Corporate governance and firm performance: an analysis of family and non-family controlled firms.
Article Type: Report
Subject: Family corporations (Management)
Family-owned business enterprises (Management)
Corporate governance (Research)
Business performance management (Research)
Author: Yasser, Qaiser Rafique
Pub Date: 03/22/2011
Publication: Name: Pakistan Development Review Publisher: Pakistan Institute of Development Economics Audience: Academic Format: Magazine/Journal Subject: Business, international; Social sciences Copyright: COPYRIGHT 2011 Reproduced with permission of the Publications Division, Pakistan Institute of Development Economies, Islamabad, Pakistan. ISSN: 0030-9729
Issue: Date: Spring, 2011 Source Volume: 50 Source Issue: 1
Topic: Event Code: 200 Management dynamics; 310 Science & research Computer Subject: Company business management
Geographic: Geographic Scope: Pakistan Geographic Code: 9PAKI Pakistan
Accession Number: 304307198
Full Text: The aim of this study is to scrutinise the impact of corporate governance mechanism on on the performance of family and non-family controlled firms in Pakistan. It has been found that a corporate governance structure influences the performance of both family and non-family controlled companies significantly. However all corporate governance mechanisms are not significant as the significant variables differ between family and non-family controlled companies. Thus, regulators need to be cautious in setting codes for different companies.

JEL classification: G34, L21, L25

Keywords: Corporate Governance, Firm Performance

1. INTRODUCTION

Family firms form the basic building block of businesses throughout the world. The economic and social importance of family enterprises has now become more widely recognised. Internationally they are the dominant form of business organisation. One measure of their dominance is the proportion of family enterprises to registered companies; this is estimated to range from 75 percent in the UK to more than 95 percent in India, Latin America and the Far and Middle East [Yasser (2011)]. The manner in which family firms are governed (the way in which they are directed and controlled) is therefore crucial to the contribution they make to their national economies as well as to their owners.

Family-owned listed companies are the backbone of Pakistan's economy. However, traditionally these companies are either unaware of the general principles of good corporate governance, or work in a relatively less open environment. Promoting basic principles of good governance for family-owned companies is crucial for economic growth.

Anderson and Reeb (2003) conclude from the US data that family companies outperform non-family companies. The same conclusions are also drawn from the studies of Miller and Breton-Miller (2006) and Villalonga and Amit (2006). Meanwhile, research in Western Europe has found that family-controlled companies have lesser agency problems between owner and manager but experience problems between family and minority shareholders [Maury (2006)]. However, studies show that owner-manager companies are less efficient in generating profits than professional non-owner manager companies [Lauterbach and Vaninsky (1999)].

In sum, a host of studies on family companies have been conducted worldwide, but few studies concern the situation in Pakistan. This study attempts to fill this research gap. Most Pakistani companies are family-owned and controlled. The researchers' aim is to find out whether Pakistani family-controlled companies perform better than non-family controlled companies or vice versa under corporate governance mechanism.

In this study financial performance has been analysed in two perspectives: accrual based and cash flow based. Accrual-based profit measures are claimed to be open to manipulations by managers [Teoh, Wong, and Rao (1998)]. Therefore, the alternative performance measure based on cash flows may be preferable. Cash flow-based studies have been carried out by several researchers [Kaplan (1989); Jain and Kini (1994); Kim, Kitsabunnarat and Nofsinger (2004)] who argue that operating cash flows are a useful measure in determining the firm's value and less sensitive to manipulation by managers. In terms of corporate governance mechanisms, this study introduces two new variables--directors' qualifications and independent directors with professional qualifications

that are expected to affect the firm's performance.

The presentation format of this study is as follows:

First, the theoretical framework on family and non-family companies' performance and corporate governance mechanism is discussed in the literature review section. The research methodology is then explained followed by the research findings and discussion. Finally, the research findings are summarised giving the study's limitations and recommendations are made for future studies.

2. THEORETICAL BACKGROUND AND HYPOTHESIS DEVELOPMENT

This section develops the hypotheses regarding the effects on performance of family-controlled and non-family controlled companies under corporate governance mechanisms.

2.1. Family and Non-family Companies' Performance

A study conducted by Daily and Dollinger (1992) shows that family companies reported higher sales growth and greater improvement in net margins than non-family companies. McConaughy, Walker, Henderson, and Mishra (1998) examine differences in efficiency and value, depending on whether the firm was founding family-controlled firm (FFCF) and had a CEO who was the founder/a descendant of the founder, or was a non-FFCF. The findings show that FFCFs are more efficient and valuable than NFFCFs in respect of industry, size and managerial ownership.

