Corporate Governance Practices, Ownership

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Corporate Governance Practices, Ownership Structure, and Corporate Performance in the GCC Countries Article in Journal of International Financial Markets Institutions and Money · January 2017 DOI: 10.1016/j.intfin.2016.08.004

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Corporate Governance Practices, Ownership Structure, and Corporate Performance in the GCC Countries

Forthcoming Journal of International Financial Markets, Institutions & Money

Abed Al-Nasser Abdallah Associate Professor of Accounting, School of Business and Management, American University of Sharjah, P.O.Box:26666, Sharjah, UAE.

Ahmad K. Ismail  Associate Professor of Finance, Olayan School of Business, American University of Beirut, Tel +961 1 350000, Fax: +961 1 750214. Email: [email protected] and [email protected]



Corresponding author: Ahmad Ismail, Olayan School of Business, American University of Beirut, Bliss Street, P.O. Box: 11-0236, Beirut, Lebanon. Tel +961 1 350000 Ext. 3731, Fax: +961 1 750214, Email: [email protected] and [email protected] 1

Corporate Governance Practices, Ownership Structure, and Corporate Performance in the GCC Countries

Abstract This study is motivated by highly concentrated ownership, the relatively large government stake in listed firms in the GCC (Gulf Cooperative Council) region, and the rapid stock market development and developing investor protection environment. The results point to heterogeneity in governance quality across exchanges. For the first time, we find that the positive relationship between governance quality and firm performance is maintained and is stronger at low levels of concentrated ownership. More interestingly, we find that the relationship between governance and firm performance is an increasing function of dispersed ownership and that the value addition of good governance is not necessarily maintained at high levels of ownership concentration. Furthermore, such a relationship reaches its highest level when the government or local corporations are the firm’s major shareholders. Keywords: Corporate Governance; performance; Ownership Structure; transparency; financial disclosure JEL Classification: G30.

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1.

Motivation and Outline

The generally documented evidence on the relationship between the quality of corporate governance and shareholders’ value and/or corporate performance is positive, regardless of which governance or investor protection metric is used, country level or firm level (see for example Gompers, Ishii, and Metrick, 2003; Bebchuk, Cohen, and Ferrell, 2009, Brown and Caylor 2006, Starks and Wei 2013 and Cheung et al., 2014). Research shows that an optimal system of governance for all firms and all countries is nonexistent (Castrillo, et al 2010), therefore “one size does not fit all” and corporate governance standards cannot be consistently applied to different structures. Additionally, some studies suggest that effective corporate governance depends on “the alignment of interdependent organizational and environmental characteristics” (e.g., Aguilera et al., 2008; Aguilera and Desender, 2012; Filatotchev, Toms, and Wright, 2006)1. Desender, Aguilera, Crespi, and GarciaCestona (2013) offer support for the view that the effectiveness of corporate governance mechanisms must be considered conditional on the ownership structure of the firm. Their results for Continental European companies disclose that board independence and audit services are complementary for dispersed ownership only. The authors suggest that ownership concentration and board composition become substitutes in terms of monitoring management and that the strength of this substitution effect depends on the type of controlling shareholder as well. Moreover, Aguilera and Crespi-Caldera (2016) argue that ownership can be easily compared across countries but corporate governance practices differ significantly across firms’ ownership concentration. Therefore, they propose that “future research should draw on micro data on firm specific ownership structures and their corporate governance practices to better understand the

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See Desender, Aguilera, Crespi, and Garcia-Cestona (2013) page 823.

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cross-national diversity of governance and its meanings and consequences”. In fact, our paper aims to fill this gap in the literature. Under the Anglo-Saxon dispersed ownership structure, the nature of conflict of interest is between shareholders and managers and therefore, the set of corporate governance practices tries to align the interests of these two groups in order to protect shareholders. In this spirit, La Porta, Lopez-de- Silanes, Shleifer, and Vishny (1997) claim that ownership concentration with its diverse set of control mechanisms is the response to inappropriate protection of investors. On the other hand, in other developed markets (e.g. Continental Europe and Japan) and in emerging markets, high ownership concentration, gives rise to conflicts between controlling shareholders and minority shareholders (Morck et al., 2005). This Principal-Principal conflict according to Young, Peng, Ahlstrom, Bruton, and Jiang (2008) calls for a different bundle of governance mechanisms under which increasing ownership concentration cannot be a remedy and may make things worse (Faccio et al., 2001) or render the performance of the firm inefficient (Goergen, 2014). Consequently, studies that test the relationship between ownership concentration and firm performance produce conflicting results (see for example Fama and Jensen, 1983; Demsetz, 1983; Chang, 2003; and Demsetz and Villalonga, 2001; Grant and Kirchmaier, 2004, Cheung, 2010; and Vintila and Gherghina, 2014 among others). Therefore, different levels of corporate governance may trigger different levels of ownership concentration across countries, while the impact on performance may not be predictable. Thus so far, and to the best of our knowledge, no studies have explored the effect of ownership characteristics on the association between governance and performance. Stated differently, a further dimension that this paper tries to explore is how the relationship between corporate

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governance and performance is affected by different levels of concentrated ownership and also by different types of ownership. The GCC (Gulf Cooperative Council) region is an ideal platform to conduct our analyses and draw conclusions that could be applicable to other emerging markets as well for various reasons. First, the ownership structure is highly concentrated in this region with large block-holders such as wealthy families, government and quasi government institutions (Santos, 2015). For instance, it is noted that approximately one-third of the market's total capital of Saudi listed firms is owned by the government (including public pension funds), and another one-third is owned by founding families2. The concentrated ownership also applies to the whole GCC region as the mean proportion of shares held by large block-holders in the GCC region is between 45% and 56%3. On the other hand, when examining the type of owner, the mean proportion of shares held by the government is around 25%4 . Secondly, financial markets in the region have grown substantially in the recent two decades and have attracted regional and international investors, which necessitated enhancing transparency and investor protection. Such a development in financial markets led Morgan Stanley Capital International (MSCI) to include UAE and Qatari stock exchange markets in the Emerging Markets Index from May 2014. According to Kem (2012), compared to global total, share volume in the GCC markets represented 0.8%, while banking assets were 1.1% by the end of 2010, and equity market capitalization stood at 1.3%, whereas debt securities outstanding represented only 0.2%. Relatively speaking, Kem (2012, p.10) states that the “GCC’s debt markets are, around half the size of Asian or Latin American markets, and

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Source: Corporate Governance Country Assessment Kingdom of Saudi Arabia, the World Bank, February 2009. Amico (2014) notes that Free float in the region is very low, despite standards for IPOs that require companies to list a minimum of 40% of their equity (e.g. in Oman) and over 55% of their equity in the UAE. For example, for the largest 400 listed companies, the average free float oscillated between 45 and 48% in the past five years (MSCI, 2014) with Kuwait, and the UAE, having free float exceeding 50% of market capitalization (World Bank, 2011). 4 Source: Ownership Structures in MENA Countries: Listed Companies, State-Owned, Family Enterprises and some Policy Implications, OECD 2006. 3

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just 70% of the relative size of these markets in Sub-Saharan Africa. Equity markets fare better, making up 75% of GDP which compares favorably with the 58% observed on average in the emerging economies. The share of banking assets, 123% of GDP also lies above the 89% average of the GCC’s peers in the emerging economies”. However, Kem (2012) argues that despite this small market size, GCC markets play an important role in in the global cross-border issuance of debt instruments since investors have easy access to these instruments.5According to (Kem, 2012), institutional investors play a major role in the GCC economies. The total value of assets managed by the region’s institutional investors estimated at 3.6 trillion dollars, corresponding to approximately 370% of GDP in the region. This is way above the international average of institutional assets to GDP of around 230%, and represents 2.5% of the institutional assets that are managed globally. Thirdly, although in the recent years awareness of good governance and improved disclosure have developed gradually, yet full adoption of governance practices and transparency measures still faces challenges as a result of the conservative and protectionist investment culture in the region which is manifested by weak disclosure of information, and unwillingness to relinquish ownership and control by large block-holders. We use a unique data set including all the publicly listed firms in the GCC region for which measures of governance and ownership structures are available for the first time for the period 2008 to 2012. For the final sample of 532 firms, the initial results show heterogeneity in Corporate Governance scores across the GCC exchanges with Muscat, Bahrain and Abu Dhabi being in the lead, while Riyadh and Kuwait are at the very bottom. Using three measures of firm

Kem (2012, p.16) states that “In 2011, almost 70% of all issuances were reported to have been co-listed on international exchanges, with Germany, the UK, and Luxembourg as the most important locations for secondary listings”. 5

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performance; these are the Tobin-Q, ROA, and ROE, we find that well governed firms outperform other firms in the sample, which is consistent with previous studies. Nevertheless, when we add the ownership concentration dimension we document for the first time that ownership concentration alters the relationship between governance and performance. Namely, we find that the positive relationship between governance and performance is maintained for majority shareholders owning at least 5% and 10%, but not for higher levels of concentration, that is, for holding percentages higher than 20% or 25%, there is no association between governance and corporate performance. Furthermore, and equally interestingly, the magnitude of the effect of governance on firm performance decreases with the increase in the level of ownership concentration. In other words, for firms with more dispersed ownership (level of ownership concentration at least 5%), better corporate governance leads to a much better performance than for firms with less dispersed ownership (level of ownership concentration at least 10%). These findings are consistent with the notion that concentrated ownership creates agency problems between majority shareholders and minority shareholders, in a way that makes the performance of the firm inefficient (Faccio et al., 2001 and Goergen, 2014). We also report further interesting results for the different types of majority ownership. We document that this bonding relationship between corporate governance and firm performance reaches its highest level when governments are the majority shareholders of the firm. This is also a new finding that is not reported in earlier studies. The rest of the article is organized as follows: Section 2 presents a review of the relevant literature; Section 3 describes the sample and methodology used in this article; Section 4 discusses the empirical results; and Section 5 concludes and indicates implications and limitations.

