the crisis as a wake-up call do banks increase screening and monitoring during a financial crisis?...
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The crisis as a wake-up callDo banks increase screening and
monitoring during a financial crisis?
Ralph de Haas (EBRD)Ralph de Haas (EBRD)
Neeltje van Horen (De Nederlandsche Bank)Neeltje van Horen (De Nederlandsche Bank)
1515thth Dubrovnik Economic Conference Dubrovnik Economic Conference
24-26 June 200924-26 June 2009
OutlineOutline
Introduction
Main hypothesis
Data
Empirical strategy
Results
Conclusions
OutlineOutline
Introduction
Main hypothesis
Data
Empirical strategy
Results
Conclusions
2008: new syndicated lending down by 41%2008: new syndicated lending down by 41%
IntroductionIntroduction
Total syndicated lending (billion US$)
Crisis
IntroductionIntroduction
• Crisis: increased uncertainty about borrower quality
• Banks sharply reduced lending to new borrowers
• Reducing credit to existing clients is costly:
• Previous gathering of proprietary information (Rajan 1992)
• Acceptance of short-term losses in anticipation of long-term profitable relationships (Boot, 1990)
Was lending decreased across the board or did banks also step up efforts to pick better customers and monitor them more carefully?
If so: did this impact certain borrowers in particular?
1. Literature on impact of crises on bank behavior
Considerable evidence on impact of crises on amount of bank lending (e.g. Calomiris and
Wilson, 2004; Ivashina and Sharfstein, 2008; De Haas and Van Lelyveld, 2009)
But not much empirical evidence on the underlying strategies of banks
2. Growing literature on structure of syndicated lending
Others looked at the structure of lending syndicates to analyze how banks deal with:
asymmetric information (Dennis and Mullineaux, 2000; Sufi, 2007)
weak creditor rights (Esty and Megginson, 2003)
risk of strategic defaults (Preece and Mullineaux, 2003)
cultural differences (Giannetti and Yafeh, 2008)
We look at the structure of lending syndicates to analyze how banks deal with a financial crisis and the associated increase in uncertainty about borrower quality
Introduction: contribution to literatureIntroduction: contribution to literature
• Large market used by a wide variety of firms (publicly listed and private, rated and unrated) in a large number of countries
• Hybrid character: combination of public financing and traditional bank lending
• Detailed loan information is publicly available (which allows us to control for loan and borrower characteristics)
• Most importantly: structure of syndicate provides information about bank behavior during a crisis
Introduction: why syndicated lending?Introduction: why syndicated lending?
• A syndicated loan is a loan jointly provided by at least two lenders to a single borrowing firm
• Typically a syndicate consists of two tiers of ‘banks’:
1. Arranging banks Senior tier who negotiate the lending terms with borrower
Mandated by the borrower to structure, organize and market the loan
Responsible for ex ante due diligence/screening and ex post monitoring
2. Participating banks Junior tier who buy a portion of the loan. Not involved in loan
organization
• The structure of lending syndicates varies substantially: (Relative) number of arrangers and participants
Share of the loan that arrangers retain (i.e. not sell down)
Concentration of the syndicate
Introduction: syndicated lendingIntroduction: syndicated lending
Introduction: a stylized lending syndicateIntroduction: a stylized lending syndicate
Introduction: a stylized lending syndicateIntroduction: a stylized lending syndicate
OutlineOutline
Introduction
Main hypothesis
Data
Empirical strategy
Results
Conclusions
Main hypothesisMain hypothesis
• Screening and monitoring reduces credit risk (Allen, 1990; Broecker, 1990)
• Crisis: screening and monitoring more beneficial as proportion of borrowers with high default probability increases
• Syndicate: arrangers screen and monitor on behalf of participants
• Because the arrangers sell most of the loan, their incentives to screen and monitor – which is costly – are diluted
• Participants can prevent arrangers from shirking by forcing them to increase the part of the loan they retain (cf. Holmström and Tirole, 1997)
• Need to prevent shirking more urgent during crisis
• We expect that during the crisis:
1. Arrangers retain a larger share of each loan to convince participants that they properly screen and monitor
2. The number of arrangers remains stable or increases and the number of participants remains stable or decreases
3. Syndicates become more concentrated
4. The above holds in particular for loans where agency problems are severe
• Without increased screening and monitoring we would expect less, but similarly structured loans
Main hypothesisMain hypothesis
Increased monitoring
OutlineOutline
Introduction
Hypothesis
Data
Empirical strategy
Results
Conclusions
Detailed info on 21,343 syndicated loans to private borrowers in 65 countries
•Source: Dealogic Loan Analytics
•All loans signed between January 2005 and April 2009
•Information about
Borrower: country of incorporation, industry, credit rating
Loan terms: maturity, volume, currency, spread, fee structure, and loan purpose
Structure of syndicate: no. arrangers, no. participants, share held by each lender (only for 20% of loans)
•Keep only loans with complete and consistent information. Excluded project finance loans, loans to (quasi-)government entities, loans where an IFI is among syndicate members
•Multiple tranches: loan variables are weighted averages of the tranches
DataData
No. MeanSt.
