CECL and the Credit Cycle

Abstract

We find that that the Current Expected Credit Loss (CECL) standard would slightly dampen fluctuations in bank lending over the economic cycle. In particular, if the CECL standard had always been in place, we estimate that lending would have grown more slowly leading up to the financial crisis and more rapidly afterwards. We arrive at this conclusion by estimating historical allowances under CECL and modeling how the impact on accounting variables would have affected banks' lending and capital distributions. We consider a variety of approaches to address uncertainty regarding the management of bank capital and predictability of credit losses.

Forecasting Expected and Unexpected Losses

“…We start by estimating the model on a "training sample" from 1985q1 to 1999q4, using the estimates to forecast the two moments in each of the twelve subsequent quarters, ending with 2002q4. This is in line with regulatory texts and banking industry practice (Loudis and Ranish, 2019), which indicate three years as the longest "reasonable and supportable" forecast horizon. We then proceed to construct similar out-of-sample forecasts by sequentially adding one quarter to the sample.…”

“…16 We start from a training sample consisting of the first 15 years of observations, 1985q1-1999q4, and then expand it by one quarterly observation at a time to generate our (pseudo) real time forecasts. In line with the literature (Covas andNelson, 2018, andLoudis andRanish, 2019), we set the maximum forecast horizon to three years (H = 12), the transition period to two years (N = 8) and the maturity of the portfolio to 7.5 years (M = 30). 17 With these choices, our first forecasts for the quarterly losses are μ00q1|99q4 ,..., μ02q4|99q4 .…”

“…In the second part of our empirical exercise, we aggregate the forecasts of quarterly losses over the loan portfolio's lifetime. Following regulatory practice and the literature (FASB, 2016, Covas and Nelson, 2018, and Loudis and Ranish, 2019, we make standard simplifying assumptions regarding the portfolio's rundown structure, as well as the behavior of losses beyond the maximum forecast horizon. These assumptions and our first-moment forecasts deliver directly forecasts of the portfolio's EL.…”

Current Expected Credit Losses (CECL) Standard and Banks' Information Production

“…Several concurrent studies examine the impact of CECL adoption on banks' lending and risk-taking. For example, some studies examine the effects of CECL on lending procyclicality by employing either actual data under the CECL approach or simulated data under the ILM [e.g., Cohen and Edwards, 2017, Abad and Suarez, 2018, Covas and Nelson, 2018, Harris et al, 2018, Loudis and Ranish, 2019, Chae et al, 2020, Huber, 2021, Chen et al, 2022, Lu and Nikolaev, 2022. These studies document mixed findings on the effects of CECL adoption on lending procyclicality, likely due to the different modeling assumptions for the simulated data or the limited data points under the CECL approach.…”

“…First, we provide empirical evidence of the economic consequences of CECL adoption, which is useful to standard setters for the Post-Implementation Review (PIR). Several concurrent studies examine the impact of CECL adoption on lending procyclicality [e.g., Cohen and Edwards, 2017, Abad and Suarez, 2018, Covas and Nelson, 2018, Harris et al, 2018, Loudis and Ranish, 2019, Chae et al, 2020, Huber, 2021, Chen et al, 2022, Lu and Nikolaev, 2022. Another stream of studies suggests that loan loss provisions under the CECL model contain some decision-useful information [e.g., Beatty and Liao, 2021, Wheeler, 2021, Gee et al, 2022.…”