Non-financial indicators, performance, and remuneration: A way to reduce agency conflicts

Indicadores não financeiros, desempenho e remuneração: Uma forma de reduzir conflitos de agência

Abstract

Purpose:  This study aims to verify whether the use of non-financial performance measures (NFPMs) influences the relationship between organizational performance and executive compensation in Brazilian companies. The central aim is to assess whether these measures can serve as control mechanisms that reduce agency conflicts and align managerial actions with shareholders’ interests.

Originality/value:  The research is original, offering an analysis of NFPMs in an emerging economy such as Brazil, which is characterized by high ownership concentration and distinctive corporate governance structures. While international studies exist, national evidence remains scarce and contradictory. We fill that gap by examining how NFPMs affect the performance-compensation relationship in a non-Anglo-Saxon market. Its practical value lies in showing that NFPMs may limit excessive executive pay and promote more balanced contracts, with implications for sustainable value creation.

Design/methodology/approach:  The research used data from 119 non-financial Brazilian companies listed on B3 from 2012 to 2019, in an unbalanced panel structure. Financial indicators such as return on assets, EBITDA margin, return on sales, and dividends per share were analyzed, comparing firms that employ NFPMs with those relying solely on financial measures.

Findings:  Prior performance was a decisive factor in current compensation. Firms adopting NFPMs showed positive relationships among EBITDA margin, return on sales, and future compensation. Interactions with ROA and DPS were not statistically significant, suggesting that managers avoid evaluation based on variables beyond their control.

Contribution/implications:  The findings support the informativeness principle, showing that NFPMs provide incremental information that improves compensation contracts, reduces agency conflicts, and strengthens corporate governance.

Keywords:
agency conflicts; non-financial measures; compensation; organizational performance; emerging markets

Resumo

Objetivo:  Verificar se o uso de indicadores de desempenho não financeiros (IDNF) influencia a relação entre o desempenho organizacional e a remuneração de executivos em empresas brasileiras. A intenção central é avaliar se esses indicadores podem atuar como mecanismos de controle que reduzam os conflitos de agência e alinhem as ações gerenciais aos interesses dos acionistas.

Originalidade/valor:  A pesquisa é original por analisar o IDNF em uma economia emergente como o Brasil, caracterizada por alta concentração de propriedade e por estruturas de governança corporativa distintas. Embora existam estudos internacionais, as evidências nacionais ainda são escassas e contraditórias. Preenchemos essa lacuna examinando como os IDNF afetam a relação entre desempenho e remuneração em um mercado não anglo-saxão. Seu valor prático reside em demonstrar que os IDNF podem limitar a remuneração excessiva de executivos e promover contratos mais equilibrados, com implicações para a criação de valor sustentável.

Design/metodologia/abordagem:  A pesquisa foi conduzida com dados de 119 empresas brasileiras não financeiras listadas na B3 entre 2012 e 2019, em um painel desbalanceado. Indicadores financeiros, como retorno sobre ativos (ROA), margem EBITDA, retorno sobre vendas (ROV) e dividendos por ação (DPA), foram analisados, comparando empresas que utilizam medidas não financeiras (MNF) com aquelas que se baseiam exclusivamente em indicadores financeiros.

Resultados:  O desempenho anterior mostrou-se decisivo para a remuneração atual. As empresas que adotaram MNF apresentaram uma relação positiva entre a margem de EBITDA, o retorno sobre vendas e a remuneração futura. As interações com ROA e DPA não foram estatisticamente significativas, sugerindo que os gestores evitam realizar avaliações baseadas em variáveis fora de seu controle.

Contribuição/implicações:  Os resultados corroboram o princípio da informatividade, indicando que as MNF fornecem informações adicionais que aprimoram os contratos de remuneração, reduzem os conflitos de agência e fortalecem a governança corporativa.

Palavras-chave:
conflitos de agência; indicadores não financeiros; remuneração; desempenho organizacional; mercados emergentes

INTRODUCTION

Why do executive compensation contracts often fail to align managerial incentives with long-term value creation, even when they rely on seemingly sophisticated performance metrics? This question remains central to both academic research and corporate governance practice (Cho, Ibrahim & Yan, 2019). Despite decades of theoretical and empirical advances, concerns about weak pay–performance sensitivity and excessive executive compensation persist across institutional contexts. In Brazil, these concerns are particularly salient: CVM data show that in 2019, CEOs of listed firms earned, on average, 75 times the median employee’s pay (Alvarenga, 2020), given the combination of high ownership concentration, heterogeneous governance structures, and relatively recent advances in disclosure practices.

Agency Theory (Jensen & Meckling, 1976) is the dominant framework for understanding this problem, emphasizing how incentive contracts can mitigate conflicts arising from information asymmetry and divergent objectives between principals and agents. Within this framework, the informativeness principle (Holmström, 1979; Feltham & Xie, 1994) offers a clear prescription: compensation contracts should incorporate performance measures that provide incremental information about managerial effort. The challenge, however, lies not in the principle itself, but in identifying which measures are truly informative in practice (Tahir, Ibrahim & Nurullah, 2019).

Traditional compensation contracts rely heavily on financial performance indicators such as return on equity, earnings, and stock-based metrics. While widely used, these measures have well-documented limitations: they are typically backward-looking, subject to accounting discretion, and influenced by macroeconomic and industry-wide shocks beyond managerial control (Banker et al., 2000), which can incentivize short-term decision-making and undermine long-term value creation (Bouwens & Lent, 2006). In response, firms have increasingly incorporated non-financial performance measures (NFPMs) into executive compensation contracts. From a theoretical standpoint, NFPMs are expected to enhance contract efficiency by capturing dimensions of performance more directly linked to managerial actions, including operational efficiency, customer satisfaction, innovation, and sustainability initiatives (Ittner & Larcker, 1998; Schiehll & Bellavance, 2009).

