Can remote voting mitigate agency problems?¹

O voto remoto pode mitigar os problemas de agência?

ABSTRACT

Purpose:

Board members are critical in resolving agency conflicts. How- ever, many are unable to perform their function due to their distance, as they are not present at board meetings. As of Instruction no. 561, the Brazilian Securities and Exchange Commission (CVM) regulated remote voting for Boards of Directors, allowing for greater attendance at meet- ings and, as a result, increased involvement. In this context, this research examines the effect of remote voting by Boards of Directors on execu- tive compensation and financial performance of publicly traded firms in Brazil.

Originality/value:

This research is innovative in the sense that it exam- ines the effect of the Board of Directors remote voting on the CEO com- pensation and financial performance of the firm, using an innovative methodology.

Design/methodology/approach:

We applied a quasi-experimental method (difference-in-differences) to assess the effects of a given group (treat- ment) before and after the event, significantly reducing endogeneity when considering an exogenous shock to the system.

Findings:

As a result, the estimation of the main model reveals statisti- cally significant differences between the effects of treatment and control on profitability and executive remuneration, indicating that remote vot- ing mitigated agency problems by generating a substitution effect for explicit incentives (as evidenced by the decrease in executive remunera- tion) and by providing greater accounting performance for companies.

Keywords:
financial performance; executive compensation; differ- ence-in-differences; remote voting; board of directors

RESUMO

Objetivo:

Os membros do conselho são essenciais na resolução de con- flitos de agência. Entretanto, muitos estão impossibilitados de exercer sua função devido à distância, não participando das reuniões do conse- lho. A partir da Instrução nº 561, a Comissão de Valores Mobiliários (CVM) regulamentou o voto a distância para os Conselhos de Adminis- tração, permitindo maior participação e maior envolvimento. Nesse contexto, esta pesquisa examina o efeito do voto remoto dos conselhos de administração na remuneração dos executivos e no desempenho financeiro das empresas de capital aberto no Brasil.

Originalidade/valor:

Esta pesquisa é inovadora na medida em que exami- na o efeito do voto remoto do Conselho de Administração nas variáveis de remuneração do CEO e desempenho financeiro da organização, com a utilização de uma metodologia inovadora.

Design/metodologia/abordagem:

Utilizou-se um método quase-experi- mental (diferença-em-diferenças), para avaliar os efeitos de um deter- minado grupo (tratamento), antes e depois do evento, reduzindo signi- ficativamente a endogeneidade ao considerar um choque exógeno ao sistema.

Resultados:

Como resultado, a estimação do modelo principal revela diferenças estatisticamente significativas entre os grupos de tratamento e controle sobre a lucratividade e a remuneração dos executivos, indi- cando que o voto remoto mitigou problemas de agência ao gerar um efeito de substituição por incentivos explícitos (evidenciado pela dimi- nuição da remuneração dos executivos) e por proporcionar maior desempenho contábil para as empresas.

Palavras-chave:
desempenho financeiro; remuneração de executivos; diferença-em-diferenças; voto a distância; conselhos de administração

INTRODUCTION

The conflict of interest between executives and stockholders arose due to segregated ownership and management (Berle & Means, 1932). Jensen and Meckling (1976) spread the concept of agency conflicts and their associ- ated costs through their research. In this sense, Tirole (2006) suggested many measures to mitigate such expenses, including monitoring the Chief Executive Officer (CEO), designing an incentive and reward system, and establishing an effective Board of Directors.

The Board of Directors is the primary entity responsible for resolving conflicts of interest or agency difficulties (Jensen, 1993), playing a critical role in corporate governance, as they are responsible for monitoring activi- ties and approving strategic decisions (Detthamrong et al., 2017; Agrawal & Nasser, 2019; Hu et al., 2020).

In pulverized capital companies, a hurdle for the Board of Directors is the attendance at General Meetings, where voting occurs, even though many directors are busy, work on other boards, and reside in different areas (Iliev & Roth, 2018). Remote voting for directors has become a facilitator with the advent of new technology. As a result of this environment, this research examines the effect of remote voting by Boards of Directors on executive compensation and financial performance of publicly traded Brazilian compa- nies by utilizing the difference-in-differences (DID) approach. So, the research question is: Can remote voting mitigate agency problems?

As a result, the estimation of the main model reveals statistically sig- nificant differences in the effects of treatment and control on profitability variables and on the average remuneration of executives, indicating that remote voting mitigated agency problems by generating a substitution effect for explicit incentives (decrease in executive remuneration) and by provid- ing greater accounting performance for companies.

This study promotes a debate about the effect of remote voting on cor- porate performance and CEO compensation by filling a gap in the field, identifying the importance of adopting remote voting on board meetings, and indicating that it is a possible solution to reduce costs and minimize the difficulties of displacement and distance. In addition, it could help reduce the expropriation of minority shareholders, who would have more active participation on the board. Additionally, the methodology innovates by adopting a quasi-experiment using the DID method, significantly reducing estimation problems when considering an exogenous shock to the system.

