Abstract
We investigate the impact of bank competition on the use of collateral in loan contracts. We analyze asymmetric information about the borrowers’ type in a Salop model in which banks choose between screening the borrower and asking for collateral. We show that the presence of collateral is more likely when bank competition is low. We then test this prediction empirically on a sample of bank loans from 70 countries. We perform logit regressions of the presence of collateral on bank competition, measured by the Lerner index. Our empirical tests corroborate the theoretical predictions that bank competition reduces the presence of collateral. These findings survive several robustness checks.
Similar content being viewed by others
Notes
See the special issue of the Journal of Money, Credit and Banking in 2004 (vol. 36, n°3) on this topic.
A similar setup is used in Degryse et al. (2008).
Qualitatively we would obtain the same result in a model in which the firms differ in their preferences for the bank offering a screening contract (for instance, because they have relationships of different intensity) but do not differ with respect to the bank offering a collateralized credit contract.
We would obtain the same qualitative result if firms had to incur some costs of application.
The countries are : Algeria, Angola, Argentina, Australia, Austria, Belgium, Bangladesh, Bolivia, Brazil, Bulgaria, Cameroon, Chile, China, Colombia, Croatia, Czech Republic, Denmark, Ecuador, Egypt, Finland, France, Germany, Ghana, Greece, Guatemala, Hong Kong, Hungary, India, Indonesia, Ireland, Iran, Israel, Italy, Ivory Coast, Jamaica, Japan, Kazakhstan, Korea, Lithuania, Malaysia, Mexico, Morocco, Netherlands, Norway, New Zealand, Oman, Pakistan, Panama, Papua New Guinea, Peru, Philippines, Poland, Portugal, Romania, Russia, Saudi Arabia, Singapore, Slovenia, Slovakia, South Africa, Spain, Sri Lanka, Sweden, Switzerland, Thailand, Tunisia, Turkey, United Kingdom, Venezuela, Viet Nam.
A term loan is defined in Dealscan as an instalment loan where amounts repaid may not be reborrowed.
As our sample includes many syndicated loans in which arrangers play a more active role than participant banks, we have also performed our estimations by considering only the number of arrangers involved in the loan. Results are totally similar.
This can lower performance in terms of social welfare because higher interest rates worsen firms’ incentives (Schnitzer 1999).
We adopt the logit model rather than the probit model, because Akaike and Schwarz information criteria are lower in logit regressions. However, we have also performed the probit regressions as a robustness check, and found similar results.
References
Beck T, Levine R (2004) Stock markets, banks, and growth: panel evidence. J Bank Finance 28:423–442
Beck T, Demirgüc-Kunt A, Levine R (2000) A new database on financial development and structure. World Bank Econ Rev 14:597–605
Beck T, Demirgüc-Kunt A, Maksimovic V (2004) Bank competition and access to finance: international evidence. Journal of Money, Credit and Banking 36, 3, 627–654
Beck T, Demirgüc-Kunt A, Laeven L, Maksimovic V (2006) The determinants of financing obstacles. J Int Money Finance 25:932–952
Berger A, Klapper L, Turk-Ariss R (2009) Bank competition and financial stability. J Financ Serv Res 35(2):99–118
Berger A, Espinosa-Vega M, Frame WS, Miller N (2011) Why do borrowers pledge more collateral? New empirical evidence on the role of asymmetric information. J Financ Intermed 20:55–70
Besanko D, Thakor A (1987) Collateral and rationing: sorting equilibria in monopolistic and competitive credit markets. Int Econ Rev 28:671–689
Bester H (1985) Screening and rationing in credit markets with imperfect information. Am Econ Rev 75:850–855
Bharath S, Dahiya S, Saunders A, Srinivasan A (2007) So what do I get? The bank's view of lending relationships. J Financ Econ 85:368–419
Broecker T (1990) Credit-worthiness tests and interbank competition. Econometrica 58:429–452
Dahiya S, John K, Puri M, Ramirez G (2003) Debtor-in-possession financing and bankruptcy resolution. J Financ Econ 69(1):259–280
Degryse H, Laeven L, Ongena S (2008) The impact of organizational structure and lending technology on banking competition. Rev Finance 13:225–259
Dell’Ariccia G (2001) Asymmetric information and the structure of the banking industry. Eur Econ Rev 45:1957–1980
Djankov S, McLiesh C, Shleifer A (2007) Private credit in 129 countries. J Financ Econ 84(2):299–329
Esty B (2001) Structuring loan syndicates: a case study of the Hong Kong Disneyland project loan. J Appl Corp Finance 14(3):80–95
Godlewski C, Weill L (2011) Does collateral help mitigate adverse selection? A cross-country analysis. J Financ Serv Res 40(1):49–78
Hainz C (2003) Bank competition and credit markets in transition economies. J Comp Econ 31:223–245