Empirical evidence on NFPM effectiveness, however, remains inconclusive. While some studies document that NFPMs improve pay–performance sensitivity and serve as leading indicators of future financial outcomes (Banker et al., 2000; Cho & Ibrahim, 2022; Gan et al., 2020), others report weak, null, or even adverse effects (Hyvönen, 2007; Abernethy et al., 2013). Importantly, the institutional environment shapes how compensation mechanisms operate: ownership concentration, board structure, and legal origin critically condition the effectiveness of incentive contracts (Sánchez-Marín et al., 2022). In non-Anglo-Saxon contexts, the use of non-financial criteria (including CSR-linked indicators) has been shown to influence both the level and structure of executive pay, with stronger effects observed in firms with weaker governance (Kharabsheh, Al-Shammari & Al-Numerat, 2022; Blanes, De Fuentes & Porcuna, 2021).

In Brazil, the picture is even more sobering. Anjos et al. (2019) found no significant evidence of relative performance evaluation among B3-listed firms, suggesting that executive compensation remains weakly tied to organizational outcomes, even when measured by multiple financial indicators. While Souza et al. (2017) suggest that NFPM-based compensation can improve future financial performance, Aguiar and Frezatti (2014) found that greater reliance on NFPMs was paradoxically associated with a shorter-term managerial orientation. More recently, Anjos et al. (2019), Brandão et al. (2019), and Freitas et al. (2020) have shown that governance characteristics, particularly ownership structure and board composition, significantly shape pay–performance sensitivity in Brazilian-listed firms, reinforcing the view that institutional context cannot be ignored when evaluating compensation design.

This evidence points to a broader gap in the literature. Most prior studies implicitly assume that NFPMs operate uniformly across performance dimensions, typically examining their direct effects or focusing on a single financial metric. As a result, we know relatively little about whether (and under what conditions) NFPMs enhance the informativeness of compensation contracts when paired with distinct financial measures that capture different aspects of firm outcomes (Said et al., 2003; Schiehll & Bellavance, 2009).

This study addresses that gap by examining whether NFPMs moderate the relationship between organizational performance and executive compensation across multiple financial indicators. Using an unbalanced panel of 119 non-financial firms listed on B3 from 2012 to 2019, we analyze how NFPM adoption affects the sensitivity of executive compensation to EBITDA margin, return on sales, return on equity, and dividends per share. We employ fixed-effects models, lagged specifications, and a Heckman two-step procedure to address endogeneity. The findings show that firms adopting NFPMs exhibit stronger pay–performance sensitivity, particularly through EBITDA margin and return on sales, consistent with the informativeness principle.

This study makes three main contributions. First, it shows that NFPM effectiveness varies with the specific financial performance dimension considered, thereby clarifying inconsistencies in the prior literature. Second, it provides systematic evidence from an emerging market in which institutional features shape incentive contracts differently than in Anglo-Saxon contexts. Third, by explicitly addressing endogeneity in NFPM adoption, it offers more credible estimates of their role in compensation design. For boards and compensation committees, the results reinforce the value of NFPMs tied to operational efficiency when designing executive bonus plans. For investors, NFPM adoption may serve as a signal of more informative compensation contracts. For regulators, the findings highlight the importance of disclosure requirements that enhance transparency regarding performance evaluation criteria, reinforcing the relevance of CVM Instruction 480/2009.

LITERATURE REVIEW

Agency theory and the compensation–performance relationship

The relationship between shareholders and managers lies at the heart of modern corporate governance. Agency Theory (Jensen & Meckling, 1976) provides the dominant analytical framework for understanding this relationship, emphasizing how goal misalignment and information asymmetry create opportunities for opportunistic managerial behavior. Because managers possess private information about their effort and strategic decisions — information that shareholders cannot perfectly observe — the design of compensation contracts becomes a critical governance instrument. Without appropriate incentives, managers may engage in shirking, excessive risk-taking, or earnings manipulation, all of which erode firm value at shareholders’ expense.

To address this problem, compensation must be tied to performance indicators that reliably capture managerial contributions to firm value. The informativeness principle (Holmström, 1979; Feltham & Xie, 1994) offers a clear prescription: any measure that provides incremental information about managerial effort should be included in compensation contracts, enabling principals to design incentive schemes that are both motivating and efficient.

In practice, most compensation contracts have long relied on financial metrics such as return on assets, return on equity, earnings, or stock returns. These measures are undeniably useful, but their limitations are well documented. They tend to be backward-looking, susceptible to accrual-based manipulation, and heavily influenced by macroeconomic conditions beyond managerial control. Perhaps most critically, they fail to capture the intangible drivers of long-term competitive advantage — innovation, customer relationships, and human capital — that often determine whether a firm thrives over time. When compensation is anchored exclusively to such metrics, managers face systematic incentives to prioritize short-term earnings management over sustainable value creation (Banker et al., 2000; Tahir, Ibrahim & Nurullah, 2019).

These shortcomings have led firms to incorporate NFPMs as complementary metrics within executive incentive plans. NFPMs are more directly shaped by managerial decisions, less susceptible to accounting distortion, and more strongly associated with long-term firm value, improving congruence between incentives and firm objectives (Ittner et al., 2003; Cho & Ibrahim, 2022; Gan et al., 2020). The challenge lies in identifying which measures are truly informative across different performance dimensions.

Non-financial performance measures, performance, and compensation

Despite the conceptual appeal of NFPMs, empirical evidence on their effectiveness remains mixed. On the one hand, these measures offer well-recognized advantages. They are inherently forward-looking, capturing processes and behaviors that precede financial outcomes. They tend to be more controllable, since managers exert greater influence over customer satisfaction, operational efficiency, and ESG improvements than over indicators shaped by external conditions. They also reduce measurement noise by being less exposed to macroeconomic shocks, providing a more accurate reflection of managerial input (Sliwka, 2002). More recent evidence reinforces these arguments: Cho & Ibrahim (2022) showed that NFPMs strengthen pay–performance sensitivity, particularly when tied to CEO-specific objectives, while Gan, Park, and Suh (2020) demonstrated that non-financial indicators complement equity-based incentives in promoting long-term firm value.

On the other hand, NFPMs pose significant challenges. Their measurement often involves subjectivity, which can create opportunities for opportunistic bias by managers or boards (Cho, Ibrahim & Yan, 2019). Firms also face uncertainty about the optimal weighting of financial and non-financial indicators in incentive contracts (Schiehll & Bellavance, 2009). The effectiveness of NFPMs varies considerably across industries, governance environments, and institutional contexts, complicating the generalization of empirical findings (Tahir, Ibrahim & Nurullah, 2019).