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2.

Literature Review 2.1 Governance and Regulations in the GCC region

Regulators of financial markets in the region and other international and independent bodies, such as the International Finance Corporation (IFC) and the Organization for Economic Cooperation and Development (OECD), have been active in promoting a culture of investor protection and good governance practices in the region for the last two decades, which resulted in drafting governance codes by the GCC member states since 2002 starting with Oman and ending with Bahrain in 2010 and Kuwait in 20136. These codes mainly differ by their enforcement requirement. For instance, almost all the GCC countries have chosen voluntary compliance (“Comply-or-Explain”), whereas the UAE opted for mandatory compliance (“Comply or-Pay Penalty”). On the other hand, these codes have other similar provisions such as Board composition7, but they use varying definitions of Director Independence. Three of the Codes recommend ongoing professional board development programs for the directors (Qatar, Saudi Arabia and UAE)8. As for Board Committees, all codes require setting up an Audit Committee which is composed mostly of independent non-executive directors. The duties of such committee are well stated in all these codes. Bahrain and Oman are setting strongest standards in terms of disclosure of remuneration. Bahrain is the only GCC country calling for shareholder approval for remuneration related matters, which is in line with international best practice.

Kuwait’s Governance Code has not yet come into force. For instance, they all call for having majority non-executive directors, at least one third of the board member should be independent, the roles of the CEO and the Chairman of the Board should be separated etc... For a detailed review of these codes please see the report titled “Hawkamah Brief on Corporate Governance Codes of the GCC”. 8 Bahrain and Oman address the need for Board evaluations. 6 7

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Family ownership is the foundation of the GCC economy since family businesses in the region generate around 80% of gross domestic product (GDP) outside the oil sector. Nonetheless, the increase in the corporate governance awareness across all GCC markets makes the establishment of good governance mechanisms vital for the long-term survival of these businesses, though not a current strategic priority. A survey by Pearl Initiative and PWC (2012), which interviewed over a hundred family firms in the GCC region, shows that though the majority of those firms believe in the importance of corporate governance for securing the long-term health of their businesses, they consider it to be less important than other challenges they currently face such as operational and commercial concerns and overall profitability. It is also worth noting that the governance of family businesses in the GCC region is faced with issues such as succession and management of conflict, which are both often directly related. Other governance issues include transparency and accountability, formalizing management structures, improving rules and processes and the need for better practices at Board level.

2.2 Corporate Governance and Performance Many empirical studies explore the effect of the quality of a firm’s corporate governance on its shareholders’ value. As a proxy for the quality of corporate governance, researchers use various types of governance indices. Some of these indices are based on charter provisions (Gompers et al. 2003; Bebchuk at al. 2009); others are based on a combination of charter provisions and board characteristics (Brown and Caylor 2006); and still others measure factors related to the corporate governance regime in the firm’s home country (Starks and Wei 2003). Regardless of which index is used, however, the majority indicates a positive association between corporate governance quality and shareholder returns. 8

Gompers et al. (2003) find that firms with stronger shareholders’ rights have higher firm value, profits, sales growth, and lower capital expenditures, while also making fewer corporate acquisitions. Core, Guay, and Rusticus (2006) find that weak governance firms underperform strong governance firms. Whereas Bebchuk et al. (2009) construct an entrenchment index with six key provisions9 and find similar results to Gompers et al. (2003) with no importance to the remaining 18 provisions. Similar evidence is documented in Brown and Caylor (2006) using a (Gov-Score) consisting of 51 governance mechanisms and in Bhagat and Bolton (2008) who find that better governance is positively correlated with better operating performance. On the other hand, the majority of studies in emerging markets provide supporting evidence to the positive association between good governance and good corporate performance or valuation (e.g. Klapper and Love, 2004 [14 emerging markets]; Leal and Carvalhal-Da-Silva, 2005 [Brazil]; Black, Jang, and Kim, 2006 [Korea]; Black, Love and Rachinsky, 2006 [Russia]; Zheka, 2007[Ukraine]; Abor and Biekpe, 2007 [Ghana]; Chong and López-de-Silanes, 2007 [Latin America]; Black, Kim, Jang, and Park, 2008 [Korea]; Cheung, Jiang, Limpaphayom, Lu, 2008 [China]; Cheung, 2011[Hong Kong]; and Srairi, 2015[GCC]). For instance, Black, Love and Rachinsky (2006) find a strong association between governance and firm market value for Russian firms. In another study, Black et al. (2008) use Korean panel data and find similar evidence. While Cheung et al. (2008) find similar evidence for 100 large firms in China, Cheung et al. (2011) find that firms in Hong Kong that exhibit improvements (deterioration) in the quality of corporate governance display a subsequent increase (decrease) in market valuation. Recent studies explore different aspects that affect the relationship between corporate governance and performance. Cheung et al (2014) use data for China, Hong Kong, Indonesia,

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This is BCF index (Four of these six provisions limit shareholder voting power (staggered boards, limits to bylaws amendments, supermajority requirements for charter amendments, and mergers, poison pills and golden parachutes)

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Philippines, and Thailand, and report a positive relationship between each of the countries’ corporate governance practices and firm’s performance. Cheung et al. (2015) find supportive evidence to the relationship between stock liquidity as an indication of good monitoring by block-holders through institutional ownership and firm performance. Qian and Yeung (2015) find that bank’s inefficiency weakens corporate governance, which in turn hurts firm performance. Similarly, Naushad and Abdul Malik (2015) find evidence that supports the expected positive relationship between corporate governance and performance for 24 banks operating in the GCC region. In a similar study, Srairi (2015) uses data from the 2011-2013’s annual reports of the 27 Islamic banks operating in the GCC region and finds a positive relationship between governance quality and performance. The recent financial crisis casts doubts about governments’ enforcement in promoting best practices corporate governance, and also about the effectiveness of these practices in encouraging a fair distribution of wealth in the stock markets, and in preventing financial crisis. In this respect, using data from 2007 and 2008 for 296 firms from 30 countries, Erkens, Hung, and Matos (2012) find that firms with higher institutional ownership and more independent boards experienced bad stock performance compared to other firms in the sample. On the contrary, Gupta et al. (2013) report statistically significant differences in stock performance (as measured by buy-and-hold stock returns) between well governed firms and poorly governed firms. In sum, the majority of the previous studies provide strong evidence that good corporate governance predicts firm performance. Hence, we develop the following hypothesis: H1: Firm performance is positively related to its level of corporate governance.

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2.3 Corporate Ownership and Performance The literature on ownership structure and performance provides inconclusive evidence. For instance, Demsetz and Lehn (1985) offer evidence of the endogeneity of a firm’s ownership structure and find no relation between profit rate and ownership concentration. Similarly, Morck et al. (1988) document no such relation between ownership concentration and various performance measures including Tobin’s Q. Conversely, McConnell and Servaes (1990) find a significant positive association between Tobin’s Q and the percentage ownership of institutional investors. Consistently, Dahlquist and Robertson (2001) report a positive association between Swedish firms’ performance and foreign institutional investors’ holdings. Demsetz and Villalonga (2001), on the other hand, account for the endogeneity of ownership structure and find no relationship between ownership structure and performance for US firms. In the context of emerging market, Yudaeva et al. (2003) find that firms with foreign ownership are more productive than domestic firms in the Russian market. In a similar vein, Chang (2003) studied the chaebol families and their affiliates in Korea and finds no evidence that links concentrated ownership to better firm performance. However, Grant and Kirchmaier (2004) observe that ownership structures in Europe are not consistent with value maximization principles and show that dominant shareholders destroy value. Whereas Choi and Hasan (2005) find that the level of foreign ownership is positively associated with bank’s return and negatively associated with bank’s risk in Korea. Other studies in emerging markets that examine the issue of ownership and performance also provide conflicting evidence. These include Xu and Wang (1999) [China], Welch (2003) [Australia], Leal and Carvalhal-da-Silva (2005) [Czech Republic ], Earle et al. (2005) [Hungry], Kapopoulos and Lazaretou (2007) [Greece], Ke and Isaac (2007) [China]; Grosfeld and Hashi

