the impact of board size on firm value: evidence from the asian

www.ajbms.org Asian Journal of Business and Management Sciences

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©Society for Business Research Promotion | 22

The Impact of Board Size on Firm Value: Evidence from

The Asian Real Estate Industry

Josephus P. Weterings University of Amsterdam E-mail: [email protected] Dirk M. Swagerman Groningen University, Faculty of Economics and Business P.O. Box 800 9700 AV Groningen The Netherlands E-mail: [email protected]

ABSTRACT

This study examines the impact of board size on firm value (as measured by Tobin’s Q) for a sample of 155 ordinary property firms and real estate investment trusts (REITs) listed in Hong Kong, Malaysia and Singapore. In contrast with findings of prior research, I present evidence for a positive relationship between board size and firm value for listed ordinary property firms. Results on REITs are not significant because of limited sample size. Results are robust to a number of controls including firm size and leverage.

Keywords: Reit, Tobin’s Q, JEL classification: G32, L85, R11

1. INTRODUCTION Over the past decade, the importance of corporate governance has been clearly demonstrated by corporate scandals like those at Enron, Worldcom, Ahold and Parmalat. As a reaction to these scandals, governments started to develop corporate governance codes. However, while empirical evidence on the existence of a negative relationship between board size and firm value is strong, none of the newly developed corporate governance codes includes requirements on board size. In February 2011, the CFA Institute1 published the report Asia Pacific REITs: building trust through better REIT governance, which called for considerable improvements of corporate governance practices in the Asian real estate investment trust sector. Since requirements on board size were not covered in present corporate governance codes, the report triggered me to examine the impact of board size on firm value in the South East Asian real estate sector, including listed ordinary property firms as well as REITs. The research question is: “What is the impact of board size on firm value in the Hong Kong, Malaysian and Singapore listed real estate market?” Like other scholars, we use a modified version of Yermack’s (1996) approach to answer this question. We regress the log of board size on firm value as measured by Tobin’s Q and include controls for firm size and leverage. The sample consists of 155 ordinary property firms and REITs listed in Hong Kong, Malaysia and Singapore for the years 2009 or 2010.

1 The CFA Institute is a not-for-profit organization aiming to support investors by setting the highest standards of ethics, education and

professional excellence. The Institute has more than 100,000 members worldwide.

mailto:[email protected]

mailto:[email protected]


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The structure is as follows. Section 2 reviews boards of directors, agency costs, corporate governance and literature on the relation between board size and firm value. Section 3 discusses REIT characteristics and markets. Subsequently, Section 4 contains hypotheses and Section 5 describes methodology. Next, Section 6 provides results. Finally, Section 7 discusses results and Section 8 concludes the study. 2. BOARD SIZE AND FIRM VALUE 2.1 Board Of Directors The board of directors is an institution intended to control management on behalf of shareholders. The board is in charge of defining and/or approving major business decisions and corporate strategy like disposal of assets, investments or acquisitions, and tender offers made by acquirers. Other responsibilities include executive compensation, oversight of risk management and audits. The board can also offer advice and network connections to management (Tirole, 2006, p. 29-30). Hermalin and Weisbach (2003, p. 7) provide us with a more theoretical definition. They state that, “boards of directors are an economic institution that, in theory, helps to solve agency problems inherent in managing an organization.” Although having a board is a legal requirement for incorporation, Hermalin and Weisbach (2003, p. 7) assume that its economic function is determined by the organizational problems they help to address. In their view, boards are a market solution to an organizational design problem. A problem resulting in agency costs. Boards differ heavily across countries. While some European countries know a two-tier system, whereby a separate executive board and supervisory board exist next to each other, other countries employ a one-tier system. In a one-tier system executives and non-executive directors are in the same board, called the Board of Directors. In the remainder of this thesis I refer to a one-tier board when mentioning the board of directors. 2.2 Agency Costs Literature on agency costs dates back to 1932. In that year, Berle and Means published their book The Modern Corporation and Private Property. They stated that historically most corporations were owned by management, but since corporations grew bigger and bigger, no single person would be wealthy enough to own a corporation. Management would no longer own the entire firm, which Berle and Means (1932) called the separation of ownership and control. Their main concern was that because incentives of owners differ from those of management, agency problems could arise. In the words of Tirole (2006, p. 15), “they showed that shareholder dispersion creates substantial managerial discretion, which can be abused.” Shleifer and Vishny (1997, p. 741) similarly describe the agency problem as “the difficulties financiers have in assuring that their funds are not expropriated or wasted on unattractive projects by management.” Expropriation can take the form of theft, fraud, insider trading, transfers or bribes, empire building, corporate perks, excessive executive pay, entrenchment and so forth (Sautner, 2010). Costs to shareholders associated with these practices are called agency costs. The next paragraph will discuss how these costs are minimized by shareholders. 2.3 Corporate Governance Corporate governance relates to “the ways in which suppliers of finance to corporations assure themselves of getting a return on their investment” (Shleifer and Vishny, 1997, p. 737). In fact, this is the same as minimizing agency costs. Corporate governance mechanisms aimed to minimize agency costs include (next to boards of directors): ownership concentration, market for corporate control and takeovers, executive