These tensions help explain the divergent findings in prior literature. Some studies document positive associations between NFPM adoption and both firm performance and pay–performance sensitivity, whereas others report null or even adverse effects. Table 1 summarizes the main studies in this research stream, highlighting their objectives, methods, and key conclusions. A recurring pattern emerges: the effectiveness of NFPMs appears to depend critically on the financial performance dimensions with which they are combined.

Table 1
Empirical studies assessing the relationship between non-financial measures and financial performance

Authors	Country	Findings
Ittner & Larcker (1998)	EUA	After analyzing customer and business-unit data, they found modest evidence that customer-satisfaction measures lead accounting performance. However, they argued that customer behavior and financial outcomes remain relatively stable across most satisfaction levels and only begin to change once certain satisfaction thresholds are reached.
Banker et al. (2000)	EUA	Using a time-series field analysis of 18 hotel chains, they found that customer satisfaction is associated with long-term performance rather than immediate results. They also found a positive association between current non-financial performance and future revenue. The authors argued that this effect is driven mainly by a volume effect rather than a price effect.
Marginson et al. (2010)	United Kingdom	They observed a significant relationship between the use of NFMs and short-termism. It appears that NFMs may foster short-term orientation when used for diagnostic purposes.
Abernethy et al. (2013)	EUA	They found that accounting performance measures (e.g., return on investment) are associated with a longer-term focus. They also showed that NFMs shift managerial attention away from the short term toward long-term activities, although not to the same extent as profitability measures do.
Aguiar & Frezatti (2014)	Brazil	Selecting 150 firms that offered variable compensation to their executives, based on the ranking “Best Companies to Work For,” the authors found evidence that runs counter to expectations: greater importance attributed to NFMs is not positively associated with long-term temporal orientation; on the contrary, the results suggest that a shorter-term orientation may in fact be associated with such performance indicators.
Souza et al. (2017)	Brazil	Using data from 2011 to 2013, they found evidence that compensation based on NFMs, as well as diversified measures (NFMs combined with financial measures), improves future financial performance, as measured by ROA and ROE.
Anjos et al. (2019)	Brazil	The state that there is no evidence that the industry performance variation reduces the impacts that the firms results obtained by the organizations exercise on the executive compensation.
Tahir, Ibrahim & Nurullah (2019)	United Kingdom	They found less income-increasing earnings management when NFPMs are used alongside, or more intensively than, FPMs. Overall, non-financial and long-term metrics shift incentives toward long-term firm value rather than short-term rewards.
Blanes, De Fuentes & Porcuna (2021)	Spain	As Corporate Social Responsability is linked to higher long-term firm value, firms that associate CSR performance to executive compensation place greater weight on equity-based compensation than others.
Cho & Ibrahim (2022)	EUA	The pay–performance sensitivity is stronger in firms that use Non-Financial Performance Measures (NFPMs) than in those that rely solely on financial measures. The use of NFPMs intensifies pay–performance sensitivity as their contractual weight increases and as financial risk rises.
Kharabsheh et al. (2022)	Jordan	Higher Corporate Social Responsability, without effective monitoring, can enable CEO self-serving behavior and ultimately undermine firm value.

Given this complexity, recent studies have begun to clarify these inconsistencies. Cho and Ibrahim (2022) show that NFPMs strengthen pay-performance sensitivity when tied to operational efficiency and CEO-specific objectives. Tahir, Ibrahim, and Nurullah (2019) show that the selection of measures has direct implications for earnings management, reinforcing the view that this is a governance choice with real consequences.

Brazil offers a particularly relevant testing ground for these arguments. Ownership is highly concentrated, board independence varies widely across firms, and disclosure of compensation metrics became mandatory only after CVM Instruction 480/2009. Prior Brazilian evidence is limited and contradictory: some studies find positive effects of NFPMs on future financial performance (Souza et al., 2017), while others find no alignment benefits (Aguiar & Frezatti, 2014). Research on the pay–performance relationship more broadly suggests that executive compensation remains weakly tied to organizational outcomes in this market (Anjos et al., 2019). These institutional characteristics may simultaneously amplify the potential benefits of NFPMs and complicate their implementation, given the heterogeneity in governance quality and disclosure practices across firms.

Taken together, the evidence reveals no consensus on the relationship between NFPMs and compensation. However, it consistently points to one conclusion: the informativeness of compensation contracts depends critically on whether performance evaluation incorporates measures that more directly capture managerial effort. Grounded in the informativeness principle (Holmström, 1979) and supported by recent empirical evidence (Cho & Ibrahim, 2022; Gan et al., 2020), this study posits that firms adopting NFPMs will exhibit a stronger relationship between organizational performance and variable executive compensation. This leads to the central research hypothesis:

• H1: The use of non-financial performance measures strengthens the relationship between organizational performance and variable executive compensation.

METHODOLOGY

Research design and sample selection

We used a panel dataset of publicly traded Brazilian non-financial firms. The sample is non-probabilistic because it includes only firms that disclose both (i) the performance measures used in executive evaluation and (ii) detailed compensation data for statutory executives. These disclosures are obtained from the Reference Form (sections 12.5, 12.6, 13.1, and 13.2), and financial information is retrieved from the Economática® database.

The sample selection followed a multi-stage filtering process to ensure data consistency and comparability across firms and over time. The initial population comprised all firms listed on B3 during the analysis period (391 firms). From this population, financial institutions were excluded due to their distinct regulatory environment and accounting structure (87 firms).

Subsequently, firms with missing or incomplete information on executive compensation and holdings were removed (120), and continuous variables were winsorized at the 1st and 99th percentiles to reduce the influence of extreme values. Additional exclusions were applied to firms with negative equity (65). After applying all filters, the final sample comprised 119 non-financial firms, yielding an unbalanced panel suitable for the empirical analyses.

The selected period begins after the implementation of CVM Instruction 480/2009, which made the disclosure of performance evaluation criteria mandatory, and ends in 2019 to avoid distortions caused by the COVID-19 pandemic.

This sample construction ensures that the panel captures differences in compensation practices, governance structures, and performance indicators while preserving consistency and comparability across firms and over time.