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(2007) [Poland and Czech Republic]; Brouthers et al. (2007) [Romania]; Hu and Izumida (2008) [Japan], Perrini et al. (2008) [Italy]; Florackis et al. (2009), and Vintila, Gherghina, 2014 [Romania]; Wahba, 2014 [Egypt]; Qian and Yeung (2015) [China], and Nguyen et al. (2015) [Singapore and Vitenam]. Nguyen et al., (2015) verifies the widely held view of agency theory about the efficient monitoring effect of large shareholders in Singapore and Vietnam. They find evidence of a positive effect of ownership concentration on performance. They also find that the quality of the national governance does matter in explaining the effect of concentrated ownership on firm performance. On the other hand, Almudehki and Zeitun (2013) explore the effect of different ownership dimensions (board ownership; foreign ownership, institutional ownership, and ownership concentration) on the performance of 29 firms listed on Doha Stock Exchange during the period 2006-2011. They find that firm performance is impacted by board, foreign, and concentrated ownership. Likewise, Zeitun (2014) focuses on the whole GCC markets, and finds that ownership structure, ownership concentration, and government ownership positively affect the performance of firms in the these markets. Nonetheless, he finds that institutional and foreign ownership have no impact on performance of these firms. 10 Arouri et al. (2014) report different results for 58 banks operating in the GCC markets. They find a positive impact of family, foreign, and institutional ownership on bank performance, but no impact of government ownership on performance. In addition, the aforementioned discussions suggest that different levels of concentrated ownership (5%, 10%, 20%, and 25%) might have different effects on firm performance. Having said that, it also can be argued that highly concentrated ownership can replace weak governance, and monitor the actions of managers, which positively affects financial performance (Grossman 10

His results suggest that the age and size of the firm have positive and significant effect on firm performance.

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and Hart, 1986; Sanches-Ballesta and Gracia-Meca, 2007; Hu and Izumida, 2008; Almudehki and Zeitun, 2013; Nguyen et al, 2015). On the other hand, a high level of ownership concertation and hence too much interference with the management decisions might hurt the financial performance of the firm, especially if block-holders seek private benefits of control as argued by Goergen (2014). In this case, a lower level of ownership concentration might be the optimal solution. For example, Jameson et al. (2014) find that controlling shareholders who are on the board of management of firms in India negatively affect the performance of these firms. Accordingly, given the conflicting theories and evidence in this respect, we propose a significant effect of ownership concentration on the relation between governance and performance but do not establish any direction for this relationship. Thus we formulate the following hypothesis.

H2: The relationship between corporate governance and performance is affected by different levels of concentrated ownership.

Moreover, prior literature provides inconclusive evidence also about which type of ownership affect performance (e.g. Zeitun, 2014; Arouri et al. 2014), hence we also develop a nondirectional hypothesis as follows:

H3: The relationship between corporate governance and firm performance is affected by the type of concentrated ownership.

3.

Sample, Methodology and Descriptive Statistics. 3.1 Sample and Methodology 13

The sample consists of all firms listed in the stock exchanges of the GCC countries for which the data is available for the period 2008-2012 on Thomson Reuters Zawya database and on Datastream. Our source for collecting governance data is the National Investor’s report11. The National Investor (TNI) in cooperation with Hawkamah (The Institute of Corporate Governance) developed the BASIC (Behavioral Assessment Score for Investors and Corporations) for all publicly listed firms in the GCC region (581 companies). BASIC measures 43 parameters encompassing three different sub-groups (Trading History, Corporate Communications and Disclosure)12. Each parameter is given one point and then the total score is converted into an index with a maximum value of 10 for a complete score of 43, for instance if a firm scored 30 points then this is converted as follows: (30/43)*10 = 6.98 and so on13. Our measure of governance is similar to other measures used in the literature for instance; Klapper and Love (2004) employ a governance score compiled by Credit Lyonnais Securities Asia (CLSA). The CSLA score is a composite of 57 binary (yes/no) questions covering seven different categories: 1) management discipline, 2) transparency and disclosure, 3) board independency, 4) board accountability, 5) management accountability, 6) investor protection and 7) social awareness. Durnev and Kim (2005) use the CLSA and a disclosure practices score prepared by Standard & Poor’s (S&P) to test the association between corporate governance and valuation for a sample of firms from 27 countries. The S&P score consists of information regarding whether a firm discloses information on 91 items that are divided into three subgroups: 1) ownership and investor relations, 2) transparency and disclosure, and 3) board structure. Chong et al., (2009) construct an index with 55 governance practices that Mexican firms can 11

Back to BASICs: An alternative look at liquidity, volatility and transparency, 2008. And BASIC Evolution: An alternative look at liquidity, volatility and transparency, 2009. 12 The 43 parameters are presented in Appendix A. 13 These are the calculations of The National Investor and Hawkamah. We take the BASIC score from our data source as is without any interference in its estimation.

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voluntarily commit to and demonstrate a significant impact of corporate governance on valuation and operating performance. For a sample of Brazilian firms, Leal and Carvalhal-da-Silva (2005) construct a corporate governance index with 24 binary (yes/no) questions. The questions are classified into four groups: 1) disclosure, 2) board composition, 3) conflicts of interest, and 4) shareholder rights. Da Silveira and Barros (2007) use an index with 20 questions taking into consideration four important aspects of corporate governance: 1) access to information, 2) information content, 3) board structure and 4) ownership structure for the year 2002. Both studies find a positive link between their indices and valuation. The main feature of BASIC is that a higher score indicates a lower corporate governance risk. This applies also for each component and every category. The BASIC ranges from zero to ten and based on the previous literature it is expected that the closer a company’s score is to ten, the better its corporate governance is. Testing the effect of corporate governance practices on firm performance in the presence of concentrated ownership and ownership structure triggers the issue of endogeneity. Abdallah et al. (2015) argue that endogeneity results from the omission of explanatory variables in the model, which leads to a correlation between the model error term and its explanatory variables. This will violate a basic assumption of Ordinary Lest Squares (OLS) model. In addition, they argue that endogeneity might also arise because reverse relationship between the dependent variable and one of more explanatory variables. Previous studies (e.g. Demestz, 1983; Demestz and Villalonga, 2001, among others) point out to a reverse-relationship between ownership structure governance, and performance. The presence of endogeneity along with unobservable firm fixed effects produces biased and inconsistent ordinary least squares (OLS) estimators (Bhagat and 15

Bolton, 2008; and Nguyen et al., 2015). Nguyen et al. (2015) argue that although the use of OLS with fixed effects controls for the time-invariant unobserved firm’s (fixed) effects, it still does not fix the problem of endogeneity of the independent variables. Bhagat and Bolton (2008) point out to the fact that the inter-relationship between ownership structure, governance and performance can only be controlled for by designing a system of simultaneous equations. Given the different choices of simultaneous equations such as 3-equation model, 2SLS Cho (1998), Demestz and Villalonga (2001), and Nguyen et al. (2015), among others, suggest the use of Blundell and Bon’s (1998) generalized method of moments (GMM) to correct for the endogeneity, which is on the contrary to 2SLS and 3SLS does not rely on external exogenous instruments, which is difficult to categorize (see also Wintoki, Linck, and Netter, 2012). Therefore, to test the effect of corporate governance practices in the GCC countries on the firm’s performance while at the same time accounting for endogeneity, we employ the following Instrumental Generalized Method of Moment (GMM) regression with robust standard error and firm clustering. The validity of the instrument test or over identification test can be measured by conducting the Hansen’s J test.

Performancet 1    1CORPGOVt   2 Leveraget   3 FCFt    4CAPEX T   5 SGRt   6TOt   7 MTBVt  Industry  Year Where the Instrumental Variable CORPGOV  f (TA, Country )

(1) (2)

Performancet+1 is one of three measures as (1) the firm’s Tobin-Q measured as the natural logarithm of the book value of assets less book value of equity plus market value of equity divided by book value of assets, (2) the return on assets (ROA) that is calculated as the natural logarithm net income scaled by the book value of assets, and (3) the return on equity (ROE), which is calculated as the natural logarithm of net income scaled by the book value of equity, all 16

are calculated at time t+1. CORPGOVt is the corporate governance measures, which were explained before, and these are: BASIC, Disclosure, Corporate Communication, and Trading History, at time t. As the BASIC score and its components were made available to the public in 2008 and 2009, only, we match the firm’s BASIC score (and its components) that was released in 2008 with the firm performance during 2009. We do the same for the BASIC score of 2009, where we match the score of each firm with its performances in 2010, 2011, and 2012. It is worth noting that for the years when the BASIC score and its components data were not released, we follow the same procedure of Gompers et al., (2003) and use the previous year’s data. Following previous studies (e.g. , Black et al., 2006, Braga-Alves and Shastri, 2011, and Cheung et al., 2011), we control for the variables that affect a firm’s performance such as Debts to Assets ratio (Leverage) and in this case we use the net debt in the numerator, which is defined as total debt minus Cash and Marketable Securities. We also use Free Cash Flow scaled by total assets (FCF), capital expenditures scaled by total assets (CAPEX), sales growth rate (SGR), the natural logarithm of the percentage of traded shares from total share outstanding or share turnover (TO), and Market to Book value of equity (MTBA), at time t. We also control for the firm’s country of origin (Country), its industry (Industry), and years (Year). All variables are winsorized at 1% level. In fact, our use of the instrumental variable is in line with previous studies that support the use of size as instrumental variable for the governance index, (see e.g. Himmelberg, Hubbard and Palia, 1999; Black, Jang and Kim, 2003; Leal and Carvalhal-Da-Silva, 2005). For instance, Leal and Carvalhal-Da-Silva (2005) argue that “there is a “scale factor” that renders adopting better corporate governance practices easier and more advantageous for larger firms. Additionally,

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Klapper and Love (2004) note that there is a large variation in their measure of governance quality within specific countries.