This paper also contributes to the existing literature about improve- ments in active monitoring and ways to mitigate existing agency problems in companies from countries with weak legal protection, in addition to incit- ing the debate about the importance of voting on the board meetings as a monitoring mechanism, contributing with professionals and shareholders to ensure greater performance in companies.

REMOTE VOTING AS A WAY TO MITIGATE AGENCY PROBLEMS

Capitalism resulted in a corporations’ expansion, which was followed by a separation between capital and control. This separation resulted in a con- flict of interests known as the agency problem (Berle & Means, 1932). Sub- sequently, the studies of Jensen and Meckling (1976) formalized this Agency Theory by highlighting agency costs associated with private benefits and the necessity for more supervision (Murphy, 2013). Corporate govern- ance was developed to mitigate these conflicts of interest. According to Agency Theory, these conflicts between managers and shareholders gener- ate wrong investments. CEOs prefer not to invest efficiently or in projects that harm organizations’ finances, mainly if hired by indication (Hung et al., 2022). One way to relieve this moral hazard problem is to promote a better fit in the organization’s corporate governance policies (Erkan & Nguyen, 2021). Salehi et al. (2021) state that, like the owner, the CEO also works to increase their profits.

Some papers indicate that competition can mitigate agency problems in emerging markets because it reduces the adverse effect of antitakeover laws on a firm’s performance (Tang, 2018; Girotti & Salvadè, 2021). However, these conflicts are mainly avoided by harmonizing the interests of the prin- cipal and the agent. Monitoring and incentive programs are two primary methods for achieving this alignment (Tirole, 2006). The Board of Direc- tors is the primary element of corporate governance and has a significant role in determining CEO compensation searching for optimal contracts that aim to maintain interest alignment, increase return on principal, and reduce agency expenses (Jensen, 1993). It also plays a critical role in effec- tive monitoring, preventing executives from engaging in negotiations for built empires at the expenses of stockholders (Fich et al., 2014). However, according to Harris and Raviv (2008), the Board of Directors may be inca- pable of monitoring.

Monitoring is also positively associated with the company ’s size, as larger companies are more difficult to monitor (Jensen & Meckling, 1976). The number of board members is also considered an important factor in boosting the firm’s efficiency (Jensen, 1993). Concerning the size of the board, the literature presents contradictory findings, indicating that a smaller number of members or with excessive grades may be unable to make effec- tive decisions (Hermalin & Weisbach, 2003).

In this context, Salehi et al. (2023) identify how the Board of Directors is formed in Iraq can considerably reduce companies’ capital costs, generat- ing greater gains. This human capital can promote a reduction in contrac- tual costs for firms (Salehi et al., 2022). Choi et al. (2007) verified that directors’ independence is an important mechanism for the company’s per- formance. A frequent challenge faced by directors of firms with scattered capital is their members’ attendance at general meetings, even because many are occupied with other activities, obstructing participation and the stock- holders’ right to vote (Iliev & Roth, 2018).

The possibility of remote voting in the Board meetings has gathered prominence with the advancement of new technology. Compared to face-to- face meetings, synchronous remote meetings are associated with directors’ better meeting attendance behavior, higher likelihood of director dissent on monitoring related proposals, higher forced CEO turnover-performance sensitivity, and more effective investments (Cai et al., 2023). When minor- ity shareholders’ voting opposition increases, promoted by remote voting, the likelihood and frequency of regulatory penalties also increase, indicating a good governance practice (Lin et al., 2023). Evidencing the benefits of remote voting in China, Lan et al. (2023) identified that the reduction of vot- ing costs through online voting is positively related to participation in share- holder meetings and firm performance.

Law no. 12.431 made remote voting mandatory in General Assemblies in Brazil in January 2018. The Brazilian Securities and Exchange Commis- sion (CVM) issued Instruction no. 561 in April 2015 in response to the need for clearer rules for virtual meetings. In addition to enabling remote voting at general meetings, this amendment established its guidelines, specifying the rules for the remote voting bulletin (CVM, 2021). Thus, the principal could vote even while they were not present.

Due to the need for social distancing because of Covid-19, this law allowed board members a safer, more agile, and transparent channel to exer- cise their right to vote online in board meetings. Through registration and identification, Lupion and Araujo (2020) inform that board members can participate in the meetings in a way almost equivalent to face-to-face, fol- lowing the dynamics of events and voting from a distance on all subjects that are deliberated, considering the reality of the moment.

When analyzing the impact of remote voting in Brazil, Paula (2018) observed that this question emerged as a possible solution to reduce costs and minimize the difficulties that shareholders face when trying to vote at meetings since remote voting would not require the presence of the mem- bers. In the same way, Bortolon et al. (2019) show the importance of dis- tance voting in Brazil, as it provides minority shareholders a way to voice their opinions.