Variables and empirical models

To examine the relationship between financial performance and executive compensation in firms that incorporate NFPMs into their bonus contracts, we employed a linear panel regression. The dependent variable is the average compensation received by executives, including bonuses, profit-sharing, meeting allowances, and other related payments. Financial performance was the primary predictor, and the NFPM dummy variable and several control variables capturing governance structure and firm characteristics were included.

Equation 1 $\begin{array}{l}VCOM{P}_{it}={ø}_{\text{0}}+{ø}_{\text{1}}\left(NFP{M}_{it}\right)+{ø}_{\text{2}}\left(F{P}_{it}\right)+{ø}_{\text{3}}\left(F{P}_{it}\times NFP{M}_{it}\right)+{ø}_{\text{4}}\left(LE{V}_{it}\right)+{ø}_{\text{5}}\left(TE{N}_{it}\right)\\ +{ø}_{\text{6}}\left(IN{D}_{it}\right)+{ø}_{\text{7}}\left(OW{N}_{it}\right)+{ø}_{\text{8}}\left(DUA{L}_{it}\right)+{ø}_{\text{9}}\left(GO{V}_{it}\right)+{ø}_{\text{10}}\left(SIZ{E}_{it}\right)+{ϵ}_{it}\end{array}$

The central coefficient for testing H1 is Ø₃, which captures the moderating effect of NFPM adoption on the relationship between financial performance and variable compensation. A positive and statistically significant Ø₃ would indicate that firms incorporating NFPMs into their incentive contracts exhibit stronger pay–performance sensitivity, consistent with the informativeness principle (Holmström, 1979). In other words, NFPMs are expected to enhance the quality of performance evaluation by providing incremental information about managerial effort, thereby reducing noise in the compensation contract and strengthening the link between observed performance and executive rewards. The coefficient Ø₂, in turn, captures the baseline pay–performance relationship for firms relying solely on financial measures, while Ø₁ reflects any level effect associated with NFPM adoption, independent of performance.

Table 2 presents all the variable definitions:

Table 2
Equation 1 variables

Variables	Definition
VComp	Logarithm of average variable compensation received by executives.
NFPM	Dummy variable equal to 1 if the firm used non-financial performance measures in its compensation contracts, and 0 if it relied solely on financial measures (Cho et al., 2019).
FP	Three accounting one financial variables were used. The accounting variables are: ROE; EBITDA Margin; and return on sales (ROS). The financial variable corresponds to dividends per share (DPS) (Anjos et al., 2015; Cho et al., 2019; Araujo et al., 2019).
Controls
Size	The natural logarithm of total assets, in order to control for firm complexity (Bartov, 1993).
Lev	Leverage, calculated as the book value of debt divided by total assets (Liu et al., 2010).
Own	Ownership concentration (voting) of the three largest shareholders (Sobrinho et al., 2014).
Ind	Proportion of independent directors relative to the total board size (Schiehll & Bellavance, 2009; Gan et al., 2020).
Ten	Managerial tenure in the position (Dechow & Sloan, 1991).
Dual	CEO duality. Dummy variable equal to 1 if there were board members holding executive positions, and 0 otherwise (Brandão et al., 2019).
Gov	Corporate Governance Level. Dummy variable equal to 1 if the firms belonged to special listing segments (N1, N2, or New Market), and 0 otherwise (Sobrinho et al., 2014).

According to Gan et al. (2020), firms may not choose whether to use non-financial performance measures (NFPMs) in compensation contracts at random. This possibility raises an endogeneity concern. As Lennox et al. (2012) note, one way to address this issue is to use the Inverse Mills Ratio (IMR), defined as ϕ(z)/Φ(z), where z is the fitted value from a probit regression.

To construct the probit model, several determinants of NFPM use, identified in the literature, were included. The challenge is selecting valid instruments that are correlated with the endogenous explanatory variables yet uncorrelated with the error term (Raithatha & Komera, 2016).

Among these instruments, Ittner, Larcker, and Rajan (1997) and Said et al. (2003) highlight that financial difficulties (DDFF) may influence the adoption of NFPMs. Firms facing a higher likelihood of failure may engage in greater earnings manipulation to present more favorable results to stakeholders; therefore, such firms tend to be less likely to adopt NFPMs.

Conversely, companies operating in regulated industries (REG) may be more inclined to adopt NFPMs in compensation contracts. Intense competition in regulated sectors may lead to customer loss, prompting firms to adopt mechanisms that promote client satisfaction and retention (Ittner et al., 1997).

Noise in financial measures (NFM) is another exogenous factor that may influence the decision to adopt NFPMs. Because NFPMs can help mitigate information asymmetry between managers and shareholders and enhance organizational performance, firms exposed to noisier traditional metrics may find NFPMs especially useful (Schiehll & Bellavance, 2009).

Firms with stronger growth strategies (STRAG) are also expected to be more likely to use NFPMs (Govindarajan & Gupta, 1985). According to Schiehll and Bellavance (2009), the underlying rationale is that a higher market-to-book ratio may capture the consequences of managerial decisions reflected in market prices but not in accounting information. Thus, adopting NFPMs can help reduce this discrepancy.

Firm size (SIZE) was also included as a determinant of NFPM use, on the assumption that larger firms employ more sophisticated performance-evaluation systems that are often oriented toward shareholder value and growth (Said et al., 2003; Schiehll & Bellavance, 2009).

Following the methodology of Tahir, Ibrahim, and Nurullah (2019), lagged control variables for corporate governance characteristics were included to address endogeneity. These include the proportion of independent directors on the board (IND), the CEO’s tenure (TEN), ownership concentration (OWN), the presence of dual roles among directors (DUAL), and the manager’s age (AGE).

The model to be estimated is as follows:

Equation 2 $\begin{array}{ll}\left[\text{P}\left({\text{NFPM}}_{\text{it}}=1\right)\right]\hfill & ={\rho }_0+{\rho }_1\left({\text{DDFF}}_{it}\right)+{\rho }_2\left({\text{NMF}}_{\text{it}}\right)+{\rho }_3\left({\text{REG}}_{\text{it}}\right)+{\rho }_4\left({\text{STRAG}}_{\text{it}}\right)+{\rho }_5\left(SIZ{E}_{\text{it}}\right)\hfill \\ \hfill & +{\rho }_6\left(AG{E}_{it}\right)+{\rho }_7\left({\text{IND}}_{\text{it}-1}\right)+{\rho }_8\left({\text{TEN}}_{\text{it}-1}\right)+{\rho }_9\left({\text{OWN}}_{\text{it}-1}\right)+{\rho }_{10}\left({\text{DUAL}}_{\text{it}-1}\right)\hfill \\ \hfill & +{ϵ}_{it}\hfill \end{array}$

Table 3 presents the definitions of the variables in equation 2.

