The effect of CEO characteristics on executive compensation

Azevedo, Francisco Gleisson Paiva; Soares, Rodrigo Oliveira

doi:10.1590/1808-057x20252189.en

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Original Article • Rev. contab. finanç. 36 (99) • 2025 • https://doi.org/10.1590/1808-057x20252189.en linkcopy

The effect of CEO characteristics on executive compensation

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The aim of this research was to investigate the relation between the characteristics of Chief Executive Officers (CEOs) and the executive compensation of Brazilian companies listed on the stock exchange. The Upper Echelons Theory (Hambrick, 2007) already pointed to a possible combined effect between characteristics and executive compensation. In Brazil, this relation became feasible only with the disclosure requirement established by the Securities and Exchange Commission of Brazil (CVM) Instruction No. 480/2009. Thus, this research contributes to theory and Brazilian literature by exploring this relation. The findings are relevant because they highlight potential criteria used by companies in determining CEO salaries and contribute to explaining variations in executive compensation. Additionally, they provide empirical evidence on which executive characteristics are valued and better compensated in an emerging market. The findings have practical and theoretical implications. For companies, they guide salary policies by showing which characteristics of CEOs influence compensation, aligning incentives with organizational strategy. For academia, they shed light on the determinants of compensation. In the Brazilian context, they reveal how the attributes of CEOs affect their compensation, contributing to an understanding of the impact of executives on organizations. To analyze the models, we used the Generalized Method of Moments (GMM-Sys). Specific attributes of CEOs influence compensation. Education aligned with the business leads to an increase in total compensation, age influences fixed compensation, and duality influences variable compensation. On the other hand, family ties reduce variable compensation, and gender seems to be irrelevant. The results contribute by highlighting these characteristics as determinants of compensation and by showing the combined effect between characteristics and executives' total, fixed, and variable compensation.

Keywords:
executive compensation; characteristics of CEOs; Upper Echelons Theory

Sector	Number of companies	Number of observations
Industrial goods	47	447
Communications	7	38
Cyclical consumption	81	737
Non-cyclical consumption	26	197
Basic materials	31	257
Oil, gas and biofuels	10	94
Health	20	162
Information technology	12	56
Public utility	38	409
Total	272	2,397

Variable	Acronym	Measurement	Hypothesis	Expected relation	Authors
Business education	FA	Dummy: 1, if the CEO has an undergraduate or postgraduate degree in administration, accounting, finance, or economics; 0, otherwise.	H1	+	Hambrick and Mason (1984); Custódio and Metzger (2014); Gupta and Mahakud (2020).
Age of the CEO	AGE	CEO's age in years.	H2	+	Custódio and Metzger (2014); Schmid and Baldermann (2021); Oliveira et al. (2021).
CEO's gender	GEN	Dummy: 1, if the CEO is female; 0, if the CEO is male.	H3	+	Lam et al. (2013); Kaur and Singh (2019); Schmid and Baldermann (2021); Mueller et al. (2021); Oliveira et al. (2021).
Duality	DUA	Dummy: 1, if the CEO is chairman of the board of directors; 0, otherwise.	H4	+	Conyon et al. (2019); Jbir et al. (2021); Ding et al. (2022); Machado et al. (2023); Dutra and Ceretta (2023).
Family CEO	CEOFAM	Dummy: 1, if the CEO is a founder, heir, or belongs to the founding family; 0, otherwise.	H5	+	Sánchez-Marín et al. (2020); Graziano and Rondi (2021); Chen et al. (2021).

Variable	Acronym	Description	Measurement	Sign	Authors
Company size	SIZE	Represented by the size of the company's total assets.	Natural logarithm (Ln) of total assets.	+	Lam et al. (2013); Kaur and Singh (2019); Ghardallou et al. (2020); Zhou et al. (2021).
Business performance	ROA	It shows how much profit you can generate in relation to your assets.	LAJIR/Total asset value.	+	Custódio & Metzger (2014); Conyon et al. (2019); Rissatti et al. (2019); Jbir et al. (2021); Zhou et al. (2021); Ding et al. (2022); Choi et al. (2022); Machado et al. (2023).
Business performance	Tobin's Q (TQ)	Used to measure the company's market performance.	Market value of shares/Total asset value	+
Indebtedness	IND	This refers to the amount of company debt in relation to total assets.	Total liabilities/Total assets	+/-	Conyon et al. (2019); Ding et al. (2022); Machado et al. (2023); Dutra & Ceretta (2023).
Age of the company	AGECOMP	Time in years since the company was founded.	Measured in years from its foundation.	+/-	Abed et al. (2014); Serra et al. (2016); Setiawan and Gestanti (2022).
Control defined	CONT	Concentration of control of shares of 50% or more in the hands of a single shareholder.	Dummy: 1, if the company has a controlling shareholder; 0, otherwise.	-	Rissatti et al. (2019); Freitas et al. (2020); Peng and Tan (2023).
Pandemic	PAN	Covid-19 pandemic period, considering the years 2020 and 2021.	Dummy: 1, pandemic period; 0, otherwise.	-	Proposed in the study.
The company's sector of activity	SEC	The economic sector in which the company operates.	Dummy: 1, for the company's sector; 0, otherwise.	+	Lam et al. (2013); Falato et al. (2015); Aguiar & Pimentel (2017).