In contrast, Lupion and Araujo (2020) analyzed the fully online board meetings held by Petrobras S/A in July 2020, and they did not identify that the new digital modality created incentives to increase the participation of minority shareholders during the Covid-19 period. This case is added to other problems reported by participants, such as obstacles to entering the digital platforms, difficulties asking questions, and false statements. So, the intermediate solution could be a hybrid meeting, allowing the members to participate in debates and exercise their voting rights at a lower cost with- out excluding face-to-face participation (Lupion & Araujo, 2020).

This legislative adaptation is seen as a significant evolution in compa- nies, as it enables the market to adapt to technological advancements, increasing market efficiency and creating chances for everyone to attend meetings, thereby increasing engagement. In this context, the first research hypothesis is generated:

• H1: The implementation of remote voting for the Boards of Directors had a positive impact on companies’ financial performance.

Corporate governance uses executive compensation to align stock- holders’ and managers’ interests (Gopalan et al., 2014). Variable remunera- tion, stocks, and options are the most relevant components of incentives because it is through them that compensation variations are verified accord- ing to performance (Tirole, 2006). In this sense, Raith (2008) confirms that Boards of Directors relate executive compensation to the company’s suc- cess. Zhao (2008) demonstrates that moral hazard exists in his remunera- tion model when the CEO’s efforts are directed toward increasing resource inflows without regard for the long term. According to Fich et al. (2014), one method to minimize this problem is to enhance CEO stock ownership or monitoring.

According to Tirole (2006) and Subramanian et al. (2002), monitoring and incentives are substitutes, as firms with the lowest compensation of executives usually have a more engaged board. Along the same line, Rediker and Seth (1995) find strong substitution effects between monitoring and incentive effects, suggesting that firms have considerable flexibility in designing efficient combinations of governance mechanisms to achieve alignment of manager-shareholder interests. Datta et al. (2021) found a substitution effect of monitoring to reduce manager-shareholder agency conflicts, mainly in the presence of female directors and executives.

Taking the expropriation theory into account, Crisóstomo et al. (2020) indicate that controlling shareholders may promote a substitution effect, renouncing strong boards and directly perform management monitoring, mitigating agency conflicts with managers and constraining the use of pri- vate benefits of control. Ben-Nasr et al. (2021) inferred that the substitution between monitoring and incentives is a value-enhancing decision in banks. In this instance, monitoring is an alternative for increased executive com- pensation, avoiding moral hazard issues. As a result of these considerations, the following hypothesis arises:

• H2: Implementing remote voting increased the executives’ monitoring, generating a substitution effect concerning explicit incentives and nega- tively impacting executive compensation.

METHODOLOGY

To examine the effect of the Board of Directors remote vote on executive compensation and financial performance of publicly traded Brazilian compa- nies, this research is classified as quantitative and descriptive. After apply- ing the Kernel Propensity Score Match (KPSM), the sample consisted of 145 publicly traded companies in Brazil between 2016 and 2019 (eight quarters before and eight quarters after the event), not including financial institu- tions. Of these, 92 companies are classified as the treatment group, having adopted remote voting for the Boards of Directors solely because of the CVM’s obligation (January 2018), while 53 are classified as a control group, having maintained remote voting for the Boards of Directors throughout all the analyzed period.

The sample was formed by quarterly data, where 736 observations are before and 736 are after the shock for the treatment group, and 424 are before and 424 are after the shock for the control group, totaling 2,320 non-bal- anced observations with gaps (the number of observations for each variable is described in Table 2). Economatica and CVM Reference Reporting gath- ered all data. The mandatory remote voting for Boards of Directors through the implementation, in Brazil, of Law no. 12.431 in January 2018 is the benchmark or external shock whose effect on executive compensation and the financial performance of companies was evaluated.

We employed the DID technique (Card & Krueger, 1994). This quasi- experimental method was designed to assess the effects of any group by conducting a test prior to and following the event. According to Donald and Lang (2007), the sample must include a control group (unaffected by the event) and a treatment group (affected by the event).

As the name implies, the DID methodology is based on a double sub- traction: one occurs in the difference between the averages of the outcome variable for both groups between the periods preceding and following the event, and the other occurs in the difference of the first difference calculated between groups (Bertrand et al., 2004). This measurement lets us deter- mine which group has the greatest difference during the analysis period. The DID model can be described according to Equation 1.

(1) $Y_{it}={\delta }_0+{\delta }_1\cdot pos{t}_t+{\delta }_{2}treate{d}_i+{\delta }_3\left(treated\text{x}pos{t}_t\right)+{\delta }_{it}covariate{s}_{it}+{\epsilon }_{it}$

where i represents the company; t represents time; Y_it represents the dependent variable; δ₁ represents causal factors of changes in Y over time; δ₂ represents the differences between the treatment and control groups before the shock in question; δ₃ represents the coefficient of interest; δit represents the coefficients of the covariates, and ε_it represents the model error.

Equation 2 estimates the coefficient of interest (δ₃), or DID purely.