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compensation, legal environment, corporate debt, product market competition and financial analysts (Sautner, 2010). However, in this thesis I focus on boards of directors. Over the past decade, the importance of corporate governance has been clearly demonstrated by corporate scandals like those at Enron, Worldcom, Ahold and Parmalat. As a reaction to these scandals, governments started to develop corporate governance codes. For instance, the U.K. introduced the Combined Code in 2003. The code requires the board to consist of at least one-half of independent directors, semi-annual financial reporting and recommends a separation of the Chairman and CEO-role. Compliance is not obligatory, but if a corporation chooses to do not, it has to explain why. In the U.S. more or less similar requirements were introduced when the Conference Board-rules came into force in 2003. These include, amongst other things, a requirement for a substantial majority of independent directors on boards and quarterly financial reporting, as required by law. As with the U.K. Combined Code, a comply or explain-regime was introduced. However, none of the newly developed corporate governance codes includes requirements or recommendations on board size. A questionable feature because, as the next paragraph will show, empirical evidence on the impact of board size on firm value is strong. 2.4 Board Size And Firm Value Prior research on the relation between board size and firm value gathered pretty consistent results. Except for one, all scholars find a significant inverse relationship. A few of them research firm profitability instead of firm value because of non-accessible market values, for example when looking at closely held corporations. Literature on board size and firm value firstly emerged in the early 1990s with the articles of Lipton and Lorsch (1992) and Jensen (1993). They advocated small boards since they believed boards would become ineffective when a group grows too large, thereby building on organizational behavior theory like Hackman (1990). In response to the suggested relationship of Lipton and Lorsch (1992) and Jensen (1993), Yermack (1996) writes a groundbreaking article. He finds a significant negative relationship between board size and firm value (as measured by Tobin’s Q) for a sample of 452 U.S. corporations during 1984-1991. His article was the first to research the link between board size and firm value empirically. Many other scholars would build further on his work, while having a comparable approach. Gertner and Kaplan’s paper The Value MaximizingBoard (1996) focuses on the boards of reverse leveraged buyouts. They argue that because of strong incentives, LBO specialists structure those boards in a way that is maximizing firm value. In line with Yermack’s findings, Gertner and Kaplan (1996) report reversed LBO boards to be smaller. Eisenberg, Sundgren and Wells (1998) research small and midsize Finnish firms since empirical evidence till then mainly focused on U.S. corporations. Because most corporations of their sample are closely held, they cannot use market valuation data. Instead, they calculate return on assets as a proxy for firm performance and, indirectly, firm value. They find a significant negative correlation between board size and profitability (as measured by ROA) for 1992-1994. In their study of corporate ownership and board structure in Singapore, Mak and Li (2001) find an insignificant negative relationship between board size and firm value (Tobin’s Q) while examining 147 Singapore corporations using 1995 data. However, in a follow-up paper Mak and Kusnadi (2005) investigate the relation between board size and firm value using more recent data (financial year 1999/2000) and a larger sample size (230 Singapore and 230 Malaysian corporations). In this paper they do find a significant negative relationship between board size and firm value.


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Also focusing on Malaysia, Shakir (2008) finds a small but significant negative relationship between board size and firm value (Tobin’s Q) while using a sample of 81 property firms listed in Malaysia. Her dataset covers the period 1999-2005. In an extensive study, Cheng (2008) amplifies evidence on the negative relation between board size and firm value by finding a significant relationship for a sample of 1,252 U.S. corporations during 1996-2004. Examining 6,850 Danish firms that are closely held, Bennedsen, Kongsted and Nielsen (2008) find a significant negative correlation between board size and firm performance (ROA) for board sizes of 6 and up. Overall, findings are consistent. All scholars find negative relationships, independent of country, industry, time period or sample size. See Figure 1 for an overview of findings.

