Executive compensation changes during periods of
deregulation
Thesis Gail Henriquez Student number: 6032613 Master in Business Economics
Field: Finance Supervisor: Jeroen Ligterink
Date: 15 December 2014
Abstract
Executive compensation changes after deregulation are covered considerably by existing literature. Previous literature has assessed that regulators use these deregulations to increase market competition and improve efficiency in an industry. While most financial economics find that compensation packages become more incentive based due to the complex and increased role of the executives, some studies also find increases in the fixed or non-incentive based component of pay. This increase in fixed pay can indicate that executive compensation not only increases due to market competition, but may have other factors affecting the level and structure of executive pay. Studies have rarely taken into account measures for corporate governance when analyzing compensation in deregulation periods. Conyon (1997) found that the effect of corporate governance on executive pay is mixed, while Core et al., (1999) study how factors of corporate governance affect CEO compensation and find that firms with weaker corporate governance structures tend to have higher salaries. Bebchuk and Fried (2003) claim that executives do not have the same interests as those of shareholders and can therefore capture part of the value created by firms by receiving excessive compensations. This study will contribute to the current literature by analyzing the corporate governance level among firms that undergo deregulation. Compensation changes are analyzed for over 3000 executives in the finance, banking, telecom and electricity industry. The results show supporting evidence of fixed and incentive based compensation increasing when deregulation takes place. Furthermore, these are found to be higher for firms with weaker corporate governance.
Table of contents
I. Introduction 3
II. Related Literature 6
A. Deregulation effects on market competition 11 B. Corporate governance & Executive compensation 13
III. Methodology 15
IV. Data 18
A. Desciptive statistics 19
V. Results 22
A. Impact of corporate governance 25
VI. Robustness check 27
VII. Conclusion &Discussion 29
A. Limitations 30
VIII. References 31
I. Introduction
The financial sector experienced two substantial deregulation periods in the 1990’s that intensified market competition (Cuñat and Guadalupe, 2009). The first was the Riegle– Neal interstate banking and branching efficiency Act in 1994, which removed many of the restrictions on opening bank branches across state lines. The second deregulation took place in 1999, namely the Gramm–Leach–Bliley Act, also known as the financial services modernization Act, which removed barriers that restricted banks, securities- and insurance companies from competing with each other. In response to these deregulations, market competition increased. As a consequence executive compensations are altered to give the proper incentives (Cunat and Guadalupe, 2009). Existing theory suggests that executive compensation is aligned with the executives’ contribution to productivity. If market competition intensifies, the executive’s role in the firm becomes larger and more complex, requiring a higher compensation in order to attract executives of higher quality. However, the public debates whether executives tend to earn substantially more than they contribute to firms’ earnings (Joskow et al., 1993). Whether the degree in which executive compensation increases is in line with the increase in market competition within an industry after deregulations takes place, remains debatable by previous research.
Regulation has two main effects on compensation policies of firms. First of all, it changes the economic context in which firms operate; this in turn could affect the executive’s impact on the profits of the firm. The Chief Executive Officer (CEO) specifically, tends to have less effect on the firm’s earnings when the industry is heavily regulated causing stockholders to choose a less incentive based and also lower compensation than in the case of deregulated industries. Secondly, regulators can choose to directly influence executives’ compensation, to reduce public concern, by limiting the compensation packages allowed to be paid out by a firm (Joskow et al., 1993).
One stream in the literature of financial economists argues that increases in competition would lead to compensation packages being more incentive based for executives. In other words compensation is used as a tool to reduce agency conflicts, which means that when competition increases, bonuses might also increase (Bryan et al.,
2005). Another stream in the literature argues that if compensation increases are not justified by increases in competition, the executives’ compensation packages are too excessive and are not in line with their productivity. If this is the case, efficiency gains might be reduced, because executives take a bigger part of the value that is created by market competition (Joskow et al., 1993). Due to this contrast in the existing literature this paper will analyze executives’ compensation increases during deregulation periods for different industries with varying degrees of competitiveness. Also since the financial crisis in 2007 there has been much public scrutiny on excessive compensation packages received by executives of banks who have experienced serious liquidity and solvency problems, while earning substantial amounts as compensation, indicating weaker corporate governance for these firms. In the banking sector executives play an important role in decisions regarding tail risk, which may lead to bank failures and in turn financial instability (Bai and Elyasiani, 2013).
Numerous studies also focus on the role of corporate governance in reducing agency conflicts and the effects this has on compensation packages. However, there is not much study done on the changes in governance structures when deregulation takes place. The question this research aims to answer is whether executive compensation tends to increase during deregulation periods and whether this can partly be explained by weaker corporate governance? The contribution to the current literature is that it focuses on the degree of competition among firms by taking four industries in to account and the corporate governance changes for these industries. This study will analyze the changes in competition with the Herfindahl index and corporate governance with the entrenchment index. By taking six provisions that measure corporate governance this last index will indicate whether corporate governance tends to become weaker after deregulation takes place. Using the market share of each firm the Herfindahl index can be calculated to measures increases in the competitiveness in an industry per year.
For this research it is expected to find, that total pay for executives tends to increase after periods of deregulation take place. Total pay will be analyzed by looking at fixed pay and incentive based pay separately. This increase in executive compensation is expected to be a consequence of increased competition among firms in an industry and by weaker corporate governance resulting due to there being less oversight on companies
when there is less regulation.
The data on executive compensation and on companies can be found in Compustat Execucomp for all firms annually, which dates back to 1992. The pay can be analyzed for options granted, restricted stock holdings, bonuses paid, fixed pay etc. The data can be divided into industry groups and will be taken for the banking, financial, telecom and electricity industry for 3 years before deregulation, except for banking due to the earliest data being from 1992 and deregulation takes place in 1994 there will only be two years of observation before deregulation. It will also be taken for 3 years after deregulation, which is equal to the period used by Bryan et al., (2005). They analyze the data for 3 years after deregulation was introduced to give sufficient amount of time for the effects to take place. For the entrenchment index the data is taken from the paper of Bebchuk and Fried (2003). The most important variables that will be analyzed in the research are bonuses and fixed salaries. The independent variables will be the deregulation variable taking on 1 after deregulation is introduced. The Herfindahl index and the entrenchment index will be taken into account in order to study the impact of competitiveness increases and of corporate governance, respectively.
