We design ordinary least squares (OLS) regression models to estimate the credit conversion factor (CCF) in order to precisely predict the EAD at the account level for defaulted private nonfinancial corporations having credit lines under distressed economic and financial conditions in a developing economy. Our primary focus is on identifying and interpreting the CCF determinants for the defaulted privately owned corporates with credit lines. We apply the models to a unique real-life cross-sectional dataset of defaulted Zimbabwean private corporations. Our empirical results show that the committed amount, the credit usage, the drawn amount, the time to default, the total assets, the ratio of bank debt to total assets, the current ratio, the earnings before interest and tax to total assets ratio, the real gross domestic product growth rate, and the inflation rate are all substantial drivers of the CCF for Zimbabwean private corporates with credit lines. We observe that accounting information is essential in analysing the CCF for private corporations with credit lines under downturn conditions in a developing country. Furthermore, we reveal that the CCF models' forecasting results and the corresponding EAD estimates are augmented by including macroeconomic variables.

Projects

Currently no objects available

Currently no objects available