Market Competition,Managerial Incentives and Agency Cost

Abstract

This study investigates the determinants of board of director compensation from the view of strategic management. Specifically, this study examines the association between product market competition and directors’ compensation for a sample of 524 listed firms in Malaysia from 2010 to 2014. We find that there is a positive relationship between a competitive firm and its compensation to its directors. Our research indicates that managerial incentives reflect more of talent appreciation, rather than purely for acknowledging better performance or a bigger size firm. This research contests the use of agency theory and managerialism in explaining directors’ compensation, especially for the developing country context of Malaysia. Our findings also imply that firms may pay higher compensation in a competitive market.

Keywords

Product market competition managerial compensation director incentives agency cost managerialism

Introduction

Managerial incentive has been advocated as a key component in bridging the agency issue between principal (shareholder) and agents (Jensen & Murphy, 1990; Tosi, Werner, Katz, & Gomez-Mejia, 2000). There is extensive literature surrounding meta-analysis research in strategic management linking the incentives with a firm’s performance (e.g., Brick, Palmon, & Wald, 2006; Cao, Liu, & Tian, 2011; Olaniyi, Simon-Oke, Obembe, & Bolarinwa, 2017; Sigler, 2011; Tosi et al., 2000; Wasserman, 2006). Theoretically, if a firm has higher profits, accordingly the manager is compensated higher.

Interestingly, this view of profit–compensation link is still the subject of much debate in economics and finance. Tosi et al. (2000) revealed that profit only contributed 4 per cent to the director compensation variance. Yet, several studies including Zhou (2000), Cao et al. (2011), Sigler (2011) and Wasserman (2006) documented firm performance contributing significantly and positively to incentives. This positive link between performance and incentives confirms the managerial alignment view of agency theory, where the director (agent) gives their best effort to induce firm performance because of their personal compensation. Another view, managerialism, refutes this postulation by showing that there is small or no effect of performance on incentives. This has been well documented in the findings of Finkelstein and Boyd (1998) and Tosi et al. (2000). From the managerial perspective, principal and agent have different views on firm operations, where directors believe that profit will benefit the owner; hence, directors have keen interest in increasing firm’s size rather than maximizing profit. This occurs because doing so may lead to more incentives, power and prestige. In fact, the managerialism view argues that this behaviour may lead to a negative link between performance and incentives. For example, Core, Holthausen, and Larcker (1999) and Brick et al. (2006) suggested that performance has a negative effect with incentives. Both views coexist without a clear consensus as to whether or not director payment is driven by performance.

This research offers a new perspective to explain the managerial compensation by gauging with strategy management. Linking compensation with profit seems to ignore the ‘ego’ of manager, which is actually the root of evil in agency cost. Rather than studying profit–compensation linkage, we investigate the effect of product market competition (hereafter PMC) on managerial compensation in explaining agency cost and managerialism.

A manager’s main task is to improve firm efficiency for optimum profits. While this is a significant and demanding role, managers are aware that they are not irreplaceable. To gain a better bargaining position, managers tend to be guilty of managerial entrenchment. In the managerial entrenchment perspective, PMC plays an important role in managerial incentives. The ability of a manager to survive in high levels of competition implies that they have superior skills, leading to better compensation (Jung & Subramanian, 2017). A principal (shareholder) hires an agent (manager) in a competitive market for talented managers. However, the agent, who is directly involved with firm operations, will better understand the intensity of competition and their ‘value’ or ability compared to their peers. This leads to higher bargaining position for the agent and indeed broadens the agency cost. On the other hand, the principal, who now knows the value of their agent’s ability in intense competition, will rationally retain their agent. Therefore, to narrow the agency cost and keep their superior agent, a higher incentive is offered.

In a competitive environment, paying directors based on average market pay is not efficient. Mediocrity-based pay will not help attract and retain talented directors nor will it encourage them to grab opportunities in value-added investments. That is to say, directors choose to join companies that pay them attractive incentives (Jung & Subramanian, 2017). Yannopoulos (2011) suggested that seizing each opportunity and strategy newly available in the market is vital in order to improve the competitive position of companies. Therefore, companies pay higher incentives in a competitive environment to attract and retain talented directors.

Frydman and Jenter (2010) explained the reasons of rising director incentives by using a market competition approach. Market competitiveness increases demand for managerial talent in companies, and, therefore, directors’ pay rises. However, several findings contend that the positive link between PMC and director compensation is an effort to induce managers to exert more effort. Furthermore, this tendency reflects an attempt to reduce agency problems, especially where the managerial decisions made concern matters affecting the stockholders’ wealth or attracting or retaining talented executives in the company (Aoki, 1982; Bulan, Sanyal, & Yan, 2010; Cuñat & Guadalupe, 2005; Dam, 2015; Jensen & Murphy, 1990; Karuna, 2007). Building on these theoretical assumptions, we aim to examine the association between PMC and managerial compensation for firms in the relatively small emerging market of Malaysia.

Malaysia offers unique characteristics for this research area. As a developing country, Malaysia’s number of new businesses registered and listed are steadily increasing. This is indicative that the level of PMC increases from year to year due to many new competitors’ entry into the market. At the same time, the competitive index increased from 4.87 in 2010 to 5.23 in 2016, implying a higher PMC in Malaysia. Yet, scant research deeply explores the Malaysian context, particularly regarding for the impact of PMC on managerial incentives.