McConaughy, Matthews, and Fialko (2001) found that family companies have higher Tobin's Q than their counterparts. The family companies controlled by the founding family have greater value, operate more efficiently and carry less debt than other companies. Miller and Breton-Miller (2006) note that family companies perform better than non-family companies when the family companies have the intention to pass on the businesses to their progenies. A study by Maury (2006) in 13 Western European countries found that active family control continued to outperform non-family controlled firms in terms of profitability in different legal regimes. In 2008, a survey conducted by Pakistan Institute of Corporate Governance (PICG) indicated that 80 percent of firms cannot reach the third generation of their founders in Pakistan.

Family companies have several incentives to reduce agency costs [Fama and Jensen (1983); Demsetz and Lehn (1985); Anderson and Reeb (2003)]. As a family's wealth is closely linked to the firm's welfare, there is a strong incentive to monitor managers and minimise the free-rider problem inherent in small, atomistic shareholders [Demsetz and Lehn (1985)]. Research also claims that executives who are stewards are motivated to act in the best interests of their principals [Donaldson and Davis (1991)]. Stewardship philosophy has been practised and is common among successful family companies [Corbetta and Salvato (2004)]. Keen involvement encouraged by stewardship philosophy creates a sense of psychological ownership that motivates the family to behave in the best interest of the firm [Zahra (2005); Corbetta and Salvato (2004)].

However, it is difficult for family companies to avoid the misalignment between principal and agents. The agency cost in family companies can take place between minority owners and the major family owners who serve as their potentially exploitative de facto agents [Morck and Yeung (2003); Villalonga and Amit (2006)]. Amran and Ahmad (2009) found that there is no difference in performance between family-controlled businesses and non-family controlled businesses for companies listed from 2000 to 2003. Firm performance diminishes as large shareholders remain active in management although they are no longer competent or qualified to run the firm. The implication is that firm performance is even worse for older family companies than for non-family companies [Shleifer and Vishny (1997)]. Hence, based on the arguments, the researcher hypothesised that:

H1: Family companies have higher financial performance than non-family companies.

2.2. Board Composition

Non-executive directors are needed on boards to monitor and control the actions of executive directors due to their opportunistic behaviour and act as checks and balances in enhancing the boards' effectiveness [Jensen and Meckling (1976)]. Additionally, non-executive directors might be considered to be "decision experts" [Fama and Jensen (1983)], independent and not intimidated by the CEO [Weisbach (1988)], able to reduce managerial consumption of perquisites [Brickley and James (1987)] and act as a positive influence over the directors' deliberations and decisions [Pearce and Zahra (1992)]. According to Tricker (1984) the presence of non-executive directors on boards provides "additional windows on the world". This is congruent with the resource dependence theory, which proposes that non-executive directors act as middlemen between companies and the external environment due to their expertise, prestige and contacts.

According to Pakistani Code of Corporate Governance (2002), boards of directors to be balanced should not have more than 75 percent executive directors. Empirical studies [Ward and Handy (1988); Ward (1991); Felton and Watson (2002); Newell and Wilson (2002)] show that family companies prefer to have independent non-executive directors in their boards. Independent directors provide neutral insights, bring in fresh, creative perspectives and help in decision-making by bringing in new dimensions of experiences that may not be found among family directors. In family companies, the representatives of non-family directors on the board can offer a functional counterpoint in decision-making. Ward and Handy (1988) report that 88 percent of companies using non-executive directors believe that their boards are more useful and valuable as corporate governance agents of performance.

In contrast, a high proportion of non-executive directors on boards, as proposed by agency and resource dependency theories, also have drawbacks. Arguments against boards dominated by non-executive directors include stifling strategic actions [Goodstein, Gautam, and Boeker (1994)], excessive monitoring [Baysinger and Butler (1985)] and lack of real independence [Demb and Neubauer (1992)]. However, research by Klein, Shapiro and Young (2005) found no evidence that board composition affects firm performance. In family-owned companies, a high level of board independence does not automatically lead to better performance. Chin, Vos, and Casey (2004) also claim that the percentage of non-executive directors has little impact on overall firm performance. It means that the composition of independent non-executives directors seem has a mixed impact on performance. Therefore, the authors hypothesised that:

H2: There is a significant association between proportion of independent non-executive directors and financial performance.