As just mentioned this research will analyze different industries, which is also done in Joskow et al., (1993) and Peoples (2003). This is done in order to compare the changes in salaries experienced for different degrees of competitiveness in the industries, however this study will also take into account the effect of corporate governance on executive compensation which is what the other research papers lack. The explanations for changes in executive compensation after deregulation have mostly been attributed to increases in competition, in the existing literature. The contribution of this paper to the existing literature is that it will also take a measure for the level of corporate governance in to account and it will provide further explanation for compensation changes of executives when restrictions are lifted in an industry. The existing literature has not provided the explicit effects of corporate governance on salary increases for the specific case of deregulation. Conyon (1997) argues that the impact of corporate governance on the CEO’s compensation is mixed. Core et al., (1999) focuses on ownership- and board structures’ effect on CEO compensation and found that these factors do in fact influence
compensation. The authors explain that CEO compensation tends to be higher for firms in which the CEO is also the chairman of the board of directors and the outside directors (directors who are not employees of the firm) are appointed by the CEO. However, these researchers do not focus on deregulation periods, which changes the economic environment of the industry in which the firms operate. This research will measure the entrenchment levels of firms in each year to provide evidence for the theory that weaker corporate governance has an increased effect on salary compensation.
In the following chapter the existing literature on corporate governance and on executive compensation in deregulation periods will be discussed. Chapter 3 contains the methodology used in this research. In chapter 4 a detailed analysis of the data and descriptive statistics will take place. Chapter 5 discusses result and chapter 6 provides robustness checks. The conclusion and limitations of this study will be given in the last chapter.
II. Related literature
The different views held on structural changes and changes in the level of executive compensation in deregulation periods will be discussed below. Afterwards the effects of deregulation on market competition for the industries studied in this paper will be explained in detail. Lastly the features of corporate governance and executive compensation will be discussed.
Finance & banking industry
Cuñat, Guadalupe (2009), Hubbard and Palia (1995) study the effect of deregulations that took place in the financial industry. While Hubbard and Palia (1995) study deregulation in the banking sector in the 1980’s, the first authors focus on the deregulations in 1994 and 1999 to assess the changes in CEO compensation structures. In 1994 all barriers to interstate banking were lifted and in 1999 barriers that separated banking, insurance and security underwriting were lifted. The authors’ aim was to find to what extent changes in compensation packages are driven by changes that arise in the product market, or put
Comment [JL1]: Can you create a
bit more coherent framework? Put up more structure
differently by competition in an industry. They study the overall change in the level of compensation and also the structure hereof. By studying these two previously mentioned periods of deregulation, a quasi-natural experiment is created that assesses the changes in compensation through an exogenous factor; market competition. This way the causal effect of competition on compensation is studied. They used panel data and difference-in-difference method to analyze the difference between a treatment and control group, before and after deregulation. The control group is an industry which did not undergo deregulation. They find that total executive pay for the banking industry in both periods of deregulation increase only marginally compared to the control group. Total compensation was used as the dependent variable, which was measured by summarizing salary, bonus, total value of restricted stock granted, total value of stock options granted, long term incentive payouts and other annual payouts. The results show that for commercial banks fixed pay decreased by 3.2 percent and for financial services a 2.6 percent decrease was found. The authors observed a decrease in fixed pay and an increase in the form of variable pay also known as performance pay, the authors conclude that when the competition in an industry increases, executive pay becomes more incentive based. In contrast to this research, Hubbard and Palia (1995) use deregulation as a proxy to measure competition in an industry. They make use of the managerial talent hypothesis, which implies that deregulations have the effect of increased potential competition among firms in an industry. The managerial talent hypothesis indicates that this will require a firm to have a more capable CEO and in order to attract these CEO’s of higher levels a higher and more responsive pay is required. They studied whether an increase in executive compensation was necessary to attract executives of the required quality or if the compensation of CEO’s were simply too excessive. The results indicate a positive effect of deregulation on salary and bonuses of CEO’s and an increase in options granted. This provides preliminary evidence that is in line with the managerial talent hypothesis, because higher incentive based pay is required in order to attract qualified CEO’s in increased competitive environments. They control for bank specific omitted variables by using a fixed effects model. The authors claim that the positive coefficient found on the dummy variable of deregulation regressed on compensation supports this theory. However, they also find that fixed pay increases in contrast to the findings of
Cuñat and Guadalupe (2009). This indicates that compensation was not increased in an incentive based manner only.
Electricity industry
Another industry that CEO compensation changes have been researched for is the electricity industry. Bryan et al., (2005) hypothesize that introducing deregulation will create market forces in an industry that will induce companies to become more efficient. By lowering their costs and improving efficiency, prices can be lowered which creates value for consumers. Furthermore, they believe that competition increases will result in compensations for CEO’s being more incentive based. CEO’s carry more risk if their compensation structure is more incentive based. In order to motivate them in making more efficient and the most profitable decisions, it is expected that the compensation package will go from a high proportion of fixed pay to a high proportion of variable pay when competition increases. To analyze whether these changes in CEO compensation are driven by deregulation periods a control group is used, which did not experienced deregulations. They find significant changes for compensations that are incentive based. The increase in this type of compensation is relatively greater than increases for the control group. This is in line with their theory, which states that during periods of deregulation, more incentive based compensation is needed to correctly incentivize CEO’s, which are in a more competitive environment post deregulation. This is also in line with the findings of Joskow et al., (1993), which also studied the electricity industry among other industries.
