1. Bank Accounting Conservatism, Lending Behaviour and Credit Crisis

2. Motivation & Literature Bank conservatism is driven by regulatory capital demand (Moyer,1990; Beatty and Liao, 2009). Effects on debt contracting is an area less studied. Bank accounting literature: Loan loss provisioning (Kanagaretnam et. al., 2004) Fair value accounting (Laux and Leuz, 2009) Credit crisis literature: Pro-cyclicality of fair value accounting (Plaintin et. al., 2008; Adrian and Shin, 2009) & incurred loan loss accounting model Research questions: 1.How does bank accounting conservatism affect debt pricing? 2. Does the effect in (1) change with the credit crisis?

3. Motivation & Literature Contributions of study: Extend conservatism literature from borrower to bank debt pricing behavior. Extend bank accounting literature in the area of loan loss effects on debt pricing. Extend credit crisis literature by showing the counter-cyclical effects of bank and borrower conservatism.

4. Motivation & Literature Contributions of study: Debt market is huge (US$8.5 trillion for 10 largest US banks alone on 2008 (McCarthy et. al., 2009)) and has multiplier effects on real economy during credit crisis. Accounting policy of banks has significant economic consequences. Practical implication for bank accounting policy. Level of accounting conservatism of bank management and accountants that drives level of loan provisions. Professional accounting judgment matters more than the accounting standard because of wide discretion in loan provisioning. Incurred loan provisioning method is not necessarily pro-cyclical.

5. Motivation & Literature Banks demand accounting conservatism in borrower (Beatty et. al., 2008) Information asymmetry between banks and borrowers (Moerman, 2008; Khan and Watts, 2009) Banks pass on benefit to borrowers in lower interest rates (Zhang, 2008) Research questions: Do conservative banks prefer conservative borrowers and do banks prefer conservative borrowers more during credit crisis? During credit crisis, do banks reduce further the spreads charged to the more conservative borrowers, relative to the less conservative borrowers?

6. Motivation & Literature Contributions of study: Direct verification that borrower conservatism is driven by banker demand by studying the bank preference for conservative borrowers, especially during credit crisis in a common debt contract sample (in view of debate). An exogenous event in credit crisis should increase information asymmetry. Expect the benefit in lower interest rates to increase during credit crisis. Add understanding of the credit crisis effects on borrower conservatism

7. Hypotheses H1a: The spreads charged by the conservative banks are more sensitive to loan losses (charge more spreads) on an overall basis. H1b: The spreads charged by the conservative banks are less sensitive to loan losses (charge less spreads) during credit crisis and more sensitive to loan losses pre-crisis. H2: More conservative banks have a greater preference for conservative borrowers. Both conservative and non-conservative banks prefer conservative borrowers more during credit crisis, with the conservative banks showing a smaller increase in preference. H3: During credit crisis, differential spreads between the more conservative and less conservative borrowers increases.

8. Methodology Accounting conservatism in timely loss recognition measured using C scores in Khan and Watts (2009) equation: X i = β 1 + β 2 Di + R i (μ 1 + μ 2 Size i + μ 3 M/B i + μ 4 Lev i ) + D i R i (λ 1 + λ 2 Sizei + λ 3 M/B i + λ 4 Lev i ) + (δ 1 Size i + δ 2 M/B i + δ 3 Lev i ) + D i (δ 4 Size i + δ 5 M/B i + δ 6 Lev i ) + ε i Where Size i is total assets, M/B i is market to book ratio and Lev i is total liabilities divided by total assets (leverage). C score is λ 1 + λ 2 Size i + λ 3 M/B i + λ 4 Lev i. Higher C scores indicate higher levels of accounting conservatism. C scores are used to rank and split the banks and borrowers into more conservative and less conservative groups and assign an indicator 1 and 0 for each group.

9. Methodology Credit risk environment: bank sector credit default swap (CDS) rates. Equation for hypothesis 1a: Spread = α 0 + α 1 rating + α 2 tenor + α 3 deal + α 4 cds + α 5 LL + α 6 cl + α 7 clLL + α 8 clrating Where “cl” indicator is 1 (0) for more (less) conservative banks, “clLL” is the interaction between “cl” and the loan loss scaled by shareholders’ equity and “clrating” is the interaction between “cl” and the borrower credit ratings. Negative α 7 : More conservative banks charge higher spreads in response to loan losses.

10. Methodology Equation for hypothesis 1b: Spread = α 0 + α 1 rating + α 2 tenor + α 3 deal + α 4 cds + α 5 LL + α 6 cl + α 7 clLL + α 8 clrating +α 9 cdsLL + α 10 cdsrating + α 11 clcdsLL + α 12 clcdsrating Positive α 11 : when bank CDS rates are higher during credit crisis, the more conservative banks are less sensitive to loan losses. Negative α 7 : pre-crisis period, the more conservative banks are more sensitive to loan losses.

11. Methodology Equation for hypothesis 2: Cb = α 0 + α 1 rating + α 2 tenor + α 3 deal + α 4 cds + α 5 Cl + α 6 cdsrating + α 7 CdsCl + α 8 cdstenor + α 9 cdsdeal Positiveα 5 : more conservative banks prefer conservative borrowers. Positive α 4 : when bank CDS are higher, banks increase their preference for borrower conservatism Negativeα 7 : when bank CDS rates are higher during credit crisis, more conservative banks show a smaller increase in preference for conservative borrowers, relative to the less conservative banks.