Table 3
Equation 2: Variable definitions

NFPM	Dummy variable equal to 1 if the firm generally uses non-financial performance measures, and 0 otherwise.
DDFF	It refers to financial distress. This is a dummy variable that takes the value 1 when firms face financial difficulties. The Altman z-score model was used following Rososchansky (2017) who validated the model for predicting risk in Brazilian firms.
NMF	Noise in financial measures. Calculated using the Fisher z-score of the correlations between return on assets and market return over the three years preceding the analysis period (Schiehll & Bellavance, 2009).
REG	Regulated industries. Dummy variable equal to 1 if the firm operates in a regulated industry, and 0 otherwise (Ittner et al., 1997; Said et al., 2003).
STRAG	Calculated as the three-year average of the market-to-book ratio (e.g., Schiehll & Bellavance, 2009).
AGE	The CEO’s age.

All regressions include industry and year fixed effects, and standard errors are clustered at the firm level to address heteroscedasticity and autocorrelation.

Addressing endogeneity concerns

Compensation research is highly susceptible to endogeneity stemming from simultaneity, omitted variables, and non-random selection into incentive structures (Antonakis et al., 2010; Lennox et al., 2012). This study employs three complementary strategies to address these concerns.

First, firm fixed effects control for time-invariant unobservable heterogeneity — including governance culture, managerial ability, and internal monitoring quality — that may jointly affect compensation and performance. Second, following Li (2006), a lagged specification ensures that performance precedes the compensation decision, mitigating simultaneity bias. Third, because the decision to adopt NFPMs may be endogenous, a Heckman two-step procedure corrects for potential sample selection bias. As noted by Lennox et al. (2012), one way to address this issue is to use the Inverse Mills Ratio (IMR), defined as φ(z)/Φ(z), where z is the fitted value from the probit regression. A probit model estimates the probability of NFPM adoption as a function of financial distress, regulated industry status, noise in financial measures, growth strategy, firm size, and lagged governance characteristics. The IMR derived from this model is then included as a control variable in the second-stage compensation regressions. A significant IMR coefficient indicates that selection into NFPM use is non-random, validating the Heckman correction and increasing confidence that the estimated pay–performance effects are not driven by systematic differences between firms that adopt NFPMs and those that do not.

Firms facing high information asymmetry, volatile financial performance, or governance frictions are more likely to adopt NFPMs, and these characteristics may directly affect compensation levels. Without correcting for this, pay–performance estimates could be biased in either direction. By combining fixed effects, lagged models, and the Heckman correction, the analysis mitigates multiple sources of endogeneity.

RESULTS

Descriptive statistics

Initially, we identified 76 firms that included NFPM in their CEOs’ compensation contracts. Among key indicators, we found that, on average, 66% of companies that incorporated NFPM into their bonus contracts used executive performance appraisals. Additionally, 36% used customer satisfaction indices, and 20% used service quality. Other prominent measures included ESG (15%), workplace safety (14%), and employee satisfaction (12%) (see Fig. 1).

Figure 1
Performance measures incorporated into compensation contracts

Descriptive statistics (Table 4) show that approximately 64% of firms in the sample adopt NFPMs in their executive compensation contracts, suggesting that NFPM use is widespread but not universal in Brazil. Executive compensation and firm size exhibit considerable heterogeneity, as do profitability, leverage, and governance indicators, supporting the use of panel fixed-effects estimation.

Table 4
Sample’s descriptive statistics

Variables	Mean	Median	S.D.	Max	Min
NFPM	0,641	1,000	-	1,000	0,000
Compensation (in millions)	0.944	0.602	1.082	11,919	0.017
Total assets (in millions)	99.935,580	7.630,779	144.401,900	332.726,900	1,965
Ln (Compensation)	5,758	5,779	0,442	6,677	4,401
ROE	43,286	19,800	52,796	112,998	-598,800
EBITDAM	-50.176	39,35	43,516	99,53	-116,964
ROS	-27,180	14,750	34,238	68,106	-140,884
DPS	0,737	0,369	1,202	15,220	0,000
Leverage	8,184	2,800	7,899	18,460	0,200
Board Independence	0,322	0,285	0,248	1,000	0,000
Ownership (%)	57,784	56,206	21,606	6,000	96,000
CEO Tenure	7,000	5,000	7,000	31,000	1,000

The performance variables (ROE, EBITDAM, ROS, and DPS) show meaningful cross-sectional and temporal variation, which is essential for identifying differences in pay–performance sensitivity across firms and over time.

The main performance variables range from -116.964 to 99.53 for EBITDAM, from -598.8 to 112.998 for ROE, and from -140,884 to 68.106 for ROS. These ranges indicate that the sample includes firms that reported both profits and losses over the period under analysis.

The average ownership concentration of the three largest shareholders (PMA) was 57%, and the maximum observed value (96%) aligns with Anjos et al. (2019). Average leverage was 818,4%, and the mean proportion of independent board members was 32%.

Pay–performance results: Contemporaneous model (t)

Table 5 reports the estimation results for Model 1, which examines how NFPM use influences the relationship between firm performance and executive compensation, as previously defined—columns 1 through 4 present results for the performance measures employed in the study. The regression specifications are similar, differing only in the performance metric included. The results in this table correspond to a contemporaneous pay–performance relationship.