Table 1 shows how both agency theory and managerialism insufficiently explain the incentive factors for the Malaysian context. QL resources have the largest compensation compared to its peers, IQ Group and Lay Hong. However, the ratio of incentives to total assets of QL is the lowest compared to the other two companies. In terms of ratio of compensation to income, QL is the second after Lay Hong. This shows that both agency theory and managerialism cannot be used for the Malaysian context. If compensation is driven by total assets, as is characteristic of managerialism, the ratio for QL should be the highest, not the lowest. If compensation is driven by performance as argued by agency theory, the ratio for QL should not be the second. In fact, Table 1 shows that IQ Group and Lay Hong have the highest ratio of incentives to assets, and incentives to income, respectively.

Interestingly, when we match compensation with PMC, it strengthens our conjecture. QL resources as the highest compensation paid to a director is in the first quartile for concentration ratio (PMC measurement, furthers details in the third section). Meanwhile, Lay Hong as the lowest compensation paid to a director is in the third quartile for concentration ratio. Therefore, the Malaysian context is also in line with our hypothetical argument that PMC may be the driver for director compensation.

In short, this study is essential to investigate the relationship between PMC and other determinants with managerial incentives of listed companies in Malaysia. The study provides clear and useful information on whether the PMC has a significant relationship with managerial compensation. Our research is different from previous research in three respects. First, instead of using a developed market as the sample, we choose the developing market of Malaysia. Note that a developing market has a different intensity of market competition as compared to a developed market due to its business cycle that is still growing. Second, our market competition is different from previous research, such as Fernández-Kranz and Santaló (2010) and Li et al. (2013), due to the research context and data availability. We only use market concentration, market size and product differentiation as PMC proxies. We expand on this method in the third section.

This study’s contribution is threefold. First, we add to the literature by extending the understanding of this research area within a small emerging market. Second, we document the empirical findings for the relationship between PMC and director compensation. Third, we further establish the fact that compensation is not solely explained by agency issue nor managerialism, but rather using a strategic view.

Table 1.

Selected Incentives, Incomes, Assets and PMC for the Year of 2015

Company	Sectors	Incentives (RM in Thousands)	Net Income (RM in Thousands)	Total Assets (Rm in Thousands)	Incentives/Assets (%)	Incentives/Income (%)	PMC (CONC)
QL resources	Consumer	9,362	191,364	2,585,268	0.4	14.6	Q1
IQ group	Consumer	4,157	24,196	155,896	2.7	4.9	Q2
Lay Hong	Consumer	2,881	19,669	427,374	0.7	17.2	Q3

Source: Calculated from annual report.

The rest of this article is organized in the following manner: the second section addresses the theoretical concepts and literature review; the third section describes the data and methodology; the fourth section reports the empirical findings and discusses it by synthesizing it with theory and finally, the fifth section presents conclusions.

Literature Review

Accounting and finance have extensively reported on the determinants of director compensation, and yet there is no consensus regarding its main driver. From the perspective of managerialism, compensation is driven by the views of the director due to his/her power in the firm’s operations. Managerialism entails that directors have high discretionary power in making every decision in company. This theory argues that, just as executives have the authority in making decisions, they also seek and prioritize activities that have high monetary values (Seth & Dastidar, 2009). Moreover, directors prefer to enlarge the firm’s size because it will increase their pride and bargaining position. This can lead to situations where directors and stockholders must negotiate with each other to obtain a mutual agreement in contract. According to Tosi et al. (2000), with the bargaining approach, both parties are not to be left out given that stockholders who do not agree with the decision of executives will sell the stocks, refuse to buy additional stocks or even remove the manager with the approval of the board of directors and the majority stockholders. However, executives still hold significant bargaining power in the case that stockholders allocate low incentive pay to them. For example, executives are able to reduce contribution of efforts and also make inefficient decisions.

Managerial positions have the discretionary power in determining whether to actively or inactively compete in the market. High commitment to this company position, hence, depends on the incentives paid to them. A company, which has many rivals in market, requires extra efforts by its executives to compete in the market. As extra efforts necessitate sustaining for the long term, stockholders are more willing to approve the high incentives to executives. Several researchers approve the significant and positive relationship between PMC and managerial incentives, which shows the relevancy of managerialism theory (Bhawsar & Chattopadhyay, 2015; Bulan et al., 2010; Cuñat & Guadalupe, 2005; Jensen & Murphy, 1990; Karuna, 2007).

According to Jensen and Murphy (1990), PMC is an external force that happens naturally in the market. Executives who fail to manage the companies in a competitive environment unable to sustain their position in the long term.

Meanwhile, another view addresses compensation as a tool to reduce agency cost. Optimal incentive schemes seem to be able to prevent principle and agent problems. This is due to high PMC leading to high managerial incentives and high stockholders’ wealth (if the agents manage the company well). Previous research uses agency theory to support their results and show a significant and positive relationship between PMC and managerial incentives (Bulan et al., 2010; Cuñat & Guadalupe, 2005; Jensen & Murphy, 1990; Karuna, 2007).

According to Dam (2015), as PMC is a natural force facing every company, it is worthy to investigate the impact of PMC on managerial incentives. High PMC only leads to greater return, thanks to the efforts in cost reduction by executives. As high PMC requires talented directors to exert serious effort, smart and hard-working directors are highly welcome to join or stay in the companies. However, directors who have this talent are ‘picky’ as they only join or stay at companies if their pay is duly high. In other words, bargaining power also can be raised if directors are particularly talented, especially while negotiating a pay that reflects their educational background and skills which is within their rights (Cunat & Guadalupe, 2009).