12. Methodology Equation for hypothesis 3: Spread = α 0 + α 1 rating + α 2 tenor + α 3 deal + α 4 cds + α 5 LL + α 6 cb + α 7 cbcds Where “cbcds” is the interaction between “cb” and bank CDS rates. Negative α 7 : when bank CDS rates are higher during credit crisis, banks charge the more conservative borrowers even lower spreads.

13. Data Source of deal and borrower data in main equations (spreads, borrower credit rating, deal amount, loan tenor) : Dealscan Loan Connector database Time period of deals: 2006 to 2009, straddles between pre-crisis and crisis periods Source of data to compute C scores (leverage, market to book, size, returns, earnings) and bank sector CDS : Datastream & annual reports Source of loan loss and shareholders’ equity: annual reports International bank sample (US/UK/Europe/Canada/Australia)

14. Empirical Results (1) Hypotheses 1a and 1b (***, ** are 1% & 5 % significance levels) Spread (dependent)H1aH1b Rating21.5697 (13.15)***21.0093 (12.72)*** Tenor-2.1483 (-2.43)**-1.7860 (-2.04)** Deal-3.8609 (-1.59)-4.7779 (-2.01)** CDS0.3950 (23.34)***0.4770 (10.65)*** LL-228.9221 (-7.97)***-530.758 (-7.82) *** Cl14.5870 (0.20)18.7027 (0.26) ClLL-430.6416 (-8.18)***-838.7354 (-8.19)*** Clrating-0.1165 (-0.15)-0.8194 (-0.95) cdsLL1.6912 (5.09)*** Cdsrating-0.0018 (-0.42) ClcdsLL2.0182 (4.60)*** Clcdsrating0.0122 (3.86)*** Intercept159.8346 (2.09)147.1086 (1.96) R-squared0.44460.4585 F37.8639.17 N3524

15. Empirical Results(2) Hypothesis 2 Dependent variable: “Cb”. ***, ** and * indicate coefficients significant at 1%, 5% and 10% respectively. Marginal effects of logit test results. H2 Rating0.0069 (1.71)* Tenor-0.0022 (-0.32) Deal0.0612 (5.09)*** Cl0.0599 (2.26)** Cds0.0074 (7.64)*** Cdsrating-0.0002 (-4.42)*** CdsCl-0.0005 (-2.16)** Cdstenor0.0004 (6.60)*** Cdsdeal-0.0010 (-9.31)*** Pseudo R20.0433 LR211.59 N3524

16. Empirical Results(3) Hypothesis 3 Dependent variable: spread (in basis points). ***, ** and * indicate coefficients significant at 1%, 5% and 10% respectively. T values after controls for bank, borrower, borrower country, borrower industry and tranche purpose fixed effects. H3 Rating20.8378 (13.50)*** Tenor-2.0729 (-2.34)** Deal-5.3128 (-2.19)** CDS0.5010 (21.68)*** LL-302.6176 (-11.56)*** Cb-11.0050 (-2.76)*** Cbcds-0.0108 (-3.84)*** Intercept217.7454 (2.36) R-squared0.4399 F37.86 N3524

17. References (1) Adrian, T., Shin, H.S., 2009. Liquidity and Leverage. Journal of Financial Intermediation, 1-20. Beatty, A., Weber, J., Yu, J.J., 2008. Conservatism and Debt. Journal of Accounting and Economics 45, 154-174. Beatty, A., Liao, S., 2009. Regulatory Capital Ratios, Loan Loss Provisioning and Pro-cyclicality. Working Paper. Kanagaretnam, K., Lobo, G.J., Yang, D., 2004. Joint Tests of Signalling and Income Smoothing through Bank Loan Loss Provisions. Contemporary Accounting Research 21, 843-884. Khan, M., Watts, R.L., 2009. Estimation and Empirical Properties of a Firm-Year Measure of Accounting Conservatism. Massachusetts Institute of Technology Working Paper. Laux, C., Leuz, C., 2009. The crisis of fair-value accounting: Making sense of the recent debate. Accounting, Organizations and Society 34, 826- 834.

18. References (2) McCarthy, M.G., Schneider, D.K., Tibbs, S.L., 2009. Investments and Loans Reported by the 10 Largest US Banks. Bank Accounting & Finance. Moerman, R., 2008. The role of information asymmetry and financial reporting quality in debt trading: Evidence from the secondary loan market. Journal of Accounting and Economics 46, 240-260. Moyer, S.E., 1990. Capital Adequacy Ratio Regulations And Accounting Choices In Commercial Banks. Journal of Accounting and Economics 13, 123-154. Plaintin, G., Sapra, H., Shin, H.S., 2008. Fair Value Accounting and Financial Stability. Chicago Graduate School of Business Research Paper No. 08–15. Zhang, J., 2008. The contracting benefits of accounting conservatism to lenders and borrowers. Journal of Accounting and Economics 45, 27–54.