Initially, we start by validating the results of earlier studies, for non GCC firms, and test the relationship between corporate governance and performance using GMM regressions. In the second stage we explore how such a relationship is affected by different percentages of ownership concentration by running the same regression for each level of concentrated ownership, where majority shareholders own at least 5%, 10%, 20%, or 25%. In the third stage of the analysis, we run the same model for each type of ownership; corporate, government, private and foreign ownership. By doing so, we test if the effect of corporate governance on a firm’s performance varies across different types of majority ownership. We label the type of ownership as corporate, private, government, and foreign, for the percentage of shares owned by a local corporate investor (Institutional Investor), an individual wealthy investor (private owner or a wealthy family), government, and foreign investor, respectively. We collect ownership data from Zawya, which is a Thomson Reuters Database for the MENA region. We collect all other accounting and market values variables from Thomson Reuters Datastream.

3.2 Descriptive Statistics Table 1 reports summary statistics for the BASIC scores of firms as disclosed in the Basic scores of 2008 and 2009, distributed by the listing location. The table shows evidence of heterogeneity in corporate governance scores across the GCC exchanges. For both years, 2008 and 2009, firms listed in Muscat stock exchange (Oman) appear to have the highest mean (median) BASIC score, followed by those listed in Manama (Bahrain), Abu Dhabi stock 18

exchanges, Doha (Qatar), Dubai, and the lowest are firms listed in Riyadh (Kingdom of Saudi Arabia) and Kuwait. The Table also shows evidence of an improvement in the Basic scores for most companies listed in the GCC markets, except those listed on Dubai Financial Market. The average Basic score for all GCC listed firms is 3.57 for 2008, which is lower than 3.9 for 2009. Similar results are reported for each stock exchange. For example, for Muscat, the mean Basic score is 4.69 in 2008 but increases to 5.05 in 2009, whereas for Bahrain, it is 4.34 in 2008 and increases to 4.62 in 2009. Insert Table 1 here Table 2 presents the results of the variables descriptive statistics after winsorizing the data at the 1% level. In terms of ownership, on average, 69.3% of majority shareholders own at least 5% (hperc5) of majority shares, followed by 46.5% of majority shareholders hold at least 10% (hperc10), 28.8% own at least 20% (hperc20), and 22.1% own at least 25% (hperc25). On the other hand, 42.8% of majority shareholders are local corporations (Shacorp), whereas, 15.6% are individual investors, 14.4% are government, and finally 10.4% are foreign shareholders. This indicates that the ownership in the GCC market have a low-float ratio, and also is highly concentrated. Insert Table 2 here Table 3 reports the results of the correlation matrix of the various variables used in the analysis such as: the governance variables, which include the BASIC score and its three main components, and the other control variables. Table 3 shows that the three components of the BASIC score are all positively correlated with the BASIC, and the highest is between the BASIC and corporate communication (78.9%). All other correlations are very low and is an indication of the existence of no multicollinearity problem in the analysis.

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Insert Tables 3 here. 4.

Empirical Results 4.1 Univariate Analysis

The preliminary analysis starts by stratifying the sample into three terciles according to the level of the BASIC score (Low, Medium and High)14. Table 4 shows that firms with high BASIC score (better governed firms) have a better performance than those with low BASIC score. For example, Tobin-Q for firms with high BASIC score is 0.777 compared to 0.731 for medium and 0.740 for low BASIC score firms respectively, and the difference in the mean Tobin-Q is significant at the 1% significance level as evidenced by Kruskal-Wallis statistics (KW_X2). Similar results are reported for ROA and ROE, which lends support to the fact that GCC firms with good governance system enjoy a better performance than those with weak governance system. The Free Cash Flow to Assets (FCF), which we use as a proxy for cash holding, is slightly higher for better governed firms (5.7%) than for badly governed firms (4.4%). The latter observation on cash holding implies that better governed firms (those with High BASIC scores) are less likely to exhibit agency type of behavior and therefore, this could help explain why they have better performance than badly governed firms, which is consistent with the free cash flow hypothesis (Jensen, 1986). The table also documents that better governed firms have more debt holding as the Net Debt to Assets ratio is 12.9% compared to 8.8% for badly governed firms.15 In addition, better governed firms make less capital expenditure (4.4% vs. 4.8%) but their shares are traded more than badly governed firms with TO of 0.6% vs. 0.4%, respectively, which is evidence of the higher liquidity of their shares. 14

We sort the BASIC scores in either ascending or descending order and we split the sample into three sub-samples based on the value of BASIC. So the sub-sample LOW consists of the first tercile (33%) of the sample firms with the lowest BASIC score, HIGH consists of the third tercile (33%) of the sample firms with the Highest BASIC scores and so on. 15 The Net Debt is calculated as Total Debt less Cash and Marketable Securities.

20

As for the ownership type, it is interesting to note that the percentages of firms with low BASIC scores are owned largely by local corporations (CORPORATE) and PRIVATE (individual) investors, with ownership percentages of 48% and 17.3%, respectively. These percentages are higher than those of better governed firms (39.5% and 14%, respectively). Conversely, Table 4 shows that GOVERNMENT and FOREIGN investments are directed more towards firms with better governance, with ownership percentages of 20.4% and 14.7%, respectively. These percentages are more than double those of badly governed firms (9.9% and 7%, respectively). As such, it can be argued that governments and foreign investors might contribute in improving the governance practices of those firms. On the other hand, this could be an indicator that the parties involved more in promoting good governance practices and transparency are investing in such firms because they simply expect good governance to pay off. Insert Table 4 here.

4.2 Multivariate Analysis: 4.2.1

Impact of the BASIC score and its components

The results of the univariate analysis are supported by conducting regression analysis whereby the dependent variable is one of the firm’s performance measures: Tobin-Q and ROA. Because the literature on corporate governance and performance takes into account the possible endogeneity, and since using lagged independent variables may not fully account for such a problem, we decided to employ Instrumental Generalized Method of Moment (GMM) regression with robust standard error and firm clustering. We mainly run Eq. 1. As specified in section 3.1, however, we use four models each time and for every corporate governance measure. That is, in model 1 and as a leading independent variable, we use the BASIC score as the main governance 21

measure; while in the three other models, we use each of the components of BASIC score, instead, as an independent variable. The results, which are reported in Table 5, confirm the findings of the univariate analysis. The coefficients of the governance measures (BASIC score, Disclosure, and Corporate Communication) are all positive and significant, except in model 4 where Trading History is used as a governance measure. These findings confirm our prediction that better governed firms enjoy a better performance and that they experience a higher market valuation as well. It also may imply that awareness of the importance of good governance practices has increased over time, hence, leading to a better acceptance of those practices by market participants, and to a more appreciation by investors for the impact of such practices on firm performance16. These findings are consistent with previous studies that find a positive relationship between the quality of corporate governance and firm performance. These include Gompers et al. (2003), Bebchuk at al. (2009), Brown and Caylor (2006), Starks and Wei (2003), Klapper and Love, 2004; Leal and Carvalhal-Da-Silva (2005,; Black, Jang, and Kim (2006); Black, Love and Rachinsky (2006), Zheka (2007) Black, Kim, Jang, and Park (2008), Cheung, Jiang, Limpaphayom, Lu (2008), Chong et. al (2009), Cheung, Connelly, Jiang and Limpaphayom (2011), and more recently Naushad and Abdul Malik (2015), who examine the relationship between governance and bank performance in the GCC region.

Insert Table 5 here. 4.2.2

Impact of the ownership concentration

The previous analysis showed that better governed firms experience better performance, after controlling for different firm and country factors. We also showed that previous studies 16

The above argument and explanation are in line with the observations and conclusions of various bodies involved in promoting good governance practices who believe that, as supported by previous empirical evidence in the USA and other countries, good governance practices are expected to lead to better firm performance.

