Abstract

Various corporate governance theories indicate that governance in small and medium-sized enterprises (SMEs) differs to that of larger corporations due to the ownership-management function within the organizational structure. This article provides empirical evidence of enhanced firm value in a sample of listed SMEs resulting from certain corporate governance mechanisms related to managerial and ownership concentration. The empirical analysis conducted in this paper is based on a panel data set consisting of 108 small and medium-sized public firms on the Spanish alternative stock exchange over a time frame of five years (2015-2019). The results suggest that CEO duality, the controlling shareholders, and the second largest shareholders all improve firm value. Conversely, the ratio of independent directors has a negative impact on firm value. These findings are robust to alternative model specifications such as dynamic panel estimators (Generalized Method of Moments -GMM-) and instrumental variable methods. Overall, we show that the governance configuration of listed SMEs can mitigate several of the central issues, such as agency problems, that large corporations face.

Keywords: firm value; managerial concentration; ownership concentration; corporate governance; alternative stock exchange
JEL Classification: G15; G32

1. Introduction

SMEs are the backbone of global economies. They play a decisive role in the diversification of the economy, create employment, foster economic growth, enhance a country´s production, and reduce the ability of large companies to control the market (Benedict et al., 2021; Hacini et al., 2022). Most studies on corporate governance have focused on large firms and have not considered many of the typical or recommended processes and activities carried out by SME boards. In fact, a common practice in small and medium-sized enterprises (SMEs) is the combined ownership-management function within the organizational structure that facilitates both the accountability of owners and the empowerment of managers (Arthurs & Busenitz, 2003). The result is that governance is more efficient in SMEs, as it avoids the agency problem that exists in larger organizations (Lappalainen & Niskanen, 2012; Omri et al., 2014).

However, these findings were not conclusive and did not reach a unanimous consensus in European contexts (Corbetta & Tomaselli, 1996; Daily & Dalton, 1992; Hermalin & Weisbach, 2003; Roffia, 2020). Researchers have argued about specific areas such as board independence, board composition, ownership structure, and management ownership, but the scientific approach has not expanded to the effectiveness of corporate governance variables within the SME segment, in which certain characteristics emerge such as low levels of board independence and high ownership concentration. In small and medium-sized enterprises, where managerial ownership is usual, agency problems are more likely to arise due to information asymmetry. Moreover, the ownership concentration can lead to risk aversion and an unwillingness to engage in strategic changes. Therefore, the managerial and ownership structure may be associated with firm performance (Lappalainen & Niskanen, 2012).

The Spanish context presents a number of unique aspects of Spanish enterprises, such as high levels of ownership and managerial concentration. The average listed Spanish firm has several large controlling shareholders, and floating stock is less than 50% for many firms. Moreover, Spanish private SMEs have a negative discount, suggesting a premium over listed firms due to the relative illiquidity and higher risk (Rodríguez-Valencia et al., 2023). On the other hand, it is very important to point out that companies listed on the Spanish Stock Exchange are required to implement a Good Governance Code and must disclose a standardized Annual Report on Corporate Governance (ARCG). However, SMEs listed on alternative stock exchanges are normally exempt from complying with this code, resulting in a certain flexibility in terms of corporate governance.

The purpose of this paper is to provide empirical evidence of enhanced firm value resulting from corporate governance mechanisms related to ownership and managerial concentrations. The above arguments lead to our central research question, i.e., Can listed Spanish SMEs enhance firm value through managerial and ownership concentration variables?

Our study contributes to the literature in the following ways. First, our research extends the strand of literature that investigates how corporate governance instruments, such as managerial and ownership concentration, affect firm value from the perspective of Spanish small and medium-sized firms. For instance, the results of the studies conducted by Fama and Jensen (1983) show that the cost of monitoring decreases and that the agency problem is mitigated, resulting in higher firm value. Second, we found that both managerial and ownership structures are significant determinants of firm performance in our sample of small and medium-sized Spanish firms. This study is based on a panel data set covering 108 firms over a time period of five years. The results suggest that (a) less board independence might be better for firm value (b) CEO duality positively affects firm value (c) controlling shareholders positively affect firm value, and (d) second-largest shareholders positively affect firm value. Our findings are in line with previous studies (Deb & Wiklund, 2017; du Plessis et al., 2018; Garg, 2020; Hamelin, 2011; Li et al., 2020; Liao et al., 2014; Martin et al., 2017; Mortazian et al., 2019). Finally, to address the problem of endogeneity in the study of managerial and ownership structures, we employed the Generalized Method of Moments (GMM) and the instrumental-variable (IV) methods. Moreover, the independent variables are one-year lagged to the respective dependent (performance) variables in order to reduce concerns over endogeneity.

