Year: 2025
Type: article
Abstract: Macroeconomic variables are crucial inputs used in the credit loss forecasting (LF) models and the use of macro effects is also mandated by regulators for stress testing purposes which allow banks to project the potential credit loss under different hypothetical macroeconomic scenarios. The COVID-19 pandemic has caused an unprecedented level of volatility in the macroeconomic variables, leading to new challenges to use macroeconomic variables in the LF and the current expected credit loss (CECL) modeling framework. Especially, the historical observed strong relationship between the macroeconomic variables and credit loss rate seems to disappear. This study examines the dynamic relationship between the charge-off rates on loans of all U.S. commercial banks and the macroeconomic factor from 1985 to 2020. This paper seeks to explore the correlation and predictive power of key macroeconomic indicators on the charge-off rates for three different portfolios – consumer, commercial and industry, and real estate loans. This study will shed light on which macroeconomic factors have high importance in the credit loss forecasting modeling. The results presented in this paper can also be served as a guideline for the macroeconomic variables selection process in the credit LF/CECL models development or model overlay design.
Source: Journal of Finance Issues
Authors: Zilong Liu, Hongyan Liang, Chang Liu
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4411811679