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Forecasting Charge-Off Rates with a Panel Tobit Model: The Role of Uncertainty

Xin Sheng (), Rangan Gupta () and Qiang Ji
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Xin Sheng: Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, CM1 1SQ, United Kingdom
Qiang Ji: Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China

No 202092, Working Papers from University of Pretoria, Department of Economics

Abstract: Based on a large panel dataset of small commercial banks in the United States, this paper employs a dynamic panel Tobit model to analyze the role of uncertainty in forecasting charge-off rates on loans for credit card (CC) and residential real estate (RRE). When compared to other standard predictors, such as house prices and unemployment rates, we find thatthe effect of uncertainty changes on charge-off rates is more pronounced. Furthermore, it is evident that including heteroskedasticity in the model specification leads to more accurate forecasts.

Keywords: loan charge-offs; panel data; Tobit model; forecasting (search for similar items in EconPapers)
JEL-codes: C11 C23 C53 G21 (search for similar items in EconPapers)
Pages: 9 pages
Date: 2020-10
New Economics Papers: this item is included in nep-ban, nep-for and nep-ore
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