This paper is organized as follows. In Section 2, we present the theoretical background and elaborate our hypotheses. In Section 3, we describe the data sources, sample formation, and empirical analyses. In Section 4, we report the results; and finally, in Section 5, we present a discussion and the conclusions of the study.

2. Theoretical background and hypotheses

The corporate governance literature has mostly focused on large listed companies. Conversely, corporate governance features in SMEs have received much less research attention compared to large companies. The definition of corporate governance originated in the large business environment (Fama & Jensen, 1983; Jensen & Meckling, 1976), who studied the effect of separating corporate control and ownership. According to agency theory (Jensen & Meckling, 1976), there are various ways in which management may not act in the best interest of the shareholders, e.g., a board mainly consisting of directors cannot effectively monitor management, and combining the roles of the CEO and the chair of the board of directors concentrates too much power in the hands of just one person (Baysinger & Butler, 1985; Fama, 1980; Lefort & Urzúa, 2008).

An alternative technique to solving agency problems is board composition. The board can be seen as a decisive connection between management and shareholders (Brunninge et al., 2007). Agency theory suggests that the separation of ownership from control may lead to agency problems when the interests of owners and managers are misaligned (Lappalainen & Niskanen, 2012). Managerial ownership or the presence of a large shareholder can lead to better performance as this significantly reduces agency problems between managers and owners, since they will be less likely to deviate from the main purpose of shareholder wealth maximization.

The result is that governance is more efficient in SMEs as it avoids the agency problem that exists in larger organizations (Banham & He, 2010). In the context of SMEs, the accountability of owners and the empowerment of managers are embedded in the organizational structure (Arthurs & Busenitz, 2003). Therefore, SMEs do not often face the classic agency problem since their directors discuss strategic issues and have a solid understanding of the company’s long-term success (Garg, 2013).

Some academics argue that monitoring by independent directors can be ineffective, as they have much less knowledge of the firm and therefore their decisions are mainly based on biased information provided by managers (Choi et al., 2021). For example, Harris and Raviv (2008) showed that firm value is maximized with less board independence when the cost of monitoring by independent directors is high; Muth and Donaldson (1998) found that board independence adversely affects firm value; Jentsch (2019) concluded that firm value is reduced by adding more independent directors to the board, and also suggested that having executive directors on the board adds value. Hence, we present the following hypothesis:

Hypothesis 1: Firm value is reduced by including independent directors to the boards of listed SMEs.

There is also no conclusive evidence regarding CEO duality, although various theoretical perspectives, such as agency theory, predict the effect of CEO duality (Donaldson & Davis, 1991). According to the separation hypothesis, two separate individuals in the highest positions of an organization can monitor more effectively (Brickley et al., 1997; Elsayed, 2007; Fosberg & Nelson, 1999). Generally, this hypothesis applies to the environments of large organizations. However, in SMEs, the situation is completely different. The combination hypothesis shows that one person unifying both roles is more efficient (Davis et al., 1997; Donaldson & Davis, 1991; Jentsch, 2019; Y.-F. Lin, 2005). Therefore, we propose the following hypothesis:

Hypothesis 2: CEO duality has a positive effect on firm value for firms listed on alternative stock markets.

Agency theory is often associated with the separation of ownership and control (Jensen, 1994; Li et al., 2020; Liao et al., 2014; Schulze et al., 2001). Nevertheless, SMEs present a diverse governance structure. Based on the corporate governance literature for SMEs, the advantages of having controlling shareholders are emphasized under the convergence of interest and the efficient monitoring premises. According to these premises, controlling shareholders are likely to exert more effective monitoring on management than small shareholders, since they possess significant investments and large voting power to protect their investments, can mitigate collective action problems faced by different shareholders, and are more committed to the firm in the long run (Berle & Means, 2017; Jensen & Meckling, 1976; Jentsch, 2019; Shleifer & Vishny, 1986; Zeckhauser & Pound, 1990). According to Kroll and Walters (2007), ownership by top management team members who are also on the board is positively associated with post-IPO performance. In line with the controlling shareholders premise, we propose the following hypothesis:

Hypothesis 3: Controlling shareholders enhance firm value for listed firms on alternative stock markets.