Yet few research studies focus on the developing country context to test the relationship between PMC and compensation. That is, most findings on this topic have been conducted in developed countries. For example, Cuñat and Guadalupe (2005) used a sample of 22,183 manufacturing firms in the UK from 1992 to 2000, studying particularly experimental design. The results prove that managerial position receives high and increasing incentives in a competitive environment. Karuna (2007) has conducted research consisting of 5,262 observations from 706 companies in 110 industries from 1992 to 2003. This study also finds that there is a significant and positive relationship between product substitution and market size with managerial incentives. On the other hand, entrance costs with managerial incentives demonstrate a negative relationship. Thus, when PMC increases, managerial incentives also increase.

Cuñat and Guadalupe (2009) again tested PMC compensation using S&P1500 index from 1992 to 2000. After using first-stage and two-stage least squares regressions, they find that PMC is significantly and positively related to managerial incentives. Top executives are compensated with high incentives when the companies face high competition pressure. The willingness to pay high incentives is due to the requirement of increasing effort and talent in the high PMC. Beiner, Schmid, and Wanzenried (2011) presented a study using more than 600 observations of 200 companies in Switzerland from 2002 to 2005. Their multivariate panel results show that competitive companies allocate high incentives to managers. This is due to the rising marginal cost of poor managerial efforts in a highly competitive environment, leading competitive companies to allocate high incentives to managers.

There are also conceptual studies surrounding this topic, including the studies by Schmidt (1997) and Wu (2012). Their studies show that compensation is reduced when there are many competitors in the market. Competition not only reduces companies’ income, but furthermore, the marginal profit will reduce if companies have a high cost of production. Due to too focused on cost reduction, the managerial incentives are reduced in a competitive market. The result also shows that despite the low incentive payout during competitive times, managerial positions are required to contribute substantial effort as they face a high threat of liquidation. Hence, despite high managerial efforts in a high PMC, this climate can lead to a reduction in managerial incentives.

Additionally, Vrettos (2013) used 540 firms’ annual observations of 46 scheduled passengers in the USA from 1992 to 2009. The study employs second-stage regression for its methodology. This study also claims that there is a significant and negative relationship between PMC and managerial incentives by distinguishing systematic risk from managerial incentive schemes, leaving only unsystematic risk. Systematic risk is uncertainty facing every company in the same industry, whereas unsystematic risk is uncertainty due to company behaviours in choosing which product to produce or sell. Determinants of unsystematic risk, which are influenced by strategic competition, are used to determine managerial incentive scheme. Hence, the study concludes that reduction of PMC will cause incremental in managerial incentives. Therefore, based on the literature, the research hypothesis is: there is a significant relationship between PMC and managerial incentives.

Research Objectives

The main objective of this research is to investigate the role of PMC on managerial incentives. It is built under two important theoretical frameworks which are managerialism theory and agency theory. Additionally, this research also investigates the effects of firm characteristics such as profitability, firm’s size and firm’s leverage on the managerial incentives.

Theoretical Framework

This research builds its theoretical framework from two main theories: agency theory and managerialism theory. It shows that PMC may affect managerial competition; hence, Figure 1 shows that this study has one dependent variable, which is managerial incentives and one main independent variable, which is PMC. Meanwhile, the firm characteristics, such as firm age, firm growth and leverage, are the control variables.

Managerialism theory is one of the earliest economic theories that explains the relationship between executives and stockholders. This theory defines that managerial position has high discretionary power in making every decision in company. Before the mid-1970, this theory is well known and applied in most companies (Utset, 1994).

This theory is still applicable today, as executives are authorized to make decision about investment and operations in companies (Utset, 1994). As executives have the authority in making decisions, they only act and prioritize activities that have high monetary values as their pay is based on performance indicators (Seth & Dastidar, 2009). According to Beasley (2012), executives seem to be introvert in taking risks and reluctant to make changes in managements or operations of companies if their efforts do not pay off with high incentives. In other words, they only act when their efforts are paying off.

According to Jensen and Murphy (1990), PMC is an external force that happens naturally in market. Executives who fail to manage the companies in competitive environment unable to sustain in long term. As extra efforts are necessary for sustaining in long term, stockholders are more willing to approve the high incentives to executives (Seth & Dastidar, 2009). Managerial position has discretionary power in determining whether to involve actively or inactively to compete in market. High commitment of managerial position in managing company depends on incentives paid to them. A company, which has many rivalries in market, requires extra efforts by executives to compete actively in market. As extra efforts are necessary for sustaining in long term, stockholders are more willing to approve the high incentives to executives. Several researchers approve the significant and positive relationship between PMC and managerial incentives, which shows relevancy of managerialism theory (Bulan et al., 2010; Cuñat & Guadalupe, 2005; Jensen & Murphy, 1990; Karuna, 2007).

Figure 1.

Source: The authors.

In short, this theory explains that executives have high discretion of power in decision-making whether to exert more or less efforts in managing company. In order to align interests between executives and stockholders, board of members shall design rewarding incentive schemes for managerial position.

Meanwhile, agency theory explains the conflicts between principals and agents due to separation functions of ownership and management in companies. Stockholders are known as principals, while managers are known as agents. Due to separation of ownership and management, the dissimilarity of intentions arose in organizations.