Panel A - CEO compensation
Variable	Mean	Standard deviation	Minimum	Maximum
RM (R$)	3,996,506.83	6,593,073.06	10,067.20	83,846,204.40
Ln_RM	14.3113	1.5205	9.8782	17.2660
RMED (R$)	2,221,737.45	3,019,722.31	7,500.00	40,061,820.52
Ln_RMED	13.9186	1.3580	9.9522	16.4558
RF (R$)	1,092,835.61	942,073.56	10,800.00	14,973,432.67
Ln_RF	13.6017	0.8660	9.2873	16.5218
RV (R$)	1,725,213.67	2,620,958.05	1,735.00	36,581,437.75
Ln_RV	13.5108	1.5094	8.5106	16.3764
Panel B - Characteristics of CEOs
Variable	Mean	Standard deviation	Minimum	Maximum
Age of the CEO	53.4864	9.5988	25.0000	91.0000
Dummy variables		Observations	Frequency
Business education		1,573	65,62%
Gender		57	2,38%
Duality		292	12,18%
Family CEO		603	25,16%
Panel C - Company characteristics
Variable	Mean	Standard deviation	Minimum	Maximum
Size	21.7816	1.8256	17.4057	25.9613
ROA	0.0507	0.1695	-0.5712	0.3971
TQ	0.7595	0.8970	0.0096	8.0244
Indebtedness	0.7273	0.5796	0.1011	3.3234
Age of the company	42.5428	27.4101	0.0000	131.0000
Dummy variables		Observations	Frequency
Control defined		1,649	68,79%
Pandemic		463	19,32%

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)
(1)Ln_RM	1.000
(2)Ln_RMED	0.957	1.000
(3)FA	0.053	0.044	1.000
(4)AGE	-0.081	-0.085	-0.190	1.000
(5)GEN	-0.082	-0.070	-0.031	-0.070	1.000
(6)DUA	-0.139	-0.133	-0.029	0.200	0.034	1.000
(7)CEOFAM	-0.046	-0.047	-0.109	-0.013	0.029	0.169	1.000
(8)SIZE	0.580	0.578	-0.016	-0.044	0.022	-0.159	-0.181	1.000
(9)ROA	0.141	0.126	-0.019	0.079	0.042	0.048	0.059	0.166	1.000
(10)TQ	0.067	0.049	-0.103	-0.036	-0.015	-0.019	0.046	-0.035	0.250	1.000
(11)IND	-0.176	-0.168	0.134	-0.008	0.042	0.104	-0.080	-0.200	-0.306	-0.248	1.000
(12)AGECOMP	-0.180	-0.177	0.084	0.219	0.045	0.160	-0.057	-0.222	0.037	-0.088	0.137	1.000
(13)CONT	-0.195	-0.187	-0.014	0.032	0.064	0.055	0.002	0.035	0.107	-0.013	0.044	-0.018	1.000
(14)PAN	0.108	0.099	0.067	-0.041	0.000	-0.043	-0.030	0.102	0.040	0.068	0.048	-0.006	0.013	1.000