<<Here Figure 1: Literature overview>>

Finally, in line with scholars discussed above, Ning, Davidson and Wang (2010) also find a significant relationship between board size and firm value (Tobin’s Q). Their sample consists of 473 U.S. firms over a 12-year period from 1988-1999. 3. ASIAN REAL ESTATE MARKETS Although the title of this chapter refers to Asia as a whole, my thesis focuses on Hong Kong, Malaysia and Singapore. These South East Asian countries enjoyed steady economic growth over the past decade and recently introduced REITs, which I discuss in paragraph 3.3. Finally, they have reasonably well-developed stock markets which enables the use of market data. 3.1 Asian Markets Asian markets differ from those in many Western economies. For example, in their paper on Singapore board structure, Mak and Li (2001, p. 235) mention a weak market for corporate control, more concentrated stock ownership and significant government ownership in many private sector firms. Another important difference is the demographic situation. As Moody’s and ICRA (2007) show in their report, in many Asian countries household size is decreasing and income level is increasing. Asian economies are not as mature as their Western counterparts, leading to higher growth. However, Lee (2001) states that investing in Asian economies is riskier and mentions four types of risk that an investor should take into account: investment risk, currency risk, political risk and institutional risk. He finds that market transparency, as part of institutional risk, is most important to the investment decision, while currency risk and political risk are not as important as one would expect. So, Asian markets are characterized by favorable demographics, high growth and in some countries, well-developed stock markets (Hong Kong, Malaysia, Singapore). This positive outlook however, is accompanied with concerns on corporate governance practices (weak market for corporate control, significant government ownership and low market transparency). 3.2 Asian Real Estate As I mentioned above, Hong Kong, Malaysia and Singapore have reasonably well-developed stock markets, that are, amongst other things, characterized by a large property sector. Due to land shortage and modest supply, real estate prices are very high, especially in Hong Kong and Singapore. Demographics (decreasing household size and increasing income level) also contribute to rising real estate prices. In the past decade, Hong Kong, Malaysia and Singapore introduced REITs, a real estate security that I discuss in the next paragraph.


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3.3 REITs 3.3.1 Characteristics

REIT stands for Real Estate Investment Trust. REITs are not like shares; they form a special asset class designed for the real estate sector. They issue units instead of shares. The holder of such a unit is called a unitholder instead of a shareholder. According to a recent report (CFA, 2011, p. 5), REITs, among other things:

- Enable investment in a diversified pool of income producing real estate assets - Are typically structured as unit trust and as such listed and traded at a stock

exchange - Enjoy flow-through taxation - Generate a high yield

So, REITs make it possible for individual investors to invest in a diversified portfolio of real estate, reducing their portfolio risk. Moreover, REITs provide liquidity to real estate by creating a secondary market. REITs are typically structured as shown in Figure 2, which is an edited version of the figure provided by the CFA (2011, p. 5). The trustee is often a bank and has to protect the rights and interests of unitholders by overseeing the functioning of management (CFA, 2007, p. 6). The manager is external to the REIT and is paid for performing management duties like operations, financing and property management (CFA, 2011, p. 6).

<<Here Figure 2: Typical REIT structure>>

Flow-through taxation implies that a REIT is not taxed on its income, but instead distributions to unitholders are taxed, preventing double taxation. Another fiscal benefit is the exemption of stamp duty on transfers of property to REITs (Singapore, Malaysia). However, in return for tax benefits, REITs have to comply with certain requirements. For instance, at least 90% of income has to be distributed to unitholders (Hong Kong, Malaysia and Singapore). In Singapore, engaging in property development or mortgages and/or securities with corresponding underlying values is prohibited for REITs. Singapore legislation also demands proper diversification and restricted gearing, which depends on credit rating. Hong Kong limits borrowing to 35% of gross asset value for all REITs (Loyens and Loeff, 2007). Finally, REITs have to comply with governance requirements on unitholder rights, related-party transactions, fee structure and mandatory disclosure. Most REITs primarily own commercial real estate like shopping malls and offices. Residential, industrial, hospitality and healthcare properties are less prevalent but also included in portfolios. Not all properties a REIT owns are located in the country of listing. For instance, CapitaRetail China Trust is listed in Singapore but owns mainly Chinese shopping malls. 3.3.2 Markets The first countries to enable the listing of REITs were the U.S. in 1962 and the Netherlands in 1969 (the first Dutch REIT was Rodamco, now part of Unibail-Rodamco). Australia followed in 1971 but it was not before 1990 that a fourth country introduced a REIT structure. However, over the past two decades a massive number of countries followed, including Japan, Germany, Italy, the U.K and France. The South East Asian REIT market is relatively young. In 2002 the first Singapore REIT, CapitaMall Trust, was listed. In 2005, The Link REIT was the first REIT to be listed in Hong Kong. Also in 2005, Axis-REIT was listed as Malaysia’s first REIT. Since then, the REIT market has shown a remarkable pace of growth. At the moment, 21% of worldwide REIT market capitalization is in the Asia-Pacific region, of which 14% is attributable to Singapore, 8% to Hong Kong and less than 1% to Malaysia. Australia and Japan count for 58% and 20% respectively (CFA, 2011, p. 8). In October 2010, total market capitalization of


