Abstract: 020-0578

Executive Compensation and Corporate Financial Performance in Brazilian

Industrial Companies

Elizabeth Krauter

University of Sao Paulo

FEA-RP/USP

Av. dos Bandeirantes, 3900 Bloco B2 sala 23

14040-905 Ribeirao Preto / SP – Brazil

Telephone: 55 16 36023907

Fax: 55 11 38184023

Email: ekrauter@usp.br

Almir Ferreira de Sousa

University of Sao Paulo

FEA/USP

Av. Luciano Gualberto, 908 sala G120

05508-900 Sao Paulo / SP – Brazil

Telephone: 55 11 38184022

Fax: 55 11 38184023

Email: abrolhos@usp.br

POMS 22nd Annual Conference

Reno, Nevada, U.S.A.

April 29 to May 2, 2011

Executive Compensation and Corporate Financial Performance in Brazilian

Industrial Companies

Abstract

The objective of this paper is to investigate the relationship between executive

compensation and corporate financial performance. The research data are secondary and

the non-probabilistic sample is comprised of 44 Brazilian industrial companies. In order

to operationalize the independent compensation variable, we use average monthly

salary, average variable salary and three indexes that we created for this research –

benefits, career and development. These compensation data refer to the fiscal year of

2006. In order to operationalize the corporate financial performance, we use two

accounting indicators – growth of sales and ROE – for the fiscal years of 2006 and

2007. We use the size of the companies as a control variable. The results of multiple

regression analysis do not allow corroborating the hypothesis that there is a positive and

significant relationship between executive compensation and corporate financial

performance.

Key-words: executive compensation; financial performance

1. Introduction

Executive compensation is a complex and controversial subject that has attracted

attention from the media (CONYON, 2006) and from researchers in several areas

(CARLON; DOWNS; WEST-GRAY, 2006). Recently, the case of “million-dollar

bonuses” became news in main communication vehicles all over the world. Executives

received considerable sums as variable compensation, despite having contributed to the

crash of the companies they managed.

The most used approach in research about executive compensation is the principal-agent

theory (CONYON, 2006), or agency theory. According to this theory, the principal

(shareholder) hires an agent (executive) to execute a task in her/his favor, involving the

delegation of authority for making decisions. If the parties – shareholder and executive

– act in order to maximize their personal usefulness, there are reasons to believe that the

agent will not always act according to the shareholder’s best interests (JENSEN;

MECKLING, 1976). Since shareholders have imperfect control over their executives,

the compensation system is considered by many an efficient mechanism to align

interests and limit divergences (AGGARWAL; SAMWICK, 1999; DEVERS et al.,

2007; SHIM; LEE, 2003).

Researches that have studied the relationship between executive compensation and

corporate financial performance have used data from American corporation and have

focused on the American context (BÁLKIN; GÓMEZ-MEJIA, 1987; BARKEMA;

GÓMEZ-MEJIA, 1998). The results are divergent and non-conclusive (BÁLKIN;

GÓMEZ-MEJIA, 1987; BARKEMA; GÓMEZ-MEJIA, 1998). Some of the researches

have found weak relationships; others have observed non-significant relationships

between the variables (BARKEMA; GÓMEZ-MEJIA, 1998).

Despite of the considerable number of the researches conducted over the past few years,

there is little empiric evidence on the existence of a relationship between executive

compensation and corporate financial performance. For Barkema and Gómez-Mejia

(1998), the conduction of research in contexts different from the American may

contribute to better understand this topic.

The relevance and importance of the theme, the divergences found in results from

previous research of the same nature and the lack of studies in the context of the

Brazilian marketplace have motivated the conduction of this research. The objective is

to investigate the relationship between executive compensation and corporate financial

performance in the context of the Brazilian marketplace.

2. Literature review and hypothesis

2.1 Human Resources (HR) management and corporate performance

Over the past few years, several researchers have tried to understand the nature of the

relationship between HR management and corporate performance. They have looked

for evidence that HR management has positive impact in this context. Some of them

focused on several HR practices and verified their effect in several performance

measures (for example, GERHART; MILKOVICH, 1990; HAREL; TZAFRIR; 1999).

Others have examined the effect of HR practices systems – named “High Performance

Work Systems” – like Huselid (1995); Varma et al. (1999).

Delery and Doty (1996) have identified three perspectives to describe this relationship:

universal perspective, contingency perspective and configurational perspective. Alcázar,

Fernández and Gardey (2005) have proposed the inclusion of a fourth perspective.

