Predicting financial distress using corporate efficiency and corporate governance measures
MetadataShow full item record
Credit models are essential to control credit risk and accurately predicting bankruptcy and financial distress is even more necessary after the recent global financial crisis. Although accounting and financial information have been the main variables in corporate credit models for decades, academics continue searching for new attributes to model the probability of default. This thesis investigates the use of corporate efficiency and corporate governance measures in standard statistical credit models using cross-sectional and hazard models. Relative efficiency as calculated by Data Envelopment Analysis (DEA) can be used in prediction but most previous literature that has used such variables has failed to follow the assumptions of Variable Returns to Scale and sample homogeneity and hence the efficiency may not be correctly measured. This research has built industry specific models to successfully incorporate DEA efficiency scores for different industries and it is the first to decompose overall Technical Efficiency into Pure Technical Efficiency and Scale Efficiency in the context of modelling financial distress. It has been found that efficiency measures can improve the predictive accuracy and Scale Efficiency is a more important measure of efficiency than others. Furthermore, as no literature has attempted a panel analysis of DEA scores to predict distress, this research has extended the cross sectional analysis to a survival analysis by using Malmquist DEA and discrete hazard models. Results show that dynamic efficiency scores calculated with reference to the global efficiency frontier have the best discriminant power to classify distressed and non-distressed companies. Four groups of corporate governance measures, board composition, ownership structure, management compensation and director and manager characteristics, are incorporated in the hazard models to predict financial distress. It has been found that state control, institutional ownership, salaries to independent directors, the Chair’s age, the CEO’s education, the work location of independent directors and the concurrent position of the CEO have significant associations with the risk of financial distress. The best predictive accuracy is made from the model of governance measures, financial ratios and macroeconomic variables. Policy implications are advised to the regulatory commission.
Showing items related by title, author, creator and subject.
Mays, Richard (The University of Edinburgh, 1998)
Advertising greenness in China: a critical discourse analysis of the corporate online advertising discourse Liu, Shubo (The University of Edinburgh, 2015-07-01)A growing number of companies, both multinationals and local firms, have begun to adopt the idea of sustainability development, and develop and market their green products/services with green advertising in developing ...
Legitimising sustainability: how individuals gain legitimacy for an emerging corporate strategy from internal organisational actors Ivory, Sarah Marie Birrell (The University of Edinburgh, 2014-11-25)Legitimacy is widely accepted as an important resource for an organisation, strategy, or individual to possess. However, the process of gaining legitimacy has received limited attention in the academic literature. This ...