Railroad, trucking, telephone, and airline industry
Joskow et al., (1993) additionally analyzes the telephone, trucking airline and railroads industry for a sample of over 1000 firms. The authors state that there is much debate whether CEO’s get paid substantially more than what they contribute or produce within a firm. If regulators can influence firm’s operations, which is the case for regulated industries, it can influence the level and structure of compensation by imposing constraints on CEO compensation packages. Regulators have the power to determine prices and the level of costs that are allowed within firms, therefore they can penalize
Comment [JL2]: Prober zoveel
mogelijk direct taalgebruik te hantere
firms which they feel pay excessive compensations to their CEOs. The reason why CEO compensation is relatively more susceptible to political pressures in regulated industries is due to their compensation packages being more visible than in deregulated industries and because there is also more contact and interaction between CEOs and members of legislation. Firms in regulated industries are also more likely to attract media attention. The period the authors analyze is from 1970 to 1990. They find that regulation can cause compensation packages to decrease and that these packages are less incentive based. The findings suggest that firms in regulated industries earn 30% to 50% less than those of deregulated industries. This is due to public scrutiny and certain instruments that regulations provide to penalize firms who implement excessive compensation packages. These findings are also in accordance with the findings of Peoples (2003) who found that manager earnings of regulated industries are significantly less when compared to deregulated industries. The industries studied are the railroad, trucking and airline industry. Data on a non-regulated industry is used as control group. They use a vector for the deregulated industries, which enter the regression as dummy variables. The degree of competition differs post deregulation among these three industries. For the trucking industry price competition followed deregulation and also the number of carriers increased. The airline industry switched from non-price to price competition post deregulation. They also experienced a surge of new carriers in the beginning. The railroad industry in contrast had a reduction in class 1 carriers and the industry experienced greater financial stability. The coefficients found on the industry dummy variables suggest that the three industries’ managers earn significantly less than the average industry prior to deregulation. After deregulation the compensation discounts fell from 13.5 to 6.3 for the airline industry, from 17.25 to 2.4 for the railroad industry and from 13.3 to 6.79 for the trucking industry. These results indicate that deregulation provides an environment in which industries become more competitive and increase the compensation of managers. This research however fails to test empirically the extent to which compensations are relatively excessive in comparison to the CEO’s productivity. The author’s furthermore state that eased political pressures and less regulatory oversight is significant in contributing to higher compensations. The explanation for the higher compensation’s of managers found post deregulation are, according to the authors, due to
the marginal productivity of managers increasing and/or having managers of higher quality. Kole and Lehn (1999) have also researched the developments in compensation packages for the airline industry. They analyzed the same period of deregulation as the previously mentioned research, namely the deregulation of 1978, for a period of 22 years and the findings are similar to those of Joskow et al., (1993). They examine annual data for 21 airline companies for their research in which the companies should be present in the sample for at least six years before and after the deregulation Act. By using non-regulated firms in the electric industry the authors create a benchmark for the financial indicators. The authors note however that the benchmark firms do not control for all relevant variables that affect compensation structures, which is due to the fact that these variables are unobservable. The airline industry was heavily regulated until this period with the objective of fostering stable economic conditions in the industry. The airline deregulation Act facilitated entry for low-fare airlines and price regulations were eliminated. The decisions that had to be made by managers altered considerably. Fare structure, route structure, fleet composition, labor costs and distribution channels were managerial decisions that became critical to the firms’ performance. The authors studied CEO pay and stock option compensations. For the stock option compensations they find significant increases after the deregulation period. However, when controlling for firm size and compensation trends, cash compensations do not increase for this period. The authors also state that these changes in executive compensation occur gradually over time. The increase in the incentive based component of the executives’ compensation package, is in line with the previous research papers that study the airline industry. These findings are also explained by the larger and more complex task of managing the firms in a deregulated environment.
Conclusion related literature
The existing literature thus indicates that compensation increases after deregulations are mostly found in the incentive based component of pay, except for Hubbard and Palia (2005) who also found significant increases in fixed pay. Peoples (2003) and , Kole and Lehn (1999) conclude that the increases found in the incentive based compensation can largely be explained by the increase in the complexity of the task and responsibilities of
the executive and not solely by reduction in political constraints on compensation and less oversight by regulators. In addition, Joskow et al., (1993) indicates that the explanation to why regulated industries have lower incentive based compensation can be attributed to regulatory oversight imposing constraints on the level of compensation packages. The current literature however fails to explain the reasons for increases found in the fixed component of executive compensation in periods of deregulation.
A. Deregulation effects on market competition
Several researchers have analyzed the effects of deregulation on industry competition. The intensity of the effect on increased competition differs on the specifics of the deregulation Act and whether penalties were introduced for not complying with the Act. For the deregulation of the banking industry in 1994, assets were reallocated to more efficient banks. Also, the exit rate increased for deteriorating banks in the industry. The relationship between performance and market share became stronger for acquisition-minded banks but also for banks that were not performing well. Indicating that after deregulation the banks that already had a large market share and were performing well, grew more and acquired larger market shares while banks that showed deteriorating performance exited the market (Stiroh and Strahan, 2003). In other words the better banks grew at the expense of poorly performing banks. This had the effect of decreasing costs and prices of banking services (Jayaratne and Strahan, 1998). Thus, the deregulations of the banking industry of 1994 seem to have increased the efficiency and also increased the competition among banks (Cuñat and Guadalupe, 2009).
The telecommunications act of 1996 deregulated the converging broadcasting and telecom market, so that anyone could enter the communications business and also that communication businesses were allowed to compete in any market. The main aim of the legislation was to restructure the telecommunication sector that was necessary since this industry has made substantial technological progress since the last reform in 1934. The Act reduced barriers to entry so that competitors can compete by components as well as services of telecom. A flaw in the Act that can potentially affect the competitiveness in the industry is that they do not impose penalties for non-compliance. This means that
companies can take their time in implementing the reforms since they will not be penalized (Economides, 1999). The telecom industry splits regulatory oversight between federal and state agencies. Because most telephone operating companies’ offer services across states, they are subject to more than one regulatory agency for reviewing of costs. So these operating companies are subject to more regulatory oversight compared to holding companies, where the executives’ compensation is only reviewed by regulators if the costs are charged back the holding companies’ operating branch.
The financial sector underwent deregulation in 1999 with the implementation of the Gramm-Leach-Bliley Act or financial modernization Act. Barriers that imposed insurance and security underwriting and traditional banking to be separated, were lifted. A significant change in stock prices of the companies that were affected by the legislation was found by Carow and Heron (2002). For example insurance companies and investment banks experienced positive abnormal returns because they were more likely to increase their target markets. On the other hand more specialized firms would see their market share under threat, like finance and thrifts companies. However, the Act did not solely benefit the larger firms, it was also observed that small companies that were highly capitalized and healthy also were successful in obtaining larger market shares.
In the year 2000 electricity was deregulated in 15 states of the United States. Before deregulation, electric utility companies were allowed to pass on regulator-approved costs of investments made by the company to their customer in the price of electricity. So consumers would have to pay for the poor decisions made by these utility companies. The deregulation entailed consumers to choose their own electric power generator. They were now competing on the basis of price competition and reliability of which they can supply power. It encouraged electric companies to pursue cost cutting by implementing their plants more efficiently, thereby reducing prices (Schweitzer and Thompson, 2000). The regulatory authorities of the electricity industry depend on the organizational structure of the firm. If the firm operates in only one state they are in oversight of that state’s public utility commission. This is a central authority which is more likely to operate tightly under political pressure when it comes to excessive compensation of executives. Regulatory responsibility of multistate holding companies
Comment [JL4]: ?
Comment [JL5]: Relate to markets
becoming more efficient or competitive, now not clear what you want to say
tends to lack clarity and conciseness in constraints on compensations. It is expected that this difference in legal structure will cause the compensations to be lower in single-state operating electricity companies (Joskow et al., 1993).