2.3. Director's Qualification

The Code of Corporate Governance (2002) recommends that directors should use their qualities (skills, knowledge and experience, professionalism and integrity) in carrying out their duties. This is consistent with the resource dependence theory. Castillo and Wakefield (2006) show that educational background and skills may influence family companies' performance. A family's special technical knowledge concerning a firm's operations may put it in a better position to monitor the firm more effectively. Also, families have incentive to counteract the free rider problem that prevents atomised shareholders from bearing the costs of monitoring, ultimately reducing agency costs. Sebora and Wakefield (1998) find a positive relationship between education of the incumbent and conflict over money, management control and strategic vision. Educated incumbents may have been exposed to better financial management than their less educated counterparts. Based on the arguments, the authors hypothesised that:

H3: There is a relationship between proportion of directors' qualification and financial performance.

2.4. Independent Director's with Professional Qualification

Independent directors' background and competence are essential factors as they contribute positively to the family-owned companies [Johannisson and Huse (2000)]. However, Hartvigsen (2007) claims that companies are facing challenge in searching for qualified directors to sit on the boards. Most of the families prefer interlock directorship to secure their point of view in business operations. A survey conducted in the US by Emst and Young reports that many companies in Europe and America complain that they struggle to find qualified directors for their boards [The Economist (2006)]. Hendry (2002) also highlights that family companies face problems of having competent and expert agents.

Moreover, Berube (2005) notes that companies cannot contend with directors who simply put in a token appearance. Companies seek qualified directors, together with their expertise. A report from Christian and Timbers in New York also reflects the tough competition for qualified outside directors [Bates (2003)]. Therefore, the authors hypothesised that:

H4: There is a relationship between the proportion of independent directors with professional qualification and financial performance.

2.5. Board Meetings

The corporate governance view is that the board should meet regularly to discuss matters that arise. There are various suggestions for the frequency of board meetings. In the US, six meetings per year in alternate months is thought to be a good balance for most companies, when supplemented by occasional special meetings [Moore (2002)]. Boards meet formally at least four times per year, supplemented by additional monthly executive committee meetings attended by directors, the chairman, the CEO and senior managers [Ward (1991)].

Pakistani Code of Corporate Governance (2002) proposes that the board should meet regularly, with due notice of issues to be discussed but should meet at least once in a quarter.

The board should disclose the number of board meetings held in a year and the details of attendance of each individual director; it should also maintain minutes of meetings. Based on the above literatures, the authors hypothesised that:

H5: There is a relationship between the number of meetings and financial performance.

2.6. Leadership Structure

The corporate governance perspective views the CEO duality to arise when the post of the CEO and Chairman are managed by one and the same person. The agency theory claims that there must be a separation between ownership and control. The separate leadership structure can curb agency problems, and enhance the firm's value [Fama and Jensen (1983)].

In contrast, duality leadership is common among family companies [Chen, Cheung, Stouraitis and Wong (2005)]. The founder-CEOs as more concerned about the survival of their companies and are willing to protect their legacy for future generations. In the US, Moore (2002) finds that some companies have the CEO as the board chairman in order to focus the company's leadership. In addition, by splitting the role of the chairman and CEO, it reduces the CEO's freedom of action [Felton and Watson (2002)]. Other researchers find that stewards who hold the position of a board executive and a chairman concurrently have significantly higher corporate performance [Donaldson and Davis (1991); Finkelstein and D'Aveni (1994)].

Still others suggest there is no significant difference in firm performance between executive and non-executive chairmen [Chaganti, Mahajan and Sharma (1985); Molz (1988)]. The CEO-chair is responsible for the firm and the CEO has the power to determine strategy without fear of counter demands by an outside chair of the board [Finkelstein and D'Aveni (1994); Davis, et al. (1991)]. Based on these mixed findings, the authors hypothesised that:

H6: There is a significant association between financial performance and the practice of separate leadership.

2.7. Control Variables

The control variables in this study are debt, firm age and firm size. Companies do appear to make their choice of financing instrument as though they had target levels in mind for both the long-term debt ratio, and the ratio of short-term total debt [Marsh (1982)]. A study by Welch (2003) finds that there is a negative correlation between a firm's debt levels and corporate performance.

Ongore (2011) argues that all companies around the globe choose internal over external finance and debt over equity. Companies do not aim at any target debt ratio; instead, the debt ratio is just the cumulative result of hierarchical financing over time. Companies that face a financial deficit will first resort to debt, and will be observed later at a higher debt ratio [Myers and Majluf (1984)].