(2) ${\widehat{\delta }}_3=\left({\widehat{y}}_{\left(treat\text{,}post=1\right)}-{\widehat{y}}_{\left(treat\text{,}post=0\right)}\right)=\left({\widehat{y}}_{\left(control\text{,}post=1\right)}-{\widehat{y}}_{\left(control\text{,}post=0\right)}\right)$

Bertrand et al. (2004) state that the DID model’s estimations are derived from the ordinary least squares (OLS) method and their associated standard errors. To select a group of companies with characteristics similar to those that have changed due to this regulation, Funchal and Monte-Mor (2016) advised using the Propensity Score Matching (PSM) technique. This proce- dure isolates the treated observations and locates an observation from the control group that correlates in size and sector dimensions to the treated observation. Leuven and Sianesi (2014) state that we can identify a similar control company for each firm affected by the law by using the KPSM.

To test the assumptions of the OLS method, we used Pearson’s Correla- tion, Shapiro-Wilk (normality), Covariance Matrix (covariance), Wooldridge (absence of serial autocorrelation), Breusch-Pagan (heteroscedasticity), VIF (variance inflation factor – Linearity) and Durbin-Wu-Hausman (endogene- ity). To smooth out the outliers, we applied winsorization at 1%. Finally, the Placebo Test was used to verify the model’s robustness.

The dependent variables correspond to the financial performance indi- cators (ROA, ROE, and Tobin Q) and executive compensation (average remuneration, executive shares, and options). The covariates are as follows: number of executives, tenure of executives, number of directors, tenure of directors, company’s size, leverage, temporal fixed effects and sector fixed effects, as shown in Table 1.

Table 1
Proxies and variables

Variable	Acr.	Description/formula	Author
Dependent variables – Performance
Return on assets	ROA	$\frac{EBI{T}^1}{TotalAssets}$	Gaur et al. (2015), Sonza and Kloeckner (2014), and Frank and Goyal (2008)
Return on equity	ROE	$\frac{NetIncome}{Equity}$	Gaur et al. (2015) and Sonza and Kloeckner (2014)
Tobin‘s Q	Q	$\frac{{\left(\text{MVE}+\text{PS}+\text{D}\right)}^2}{TotalAssets}$	Futema et al. (2009) and Tristão and Sonza (2021)
Dependent variables – Executive compensation
Average remuneration	RM	$log\left(\frac{Av.Exec.Remuneration}{NumberofExecutives}\right)$	Krauter (2013), Aguiar and Pimentel (2017), Jensen and Murphy (1990), and Kaplan (1994).
Shares and options	AP	Log (value of executive’s shares and options)	Jensen and Murphy (1990) and Sonza and Kloeckner (2014)

Covariates2				F	C
Number of executives	NE	Log (number of executives)	Chen et al. (2008), Granzotto and Sonza (2019), and Schmid and Wurster (2016)	-	+
Tenure of executives	TE	Log (average tenure of the executives)	Chen et al. (2008), Granzotto and Sonza (2019), and Schmid and Wurster (2016)
Number of directors	ND	Log (number of directors)	Hermalin and Weisbach (2003), Jensen (1993), Granzotto and Sonza (2019), and Conyon et al. (2019)	+ -	-
Tenure of directors	TD	Log (average tenure of directors)	Chen et al. (2008), Sonza and Kloeckner (2014), Granzotto and Sonza (2019), and Conyon et al. (2019)	+	-
Size	Size	Log (total assets)	Klapper and Love (2004), Krauter (2013), Aguiar and Pimentel (2017), and Cai et al. (2023)	+ -	+
Leverage	AL	$\frac{shortandlongtermdebt}{Equity}$	Rajan and Zingales (1995), Lemmon et al. (2008), and Frank and Goyal (2008)	- +	-
Sectorial fixed effects	Sector FE	Dummies: 1 company belongs to the industrial sector and 0 otherwise	Sonza and Kloeckner (2014)
Time fixed effects	Time FE	Dummies: 1 company belongs to the year in which the data is generated and 0 otherwise	Sonza and Kloeckner (2014)

• Note.¹Earnings Before Interest and Taxes; ²Suggested by Chung and Pruitt (1994), whose market value is the sum of the MVE – the company’s share price multiplied by the number of outstanding common shares, PS – the settlement value of the outstanding preferred shares and D – total debt (current liabilities minus current assets plus inventories and long-term debt). ²F – financial performance; C – executive compensation.

ANALYSIS OF THE RESULTS

The descriptive statistics were compared between the treatment and control groups in Table 2, taking the shock into account, revealing a consid- erable shift in accounting and market performance indicators, implicit incen- tives, executive stocks, options, monitoring indicators, and size. The average return on assets (ROA) of the treatment companies increased significantly from 0.02 to 0.04; the average return on equity (ROE) increased signifi- cantly from 0.04 to 0.09; and the average Tobin’s Q (Q), which indicates the market value of the company, increased significantly from 0.66 to 0.78, indi- cating a high expected value.

