The Project Report In Executives Salaries Commerce Essay

The Project Report In Executives Salaries Commerce Essay Are CEOs overpaid? Many people think so and many potential causes have been identified such as too much power, inattentive boards of directors, conflicts of interest by compensation consultants, the use of stock options and the list goes on. Some studies show that the average CEO was paid $10 million to $15 million in 2005. This includes their salary, bonus, stock option gains, stock grants and various executive benefits and prerequisites (news.cnet.com). We now look at the highest 10 paid jobs in UK and find not surprisingly that Company CEOs are right there at the top of the list by a huge pay difference when compared with others high in the list. 10 Highest paid UK jobs June 2009 Company CEO/Directors  £171,509 Doctors  £81,744 Brokers  £80,233 Financial Managers Chartered Secretaries  £79,545 Civil Servants (Senior)  £71,824 Aircraft Pilots Flight Engineers  £61,585 Management Consultants/Economists  £52,505 Lawyers, Judges Coroners  £51,579 Police Officers (Inspector and above)  £51,487 Managers (Marketing and Sales)  £50,575 ( Source : careerbuilder.co.uk ) Research Question What factors affect chief executive officer salaries? The files CEOSAL1.RAW and CEOSAL2.RAW are data sets that have various firm performance measures as well as information such as tenure and education. Compared with CEOSAL1.RAW, the second data set contains more information about the CEO, rather than about the company is included (Wooldridge, 2008). In the dataset, Wooldridge took a random sample of data reported in the May 6, 1991 issue of Businessweek. Literature Review In context of current financial crisis, CEO compensation has been a major subject of discussion among businessmen and academics since early 1920s (McKnight et al., 2000). How high should be the compensation, what is the relationship between CEO pay and his abilities, what is the correlation between CEO compensation and companys performance? We have chosen the topic due to its obvious relevance with current financial situation. During the literature review we found a number of empirical articles, exploring various aspects of CEO compensation. McKnight et al (2000) in CEO age and Top Executive Pay: A UK Empirical Study examines the implication of CEO age on managerial pay. They promote four hypotheses: The positive relationship between CEO pay and age The positive relationship between company size and CEO compensation, however it would weaken with the increase of CEO age The relationship between company performance and CEO salary would weaken with increasing age of CEO The relationship between company performance and CEO incentive pay would be positive and would strengthen with increase of CEO age They have explored over 100 UK companies and not only considered CEO pay but have divided it into salary, performance bonuses and share options in order to obtain clearer results. McKnight et al (2000) have concluded that relationship between CEO age and their bonuses appeared to be non-linear. The data did not support Hypothesis 3 and 4, although Hypothesis 1 and 2 were proved by the data. The practical implication of their research suggests that board members considering CEO pay should take into account the age, family and financial circumstances of the CEO, especially if CEO age is about 53 years, as it is an inflection point on curvilinear association of the effect of CEO age on bonus. This conclusion highlights the different aspect of CEO pay, whereas in earlier research McKnight (1996) examined 200 UK firms and found that performance and firm size are the important predictors of executive remuneration. Rose and Shepard (1997) in Firm diversification and CEO compensation: managerial ability or executive entrenchment? explored empirical association between CEO pay and a number of different firm characteristics, such as size and performance. They have also considered CEO personal abilities and characteristics, however the major focus of their research was on correlation between CEO pay and company diversification. They conclude that firm diversification in most cases does not benefit stockholders by increasing company value, but might only benefit the decision makers. Rose and Shepard (1997) admit that such conclusion is controversial and required further empirical research. Rose and Shepard (1997) considered firm diversification as one important determinant of CEO compensation. Investigating the relationship between CEO compensation and firm diversification over 1985-1990, they found that the CEO of a firm with two lines of business averages 13% more in salary and bonus than the CEO of a similar-sized but undiversified firm, ceteris paribus. The term Ceteris Paribus means that all other relevant factors held fixed or constant (Morris, 2008). In the later paper of Van Putten and Bout (2008), the relationship between CEO compensation and company