Determining the Effects of Governance Variables in the Relational Approach

In this Chap. 3 of this Stage 2 the reader/user is introduced to determining the effects of ‘governance variables’ in the Relational Corporate Governance Approach Model for Australian Banks. The conceptual result of mixing or combining the components in Chap. 2 is that eight ‘governance factors’ are ‘weighed’ in the conceptual ‘scales’ of the ‘three relational axes of good governance’ to obtain or derive the hypothesised or predicted interrelationships between the original thirty-nine governance variables. This is achieved using an additional key component – a diagram called the ‘Shareholder-Primacy Interrelationship Scheme’. Thus, the Interrelationship Scheme gives the relational approach its name of relational corporate governance – each of the thirty-nine governance variables affect each other according to the hypothesised or predicted interrelationships set out in this diagram below. The Shareholder-Primacy Interrelationship Scheme is used to build an hypothesised or predicted ‘relational effect path’ for each governance variable. The Key Code sets out each hypothesised or predicted relational effect path of each governance variable identifying the governance factor affected and the direction of the effect culminating in two operational tables, the ‘Coverage Table’ and the ‘Relational Proximity Table’. The hypothesised or predicted relational proximity rating of each governance variable is akin to the ‘Richter scale’ for earthquakes. Relational proximity does not give the user a dollar value of the effect of the governance variables on each other and the firm’s/bank’s value/share price, operating performance/profit or likelihood of earnings manipulation. Instead, it gives the user a relative measure out of 100 of the importance/strength of the governance variable in affecting those measures.