Table 5
Results of the estimation of the determinants of compensation

Variables	(1) VCOMP	(2) VCOMP	(3) VCOMP	(4) VCOMP
	Coef P-value	Coef P-value	Coef P-value	Coef P-value
NFPM	0,066* (0,069)	-0,035 (0,431)	-0,001 (0,991)	0,053 (0,122)
ROE	0,644*** (0,000)
NFPM*ROE	-0,222 (0,225)
EBITDAM		0,001 (0,337)
NFPM*EBITDAM		0,004** (0,018)
ROS			-0,106 (0,577)
NFPM*ROS			0,659*** (0,004)
DPS				0,038 (0,153)
NFPM*DPS				0,003 (0,911)
LEV	-0,034 (0,639)	0,015 (0,834)	-0,023 (0,754)	-0,047 (0,510)
SIZE	0,395*** (0,000)	0,370*** (0,000)	0,371*** (0,000)	0,384*** (0,000)
OWN	-0,001 (0,253)	0,000 (0,556)	0,000 (0,878)	-0,000 (0,651)
IND	-0,139** (0,018)	-0,149** (0,012)	-0,086 (0,156)	-0,146** (0,013)
TEN	0,014 (0,387)	0,013 (0,414)	0,005 (0,973)	0,007 (0,657)
DUAL	0,213*** (0,000)	0,210*** (0,000)	0,213*** (0,000)	0,176 (0,000)
GOV	-0,189*** (0,000)	-0,226*** (0,000)	-0,240*** (0,000)	-0,152*** (0,000)
Constant	1,931*** (0,000)	2,226*** (0,000)	2,243*** (0,000)	2,073*** (0,000)
Mean VIF	2,04	2,10	1,94	2,09
Interaction VIF	4,48	4,86	3,94	4,75
Hausman	Fixed effects	Fixed effects	Fixed effects	Fixed effects
Heteroscedasticity	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00
Autocorrelation	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00
R2	0,46	0,47	0,42	0,43
N	765	725	793	790

• Source: Data obtained from Economatica® and the Reference Form.
• ^{***, **, *}
  Note. indicate significance at the 1%, 5%, and 10% levels, respectively. All variables were winsorized at the 1st and 99th percentiles to address outliers.

For the model structure, the Hausman test indicated that the fixed-effects model was most appropriate for each regression. Each regression was estimated with industry and year controls, following Cho et al. (2019). Additionally, each regression was corrected using robust standard errors to account for heteroskedasticity and autocorrelation.

The results indicate that the NFPM variable was statistically significant only at the 10% level in column (1), consistent with Santos (2018), who reports a positive and significant relationship between non-financial performance indicators and executive compensation in Brazilian family firms. Among the performance measures, only ROE was significant at the 1% level for the full sample (column 1), corroborating evidence from Anjos et al. (2019) and Ferreira et al. (2018).

Regarding the interaction terms, the coefficients for NFPM*EBITDAM (significant at 5%) and NFPM*ROS (significant at 1%) were both positive, indicating that in firms using NFPMs, executive compensation is more sensitive to financial performance than in firms relying solely on financial measures. These findings do not allow us to reject H1. In contrast, the interaction terms NFPM*DPS (column 4) and NFPM*ROE were not statistically significant: the former, although positive, had a high p-value, while the latter was negative but not significant at conventional levels.

The control variables showed consistent signs and magnitudes across specifications. As expected, firm size was a positive and significant determinant of compensation, consistent with Araujo, Ribeiro & Moraes (2019), Ferreira et al. (2018), and Freitas et al. (2020), who also find that larger firms tend to pay higher executive compensation. Moreover, the negative and significant coefficient on IND in all regressions aligns with Brandão et al. (2019), suggesting that a higher proportion of independent directors may constrain managerial influence over board compensation decisions. Finally, the positive and significant effect of DUAL across all columns reinforces the findings of Bugeja, Silva Rosa, Duong, and Izan (2012), indicating that boards partially composed of own-firm executives may be more likely to approve compensation packages that favor executives at the expense of shareholder interests.

To further assess the robustness of H1, the model was re-estimated using a lagged specification in which performance in period (t) is related to compensation in the subsequent period (t+1). According to Li (2016), using lagged variables to examine the pay–performance relationship is a straightforward way to address the simultaneity problem between performance and compensation variables. Antonakis et al. (2010) highlight that this form of endogeneity is among the most debated issues and poses a challenge for researchers in economics and finance.

The results in Table 6 indicate that the estimated coefficients on the interaction terms are similar in magnitude to those in the contemporaneous regressions (Table 5). The interactions NFPM*MEBITDA and NFPM*ROS are statistically significant and positive. This suggests that using NFPMs in compensation contracts strengthens the link between current performance and future compensation, providing additional support for H1 and reinforcing that the moderating effect of NFPMs on pay–performance sensitivity is not contemporaneous but extends to subsequent compensation decisions.

Table 6
Results for the determinants of compensation in period (t+1)

Variables	(1) ROE	(2) EBITDAM	(3) ROS	(4) DPS
	Coef P-value	Coef P-value	Coef P-value	Coef P-value
NFPM	0,083* (0,067)	0,004 (0,930)	0,017 (0,648)	0,058 (0,132)
ROE	0,575*** (0,004)
NFPM*ROE	-0,294 (0,198)
EBITDAM		0,001 (0,387)
NFPM*EBITDAM		0,002** (0,043)
ROS			-0,105 (0,656)
NFPM*ROS			0,563** (0,039)
DPS				0,023 (0,424)
NFPM*DPS				0,011 (0,736)
Constant	1.961*** (0,000)	2,341*** (0,000)	2,330*** (0,000)	2,222*** (0,000)
Control variables	Included	Included	Included	Included
Hausman	Fixed effects	Fixed effects	Fixed effects	Fixed effects
Interaction VIF	5,17	4,94	3,92	4,54
Mean VIF	2,19	2,11	1,94	2,06
Heteroscedasticity	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00
Autocorrelation	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00
R2	0,44	0,47	0,42	0,42
N	631	600	656	649

• Source: Economatica® and Reference Form.
• ^{***, **, *}
  Note. indicate significance at the 1%, 5%, and 10% levels, respectively. The variables were winsorized at the 1% and 99% levels to treat outliers.

According to Li (2016), one way to address endogeneity, particularly when an unobservable variable may simultaneously affect both compensation and performance, is to use fixed effects. The two-stage Heckman method is an alternative approach for handling endogeneity arising from sample selection bias (Lennox, Francis & Wang, 2012).

As Antonakis, Bendahan, Jacquart, and Lalive (2010) note, when treatment selection is not modeled (i.e., when participant selection is not random), the estimates will be inconsistent because the unobserved variance affecting selection may be correlated with that affecting the dependent variable. We addressed this issue by including the inverse Mills ratio, derived from a probit model (Model 2), as a control variable in Equation (1).