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the Asia-Pacific was 89 billion U.S. dollar (CFA, 2011, p. 8). Singapore currently has 23 listed REITs, Hong Kong 9, and Malaysia 13. 4. HYPOTHESES The relation between board size and firm value has been described by many scholars. All report an overall negative relationship, and most of them also report that relationship to be significant. Our research focuses on the Asian real estate sector and more specifically, on the real estate sector of Hong Kong, Malaysia and Singapore. We distinguish between listed ordinary property firms and REITs and examine both separately as well as together. We do expect board size to be negatively associated with firm value in all subsamples, although the legal structure of REITs is considerably different from that of ordinary firms. Our main hypotheses are: H1: For ordinary property firms listed in Hong Kong, Malaysia and Singapore, board size is negatively related to firm value. H2: For Hong Kong, Malaysian and Singapore REITs, board size is negatively related to firm value. H3: For the Hong Kong, Malaysian and Singapore listed real estate sector as a whole, board size is negatively related to firm value. 5. METHODOLOGY 5.1 Data Description Our initial sample consists of all listed property sector corporations and REITs in Hong Kong, Malaysia and Singapore as of December 31, 2010. They totaled 60 for Hong Kong, 96 for Malaysia and 67 for Singapore. Corporations qualified for this sample by being listed as a property sector constituent at the SGX (Singapore), by being listed as a property sector constituent at the MYX (Malaysia) or by being listed as a property & construction sector constituent at the Hang Seng Composite Industry Index (Hong Kong). Unfortunately, the latter does not distinguish between property and construction, making me exclude all non-property corporations by hand. Also we exclude corporations that are highly illiquid, are in liquidation or have too many missing values for variables. Corporations and REITs that are cross-listed in two or more countries under examination we exclude from the total sample but are still included in country subsamples. Our final sample then consists of 52 Hong Kong-based, 49 Malaysia-based and 55 Singapore-based corporations and REITs. See Appendix A for an overview of the final sample. Next, we construct eight subsamples: one containing all listed ordinary property firms (ALL STOCKS), all REITs (ALL REITS), Hong Kong firms (HK STOCKS), Hong Kong REITs (HK REITS), Malaysian firms (MK STOCKS), Malaysian REITs (MK REITS), Singapore firms (SP STOCKS) and Singapore REITs (SP REITS). For the total sample, we collect data on financial variables and board size. The main source for these data is Bloomberg, a financial information provider. Missing information we complement by consulting annual reports. The main variables for which we collect data are board size and Tobin’s Q (as a measure of firm value). Control variables include a dummy for the year of data collection, market capitalization as a measure of firm size and debt/equity-ratio as a measure of leverage. These were also used by earlier scholars (Yermack, 1996; Mak and Li, 2001; Mak and Kusnadi, 2005; Shakir, 2008). We do not include board independence since prior research showed that board independence is not linked to firm value (Yermack, 1996; Mak and Li, 2001; Mak and Kusnadi, 2005; Shakir, 2008). We do not include a proxy for investment opportunities or capital expenditures/sales-ratio since we believe this variable is less relevant to the property sector. Moreover, while examining the Malaysian property sector,