performance has been stressed and their research was made during financial crisis and therefore might be more relevant in todays economic situation. Deckop (1988) analyse data from 120 firms in 1977-81 to show that CEOs were not given an incentive through compensation to increase the size of the firm at the expense of profit which is contrary to the findings of some other studies. Rather, CEO compensation was positively related to profit as a percentage of sales. The market equity value of the firm and the CEOs age and years of service as a CEO had a little effect on compensation (Deckop, 1988). Wright, Kroll and Elenkov (2002) provide us with a theoretical argument that the effect of acquisition-related factors on CEO compensation is contingent upon the intensity of monitoring activities. In firms with vigilant monitors, returns will explain changes in CEO compensation while in firms with passive monitors, increased corporate size due to an acquisition will explain compensation changes. They found support for their hypothesis in a sample of 171 acquisitions over the 1993-98 time period. Various researchers have come up to different conclusions exploring factors affecting CEO pay, therefore we have found this question interesting and we would consider the data from Cengage database and look for some other factors, affecting CEO compensation. Data Description The data has been downloaded from CEngage Learning which has online data sets for Wooldridges Introductory Econometrics: A Modern Approach (cengage.com). It contains two data sets namely CEOSAL1.RAW and CEOSAL2.RAW. CEOSAL2.RAW, the second data set contains more information about the CEO, rather than about the company as in case of CEOSAL1.RAW. The Table below describes the variables in the data sets CEOSAL1 and CEOSAL2. These two data sets were merged to give one final data set namely CEOSAL3.DTA. The variable description for the final data set CEOSAL3 can be found in the Appendix. Variable Descriptions for CEOSAL1 Salary Annual salary (including bonuses) in 1990 (in thousands) $ Sales Firm sales in 1990 (in millions) $ Roe Average return on equity, 1988-90 (in percent) Pcsal Percentage change in salary, 1988-90 Pcroe Percentage change in roe, 1988-90 Indust = 1 if an industrial company, 0 otherwise Finance = 1 if a financial company, 0 otherwise Consprod = 1 if a consumer products company, 0 otherwise Util = 1 if a utility company, 0 otherwise Ros Return on firms stocks 1988-90 Lsalary Natural log of salary Lsales Natural log of sales Variable Descriptions for CEOSAL2 Salary Annual salary (including bonuses) in 1990 (in thousands) $ Age Age in Years College = 1 if attended college, 0 otherwise Grad = 1 if attended graduate school, 0 otherwise Comten Years with Company Ceoten Years as CEO with Company Sales Firm sales in 1990 (in millions) $ Profits Firm Profits in 1990 (in millions) $ Mktval Market Value (in millions) $, end 1990 Lmktval Natural log of mktval Lsalary Natural log of salary Lsales Natural log of sales Comtensq comten^2 (company tenure squared) Ceotensq ceoten^2 (ceo tenure squared) Profmarg profits as % of sales Data Analysis We used regression analysis to look out the factors that affect chief executive officer salaries. We chose a multivariate model because most variables cannot be explained by a single variable and estimations based on a single explanatory variable may lead to biased coefficients (Baum, 2006). A multivariate model allows for ceteris paribus analysis and we can avoid the missing variable bias. We used Stata 10 for the regression analysis of the data set. The data sets namely CEOSAL1.DTA and CEOSAL2.DTA were combined to get a single data set CEOSAL3.DTA. The merging of data sets was possible because the variable salary and sales were common to both data sets and this was necessary to come up with a single equation. The data set CEOSAL1.DTA in memory was appended with CEOSAL2.DTA on disk using the append datasets option in Stata 10 by clicking on Data tab and selecting combine datasets option. Econometric Methodology The methodology is econometric as statistical tool (Stata 10) was used to address economic issues. The analysis is based on observational (non-experimental) data. We then derive a relationship from economic theory or come up with an equation that serves us as an econometric model. lsalary = 4.78 (.51) + .191 (.04) lsales + .083 (.06) lmktval + .017 (.005) ceoten .094 (.079) grad .065 (.23) college .01 (.003) comten + I + u where lsalary = dependent variable, regressand; lsales / lmktval / ceoten / grad / college / comten = explanatory variables, regressor ; u = error term / disturbance; I = dummy / dichotomous variable for Industry ; 4.78 = intercept parameter, .19 / .08 / .017 / -.09 / -.06 / -.01 = population / slope parameters and the respective standard errors are shown in brackets and the bold variables represent that the variable is statistically significant in the data. In the above equation