22

point out that a firm’s performance is also affected by the ownership structure. It has been argued that ownership concentration mitigates agency problem because of the influence that the major shareholder exercises over the firm’s management. Previous studies investigate only the relationship between ownership concentration and firm performance, and produce conflicting results (see Fama and Jensen, 1983; Demsetz, 1983; Chang, 2003; Demsetz and Villalonga, 2001; Grant and Kirchmaier, 2004; Cheung, 2010, among others). In this section we aim to add a further dimension to the literature by examining the association between governance and performance at different levels of ownership concentration. Table 6 presents results of Eq.1 for different levels of ownership concentration (majority shareholders owning at least 5%; 10%; 20%, and 25%). The variable of interest is the coefficient of the BASIC score variable. Table 6 shows the following: first, the relation between corporate governance and a firm performance, be it Tobin-Q, ROA, or ROE, is positive and statistically significant at the 1% level for holding percentages that are at least 5% and 10%. Secondly and most importantly, the magnitude of such a relationship, (the BASIC variable’s coefficient), decreases with the increase in the percentage of concentrated ownership. This result, along with the insignificant BASIC coefficients in regressions (3, 4, 7, 8, 11, and 12), where ownership concentration is very high, i.e. at least 20% and 25%, provide new evidence on the relation between good governance and performance, and simply imply that the value addition of good governance is not necessarily maintained at high levels of ownership concentration. Our results are not in line with the prediction of agency theory about the efficient monitoring effect of large shareholders in markets with highly concentrated ownership. Therefore they are inconsistent with the view that ownership concentration is a positive function of a firm performance (Berle and Means, 1932; Jensen and Meckling, 1976) as managers exercise less 23

freedom in expropriating the firm’s resources (Amihud and Lev, 1981; Hill and Snell, 1989; Shleifer and Vishny, 1997). Our results also contrast those of Nguyen et al., (2015) who find that ownership concentration has a positive effect on performance in firms operating in Singapore and Vietnam. However, our findings are consistent with the argument advanced in prior research (see e.g. Goergen, 2014) that high level of ownership concentration creates agency problems between majority shareholders and managers/minority shareholders, in a way that makes the performance of the firm inefficient or at best less efficient. Our results are also consistent with the view that highly concentrated ownership becomes less effective in monitoring management actions and promoting good performance (Sánchez-Ballesta and Gracía-Meca, 2007), and this is the case of inactive block-holders. This can also be the case when large shareholders exercise sever monitoring over the firm and hence prevent managers from making managerial decisions that maximize shareholders value, or because large shareholders exercise heavy monitoring in order to extract private benefits at the expense of small shareholders (Earle et al. 2005; Perrini et al. 2008; Grosfled and Hashi, 2007).

These results are also consistent with the growing proposition that the performance effectiveness of corporate governance mechanisms depends on organizational and environmental characteristics (Kumar and Zattoni, 2013). They also support the view that effective corporate governance depends on “the alignment of interdependent organizational and environmental characteristics” (e.g., Aguilera et al., 2008; Aguilera and Desender, 2012; Filatotchev, Toms, and Wright, 2006). Our findings also provide supporting evidence to Desender, Aguilera, Crespi, and Garcia-Cestona (2013) who argue that the effectiveness of corporate governance mechanisms must be considered conditional on the ownership structure of the firm. Our findings 24

are also similar to those of Hovey et al. (2003) who find no relation between ownership concentration and firm performance in China. Our results fall in the category of papers that argue and find that diffuse ownership adds more value than concentrated ownership (e.g. Demsetz and Lehn,1985; Demsetz and Villalonga, 2001; Chang, 2003 and Grant and Kirchmaier, 2004). For the first time, these results provide new evidence that contributes to the corporate governance literature, which suggests that a well dispersed ownership strengthens the relationship between corporate governance and performance, while in a concentrated ownership environment; good governance does not necessarily lead to better performance.

Insert Table 6 here. 4.2.3

Impact of the ownership types

The effect of the type of ownership on the relationship between governance and performance is also another interesting dimension that has not been given enough attention in previous research. Table 7 presents the results of Eq.1 but for each type of ownership. The three performance measures used: Tobin-Q, ROA and ROE provide strong evidence of the positive association between the performance of the GCC listed firms and their levels of corporate governance for three types of majority shareholders; these are CORPORATE, GOVERNMENT and FOREIGN, while good governance does not appear to lead to better performance when a private (individual) investor is the major shareholder. Moreover, Table 7 indicates that this relationship is at its strongest level when the major shareholder is GOVERNMENT, providing supporting evidence on the importance of corporate governance for GCC governments. Our results for the effects of government on firm performance is inconsistent with Brouthers et al. (2007) and Wei (2007), who find that government ownership negatively affect the performance of firm, especially when 25

the ownership percentage is very high and more than 50%. Such inconsistent result can be related to differences in corporate governance across countries, where country characteristics influence the practice and ranking of corporate governance scores in these countries (Doidge et al., 2007). In the GCC region we may compare our findings to Arouri et al. (2014) who report positive impact of family, foreign, and institutional ownership on bank performance, but no impact of government ownership on performance for 58 banks operating in the GCC markets. Again this partial consistency with their results could be explained by the difference in sample period and characteristics as they focus only on 58 banks while our study uses the whole universe of publicly listed firms in the GCC region. However, our results are consistent with Zeitun (2014) who find that Government ownership positively affects corporate performance in the GCC region. They are also consistent with those of (Ang and Ding, 2006) who document that GLCs (Government Linked Companies) in Singapore have higher valuations and have better corporate governance than a control group of non-GLCs. They are also in line with findings reported in other studies focusing on the Asian market such as Hess et al. (2010) and Yu (2013) who document a U-shaped relationship between State ownership and firm performance for Chinese firms. Therefore, it can be argued as well that GCC governments are investing heavily to develop their capital markets, and to meet international best practices of corporate governance in order to attract more foreign direct investment. Accordingly, it is in the best interest of GCC governments to improve the performance of the state-owned firms to show their commitment to improving the governance system across the GCC countries. Furthermore, our results for foreign ownership are in line with Jeon, Lee and Moffett (2011) who find evidence of the monitoring role of foreign investors who are mostly institutional investors at the same time.

26

All in all, when considering the results of Table 6 which show that there is no relationship between governance quality and firm performance at high levels of concentrated ownership, someone may, erroneously, interpret this result as an indication that the government and local firms as major shareholders within a highly concentrated shareholder base do not appear to have a mitigating role towards the agency problem. However, when these results are also examined together with those in Table 7 which show that the positive relationship between governance quality and firm performance is not maintained for wealthy families (Private owners) as major shareholders, we may simply deduce that the wealthy families as major shareholders within a highly concentrated shareholder base do not appear to have a mitigating role towards the agency problem. Finally, this presumption is also consistent with the findings of the Pearl Initiative and PWC (2012) that corporate governance is a lower strategic priority at present for family businesses. Insert Table 7 here. 4.2.4

Further Robustness checks

We conduct further robustness checks in order to insure that the previous findings are free of any model specification errors, and for this reason, in addition to our GMM fixed-effects regressions we control for further country time variant factors such as the GDP growth rate, the level of Foreign Direct Investment (FDI), in addition to other country level factors obtained from the website of the World Bank and these include Gov_Effect (Government Effectiveness) and Reg_Quality (quality of regulation) (see e.g. Low, Tee and Kew, 2012). We replicate the analysis of tables 5, 6 and 7, however in order to conserve space we only report the results

27

reproducing table 6 and we report them in Appendix B17. All in all, our conclusions are unaltered and our earlier results of tables 5, 6, and 7 are robust. We also use pooled regression with country and industry fixed-effects and we found similar results. 5.

Conclusion, limitations and implications 5.1 Conclusions

Unlike previous studies that explore the relationship between firm performance and either governance or ownership concentration only, we investigate the relationship between performance and governance subject to different levels of ownership concentration, and also to different types of majority shareholders. Our study falls in the category of research that suggest that effective corporate governance depends on “the alignment of interdependent organizational and environmental characteristics” (e.g., Aguilera et al., 2008; Aguilera and Desender, 2012; Filatotchev, Toms, and Wright, 2006). In other words, in this paper we provide support for the view that the effectiveness of corporate governance mechanisms must be considered conditional on the ownership structure of the firm We initially provide evidence, in line with previous studies, that the level of corporate governance is positively related to firm’s performance. More interestingly, we find that such a relationship holds, and in a decreasing magnitude, as the level of ownership concentration increases from 5% to 10%; however, for high ownership concentration levels (20% or higher) we do not find a significant association between corporate governance and performance. More specifically, our results present evidence in support of the value relevance of dispersed ownership, instead, and provide new evidence on the relation between good governance and 17

Results replicating table 5 and 7 are also available upon request.

28

performance, and simply imply that the value addition of good governance is not necessarily maintained at high levels of ownership concentration. These results support the view of Young et al., (2008) whereby under Principal-Principal conflict increasing ownership concentration cannot be a remedy and may make things worse (Faccio et al., 2001) or render the performance of the firm inefficient (Goergen, 2014).

Furthermore, we document that the positive effects of corporate governance on performance is the highest when the majority shareholders are the government or local corporations. Our results are consistent with previous findings in Asia such as, Ang and Ding (2006) who document that GLCs (Government Linked Companies) in Singapore have higher valuations and have better corporate governance than a control group of non-GLCs. They are also in line with findings reported in other studies focusing on the Asian market such as Hess et al. (2010) and Yu (2013) who document a U-shaped relationship between State ownership and firm performance for Chinese firms. These results may stem from the benefits of government support and political connections which could prove to be helpful in bad market conditions as well.