Next, the firm age is an important determinant of firm growth, the variability of firm growth and the probability of firm dissolution [Evans (1987)]. A study relating to firm age conducted by Dunne and Hughes (1994) finds that smaller companies were growing faster than the larger ones, though with more variable growth rate patterns. The smaller companies also shared a relatively low death rate from takeover as compared to the large companies, while medium sized companies were most vulnerable to takeover. The findings also revealed that younger companies, for a given size, grew faster than older companies.

Firm size can be "retarded" if a family management team is reluctant to raise external funds because it fears it will entail a loss of family control [Yasser (2011)]. Daily and Dollinger (1992) argue that some family companies operate without growth plans. As a result, some family companies only grow at a pace consistent with meeting the advancement needs of organisational members in the family system. Cromie, Stephenson, and Montieth (1995) found that family companies were smaller in terms of employment and sales turnover than non-family companies. Trow (1961) argues that larger companies have more resources, making it easy to attract, train, and develop potential successors and to engage outside advisers who may encourage continuity planning [Yasser (2011)].

3. RESEARCH METHODOLOGY

3.1. Data

The researcher gathered data from a sample of Pakistani companies listed on the Karachi Stock Exchange over the period of 2003 to 2008. This period was selected because this study seeks to examine the post effect of the implementation of the Code of Corporate Governance issued in 2002. A total of 134 companies have been selected for the study so the sample size for six years' observations was 804. This study adopted panel regression model analysis to determine the coefficient correlation between independent and dependent variables [Gorriz and Fumas (2005); Anderson and Reeb (2003)].

The definition of family-controlled firm was consistent with previous studies [Anderson and Reeb (2003); Villalonga and Amit (2006)]. In determining the family companies, the information on directors' profile and shareholdings were collected from the annual reports and corporate websites of companies. Data on board composition, directors' education, independent directors with professional qualification, number of meetings and leadership structure were also obtained from the annual reports. Financial data such as market value of ordinary shares, total assets, net income, earnings before interest, tax, depreciation and amortisation (EBITDA), shareholder's equity, return on assets (ROA), long term debt and operating cash flow were gathered from independent financial analysts. Then, the financial data was cross-checked with the printed annual reports to make the information more reliable.

3.2. Research Model and Measurement

In this study, the research model is as follows:

Model for total sample:

[FPERF.sub.it] = [b.sub.0] + [b.sub.1] [FCP.sub.it[ + [b.sub.2] [BCOMPO.sub.it] + [b.sub.3] [DIRQUAL.sub.it], + [b.sub.4[ [PROQUL.sub.it] + [B.sub.5] [MEETG.sub.it] + [b.sub.6] [LSHIP.sub.it] + [b.sub.7] [DEBT.sub.it] + [b.sub.8] [FAGE.sub.it] + [b.sub.9] [FSIZE.sub.it] + [[alpha].sub.i] + [[lambda].sub.t] + [[mu].sub.it] (1)

Model for family-controlled companies and non-family controlled companies:

[FPERF.sub.it] = [b.sub.0] + [b.sub.1] [FCP.sub.it] + [b.sub.2] [BCOMPO.sub.it] + [b.sub.3] [PROQUAL.sub.it], + [b.sub.4[ [METG.sub.it] + [B.sub.5] [SLHIP.sub.it] + [b.sub.7] [DEBT.sub.it] + [b.sub.8] [FAGE.sub.it] + [b.sub.9] [FSIZE.sub.it] + [[alpha].sub.i] + [[lambda].sub.t] + [[mu].sub.it] ... (2)

3.3. Model Specification

Variables, definitions and measurements are given in Table 1 mentioned below.

3.4. Panel Data Approach

In order to test the proposed model equations, this paper employs panel data approach because it facilitates elimination of the unobservable heterogeneity that the different companies in the sample data could present [Himmelberg, et al. (1999)]. Yasser (2011) describe that a panel data regression has some advantages over regression that run cross sectional or time series regression independently. First, combining time series and cross sectional observation panel data gives more informative data, variability, less colinearity among the variables, more degree of freedoms, and more efficiency. Secondly, by making data available for several thousand units, a panel data can minimise the bias that might result if individual or firm level data are divided into broad aggregates. Last, panel data can better detect and measure effects that simply cannot be observed in pure cross-section or pure time series data [Gujarati (2003); Baltagi (2001)].

