Expected Loan Loss Provisioning: An Empirical Model

63 Pages Posted: 1 Mar 2019 Last revised: 18 May 2021

See all articles by Yao Lu

Yao Lu

Cornell University - Samuel Curtis Johnson Graduate School of Management

Valeri V. Nikolaev

University of Chicago Booth School of Business

Date Written: May 17, 2021

Abstract

The new accounting standard requires that financial institutions estimate expected credit losses on their loan portfolios. The predictability of long-term losses, however, remains an open question. We develop a model that predicts long-term loan losses and incorporates adjustments for macroeconomic forecasts. The model combines cross-sectional predictions with a high-dimensional dynamic factor model that tracks aggregate losses over the business cycle. The model predicts long-term losses out-of-sample with significantly greater accuracy than the Harris et al. (2018) model and several other alternatives. It is also more effective at detecting bank failures. We use the model to estimate the present value of expected losses and the expected loss overhang for a given bank-quarter. The estimated present values subsume information in reported allowances and in fair value disclosures about long-term losses; the evidence is also consistent with loss overhang distorting banks’ decisions. The model provides a useful benchmark to study loan loss provisioning.

Keywords: Expected long-term credit losses, CECL, prediction, aggregate credit losses, expected loss overhang

JEL Classification: G21, M40, M41

Suggested Citation

Lu, Yao and Nikolaev, Valeri V., Expected Loan Loss Provisioning: An Empirical Model (May 17, 2021). Chicago Booth Research Paper No. 19-11, Available at SSRN: https://ssrn.com/abstract=3344657 or http://dx.doi.org/10.2139/ssrn.3344657

Yao Lu

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

Valeri V. Nikolaev (Contact Author)

University of Chicago Booth School of Business ( email )

5807 South Woodlawn Avenue
Chicago, IL 60637
United States

HOME PAGE: http://faculty.chicagobooth.edu/valeri.nikolaev/index.html

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
417
Abstract Views
1,999
rank
87,922
PlumX Metrics