Using the terminology presented by Brewster (1995), they have called it “contextual

perspective”.

The universal perspective represents the simplest approach for analysis of the

relationship between HR management and corporate performance (ALCÁZAR;

FERNÁNDEZ; GARDEY, 2005; BOSELIE; DIETZ; BOON, 2001; DELERY; DOTY,

1996). The relationship between the independent variable (HR practices) and the

dependent variable (corporate performance) is universal, and the same for the entire

population (DELERY; DOTY, 1996; YOUNDT et al., 1996). The main premises of this

perspective are:

a) There is linear relation between HR practices or systems and the company

performance (BOSELIE; DIETZ; BOON, 2001; DELERY; DOTY, 1996;

YOUNDT et al., 1996);

b) Some HR practices are better than others, and the use of such practices results in

better organizational performance. They are named “High Performance Work

Practices” or “best practices” (DELERY; DOTY, 1996);

c) The company performance is measured in terms of financial indicators, such as

profit, or by market share and sales level (BOSELIE; DIETZ; BOON, 2001).

The universal perspective does not consider synergy or integration of different HR

practices. Even when different practices are analyzed together, like in the High

Performance Work Systems model (BECKER; HUSELID, 1998; HUSELID, 1995), the

analysis is limited to an additive point of view (ALCÁZAR; FERNÁNDEZ; GARDEY,

2005). Additionally, there is no consensus among researchers concerning what the

“best” practice would be (YOUNDT et al., 1996).

The contingency perspective rejects the universal perspective’s linearity and includes

interactivity among variables. The relationship between independent variable and

dependent variable is not stable, and changes due to the presence of other variables,

named “contingency variables.” Thus, the influence of HR practices over corporate

performance is conditioned by other variables (ALCÁZAR; FERNÁNDEZ; GARDEY,

2005; DELERY; DOTY, 1996). According to Alcázar, Fernández and Gardey (2005),

contingential variables can be grouped into three categories:

a) Strategic variables: HR practices need to be consistent with the company’s

strategy to result in higher performance (DELERY; DOTY, 1996; YOUNDT et

al., 1996). According to Delery and Doty (1996), strategy is the contingency

variable most used in research.

b) Organizational variables: HR practices are conditioned by factors such as:

company size, technology, structure.

c) Environmental variables: HR practices cannot be formulated and implemented

without considering the context: competitive, technological, macroeconomic and

labor.

The configurational perspective is more complex than the two previous ones. It adopts a

systemic point of view, considers synergy and incorporates the principle of equifinality

(ALCÁZAR; FERNÁNDEZ; GARDEY, 2005; DELERY; DOTY, 1996). According to

this principle, a single goal can be achieved by using different paths and starting from

different initial conditions (CHIAVENATO, 2000).

This vision defines the HR system as a multidimensional set of different elements that

may be combined to form an infinite set of configurations (ALCÁZAR; FERNÁNDEZ;

GARDEY. 2005). Such configurations represent ideal types and, therefore, are not

phenomena observable empirically (DELERY; DOTY, 1996).

According to this perspective, in order for a company to achieve superior performance,

its HR practices need to have horizontal and vertical alignment. Horizontal alignment is

the internal consistency of HR practices from a company. Vertical alignment is the

congruency of HR practices with other organizational features – for example, with the

company’s strategy (ALCÁZAR; FERNÁNDEZ; GARDEY, 2005; DELERY; DOTY,

1996).

The contextual perspective was created to explain the European organizational context.

This perspective proposes the expansion of the concept of HR management to

encompass the company relations with government and unions. It also aims at

expanding the players involved in the formulation and implementation of HR

management, with the inclusion of stakeholders. Different from other perspectives, this

one adopts the social environment as analysis level (ALCÁZAR; FERNÁNDEZ;

GARDEY, 2005).

For the contextual perspective, HR management contributes to the success and long-

term survival of the company not only because it improves performance, but also for

helping to integrate and legitimate the company in its environment (ALCÁZAR;

FERNÁNDEZ; GARDEY, 2005).

2.2 Compensation and corporate performance

From all HR practices, compensation is considered crucial both for the company, for

being a relevant item in cost composition, and for people, because it symbolizes the

relative value of their work (DUTRA, 2002; SCHUSTER; ZINGHEIM, 1992).

The underlying assumption is that the compensation system may help to direct the

efforts of employees towards the business’ strategic purposes. When the compensation

system is structured appropriately, such process may contribute to enhance the corporate

performance (GÓMEZ-MEJIA; WELBOURNE, 1988).