The classical normal linear regression assumes that the error term is constant over time periods and locations. If such assumption is true than it is said that homoskedasticity exists. However, if there are variations in the observation, it may cause the variance of the error term produced from the regression not to be constant and as a result, the problem of heteroskedasticity prevails. If that occurs, the estimates of the dependent variable become less predictable [Gujarati (2003)].

4. RESULTS AND ANALYSIS

4.1. Descriptive Analysis

Table 2 summarises the statistics on all companies, family-controlled companies and non-family controlled companies with relation to the sector. Overall, the highest sector in this sample was properties (27.4 percent), followed by industrial products (26.71 percent), trading services (15.75 percent), consumer products and plantations (10.96 percent). Then, the sample was split into family-controlled and non-family controlled companies. For family-controlled companies, the first place is industrial products (27.38 percent), followed by properties (26.19 percent), and trading services (16.67 percent). Meanwhile, for non-family controlled companies, properties sector (29.03 percent) was in the top rank, followed by industrial products (25.81 percent).

4.2. Univariate Tests

In Table 3, t-test results show that there was a difference in performance (as measured by TOBINS Q) between family and non-family controlled companies. Family-controlled companies have shown higher mean value (0.828) as compared to non-family controlled companies (0.674). It implies that family-controlled companies have better firm performance. These findings are in line with previous studies [Daily and Dollinger (1992); McConaughy, et al. (1998); Anderson and Reeb (2003); Miller and Breton-Miller (2006); Martinez, Stohr, and Quiroga (2007)] which indicate that family-controlled companies are likely to achieve higher performance than non-family controlled companies. Family companies have greater firm value, operate more efficiently and families have the intention to keep the business for their next generations. In contrast, when OCF is used as dependent variable, it is evident that non-family controlled companies have a higher mean of OCF (0.062) compared to family-controlled companies (0.038). It shows that non-family controlled companies are better at managing the companies' cash flows.

In terms of PROQUAL, the mean for non-family controlled companies (0.183) is higher than that of family-controlled companies (0.157). The results show that non-family controlled companies prefer to have more independent professional directors on their boards as compared to family-controlled companies. The independent directors, it is claimed bring in fresh creative perspectives, are more objective, have new dimensions of experience, are more open in discussions and enhance management accountability [Ward and Handy (1988)]. On the other hand, owners of family-controlled companies were reluctant to appoint independent directors because they were afraid of losing control, did not believe that the non-executive directors understood the firm's competitive situation, were afraid of opening up to new, external ideas and their boards spent a lot of time on more urgent, operational issues [Ward (1991)]. Executives provide rich firm-specific knowledge and strong commitment to the firm [Sundaramurthy and Lewis (2003)]. The LSHIP variable is significant, whereby there are differences between leadership structure practised by family and non-family controlled companies. For DEBT, family-controlled companies favour the use of debt more than non-family controlled companies. The mean value of debt for family-controlled companies was 0.125, while that for non-family controlled companies was 0.117.

The use of debt is preferred by family-controlled companies because they prefer internal to external fund. This finding supports Myers and Majluf's study (1984). On the other hand, non-family controlled companies prefer to have lower usage of debt and use other sources of financing to run their business operation. This finding supports Welch's study (2003). However, the results discussed above only give directions for the hypotheses. The next section discusses the multivariate analysis which is more robust.

4.3. Multivariate Tests

4.3.1. Pooled OLS

On the bases of the results reported in Table 4, when data is pooled together (for all companies), results reveal that family-controlled firm (H1) and board composition (H2) hypotheses are supported using Q, ROA and OCF.

The director's qualification (H3) and independent directors with professional qualification (H4) are only supported when Q is used as indicator to measure firm performance. Meeting (H5) and leadership structure (H6) are supported only when ROA is applied.

The findings reveal that family-controlled companies have higher firm performance as compared to non-family controlled companies. Thus, H1 is accepted. This is in line with previous studies [McConaughy, et al. (2001); Anderson and Reeb (2003); Maury (2006); Matinez, Stohr, and Quiroga (2007)]. In terms of board composition, the results indicate that higher proportion of independent directors leads to lower firm value. These results may explain that independent directors that dominated the board may act as "additional windows" [Trickers (1984)] and lack of real independence [Demb and Neubauer (1992)]. So, this study does not support H2.

When Q is used as a performance indicator, the results show that DIRQUAL and PROQUAL are significant. Thus, H3 and H4 are accepted. The results indicate a positive direction whereby directors with qualifications may enhance firm performance. Moreover, when the board consists of higher numbers of independent directors with professional qualifications, the firm's value increases. This is because the educational background, competence and skills are used to manage the companies. Thus, these findings support previous studies [Johannisson and Huse (2000); Castillo and Wakefield (2006)].