Table 2
Descriptive statistics of the treatment and control group

Treatment group
Before the shock						After the shock
Var.	(n)	Mean	Min.	Max.	SD	(n)	Mean	Min.	Max.	SD	t
ROA	736	0.02	−0.22	0.23	0.07	736	0.04	−0.22	0.23	0.07	−5.09	***
ROE	736	0.04	−0.59	0.72	0.17	736	0.09	−0.59	0.72	0.17	−5.11	***
Q	736	0.66	0.07	4.26	0.62	736	0.78	0.07	4.26	0.68	−3.49	***
RM	416	1.951	0.00	15.701	2.041	208	1.861	0.00	11.401	1.811	0.49
AP	416	0.721	0.00	14.801	2.091	200	1.571	0.00	33.101	4.991	−2.98	***
NE	416	4.60	2.00	13.00	2.21	208	4.56	2.00	9.00	1.86	0.23
TE	408	4.90	0.50	21.00	3.72	197	5.67	0.50	21.00	3.85	−2.36	**
ND	648	0.82	0.48	1.32	0.17	649	0.82	0.48	1.32	0.16	0.15
TD	412	4.65	0.50	19.2	3.60	200	5.22	0.90	19.2	3.77	−1.78	**
Size	736	6.41	5.19	7.65	0.59	736	6.48	5.19	7.82	0.61	−1.97	**
AL	736	1.82	0.10	16.81	2.46	736	1.76	0.10	16.81	2.15	0.47
ROA	424	0.04	−0.18	0.23	0.07	424	0.05	−0.13	0.23	0.06	−1.48	*
ROE	424	0.10	−0.59	0.72	0.20	424	0.12	−0.59	0.72	0.18	−1.27
Q	424	1.00	0.07	4.26	0.98	424	1.11	0.10	4.26	0.98	−1.69	**
RM	224	3.12	0.10	31.00	4.21	112	3.60	0.24	12.90	3.10	−1.05
AP	224	2.91	0.00	28.00	5.57	112	3.88	0.00	43.00	9.08	−1.21
NE	216	6.39	2.00	14.00	3.01	108	6.78	2.00	14.00	2.87	−1.11
TE	224	5.33	1.00	13.25	3.03	112	5.49	1.00	11.50	2.82	−0.47
ND	424	0.90	0.48	1.32	0.15	424	0.90	0.48	1.32	0.15	0.60
TD	224	4.48	0.86	13.14	2.57	112	4.94	1.30	10.20	2.45	−1.55	*
Size	424	7.12	6.00	8.53	0.57	424	7.20	6.09	8.53	0.55	−2.03	**
AL	424	2.23	0.13	16.81	2.68	424	2.46	0.10	16.81	3.17	−1.10

• Note.¹ in million; *** significant at p < 0.01; ** significant at p < 0.05; * significant at p < 0.1.

This level of gain is not observed in the control group, where only ROA and Tobin’s Q were significant, although to a greater magnitude. This fact leads us to assume that mandatory remote voting increased directors’ activity in monitoring executives, resulting in increased performance, consistent with Jensen and Murphy’s (1990) and Sonza and Kloeckner’s (2014) investigations.

Additionally, in Table 2, the average AP (stocks and options) increased significantly from 0.72 million to 1.57 million in the treatment group; the average tenure of executives (TE) and directors (TD) also increased signifi- cantly from 4.90 to 5.67 and 4.65 to 5.22, respectively; and finally, the aver- age logarithm of size increased significantly from 6.41 to 6.48. Only a couple of these variables changed significantly in the control group: the average TD and the company size, which increased significantly and positively from 4.48 to 4.94 and 7.12 to 7.20, respectively. There were no significant changes in the other factors (executive remuneration, number of executives, number of directors, and leverage).

In summary, the descriptive statistics indicate that the control group is formed by larger companies already suited to the new board voting system. Hence, the changes were not as significant. On the contrary, in the treat- ment group, the shift to remote voting was impacted considerably, where the difference in means was significant in almost all variables. This result is in accordance with Lin et al. (2023) and Lan et al. (2023), who relate remote voting to good governance practices.

Following the descriptive statistics, we analyzed Pearson’s correlation to test the relationship between variables or the collinearity between them. If the correlation is greater than 0.7, including both in the modeling is unnec- essary, as their effects on the estimations will be similar. According to the analysis, only ROA and ROE showed a nearly perfect correlation (0.85), which was expected, given that both are identical performance metrics; so, they aren’t used in the same regression.

Following that, additional validation tests of the OLS model were con- ducted to ensure the quality of these adjustments. The Shapiro-Wilk nor- mality test did not reject the null hypothesis at the 1significance level, indicating that there isn’t normal data (Shapiro & Wilk, 1965). The null hypothesis that the matrix is diagonal (p-value less than 0.05) is rejected for the covariance test; the answer variables do not exhibit an independent rela- tionship (Karpeshina et al., 2002).