Dev. No. MeanSt.
Dev.
Syndicated loan characteristicsVolume (US$ million) 20,950 460 1338 9,352 429 1403 0.07Maturity (years) 20,286 4.41 2.73 8,942 3.93 2.89 0.00Loan is guaranteed 21,343 0.04 0.19 9,355 0.04 0.20 0.02Loan is secured 20,953 0.15 0.36 9,355 0.12 0.33 0.00Loan for refinancing purposes 21,343 0.25 0.43 9,355 0.20 0.40 0.00Loan for acquisition purposes 21,343 0.15 0.36 9,355 0.13 0.33 0.00Loan for general corporate purposes 21,343 0.49 0.50 9,355 0.55 0.50 0.00
Syndicate structure characteristicsNumber of arrangers 21,343 2.48 2.30 9,355 2.42 2.24 0.06Number of participants 21,343 4.20 4.86 9,355 3.24 3.98 0.00Total share held by arrangers 6,623 0.55 0.26 2,130 0.63 0.27 0.00Average share held by arrangers 6,578 0.35 0.22 2,109 0.34 0.20 0.08Concentration: share of five largest lenders 6,623 0.85 0.21 2,130 0.88 0.19 0.00Concentration: Herfindahl index 6,623 0.29 0.19 2,130 0.30 0.18 0.04
Borrower and lender characteristicsBorrower has credit rating 21,343 0.25 0.43 9,355 0.21 0.41 0.00Borrowed at least once in 5 years prior to loan signing21,343 0.49 0.50 9,355 0.60 0.49 0.00Located in USA 21,343 0.40 0.49 9,355 0.37 0.48 0.00Located in Japan 21,343 0.23 0.42 9,355 0.27 0.45 0.00Located in emerging market 21,343 0.13 0.34 9,355 0.16 0.36 0.00Average market share arrangers at time t-1 21,196 1.13 0.97 9,235 1.13 0.99 0.97Rating of sovereign (numerical, D=1 & AAA=21) 21,343 16.15 3.44 9,355 16.05 3.67 0.02
T-testPre-Crisis Crisis
Data: Syndicated lending pre-crisis (Jan 2005 - Sept 2007) versus during the crisis (Oct 2007 - April 2009)
Main changes in loan characteristics during crisis:
Loans become on average 7% smaller
Maturity drops by 6 months on average
Percentage of loans secured by collateral drops by a
fifth
DataData
Changes in syndicate structure during crisis:
Mean number of arrangers unchanged; mean number of participants declines from 4.2 to 3.2
Total share retained by arrangers increases by 15%
Syndicates more concentrated: share of five largest lenders increases by 4% and the Herfindahl index by 3%
DataData
Changes in borrower and lender characteristics:
Decline in the percentage of rated borrowers
Increase in the proportion of borrowers in emerging markets (from 10% to 15%)
Mean ‘reputation of borrower’ (number of previous loans the borrower raised successfully) decreases during crisis
Mean ‘arranger reputation’ (market share in previous year) decreases during crisis
DataData
OutlineOutline
Introduction
Hypothesis
Data
Empirical strategy
Results
Conclusions
• Regress syndicate structure measures on crisis dummy
• Include loan-specific and borrower specific control variables:(1) loan volume (5) maturity
(2) (un)rated (6) (not) guaranteed
(3) loan purpose (7) borrower and arranger reputation
(4) sovereign rating (8) regional dummies
• Control for participant liquidity
• Separate regressions / interaction terms for loans with above/below average expected information asymmetries
• Dependent variables are either one-sided or two-sided censored: Tobit
• Standard errors clustered at borrower level
Empirical strategyEmpirical strategy
OutlineOutline
Introduction
Hypothesis
Data
Empirical strategy
Results
Conclusions
Results: basic regression resultsResults: basic regression results
Basic results all point to a strategy of increased screening and monitoring by lending syndicates:
Small increase in number of arrangers
Drop number of participants of 20% of pre-crisis mean
Total share of arrangers increased by about 16%
Average share held by each arranger increased by 5%
Stronger concentration of syndicate (increase of 5% for share held by Top 5 and 10% for HHI)
ResultsResults
• Rated companies: Less screening and monitoring due to availability of public information
• Borrowers with better reputation: Less screening and monitoring
• Arrangers with better reputation: Less screening and monitoring
• Secured loans: More screening and monitoring
Results: control variablesResults: control variables
Results are robust to various regression techniques and specifications:
• Longer crisis period (August 2007 – April 2009)
• Clustering by bank
• Additional regressors (i.e. sectoral dummies)
• OLS and Poisson (where relevant)
• Controlling for liquidity of participants
ResultsResults
Results: differentiated impact of crisisResults: differentiated impact of crisis
Crisis has no differentiated impact on rated versus unrated companies → screening and monitoring has become more