The results of the researches that have studied the relationship between executive

compensation and corporate financial performance are divergent (BÁLKIN; GÓMEZ-

MEJIA, 1987; BARKEMA; GÓMEZ-MEJIA, 1998). Some have found weak

relationships; others have observed non-significant relationship between the variables

(BARKEMA; GÓMEZ-MEJIA, 1998). They have used data from American companies

and have focused on the American context (BÁLKIN; GÓMEZ-MEJIA, 1998).

Several of these researches have used fixed salary and variable salary to measure

compensation. Companies have, frequently, included non-financial compensation into

their compensation packages for executives (CARLON; DOWNS; WEST-GRAY,

2006) and such information has been ignored in many researches Non-financial

compensation encompasses: mechanisms for career planning and professional

development. Figure 1 presents the concept of compensation used in this research.

Figure 1 – The concept of compensation

Source: Prepared by the authors

Most of the researches have used only one accounting indicator to measure financial

performance. The performance was measured subjectively, from the respondent’s

perception (BECKER; GERHART, 1996).

These facts, along with the lack of research in the context of the Brazilian marketplace,

have led us to test the following hypothesis:

There is a positive and significant relationship between executive compensation and

corporate financial performance, in the context of the Brazilian marketplace.

3. Methodology

This research is descriptive and we use the quantitative method. According to the

classification proposed by Delery and Doty (1996) to describe the relationship between

RH management and corporate performance – presented on section 2.1 – this research

fits the universal perspective, because it starts from the premise that there is linear

relationship between compensation and corporate performance, and this relationship is

universal.

Financial compensation

Compensation

Non-financial compensation

Direct compensation

Indirect compensation

Variable salary

Benefits

Monthly salary

We use multiple regression analysis. It was used in previous researches as the

developed by Attaway (2000), Ozkan (2007). The sampling method used was non-

probabilistic. The sample is comprised of 44 industrial companies. We use SPSS 16.0

for Windows.

The data used on research is secondary. Information from independent variables and

from control variable was extracted from PROGEP (Programa de Estudos em Gestão de

Pessoas) database. Data from the dependent variables was extracted from FIPECAFI

(Fundação Instituto de Pesquisas Contábeis, Atuariais e Financeiras) database.

The information on compensation is from the fiscal year of 2006 and refers to

compensation received by directors, vice-presidents and presidents, herein named

“executives.” To operationalize compensation variable, we collected the following

information on PROGEP database:

a) Value of the average monthly salary of the executive in December 2006, in

Brazilian real;

b) Average sum received by the executive in 2006, in Brazilian real, as variable

compensation or bonus;

c) Access of executives to 12 benefits: healthcare plan, medical ambulatory in the

company facilities, dental plan, subside for purchasing medications, psychological

support, group life insurance, subside for education, subside for professional

specialization, subside for studying languages, support to children’s education,

subside for purchasing a home, and financing and loans.

d) Access of executives to 25 mechanisms for stimulating and supporting career, which

include: planning and tracking of professional development, encouragement and

support to career planning, repositioning of dismissed executives, internal

recruiting, information about career possibilities, and preparation for retirement.

e) Access of executives to 8 mechanisms to encourage education and professional

development: educational programs that incorporate the identification of critical

corporate and human competencies; multiple learning methods; programs that

reflect the company’s commitment to corporate citizenship; managers and leaders

involved with the learning process; programs to disseminate the organizational

culture; efficient systems for assessing investments in education and the results

achieved; sharing knowledge and exchanging experiences; partnerships with higher

education institutes.

As from this information about benefits, career, education and professional

development, we have been created 3 indexes: benefits, career and development. In the

database, such information is classified as:

No (= the company does not offer the item to its executives)

Partial (= the company offers the item to some of its executives)

All (= the company offers the item to all its executives)

To create such indexes, points from 0 to 2 have been attributed, as follows:

No = 0 point

Partial = 1 point

All = 2 points

To create the benefits index, which measures the access of the executives to 12 benefits,

2 points for each benefit offered by the company to all executives have been attributed;

1 point for each benefit conceded to some of its executives; 0 point for each benefit not

offered at all.

The points have been summed up, and the result corresponds to the organization’s

benefits index. The punctuation varies from 0 to 24, that is, the index of the company

that does not offer any of the 12 benefits to its executives is equals 0; the index of the

company that offers the 12 benefits to all of its executives is equals 24.