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Shakir (2008) also does not include a proxy for this. Lastly, we do not include a proxy for diversification or business segments since all corporations and REITs in my sample focus on the property sector. We will now discuss more extensively the variables we do use in the rest of my thesis, starting with the dependent variable measuring firm value. For all variables we use 2010 data. However, when 2010 data are not available, I use 2009 data. This is reflected in the dummy for the year of data collection. See Figure 3 for descriptive statistics of the total sample, stock subsample and REIT subsample. Other subsamples are to be found in Appendix B. 5.1.1 TOBIN’S_Q We measure firm value using Tobin’s Q, which all relevant scholars do when examining listed corporations (Yermack, 1996; Mak and Li, 2001; Mak and Kusnadi, 2005; Shakir, 2008; Cheng, 2008; Ning, Davidson and Wang, 2010). Tobin’s Q is calculated by dividing market value of assets by replacement cost of assets (Yermack, 1996, p. 190). Market value of assets is calculated by multiplying the number of shares outstanding with the closing price as of December 31, 2010. Replacement cost of assets is calculated by book value of assets minus book value of total liabilities as of December 31, 2010. A Tobin’s Q below 1 reflects a discount to net asset value while a Tobin’s Q higher than 1 reflects a premium to net asset value. Mean Tobin’s Q for my total sample is 0.98, while the mean of the stock subsample and REIT subsample is 0.99 and 0.94 respectively. 5.1.2 Board Size Since Hong Kong, Malaysia and Singapore all employ the one-tier board system, we measure board size by the total number of executive and non-executive directors of the board as of December 31, 2010. Mean board size for my total sample is 8.86, while the mean of the stock subsample and REIT subsample is 9.16 and 7.83 respectively. However, since we expect the association between board size and firm value to be convex (firm value first increasing and then declining with board size), we use the natural logarithm of board size instead of actual board size in my regression. I call the natural logarithm of board size BOARD_LOG. Earlier scholars followed a comparable procedure (Yermack, 1996; Cheng, 2008). 5.1.3 Data For all financial and board size variables, we use 2010 data. However, when 2010 data is not available, I use 2009 data for all variables of a particular corporation or REIT. To control for distorted data, we include a dummy named DATE. Its value equals 1 when 2010 data is used and 0 when 2009 data is used. 5.1.4 Market Cap As a control variable, MARKET_CAP stands for market capitalization in thousands. The variable measures firm size, which is an important factor when examining Tobin’s Q. Scholars find an overall positive impact of firm size on firm value (Yermack, 1996; Mak and Kusnadi, 2005; Shakir, 2008; Cheng, 2008; Bennedsen, Kongsted and Nielsen, 2008; Ning, Davidson and Wang, 2010). Because Hong Kong, Malaysia and Singapore have different currencies, we convert all market capitalizations to Singapore dollars in order to be able to compare firm size. We use the exchange rate of July 12, 2011 which is 2.4687 Malaysian ringgit (MYR) or 6.3496 Hong Kong dollar (HKD) per Singapore dollar (SGD). Mean market capitalization for my total sample is 2,676,695 SGD, while the mean of the stock subsample and REIT subsample is 2,989,490 SGD and 1,604,253 SGD respectively.


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5.1.5 Debt Equity The last control variable we include is the debt/equity-ratio, which proxies for leverage. Earlier research also includes this control variable and finds a significant positive impact of leverage on firm value (Mak and Kusnadi, 2005; Cheng, 2008). The debt/equity-ratio is calculated by dividing total debt by total equity. Mean debt/equity-ratio for my total sample is .61, while the mean of the stock subsample and REIT subsample is .65 and .47 respectively. 5.2 Data Analysis The method I use to analyze data is multiple regression. More specific: we perform an Ordinary Least Squares (OLS) regression. Since OLS assumes a linear relation between variables, we adjust for this by using the natural logarithm for board size instead of board size itself. Our significance level is 5%. TOBINS_Q is my dependent variable and we enter BOARD_LOG, DATE, MARKET_CAP and DEBT_EQUITY as independent variables. Since we make use of actual market data, no reliability analysis is needed. We do check for multicollinearity. However, no multicollinearity problem arises because tolerance levels are significantly above .20 and VIF values are significantly below 5. This holds for my total sample as well as for all subsamples. Checks for homoscedasticity and skewness do not yield any problems.

<<Here Figure 3: Descriptive statistics of main samples>> 6. RESULTS 6.1 Pearson Correlations Pearson correlations of my total sample are shown in Figure 4. At the .01 level of significance, TOBINS_Q is positively correlated to all other variables, including BOARD_SIZE. Next, MARKET_CAP is positively correlated to BOARD_SIZE and DATE is positively correlated to DEBT_EQUITY.

<<Here Figure 4: Correlations of total sample>> See Appendix C for correlations of the stock subsample and REIT subsample. 6.2 Regression Analysis This section provides OLS regression results for the main samples (total sample, stock subsample and REIT subsample). See Appendix D for results of other subsamples. For the stock subsample and total sample, regression models are of significant explanatory power. However, the regression model of the REIT subsample is not, probably at least in part because of its small sample size. From the other subsamples, only Malaysian Stocks and Hong Kong Stocks have a significant regression model (at the .05 significance level). The regression model of the total sample has an R-squared of .264, meaning that 26.4% of total variance is explained by the variables included in the model. Figure 5 shows regression coefficient estimates for the stock subsample. Although hypothesis 1 states that for ordinary property firms listed in Hong Kong, Malaysia and Singapore board size is negatively related to firm value, regression analysis results do not yield support for this. Instead, I find a significant positive relation between BOARD_LOG and TOBINS_Q. So, hypothesis 1 is rejected. As expected, I find MARKET_CAP and DEBT_EQUITY to be positively related to TOBINS_Q, although only DEBT_EQUITY is of significance. DATE also displays a significant impact.