Hauswald R, Marquez R (2006) Competition and strategic information acquisition in credit markets. Rev Financ Stud 19(3):967–1000
Inderst R, Mueller H (2007) A lender-based theory of collateral. J Financ Econ 84:826–859
Jimenez G, Saurina J (2004) Collateral, type of lender and relationship banking as determinants of credit risk. J Bank Finance 28:2191–2212
Jimenez G, Salas V, Saurina J (2006) Determinants of collateral. J Financ Econ 81:255–281
Kaufmann D, Kraay A, Mastruzzi M (2007) Governance matters VI: governance indicators for 1996–2006. World Bank Policy Research Paper n°4280
La Porta R, Lopez-de-Silanes F, Shleifer A, Vishny RW (1997) Legal determinants of external finance. J Finance 52:1131–1150
La Porta R, Lopez-de-Silanes F, Shleifer A, Vishny RW (1998) Law and Finance. J Polit Econ 106:1113–1155
Manove M, Padilla AJ, Pagano M (2001) Collateral versus project screening: A model of lazy banks. RAND J Econ 32(4):726–744
Maudos J, Fernandez de Guevara J (2004) Factors explaining the interest margin in the banking sectors of the European Union. J Bank Finance 28:2259–2281
Maudos J, Fernandez de Guevara J (2007) The cost of market power in banking: social welfare loss vs. cost inefficiency. J Bank Finance 31:2103–2125
Qian J, Strahan P (2007) How laws & institutions shape financial contracts: the case of bank loans. J Finance LXII 6:2803–2834
Schnitzer M (1999) On the role of bank competition for corporate finance and corporate control in transition economies. J Inst Theor Econ 155(1):22–46
Sufi A (2007) Information asymmetry and financing arrangements. J Finance 62(2):629–668
Taylor A, Sansone A (2007) The handbook of loan syndications and trading, McGraw-Hill
Author information
Authors and Affiliations
Corresponding author
Additional information
Financial support by the German Science Foundation, under SFB-Transregio 15 and HA 3039/2-1, is gratefully acknowledged. We received substantive comments during seminar presentations at the University of Munich, the ifo Institute Munich, the XVII International Tor Vergata Conference on Banking and Finance in Rome, the 2009 CESifo Area Conference on Applied Microeconomics in Munich, the 2009 Northern Finance Association Meeting in Niagara on the Lake, the 2009 Southern Finance Association Meeting in Captiva Island. Of course, all remaining errors are our own.
Appendix
Appendix
1.1 Proof of Lemma 1
From (IC.BF_L) we know that L = 1. Moreover, the participation constraint of the good firm must hold:
If the project is successful, a good firm repays R L from the payoff X it generates. In the case of failure, collateralized assets in the amount of 1 are seized by the bank. The expected payoff when the investment is credit-financed has to be at least as high as the payoff from not investing (which is A).
Bank 1 will participate if it makes at least zero expected profit with the contract offered. The bank’s expected profit by each (good) firm is given by
which implies that it needs a repayment of at least \( {R^L} \). Since all banks are identical bank 1 cannot demand a higher repayment without losing all its customers. Q.E.D.
1.2 Proof of Lemma 2
When bank 1 offers a screening contract it must take into account that the other banks offer a collateralized contract. Given this outside option of the firm, bank 1 can demand a repayment of \( R_1^S \) without losing the firm as a customer:
Bank 1’s expected profit per borrower with this repayment is:
which is non-negative if \( d \leqslant \frac{{\left( {1 - p} \right)\left( {1 - \alpha } \right)}}{c} \). For firms located further away, the costs of producing information are lower with a collateralized contract. This means that bank 1 cannot undercut the expected repayment of a collateralized contract because it would need a repayment of at least \( { }R_1^S = { }1 + \frac{{cd}}{p} \). As a result, firms at a distance \( d > \frac{{\left( {1 - p} \right)\left( {1 - \alpha } \right)}}{c} \), apply for a collateralized loan from bank 2 which makes zero expected profits. Q.E.D.
1.3 Proof of Proposition 2
All banks are identical. Bank 1 finances the following fraction of firms through a screening contract:
As a result, the fraction of firms financed through a screening contract increases as the number of banks increases.
Moreover, a collateralized contract is a viable alternative only if \( \left( {1 - p} \right)\left( {1 - \alpha } \right) < \frac{c}{{2N}} \). Thus, as N increases, the parameter range in which this condition holds, decreases.
Q.E.D.
Rights and permissions
About this article
Cite this article
Hainz, C., Weill, L. & Godlewski, C.J. Bank Competition and Collateral: Theory and Evidence. J Financ Serv Res 44, 131–148 (2013). https://doi.org/10.1007/s10693-012-0141-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10693-012-0141-3