From the previous literature on the effects that implementation of deregulation can have, it is clear that the extent to which competition increases depends on the specifics of the Act. For example the effect may be expected to have a stronger effect on competition if the Act is implemented state wide compared to when it is only implemented in particular states. Another potential difference in the effectiveness depends on the legal structure of the company and if penalties were imposed for non-compliance with the Act.
B. Corporate governance & executive compensation
Corporate governance exists to address the issue of the principal agency conflict problem (Shleifer and Vishny, 1997). Its mechanisms are used to ensure financiers of capital that they will receive the return on their investment, when there is separation between ownership and control. Executives are in charge of running the firm, if they have different interests than the shareholders of the company they might make bad investment decisions or forego investment opportunities that could harm shareholders value in serving their own personal benefits. While product market competition is considered to be a strong force to promote economic efficiency, it is debatable whether it can contribute to addressing corporate governance issues.
Another form of addressing corporate governance besides market competition is executive compensation. It is believed that compensation contracts can help address the issue of corporate governance by aligning incentives of shareholders with those of the executives, for example by increasing bonuses related to firm performance or paying out compensation in the form of equity holdings. Bebchuk and Fried (2003) however, believe that if companies have dispersed ownership, executives have substantial power. As a consequence they have too much power in forming their own compensation contracts.
Comment [JL6]: Do you explain this
The board of directors is responsible for approving the compensation contracts of the executives. Just as it is not self-evident that executives have the best interests of the shareholders in mind, the same could be said for directors of the board. Re-nomination of board members is influenced by the CEO. The CEO can also affect the compensations and perks received by the members of the board; these are reasons why the board might be inclined to agree with the CEO’s proposal for executive compensation contracts even when these are not in line with their productivity. Bebchuk and Fried (2003) constructed an entrenchment index (E-index) to measure the level of corporate governance in a firm. This index is based on six provisions that measure corporate governance. Each company is given a score from 0 to 6 based on how many of these provisions the firm has in a year. They take into account that executive compensation can be both an instrument in addressing the agency problem and can be part of the problem as well. The authors conclude that market forces are not sufficient in stimulating optimal compensation contracts. The E-index is used in this paper to measure corporate governance and whether this is an explanatory factor of executive pay.
Hypothesis
From the analysis of the existing literature on executive compensation after deregulation periods the hypothesis can be derived and are provided below:
1. After deregulation, incentive based salaries tend to increase (Joskow et al., 1993 & Cuñat and Guadalupe, 2009).
2. An increase in the fixed pay will also take place for companies after deregulation (Hubbard and Palia, 1995).
3. Firms with weaker corporate governance after deregulation experience higher increased salaries (Bebchuk and Fried, 2003).
Hypothesis regarding increased competition after deregulation and executive compensation?
on executive compensation in deregulation periods. It is expected that an increased competitive environment, will cause incentive based compensation to increase post deregulation. The third hypothesis stems from the previous findings on fixed salary. If this component of compensation increases after deregulation, it might not be justified by increases in competition; it may also be due to changes in corporate governance due to there being less oversight on companies. Bebchuck and Fried (2008) claim that executive compensation can, in addition to being used as an instrument in addressing agency conflict problems, also be considered part of the problem itself. Instead of functioning as an incentivizing instrument, executive pay can be considered a way for managers to reap personal benefits. Firms with weaker corporate governance (higher entrenchment levels) are therefore expected to have higher fixed and incentive based salaries after deregulation than firms who have stronger corporate governance.
III. Methodology
The research method used in this study will serve to find an explanation, besides market competition as to why compensation levels might change when deregulation takes place. The key factor observed will be the level of corporate governance. This factor is expected to have an effect on fixed and incentive based salary. A fixed effects regression will be run in order to assess whether both fixed- and incentive based components of executive compensation tends to increase during periods of deregulation for four different industries. A fixed effect regression serves to eliminate the problem of omitted variable bias that might occur because of variations across executives’ salaries. This method ignores the variation that exists between entities and focuses only on within entity variation. The differences in the level of salaries depend on many factors, for example executive quality, gender, years of education etc. which generally do not vary over time. Therefore the fixed effects model, which controls for unobserved time-invariant variation, takes care of this problem. It is however important to control for variables that may affect the level of salaries that do vary over time. These variables are mentioned as the control variables for the regression later on in this chapter. Another potential issue that often occurs in regression analysis is the problem of reverse causality. This however
will not be an issue in this paper because a causal relationship is implied. Deregulation is an external factor that has the effect of increasing competition, which in turn causes increases in compensations. Finding a positive correlation between compensation levels and deregulation thus can only imply that the latter caused the former. This causality is nevertheless indirectly caused by the structural changes experienced in the industry because of deregulations. The following regressions will be run on fixed salary per year and bonuses per year, where the bonuses will be taken to measure incentive based pay.
Regressions
Model I: LogExecutiveSalaryijt= α + βjt*Deregulationjt + γjt*HHIjt + δjt*Deregulationjt*HHIjt + controlvar + ε
Model II: LogExecutiveBonusijt= α + βjt*Deregulationjt + γjt*HHIjt + δjt*Deregulationjt*HHIjt + controlvar + ε
Where i stands for executive, t for years and j for the industry. These two regressions will serve to provide evidence of the first and second hypothesis. Additionally a variable will be added to each regression in order to provide evidence for the third hypothesis, by including an E-index that will assess the level of corporate governance in the firm. The models with the E-index added as variable will be referred to as the extended models. These are provided below:
Model III: LogExecutiveSalaryijt= α + βjt*Deregulationjt + γjt*HHIjt + δjt*Deregulationjt*HHIjt + ƔijtEindexijt + Ʊit*Eindexijt*Deregulationjt + controlvar + ε
Model IV: LogExecutiveBonusijt= α + βjt*Deregulationjt + γjt*HHIjt + δjt*Deregulationjt*HHIjt + ƔijtEindexijt + Ʊijt*Eindexijt*Deregulationjt + controlvar + ε
A positive coefficient on the dummy variable of deregulation is expected for the regressions on salary and bonuses, for all industries in accordance with the first and second hypothesis. This effect is expected because industries become more competitive once deregulations take place (Joskow et al., 1993). In order to reduce the agency conflicts that occur between shareholders of firms and the executives running the
Comment [J7]: You can still have the
problem of unobserved
heterogeneity; issue of endogeneity is not fully resolved.
company, executives are given personal incentives that increase shareholders value. This will be done by increasing the incentive based component of compensations. By tying compensations of executives to firm performance the shareholder’s- and executives’ interests are more aligned. A negative coefficient on the interaction variable, Deregulation x HHI is expected, implying that higher salaries are observed for companies who experience higher competition increases. The HHI variable measures increases in competition in an industry, which is shown in decreases of the HHI variable itself. This becomes clearer when the computation of the HHI variable is explained later on in this chapter. In accordance with the third hypothesis it is expected that for the regressions stated in model 3 and 4, the coefficient on the E-index variable and the interaction of the E-index and deregulation variable, will be positive. It is expected that weaker corporate governance, can partly explain increases in compensation. Because there is less oversight on companies, executives of the firm have more power to influence the level of their salaries in their own personal benefit. Seeing as bonuses are mostly tied to firm performance, the increased competition due to deregulation might affect earnings of the firm in a negative manner. The CEO might therefore choose to increase executives’ fixed salaries in order to ensure that they receive higher levels of compensations, which are equal to what they earned before deregulation took place. Because the E-index is expected to have explanatory power for salaries, including this variable in the regression will expect to produce a more efficient model.
