Credit Availability: Identifying Balance-Sheet Channels with Loan Applications and Granted Loans

Size: px

Start display at page:

Download "Credit Availability: Identifying Balance-Sheet Channels with Loan Applications and Granted Loans"

Judith Dean
5 years ago
Views:

1 Credit Availability: Identifying Balance-Sheet Channels with Loan Applications and Granted Loans G. Jiménez S. Ongena J.L. Peydró J. Saurina Discussant: Andrew Ellul * * Third Unicredit Group Conference on Banking and Finance

2 Overview of the Monetary Transmission Mechanism Source: Kuttner and Mosser (2002)

3 Results and Contribution Investigates credit availability during the business cycle and addresses the question as to whether agency costs ( rms-banks, and banks- nanciers) make lending more di cult in economic downturns or monetary contraction periods. Use a comprehensive micro-dataset on (a) rms loan applications to their non-current banks, and (b) all business loans, in Spain (bank-dependent country). Result 1: Worse economic and tighter monetary conditions reduce loan granting. Result 2: Loan granting in such times is even worse to rms or from banks with lower capital or liquidity ratios. Result 3: Responding to applications for the same loan, weak banks are less likely to grant a loan.

4 Results and Contribution The literature (e.g. Berger and Udell (1990, 1994), Peek and Rosengren (1995), Asea and Blomberg (1998), Kashyap and Stein (2000), amongst others) does not disentangle (a) loan demand and supply, and (b) rm and bank balance sheet channels to address "this old and very basic question" (Kashyap and Stein (2000)). This paper: brings together both rm (demand side) and bank (supply side) balance sheet data to identify the impact of balance sheet channels on credit availability. Implication 1: Existing literature may have signi cantly underestimated the strength of the bank lending channel. Implication 2: Policy conclusions are cleaner when the demand-side e ect is disentangled from the supply-side e ect.

5 -1 The main conclusion of the paper is that "under tighter monetary and economic conditions, a capital crunch begets a credit crunch". Bernanke and Lown (1991) de ne a credit crunch as a signi cant leftward shift in the supply curve for loans, holding constant both the safe real interest rate and the quality of potential borrowers. During a credit crunch, credit supply should shift relative to the "normal". This in turn calls for the use of a "control period" and the "abnormal" relationships during a credit crunch compared to what is "normal". The empirical methodology does not disentangle "normal" periods from periods where supply and demand shifts occur.

6 - 2 Using data on loan approvals has its own advantages. But it has one signi cant drawback: are you capturing the e ect of balance sheet channels on credit availability or banks lending standards? Asea and Blomberg (1998) and Dell Ariccia, Igan and Laeven (2007) show that lending standards are pro-cyclical. Asea and Blomberg (1998) show that loans extended on easier terms during expansions return to haunt banks as problem loans during contractions. Credit market imperfections may have a more profound e ect on aggregate activity during expansions than during contractions.

7 - 3 Azariadis and Smith (1993) have a general equilibrium model with adverse selection in credit markets. Two results emerge: credit market problems are more severe in expansions than in contractions and equilibria display endogenous regime switches. Implication 1: A benchmark period is required to assess the exact magnitude and dynamics of a credit crunch. The issue may not be low loan approval rates during tight monetary and worse economic conditions, but rather over-lending when monetary policy is lax or good economic conditions. Implication 2: A Markov regime-switching model may be richer and more robust than the methodology used, allowing you to deepen your analysis.

8 - 4 A key theoretical concept is the external nance premium, both for banks and rms. For rms, the external nance premium depends on rms nancial strength, liquidity and future cash ows. Question 1: Since the external nance premium is presumably larger for rms in industries with high nancial dependence (Rajan and Zingales (1998)), do we see these rms su ering most? Question 2: Since future cash ows depend on rm s investment opportunities, do we see credit rationing experienced by rms with high investment opportunities as well? Hard to get proxies for investment opportunities (market-to-book ratios) at the rm level, but it is possible to obtain these at the industry level.

9 - 5 Banks themselves face an external nance premium, which is in turn re ected in the cost and availability of funds to bank-dependent borrowers. Nondeposit sources of funding for banks are likely to be relatively more expensive than deposits, re ecting credit risks associated with uninsured lending (Stein, 1998). Question 1: Are banks with high external nance premia, presumably those with high levels of nondeposit sources of funding, the most aggressive in credit rationing? Question 2: Using the dataset for the longer period ( ) did we see banks with high numbers of bank- rm relationships invest in deposit capacity to reduce their external nance premia along the lines of Black, Hancock, and Passmore (2007)?

IV SPECIAL FEATURES THE IMPACT OF SHORT-TERM INTEREST RATES ON BANK CREDIT RISK-TAKING

IV SPECIAL FEATURES THE IMPACT OF SHORT-TERM INTEREST RATES ON BANK CREDIT RISK-TAKING B THE IMPACT OF SHORT-TERM INTEREST RATES ON BANK CREDIT RISK-TAKING This Special Feature discusses the effect of short-term interest rates on bank credit risktaking. In addition, it examines the dynamic