However, when ROA is used as the performance indicator, it is found that MEETG is negatively related with firm performance. It explains that greater frequency of meetings is not an effective factor, it can deteriorate the firm value.

So, H5 is not supported. DEBT and FAGE are negatively related with firm performance. Debt findings and firm age results are in line with studies by Dunne and Hughes (1994). This research found FSIZE to be positively related to firm performance. This is consistent with a previous study by Trow (1961).

4.3.2. Panel Data Regression

Besides using the Pooled Ordinary Least Square (OLS), a Hausman test was carried out to determine whether the Fixed Effect Model (FE) or Random Effect Model (RE) is appropriate in this study. The result of the Hausman test shows that the p value was significant, so the F-statistic result, FE is more applicable in this study.

Table 5 explains that board composition for family and non-family controlled companies is negatively related with firm performance. It explains that when more independent directors sit on the board, the firm's performance decreases. Thus, companies do not fully utilise the roles of the independent directors. The directors may sit on the board to fulfill the board composition requirements or to show that the board is "independent", but in reality it is not. These findings do support previous studies [Trickers (1984); Demb and Neubauer (1992)].

In terms of the director's qualifications, only non-family controlled companies show positive relations with performance. Higher qualifications of directors help companies to achieve higher firm performance. The directors' educational background, competence and skills are used to manage the companies. This finding supports previous studies [Castillo and Wakefield (2006)]. For variable PROQUAL, family and non-family controlled companies show a negative relationship with the firm performance. The results indicate that having a higher number of independent directors with professional qualifications, does not improve a firm's performance. This explains that family and non-family controlled companies may have problems getting competent directors on their boards [Henry (2002)].

Family-controlled companies favour more meetings to enhance firm performance. This may be due to the fact that the more regularly they meet; the more they discuss matters without being constrained by time. Decision-making is taken seriously because the companies seek to have their assets transferred to future generations. In contrast, for non-family controlled companies, several meetings are ineffective. Non-family controlled companies usually comprise more outsiders. So, these outsiders work professionally such that when conducting meetings, every matter is taken seriously and time is used wisely.

The LSHIP variable for non-family companies is negatively related with firm performance. It shows that separate leadership actually enhances firm performance. In terms of control variables (debt, firm age and firm size) the results show a negative relationship with firm performance. Non-family controlled companies do not favour the use of debt which is consistent with previous studies by Welch (2003). Family and non-family controlled companies support the notion that a firm's value decreases as it ages, and this is in line with studies by Dunne and Hughes (1994). The finding supports research by Daily and Dollinger (1992). The research found that being non-family controlled enhances firm performance (when ROA and OCF are used as firm performance indicators). Thus, this finding also supports previous studies by Trow (1961).

5. CONCLUSION

Overall, this study finds that there are significant differences between family and non-family controlled firms' performance when measured by Tobin Q, ROA and OCF. For family-controlled companies, only two variables (PROQUAL and MEETG) are significant. Boards that have higher composition of professional directors show higher firm performance. But board meetings' frequency constitutes a variant trend. Family-controlled companies do show lower number of meetings. For non-family controlled companies, the board governance variables (BCOMPO, DIRQUAL, PROQUAL, MEETG and LSHIP) as suggested by Pakistan's Code of Corporate Governance (2002) have improved the firm performance. In addition, debt, firm size and firm age affect a firm's performance. It shows that corporate governance does play a vital role in influencing Pakistani companies' financial performance. Family-controlled companies do not comply with the guidelines provided by the Securities and Exchange Commission of Pakistan (2002). Thus, regulators need to take note that family and non-family controlled companies apply different sets of practices in managing their companies.

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Table 1
Variables, Definitions and Measurements

Variable                         Measurement

Dependent Variables
  Tobin's Q (Q)                  Market value of common equity plus
                                 book value of preferred shares and
                                 debt divided by book value of total
                                 assets.

  Return on assets (ROA)         Net income divided by book value of
                                 total assets.

  Operating cash flow (OCF)      Ratio of cash flow from operating
                                 activities to total assets.

Independent Variables            Family-controlled firm is defined as:
  Family-controlled firm (FCF)   (1) Founder is the CEO or successor
                                 is related by blood or marriage, (2)
                                 At least two family members in the
                                 management, and (3) Family directors
                                 have managerial ownership (direct and
                                 indirect shareholdings) of minimum 20
                                 percent in the firm. It is coded as 1
                                 if it is a family-controlled firm, 0
                                 for non-family controlled firm.