5.2 Implications This paper has several important implications. Firstly, our findings add significant evidence to the existing literature as they expand our understanding about the important role that the dispersed ownership and the types of majority shareholders/block-holders play in strengthening the value-added function of good corporate governance practices. These results are very important for companies’ shareholders, management, foreign investors, regulators, and academics to help enhance stock markets development through improving best practices and 29

hence helping to reach an optimal corporate ownership structure that fits the corporate governance model in the region. Hence, the results may offer recommendations to policy makers suggesting the inclusion of minimum ownership dispersion for publicly listed companies to ensure normal trading in the stocks of these companies. Thirdly, unlocking facts relating to the practice of businesses in a region that is characterized by a secretive culture and reluctance to disclose information (Kamla and Roberts, 2010), and dominated by family businesses, is vital to many International organizations (e.g., OECD, IFC), regulators, government bodies, and standards setters. The results signal to those parties the importance of continuing their efforts in reforming and promoting investor protection, transparency and disclosure measures in order to improve the efficiency of financial markets and enhance investor confidence. In a survey about corporate governance enforcement in the MENA region, Middle East and North African Countries, Amico, (2014), highlights the fact that better corporate governance enforcement has emerged in the region, particularly, in the past three years in response to political changes, change in government priorities and policy challenge, and to calls for meeting international best practices of corporate governance. Our paper provides the first evidence that such efforts of GCC governments and other corporate governance bodies in spreading corporate governance awareness are paying off.

5.3 Limitations and future research Because no research is close to perfection, we believe that some limitations exist and these could pave the way for further research over time. For instance, GCC stock markets are still underdeveloped and trading, especially, by individual investors is not always driven by fundamental data but rather by emotional factors. Therefore, one possible limitation of our study

30

is the inability to control for behavioral factors due to the unavailability of such data for the GCC firms. Collecting data related to investor or market sentiment in the GCC region is a challenging and time consuming task which may jeopardize the timely progress of any research. Hence, future research may seek uncovering new results pertaining to the impact of investor sentiment on the relation between ownership structure and performance. Furthermore, other future research may shed lights on other developing economies with similar institutional characteristics and ownership structure. Such research may investigate and verify the existence of a mechanism creating a negative relation between government and local firm shareholding and financial performance which refutes the basic assumption of the agency theory and the mitigating role of large shareholders. Additional future research may also include reinvestigating the relation between governance and corporate performance in developed markets after accounting for the role of ownership structure. In other words, based on the notion that “one size does not fit all”, researchers may examine how adopting certain governance mechanisms maybe preferred over others by corporations with dissimilar ownership structure, and hence examine their impact on corporate performance.

31

Appendix A: BASIC Score Composition BASIC is made up of 43 parameters across 3 categories; these are: Trading History, Corporate Communications and Disclosure. Below we state the parameters within each category.

A. Trading History: Trading history is an evaluation of volatility, length of trading history, liquidity and shareholding structure. This category consists of Nine measures:

1. Stock volatility 2. Market volatility 3. Trading history 4. Trading frequency 5. Average daily turnover 6. Bid/ask spread 7. Number of shareholders 8. Possibility of foreign ownership 9. Proportion of foreign ownership B. Corporate Communication: The corporate communication score assesses the extent to which a company communicates with its shareholders and the broader market. It contains Nine measures as well 1. History of publicly available accounts 2. Availability of a corporate website 3. Availability of the latest annual report on the website 4. Availability of Investor Relations contact detail

32

5. Pre-announcement of results publication date 6. Holding of analyst meetings/conference calls 7. AGM pre-announcement date 8. AGM’s notice period in days 9. EPS calculation C. Disclosure: The disclosure score evaluates access to, and quality of, public corporate information and it consists of Twenty five measures 1. Disclosure of number of shareholders 2. Disclosure of whether or not foreign ownership allowed 3. Disclosure of percentage foreign ownership allowed 4. Disclosure available in English 5. Disclosure typed 6. Disclosure in non-alterable format 7. Complete interim results disclosure 8. Annual report items: In addition to the seven disclosure items above, the annual reports of 581 companies have been screened for the presence of the following information. a. Management/chairman’s report. b. Financial performance summary c. Summary of operations d. Corporate governance policies e. Board sub-committees f. Director independence g. Executive/non-executive directors

33

h. Management profiles i. Board member profiles j. Revenue breakdown by geography k. Revenue breakdown by business line l. Directors’ shareholdings m. Shareholders holding >= 5% of total shares n. Pre-emptive rights policy o. Proxy voting policy p. Cumulative voting policy q. Disclosure of accounting policy r. Auditor’s approval

34

Appendix B: Table 6 Replicated for Robustness tests using country variant factors and governance data from the World Bank. Dependent Model

Tobin-Q

ROA

ROE

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Sh% =>5

Sh%=>10

Sh%=>20

Sh%=>25

Sh%=>5

Sh%=>10

Sh%=>20

Sh%=>25

Sh%=>5

Sh%=>10

Sh%=>20

Sh%=>25

0.026**

0.024**

0.014

0.041

0.016***

0.011**

0.004

0.011

0.033***

0.026**

0.025

0.017

(2.15)

(2.01)

(0.21)

(0.87)

(2.58)

(2.32)

(0.43)

(1.07)

(2.64)

(2.25)

(0.92)

(0.18)

0.127

0.093

0.517

0.141

-0.002

-0.017

-0.005

-0.022

-0.175*

-0.173**

0.136

0.248

(1.34)

(1.01)

(0.66)

(0.45)

(-0.06)

(-0.66)

(-0.04)

(-0.31)

(-1.86)

(-1.97)

(0.33)

(0.31)

0.127

0.164*

-5.574

-2.727

0.182***

0.200***

-0.715

-0.546

0.449***

0.469***

-2.551

-5.315

(1.36)

(1.86)

(-0.96)

(-0.92)

(4.12)

(4.94)

(-0.76)

(-0.81)

(4.50)

(4.73)

(-0.79)

(-0.54)

0.461***

0.457***

1.935

1.598

0.131**

0.116**

0.337

0.359

0.131

0.134

0.986

2.319

(2.91)

(2.85)

(1.17)

(1.38)

(2.42)

(2.40)

(1.33)

(1.46)

(1.00)

(1.13)

(1.11)

(0.64)

0.005

0.004

0.278

0.151

0.012***

0.014***

0.051

0.039

0.020**

0.022**

0.146

0.276

(0.50)

(0.37)

(1.05)

(1.16)

(2.71)

(3.15)

(1.18)

(1.26)

(2.11)

(2.35)

(0.99)

(0.58)

0.286

0.352

0.094

-0.994

-0.025

0.139

0.085

-0.437

-0.380

-0.014

-0.300

-2.700

(0.86)

(1.06)

(0.04)

(-0.58)

(-0.10)

(0.56)

(0.14)

(-0.92)

(-0.78)

(-0.03)

(-0.19)

(-0.74)

0.090***

0.090***

0.109**

0.097***

0.002

-0.000

0.005

0.004

-0.009

-0.013

0.012

0.017

(8.47)

(8.22)

(2.38)

(3.87)

(0.62)

(-0.13)

(0.77)

(0.65)

(-0.76)

(-1.10)

(0.55)

(0.36)

0.002

0.002

-0.002

-0.002

0.002***

0.001**

0.001

0.001

0.004***

0.003***

0.002

-0.001

(1.52)

(1.47)

(-0.44)

(-0.51)

(2.92)

(2.56)

(1.11)

(1.52)

(2.79)

(2.58)

(0.71)

(-0.08)

0.002

0.002

0.006

0.005

0.001

0.000

0.000

0.001

0.002

0.001

0.004

0.001

(1.28)

(1.13)

(0.66)

(0.73)

(1.35)

(0.57)

(0.22)

(0.40)

(1.47)

(1.00)

(0.85)

(0.08)

0.001

0.001

0.003

0.001

0.001

0.001

0.002

0.001

0.000

0.000

0.003

0.005

(0.51)

(0.26)

(0.42)

(0.10)

(1.15)

(1.42)

(1.38)

(0.60)

(0.11)

(0.14)

(0.79)

(0.30)

Country/Industry/Year

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

_cons

-0.299

-0.196

-0.742

-0.479

-0.275**

-0.149

-0.040

-0.060

-0.113

0.071

-0.595

-0.660

chi2

(-0.83) 406.081

(-0.51) 419.952

(-0.37) 22.933

(-0.39) 51.985

(-2.22) 383.252

(-1.31) 426.001

(-0.12) 89.297

(-0.19) 75.562

(-0.40) 301.722

(0.26) 348.308

(-0.56) 48.253

(-0.29) 12.011

(0.000)

(0.000)

(0.852)

(0.011)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.000)

(0.025)

(0.999)

BASIC Leverage FCF Capexd SGR TO MTBV GDP_Growth Government Effectiveness Regulatory Quality

pv_chi2

35

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42

Table 1: Summary of BASIC score for the GCC markets The table contains a summary of the BASIC score for those companies listed in the GCC markets and reported in the Basic report of 2008 and 2009. The BASIC score is comprised of 43 parameters and these are reported in Appendix A along with those parameters for its components as well.