The second-largest shareholder represents the dispersion of power in the company among all groups of shareholders. Commonly, shareholders with a small number of shares find themselves in an unfavorable situation, as monitoring managers is costly and the exacerbation of the information asymmetry problem between investors is growing. Therefore, small shareholders rely only on market regulations to protect themselves from being expropriated by managers (La Porta et al., 2000). Nevertheless, the presence of small shareholders also diminishes the incentives to extract private benefits at their expense. According to Maury and Pajuste (2005) and Mortazian et al. (2019), the second largest blockholder has a positive impact on firm value. Thus, we present the following hypothesis:

Hypothesis 4: The second largest shareholders of SMEs have a positive impact on firm value.

3. Methodology

3.1. Data and sample selection

The study is based on data regarding the managerial and ownership concentration of public SMEs in Spain. SMEs are defined in Recommendation 2003/361/EC as follows: "The category of micro, small, and medium-sized enterprises consisting of firms that employ fewer than 250 people and whose annual turnover does not exceed 50 million euros, or whose annual balance sheet does not exceed 43 million euros” (Lozano-Reina & Sánchez Marín, 2019).

The Alternative Stock Market (https://www.bmegrowth.es/) is a sub-market of the stock exchange that allows smaller firms to obtain financing for their operations, to access stock markets, and to float their capital under a more flexible regulatory framework than larger corporations (Rodríguez-Valencia & Lamothe Fernández, 2022). Firms seeking admission to alternative stock exchanges are required to be public companies which meet the level of transparency demanded in all procedures, and must report the half-yearly and annual information required by BME Growth, as well as contract a registered advisor and a liquidity provider to help the company in the process to be listed. In order to join an exchange market, the stocks held by shareholders holding less than 5% of the share capital must have an estimated value of more than €2 million. Frequently, companies who do not initially meet this requirement do so later via a share placement or share sale upon admission to the market (BME Growth, 2022).

The final sample initially generated non-balanced panel data from 108 firms from 2015 to 2019. We decided to exclude observations from companies operating in the financial sector and from newly listed companies, which are not recommended for use in analyzing this research. The primary source of data for these firms was a database with integrated detailed company information published by Bureau van Dijk (see Table A1 in Appendix A).

Table 1 reports the sample descriptive statistics. The table below shows the data characteristics, including the total number of observations, the means, the standard deviation, and the respective minimum and maximum values of all listed firms. To address endogeneity concerns, this study uses lags. Firm value is measured using Tobin’s Q with an average proportion of 0.83 (= exp (-0.192)).

Variable Names N Mean Median Std. Dev. Min. Max.
Key independent variables:
Managerial Concentration
CEO duality 416 0.373 0.000 0.484 0 1
Ratio of independent directors 384 -0.250 -0.105 0.642 -7.313 0
Ownership Concentration
Controlling shareholder 400 -0.910 -0.724 0.800 -2.984 0
Second-largest shareholder 362 -2.571 -2.207 1.442 -9.210 -0.768
Dependent variables:
Tobin’s Q (ln) 416 -0.192 0.060 1.407 -8.397 2.589
Control variables:
Firm Size (in total assets) 416 16.971 17.073 1.816 8.029 21.265
Tobin's Q t-1 413 0.278 0.359 1.028 -7.901 2.614
Leverage (ln) 416 -1.106 -0.690 1.360 -8.397 1.791
Table 1.Descriptive StatisticsThis table shows the descriptive statistics of the sample, which includes 108 Spanish public SMEs (from BME Growth) from 2015 to 2019. The key independent variables are divided into Managerial and Ownership Concentration. Detailed definitions of all variables are given in Table A1 in Appendix A.

The independent variables are the variables that illustrate the corporate governance framework. The model tested in this research consists of four explanatory variables, two for each corporate governance device (board composition and shareholder ownership). As this study uses a short panel of five years, the governance variables tend to be stable; thus, we report the within and between variances for all variables. CEO duality represents 37% of firm-year observations and a standard overall deviation of 0.42; on average, the ratio of independent directors represents 78% of firm-year observations, which is high compared to the results of Crespí-Cladera and Pascual-Fuster's (2014) research, in which a panel of Spanish listed firms classify 14.2% of the directors as strictly independent, whereas the firms classify 32.5% of the board members as being independent directors.

Controlling shareholders move between 0.05 (= exp (-2.98)) and 1 (= exp (0)), with a mean of 0.40 (= exp (-0.91)). The average proportion of second-largest shareholder represents 8%. The smallest ratio is 0% and the largest ratio is 46.40%. As the data in this table further show, the number of controlling shareholders is quite high during this period. Firm Size, calculated as the natural logarithm of total assets, ranges from 8.03 to 21.27, with a mean of 16.97 and a standard deviation of 1.82. The leverage ratio can theoretically take values between 0 and 1. The mean leverage of all sample firms is 0.33 (= exp (-1.11)), meaning that the average firm in the sample has a debt of 33% of its total assets.