The Wooldridge test points out first-order serial autocorrelation among the sample variables since the null hypothesis is not rejected (p-value more than 0.05) (Wooldridge, 2010). The Breusch-Pagan test demonstrates het- eroscedasticity in the model; that is, the variance of the residues generated by the model estimate isn’t constant (Breusch & Pagan, 1979). The average value of the VIF is 3.16, indicating low dependence between the variables since, according to Berk (1977), if the VIF is greater than 10, multicollinear- ity can be considered a problem. Finally, because the null hypothesis is not rejected, the Durbin-Wu-Hausman test revealed an endogeny problem in the variables (Davidson & MacKinnon, 1993).

In summary, we identified that the sample is not normal, exhibits first- order serial autocorrelation, the covariance matrix is not diagonal, the resi- dues are heteroscedastic, and there is endogeneity in the variables. For this reason, a more robust model is required to mitigate these issues. In this case, the quasi-natural experiment is indicated, inserting an exogenous variable into the system.

The DID modeling begins with a graphical analysis of executive com- pensation indicators and financial performance of companies in the treat- ment and control groups between the first quarter of 2016 and the fourth quarter of 2019 (Figure 1). The graphic comparison of the indicators ena- bles observation of the dependent variables’ behavior, satisfying the parallel trends hypothesis (Villa, 2016). Due to the unique nature of the analysis, we expected that companies would have significant disparities in their indica- tors prior to the Law’s implementation and that similar trends would be observed following treatment, which would indicate that both groups approached after the instruction for mandatory remote voting for councils.

Figure 1
Graphic analysis of the executive compensation and financial performance median of the firm

By visually inspecting Figure 1, we observed that the median of ROA, ROE, and executive remuneration displayed variances prior to the law but began to exhibit parallel patterns following the event, indicating a significant change between the two periods for these variables. The event under analysis (remote voting) aided treatment and control groups in behaving similarly following the event, thus reducing the existing differences in the variables.

However, this tendency is not observed in Tobin’s Q and the executives’ stock options charts. Another point worth noting is that, following the implementation of the remote vote, accounting performance indicators (ROA and ROE) increased significantly in both groups, while CEO compen- sation declined.

Following the graphic analysis, Table 3 presents the DID modeling esti- mates, defining the difference (treatment – control) in the time preceding the shock and the difference (treatment – control) following the shock’s occur- rence. In this model, all covariates for applying the KPSM model were con- sidered (number of executives, TE, number of directors, TD, size, leverage, and sector fixed effects).

Table 3
Difference-in-differences estimations

	ROA		ROE		Q	RM		AP
Before
Treatment	0.03		0.06		0.65	14.19		13.84
Control	0.08		0.12		0.72	14.47		13.29
Difference	−0.06	***	−0.06	***	−0.07	−0.28	***	0.55
SD	(0.01)		(0.01)		(0.05)	(0.07)		(0.34)
t	8.83		−4.2		−1.36	−3.95		1.60
After
Treatment	0.04		0.09		0.78	14.10		14.13
Control	0.05		0.09		0.81	14.97		13.89
Difference	−0.01		0.00		−0.03	−0.86	***	0.24
SD	(0.01)		(0.02)		(0.06)	(0.10)		(0.40)
t	0.93		0.00		0.49	8.78		0.60
DID	0.05	***	0.06	***	0.04	−0.58	***	−0.31
DP	(0.01)		(0.02)		(0.08)	(0.12)		(0.53)
t	5.10		2.79		0.53	4.81		0.59

• Note. *** significant at p < 0.01.

Analyzing Table 3, we observed that, in the period preceding the event, the variables ROA, ROE, and RM had statistically significant negative differ- ences of 0.06, 0.06, and 0.28 at the 1level. These findings reveal that the control effect on ROA and ROE, as well as the average remuneration (RM) of executives, was 0.08, 0.12, and 14.47 points, higher than the treatment effect, which had coefficients of 0.03, 0.06, and 14.19 points, respectively.

Regarding the period after the event, that is, following the implementa- tion of remote voting, a negative and statistically significant difference of 0.86 in the remuneration indicator was identified at the 1level, indicating changes in the effects of the treatment and control groups following the event. The compensation coefficients following the shock were 14.10 for treatment and 14.97 for control companies, indicating that the treatment group experienced a stronger effect. ROA, ROE, Q and AP coefficients lacked statistical significance for the treatment and control groups after the shock.

In the DID estimator, the coefficients indicate a positive difference between the treatment and control groups on ROA (0.05) and ROE (0.06), which is significant at 1%. These results do not reject the hypothesis 1. They are in accordance with Bortolon et al. (2019) and Cai et al. (2023), who indicate remote voting as a possible solution to reduce costs and minimize the difficulties that shareholders face when voting at meetings, improving the accounting performance for companies.

In terms of remuneration, the coefficient was negative (0.58) and sig- nificant at 1%, showing that remote voting mitigated agency problems by generating a substitution effect for explicit monitoring incentives (as evi- denced by the decrease in executive remuneration), consistent with Rediker and Seth (1995), Subramanian et al. (2002) and Ben-Nasr et al. (2021), not rejecting the hypothesis 2. It follows Iliev and Roth’s (2018) findings, who discuss the difficulty of increasing director engagement, particularly in com- panies with dispersed capital, because many directors are busy, work on other boards, or live in different locations, making it difficult to attend the meetings. This situation aggravates in this pandemic era, in which face-to- face meetings put board members’ security at risk, facilitating private ben- efits by the executives.

