Credit Rationing by Loan Size: A Synthesized Model

23 Pages Posted: 30 Jan 2012 Last revised: 22 Dec 2015

See all articles by Einar C. Kjenstad

Einar C. Kjenstad

Aarhus University

Xunhua Su

Norwegian School of Economics (NHH)

Li Zhang

Shanghai Pudong Science and Technology Financial Services Association

Date Written: February 1, 2015

Abstract

We construct a synthesized model to study credit rationing by loan size. In our model, the borrower faces a trade-off between raising debt and exerting costly effort to undertake an investment project. In the absence of agency costs, increasing the loan size at the equilibrium interest rate raises the default risk and hence reduces the average cost of the loan for the borrower, so the borrower always demands a larger loan than what the lender can offer. Furthermore, agency cost raises this excess demand for a given interest rate. If the agency cost is sufficiently high, the borrower is unable to obtain the loan that she needs at any interest rate, requiring the use of non-price instruments in the loan contract. This is the common logic underlying the agency models of non-price credit rationing, as we show in the cases of costly state verification, money diversion, risk-shifting and hidden shirking.

Keywords: credit market, debt, credit rationing, agency cost, hidden effort, moral hazard, money diversion, costly state verification, monitoring cost

JEL Classification: D82, D86, G21, G32

Suggested Citation

Kjenstad, Einar C. and Su, Xunhua and Zhang, Li, Credit Rationing by Loan Size: A Synthesized Model (February 1, 2015). Quarterly Review of Economics and Finance, Volume 55, February 2015. Available at SSRN: https://ssrn.com/abstract=1994459 or http://dx.doi.org/10.2139/ssrn.1994459

Einar C. Kjenstad

Aarhus University ( email )

Nordre Ringgade 1
Aarhus, 8000
Denmark

Xunhua Su (Contact Author)

Norwegian School of Economics (NHH) ( email )

Helleveien 30
Bergen, NO-5045
Norway

HOME PAGE: http://sites.google.com/site/xunhuasu/research

Li Zhang

Shanghai Pudong Science and Technology Financial Services Association ( email )

Pudong
Shanghai
China

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
293
Abstract Views
1,808
rank
109,098
PlumX Metrics