MODERATING IMPACT OF BOARD COMPOSITION ON THE RELATION BETWEEN COMPANY ATTRIBUTES AND PERFORMANCE OF BANKS IN NIGERIA

A hierarchical regression model consisting of hypothesised board composition, company attributes and performance were formulated and subjected to various diagnostic and robustness tests to ascertain the Best Linear Unbiased Estimators (BLUE) in the model.

Model Specification PER = β0+ β1it BC it + β2itSIZ + β3it LEV + β4itBSIZ + β5itAGE + ԑ ........... (1) Where; Β0..., βk is the regression model coefficients of the independent variables x0..., xk is the parameters of the explanatory variables ԑ is the random error term it at a given period or point in time Where; LEV= Leverage SIZ= Size BC= Board Composition PER= Performance proxied by ROA= Return On Equity BSIZ= Board Size AGE= Firms’ Age Table 3.1: Variables Definition and Measurement Variables A priori Signs Measurement Source Independent variables (Total Firm Characteristics) Firm Size + Measured as Natural log of total assets Annual report Leverage + Measured as the ratio of total debt to total assets Annual report Board Size + Measured as the total number of Directors on Annual report the board Firms Age + Measured as Number of years in existence Annual report Dependent Variable (Performance) Return on Equity + Measured as the ratio of profit after tax to Annual report total equity Moderating variables (Board Composition) Board Composition + Measured as the ratio of the number of Annual report non-executive directors to the total number of directors on the board.