Table 2 shows the Pearson correlation matrix. Tobin’s Q has a negative correlation with the independent director ratio, which is consistent with the results of previous studies (e.g., Adams & Ferreira, 2007; Ahn & Shrestha, 2013; Boone et al., 2007; Farag & Mallin, 2019; Hermalin & Weisbach, 1998). Conversely, Tobin’s Q has a positive correlation with CEO duality and the percentages of controlling shareholders and second-largest shareholders (Colombo et al., 2014; Deb & Wiklund, 2017; du Plessis et al., 2018; Garg & Eisenhardt, 2017; Liao et al., 2014; Martin et al., 2017).

(1) (2) (3) (4) (5) (6) (7) (8)
(1) Tobin's Q 1.000
(2) CEO duality 0.082* 1.000
(3) Independent director ratio -0.031 -0.260*** 1.000
(4) Controlling shareholder 0.117** -0.172*** 0.183*** 1.000
(5) Second-largest shareholder 0.117** 0.097* -0.137*** -0.219*** 1.000
(6) Leverage 0.645*** 0.115** 0.047 -0.170*** 0.216*** 1.000
(7) Tobin's Q t-1 0.248*** 0.107** -0.065 -0.050 -0.025 0.136*** 1.000
(8) Firm size 0.150*** -0.051 0.039 0.065 -0.169*** -0.014 0.045 1.000
Table 2.Correlation MatrixThe table shows the correlation matrix of variables used in this study. Detailed definitions of all variables are provided in Table A1 in Appendix A. The symbols ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

3.2. Models

To study the relationship between corporate governance and firm value, we estimate the following baseline model:

\[Firm\:Value_{i,t}=\beta_0+\beta_1 Control\:Variables_{i,t-1}+\beta_2 Board\:Independence\:Variables_{i,t-1}+\beta_3 Ownership\:Structure\:Variables_{i,t-1}+d_t+u_i+\varepsilon_{i,t}\,\,(1)\]

In Eq. (1), dt is the year fixed effect of year t, ui is the firm fixed effect of firm i, and εi,t is the error term of firm i in year t; β0 represents the constant term; and Firm Value represents the natural logarithm of Tobin’s Q. According to finance literature, firm value can be measured as stock market performance, accounting performance, or a mix of both performance measures (Bhabra, 2007; Xu & Wang, 1999).

Following previous studies (e.g., Bertoni et al., 2014; Jentsch, 2019), we include three control variables which represent the firm-specific variables of firm size, leverage, and lagged Tobin's Q (to control past performance). Firm size is defined as the natural logarithm of total assets in each year. Our measure for the financial structure is the leverage ratio, which is defined as the ratio of total liabilities to total assets.

The first variable for measuring board composition is the Independent Director Ratio (IDR), which represents the percentage of independent directors on the board of directors. This continuous variable ranges between 0.5 and 1. The second variable measuring board composition is CEO Duality, a binary variable equal to 1 when the CEO and the chairman of the board of directors are the same person, and 0 otherwise (C.-P. Lin & Chuang, 2011).

We employ two variables to test for the effect of ownership concentration. Controlling shareholder is measured as the percentage of shareholding held by the largest shareholder, and second-largest shareholder is measured as the percentage of shareholding held by the second-largest shareholder.

For methodological reasons, the independent variables are one-year lagged to the respective dependent (performance) variables in order to mitigate concerns over endogeneity. Moreover, we chose to lag our independent variables, as the effects of board composition and ownership may take time to reflect on firm value. In unreported tests and in order to avoid losing too many observations, we also ran the regressions with year firm characteristics, and the results held1.

4. Results

4.1. Baseline results

Table 3 reports the results from the baseline model using multiple OLS regressions. All regressions include year and industry fixed effects. We predicted that we would find the determinants of firm value to be both statistically significant and to possess the expected signs according to the theoretical background and hypotheses included in this study.