Variables	RM						RMED
	Hypothesis 1	Hypothesis 2	Hypothesis 3	Hypothesis 4	Hypothesis 5	General model	Hypothesis 1	Hypothesis 2	Hypothesis 3	Hypothesis 4	Hypothesis 5	General model
	(1)	(2)	(3)	(4)	(5)	(6)	(1)	(2)	(3)	(4)	(5)	(6)
RM	0.620***	0.623***	0.628***	0.623***	0.624***	0.623***	0.541***	0.537***	0.543***	0.540***	0.541***	0.540***
RMED _t-1	(9.988)	(10.081)	(10.268)	(10.106)	(10.108)	(10.056)	(7.158)	(7.059)	(7.241)	(7.214)	(7.172)	(7.110)
FA	0.072					0.067	0,090*					0,083*
FA	(1,465)					(1,333)	(1,938)					(1,742)
AGE		-0.001				-0.000		-0.003				-0.002
AGE		(-0,560)				(-0,204)		(-1,245)				(-0,763)
GEN			-0.154			-0.149			-0.050			-0.060
GEN			(-1,161)			(-1,096)			(-0,427)			(-0,519)
DUA				-0.073		-0.070				-0.064		-0.056
DUA				(-0,954)		(-0,929)				(-0,905)		(-0,829)
CEOFAM					0.024	0.045					0.024	0.044
CEOFAM					(0,376)	(0,703)					(0,367)	(0,673)
SIZE	0,215***	0,212***	0,210***	0,211***	0,212***	0,213***	0,233***	0,234***	0,230***	0,232***	0,233***	0,234***
SIZE	(5,492)	(5,444)	(5,485)	(5,443)	(5,466)	(5,533)	(5.729)	(5,757)	(5,724)	(5,743)	(5,775)	(5,776)
ROA	0,328*	0,353*	0,362*	0,371**	0,346*	0,347*	0.242	0.271	0.276	0.282	0.262	0.259
ROA	(1,718)	(1,865)	(1,957)	(1,965)	(1,828)	(1,853)	(1,329)	(1,502)	(1,560)	(1,578)	(1,454)	(1,446)
TQ	0,060*	0,058*	0,058*	0,059*	0,059*	0,061**	0.056	0.052	0.053	0.053	0.054	0.056
TQ	(1,920)	(1,852)	(1,844)	(1,869)	(1,899)	(2,018)	(1,520)	(1,434)	(1,452)	(1,446)	(1,487)	(1,577)
IND	-0.028	-0.019	-0.016	-0.014	-0.017	-0.017	-0.028	-0.018	-0.014	-0.014	-0.015	-0.020
IND	(-0.468)	(-0,318)	(-0,282)	(-0.242)	(-0,291)	(-0,303)	(-0,459)	(-0,300)	(-0,228)	(-0,227)	(-0,251)	(-0,325)
AGECOMP	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001	-0.001
AGECOMP	(-1,396)	(-1,270)	(-1,263)	(-1,223)	(-1,305)	(-1,138)	(-1,303)	(-1,096)	(-1,206)	(-1,115)	(-1,191)	(-1,030)
CONT	-0,193***	-0,196***	-0,193***	-0,191***	-0,198***	-0,188***	-0,187***	-0,194***	-0,192***	-0,188***	-0,194***	-0,188***
CONT	(-3,075)	(-3,107)	(-3,097)	(-3,041)	(-3,096)	(-3,018)	(-2,731)	(-2,812)	(-2,786)	(-2,740)	(-2,800)	(-2,718)
PAN	0,125**	0.112	0,133**	0,126**	0,152*	0.102	0.001	0.013	0.016	0.010	0.017	0.110
PAN	(1,990)	(1,342)	(2,139)	(1,980)	(1,809)	(1,200)	(0,019)	(0,208)	(0,256)	(0,148)	(0,266)	(1,572)
Time	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Sector	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Constant	0.783	0.860	0.807	0.851	0.785	0.778	1,544***	1,723***	1,579***	1,600***	1,542**	1,596***
Constant	(1,371)	(1,495)	(1,427)	(1,481)	(1,371)	(1,363)	(2,614)	(2,841)	(2,663)	(2,704)	(2,559)	(2,601)
Observations	2,124	2,124	2,124	2,124	2,124	2,124	2,124	2,124	2,124	2,124	2,124	2,124
Companies	272	272	272	272	272	272	272	272	272	272	272	272
Instruments	39	39	39	39	39	43	39	39	39	39	39	43
Prob>F	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
AR (1)	-6,998***	-6,997***	-7,004***	-7,021***	-7,015***	-7,018***	-7,352***	-7,304***	-7,339***	-7,343***	-7,340***	-7,348***
AR (2)	0.416	0.426	0.415	0.423	0.431	0.402	0.245	0.253	0.258	0.248	0.261	0.234
Hansen	0.391	0.343	0.312	0.332	0.328	0.362	0.215	0.181	0.160	0.170	0.261	0.213