<<Here Figure 5: Regression coefficient estimates for stock subsample >>


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Figure 6 shows regression coefficient estimates for the REIT subsample. Although hypothesis 2 states that for Hong Kong, Malaysia and Singapore REITs board size is negatively related to firm value, regression analysis results do not yield support for this. We do find BOARD_LOG and TOBINS_Q to be negatively related, but the relationship is insignificant. So, hypothesis 2 is rejected. As expected, we find MARKET_CAP and DEBT_EQUITY to be positively related to TOBINS_Q. However, both relations are insignificant. DATE is not included in this regression since the dummy variable is constant, implying that all data on REITs is from the same year (2010).

<<here Figure 6: Regression coefficient estimates for REIT subsample>> Finally, Figure 7 shows regression coefficient estimates for the total sample. Although hypothesis 3 states that for the Hong Kong, Malaysia and Singapore listed real estate sector as a whole board size is negatively related to firm value, regression analysis results do not yield support for this. Instead, I find a significant positive relationship between BOARD_LOG and TOBINS_Q. So, hypothesis 3 is rejected. As expected, we find MARKET_CAP and DEBT_EQUITY to be positively related to firm value (both significant). DATE is also of significant impact.

<<Here Figure 7: Regression coefficient estimates for total sample>>

So, regression analysis results of the total sample and stock subsamples do not support my hypotheses but rather indicate the existence of a relation in the opposite direction. Results of REIT subsamples however yield a relationship in line with my hypotheses, but these results appear to be insignificant. See Figure 8 for an overview of findings on the relationship between BOARD_LOG and TOBINS_Q broken down by subsample.

<<Here Figure 8: Findings on relationship BOARD_LOG and TOBINS_Q>> To conclude the result section, Figure 9 shows the relation between board size and Tobin’s Q graphically, with board size on the x-axis and Tobin’s Q on the y-axis. The data is consisted of the total sample.

<<Here Figure 9: Board size (x-axis) and Tobin’s Q (y-axis)>> 7. DISCUSSION As mentioned in the result section, we find evidence of a significant positive relationship between board size and firm value, although we expected a negative relationship. Moreover, results of stock subsamples are significantly different from that of REIT subsamples. While stock subsamples support evidence for a significant positive relation, REIT subsamples show a negative relationship, though not significant. Results of control variables’ correlation are more or less as expected. In this section, we discuss why findings are inconsistent with those of other scholars, why results from the stock and REIT subsample differ significantly. Next, we emphasize limitations and directions for future research. 7.1 Inconsistency Of Results With Prior Research Firstly, a possible explanation for at least some of the inconsistencies is that more stocks than REITs are included in my sample since more stocks are listed in the countries under examination. This could distort findings since it implies that in the total sample, more weight is allocated to stocks. Other scholars however do examine stocks only, causing my sample with an overweighed stock subsample to be comparable. Secondly, sample characteristics could help explain inconsistency with prior research. My sample differs from that of other scholars in terms of geography, industry, average firm size