Dependent variable: ln (Tobin's Q) FEM 1 FEM 1a FEM 1b FEM 1c FEM 1d FEM 1e FEM 1f FEM 1g FEM 1h
Constant -1.711***(-3.38) -1.919***(-3.14) -1.687***(-3.32) -1.776***(-3.49) -1.755***(-3.52) -1.821***(-3.06) -1.718***(-3.41) -1.865**(-3.11) -1.948***(-3.16)
Independent variables
Managerial Concentration
CEO duality 0.048(0.36) 0.042(0.34) 0.037(0.26) 0.044(0.33) 0.021(0.19)
Independent director ratio -0.015(-0.09) -0.021(-0.14) -0.011(-0.07) -0.010(-0.06) -0.032(-0.22)
Ownership Concentration
Controlling shareholder 0.032(0.46) 0.035(0.49) 0.029(0.42) 0.009(0.15) 0.01(0.15)
Second-largest shareholder -1 0.038(0.64) 0.010(0.20) 0.039(0.67) 0.035(0.60) 0.008(0.14)
Control variable (firm-specific variable)
Firm size (ln) 0.135***(4.64) 0.142***(4.04) 0.135***(4.61) 0.132***(4.75) 0.135***(4.64) 0.136***(3.99) 0.131**(4.65) 0.138**(4.08) 0.142***(4.03)
Tobin’s Q t-1 0.157***(2.76) 0.157***(2.76) 0.159***(2.79) 0.145***(2.70) 0.156***(2.75) 0.124***(2.78) 0.129***(2.43) 0.145***(3.22) 0.157***(2.77)
Leverage (ln) 0.653***(6.44) 0.623***(6.19) 0.654***(6.48) 0.664***(7.23) 0.650***(6.39) 0.636***(7.05) 0.669***(7.29) 0.633***(7.00) 0.621***(6.20)
No. of groups 104 106 104 105 104 107 105 107 106
No. of observations 345 358 345 379 345 412 381 396 358
Hausman test 0.008 0.001 0.009 0.000 0.042 0.000 0.000 0.000 0.002
R-sq 0.4279 0.3992 0.428 0.4208 0.427 0.389 0.416 0.396 0.399
Wald (chi-sq) 117.50 92.95 115.20 125.84 115.78 100.08 120.42 103.92 90.23
Wooldridge test 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Table 3.Baseline RegressionsThis table reports the OLS results showing the relationship between firm value and corporate governance variables. Firm value is ln (Tobin’s Q). Managerial Concentration variables include CEO duality and the percentage of independent directors on the board. Ownership Concentration includes the controlling shareholder and the second-largest shareholder. Detailed definitions of all variables are provided in Table A1 in Appendix A. All models include year and industry fixed effects, and z-values are reported in parentheses. The symbols ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

The base model (FEM 1) is a year-firm-fixed effects model with the four standard explanatory variables of Managerial and Ownership Concentration, and the three firm-specific control variables of Firm size, Leverage, and past performance measure (Tobin’s Q). The ratio of independent directors has a negative coefficient and is not statistically significant. Meanwhile, the coefficients of CEO duality, controlling shareholder, and second-largest shareholder are positive and not statistically significant. The results show that the effect of the four governance variables of CEO duality, independent director, controlling shareholder, and second-largest shareholder are in line with the above hypotheses, which state that the agency problem is less central in SMEs, but none of these are statistically significant. The respective coefficients of all the control variables are positive and statistically significant.

The models FEM1a – FEM1d report the effect of each individual independent variable on firm valuation when the rest of the variables are considered together. Meanwhile, the effects of each of the corporate governance variables on firm valuation are reported in models FEM1e - FEM1h. We found the control variables to be positive and statistically significant, while the remaining variables were found to be non-significant. However, the expected signs of each variable are correct. This finding supports our first, second, third, and four hypotheses.

In model FEM1e, we find that CEO duality has a positive and statistically non-significant coefficient, implying that the predicted Tobin’s Q is higher by an average of 1.02 (= exp (0.021) for companies that have CEO duality than for those that do not. This result is consistent with the findings of Banham and He (2010), Garg (2013), Wasserman (2017), Arthurs and Busenitz (2003) and Deb and Wiklund (2017), who stated that CEO duality is considered to be effective in more dynamic environments, and therefore SMEs do not frequently face the classic agency problem.

Model FEM1f shows that the ratio of independent directors also has a negative coefficient but is not statistically significant. According to the results, the ratio of independent directors tends to decrease Tobin’s Q by 0.97 (= exp (-0.0.32)). This finding is in concordance with the SME corporate governance literature, which suggests that less board independence might be better for shareholder value (Adams & Ferreira, 2007; Ahn & Shrestha, 2013; Boone et al., 2007; Farag & Mallin, 2019; Hermalin & Weisbach, 1998).