To create the career index, which measures the access of the executives to 25 career

support mechanisms, the same criterion of the previous index has been used. Two points

have been attributed for each career support mechanism offered by the company to all

of its executives; 1 point for each mechanism granted to part of its executives; 0 point

for each career support mechanism not offered.

The points have been summed up, and the result corresponds to the career index. The

index punctuation varies from 0 to 50. The index of the company that does not offer any

of the 25 career support mechanisms to its executives is equals 0. As for that company

that offers the 25 mechanisms to all of its executives, its index is equals 50.

To create the development index, which measures the access of the executives to 8

educational and professional development mechanisms, the same procedure of the

previous indexes has been used. Two points have been attributed for each educational

and professional development mechanism offered by the company to all of its

executives; 1 point for each mechanism granted to part of its executives; 0 point for

each mechanism not offered.

The points have been summed up, and the result corresponds to the development index.

The index punctuation varies from 0 to 16. The index of the company that does not offer

any of the 8 educational and professional development mechanisms to its executives is

equals 0. As for that company that offers the 8 mechanisms to all of its executives, its

index is equals 16. (The tables with PROGEP research questionnaire items and the

companies’ punctuation in the three indexes are not attached. They may be requested to

the authors).

To measure the financial performance of the companies, 2 accounting indicators are

used: sales growth and return on equity, of two fiscal years – 2006 and 2007. These

indicators are among the most used ones for empiric researches (CARTON; HOFER,

2006; LEE; HALL; RUTHERFORD, 2003).

The control variable has been selected based on the possible influence that it exercises

upon the dependent and independent variables. Literature highlights that the company

size is an important factor. In this work, the size is represented by the number of

employees in 2006 – Terpstra and Rozell research (1993) used the number of employees

as control variable. Due to the great variation in the number of employees among the

sampled companies, we have opted by the variable transformation. This way, the natural

logarithm of the number of employees is used to measure the sampled organizations

size.

The sector of actuation is another variable of control very used in the researches. In the

case of this study, the sampled companies belong to 14 different sectors, and the

number of companies in each area is small. Thus, we have opted by not using the sector

as control variable.

4. Results

According to the criterion adopted by PROGEP to classify the organizations regarding

the size, 9 (20.5%) are small-sized (they have between 100 and 500 employees); 14

(31.8%) are medium-sized (they have between 501 and 1500 employees); and 21

(47.7%) are large-sized (they have more than 1500 employees).

Table 1 shows the descriptive measures of the three indexes. The mean value of benefits

index was 16.23 points; with 50% of the companies presenting values equals or lower

than 16 points. The index value varied from a minimum of 9 and a maximum of 24

points.

The career index presented mean value of 22.80 points, oscillating between 2 and 48.

Fifty percent of the companies presented value equals or lower than 22.50 points.

Bearing in mind that the maximum punctuation for this index is 50, we conclude that

there is little stimulus and support for professional growth of the executives. We stress

out that the career offered by the company is an item that is quite valorized by these

professionals (FIA, 2007). Thus, it is a background that suggests important

opportunities to be developed by the organizations.

The development index presented mean value of 11.50 points, varying from 0 to 16.

Fifty percent of the companies indicated spectrum equals or lower than 12 points. The

researched organizations differ a lot with regard to this data. While some of them do not

offer any educational and professional development support mechanism, others provide

the 8 mechanisms to all of its executives.

Table 1 – Descriptive statistics of the indexes

n Mean Median Standard-

deviation Minimum Maximum

Benefits index 44 16.23 16.00 3.15 9 24 Career index 44 22.80 22.50 10.87 2 48 Development index 44 11.50 12.00 4.45 0 16

From PROGEP database, information on average monthly salary and average variable

salary earned by the executives in 2006 was also extracted. The mean of the average

monthly salary was R$ 27,000.40, varying between R$ 10,012.00 and R$ 52,000.00. As

for the mean of the average variable salary was R$ 141,767.47 in the year of 2006,

which is equivalent to approximately R$ 11,813.96 a month. Some companies do not

pay variable salary to its executives, because of this, the minimum value corresponds to

zero. Table 2 shows the descriptive measures of such information.

Table 2 – Average salary of executives in 2006

n Mean Median Standard-

deviation Minimum Maximum

Average monthly salary (in Brazilian real) 44 27,000.40 25,738.21 8,914.11 10,012.00 52,000.00 Average variable salary (in Brazilian real) 44 141,767.47 107,086.95 136,590.00 0.00 480,700.00

Table 3 shows the descriptive measures of accounting indicators. The sales growth of

2006 presented mean of 5.12%, varying from –19.1% to 34.8%. The return on equity

(ROE) of 2006 presented mean of 18.51%, oscillating between –44.8% and 57.7%. The

sales growth mean value of 2007 was 4.96%, varying from –35.4% to 66%. The mean

of the ROE in 2007 was 16.67%, varying from –23.8% to 54.6%.