Competition and the Herfindahl index
In order to measure competition the HHI index is computed. First the market share of each firm is calculated, by taking total revenues of one firm and dividing it by total revenues of all firms in the corresponding industry. Afterwards the market share is squared and summed for all companies in the industry to compute the HHI. The HHI is an integer that ranges from zero to one for all firms, which means that firms which are very small have an integer close to zero and for firms who have monopoly in the industry, the index is observed to be one. An increase in this index thus indicates
decreases in market competition for the firm. This is why for the interaction variable of deregulation and HHI a negative coefficient is expected. It is expected that the decreases in the HHI after deregulation, indicating competition increases, will cause higher increases in executive compensation for both fixed- and incentive based salary.
Control variables
Control variables used will be firm size, because larger firms tend to have different characteristic than smaller firms. Larger firms have more hierarchical levels in the company of executives and the span of control is higher for each level, this then leads to scarce managerial talent being used more productively if the managers with the most talent work at larger firms. This means that their talent will spread across the firm even on to the lower levels. Previous research has indicated a positive correlation between executive compensation and firm size of about 25% (Joskow et al., 1993). There are some studies, which choose to leave out this control variable due to its possible correlation with firm performance. However due to it being one of the most consistent findings in previous literature and the correlation with compensation being relatively high, this paper will include this measure as a control variable. The size of the firm is measured by total assets of the company, which will be taken in the natural logarithm form for the regressions. Furthermore, there will be controlled for firm profitability, firms with larger earnings are expected to pay out higher bonuses than firms with smaller earnings. The existing literature suggests this relationship to vary on the measure used for firm performance. For this study the net income of the company will be used, which will also be taken in its natural logarithmic form. It is expected to find positive coefficients for these variables.
IV. Data
The panel data used in this paper is taken from COMPUSTAT for the company specifics. From this data set the total assets and net income of each company in the sample is taken.
Comment [J8]: Do you somewhere
discuss whethr this actually is the case, iotherwise this would be a good place to do so (but also possible under results!
These are then merged with the executive compensation information, which is taken from EXECUCOMP. There are different structures among firms’ compensation packages, for example some firms do not pay out bonuses while others pay out in different types for example equity or stock options. For this reason this research will be restricted to salary per year also known as the fixed pay and the bonuses in cash form paid out, which is also referred to as incentive based pay, in order to consistently measure executive compensation over time. The data goes back to 1992. So only the banking industry will have observations up to two years prior to deregulation, from 1992 to 1997. For the remaining three industries three years prior and the three years following deregulation will be observed, in order to give sufficient time for the effects of deregulation to take place.
The electricity industry only passed deregulation in 15 states of the US. For the estimates in changes of salary components to be representative of the results, the states which did not undergo deregulation have been removed from the sample. Furthermore, this research does not differentiate among firms who have the same executive throughout the sample period with firms who do have the same executive in the sample period. Regressions will be run on two independent variables of executive compensation with the data collected from the above mentioned databases; the first regression will be for the fixed component with a total of circa 7000 observations. The second regression will be on incentive based compensation, namely bonuses, in which there are over 6000 observations in the sample. Afterwards the E-index will be merged with the existing data to perform the 3rd and 4th regression. This index will be added as a variable to both regressions to estimate whether the increases in salary components can be attributed to the entrenchment level of a company. The index is not available for all companies in the sample, which is why for these regressions there will be less observations. There will be around 1000 observations for fixed salary and for bonuses. This index is taken from the paper of Bebchuk and Fried (2003) who study ‘Executive compensation as an agency problem’. It is based on six provisions that measure corporate governance namely; staggered boards, limits to shareholder amendment of the by-laws, poison pills, supermajority requirements for mergers and for characteristic amendments and the golden parachute arrangement. Each company is given a score from 0 to 6 based on how
Comment [J10]: Hence you ignore
the options and stock part? Can you provide later (eg in robustness analyses) brief analysis of the relevance of these issues in relation to deregulation/increased competition
many of these previously mentioned provisions the firm has in a year. A higher score thus indicates weaker corporate governance.
A. Descriptive statistics
In table 1 the mean and standard deviations are given of the HHI-index along with the mean of the E-index, before and after deregulation for each industry in the sample. In table 2 these statistics are given for the fixed salary and bonuses of executives. For all variables with exception of the HHI-index, it can be observed that the between variation is higher than the within variation of the sample. The between variation consists of the differences observed over the entity group, which are the executives. While the within variation is the variation that exists over the sample period of the executive. This is expected for panel data, seeing as the differences between companies on the level of salary and especially bonuses can vary substantially for each executive. This is also why fixed effects regression is used to model the data, it mainly focusses on the within variation to assess the changes occurring in the dependent variable.
E-index
Regarding the E-index, an increase in the average is observed for all industries after deregulation with the exception of the finance industry, which experiences a slight decrease in the average entrenchment level of 0.35. The lowest entrenchment level is observed for the telecom industry, compared to the other industries, with a level of 1.26 before and 1.78 after deregulation. The industry with the highest increase in average level of entrenchment is observed for the electricity industry. The entrenchment level increases by 0.73, from 2.47 to 3.20, which is also the overall highest average of the industries observed, when looking at the correlations. For the banking and telecom industry a positive relationship for the E-index is also the case. This relationship found indicates that for the industry the entrenchment level becomes higher after periods of deregulation.
HHI index
When analyzing the HHI-index the finance industry is again an exception, in that it experiences an opposite movement in direction as opposed to the other three industries.