As executives prioritize its own benefits instead of maximizing stockholders’ wealth, it leads to principal–agent problem. Principal–agent problem can be solved only when the stockholders able to monitor every behaviour of managers. As it is impossible to monitor each action of managers, designation of incentives scheme to managers is one of the ways to make sure the actions of managers are towards maximizing stockholders’ wealth (Jensen & Murphy, 1990).

Competitive advantages of companies such as offering low price of goods due to low average operation cost will be beneficial to the companies and stockholders especially in a competitive market. As sustainability and successful achievement of companies is essential in competitive market, aligning incentives scheme with PMC is vital where both managers and stockholders are better off. Optimal incentive schemes able to prevent principle and agent problem as high PMC leads to high managerial incentives as well as high stockholders’ wealth if the managers manage the company well. Previous research results use agency theory to support their results and show a significant and positive relationship between PMC and managerial incentives (Bulan et al., 2010; Cuñat & Guadalupe, 2005; Jensen & Murphy, 1990; Karuna, 2007).

In summary, agency theory has similarity with managerialism theory, which is stockholders willing to increase managerial incentives in high PMC environment. However, the differences are as follows: managerialism theory emphasizes the necessity of high managerial incentives to induce CEOs to exert more or less effort, whereas agency theory emphasizes on the necessity of high managerial incentives to generate stockholders’ wealth.

Methodology

Data

We use annual report to collect a panel set of annual financial data for Malaysian publicly listed firms from 2010 to 2014. Our initial sample covers the entire 844 publicly listed firms in the Bursa Malaysia (Malaysia stock exchange). We exclude firms in the financial services industry and utilities industry from our sample due to those industries having a different nature of business and regulation in the Malaysian context. According to Ghazali and Weetman (2006), the financial sector is not suitable for analysis given that it is subject to varieties of rules and conduct as well as types of operation. We also remove any firm that has missing data throughout the 5-year period. Overall, 524 non-financial listed companies are chosen to be in the sample study, with 2620 pooled firm-year panel data.

Estimation Model

This research constructs the estimation model according to the traditional view on director compensation. This baseline follows research such as Cao et al. (2011), Sigler (2011) and Wasserman (2006) where compensation is the function of profitability, size and leverage. The function is given as follows:

Managerial compensation = f (Profitability, size, Leverage)

We pool the data and empirically estimate the function above by using the following regression model:

C o m p e n s a t i o n_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + ε_{i, t} T

where PROFIT refers to firm profitability as measured using ratio of total net income to total assets. Meanwhile, SIZE refers to firm’s size or the lognormal of total assets. LEVERAGE denotes division of total debt by total equity. Epsilon ‘ε’ indicates all other possible variables that might influence the managerial incentives of non-financial firms in Malaysia. ‘i’ and ‘t’ are to indicate the cross-sectional and time series data, respectively. Meanwhile, the symbol ‘β₀’ indicates the expected y-intercept when all independent variables are equal to zero.

The main objective of this research is to examine the role of PMC on compensation. We follow Karuna (2007) and Vrettos (2013) in constructing the model by adding PMC to our baseline model. Therefore, compensation is now a function of PMC and three other firm characteristics. The function model is as follows:

Managerial compensation = f (Profitability, size, Leverage, PMC)

We empirically test the function by using the following regression model:

C o m p e n s a t i o n_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + β_{4} P M C_{i, t} + ε_{i, t}

Note that PMC consists of three components, which are market size (MKTSIZE), product differentiation (DIFF) and market concentration (CONC). We use dynamic GMM panel regression as statistical tools to avoid endogeneity issue.

Managerial Compensation

Generally, compensation is the sum of salary, bonuses and other gratifications received by directors in a particular financial period. This method is used by Lewellen (1968), Rappaport (1983), Gomez-Mejia, Tosi, and Hinkin (1987), Werner and Tosi (1995), Ortiz-Molina (2007) and Cornett, Marcus, Saunders, and Tehranian (2007).

Total compensation is subject to approval and obligatory expenses by related authorities (government regulation and decision from annual grand meeting) to managerial positions, given the binding nature of the managerial agreement to perform duties. The information has to be disclosed in the financial statement of the firm’s annual report.

Market Competition Measures

This research constructs three different market competition proxies by following Botosan and Haris (2000), Karuna (2007) and Li, Lundholm, and Minnis (2013). First, we construct product differentiation adjusted by its Industry Hirschman–Herfindahl Index. The usage of product differentiation can be explained as the price-cost margin used to calculate the product differentiation. The margin has a negative relationship with level of product differentiation. Furthermore, the higher the price-cost margin, the lower the product differentiation level. Low product differentiation indicates a high level of market competition. This is calculated by the ratio of sales over industry median’s sales divided by operating cost and industry median operating cost.

The second measure for market competition is market size. The usage of proxy measure is due to the market size able to reflect consumer density in the industry. The higher the market size, the higher the competition level. It is measured by the ratio of sales over industry median for sales. Finally, we use concentration ratio from Hirschman–Herfindahl Index (HHI) and use HHI as a proxy measure to PMC as supported by Fernández-Kranz and Santaló (2010).¹

Fernández-Kranz and Santaló (2010) used three measures of PMC, which are: Hirschman–Herfindahl index (market concentration), number of competitors, import and tariff penetration. The second measure (number of competitors) is hard to trace for the Malaysian context due to its pyramiding ownership and intersection with numerous industries (because of high diversification). The third measure cannot be applied here due to data unavailability for Malaysia.