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etcetera. While most relevant scholars focus on U.S. corporations, I focus on South East Asia. Only Shakir (2008), Mak and Li (2001) and Mak and Kusnadi (2004) do so too, but neither includes Hong Kong. Next, while most relevant scholars examine all sectors except services and financials, I only examine the listed property sector. Only Shakir (2008) does so too, but only for Malaysia. Finally, while most scholars focus on large corporations, I also include smaller corporations since we choose to examine an entire sector, regardless of firm size. Again, only Shakir (2008) does so too. Eisenberg, Sundgren and Wells (1997) and Bennedsen, Kongsted and Nielsen (2007) also examine small firms however, they do not include large firms. Thirdly, the time frame could help explain inconsistency. The latest article on the topic dates back to 2008, with a dataset collected in pre-crisis years. Since my data are from 2009 and 2010, it could be affected by the current credit crisis. Maybe a large board is only generating agency costs in times of sound economic growth, but its wide variety of experience and expertise is preferable in times of economic downturn. A fourth explanation for inconsistency is the difference in board size range. In the sample of Yermack (1996), minimum board size is 4 and maximum is 34 while the mean is 12.25. In my sample, minimum board size is 5 and maximum is 24 while the mean is 8.86. A possible conclusion could be that in South East Asia, or at least in South East Asian real estate, average board size is smaller and no boards of excess size exist. This could minimize negative effects of large boards, like inefficiency and free-rider problems, which in turn could lead to more focus on positive features of larger boards, including more experience and expertise. Lastly, control variables could help explain inconsistency. Perhaps crucial control variables have been excluded. Results show that the dummy variable DATE is of significant impact. However, the variable is not equally distributed across stocks and REITs. All data on REITs is stemming from 2010, while only 50% of stock data is. This causes DATE to be in part a dummy for REIT or stock. 7.2 Differences Between Subsamples As described above, results of the stock and REIT subsample differ significantly. A few explanations are possible. First of all, REITs are not corporations, but trusts. Their legal structure is completely different from ordinary firms. Instead of shareholders, an investor in a REIT is called unitholder. No annual general meetings are obligatory and unitholders cannot vote for board member appointments. This hampers control by investors on the board of directors, resulting in increased managerial discretion. REIT subsample results, showing a negative but insignificant relation while the stock subsample showed a positive significant relation, could be attributable to this. Secondly, sample size of the REIT subsample is small (35 compared to 120 for the stock subsample). This contributes, besides other factors, to low significance of results. However, since the South East Asian REIT market is pretty young, no more REITs are listed yet. 7.3 Limitations And Future Research Limitations include, among others, endogeneity of variables, limited sample size and the time frame of my dataset. Most important is the endogeneity of variables, since almost all variables of interest are endogenous. For example, as Sautner (2010, p. 6) mentions, firm value is both a result of the actions of the previous board and a factor that could influence the subsequent board. Large board size then could cause low firm value or could be the result of low firm value, being enlarged in order to improve performance and firm value. Endogeneity causes results to be hard to interpret.


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Another limitation is limited sample size. Although my sample includes the entire listed real estate sector of Hong Kong, Malaysia and Singapore, total sample still includes only 155 corporations, which is low compared to the sample size of 452 of Yermack (1996). The Hong Kong REIT subsample even includes only 6 REITs; a serious threat to reliability requiring me to be very careful drawing conclusions. The last thing we want to discuss is the time frame of my dataset. We make a snapshot by using only the most recently available data. Other scholars, including Yermack (1996) and Shakir (2008), collect data for several years. Eisenberg, Sundgren and Wells (1997), Mak and Li (2001), Mak and Kusnadi (2004) and Bennedsen, Kongsted and Nielsen (2007) however collect data for one year as well, so my approach is not unusual. Future research could help better explain the impact of board size on firm value in the South East Asian real estate sector. It should include more control variables and increase sample size, the latter preferably by collecting data for several years. Serious attention should be directed at endogeneity, since it is a major issue when analyzing data. 8. CONCLUSION This thesis examines the impact of board size on firm value for a sample of 155 listed ordinary property firms and REITs in Hong Kong, Malaysia and Singapore. In line with other scholars, we hypothesize a negative relation. Results however do not support this. Instead, we find a significant positive relation between board size and firm value for the overall sample, which is mainly due to the result of the listed ordinary property firm subsample. Results of the REIT subsample are not significant, at least in part because of limited sample size. Findings show that, with regard to Hong Kong, Malaysian and Singapore listed real estate, reducing the size of boards of directors does not contribute to higher firm value. Because findings contradict those of prior research, a more extensive examination of the relationship between board size and firm value is needed. It should include more control variables, a focus on endogeneity of variables, and it should increase sample size. The impact of the macro-economic situation and board size ranges should also be included. In the meantime, the countries mentioned above should not include requirements on board size when revising corporate governance codes (as for listed real estate). An overhasty implemented new policy could turn out to be counterproductive.

Amsterdam-Groningen, December 2011 REFERENCES Bennedsen, M., H.C. Kongsted and K.M. Nielsen (2008). The causal effect of board size in

the performance of small and medium-sized firms. Journal of Banking & Finance, 32, 1098-1109.

Berle, A. and G. Means (1932). The modern corporation and private property. New York: Macmillan.

CFA Institute (2011). Asia-Pacific REITs: Building trust through better REIT governance. Retrieved from www.cfapubs.org/doi/pdf/10.2469/ccb.v2011.n4.1

Cheng, S. (2008). Board size and the variability of corporate performance. Journal of Financial Economics, 87, 157-176.

Eisenberg, T., S. Sundgren and M.T. Wells (1998). Larger board size and decreasing firm value in small firms. Journal of Financial Economics, 48, 35-54.

Gertner, R. and S.N. Kaplan (1996). The value-maximizing board (working paper). Chicago: University of Chicago.