Variables	RF						RV
	Hypothesis 1	Hypothesis 2	Hypothesis 3	Hypothesis 4	Hypothesis 5	General model	Hypothesis 1	Hypothesis 2	Hypothesis 3	Hypothesis 4	Hypothesis 5	General model
	(1)	(2)	(3)	(4)	(5)	(6)	(1)	(2)	(3)	(4)	(5)	(6)
RF/RV _t-1	0.520***	0.516***	0.519***	0.523***	0.520***	0.515***	0.330***	0.326***	0.326***	0.322***	0.326***	0.327***
RF/RV _t-1	(8.766)	(8.812)	(8.664)	(8.754)	(8.772)	(8.621)	(5.476)	(5.413)	(5.428)	(5.400)	(5.461)	(5.512)
FA	0,019					0,031	0,098					0,086
FA	(0,707)					(1,087)	(1,411)					(1,202)
AGE		0,003**				0,003**		-0,001				0,000
AGE		(2,219)				(2,287)		(-0,242)				(0,046)
GEN			-0,049			-0,032			0,044			0,048
GEN			(-0,546)			(-0,362)			(0,187)			(0,201)
DUA				0,022		0,012				0,179*		0,179*
DUA				(0,695)		(0,346)				(1,756)		(1,756)
CEOFAM					0,001	-0,001					-0,231**	-0,237**
CEOFAM					(0,042)	(-0,020)					(-2,216)	(-2,200)
SIZE	0,124***	0,126***	0,123***	0,123***	0,123***	0,126***	0,256***	0,257***	0,256***	0,259***	0,252***	0,257***
SIZE	(5,979)	(6,156)	(5,852)	(5,961)	(5,979)	(5,998)	(5,729)	(5,742)	(5,731)	(5,849)	(5,799)	(5,967)
ROA	-0,049	-0,052	-0,038	-0,049	-0,044	-0,051	1,109***	1,160***	1,163***	1,156***	1,233***	1,174***
ROA	(-0,367)	(-0,398)	(-0,292)	(-0,376)	(-0,336)	(-0,395)	(2,861)	(3,039)	(3,050)	(3,025)	(3,251)	(3,038)
TQ	0,021	0,021	0,020	0,020	0,020	0,022	0,195***	0,189***	0,189***	0,192***	0,183***	0,192***
TQ	(0,979)	(0,996)	(0,945)	(0,944)	(0,966)	(1,009)	(3,458)	(3,410)	(3,408)	(3,474)	(3,321)	(3,454)
IND	-0,027	-0,023	-0,023	-0,027	-0,024	-0,025	0,296*	0,315*	0,315*	0,323*	0,298*	0,291*
IND	(-0,622)	(-0,548)	(-0,542)	(-0,625)	(-0,572)	(-0,576)	(1,651)	(1,757)	(1,755)	(1,791)	(1,682)	(1,657)
AGECOMP	-0,001	-0,001*	-0,001	-0,001	-0,001	-0,001*	-0,008***	-0,008***	-0,008***	-0,008***	-0,008***	-0,008***
AGECOMP	(-1,489)	(-1,703)	(-1,427)	(-1,498)	(-1,442)	(-1,790)	(-3,923)	(-3,896)	(-3,935)	(-4,033)	(-4,060)	(-4,287)
CONT	-0,020	-0,023	-0,022	-0,022	-0,021	-0,024	-0,211**	-0,220**	-0,222***	-0,229***	-0,204**	-0,206**
CONT	(-0,468)	(-0,528)	(-0,501)	(-0,505)	(-0,488)	(-0,545)	(-2,425)	(-2,551)	(-2,582)	(-2,651)	(-2,376)	(-2,390)
PAN	0,015	0,017	0,016	0,016	0,016	0,015	0,644***	0,451***	0,453***	0,469***	0,651***	0,450***
PAN	(0,573)	(0,660)	(0,608)	(0,626)	(0,601)	(0,586)	(5,825)	(4,018)	(4,027)	(4,176)	(5,916)	(3,989)
Time	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Sector	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Constant	4,025***	3,889***	4,043***	3,995***	4,026***	3,886***	3,305***	3,435***	3,398***	3,335***	3,496***	3,293***
Constant	(6.790)	(6.546)	(6.862)	(6.691)	(6.676)	(6.416)	(3.059)	(3.185)	(3.172)	(3.088)	(3.244)	(3.010)
Observations	2,114	2,114	2,114	2,114	2,114	2,114	1,501	1,501	1,501	1,501	1,501	1,501
Companies	272	272	272	272	272	272	234	234	234	234	234	234
Instruments	38	38	38	38	38	42	39	39	39	39	39	43
Prob>F	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
AR (1)	-5,126***	-5,127***	-5,135***	-5,144***	-5,139***	-5,116***	-6,497***	-6,472***	-6,468***	-6,460***	-6,512***	-6,508***
AR (2)	0.272	0.269	0.272	0.271	0.272	0.270	0.209	0.223	0.222	0.234	0.208	0.210
Hansen	0.199	0.188	0.193	0.201	0.198	0.185	0.321	0.291	0.289	0.276	0.306	0.319

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Universidade de São Paulo, Faculdade de Economia, Administração, Contabilidade e Atuária, Departamento de Contabilidade e Atuária - Cidade Universitária Avenida: Professor Luciano Gualberto, 908 - FEA 3 - sala 118, CEP: 05508-010, Telefone: (+55 11) 2648-6320 - São Paulo - SP - Brazil
E-mail: recont@usp.br

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