Analysis

Table 2 contains descriptive statistics for our sample firm year. The reported figures have been transformed using a normal logarithm to achieve normally distributed data. We also eliminate outliers and extreme values of year-firm observation for the same reason. The data are strongly balanced panel data.

We report three measures of PMC in Table 2: product differentiation (DIFF), market size (MKTSIZE) and concentration ratio (CONC). CONC has the highest mean with the value of 4.5998, and it is followed by DIFF with the value of 0.8732. MKTSIZE has the lowest mean value among all the measures. However, comparing mean to standard deviation, DIFF has the highest ratio and CONC has the smallest.

Table 2 also shows the mean and median for each variable, none of which have huge gaps, implying normal distribution. The largest gap of mean-median belongs to market size (MKTSIZE), while firm’s size (SIZE) has the smallest. Standard deviation for each variable shows acceptable variance for inferential statistics.

Correlations are shown in Table 3. Compensation is significantly correlated with all PMC measures. Compensation is moderately correlated with DIFF, MKTSIZE and CONC, where the coefficient correlation values are higher than 0.3. Among the PMC measures, the highest correlation is between MKTSIZE and CONC with the coefficient value of 0.7226. The lowest one is between DIFF and CONC. The control variables have low correlation values except for SIZE. In a nutshell, Table 3 implies that compensation has a significant and moderate correlation with PMC.

Table 2.

Descriptive Statistics Results

	Mean	Median	Standard Deviation	Skewness	Kurtosis
COMP	11.9983	11.8982	1.6415	0.1204	2.8905
DIFF	0.8732	0.9500	0.3761	−0.2076	−0.9910
MKTSIZE	0.2446	0.1688	0.0723	0.7962	2.3660
CONC	4.5998	4.3953	1.1120	0.3962	0.4129
SIZE	1.7293	1.7210	0.1061	0.3076	3.2996
LEVERAGE	0.9105	0.7985	0.2833	0.2795	3.8018
ROA	0.8313	0.9262	0.3792	−0.2760	2.5165

Source: The authors.

Table 3.

Correlation Matrix

	COMP	DIFF	MKTSIZE	CON	ROA	SIZE	LEVERAGE
COMP	1
DIFF	0.225**	1
	(0.0484)
MKTSIZE	0.3743*	0.3913***	1
	(0.0505)	(0.000)
CONC	0.3452**	0.3169***	0.7226***	1
	(0.0271)	(0.0000)	(0.0000)
ROA	0.1046**	0.0780***	0.0496**	0.2289*	1
	(0.0393)	(0.0006)	(0.03)	(0.0000)
SIZE	0.2185*	0.2411***	0.6363***	0.8901***	0.1131***	1
	(0.0793)	(0.0000)	(0.0000)	(0.0000)	(0.0000)
LEVERAGE	0.1324	0.0775***	0.1358***	0.1297***	0.0234	0.1658***	1
	(0.1069)	0.0007	(0.0000)	(0.0000)	0.3055	(0.0000)

Source: The authors.

Note: *, ** and *** denote the significant level at 1%, 5% and 10%, respectively.

Table 4 reports the baseline model and the association between PMC and competition. We run the model under a panel regression model. Each model is run first under Breusch Pagan LM and Wald tests to check the poolability and individual effect of our estimation model. Then, we run a Hausman test and F-test (using LSDV) to check whether our panel regression has fixed or random effects. The conclusion for each model is the same where all models have to run under fixed effect panel regression model. The next procedure is employing AR(1), AR(2) and Sargan test due to the endogeneity issue. Note that Pedroni (2001) argues that if a firm is significantly outnumbered the time period, there is possibility of endogeneity. Using static panel regression causes estimation bias if there is endogeneity issue. Hence, we follow Arellano and Bond (1991) and Pedroni (2001) to adapt dynamic panel regression. Dynamic panel regression model that allows for dynamics in the underlying process may be crucial for recovering consistent estimates of other parameters. The dynamic relationships are characterized by the presence of a lagged dependent variable among the regressors. It will eliminate the estimation bias that caused by the endogeneity. Although we have eliminated the autocorrelation problem²

We run a Wooldridge test for our panel regression (xtserial command in Stata), and we could rectify this issue using White test (vce[robust] command in Stata) or clustering the lagged residual. However, it may not solve the issue of a present lagged effect.

and individual effect, the endogeneity issue must still be effectively tackled using dynamic GMM panel regression.³

For each model in this article, we run the same process.

Table 4. Regression Results for PMC and Compensation

	Baseline	Model 2(a)	Model 2(b)	Model 2(c)
PMC		0.3560**	0.0879**	0.8688***
		(0.1432)	(0.0391)	(0.2745)
COMP(−1)	0.1463	0.1504	0.0953	0.1077
	(0.1070)	(0.1071)	(0.1039)	(0.1030)
SIZE	1.1411***	1.1021***	0.0869**	0.1106*
	(0.1046)	(0.1056)	(0.0428)	(0.0670)
LEVERAGE	0.0652***	0.0599***	0.0537**	0.0695***
	(0.0222)	(0.0212)	(0.0236)	(0.0272)
ROA	0.1398***	0.1351***	0.0653**	0.0127***
	(0.0444)	(0.0438)	(0.0324)	(0.0045)
CONSTANT	5.5741***	5.5671***	5.5747***	0.7310***
	(0.5795)	(0.5951)	(0.4414)	(0.1124)
AR(1)	−3.2814	−2.5993	−3.0849	−3.1817
AR(2)	−0.2160	−0.2429	0.2164	0.2428
SARGAN	6.2684	5.9608	5.7461	6.4109

Source: The authors.