  Board composition (BCOMPO)     % of independent non-executive
                                 director/ total directors.

  Director's qualification       % of directors' with degree/ total
  (DIRQUAL)                      directors.

  Professional qualification     % of independent director with
  (PROQUAL)                      professional qualification/ total
                                 directors. Professional is defined as
                                 an individual that hold the
                                 professional title (CA, CMA, CPA, and
                                 ACCA), engineering, information
                                 technology, law and others.

  Meeting (MEETG)                The frequency of meetings per year.

  Leadership structure (LSHIP)   Firm practice whether separate or
                                 duality leadership. It is coded as 1,
                                 if firm practice separate leadership,
                                 0 for duality separate or duality
                                 leadership.

Control Variables

  DEBT                           The book value of long-term debt/
                                 total assets.

  Firm Age (FAGE)                The number of years since
                                 incorporated.

  Firm Size (FSIZE)              The natural log of the book value of
                                 total assets.

Source: Developed for this research.

Table 2
Descriptive Analysis

                        All
Sectors               Companies     %      FCF     %      NFCF     %

Personal Goods           198      21.21%   132   26.51%     66   21.57%
Industrial Product       102      12.88%    66   13.25%     36   11.76%
Insurance                60        4.55%    24    4.82%     36   11.76%
Household Goods          48        5.30%    24    4.82%     24    7.84%
Construction and         42        3.79%    24    4.82%     18    5.88%
  Material
Food Producer            180      34.85%   144   28.92%     36   11.76%
Chemical                 66        6.82%    42    8.43%     24    7.84%
Financial Services       72        6.82%    18    3.61%     54   17.65%
Automobile and Parts     36        3.79%    24    4.82%     12    3.92%
Total                    804        100%   498     100%    306     100%

Source: Developed for this research.

Notes: FCF = Family-controlled companies, NFCF = Non-family controlled
companies.

Table 3
Means, Standard Deviation and Tests of Differences in Means between
Family and Non family Controlled Companies and Corporate
Governance Mechanisms with Performance Indicators

            All Companies         FCF               NFCF

           Mean     S.D      Mean     S.D      Mean     S.D

Tobin Q    0.773    0.132    0.828    0.116    0.674    0.138
ROA        0.042    0.079    0.049    0.057    0.041    0.101
OCF        0.048    0.136    0.038    0.070    0.062    0.192
BCOMPO     0.396    0.115    0.372    0.090    0.429    0.136
DIRQUAL    0.770    0.198    0.725    0.199    0.839    0.174
PROQUAL    0.168    0.131    0.157    0.119    0.183    0.146
MEETG      5.305    1.999    4.967    1.212    5.765    2.658
DEBT       0.121    0.137    0.125    0.136    0.117    0.146
FAGE      11.830   13.910   10.971   12.264   12.994   15.817
FSIZE     13.599    0.801   13.655    0.812   13.524    0.780
LSHIP      0.898    0.295    0.850    0.358    0.970    0.174

          Dif. In Mean    t-value

Tobin Q       0.026       4.306 *
ROA           0.002       0.258
OCF          -0.025      -2.41
BCOMPO       -0.056      -6.755 *
DIRQUAL      -0.119      -8.397
PROQUAL      -0.026      -2.649 *
MEETG         0.798       5.434
DEBT          0.008       0.796 **
FAGE         -2.022      -1.945
FSIZE         0.131       2.184
LSHIP        -0.120      -7.683 ***

Source: Developed for this research.

Notes: * Significant at 0.05 (1 tailed); ** significant at 0.01 (1
tailed); Tobin Q=Market value of common equity plus book value of
preferred shares and debt divided by book value of total assets,
ROA=Net income divided by book value of total assets, OCF=Ratio of
cash flow from operating activities to total assets, LSHIP=Type of
leadership that a firm practice, whether separate leadership or
duality leadership, BCOMPO = Percentage of independent non-executive
director divided by total directors, DIRQUAL = Percentage of
directors' with degree and above divided by total directors, PROQUAL =
Percentage of independent director with professional qualification
divided by total directors, MEETG = The frequency a firm conducts
meetings per year, DEBT = The book value of long-term debt by total
assets, FAGE = Number of years since incorporated, FSIZE = Natural log
of the book value of total assets; # For LSHIP, a chi-square test was
applied.