As shown in Table 7, the results from the two-stage Heckman procedure are consistent with those reported in Table 6. In line with these findings, a positive and significant relationship emerges between NFPM and MEBITDA, as well as between NFPM and ROS.

Table 7
Determinants of compensation – Heckman Model

Variables	(1) ROE	(2) EBITDAM	(3) ROS	(4) DPS
	Coef P-value	Coef P-value	Coef P-value	Coef P-value
NFPM	0,060 (0,108)	-0,075 (0,120)	-0,015 (0,646)	0,028 (0,411)
ROE	0,595*** (0,000)
NFPM*ROE	-0,211 (0,268)
EBITDAM		-0,001 (0,734)
NFPM*EBITDAM		0,005*** (0,004)
ROS			-0,171 (0,388)
NFPM*ROS			0,638*** (0,006)
DPS				0,036 (0,178)
NFPM*DPS				0,006 (0,830)
IMR (mills inverse)	-0,115* (0,098)	-0,256*** (0,001)	-0,291*** (0,000)	-2,992*** (0,000)
Constant	2,391*** (0,000)	3,193*** (0,000)	3,229*** (0,000)	3,096*** (0,000)
Control variables	Included	Included	Included	Included
IMR VIF	3,23	3,63	3,33	3,34
Interaction VIF	4,98	5,11	3,95	4,73
Mean VIF	2,44	2,47	2,23	2,36
Hausman	Fixed effects	Fixed effects	Fixed effects	Fixed effects
Heteroscedasticity	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00	Prob>chi2 = 0,00
Autocorrelation	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00	Prob > F = 0,00
R2	0,45	0,48	0,43	0,44
N	749	712	775	771

• Source: Economatica® and Reference Form.
• ^{***, **, *}
  Note. indicate significance at the 1%, 5%, and 10% levels, respectively.

The NFPM*ROE and NFPM*DPS interaction terms, with negative and positive signs, respectively, were not statistically significant. Based on the NFPM*MEBITDA and NFPM*ROS interactions, the results provide evidence of a positive relationship between performance and compensation in firms that used NFPMs compared with those that relied solely on financial measures.

It was observed that the IMR has a negative and significant coefficient in columns (2)–(4). According to Lennox et al. (2012), the statistical significance of the inverse Mills ratio indicates selection bias in the first-stage model, and its inclusion in the second-stage model is considered an effective control for such bias. Overall, the Heckman results consistently support the earlier analyses, indicating that the findings were not affected by sample selection bias.

It is also worth noting that when the inverse Mills ratio was included in the regression with lagged variables, the results remained consistent with previous findings: NFPM*ROS was the only significant interaction term, and the control variable IMR was significant. This confirms that, in general, sample-selection bias did not affect the results of this study.

DISCUSSION

The findings of this study provide consistent evidence that the use of Non-Financial Performance Measures (NFPMs) enhances the informativeness of executive compensation contracts in Brazilian firms. Across all econometric specifications, including contemporaneous, lagged, and Heckman-corrected models, the interaction terms between NFPMs and operational performance indicators (EBITDA margin and ROS) remain positive, statistically significant, and economically meaningful. These results robustly support the informativeness principle, which holds that performance metrics that provide incremental, effort-related information should be incorporated into compensation arrangements.

The positive moderation effects observed in this study align with prior research indicating that non-financial measures mitigate managerial short-termism (Bouwens & Lent, 2006). By complementing traditional financial indicators with forward-looking, strategically relevant measures, NFPMs shift managerial focus away from narrow, earnings-based targets. This is especially salient in the Brazilian context, where financial outcomes may be influenced by macroeconomic instability, accounting discretion, and varying corporate governance quality.

Our results reinforce this interpretation: NFPMs increase the sensitivity of compensation to operational results, such as EBITDA margin and ROS, which reflect managerial efforts in productivity, customer satisfaction, and process improvements. These measures are inherently tied to value creation and less susceptible to external noise or short-term accounting manipulation.

An important insight from this study is that NFPMs improve the informativeness of operational performance but not of accounting-based returns (ROE) or board-determined policies (DPS). This distinction is consistent with both theory and the empirical literature. The absence of significant moderation effects for ROE and DPS warrants careful interpretation. ROE is heavily influenced by leverage and capital structure decisions that lie largely outside operational management, introducing systematic noise that dilutes its ability to reflect individual managerial effort. When compensation is tied to ROE in the presence of NFPMs, the incremental informational value of non-financial measures may be insufficient to overcome this structural limitation. This interpretation aligns with the controllability principle in agency theory, which suggests that performance measures should be filtered for factors beyond managerial control, a condition that ROE frequently violates in highly leveraged or capital-intensive firms. DPS, in turn, is primarily determined by board-level dividend policy rather than by operational decisions, making it a poor proxy for managerial effort regardless of whether NFPMs are present.

The non-significance of NFPM*DPS therefore reflects not a failure of NFPMs per se, but rather the inherent limitations of dividends per share as a performance criterion in executive incentive contracts. Taken together, these results suggest that the informational benefits of NFPMs are not universal but depend critically on whether the financial performance dimension they are paired with is sufficiently sensitive to managerial actions. Thus, NFPMs appear to enhance alignment specifically where managerial discretion is greatest. The economic significance of these findings further supports their relevance. A one-standard-deviation increase in EBITDA margin is associated with an approximately 17.4% increase in variable compensation in firms adopting NFPMs, relative to firms relying solely on financial measures.

The effect is even more pronounced for ROS: a one-standard-deviation increase corresponds to an approximately 22.6% increase in variable compensation. The stronger effect of ROS relative to EBITDAM is economically meaningful because ROS captures the full impact of managerial decisions on profitability, including cost management, pricing strategy, and operational efficiency, making it a more comprehensive signal of managerial effort than the operating margin. These magnitudes suggest that NFPMs do not merely exert a statistically detectable influence on compensation; they produce economically substantial differences in how performance is rewarded across firms. The core findings converge with Cho and Ibrahim (2022), who demonstrate that NFPMs heighten pay–performance sensitivity, particularly when tied to operational efficiency and CEO-specific objectives. Similarly, the results support Gan, Park, and Suh’s (2020) view that NFPMs complement longer-term incentive mechanisms by reinforcing strategic, value-oriented behavior. These results are also consistent with earlier foundational evidence. Banker et al. (2000) demonstrated that non-financial indicators positively predict future revenue growth in the hotel industry, suggesting that NFPMs capture forward-looking dimensions of performance that financial metrics alone cannot reflect. Similarly, Ittner and Larcker (1998) showed that customer satisfaction measures serve as leading indicators of accounting performance, reinforcing the view that NFPMs improve the informativeness of incentive contracts by capturing effort-related signals that precede financial outcomes. The present study extends this evidence to an emerging market context, where such informational benefits may be particularly valuable given the greater volatility and lower reliability of purely financial performance signals.