Note: *, **and *** denote the significant level at 1%, 5% and 10%, respectively.

We run post-estimation specification test following Arellano and Bond (1991) to ensure whether our GMM estimation model is robust and valid. The first test is the Sargan test which is a test for the correlation between instruments and error terms incurred from our model. The null hypothesis for this test is that our instruments are robust and valid if there is no correlation between instruments and the error terms in first-difference equation. In other words, if the Sargan test rejects the null hypothesis, this means our estimation of GMM is biased and inconsistent. The results of Sargan test show high level of chi-square or, in other words, the p-value is higher than 0.05. This means that our GMM estimation model is robust and valid.

The second post-estimation specification test is the residual serial correlation which is captured by the order of serial correlation. The assumption is that if the error terms (ε _{_it} ) are serially independent, then. $E [Δ ε_{i, t} Δ ε_{i, t - 1}] = E [(ε_{i t} - ε_{i t - 1}) (ε_{i t - 1} - ε_{i t - 2})] = - E [ε_{i t - 1}^{2}] = - σ_{ε}^{2}$ Thus, we would not, however, expect first-order serial correlation. However, we would not expect there to be any second-order serial correlation from error terms as written as: $E [Δ ε_{i, t} Δ ε_{i, t - 2}] = E [(ε_{i t} - ε_{i t - 1}) (ε_{i t - 2} - ε_{i t - 3})] = 0$ . Therefore, the presence of second-order serial correlation indicated a specification error. In a simple word, the test should reject the null of no first-difference serial correlation (AR(1)), but it should not reject the null when there is no second-order serial correlation (AR(2)). This is to ensure whether the GMM estimation model is consistent and unbiased due to the endogeneity effect. The results of our AR(1) show that the value is higher(lower) than 1.98(–1.98), indicating the null rejection. Meanwhile, the results of our AR(2) show the value is higher(lower) than 1.98(–1.98), indicating that the null hypothesis cannot be rejected. This means that our GMM estimation model is consistent and unbiased.

Hence, we construct estimators based on moment equations constructed from further lagged levels of y_it and the first-differenced errors ε_it. This model creates moment conditions using lagged levels of the dependent variable with first differences of the errors . This leads us to use generalized moment method (GMM) panel regression as suggested by Holtz-Eakin, Newey, and Rosen (1988) and Arellano and Bond (1991).

Table 4 reports our dynamic GMM panel regression for each PMC measure. First, the baseline model shows that all control variables have positive and significant effects on compensation except the lagged one of compensation. This indicates that previous compensation does not significantly associate with this year’s compensation. These findings are consistent with the previous research by Karuna (2007), Bau and Dowling (2007), Tello-Trillo (2010) and Wasserman (2006).

Meanwhile, the evidence presented in Table 4 clearly suggests a positive relationship between PMC and compensation. Those companies with higher product differentiation (DIFF) have higher compensation, and it is significant at the 5 per cent level. This means that higher compensation for directors is not only due to the size, leverage, or profitability as suggested by previous research, but it is also due to how big the product differentiation is for a firm.

We then change the PMC measure by using market size (MKTSIZE). The conclusion is indifferent. Our model 2(b) shows that there is a positive association between PMC and compensation. This association is significant at the 5 per cent level. This tells us that firms will pay higher compensation for directors who can lead the way to higher market size.

Finally, we rerun the model with another PMC measure: concentration ratio. As depicted by model 2(c), there is a significant relationship between PMC and compensation at the 1 per cent level, confirming our two previous estimation models’ results. The relationship is also positive with a coefficient value of 0.8688, implying that compensation for directors is also associated with the market concentration of a firm. Therefore, we conclude that there is a positive and significant association between PMC and compensation. Our findings are consistent with previous research by Cuñat and Guadalupe (2009), Beiner et al. (2011) and Cao et al. (2011).

The positive and significant association between PMC and compensation confirms our postulation about a strategical view approach. Directors (the agent) know the condition of firm operations and furthermore recognize that their role is to optimize the wealth of shareholders (the principal). Running the firm at its best to improve the efficiency may generate higher profit or larger assets; however, it does not mean that directors are not replaceable. Therefore, directors employ managerial entrenchment to survive and to earn higher compensation. A manager’s ability to improve a firm’s competitiveness means they have valuable talents, superior to that of their peers. Hence, principals will compensate managers with higher pay (Jung & Subramanian, 2017).

Enhanced PMC has more benefits for directors than enlarging the firm’s size or profitability, such as rewards and accolades that inflate their self-esteem. Higher firm’s size and profitability may not require exemplary managerial skills or talent because this can be achieved through a typical business cycle (Campello, 2003; Decker & D’Erasmo, 2016), economy of scale (Mayer, Melitz, & Ottaviano, 2014) or networking (Luo, 2007). Yet gaining better PMC needs real managerial talent (Acharya, Pagano, & Volpin, 2016), and this talent leads to better compensation.

Another consideration is that less compensation may not attract director’s talent, especially in a competitive market. The ego of a director in treating competition as a trade-off with payment may cost the company with higher compensation (narcissistic-driven compensation). Market competitiveness increases the demand of superior managerial talent in companies and accordingly gives rise to director pay. However, several findings explain the positive link between PMC and director compensation as an effort to induce managers to exert more effort, reduce agency problems where the decisions concern stockholders’ wealth and attract or retain the talented executives in the company (Aoki, 1982; Cuñat & Guadalupe, 2005; Dam, 2015; Jensen & Murphy, 1990; Karuna, 2007).