We continue our analysis by estimating multivariate models and includ- ing a set of controls. The OLS estimation with covariates is presented in Table 4 using the standard DID structure. In this model, we incorporate sec- tor and time-fixed effects to control sectoral heterogeneity and aggregate economic shocks.

Table 4
OLS analysis with covariates

Variable	ROA		ROE		Q		RM		AP
	(n = 869)		(n = 869)		(n = 869)		(n = 853)		(n = 356)
Treat	−0.05	***	−0.11	***	−0.24	***	−0.02		−1.68	**
t	−5.34		−3.97		−5.64		−0.19		−2.22
Post	0.00		0.03		0.16	***	0.42	***	−0.42
t	0.13		0.94		2.49		3.59		−0.83
DID	0.02	**	0.01		0.06		−0.42	***	0.16
t	2.36		0.55		1.19		−4.94		0.33
NE	0.00		0.00		0.02	***	−0.09	***	−0.09
t	1.37		−0.44		2.62		−6.08		−0.81
TE	0.00	***	0.00		−0.01	*	0.03	***	−0.08
t	3.16		1.44		−1.66		2.72		−1.49
ND	−0.06	***	−0.14	***	−0.15		−0.36		−4.10	***
t	−4.33		−2.97		−1.50		−1.40		−3.24
TD	0.00	***	0.01	***	0.01		-0.07	***	0.20	*
t	4.83		2.93		1.04		−5.69		1.77
Size	0.00		0.01		0.03		0.92	***	0.83
t	−0.50		0.62		0.71		11.09		1.39
AL	−0.01	***	−0.03	***	−0.03	***	−0.02		0.01
t	−5.33		−3.04		−4.71		−1.38		0.16
Constant	0.11	**	0.14		0.22		9.17	***	1.12	**
t	1.93		0.91		0.65		14.97		2.24
Sector FE	Yes		Yes		Yes		Yes		Yes
Time FE	Yes		Yes		Yes		Yes		Yes
R2	0.55		0.39		0.81		0.65		0.66

• Note. *** significant at p < 0.01; ** significant at p < 0.05; * significant at p < 0.1.

As per our previous model (Table 3), the DID coefficients are significant and positive for ROA (but not for ROE) and negative for CEO compensa- tion, validating our earlier findings. Increases in the number of executives had detrimental consequences, increasing Tobin’s Q by 0.02 percentage points at the 1significance level and decreasing executive compensation by 0.09 percentage points at the 1significance level. The findings contradicted those in the literature, including those by Granzotto and Sonza (2019) and Schmid and Wurster (2016).

Regarding executive tenure, a one-point increase in this variable reduces Tobin’s Q by 0.01 percent at the 10level and increases executive compen- sation by 0.03 percentage points at the 1level. ROA is significant but has a null effect. This finding is consistent with Chen et al. (2008) and Schmid and Wurster (2016), who assert that executives with a longer tenure tend to become more entrenched, establishing their power bases. As a result, they earn more money but are less likely to be dismissed for poor performance over time, tend to reduce their efforts, and increase their myopia, narcis- sism, and overconfidence, negatively affecting the company’s performance (Seifzadeh, 2020).

This variable was negative in almost all analyses regarding the number of directors. Still, it was significant for ROA, ROE, and AP, where an increase in the number of directors by one percentage point reduces the ROA, the ROE, and the value of the executives’ stocks and options by 0.06, 0.14, and 4.10 percentage points, respectively, all at the 1significance level. This finding is consistent with Granzotto and Sonza (2019), who assert that a very large board has a harder time making choices, a tendency to act improp- erly and a negative impact on the company’s success. Additionally, it cor- roborates with Conyon et al. (2019), who imply that the larger the board, the more closely executives are monitored, without requiring executives to have greater incentives to behave in the company’s best interests.

The TD likewise produced expected impacts in almost all analyses, where an increase of one percentage point in this variable increases ROE by 0.01 percentage points and decreases executive remuneration by 0.07 per- centage points, both at the 1level. This finding was expected, as more experienced directors are more likely to make wise decisions that benefit the companies’ performance (Sonza & Kloeckner, 2014) and to oversee execu- tives more effectively, lowering the need for increased remuneration incen- tives (Conyon et al., 2019). The ROA also produced a significant but neutral (near zero) result, whereas the AP regression produced a substantial but positive result, contrary to the literature.

The size of the companies (logarithm of total assets) is statistically sig- nificant for RM, indicating that increasing this variable by one percentage point increases executive remuneration by 0.92 percentage points at the level of 1%. This finding corroborated with Aguiar and Pimentel (2017), who assert that larger companies generally pay the executives better. Finally, leverage was negative and significant for all performance analyses, where an increase in this variable decreased ROA by 0.01, ROE by 0.03, and Tobin’s Q by 0.03 percentage points, all at a 1significance level. This result is consistent with the pecking order theory, in which the most lucrative busi- nesses rely less on third-party finance (Rajan & Zingales, 1995; Lemmon et al., 2008; Frank & Goyal, 2008).