Not all prior evidence points in the same direction. Hyvönen (2007) found that customer-centered performance measures did not improve firm performance in Finland. In contrast, Abernethy et al. (2013) concluded that NFPMs do not uniformly redirect managerial attention toward the long term. These divergent findings likely reflect context-specific conditions, including industry characteristics, governance quality, and the degree of strategic alignment between NFPMs and firm objectives, which moderate the effectiveness of non-financial measures.

In the Brazilian context, Aguiar and Frezatti (2014) reported that greater reliance on NFPMs was paradoxically associated with a shorter-term managerial orientation. This finding directly contrasts with the present study’s results. One plausible explanation for this divergence lies in the composition of NFPMs in our sample: the predominance of operational and customer-oriented measures, such as executive performance appraisals, customer satisfaction indices, and service quality indicators, may be more effective at reinforcing long-term value creation than the broader set of measures examined in prior Brazilian research. This interpretation aligns with Cho and Ibrahim’s (2022) finding that NFPM effectiveness is strongest when measures are tied to CEO-specific and operationally relevant objectives.

Notably, the significant effects in the Brazilian context provide a powerful extension of this literature: they suggest that NFPMs are not merely a feature of sophisticated compensation structures in developed markets but also a valuable governance instrument in emerging economies with weaker monitoring and less consistent reporting quality.

Brazil’s corporate environment, marked by high ownership concentration, heterogeneous governance quality, and elevated earnings volatility, creates conditions in which financial metrics alone may be insufficiently informative. NFPMs appear to fill this gap: their consistent moderating effect across models suggests they help boards better observe managerial effort and distinguish between controllable and uncontrollable performance factors, making them particularly relevant where traditional governance mechanisms are less effective.

This study advances the literature in at least three ways. First, it provides evidence from an emerging economy, where the informativeness of NFPMs has been understudied. Second, it clarifies inconsistent findings in prior Brazilian research by showing that NFPM effectiveness varies across dimensions of financial performance. Third, it demonstrates that NFPMs retain their explanatory power after correcting for endogeneity, suggesting that their impact on pay–performance sensitivity is substantive rather than driven by firm-selection patterns.

The results closely align with predictions from Agency Theory. By improving the signal quality of performance measures, NFPMs enable firms to design incentive contracts that reduce managerial risk and better align with shareholder interests. In summary, NFPMs serve as informational complements that enhance incentive alignment in settings of high uncertainty and imperfect monitoring, conditions that characterize many Brazilian-listed firms.

CONCLUSIONS

This study examined whether the use of NFPMs in executive compensation contracts affects the pay–performance relationship among Brazilian firms. Using an unbalanced panel of 119 companies from 2012 to 2019, we analyzed both contemporaneous and lagged compensation models.

Across all specifications, the interaction terms NFPM × EBITDAM and NFPM × ROS were consistently positive and statistically significant, suggesting that NFPMs may strengthen the alignment between executive compensation and operational performance. In contrast, interactions with ROE and DPS were not statistically significant, consistent with the interpretation that NFPMs tend to enhance informativeness primarily in performance dimensions more directly influenced by managerial decisions. These results broadly align with Agency Theory predictions. By improving the signal quality of performance measures, NFPMs may enable firms to design incentive contracts that better align managerial behavior with shareholder interests, reducing moral hazard and curbing short-termism. However, the magnitude and significance of these effects varied across performance dimensions, suggesting that the benefits of NFPMs are conditional rather than universal, a nuance that distinguishes the present findings from those in studies conducted in more institutionally developed markets.

The findings may have implications for boards of directors, compensation committees, and regulators. For boards and compensation committees, the results suggest that incorporating NFPMs tied to operational efficiency and strategic objectives may help create more balanced incentive contracts, reducing reliance on short-term financial metrics alone. For regulators and oversight bodies, the evidence suggests that requiring disclosure of performance evaluation criteria may be valuable, particularly in emerging markets where governance quality varies widely across firms.

Several limitations constrain the interpretation of these findings. The NFPM variable is operationalized as a binary indicator, which does not capture variation in the type, weight, or quality of the non-financial measures adopted. Unobservable time-varying factors may also influence both compensation and performance, and residual omitted-variable bias cannot be fully ruled out. Additionally, industry heterogeneity may condition the extent to which NFPMs influence the pay–performance relationship in ways not fully captured by the model.

These limitations suggest several avenues for future research. Subsequent studies could examine specific categories of NFPMs, such as operational, customer-related, innovation-based, or ESG-oriented, to assess which types have the strongest effects on incentive alignment. Research might also explore how the contractual weight assigned to NFPMs shapes compensation sensitivity, or whether NFPM effectiveness varies across industries with distinct strategic or regulatory characteristics. Future work could further investigate how governance mechanisms, including board independence, ownership concentration, and audit quality, interact with NFPM adoption to influence the overall effectiveness of executive incentive systems.

Open Data:

data is available on demand from referees.

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Correspondence

Correspondence concerning this article should be addressed to Luiz Carlos Marques dos Anjos, Avenida dos Economistas, s/n, Cidade Universitária, Recife, Pernambuco, Brazil. ZIP Code: 50670-901. E-mail: [e-mail]

Edited by

EDITORIAL BOARD

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Almir Martins Vieira

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David Ferreira Lopes Santos

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Vitória Batista Santos Silva

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Publishing coordination

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Sofia Lelis

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Publication Dates

• Publication in this collection
  30 Oct 2026
• Date of issue
  2026

History

• Received
  26 Jan 2026
• Accepted
  22 May 2026