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Banks’ Risk and Monetary Policy: Altunbas, Gambacorta and Marques

Banks’ Risk and Monetary Policy: Altunbas, Gambacorta and Marques. Discussion by Alistair Milne, Cass Business School, 22 nd May 2008. What paper does…. Panel data estimates: effect of monetary policy ( Δ i t ) on loan growth ( Δ ln (L) t ) Euro-zone data (Bankscope), 1999-2005,

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Banks’ Risk and Monetary Policy: Altunbas, Gambacorta and Marques

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  1. Banks’ Risk and Monetary Policy: Altunbas, Gambacorta and Marques Discussion by Alistair Milne, Cass Business School, 22nd May 2008

  2. What paper does… • Panel data estimates: effect of monetary policy (Δit) on loan growth (Δln(L)t) • Euro-zone data (Bankscope), 1999-2005, • Innovations/ features • Inclusion of “expected default frequency” EDF • as a level term • interacted with interest rates • time varying bank specific variables (liquidity LIQ, log assets SIZE, capital asset ratio CAP) • Measured relative to sample mean (so interaction terms sum to zero) • Both as level terms and interacted with interest rates • In line with (but also different from) literature on ‘bank lending channel’ • Findings • All these levels and interaction terms highly statistically significant • Coefficients match conventional bank lending view • constrained banks (low LIQ, SIZE, CAP) respond more to monetary policy • Lower EDF associated with rapid lending growth • Interpretation less risky banks respond more to monetary policy

  3. Motivation • This paper is highly topical and has a great motivation • Since July 2007 • sharp drop in bank equity prices (higher EDF) • evident constraints on bank funding/ loan growth • So potential to reveal important lessons about the credit crunch

  4. But a lot of work to be done… • Better relationship to existing literature • Distinguishing bank loan demand from bank loan supply • Improving econometrics

  5. Better relationship to literature • Confusing literature • Many papers, few relate clearly to each other • Bank balance sheet characteristics may affect supply of intermediated credit • Because of constrained access to wholesale funding markets • Different aspects of this story • Cross-sectional: some banks constrained • Time series: access to wholesale funding varies over time. • In my view original cross-sectional theory (Bernanke and Blinder (1988), Stein (1988)) flawed • Stein (personal correspondance) admits the theory is ambiguous, • Too simple to say “results in line with bank lending channel” • Literature says almost anything goes!

  6. Loan demand v. supply • The key empirical issue – must be able to distinguish loan demand from loan supply • eg work of Kashyap and Stein (2000) • Go to great lengths to argue that their results reflect differences in loan supply • EDF is correlated with loan demand • High loan growth associated with higher equity price and hence lower EDF • You have to find instruments for EDF that are correlated with loan supply and not loan demand • Other variables (SIZE, LIQ, CAP) may also be correlated with loan demand

  7. Econometric issues • Essential to use time-country dummies • In Euro area different response of loan demand to interest rates in different countries • I think time country dummies may be only way to correct for this • Model includes level variables • Therefore must include bank fixed effects • Unclear from draft if you do this • Why are interaction results (SIZE, CAP, LIQ) so different from Ehrman et. al. ? • Is this choice of data period? Please investigate

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