In models FEM1g and FEM1h, a concentrated equity ownership, as measured by the largest shareholder and the second-largest shareholder, was found to have a positive and non-significant coefficient. A controlling shareholder variable tends to increase Tobin’s Q by 1.01 (= exp (0.01)), and so we may conclude that the presence of a controlling shareholder does not decrease, but rather increases firm value. However, for the second-largest shareholder, Tobin’s Q tends to increase by 1.008 (= exp (0.008). This result is consistent with the findings of Goodstein et al. (1994), Brunninge et al. (2007), Weir et al. (2002), and Ang et al. (2000), who stated that a controlling shareholder may introduce strategic practices and monitoring mechanisms according to their own values and interests, and which limit the ability to extract wealth from outside shareholders and hence mitigate agency conflicts. Overall, we find these results support hypotheses 3 and 4.

The coefficients of the firm characteristics control variables in models FEM1 through FEM1h are consistent with those in previous studies of firm value. For example, the coefficient of Size is positive and significant, which suggests that larger SMEs in Spain have higher firm value (consistent with Arifianto & Chabachib, 2016; Jentsch, 2019; Mura, 2007), i.e., investors have more trust in large-scale companies since they have better access to capital markets and benefit from economies of scale and size-induced entry barriers. Base model FEM 1 shows that firm size enhances Tobin’s Q by an average of 1.14 (= exp (0.134)).

In short, the totality of the results presented in the Models in Table 3 suggests that the governance figures of SMEs reduce some of the essential issues, such as the agency problem (Arthurs & Busenitz, 2003; Banham & He, 2010; Garg, 2020). Statistically, the empirical results provide us with considerable evidence to accept Hypotheses 1, 2, 3, and 4.

4.2. Robustness tests

First, following Choi et al. (2021), we performed a sensitivity analysis of our findings, using different measures of performance as the dependent variable. The results show that our findings continue to hold. (Our results have been omitted to save space, but are available on request).

Dependent variable: ln (Tobin's Q) GMM 1 GMM 1a GMM 1b GMM 1c GMM 1d GMM 1e GMM 1f GMM 1g GMM 1h
Constant -0.950(-1.01) -1.119(-1.13) -0.884(-0.98) -0.878(-1.12) -0.748(-0.79) -0.590(-0.72) -0.684(-0.93) -0.784(-0.95) -0.696(-0.73)
Independent variables
Managerial Concentration
CEO duality 0.059(0.65) 0.148*(1.64) 0.049(0.53) 0.067(0.73) 0.115(1.21)
Independent director ratio -0.249***(-3.66) -0.267***(-3.80) -0.261***(-3.44) -0.258***(-3.81) -0.291***(-3.85)
Ownership Concentration
Controlling shareholder 0.088**(1.90) 0.092**(1.99) 0.090**(1.91) 0.066(1.37) 0.097*(1.76)
Second-largest shareholder 0.018(0.38) 0.016(0.35) 0.019(0.40) 0.023(0.46) 0.023(0.50)
Control variable (firm-specific variable)
Firm size (ln) 0.067(1.20) 0.079(1.34) 0.065(1.19) 0.062(1.39) 0.062(1.09) 0.052(1.09) 0.055(1.30) 0.060(1.26) 0.066(1.12)
Tobin Q t-1 0.468***(3.90) 0.426***(3.75) 0.468***(3.89) 0.625***(2.52) 0.469***(3.91) 0.563**(2.37) 0.627***(2.54) 0.563**(2.33) 0.429***(3.77)
Leverage (ln) 0.119(0.81) 0.159(1.11) 0.121(0.82) 0.066(0.39) 0.125(0.86) 0.111(0.71) 0.073(0.43) 0.105(0.66) 0.170(1.20)
No. of groups 83 87 83 92 83 98 92 98 87
No. of instruments 10 9 9 9 9 7 7 7 7
Wald (chi - sq) 44.66 48.21 44.07 56.20 36.55 38.71 43.15 49.53 35.94
p-value of Hansen test 0.156 0.111 0.157 0.146 0.156 0.087 0.147 0.086 0.112
p-value of AR (1) test 0.019 0.014 0.019 0.039 0.019 0.049 0.038 0.051 0.014
p-value of AR (2) test 0.985 0.971 0.985 0.820 0.983 0.969 0.818 0.780 0.974
Table 4.Two-step system GMMNote: GMM= Random effects model; z-values are reported in parentheses; the symbols ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

The results from the system GMM regression models are presented in Table 4. Model GMM1 reports the regression with the firm specific variables considered as control variables and corporate governance variables. Our conclusions remain the same with this alternative methodology. Models GMM1a–GMM1h report the effect of corporate governance on firm valuation, aiming to directly test the relevance of the governance effect.

