Estimation of the Loan Spread Equation with Endogenous Bank-Firm Matching
Abstract
This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I supplement the loan spread equation with a two-sided matching model and estimate them jointly. Bayesian inference is feasible using a Gibbs sampling algorithm that performs Markov chain Monte Carlo (MCMC) simulations. I find that medium-sized banks and firms tend to be the most attractive partners, and that liquidity is also a consideration in choosing partners. Furthermore, banks with higher monitoring ability charge higher spreads, and firms that are more leveraged or less liquid are charged higher spreads.
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Acknowledgements
Acknowledgment
I thank Jan Brueckner, Linda Cohen, Joseph Harrington, Ivan Jeliazkov, Ali Khan, Robert Moffitt, Dale Poirier, Matt Shum, Tiemen Woutersen, and seminar participants at Brown, Iowa, Johns Hopkins, St. Louis Fed, UC Irvine, USC, Williams College, and the 13th Advances in Econometrics Conference for their helpful comments.
Citation
Chen, J. (2013), "Estimation of the Loan Spread Equation with Endogenous Bank-Firm Matching", Structural Econometric Models (Advances in Econometrics, Vol. 31), Emerald Group Publishing Limited, Leeds, pp. 251-289. https://doi.org/10.1108/S0731-9053(2013)0000032009
Publisher
:Emerald Group Publishing Limited
Copyright © 2013 by Emerald Group Publishing Limited