intense for both types of borrowers
Results: differentiated impact of crisisResults: differentiated impact of crisis
During crisis loans to repeat borrowers are granted by less concentrated syndicates → loans are perceived as less risky
and plagued by fewer agency problems
Results: differentiated impact of crisisResults: differentiated impact of crisis
During crisis secured loans are granted by less concentrated syndicates → secured loans are perceived as less risky and
plagued by fewer agency problems
Results: emerging markets
Results: financial firms
• Results so far interpreted as a reflection of increased need to contain moral hazard with regard to screening and monitoring effort on part of arrangers
• Arrangers need to signal to participants that they step up screening and monitoring efforts during crisis
• Alternative ‘agency’ interpretation is one of adverse selection:
Arranger has private information not known to participant and has incentive to syndicate out more of ‘bad’ loans
So increase in share held by arranger might reflect that participants force arrangers to signal that arranger do not sell off “bad” loans
Results: moral hazard or adverse selection?Results: moral hazard or adverse selection?
These two effects can be disentangled (Sufi, 2007):
• Previous lending relationships between borrower and arranger capture information advantage of arranger
• Moral hazard: arranger already knows the borrower through previous deals, so less need for additional screening and monitoring: → arranger needs to retain less of loans to repeat borrowers
• Adverse selection: arranger already knows the borrower through previous deals, so needs to show to participant that (s)he will not abuse it → arranger needs to retain more of loans to repeat borrowers
Results: moral hazard or adverse selection?Results: moral hazard or adverse selection?
ResultsResults
Change in syndicate structure is due to participants aiming to contain moral hazard, not adverse selection
OutlineOutline
Introduction
Hypotheses
Data
Empirical strategy
Results
Conclusions
During the crisis banks did not indiscriminately reduce their lending but stepped up screening and monitoring:
– Especially for less reputable borrowers
– Especially for borrowers in the financial sector
– Especially for unsecured loans
– Especially for unrated borrowers (in emerging markets rating does not alleviate agency problems)
– Especially in case of less reputable arrangers (in emerging markets arranger reputation does not alleviate agency problems)
Future work: impact on borrowers
ConclusionsConclusions
THANK YOU
Additional slides
Would not be an equilibrium outcome
We have information on whether the loan volume has decreased during negotiations (likely first step). During crisis, slight increase compared to normal times but still < 1% of loans
We show that crisis impact on syndicate structure is not homogenous but higher for loans where agency problems can be expected to be particularly severe
We explicitly control for participant liquidity
Results driven by decrease in Results driven by decrease in participants’ liquidity during crisis?participants’ liquidity during crisis?
Mean Share Held By Arrangers Herfindahl Index
Crisis 0.019** 0.030***
[0.033] [0.000]Crisis*Participant Liquidity -0.011 -0.015
[0.493] [0.325]Participant Liquidity 0.016* 0.018**
[0.085] [0.033]Observations 6,879 6,879LR chi2 5,713.23 4,485.74Log Likelihood 2,646.78 3,622.50
Controlling for participant liquidity
Diversification Diversification across imperfectly correlated projects
decreases aggregate portfolio risk (Markowitz 1959; Hart and Jaffee 1974)
Helps banks to reduce threat of insolvency and to act as better delegated monitors (Boyd and Prescott 1986)
Well-diversified loan portfolio will make it easier to convince depositors and other creditors to keep funding banks during a crisis
HypothesesHypotheses
If this strategy is dominant we expect that:
all syndicate members (arrangers and participants) have reacted to the crisis by spreading their lending over a larger number of syndicated loans
each member will have reduced the average share of each syndicated loan it retained or bought
all else equal, increase in number of arrangers and participants per syndicate and less concentrated syndicates
HypothesesHypotheses
Hypotheses: diversificationHypotheses: diversification
Hypotheses: diversificationHypotheses: diversification