distance and information asymmetries in lending decisions
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Distance and Information Asymmetries in Lending Decisions. by Sumit Agarwal and Robert Hauswald (& sons) Discussant Hans Degryse CentER – Tilburg University, TILEC, K.U. Leuven and CESIfo TILEC-AFM Chair on Financial Market Regulation - PowerPoint PPT PresentationTRANSCRIPT
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Distance and Information Asymmetries in Lending Decisions
by
Sumit Agarwal and Robert Hauswald (& sons)
Discussant
Hans Degryse CentER – Tilburg University, TILEC, K.U. Leuven and CESIfo
TILEC-AFM Chair on Financial Market Regulation
Conference on the “Changing Geography of Banking”, Ancona, September 2006
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General Issue• Does distance still matter?
– Petersen and Rajan (JF2002): US• No, as distance between lender and borrower has quadrupled
from 1970’s to 90s
• Yes, as loan rate decreases in distance
– Degryse and Ongena (JF2005): Belgium• Yes, distance between lender and borrowers did not increase
substantially over from 1975-97
• Yes, as loan rate hinges on distance to lender and distance to competitor
– This paper: US• Loan pricing: when controlling for score, no
• Loan volume and switching: yes
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General Issue: evidence
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General Issue: why should distance matter?
• What does distance capture?– Petersen and Rajan (JF2002): US
• No, as distance between lender and borrower has quadrupled from 1970’s to 90s
• Yes as loan rate decreases in distance
– Degryse and Ongena (JF2005): Belgium• Yes; distance between lender and borrowers did not
decrease dramatically
• Yes, as loan rate hinges on distance to lender and distance to competitor
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This paper’s findings• Loan rate determinants
– decreases in borrower-lender distance (DL) and increases in borrower-competitor distance (DC)
– Distance loses statistical significance when introducing the internal score of lender
– Interaction between score, and DL and DC shows that higher scored firms that are closer pay higher rates, hinting at asymmetric information being the driver
– Nice treatment of potential selection issues
• Decision to offer credit– Decrease in DL and increase in DC– Increase in score; distance remains significant
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This paper’s findings
• “Switchers away from Bank”– Increase in DL and decrease in DC– Interaction of score, and DC and DL suggest
that higher scored firms are more likely to switch when DC is large, suggesting asymmetric information
• delinquency: further away borrowers are more delinquent
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Comments:Setting more inclined towards asymmetric information?
“transportation costs” vs. “asymmetric information”
• Degryse and Ongena (JF2005): Belgian sample: 44% borrowed from closest branch
• US: “borrowers do not turn to the closest branch but prefer to borrow from further away”
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Comments:Setting more inclined towards asymmetric information?
1. US versus Belgium: absolute differences in distance
2. US versus Belgium: huge relative differences in DL versus DC
=> how would results be in a restricted sample with “similar” absolute and/or relative differences
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Comments: asymmetric information?
• Inclusion of “score” in loan pricing model– Removes statistical significance of distance as
standard errors increase– Magnitude of coefficients and economic
significance, however, often remains
• Main Bank and Duration of Relationship (Months on Books)– Relatively short duration: median of 30 months– both have a negative coefficient in loan rate
regression => asymmetric information would suggest a positive coefficient
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Comments: Is it asymmetric information?
• Suppose branch managers know that the bank applies the following pricing model:
Loan rate = f (Score)
=> Branch managers reflect local market power in score => borrowers where the branch manager asserts to enjoy a lot of market power get low score
(see Ioannidou and Ongena (2006): competing bank credit scores get adjusted to allow loan officers to give borrowers lower rate to attract borrowers)
=> distance and competitive setting gets reflected into score
• On p. 8-9 the authors mention: our bank estimates that, on average, 20 to 30% of our bank’s scores consists of soft information
• Suggestion: orthogonalize score to investigate the separate impact of distance and check in how far “internal score” differs from “external score”
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Comments: Technology and potential selection
• Loans are from January 2002-April 2003, a recent period when new technologies may already be in place– Is the bank only granting loans via its branches, or are
also loans through other channels like• Internet• Online banking• Other stores/shops, available=> i.e. do you cover all the loan applications and approvals of the
bank?=> if not, potential selection issues
– Similar issues and question for rival banks?
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Minor Comments– Do “competing branches” include own bank’s
branches?– “Switching away from bank” versus “switching
towards bank”– Should “months on books” and “main bank” and
some other variables still play a role when internal score is good proxy of private information?
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Summary
• Interesting topic? Yes!
• Interesting paper? Yes!
• Do I recommend that you read it? Yes!
• Am I convinced? May be … Not Yet