Table 3 – Descriptive statistics of accounting indicators

n Mean Median Standard-

deviation Mimimum Maximum

Sales growth 2006 (%) 44 5.12 3.50 11.02 -19.1 34.8 ROE 2006 (%) 44 18.51 17.75 17.53 -44.8 57.7 Sales growth 2007 (%) 44 4.96 4.30 17.63 -35.4 66.0 ROE 2007 (%) 44 16.67 14.75 13.98 -23.8 54.6

We use the size as a control variable. The size is represented by the number of

employees in 2006. As the variable had great variation, from a minimum of 131 to a

maximum of 20,228 employees, we have opted by the variable transformation. We used

the natural logarithm (ln) of the number of employees. Table 4 exposes the descriptive

measures before and after the transformation. Table 5 shows the variables acronyms

used in the statistical tests.

Table 4 – Descriptive statistics of control variable

n Mean Median Standard-

deviation Mimimum Maximum

Number of employees 44 3,194.68 1,359 4,097.92 131 20,228 Size (ln number of employees) 44 7.40 7.21 1.21 4.88 9.91

Table 5 – Variables acronyms

Variable name Acronyms

Average monthly salary salmen Average varible salary salvar Benefits index ibenef Career index icarr Development index idesen Sales growth – 2006 cven06 Return on equity – 2006 roe06 Sales growth – 2007 cven07 Return on equity – 2007 roe07 Size size

To test the hypothesis that there is a positive and significant relationship between

executive compensation and corporate financial performance, we use linear regression

analysis. We use, simultaneously, all compensation variables as independent variable;

the financial performance variables, alternately, as dependent variable; size as control

variable. We use this general model of multiple regression:

DFi = β0 + β1 salmeni + β2 salvari + β3 ibenefi + β4 icarri + β5 ideseni + β6 sizei + µi

Where: i represents the ith company; DF represents financial performance variables

(cven06, roe06, cven07, roe07); µ = error term.

Table 6 shows the results of the multiple regression, estimated with the least square

method (LSM), with “cven06” as dependent variable. The value of R2 indicates that

19.3% of the variation in “cven06” is explained by the set of variables in the regression.

The model presents R2 adjusted of 6.2%. The Sig. (p-value) of F test, equals 0.213

(higher than 10%) does not allow rejecting the null hypothesis, which is R2 equals zero.

Sig. t analysis indicates that only “ibenef” and “icarr” variable coefficients are

significant; “icarr” coefficient presents negative sign.

Table 6 – Results of multiple regression model – cven06

Independent

variables

Standardized

coefficients

t Sig. t

constant 0.090 0.929 size -0.105 -0.540 0.592 salmen 0.030 0.150 0.882 salvar 0.283 1.146 0.259 ibenef 0.290 1.870 0.069 icarr -0.374 -2.276 0.029 idesen -0.043 -0.262 0.795 R

2 = 0.193

R2 adjusted = 0.062

Sig. F = 0.213 n = 44

Table 7 – Results of multiple regression model – roe06

Independent

variables

Standardized

coefficients

t Sig. t

constant 1.873 0.069 size -0.283 -1.483 0.146 salmen -0.005 -0.024 0.981 salvar 0.332 1.368 0.180 ibenef 0.202 1.328 0.192 icarr -0.295 -1.833 0.075 idesen -0.197 -1.222 0.229 R

2 = 0.223

R2 adjusted = 0.097

Sig. F = 0.132 n = 44

Table 7 shows the results of the multiple regression, estimated with the least square

method, with “roe06” as dependent variable. The value of R2 indicates that 22.3% of the

variation in “roe06” is explained by the set of variables in the regression. The model

presents R2 adjusted of 9.7%. The Sig. of F test, equals 0.132 (higher than 10%) does

not allow rejecting the null hypothesis, which is R2 equals zero. Sig. t analysis indicates

that only “icarr” variable coefficient and constant are significant; “icarr” coefficient

presents negative sign.