Table 4 also reports the Wald Chi-square test statistic, the significance of Hansen test, and the AR (1) and AR (2) tests. In all cases, the Hansen test and the AR (2) test are larger than 0.05, which indicates failure to reject the null hypothesis of over-identification and second-order serial correlation of error terms.

We also perform the instrumental variable and two-stage least squared (IV-2SLS) regression analyses to find the effect of the independent director ratio on firm value (see Table 5). Furthermore, we employ the percentage of IDR (independent director ratio) of a specific firm, measured as the mean value of the independent director ratio for other firms in the same industry in the same fiscal year, i.e., the independent director ratio is likely correlated with industry peers due to the similar board composition and the same legal regulations for SMEs. The models show that CEO duality, controlling shareholder, and second-largest shareholder positively affect firm value, but the independent director ratio still has a negative effect on firm value. These findings support all of the above hypotheses.

1ft Stage 2nd Stage 1ft Stage 2nd Stage 1ft Stage 2nd Stage 1ft Stage 2nd Stage 1ft Stage 2nd Stage
Dependent variable: ln (Tobin's Q) ln (Tobin's Q) ln (Tobin's Q) ln (Tobin's Q) ln (Tobin's Q)
Instrumented: IDR IDR IDR IDR IDR
Independent variables
Managerial Concentration
CEO duality 0.251***(4.96) 0.599(0.48) 0.482***(8.10) 0.911(0.59)
Independent directors ratio -0.839(-0.36) -0.726(-0.34) -0.352(-0.20) -0.176(-0.20) 0.186(0.21)
Ownership Concentration
Controlling shareholder 0.428***(7.93) 0.677(0.50) 0.752***(17.72) 0.898(0.54)
Second-largest shareholder 1.245***(8.91) 1.842(0.49) 1.878***(12.74) 0.929(0.36)
Industry average IDR 0.478***(7.28) 0.517***(5.38) 0.548***(8.64) 0.978***(14.59) 0.998***(12.01)
Control variable (firm-specific variable)
Firm size 0.001(0.29) 0.298***(6.19) 0.006(1.35) 0.305***(6.22) 0.0002(0.35) 0.297***(6.18) 0.006*(1.52) 0.301***(6.26) 0.008*(1.72) 0.302***(6.26)
Tobin’s Q t-1 0.005(1.39) 0.086(1.41) 0.006(1.18) 0.088(1.42) 0.005(1.33) 0.086(1.40) -0.010**(2.05) 0.086***(1.40) 0.010*(1.75) 0.086(1.41)
Leverage 0.001(0.17) 0.803***(10.18) -0.007(-0.10) 0.801***(10.15) 0.002(0.35) 0.804***(10.21) -0.001(-0.17) 0.801***(10.18) -0.001(-0.14) 0.801***(10.20)
Constant -0.059(-0.89) -4.506***(-4.37) 0.104(1.09) -4.270***(-3.39) -0.026(-0.37) -4.50***(-4.43) -0.294***(-3.58) -4.676***(-5.05) -0.129(-1.28) -4.593***(-4.68)
Year/Industry Yes Yes Yes Yes Yes
F-test of instruments 51.29 23.21 42.81 33.05 37.49
p-value 0.000 0.000 0.000 0.000 0.000
Wald (chi - sq) 164.33 163.57 165.01 164.12 164.11
p-value 0.0000 0.0000 0.0000 0.0000 0.0000
No. of observations 411 411 411 411 411 411 411 411 411 411
Adj. R-squared (%) 0.3866 0.3909 0.3800 0.4196 0.4177
F value (first-stage) 105.77 105.15 126.96 123.65 124.46
Endogeneity test p=0.092 p=0.092 p=0.056 p=0.06 p=0.05
Durbin Chi2 test:
Wu-Hausman F test p=0.095 p=0.095 p=0.058 p=0.06 p=0.05
Overidentifying test:
Wooldridge´s score test p=0.1753 p=0.1026 p=0.3210 p=0.1711 p=0.2242
Table 5.IV - 2SLS EstimationThis table reports the IV-2SLS results, showing the relationship between firm value (ln Tobin’s Q) and the independent director ratio. Industry average IDR is the industry average of independent director ratio of companies from the sector. Detailed definitions of the variables are presented in Table A1 in Appendix A. All models include year and industry fixed effects. Numbers in parentheses are z-values are reported in parentheses. The symbols ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. After the IV-2SLS estimation, the F-test, and the Wald Chi-square tests for weak instrument, the Durbin and Wu–Hausman statistics for endogeneity and Wooldridge’s test for overidentifying restrictions are reported

5. Discussion and Conclusions

Conventional corporate governance theory argues that a board should primarily consist of a significant number of independent directors, the chairman should not simultaneously serve as CEO, and ownership concentration should not be allowed. However, this theory only applies for larger corporations. This paper finds that agency theory may not adequately explain the case of listed SMEs due to the different governance scheme that applies specifically to large firms. The innovative aspect of our study is that it demonstrates that the governance configuration of listed SMEs can mitigate several of the central issues, such as the agency problem, that large corporations face.

