| This study addressed the issue of the relationship between CEO compensation and both firm specific characteristics and CEO specific characteristics. The study design used Pearson Product Moment correlation, least squares regression analysis and stepwise Regression Analysis to test the relationship between CEO compensation against both firm specific characteristics and CEO specific characteristics. The independent variables for this study consisted of performance variables (percentage change in stock market return and percentage change in return on equity) and size variables (sales, assets, and number of employees). Also, the independent variables for this study consisted of CEO specific characteristics (age, job tenure, education, and CEO stock ownership). The two dependent variables are percentage change in CEO compensation and dollar level of CEO compensation, which was defined as each CEO's salary plus bonus.; The data was gathered for the years 2001--2003. The sample for the study consisted of 108 years of CEO characteristics and firm data for 36 firms in the U.S. Commercial banking industry. This study was limited to firms with data available for all three years. The sources of information for this study were secondary data from Standard and Poor's Compustat database, Forbes 500 Compensation Report, Hoover's Company database, Business Week, Fortune 500 and filings of 10K Reports with the Securities and Exchange Commission. Two tests were conducted using Pearson Product Moment Correlation Analysis: First, a test to determine if there is a positive correlation between total salary plus bonus compensation and the indicators for firm specific characteristics over the three-year period. Second, a test to determine if there is a positive correlation between total salary plus bonus compensation and the indicators for CEO specific characteristics over the three-year period. Regression analysis was used to predict CEO compensation based on firm performance, firm size and CEO characteristics. Stepwise regression analysis was used to determine the contribution of each independent variable in the regression model.; The results indicated there is a weak relationship between both percentage stock price return and percentage return on equity and the percentage change in CEO compensation. There is a strong relationship between sales, assets and number of employees and dollar level of CEO compensation. There is a weak relationship between age, CEO tenure in present position, education and CEO stock ownership and the dollar level of CEO compensation.; The results of the First Stepwise Regression analysis found that percentage change in return on equity was more important than percentage change in stock market return in determining percentage change in CEO compensation.; The results of the Second Stepwise Regression analysis found that the order of importance made to dollar level of CEO compensation was the following: Assets, Sales, Number of Employees and Tenure of CEO in Present Position. In addition, recommendations were offered for further study. |