Table 4
The Pooled Ordinary Least Square by Using Q, ROA and OCF
(All Companies)

                     Tobin Q                     ROA

              Coefficient    t-value    Coefficient    t-value

FCF            0.034         3.54 ***    0.018         3.07 ***
BCOMPO        -0.089        -2.15       -0.08         -3.32
DIRQUAL        0.041         1.71 ***    0.017         1.25
PROQUAL        0.098         2.72 ***    0.021         0.99
MEETG          0.001         0.38       -0.004        -2.99
LSHIP         -0.022        -1.45        0.008         0.84
DEBT           0.046         1.65 **    -0.051        -3.13
FAGE           0.00          0.85        0.00         -2.21
FSIZE         -0.024        -5.78        0.016         6.79 ***
F-statistic            7.44                      11.74
[R.sup.2]              0.04                       0.07

                     OCF

              Coefficient   t-value

FCF           -0.016        -2.57
BCOMPO        -0.062        -2.34
DIRQUAL       -0.009        -0.57
PROQUAL        0.034         1.51
MEETG         -0.001        -1.06
LSHIP          0.001         0.15
DEBT          -0.053        -3.02
FAGE          -0.001        -3.82
FSIZE          0.009         3.6 ***
F-statistic            5.37
[R.sup.2]              0.03

Source: Developed for this Research.

Notes: * Significant at 0.1 (1 tailed); ** significant at 0.05 (1
tailed); *** significant at 0.01 (1 tailed); Q = Market value of
common equity plus book value of preferred shares and debt divided by
book value of total assets, ROA = Net income divided by book value of
total assets, OCF = Ratio of cash flow from operating activities to
total assets, FCF = Family-controlled firm, LSHIP = Type of leadership
that a firm practice, whether separate leadership or duality
leadership, BCOMPO = Percentage of independent non-executive director
divided by total directors, DIRQUAL = Percentage of directors' with
degree and above divided by total Directors, PROQUAL = Percentage of
independent director with professional qualification divided by total
directors, MEETG = The frequency a firm conducts meetings per year,
DEBT = The book value of long-term debt by total assets, FAGE = Number
of years since incorporated, FSIZE = Natural log of the book value of
total assets.

Table 5
Tobin Q, ROA and OCF (Family and Non family Controlled Companies)

                      Tobin Q                       ROA

                  FCF          NFCF           FCF          NFCF
              Coefficient   Coefficient   Coefficient   Coefficient

FCF            0.000        -0.0073        0.0002        0.000
BCOMPO        -0.024         0.103 ***    -0.021        -0.105 ***
DIRQUAL       -0.008         0.116 ***    -0.004         0.053 **
PROQUAL        0.314 ***    -0.106 ***     0.050 ***     0.004
MEETG          0.011 **      0.000         0.000        -0.006 ***
LSHIP         -0.017        -0.064         0.002         0.045
DEBT           0.021         0.103 ***    -0.009        -0.130 ***
FAGE           0.000         0.000        -0.000 ***     0.000
FSIZE         -0.022 *      -0.028         0.000         0.029 ***
F-statistic   21.00         12.21          8.24          2.42

                       OCF

                  FCF          NFCF
              Coefficient   Coefficient

FCF            0.0000        0.0007
BCOMPO        -0.009        -0.091
DIRQUAL       -0.011        -0.029
PROQUAL       -0.012         0.088 **
MEETG          0.001        -0.003
LSHIP          0.003         0.007
DEBT          -0.021        -0.121
FAGE           0.000 *       0.001
FSIZE          0.002         0.017
F-statistic   10.65          3.92

Source: Developed for this research.

Notes: * Significant at 0.1 (1 tailed); ** significant at 0.05 (l
tailed); *** significant at 0.01 (1 tailed); FCF = Family-controlled
companies, NFCF = Non-family controlled firm, Tobin Q = Market value
of common equity plus book value of preferred shares and debt divided
by book value of total assets, ROA = Net income divided by book value
of total assets, OCF = Ratio of cash flow from operating activities to
total assets, LSHIP = Type of leadership that a firm practice, whether
separate leadership or duality leadership, BCOMPO = Percentage of
independent non-executive director divided by total directors, DIRQUAL
= Percentage of directors' with degree and above divided by total
Directors, PROQUAL = Percentage of independent director with
professional qualification divided by total directors, MEETG = The
frequency a firm conducts meetings per year, DEBT = The book value of
long-term debt by total assets, FAGE = Number of years since
incorporated, FSIZE = Natural log of the book value of total assets.
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