The three remaining industries experience a decrease in the HHI-index after deregulation takes place, which is in accordance with the existing theory that competition increases (HHI decreases) when deregulations take place. The Horizontal Merger Guidelines of the U.S. Department of Justice indicates that an index below 0.01 would correspond to a highly competitive market, while an index below 0.15 would indicate an un-concentrated industry. According to these indices the banking industry belongs to an un-concentrated industry for the period before 1994, while after deregulation it becomes a highly competitive industry. The telecom industry at first has an index of 0.16, which is in accordance with an industry with moderate concentration. The decrease found after deregulation takes place is 0.05, which gives the telecom industry a HHI level of 0.11 corresponding to an un-concentrated market. The electricity company is observed to be an un-concentrated industry both before and after deregulation. Lastly, the finance industry also remains an un-concentrated industry throughout the sample period with a slight increase in the variable after deregulation takes place. The competition may however be affected by other factors other than deregulation and that is why looking at differences in averages may not give the results that are expected according to existing literature. The correlations are also observed for the variables relevant to this paper, which are shown in table 3. Between the HHI index and deregulation of the industry, it can be observed that a negative relationship (corresponding to higher competitiveness) is found for the finance and banking industry with the HHI, while the relationship found for the electricity and telecom industry is observed to be positive. Indicating increases in competition for the banking- and finance industry and decreases for the telecom- and electricity industry.
Fixed & Incentive based Salary
From table 2 an increase in mean wages for both fixed and incentive based pay is observed for the telecom, banking and finance industry after a deregulation. The biggest increases in compensation are found for the finance industry, where the fixed component increases by about $ 250.000 after deregulation in fixed salary per year and the average bonus increases by about $ 670.000. For the banking and telecom industry the increases in fixed pay are much smaller. These are observed to increase by $ 40.000 and $35.000,
Comment [J11]: Indirect taalgebruik
respectively. While the average bonus after deregulation increases by $ 120.000 for the banking- and by $ 450.000 for the telecom industry. This provides preliminary evidence that after deregulation both fixed and incentive based pay increase. The standard deviation of bonuses for this industry also increases substantially from 125.20 before to 1431.68 after deregulation. The electricity industry in contrast to the remaining industries experienced decreased average fixed and incentive based salaries post deregulation. Average fixed salary decreased by circa $ 75.000, while the mean of bonuses decreased with almost $ 50.000 after deregulation. As mentioned earlier, in the electricity industry regulations are implemented depending on the companies’ structure, which may cause the deregulation effects on competition to not have the same impact on salaries throughout the industry.
V. Results
The results for fixed- and incentive based salary are shown in table 4 of the appendix. The first hypothesis, stating that incentive based salary increases after deregulation takes place, is tested by looking at the relationship found for the deregulation dummy variable, of models 2, 2a and 2b on bonuses. In order to provide evidence for the second hypothesis, which indicates an increase in fixed compensation, the coefficient of the deregulation dummy variable will be assessed in the regression run on fixed salaries in models 1,1a and 1b. For the interpretation of the coefficients it is best to use clustered standard errors for the regressions. All specifications are clustered over entities, which in this paper are the executives. This is because when errors are correlated with the regressors, the assumption E(uit|Xi1,….,XiT ) = 0 is violated. This is often the case when using panel data, because the variable of salary observed over the year for each entity is mostly related to its predecessor. When the size of the entities, N is large and the amount of years is small relative to N it is more useful to cluster over entities than over time. When analyzing the regressions on bonuses and salaries the significance will differ whether clustered errors or normal standard errors are used. Normal standard errors tend to underestimate the real standard errors, which results in higher t-values. This in turn will give very low p-values leading to easily rejecting the hypothesis that the coefficients
are statistically different from zero. The interpretation of the variable coefficients due to the dependent variable being in logarithmic form is analyzed by taking the exponential of the coefficient. If the coefficient found is between 0 and 1, the effect on the dependent variable can be analyzed by multiplying the coefficient with 100, which would give an approximation of the change in percentage terms. So a coefficient of 0.25 for the independent variable would indicate that when this variable increases by one, a 25% increase is found for the dependent variable, which in this research are the salaries of executives.
Fixed Salary
The results found for this dependent variable are summarized in table 4 of the appendix in model 1, 1a and 1b. Model 1a and 1b include a dummy deregulation variable in order to assess whether compensation increases are experienced after deregulation. This seems to be the case seeing as both models have a significant positive relationship for this variable. Afterwards the model is changed by taking the deregulation variable separately for each industry in model 1. These four variables are all found to have a p-value below 0.01, which implies that these coefficients are found to be significantly different from zero at the 1% level. For the telecom industry a 15.26% increase is experienced in the fixed component of pay after deregulation. The finance- and banking industry experience fixed salary increases of 16.33% and 8.38%, respectively. The only industry which experiences a decrease in fixed salary is the electricity industry. The reason here for can be explained in the way electricity companies are regulated according to the company’s structure. Single state companies tend to operate tightly under political pressure when it comes to compensation of executives, while multistate holding companies tend to lack clarity and conciseness in constraints on compensations (Joskow et al., 1993). Because this difference in legal structure is not corrected for it might explain why this industry experiences an opposite sign in the coefficient compared to the remaining industries. These findings thus largely support the first hypothesis stating that fixed pay will increase after deregulation.
When analyzing the interaction variable, which is the Herfindahl index multiplied with deregulation, the coefficient is significant for both models in which this variable is
analyzed (model 1b and model 1). The relationship found is negative, which is what is expected to be found in this paper. This negative relationship may seem confusing at first, but as mentioned previously, an increase in competition is shown by a decrease in the Herfindahl index. The interpretation is as follows; if a negative relationship is found between this interaction variable and fixed salary, the increases in salaries are found to be higher for firms which experience higher competitiveness increases after deregulation. This is in accordance with previous literature, which claims that market competition increases the salaries of executives after deregulation takes place. The Herfindahl index however, does not give explicit measurement of the increases in competitiveness, as explained earlier in chapter four; it merely gives an indication of the degree to which increases in competitiveness are observed. These findings on fixed salaries are observed to be inconsistent with the paper of Cuñat and Guadalupe (2009), who found that fixed components of salaries are compensated with the incentive based component when industries become more competitive. The fixed salaries are found to decrease by 61%, compared to the 21.72% increase in this paper, when deregulation was implemented in the banking industry in 1994. For the finance industry the authors found a negative change of 37% for fixed pay after implementation of deregulation, while in this paper these industries experience increases in fixed salary. Although the authors focus on the same sample as this paper the reason for the different findings can be due to the difference in the methodology used by the authors. The change in the components of salaries is measured differently when compared to this paper, they measure the percentage change as opposed to the level change of salary. They add firm performance as an explanatory variable of compensation, while in this paper firm performance is merely used as control variable. Furthermore the researchers use a control group, which did not undergo deregulation, as a benchmark. The findings of this study are however found to be in accordance with the study by Hubbard and Palia (2005), who found marginal increases for fixed salary components in the banking sector in the 80’s.