Basic Scores as of Year 2008 Abu Dhabi Bahrain Doha (Qatar) Dubai Kuwait City Muscat-Oman Riyadh (Saudi Arabia) GCC Basic Scores as of Year 2009 Abu Dhabi Bahrain Doha (Qatar) Dubai Kuwait City Muscat-Oman Riyadh (Saudi Arabia) GCC

N_Firms

Mean

Median

Min

Max

p25

p75

STD

62 45 38 40 175 126 95 581

4.13 4.34 4.03 3.90 2.64 4.69 2.77 3.57

4.155 4.98 3.985 3.865 1.99 4.75 2.36 3.77

1.53 1.39 1.71 1.54 1.29 1.54 1.59 1.29

6.23 7.49 6.33 5.78 5.55 6.89 6.09 7.49

3.65 2.05 3.53 3.2 1.71 4.32 2.19 2.19

4.73 5.74 4.5 4.41 3.81 5.36 3.09 4.69

0.84 1.81 0.96 0.96 1.18 1.00 0.97 1.40

63 46 55 174 123 40 104 605

4.38 4.62 4.40 2.96 5.05 4.36 3.06 3.9

4.16 4.78 4.37 2.42 5.21 4.19 2.46 4.07

2.32 1.38 1.61 1.27 1.90 2.41 1.74 1.27

7.28 7.95 7.46 6.31 6.79 6.38 6.58 7.95

3.73 3.68 3.45 1.78 4.63 3.81 2.29 2.39

4.84 6.02 5.15 4.19 5.75 4.69 3.43 5.03

0.95 1.78 1.26 1.30 1.03 0.85 1.23 1.49

43

Table 2: Data Descriptive Statistics Governance measure is represented by the BASIC score and its three main components, which are Trading History (Trading), Corporate Communication (CorCom) and Disclosure. The dependent variable is the firm performance, which is denoted by Tobin-Q, ROA, and ROE. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity plus the market value of equity divided the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The Return on Equity (ROE) is calculated as the natural logarithm of the Net Income divided by book value of Equity. The explanatory variables are the natural logarithm of the book value of assets (TA), sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding. Hperc5, Hperc5, Hperc10, Hperc20, and Hperc25 represent the number of shareholders who own at least 5%, 10%, 20%, and 25% of the firm’s traded shares. Shcorp, Shprivate, Shgov, and Shforeign stand for the number of firms owned by corporations, individuals, governments, or foreign shareholders. All variables were winsorized at the 1% level. NOBS represents the number of firm-year observations.

Variable

NOBS

mean

max

p25

p75

Basic Trading CorCom Disclosure Tobin-Q TA Leverage fcf_ta Capexd_ta SGR MTBV To ROA ROE Hperc5 Hperc10 Hperc20 Hperc25 Shcorp Shprivate Shgov Shforeign

1669 1669 1669 1669 1493 1611 1562 1611 1547 1589 1605 1519 1505 1556 1876 1876 1876 1876 1876 1876 1876 1876

4.016 5.364 3.705 4.076 0.749 12.290 0.113 0.049 0.044 0.106 1.573 0.006 0.035 0.042 0.693 0.465 0.288 0.221 0.211 0.167 0.079 0.057

7.46 8.44 10 128 1.398 18.648 0.810 0.356 0.407 3.341 6.69 0.131 0.291 0.507 1 1 1 1 1 1 1 1

3.12 4.68 2.22 2.69 0.624 10.320 0.000 0.000 0.002 -0.104 0.81 0.000 0.003 0.000 0 0 0 0 0 0 0 0

5.07 6.22 5.11 5.38 0.843 14.090 0.161 0.105 0.055 0.296 2.04 0.004 0.086 0.163 1 1 1 0 1 0 0 0

44

Table 3: Correlation Matrix among the BASIC score Components and control variables Governance measure is represented by the BASIC score and its three main components, which are Trading History (Trading), Corporate Communication (CorCom) and Disclosure. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity minus the market value of equity divided the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The Return on Equity (ROE) is calculated as the natural logarithm of the Net Income divided by book value of Equity. The table also includes the book value of assets (TA), sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding.. ***, **, * Denote significance at the 1%, 5% and 10% levels, respectively.

Basic Basic

Trading

CorCom

Disclosure

Tobin-Q

ROA

ROE

Leverage

FCF

TA

Capexd

SGR

TO

1

Trd_Hist

0.288***

1

CorCom

0.766***

0.180***

1

Disclosure

0.257***

-0.011

0.149***

1

Tobin-Q

0.0788**

-0.019

0.0377

0.0347

1

ROA

0.147***

-0.0630*

0.124***

0.0923***

0.318***

1

ROE

0.149***

-0.0413

0.150***

0.0740**

0.267***

0.843***

1

Leverage

0.121***

0.146***

0.0836***

0.00279

-0.03

-0.0274

-0.0483

1

FCF

0.0476

-0.0358

0.0489*

0.0471

0.291***

0.368***

0.297***

-0.106***

1

TA

0.276***

0.367***

0.566***

-0.0127

-0.0626*

0.0346

0.124***

0.0951***

-0.0194

1

Capexd

-0.039

0.0217

-0.0465

-0.033

0.198***

0.208***

0.156***

0.237***

0.209***

-0.0651*

1

SGR

0.0193

0.0221

0.0327

-0.00164

0.0647*

0.130***

0.108***

0.035

0.0429

0.0632*

0.0897***

1

TO

0.0321

-0.0713**

-0.0411

0.0129

0.014

-0.00092

-0.0119

0.0395

-0.0252

-0.193***

0.0124

0.0376

1

-0.00728

0.110***

0.0195

-0.00913

0.470***

0.0115

-0.0548*

0.0683**

0.121***

0.0863***

0.0885***

0.0574*

-0.0344

MTBV

MTBV

45

1

Table 4: Univariate Analysis for Control Variables, by the ranking of the BASIC score. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity plus the market value of equity divided by the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The Return on Equity (ROE) is calculated as the natural logarithm of the Net Income divided by book value of Equity. The other variables are the book value of assets (TA), sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding. Corporate, Private, Government, and Foreign stand for the fraction of shares owned by corporations, individuals, governments, or foreign shareholders. All variables were winsorized at the 1% level. KW_χ2 is the Kruskal Wallis rank test of significance across groups. NOBS is the number of firm-year observations. Low Medium High NOBS Variable Tobin-Q 478 TA 541 Leverage 523 FCF 541 Capexd 516 SGR 528 MTBV 538 TO 496 ROA 518 ROE 520 By Shareholder Type Corporate 554 Private 554 Government 554 Foreign 554 KW_χ2

Mean

NOBS

Mean

NOBS

Mean

KW_χ2

0.740 11.378 0.088 0.044 0.048 0.061 1.579 0.004 0.020 0.004

496 539 522 539 517 535 534 511 503 521

0.731 12.875 0.121 0.044 0.038 0.143 1.532 0.006 0.032 0.034

482 531 517 531 514 526 533 512 484 515

0.777 12.624 0.129 0.057 0.044 0.113 1.607 0.006 0.054 0.088

(0.000) (0.000) (0.000) (0.008) (0.098) (0.014) (0.028) (0.460) (0.000) (0.000)

0.480 0.173 0.099 0.070 (0.000)

556 556 556 556

0.406 0.151 0.142 0.104 (0.000)

559 559 559 559

0.395 0.140 0.204 0.147 (0.000)

(0.029) (0.620) (0.009) (0.090)

46

Table 5: Instrumental variables (GMM) regression with robust standard error, clustered by firm. Governance measure is represented by the BASIC score and its three main components, which are Trading History (Trading), Corporate Communication (CorCom) and Disclosure. The dependent variable is the firm performance, which is denoted by Tobin-Q and ROA. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity plus the market value of equity divided the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The explanatory variables are sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding. All variables are winsorized at the 1% level, and Z statistics are reported in parentheses. ***, **, * Denote significance at the 1%, 5% and 10% levels, respectively.