as the dependent variable is also in natural logarithm, the natural log of the explanatory variable gives us elasticity. Elasticity is the percentage change in one variable given a 1% ceteris paribus increase in another variable (Wooldridge, 2008). So, the coefficients of lsales and lmktval give us the elasticity i.e the percentage increase in the dependent variable when the explanatory variable is increased by 1% ceteris paribus. For example, a 1% unit increase in lsales will account for approximately 19% increase in lsalary and similarly a 1% unit increase in lmktval will account for approximately 8% increase in lsalary. Interpretation The t-statistic or t-ratio is defined as the coefficient of the variable divided by its standard error (Wooldridge, 2008). If the numerical value of t-statistic or t-ratio is greater than 2 i.e |t| >2, then the variable is statistically significant. In the data after running the regression analysis, we find the t-ratio of lsales, ceoten, comten and the constant ( y intercept parameter) to satisfy the above inequality [ |t| >2 ] and hence these variables can be declared as statistically significant. The R square for the model is 0.355 ( approximately 36% ) which is moderate as a high R square does not necessarily imply a better model as the coefficient can be misleading at times. However, it is a good starting point and generally bigger R square is good. We get the constant ( y intercept ) to be statistically significant as this would allows us to make an idea of the basic salary of CEO even when sales, profits and market value is down because the CEO gets paid his basic salary, rega rdless of the firm making profits or losses. Critical Analysis With reference to our group presentation and the video reported by ABC News, NewYork which showed that CEOs average annual bailout is $ 13.7 million and average wage earner earns $ 31, 589. This is almost 436 times the salary of an average wage earner which seems to raise few questions and a debate over whether CEOs are overpaid ( youtube.com ). This then raises the point that no survey of executive compensation is complete without the discussion of political factors influencing the great level of CEO pay. The controversy heightened with the November 1991 introduction of Graef Crystals (1991) expose on CEO pay, In Search of Excess, and exploded following President George Bushs ill-timed pilgrimage to Japan in January 1992, accompanied by an entourage of highly paid US executives (Murphy, 1999). Conclusion The research aimed to find out the factors that affect chief executive officer salaries and why CEOs are compensated greatly. The data sets namely CEOSAL1.DTA and CEOSAL2.DTA were combined to give a final data set that was used to answer the research question and draw the conclusion that sales, market value ceotenure have a positive effect on CEO salary while company tenure and college / graduation have a negative effect. In our research and data analysis, the most significant factor comes out to be sales. Limitations The data Wooldridge took is from an issue of Busineesweek in 1991 which is quite old. The files need to be updated and it could be very interesting to know the current trend in CEO Compensation and whether the current economic recession had any effects. Due to the current prevalent economic crisis, the findings can be really interesting which could further add some value to the research that has been already done and leave some space for more research to be carried out in this particular topic. An interesting comparison could be made between the factors e.g sales, ros (return on stocks), roe (return on equity), CEOs age, CEO tenure, profits, market value, comten (years with company), etc highlighted in our literature review and our results so that we know which factor plays the most important role and consequently affects chief executive officer salaries when contrasted in relative terms with other studies. The sample size in the data is approximately 200 observations which is not gr eat. The data shows no evidence for the location of firms and the gender of the CEO. It would be a more contemporary question to pose that is there any gender discrimination in CEO Compensation. The policies of the government are also unknown to see if there were any tax evasions present or not. Further Research A further deep research could use the current data to find the factors affecting CEO salaries. Then, the effects of current economic recession could be looked into and a further study could try to find whether CEOs are overpaid and if so what are the reasons for it? Is it truly because of their managerial ability or it is just an executive entrenchment? Then one could also look at the role of monitoring CEOs and their firms. Are these small, medium or family operated firms and what factors affect their growth and output? Is there sex discrimination in CEO compensation? 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