Incentive based pay
As for the regression run on bonuses in Model 2, 2a and 2b, which is displayed in table 4, the standard errors are observed to be much larger than for fixed salary. This makes sense
Comment [J13]: Still the different
result remains puzzling; what is mots reliable result?
intuitively, because some companies pay out zero in bonuses while others pay out very high bonuses, so the variation between entities is very high. When analyzing the dummy variables for deregulation the coefficient is found to be statistically significant in model 2a and 2b, implying a positive effect on incentive based salary after deregulation. This supports the first hypothesis, namely that incentive based pay increases after deregulation takes place. For model 2, which takes the deregulation variable separately for all variables, the only coefficients found to be significantly different from zero at the 1% level, is for the banking- and electricity industry. The increase in bonuses found is 43.11% for the banking industry. This finding is also in accordance with the research by Hubbard and Palia (1995) who found positive changes on the compensation of CEO’s when interstate banking was allowed. The authors observe a different period of deregulation than studied for in this paper, however the results found are consistent. The findings on executive compensation in this study are also in line with the paper of Joskow et al., (1993) which found that the compensation earned by executives of deregulated industries as opposed to regulated industries are higher. The coefficient on the electricity industry is again observed to be negative when analyzing bonuses. This can be due to the fact mentioned on how regulatory authorities of the electricity industry depend on the organizational structure of the firm. When analyzing the interaction variable of deregulation with the HHI, the relationship is also found to be negative as with fixed salaries, however the coefficient is not statistically different from zero in model 2. For model 2b however a negative and significant relationship is found. This negative relationship on the interaction variable indicates that higher salaries are experienced for firms with higher competitiveness after deregulation.
Control variables
For the control variables firm profitability, measured by net income and firm size, measured by total assets, a highly significant and positive relationship with fixed salary is found. This indicates that firm size and firm profitability have an effect on the increases in fixed salary components. These variables are also taken in logarithmic form and the findings suggest that firm size affects fixed salaries positively by 0.08% while for firm profitability the effect is also positive and found to be 0.12% for model 1. For the
regression on bonuses the results differ. Net income has a positive effect on salaries of 0.47%, while the effect of firm size is not found to be significant.
A. Impact of corporate governance
In order to provide evidence for the third hypothesis, stating that firms with weaker corporate governance might have higher salary increases, the 3rd and 4th models mentioned in the methodology are tested. These models are an extension of model 1 and 2, respectively with two added variables. One variable is added for the entrenchment level, the E-index and one interaction variable is added to analyze the entrenchment level in combination with deregulation. This E-index is used to assess whether weaker corporate governance can partly explain the increases found in executive compensation. The interaction variable will take deregulation into account, this variable will assess whether increases in salaries are found to be higher for firms with weaker corporate governance after deregulation, in accordance with the 3rd hypothesis. In table 4 the results found on the two extended models are displayed along with their restricted versions for comparison.
For the regression on fixed salary the deregulation dummy variable for the finance industry, in comparison to the restricted model, increases from 16.33% to 30.92%. For the banking industry the coefficient remains more or less of the same magnitude. For the telecom and electricity industry the coefficient is not statistically significant for the extended model. Regarding the interaction variable of deregulation and the HHI index, though the significance of the coefficient changes, it does remain negative. Regarding the E-index, a negative significant relationship is found when observed for the fixed component of salary. The coefficient found indicates that the fixed salary decreases with 5.6% when entrenchment levels increase by one. This relationship is significant at the 1% level. This is a surprising finding and is not in accordance with what is expected. Higher entrenchment levels indicate weaker corporate governance, which would be expected to be paired with salary increases. However, Kole and Lehn (1997) study the effect of deregulation on corporate governance for the airline industry and found that these governance structures tend to adapt to the changes in the business environment, namely competition. The authors claim that when deregulation takes place the role of managers,
Comment [J14]: Relate to relevant
literature; is this in line/against previous literature
increase and become more complex, due to the increased competitive environment. In order to mitigate this, corporate governance is likely to change and become stronger. The increased competitive environment also has its effects on compensation structures. Thus deregulation has two separate effects; an increase on compensation levels and improvement of corporate governance, both resulting because of the increased market competition. To analyze the sole effect on compensation of corporate governance in deregulation periods an interaction variable is taken of the E-index and deregulation. This interaction variable does show evidence for the third hypothesis with a positive sign for the coefficient. The finding for this variable implies that salary increases are found to be higher for firms with higher levels of entrenchment (weaker corporate governance) after deregulation.
For the 4th model measuring incentive based pay, the deregulation dummy variables are observed to be statistically different from zero at the 5% level for the banking and electricity industry, which is the same for model 1. The banking industry has a smaller but still positive effect on bonuses when compared to the restricted model, in accordance with the second hypothesis. The coefficient found for the electricity industry remains negative. Regarding the E-index variable for the 4th model, a negative coefficient of -0.32 is observed, indicating a 32% decrease in salaries if the entrenchment level is raised by one. To isolate the deregulation effect, the interaction variable of the E-index and deregulation is analyzed. The 4th model also shows a positive effect as found for the 3rd model of fixed salaries. Thus for the incentive based salary as well the coefficient indicates that higher salaries are observed for companies that have higher entrenchment levels (weaker corporate governance) after deregulation, in accordance with hypothesis 3.
Due to the changes in significance- and magnitudes of the coefficients when comparing the restricted- with the extended models, a likelihood ratio test is run in order to assess which model best explains the data. The null hypothesis in this test states that the coefficient of the added variables, the E-index and the E-index*deregulation, is zero
(Hypothesis likely-hood ratio test: H0: Ʊit=0 & Ɣit=0 and H1: Ʊit=0 ˅ Ɣit≠0). The null hypothesis is rejected for both models. This indicates that the model where the E-index and E-index*Deregulation is added as explanatory variable represents the data better than the restricted model, where this variable is left out. In other words the change
in the compensation of executives can partly be explained by the entrenchment level in a firm and the extended model is therefore more efficient. Leaving this variable out will cause omitted variable biases in the coefficients of the restricted models.
VI. Robustness Checks
A robustness check is performed in order to control for differences that might occur due to the executive being the CEO of the firm and for the amount of shares owned by the executives.