In this study, we hypothesized that three variables i.e., CEO duality, controlling shareholder, and second-largest shareholder lead to improved company performance, and that a lower ratio of independent directors on the boards of SMEs leads to better firm value. To test these hypotheses, we conducted a firm-year-fixed model as the baseline model, and performed robustness tests such as the generalized method of moments and the two-stage least-square (2SLS) analyses.

The empirical results suggest important findings. First, they suggest that listed SMEs have better governance systems since the agency conflict is not as relevant as in large corporations. We demonstrate that, as corporate governance practices differ between small and medium enterprises and large firms, these could have different impacts on firm value. Second, a negative relationship was found between the independent director ratio and Tobin's Q, used as a proxy for firm performance. Third, CEO duality may improve firm valuation in the context of Spanish listed firms. This finding is also consistent with previous literature (Colombo et al., 2014; Deb & Wiklund, 2017; Garg, 2013; Wasserman, 2017). Fourth, the results of the analysis, with regard to blockholder ownership, further suggest that the presence of a controlling shareholder does in fact increase firm value. Fifth, our findings reveal that the second-largest shareholder has a positive impact on the performance (Tobin's Q) of small and medium-sized listed firms. This result is in line with previous studies (du Plessis et al., 2018; Koh, 2022; Martin et al., 2017; Mukherjee, 2022).

This research has some limitations. First, the data were collected in a limited geographical area (i.e., Spain), thereby limiting the possibility of generalizing the results. Second, a considerable problem with managerial and ownership concentration studies is endogeneity. To address endogeneity concerns, at least to a certain extent, this study uses lags. Moreover, the use of year-firm-fixed effects is aimed at reducing potential endogeneity problems. Third, this research aims to limit omitted variable bias by controlling for year-firm-fixed effects, and also tries to avoid omitted variable bias by including the most common control variables.

Future research could focus on the relationship between governance variables and firm value in the context of non-listed SMEs. In addition, research could be conducted in other developed economies with similar levels of ownership and managerial concentration, such as Germany, France, and Italy. Furthermore, we plan to expand the literature by considering different samples of corporate governance variables, i.e., management ownership, frequency of meetings, auditing, etc.

The results of this paper contribute to the existing literature in three ways. First, it extends the analysis of governance schemes to SMEs. Corporate governance characteristics in SMEs have received much less research attention compared to large companies. By employing the findings of this paper, SME directors will be able to identify the key governance variables that affect firm value, and will therefore be able to concentrate their efforts on them. Second, our study includes financial and some corporate governance variables, but it would be possible to analyze other governance variables that also influence firm performance. Finally, the findings may also be useful for various stakeholders, such as investors or regulators of corporate governance, considering the active contribution of SME boards in the value creation process.

Appendix A

Variable Names Measurement
Key Independent Variables:
Managerial Concentration
CEO duality A variable. Concurrent positions on the board of directors, equal to 1 if the CEO and chairperson of the board are the same person, and 0 otherwise.
Independent director ratio Percentage of independent directors on the board (%). Ratio of independent directors / total of directors on board. This continuous variable ranges between 0 and 1.
Ownership Concentration
Controlling shareholder Shareholding of the largest shareholder (%). This continuous variable ranges between 0 and 1.
Second-largest shareholder Shareholding of the second-largest shareholder (%). This continuous variable ranges between 0 and 1.
Dependent variables:
Tobin’s Q (ln) Natural logarithm of Tobin’s Q, where Tobin’s Q equals (year-end value of the firm’s common stock + estimated year-end market value of the firm’s preferred stock + year-end book value of the firm’s long-term debt + year-end book value of the firm’s short-term debt with a maturity less than one year / firm’s year-end book value of total assets
Control variables:
Firm Size (ln Total assets) Natural logarithm of total assets of the company
Tobin’s Q t-1 Natural logarithm Tobin’s Q lagged one period
Leverage (ln) Natural logarithm of total liabilities relative to total assets
Table A1.Definition of variables

Footnotes

  • 1 Our results have been omitted in order to save space, but are available on request.

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