Dependent Model

(1) Basic

Tobin-Q (2) (3) (4) Disclosure Corcom Trading

(5) Basic

ROA (6) (7) Disclosure Corcom

(8) Trading

0.018*** (3.88)

0.014*** (2.64)

0.015** (2.24)

-0.007 (-0.25)

0.016*** (3.63)

0.011*** (3.47)

0.014*** (2.88)

-0.002 (-0.44)

Leverage

0.045 (0.88)

0.023 (0.53)

0.049 (0.84)

-0.005 (-0.12)

-0.036* (-1.79)

-0.054** (-2.22)

-0.031 (-1.44)

-0.055*** (-2.62)

FCF

0.165** (2.47)

0.233*** (3.63)

0.144 (1.55)

0.273*** (4.85)

0.234*** (5.76)

0.308*** (6.76)

0.222*** (4.89)

0.300*** (8.34)

Capexd

0.312*** (2.71)

0.280*** (2.66)

0.346** (2.56)

0.191* (1.90)

0.096** (2.17)

0.082* (1.71)

0.107** (2.17)

0.041 (0.94)

SGR

0.007 (0.74)

0.002 (0.21)

0.005 (0.56)

-0.004 (-0.57)

0.012*** (2.82)

0.006 (1.40)

0.012*** (2.93)

0.010** (2.43)

TO

-0.194 (-0.64)

-0.274 (-0.88)

-0.109 (-0.34)

-0.364 (-1.10)

-0.133 (-0.59)

-0.167 (-0.78)

-0.081 (-0.33)

-0.148 (-0.61)

MTBV

0.079*** (10.83)

0.079*** (11.22)

0.079*** (10.55)

0.078*** (11.78)

-0.002 (-0.66)

-0.003 (-1.00)

-0.002 (-0.74)

-0.003 (-1.07)

Country Industry Year _cons

Yes Yes Yes 0.175 (1.23)

Yes Yes Yes 0.311*** (3.24)

Yes Yes Yes 0.152 (0.72)

Yes Yes Yes 0.633*** (5.26)

Yes Yes Yes -0.034 (-0.59)

Yes Yes Yes 0.115* (1.87)

Yes Yes Yes -0.056 (-0.73)

Yes Yes Yes 0.145** (2.54)

527.466 (0.000)

673.357 (0.000)

474.381 (0.000)

542.903 (0.000)

391.739 (0.000)

298.867 (0.000)

334.042 (0.000)

330.461 (0.000)

(0.137)

(0.517)

(0.164)

(0.130)

(0.553)

(0.157)

(0.535)

(0.320)

Gov.Measure

Wald_chi2 pv_Chi2 Hansen-J test of overidentification (p-value)

47

Table 6: Instrumental variables (GMM) regression with robust standard error and firm cluster, by the holding percentages Governance measure is represented by the BASIC score. The dependent variable is the firm performance, which is denoted by Tobin-Q and ROA. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity plus the market value of equity divided the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The Return on Equity (ROE) is calculated as the natural logarithm of the Net Income divided by book value of Equity. The explanatory variables are sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding. Sh%=> represents the least holding percentages. All variables are winsorized at the 1% level, and Z statistics are reported in parentheses. ***, **, * Denote significance at the 1%, 5% and 10% levels, respectively. Dependent Model

BASIC Leverage FCF Capexd SGR TO MTBV Country Industry Year cons Wald_chi2 pv_Chi2

Tobin-Q

ROA

ROE

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

Sh% =>5

Sh%=>10

Sh%=>20

Sh%=>25

Sh%=>5

Sh%=>10

Sh%=>20

Sh%=>25

Sh%=>5

Sh%=>10

Sh%=>20

Sh%=>25

0.028** (2.13) 0.082 (1.13) 0.173** (2.39) 0.378*** (2.87) 0.004 (0.35) 0.274 (0.92) 0.083*** (9.28) Yes Yes Yes 0.100 (0.41) 413.557 (0.000)

0.025** (2.05) 0.070 (0.97) 0.200*** (2.72) 0.404*** (2.86) 0.005 (0.44) 0.339 (1.03) 0.085*** (8.97) Yes Yes Yes 0.075 (0.29) 418.947 (0.000)

0.007 (0.20) 0.018 (0.06) -3.520 (-1.31) 1.359* (1.86) 0.189 (1.47) 0.380 (0.27) 0.108*** (3.93) Yes Yes Yes 0.866 (1.06) 49.502 (0.000)

0.027 (0.87) -0.000 (-0.00) -2.941 (-1.28) 1.598** (1.97) 0.161 (1.48) -0.907 (-0.55) 0.094*** (4.64) Yes Yes Yes 0.533 (0.85) 55.625 (0.000)

0.016*** (3.70) -0.028 (-1.08) 0.234*** (6.01) 0.087* (1.84) 0.012*** (2.84) -0.081 (-0.34) -0.002 (-0.75) Yes Yes Yes -0.034 (-0.50) 375.319 (0.000)

0.013*** (3.37) -0.027 (-1.15) 0.235*** (6.28) 0.082* (1.89) 0.015*** (3.34) 0.078 (0.31) -0.003 (-1.12) Yes Yes Yes -0.001 (-0.02) 394.023 (0.000)

0.007 (0.60) -0.060 (-0.75) -0.922 (-1.09) 0.409* (1.80) 0.061 (1.53) 0.150 (0.23) 0.009 (1.14) Yes Yes Yes 0.250 (0.96) 62.010 (0.000)

0.011 (1.29) -0.050 (-0.87) -0.617 (-0.95) 0.388* (1.72) 0.042 (1.42) -0.404 (-0.81) 0.005 (0.83) Yes Yes Yes 0.145 (0.86) 67.405 (0.000)

0.026** (2.27) -0.259*** (-2.73) 0.557*** (5.68) 0.047 (0.36) 0.018* (1.84) -0.526 (-1.06) -0.014 (-1.14) Yes Yes Yes 0.359* (1.84) 262.425 (0.000)

0.023** (2.26) -0.221*** (-2.59) 0.527*** (5.34) 0.089 (0.74) 0.021** (2.15) -0.122 (-0.24) -0.012 (-0.95) Yes Yes Yes 0.375** (2.07) 312.846 (0.000)

0.019 (0.83) -0.212 (-1.16) -1.939 (-1.06) 0.829* (1.70) 0.120 (1.43) 0.080 (0.06) 0.019 (0.94) Yes Yes Yes 0.678 (1.27) 60.146 (0.000)

0.018 (0.46) 0.125 (0.27) -4.945 (-1.09) 2.315 (1.33) 0.262 (1.19) -2.469 (-0.87) 0.014 (0.43) Yes Yes Yes -0.019 (-0.02) 16.075 (0.000)

48

Table 7: Instrumental variables (GMM) regression with robust standard error and firm cluster, by ownership type Governance measure is represented by the BASIC score. The dependent variable is the firm performance, which is denoted by Tobin-Q and ROA. Tobin-Q is calculated as the natural logarithm of the book value of total assets minus the book value of total equity plus the market value of equity divided the book value of total assets. The Return on Assets (ROA) is calculated as the natural logarithm of the Net Income divided by the book value of total Assets. The Return on Equity (ROE) is calculated as the natural logarithm of the Net Income divided by book value of Equity. The explanatory variables are sales growth rate (SGR), Market to Book value of equity (MTBV), Leverage and is calculated as Net Debt scaled by book value of assets whereby Net Debt is calculated as Total Debt minus Cash and Marketable securities, free cash flow scaled by total assets (FCF), capital expenditure scaled by total assets (Capexd), and shares turnover (to) measured as the natural logarithm of the total number of traded shares divided by the number of shares outstanding. All variables are winsorized at the 1% level, and Z statistics are reported in parentheses. ***, **, * Denote significance at the 1%, 5% and 10% levels, respectively. Dependent Tobin-Q ROA ROE Model (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Share Type Corporate Government Private Foreign Corporate Government Private Foreign Corporate Government Private Foreign BASIC 0.020** 0.032** 0.049 0.016** 0.019*** 0.028** -0.053 0.015*** 0.046*** 0.142** -0.070 0.052*** (2.25) (2.55) (1.03) (2.31) (5.01) (2.24) (-0.67) (2.78) (5.36) (2.52) (-0.77) (3.10) Leverage -0.048 0.118 0.036 -0.166 -0.053* -0.048 -0.334 -0.068 -0.248*** -0.456*** -0.617 -0.230 (-0.70) (1.36) (0.15) (-1.58) (-1.82) (-1.20) (-1.13) (-1.51) (-2.69) (-2.68) (-1.38) (-1.53) FCF 0.277*** 0.427** 0.026 0.197 0.225*** 0.251*** 0.400 0.118* 0.501*** 0.611* 0.597* 0.107 (3.90) (2.40) (0.15) (1.42) (5.88) (3.30) (1.37) (1.88) (4.88) (1.83) (1.71) (0.62) Capexd 0.303** -0.058 0.598*** -0.444 0.107** 0.063 0.040 0.245* 0.154 0.250 -0.102 0.828** (2.16) (-0.33) (2.74) (-1.11) (2.20) (0.90) (0.16) (1.82) (1.05) (1.19) (-0.24) (2.20) SGR -0.004 -0.013 0.024 0.006 0.004 0.014* -0.006 0.013* 0.008 0.032 -0.016 0.040* (-0.44) (-1.19) (1.02) (0.47) (0.94) (1.84) (-0.22) (1.83) (0.76) (1.61) (-0.39) (1.79) TO -0.031 0.980 0.209 -0.002 -0.245 0.231 0.175 -0.147 -0.784 -1.921 -0.277 -0.694 (-0.09) (1.02) (0.28) (-0.00) (-1.45) (0.40) (0.51) (-0.46) (-1.64) (-1.02) (-0.38) (-0.68) MTB 0.076*** 0.103*** 0.070*** 0.068*** -0.003 0.009 -0.035 0.007 -0.016 0.048 -0.066 0.006 Country Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes _cons 0.488*** 0.645 0.139 1.126*** -0.009 0.095 0.803 -0.074 0.096 -0.401 1.474 -0.271 (2.90) (0.82) (0.23) (4.20) (-0.21) (0.31) (0.93) (-0.94) (0.64) (-0.41) (1.29) (-1.09) Wald_chi2 427.543 122.463 311.635 213.935 260.203 181.859 94.266 101.585 152.223 58.840 28.552 82.468 pv_chi2 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

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