Comparison of going concern models with and without corporate governance - Paul Hammond; Mustapha Osman Opoku; Paul Adjei Kwakwa; Daniel Berko (Cogent Business & Management, 2023)
This study examines the effectiveness of going-concern prediction models by comparing models that incorporate corporate governance variables with models based solely on financial ratios. The aim was to compare the predictive power of going-concern models that combine corporate governance variables and corporate reporting ratios with models that used only financial ratios. Utilising secondary data obtained from published annual financial statements from 15 Ghanaian, 10 Nigerian, and 10 South African banks, we developed two logistic models: one comprising financial variables alone and another integrating both financial and corporate governance variables. The findings demonstrate that models incorporating corporate governance outperform those relying solely on financial ratios. Among the financial ratios, working capital to total assets and retained earnings to net profit emerged as significant predictors of going concern. Additionally, two corporate governance variables, namely board size and board independence, displayed contrasting relationships with the going concern. Board independence exhibited a direct relationship, while board size demonstrated an inverse association. This research contributes to the existing body of knowledge by providing stakeholders in financial institutions with robust models for measuring and predicting the firms' going-concern position. We recommend incorporating corporate governance variables alongside financial ratios in the development of going-concern models to enhance their predictive capabilities.
Keywords: 650; board independence; board size; corporate governance; financial ratios; going concern; logistic regression