Table 8 – Results of multiple regression model – cven07

Independent

variables

Standardized

coefficients

t Sig. t

constant -0.870 0.390 size 0.348 1.689 0.100 salmen 0.172 0.819 0.418 salvar -0.248 -0.946 0.350 ibenef -0.097 -0.591 0.558 icarr 0.034 0.194 0.847 idesen -0.160 -0.922 0.363 R

2 = 0.094

R2 adjusted = -0.053

Sig. F = 0.697 n = 44

Table 8 shows the results of the multiple regression, estimated with the least square

method, with “cven07” as dependent variable. The value of R2 indicates that 9.4% of

the variation in “cven07” is explained by the set of variables in the regression. The

model presents R2 adjusted negative and equals 5.3%. The Sig. of F test, equals 0.697

(higher than 10%) does not allow rejecting the null hypothesis, which is R2 equals zero.

Sig. t analysis indicates that only “size” variable coefficient is significant.

Table 9 shows the results of the multiple regression, estimated with the least square

method, with “roe07” as dependent variable. The value of R2 indicates that 9.7% of the

variation in “roe07” is explained by the set of variables in the regression. The model

presents R2 adjusted negative and equals 4.9%. The Sig. of F test, equals 0.680 (higher

than 10%) does not allow rejecting the null hypothesis, which is R2 equals zero. Sig. t

analysis indicates that no coefficient is significant.

Table 9 – Results of multiple regression model – roe07

Independent

variables

Standardized

coefficients

t Sig. t

constant 0.662 0.512 size -0.025 -0.123 0.903 salmen 0.126 0.597 0.554 salvar 0.065 0.249 0.805 ibenef 0.152 0.926 0.361 icarr -0.211 -1.214 0.232 idesen -0.160 -0.923 0.362 R

2 = 0.097

R2 ajustado = -0.049

Sig. F = 0.680 n = 44

Therefore, the 6 models tested do not present any statistical significance. The Sig. of the

F test was higher than 10%, in all models, not allowing to reject H0, R2 is equals zero.

The 6 models comply with all requirements of the multiple regression analysis. The

residual normality assumption was reached by using the Kolmogorov-Smirnov test. The

homoscedasticity of residues was verified by means of the Pesarán-Pesarán test. The

absence of serial autocorrelation in the residues was verified by means of Durbin-

Watson test. The multicollinearity exam among independent variables was made by the

VIF measurement (Variance Inflation Factor).

The results of multiple linear regression analysis did not allow corroborating the

hypothesis that there is a positive and significant relationship between executive

compensation and corporate financial performance, in the context of the Brazilian

marketplace. These results are compatible with the results of others researches

developed in other context which did not corroborate the relationship between the

variables.

5. Conclusion

The objective of this research is to investigate the relationship between executive

compensation and corporate financial performance. The non-probabilistic sample is

comprised of 44 industrial companies.

This research is different from previous one for producing broader concepts to

operationalize the variables. Previous one has used fixed salary and variable salary to

operationalize compensation variable. We use direct compensation (monthly salary +

variable salary) and three indexes that we created – benefits, career and development.

The benefits index measures the access of executives to 12 benefits; the career index

measures the access to 25 career support mechanisms; the development index measures

the access to 8 professional development mechanisms. Moreover, we use two

accounting indicators for two fiscal years, and they were extracted from FIPECAFI

database. Several of previous researches adopted only one accounting indicator to

measure financial performance and the performance was measured subjectively, from

the respondent’s perception.

The results of multiple regression analysis did not allow corroborating the hypothesis

that there is a positive and significant relationship between executive compensation and

corporate financial performance in the context of the Brazilian marketplace. We

expected that the utilization of an approach other than that used in previous researches –

creation of three indexes, use of two accounting indicators of two fiscal years – would

enable corroborating the hypothesis. However, such expectation has not been

confirmed.

The main contributions of this research are in: expanding the existing knowledge on the

relationship between executive compensation and corporate financial performance;

studying this relationship in the context of the Brazilian marketplace; and providing

subsidies for companies to enhance their compensation systems.

This research has some limitations. The sampling method used to select the companies

is non-probabilistic. Thus, it is not possible to generalize the results found for the

population. Another limitation is the size of the sample. Due to the difficulty to obtain,

in Brazil, the corporate accounting data, the sample is comprised of 44 companies.

Additionally, the utilization of accounting information can be a limiter, because it is

subject to manipulation.

This research has adopted the universal perspective to investigate the relationship

between executive compensation and corporate financial performance. According to this

perspective, this relationship is linear and universal. New researches can be developed

using others perspectives.

In spite of these limitations, the results are important for the discussion on the

relationship between executive compensation and corporate financial performance.

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