Chapter 1: Introduction
1.8 Contributions of the study
The major contributions of this thesis can be divided into five as set out in chapters two to six. To the best of the author’s understanding, this study is the first piece of research work to examine credit risk for privately-traded non-financial corporations under distressed economic and financial conditions in a developing country (Zimbabwe). The results of the study are interesting since the majority of the existing studies on private firm credit risk modelling are primarily dedicated to advanced economies. To fit the models, this research project adopts unique real-world cross-sectional data sets pooled from an anonymised major Zimbabwean commercial bank. Macroeconomic values are mined from an online open-source, the World Bank Group. Zimbabwe gives a stimulating and challenging case in examining credit risk for privately-traded non- financial corporations in developing countries. Over the past two decades Zimbabwe has experienced severe and prolonged distressed economic and financial conditions.
The distressed economic and financial conditions experienced in Zimbabwe are rarely found in developed economies or even in some developing economies.
21 Firstly, this research project adds new knowledge to the existing body of bankruptcy literature by conducting a review of literature on privately-owned non-financial firm bankruptcy prediction in developing economies using Arksey and O’Malley’s (2005) scoping review framework. Whereas the bankruptcy forecasting literature for publicly- owned corporations has been systematically reviewed in several studies, no systematic review or any other form of literature review has been carried out for privately-traded corporations in developing economies. This scoping review examines the reasons and motives for research, the emerging trends and research gaps in forecasting bankruptcy probability for private non-financial corporations in developing economies. The results of the research project disclose that the prediction of bankruptcy probability for private non-financial corporates in developing economies is an imperative discipline that has not been suitably investigated and has some distinctive and unexplored areas due to its complexity and the diverse business ethos of private corporations. For instance, it is highlighted that the examination of default probability for privately-traded non-financial firms under distressed economic and financial conditions in developing economies is an issue that needs further investigation.
Secondly, stepwise logistic regression models are created, premised on different combinations of financial ratios, firm and loan features and macroeconomic variables, and a stepwise selection of some threshold criteria to predict default probability for privately-held non-financial firms under distressed economic and financial conditions in a developing country (Zimbabwe). The main aim of this thesis is to identify and interpret the predictor variables of private firm default probability. Several new predictor variables are embraced in predicting probability of default and a comprehensive examination of the predictors used in the estimation of default probability is given. The results of the experiment indicate that accounting information is useful in distinguishing between defaulted and non-defaulted privately-held non- financial corporations under distressed economic and financial conditions in Zimbabwe.
Further, the study shows that the estimation results of probability of default models for private non-financial firms are enhanced by incorporating macroeconomic factors.
Thirdly, the research project separately predicts probability of default for audited and unaudited privately-owned non-financial corporations under distressed economic and financial conditions in a developing country (Zimbabwe) implementing stepwise logit models premised on diverse combinations of financial ratios, firm and loan features and macroeconomic variables. The main aim of the thesis is to identify and interpret the
22 drivers of probability of default for audited and unaudited Zimbabwean privately-traded non-financial corporations. A number of new predictor variables are employed in separately predicting probability of default for audited and unaudited corporates and a comprehensive examination of the predictors used in probability of default modelling is presented. The study results show that under distressed economic and financial conditions, accounting information is crucial in distinguishing defaulted and non- defaulted audited and unaudited Zimbabwean privately-traded non-financial corporations, and the forecasting ability of default probability models for audited and unaudited privately-held non-financial corporates is augmented by incorporating macroeconomic variables.
Fourthly, stepwise Ordinary Least Squares (OLS) regression models are designed based on different combinations of firm characteristics, loan features and macroeconomic variables to predict workout recovery rates for defaulted bank loans for privately-traded non-financial corporations under distressed financial and economic conditions in a developing economy (Zimbabwe). The main aim of the research project is to identify and interpret the predictor variables of private firm defaulted bank loans recovery rates.
Several new predictor variables are implemented in forecasting the recovery rates and a broad analysis of the adopted predictors in modelling the recovery rates is set out. The thesis reveals that accounting information is valuable in examining the recovery rates for defaulted bank loans for privately-held non-financial corporations under distressed economic and financial conditions in Zimbabwe. Further, the research project discloses that the forecasting results of the recovery rate models are enhanced by incorporating macroeconomic variables.
Lastly, OLS regression models are designed based on diverse mixtures of borrower features, account characteristics and macroeconomic factors to predict the credit conversion factor (CCF) in order to accurately estimate, at the account level, exposure at default for defaulted privately-traded non-financial corporations having credit lines under distressed economic and financial conditions in a developing country (Zimbabwe). The primary emphasis of this thesis is on identifying and interpreting the predictor variables of the CCF for the defaulted privately-owned non-financial corporations with credit lines. A number of new predictor variables are adopted in predicting the CCF and a comprehensive examination of the drivers implemented in the prediction of the CCF is outlined. The study results show that accounting information is essential in examining the CCF for defaulted privately-owned non-financial
23 corporations with credit lines under distressed economic and financial conditions in Zimbabwe. Moreover, the research project reveals that the CCF models' prediction results and the corresponding exposure at default estimates are improved by incorporating macroeconomic variables.