.1020.480.170.00 0.07 0.060.120.100.130.440.00 0.110.100.090.160.140.120.290.00 0.01 0.050.320.00 0.03 0.210.05 0.220.170.00 0.020.010.050.020.030.090.140.00 0.020.010.050.030.020.040.320.00 0.040.00 0.01 1.00 0.010.000.03 0.000.770.280.00 -0.10-0.060.18-0.020.001.990.490.00

13. Empirical analysis: Results (2/3) (3)(4)(5)(6) 8.217.557.476.73 -2.76-2.68-2.71-2.62 56.09*57.18*50.0951.38 2.742.641.931.82 240.57***240.84***217.18***217.47*** -18.94*-19.37*-16.97-17.40 -47.01-49.32-38.82-41.45 -0.12-0.11 -0.10 0.00 -0.01 3.27*-3.26*- -2.01-1.76 --30.46***30.31*** -3.38-3.40-3.18 Country Dummies Yes Observations 2982 Groups 672 R^2 0.100.090.10

14. Empirical analysis: Results (3/3) (5)(6) (7)(8) 7.476.737.276.5 -2.71-2.62-2.71-2.61 50.0951.3852.954.69 1.931.821.701.55 217.18**217.47**218.07**218.29** -16.97-17.40-16.82-17.19* -38.82-41.45-39.29-42.06 -0.11-0.10 -0.09 0.00-0.010.00 3.26--- -1.76-- 30.46**30.31**-- --38.35* --28.83** 39.47* 28.44** -3.18 -3.15-3.12 Country Dummies Yes Observations 2982 R^2 0.10

15. Introduction Literature review Empirical analysis: Sample Methodology Results Conclusions Index

16. The role of the market trend is not independent with the respect of the specialization of the bank in the real estate sector and, due the higher expertise in the sector, normally Real estate banks are those that are less affected by any positive or negative market dynamics. Looking at the literature on the diversification of the lending portfolio of a bank, evidences provided support the hypothesis hypnotized in literature that the reduction of the bank risk is not always related only to the degree of diversification (i.a. Demsetz and Strahan, 1997) and REBs can reduce their risk exposure using their specific knowledge in the real estate lending. Conclusions

17. Contact Information Lucia Gibilaro University of Bergamo e-mail: lucia.gibilaro@unibg.itlucia.gibilaro@unibg.it Gianluca Mattarocci University of Rome Tor Vergata e-mail: gianluca.mattarocci@uniroma2.itgianluca.mattarocci@uniroma2.it Thanks for you attention