Joskow et al., (1993) Bryan et al., (2005) Cuñat and Guadalupe (2009) focus their research on compensation of CEOs as opposed to Peoples (2003) who studied managers of different levels. Executive compensation literature predicts that the gap between CEO compensation and compensation levels for other executives in the company have to be large in order to motivate other executives to compete for the position of CEO. If implementing more regulations in an industry will substantially reduce the scope of the CEOs actions, the difference in pay should become smaller. This means that when deregulation is introduced, the difference between executives’ pay and the CEO’s pay might become larger (Joskow et al., 1993). For this reason a robustness check will be performed in order to assess whether changes in executive compensation differ whether the executive is the CEO of the firm. The regression of the 3rd model will be extended with an interaction variable CEO*deregulation, where CEO takes on 1 when the executive is the CEO. The observations for these regressions are 1298 for fixed salary and 1155 for bonuses. For the regression on fixed salary displayed in table 5 (model 3a), the coefficient is found to be 0.4018 and statistically significant at the 1% level. As for the incentive based salary (model 4a) the variable has a positive coefficient of 0.5051 with 1% significance. This indicates that CEO’s salaries tend to increase more after deregulation than salaries of other executives. The salaries increase about 40% more for the fixed component and 50% more in bonuses than those of other executives.
Another factor that is taken into account is the amount of shares owned by the executive. A regression is run where this variable is added, to test whether an executive holding stock in the company receives a higher salary. However, it must be noted that this information is not available for many executives, which reduces the number of
observations substantially in the regression, which consequently reduces the explanatory power of the regression. The variable is observed in model 3b with 51 observations for fixed salary and model 4b with 46 observations for bonuses. A significant relationship is found for this variable in the regression run on bonuses, with a small positive coefficient. Indicating that executives who hold more stock in the company tend to earn marginally higher salaries. The coefficient for shares owned when run on fixed salary however, is found to be insignificant. This finding is partly in line with the study by Bryan et al., (2005) who found insignificant coefficients for the variable reflecting equity holdings by the CEO.
VII. Conclusion & Discussion
In this chapter a conclusion is provided for the findings on fixed salary and incentive based salary along with the concluding remarks for the evidence found for the hypotheses stated in this paper. Afterwards possible limitations of this study will be provided.
For fixed salary significant increases were found after the deregulation period for all industries, except for the electricity industry. This positive effect is in accordance with the findings of Hubbard and Palia (2005). The difference for the electricity industry can be explained by how regulatory authorities depend on the organizational structure of the company. The same is found for incentive based pay regarding the electricity industry. Furthermore for the incentive based salary, the banking industry is found to have a statistically significant positive effect on compensation after deregulation. The interaction variable of deregulation and HHI for both fixed and incentive based salary is found to be negative, indicating that salaries are found to be higher for companies who experience higher increased competitiveness after deregulation. These findings provide evidence for the first and second hypothesis, which state that deregulation increases incentive based- and fixed salary. For the extended models the regressions are shown to possess greater explanatory power, when running a likelihood ratio test. The E-index however is found to decrease when salary components increase; this is shown in the negative coefficient found for this variable in the extended models. These findings do not provide evidence
Comment [J15]:
Comment [J16]: Leave out, start
for the third hypothesis, this is because deregulation has two isolated effects; salaries are increased as a consequence of the increase in market competition and the latter also causes corporate governance to improve (Kole and Lehn, 1997). Thus, in order to provide evidence for the third hypothesis the interaction variable of E-index and deregulation must be taken and a positive relationship is found here for. This does provide evidence for the third hypothesis which states that salaries increase more for companies who have weaker corporate governance (higher entrenchment levels) after deregulation than firms with strong corporate governance. Lastly, a robustness check is run to assess whether the executive being a CEO or not has a different effect on salary increases after deregulation and whether the executive holds stock of the company produces higher salaries. The results partially resemble those of Bryan et al., (2005); the amount of stock held by the executive is shown to be positive and significant in explaining bonus increases, but is not significant for fixed salary. Furthermore, the CEO of the company tends to receive higher salary increases of about 40% for fixed salary and 50% for bonuses compared to other executives when deregulation takes place.
A. Limitations
There are several reasons why the findings of this paper may not be fully representative of the true movements in executive compensation in periods of deregulation. The first reason may be due to the fact that the compensation structure of executives is much more complex than salary and bonuses alone. Executives tend to earn part of their compensation in equity, stocks, option awards etc. The values of the options awarded furthermore can differ in the valuation method used. The components observed for this research are therefore limited observations of the total compensation packages received by executives. Joskow et al., (1993) found that when total compensation rather than bonus plus salary is taken as measure, the sensitivity to firm performance increases. This is due to long term performance compensation, for example option awards, being highly correlated with firm performance. The increase in competition among firms will also induce compensation structures to change from short term to long term performance incentives. Thus taking only salary and bonus as dependent variables for the regressions can provide shortcomings for this paper’s results.
Comment [J17]: Emphasize more
your contribution in relation to the existing literature
Another factor that may affect the representativeness of the data might be the fact that all executives are taken for in the sample and not only CEOs of firms. This is controlled for in a robustness check and found to be statistically significant in producing higher salary increases after deregulation when compared to other executives.
Furthermore the possibility of biases in the coefficients might occur because there is no differentiation made between firms who have the same executive throughout the sample period and firms who do not have the same executives throughout the entire sample period. The differences in individual characteristics that affect compensations of executives who may have entered the sample later or leave the sample before the last year observed, is not accounted for in this study. This is also not controlled for at firm level, so firms are not necessarily present during the entire sample period observed. This might have the effect of survivorship biases occurring. Omitted variable biases in the regression can be the case due to these variables not being taken into account.
Taking these above mentioned factors into account as variables has the disadvantage of decreasing the sample size considerably, for example when eliminating executives who leave the sample. Some variables are also not available in the first place. For this reason they were not controlled for in this study. In future studies, these factors can be added as variables into the regression to provide greater explanatory power of the results, provided that the data sample does not become too small and the data can be found.
VIII. References
Bai, G., & Elyasiani, E. (2013). Bank stability and managerial compensation. Journal of Banking & Finance, 37(3), 799-813.
Bebchuk, L. A., & Fried, J. M. (2003). Executive compensation as an agency problem (No. w9813). National Bureau of Economic Research.
Bryan, S., Hwang, L. S., & Lilien, S. (2005). CEO Compensation after Deregulation: The Case of Electric Utilities*. The Journal of Business, 78(5), 1709-1752.
Conyon, M. J. (1997). Corporate governance and executive compensation. International journal of industrial organization, 15(4), 493-509.