PMC, Ownership Identity and Compensation

The main driving forces behind the compensation engaged by firms may be due to product compensation. But one important institutional characteristic that could possibly lead to different PMC effects is the behaviour of owners. That is, family firms in the developing market of Malaysia may indirectly have a different structure for compensation within government firms. Furthermore, Claessens, Djankov, Fan, and Lang (2002) suggested that commonly found business groups in Asian countries, where numerous firms belong to a shared ownership entity through pyramiding and crossholding, can have different success stories in implementing corporate strategy. Typically, in Asian countries, most of these affiliated groups belong to family-controlled owners (Claessens et al., 2002; Tam & Tan, 2007). These family ultimate owners usually participate actively in the management’s decision-making process without necessarily owning significant majority shareholdings in the firm. As a result, the Anglo-Saxon normative practice of separation of ownership and controls barely exists in the emerging markets. Given the fact that emerging markets generally have poor shareholder protection mechanisms in place, the issue of corporate governance is an unsurprisingly serious concern, in which the agency problem between majority and minority shareholders has overshadowed the agency problem between owners and managers. This is more common in developed countries. In family firms, most likely, the directors are chosen from the principal family. As part of the family, the family-directors may increase the compensation with or without taking PMC into consideration. Meanwhile, government firms have different ways in choosing their director, which is characterized as a lengthy and involved political procedure. Therefore, we breakdown our sample into three types of companies: family firm, government firm and foreign-owned firm to contest the hypothesis above.

We then subsample our data by dividing it into family, government and foreign and rerun the estimation model. The model is as follows:

O W N E R * [C O M P_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + β_{4} D I F F_{i, t} + ε_{i, t}]

3(a)

O W N E R * [C O M P_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + β_{4} M K T S I Z E_{i, t} + ε_{i, t}]

3(b)

O W N E R * [C O M P_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + β_{4} C O N C_{i, t} + ε_{i, t}]

3(c)

The regression procedure is the same as the previous estimation wherein we run dynamic GMM panel regression. It is important to note that we do not treat the data using a dummy variable and make it as one estimation model⁴

$\begin{array}{l} C O M P_{i, t} = β_{0} + β_{1} P R O F I T_{i, t} + β_{2} S I Z E_{i, t} + β_{3} L E V E R A G E_{i, t} + β_{4} D I F F_{i, t} + β_{5} D G O V_{i, t} \\ + β_{6} D F O R_{i, t} + β_{4} D G O V * P M C_{i, t} + β_{4} D F O R * P M C_{i, t} + ε_{i, t} \end{array}$

for three reasons. First, we do not aim to reveal the best or the worst association between PMC and compensation from those three identities. We also do not aim to reveal the moderating effect of ownership on PMC and compensation by simply taking the interaction.⁵

Read further Balli and Sorensen (2013).

Second, benchmarking one of ownership identities to avoid the dummy trap may offer a misleading conclusion. Finally, our objective is simply to reveal whether a different ownership identity will produce a different conclusion, so it can be compared to our main model.

Table 5 reports our findings for the association between PMC and compensation according to the ownership identity. It shows a new perspective to our conclusion. For instance, by not dividing the data into different types of ownership, all control variables are positive and significantly related to compensation. However, Table 5 shows that only firm’s size has consistent results where it has a significant effect on compensation for all models. Leverage is also significantly associated with compensation, except when the PMC measure is product differentiation (DIFF), and in the estimation model of family and government firms. Meanwhile, profitability does not hold any significant association with compensation, except the 10 per cent significant level at family firm models.

Table 5.

PMC and Ownership Identity

	Family 3(a)	3(b)	3(c)	Government 4(a)	4(b)	4(c)	Foreign 5(a)	5(b)	5(c)
DIFF	0.0375***			0.2130*			0.0127
	(0.0145)			(0.1207)			(0.2634)
MKTSIZE		0.4131***			0.7554***			0.5391**
		(0.1206)			(0.2558)			(0.2556)
CONC			0.1041*			0.1278*			0.2506***
			(0.0596)			(0.0667)			(0.0362)
COMP(−1)	0.0580	0.0495	0.0459	0.4428*	0.4362*	0.4439*	0.3216**	0.3802***	0.3322***
	(0.1426)	(0.1402)	(0.1410)	(0.2314)	(0.2294)	(0.2285)	(0.1311)	(0.1285)	(0.1274)
SIZE	0.8250***	0.9753***	0.8371***	0.9576***	0.9078***	0.9057***	0.8537**	0.9489**	0.8131**
	(0.2763)	(0.2613)	(0.2644)	(0.1866)	(0.1882)	(0.1889)	(0.4284)	(0.4677)	(0.4070)
LEVERAGE	0.0154	0.0616***	0.0253***	0.0415	0.0472*	0.0470*	0.0563***	0.0457***	0.4019**
	(0.0096)	(0.0177)	(0.0058)	(0.0269)	(0.0245)	(0.0247)	(0.0184)	(0.0151)	(0.1649)
ROA	0.0203*	0.0261*	0.0195	0.0218	0.0161	0.0155	0.0127	0.0114	0.0114
	(0.0112)	(0.0147)	(0.0215)	(0.0247)	(0.0252)	(0.0253)	(0.0377)	(0.0345)	(0.0360)
CONSTANT	1.5377	0.0714***	1.0845***	0.4840	0.4819	0.4974	0.7003	0.5664	0.5989
	(1.0982)	(0.0137)	(0.1472)	(0.4124)	(0.4085)	(0.4080)	(0.4353)	(0.4234)	(0.4552)
AR(1)	−2.7596	−2.7283	−2.6950	−2.1473	−2.2035	−2.2192	−2.4732	−2.2772	−2.4286
AR(2)	−0.8198	−0.8510	−0.8400	−0.3338	−0.0177	0.0049	−0.9470	0.7552	0.7971
SARGAN	7.2872	7.2399	7.2425	2.2354	2.7001	2.7891	2.5760	2.6995	2.2197

Source: The authors.