Finally, the Placebo test (Table 5) was used to assess the model’s robust- ness, determining whether DID modeling estimates were unaffected by further external or endogenous shocks. We conducted the Placebo by chang- ing the period corresponding to the shock under research from 2018/1 to 2016/3. None of the factors demonstrated statistical significance for the DID coefficient (the most important variable in the investigation). This finding confirms that the changes studied in the DID modeling were caused by the event, mandatory remote voting, and not by other shocks or trends.

Table 5
Placebo test (Alternative shock: 2016/3)

	ROA		ROE		Q	RM		AP
Before
Treatment	0.03		0.06		0.58	14.11		13.47
Control	0.06		0.09		0.58	14.51		12.95
Difference	−0.03	**	−0.03		0.00	−0.40	*	0.53
SD	(0.01)		(0.03)		(0.11)	(0.14)		(0.70)
t	−2.55		−0.90		0.01	−2.84		0.76
After
Treatment	0.03		0.07		0.75	14.15		13.93
Control	0.07		0.12		0.75	14.75		13.45
Difference	−0.04	*	−0.05	*	0.00	−0.60	*	0.48	***
SD	(0.01)		(0.01)		(0.04)	(0.06)		(0.28)
t	8.05		4.67		0.04	9.76		1.72
DID	−0.01		−0.02		0.00	−0.20		−0.05
DP	(0.01)		(0.03)		(0.11)	(0.15)		(0.75)
t	0.38		0.76		0.02	1.30		0.07

• Note. *** significant at p < 0.01; ** significant at p < 0.05; * significant at p < 0.1.

CONCLUSIONS

Boards of Directors play a critical role as they are responsible for moni- toring and making strategic decisions. In pulverized capital companies, the participation of directors at general meetings, where voting occurs, is a bar- rier for these Boards, even because many are busy, work on other boards, and reside in different areas (Iliev & Roth, 2018). With the advancement of new technology, the implementation of remote voting has facilitated this process, increasing directors’ engagement in resolving crucial issues and improving monitoring. In this context, the current study examined the effect of remote voting on the Boards of Directors on CEO compensation and financial performance of companies. This topic is still little explored.

According to the results found and debated, descriptive statistics indi- cate a considerable shift in accounting and market performance and implicit incentives and monitoring indicators when comparing the treatment group before and after the Law’s implementation. With the visual graphic inspec- tion of the model, we identify that, in the accounting performance and exec- utive remuneration indicators, the event (mandatory remote voting) aided treatment and control groups in behaving similarly, hence eliminating exist- ing differences in the variables.

The estimation of the main model indicated statistically significant dif- ferences in the effects of treatment and control on the profitability variables (ROA and ROE), showing that the implementation of remote voting by the Boards of Directors had a positive impact on the financial performance of the companies, not rejecting hypothesis 1. This finding is consistent with Iliev and Roth (2018), who noted the difficulty of increasing director’s engagement since many directors are busy, work for other boards, or live in different locations, making attendance at board meetings difficult. This dif- ficulty is exacerbated by the Covid-19 pandemic, where massive director participation may provide greater monitoring of executives, resulting in gains for companies.

We also identified that the implementation of remote voting had a neg- ative effect on the average remuneration of executives, indicating that imple- menting this law mitigated agency problems by generating a substitution effect of explicit incentives for increased monitoring, not rejecting hypoth- esis 2. This finding corroborates with Rediker and Seth (1995), Subrama- nian et al. (2002), and Ben-Nasr et al. (2021), who stated that executives with lower salaries also had a more active Board of Directors. The majority of the control variables presented the expected results.

The current study distinguishes itself from others by emphasizing remote voting as an important governance instrument that improves com- pany monitoring. It brings it into the debate over company performance and executive compensation, filling a gap in the literature on the subject. As it is a relatively new topic, we have, as a limitation of the study, a small time window for analysis after implementing the law. About the method, there is the possibility that the endogeny remains. For future work, we suggested verifying the effect of remote voting on other variables, such as the capital structure of companies.

• This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (Capes) – Finance Code 001. Funders had no influence on the study design, data collec- tion and analysis, decision to publish, and article preparation.

• RAM does not have information about the existence of open data regarding this manuscript.

• RAM does not have authorization from the authors and/or evaluators to publish this article’s review.

• This paper may be copied, distributed, displayed, transmitted or adapted for any purpose, even commercially, if provided, in a clear and explicit way, the name of the journal, the edition, the year and the pages on which the paper was originally published, but not suggesting that RAM endorses paper reuse. This licensing term should be made explicit in cases of reuse or distribution to third parties.

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Publication Dates

• Publication in this collection
  24 June 2024
• Date of issue
  2024

History

• Received
  31 Jan 2023
• Accepted
  26 July 2023