Note: *, ** and *** denote the significant level at 1%, 5% and 10%, respectively.

In terms of PMC, there is a significant relationship between DIFF and compensation in family firm and government firm models, but not for foreign firms. The association is positive with a coefficient value of 0.0375 and 0.2130 in family firm model and government firm model, respectively. Meanwhile, when we use market size (MKTSIZE) as the proxy for PMC, it demonstrates a significant relationship with compensation in all firm types. The coefficient values are 0.4143, 0.7554 and 0.5391 in family, government and foreign firm models, respectively. Finally, we again change the PMC measure into concentration ratio and found the same conclusion: there is a positive and significant relationship between PMC and compensation. However, the significant level is only 10 per cent in family firm and government firm models.

Overall, we conclude that there is a different interpretation for the association between PMC and compensation. Earlier, the findings reveal the significant association for pooled data without segregating the ownership identity. Yet Table 5 depicts that even though PMC has significant effects on compensation, different types of ownership have different perceptions in compensating PMC. For example, the directors’ compensation in family firm is significantly associated with higher product differentiation, or higher market size, or higher market concentration. The same conclusion can be found in government firms where all PMC measures are significantly associated with compensation. However, the directors’ compensation in foreign firms are only significant if the PMC is measured using market size or market concentration. This shows that unlike family firms and government firms, foreign firms will compensate their director with higher payment if their firms are competitive in terms of market size and market concentration. Foreign firms do not compensate directors’ talent if they only provide higher product differentiation. This is tally with corporate strategy research findings by Hult and Ketchen (2001), where foreign firms will have excess value if they are more competitive in the market, rather than more diversified (Lee, Hooy, & Hooy, 2012). Our findings are also consistent with empirical findings by Gomez-Mejia, Larraza-Kintana, and Makri (2003), Carlson et al. (2006), Wang, Wang, and Liang (2014) and Tsao, Lin, and Chen (2015), where family firms and government firms compensate their directors relatively higher than foreign firm in the case that they have better human capital. Meanwhile, foreign firms, which have broader and wider access in the director market, compensate their directors differently due to their internationalization information. Top directors in family firms may be perceived as mediocre directors in foreign firms as they have more information on the labour market. This provides foreign firms with a greater advantage in determining compensation and making their decision relatively easier as well.

Conclusion

Our study addresses a new perspective on the compensation factors in emerging countries like Malaysia. Our study is mainly motivated by the lack of reporting on these deserving emerging countries, despite their unique characteristics. Moreover, most director compensation emphasizes either agency cost or the managerialism perspective. Few research studies empirically define compensation in the strategy management view. By all means, this article lays the foundation for further research on this topic, especially within the emerging market context and a narrower focus on the institutional setting or other specific characteristics dimensions.

In this article, we provide strong empirical evidence that competitive firms better compensate their directors. Our results indicate that higher competition in the marketplace leads to higher compensation. Furthermore, our findings indicate that different types of ownership identity compensate different types of market competitions. It also reveals that market size and market concentration are more important for director compensation. These results are consistent with the strategic view in agency cost in which directors may not only enlarge the firm’s size and profitability to achieve higher compensation but also induce firm market competition. Although we cannot claim that all director compensation is solely driven by market competition, our findings implicate that the models based on purely managerialism or purely alignment are a worse fit with our estimate of firm behaviour. Note, however, we cannot reject all managerialism or alignment reasons for compensation since it could also be morally motivated and, at the same time, strategically chosen to serve the interests of the firm. Our study uses a panel data approach that allows for assessing changes in market competition and compensation level over time—albeit, no significant changes in variables levels over time—and thus giving more reliable estimates.

Managerial Implications

Board members or directors in non-financial industries or also known as policymaker are incharge of setting the level of managerial incentives. Knowledge in knowing the deterministic relationship between PMC and managerial incentives can help to develop suitable contracts with fair amount of managerial incentives. As the relationships are obvious, policymaker is able to avoid immoral behaviour of managerial position in achieving success performance in the short run instead of the long run. For instance, based on the result of study, policymaker should provide higher managerial incentives when managerial position works in an environment that is higher PMC, older company, slow firm growth and higher leverage environment. Apart from that, this research study also contributes to the other possible factors: firm age, firm growth and leverage that may truly affect managerial incentives. Policymakers shall utilize these determinants in designing optimal managerial incentives scheme. Therefore, this study provides important implications and contributions to the directors, board members and stockholders.

Limitations and Future Research

Having said this, all our findings need to be validated by further research on other emerging countries. This will help verify some facts about certain common characteristics embedded in the emerging markets as compared to advanced markets. First, more in-depth insights can be gained through examining corporate governance attributes, like board structure or managerial power, or board capital can be another interesting extension of study for this analysis.

Acknowledgement

The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Usual disclaimers apply.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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