Hackmann, J. R. (Ed.) (1990). Groups that work. San Francisco: Jossey-Bass. Hermalin, B.E. and M.S. Weisbach (2003). Boards of directors as an endogenously

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7-26. Jensen, M.C. (1993). The modern industrial revolution, exit, and the failure of internal

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Business Lawyer, 48, 59-77. Loyens and Loeff (2007). REITs in Singapore, Malaysia and Hong Kong compared.

Proceedings of the presentation by P.L. de Ridder on the Greenwood & Freehills Real Estate Investment Trust Conference, 1-25.

Mak, Y.T. and Y. Li (2001). Determinants of corporate ownership and board structure: evidence from Singapore. Journal of Corporate Finance, 7, 235-256.

Mak, Y.T. and Y. Kusnadi (2005). Size really matters: further evidence on the negative relationship between board size and firm value. Pacific-Basin Finance Journal, 13, 301-318.

Moody’s Investor Service and ICRA Limited (2007). Indian real estate and the prospects for REITs (report number 103316). Retrieved from www.inrnews.com/indianrealestate/reports/reits.pdf

Ning, Y., W.N. Davidson and J. Wang (2010). Does optimal corporate board size exist? An empirical analysis. Journal of Applied Finance, 20, 57-69.

Sautner, Z. (2010). Corporate governance: a framework and overview. Proceedings of the course Internal and External Governance, 1-48. Amsterdam: University of Amsterdam.

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Tirole, J. (2006). The theory of corporate finance. Princeton: Princeton University Press.Yermack, D. (1996). Higher market valuation of companies with a small board of directors. Journal of Financial Economics, 40, 185-211.

APPENDIX A: Overview of final sample. Hong Kong Stocks Name Bloomberg Ticker Agile Property 3383:HK BBMG 2009:HK CC Land Holdings 1224:HK Cheung Kong 1:HK China Overseas 688:HK Chine Res Land 1109:HK China SCE Properties 1966:HK Country Garden Holdings 2007:HK Evergrande Real Estate Group 3333:HK Fantasia Holdings Group 1777:HK Franshion Properties 817:HK Glorious Properties Holdings 845:HK Great Eagle Holdings 41:HK Greentown China 3900:HK Hang Lung Properties 101:HK HKC Holdings 190:HK HKR International 480:HK Hopson Development Holdings 754:HK Hysan Development Co. 14:HK K. Wah International Holdings 173:HK Kaisa Group 1638:HK Kerry Properties 683:HK Kowloon Developments 34:HK KWG Property 1813:HK


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Longfor Properties 960:HK Midland Holdings 1200:HK Mingfa Group 846:HK Minmetals Land 230:HK New World China 917:HK Poly HK Investments 119:HK Polytec Asset Holdings 208:HK Powerlong Real Estate Holdings 1238:HK R&F Properties 2777:HK Renhe Commercial 1387:HK Shenzhen Invest 604:HK Shimao Property 813:HK SHK Properties 16:HK Shui On Land 272:HK Sino Land 83:HK Sinolink Holdings 1168:HK Sino-Ocean Land 3377:HK SOHO China Holdings 410:HK Sunac China Holdings 1918:HK Wheelock and Co. 20:HK Yexiu Property 123:HK Yuzhou Properties 1628:HK Hong Kong REITs Name Bloomberg Ticker Champion REIT 2778:HK Fortune REIT 778:HK GZI REIT 405:HK Prosperity REIT 808:HK Regal REIT 1881:HK The Link REIT 823:HK Malaysian Stocks Name Bloomberg Ticker Asia Pacific Land APL:MK Asian Pacific Holdings APH:MK Bandar Raya Developments BRD:MK Bertam Alliance BERT:MK Bolton BOL:MK Eastern & Oriental EAST:MK Equine Capital EQC:MK Farlim Group FG:MK Gromutual GMUT:MK Guocoland Malaysia GUOL:MK IGB Corporation IGB:MK IJM Land IJMLD:MK Ivory Properties Group IVORY:MK Karambunai Corporation KRBN:MK Keladi Maju KLMA:MK KLCC Property Holdings KLCC:MK Kumpulan Hartanah Selangor KHSB:MK Land & General LGH:MK LBS Bina Group LBS:MK Magna Prima MAGNA:MK Mah Sing Group MSGB:MK Malton MALT:MK Meda Incorporated MEDA:MK


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MK Land Holdings MKL:MK Naim Holdings NHB:MK OSK Property Holdings OSKP:MK Perduren M PRDU:MK Petaling Tin PEG:MK PJ Development Holdings PJD:MK SBC Corporation SBC:MK SP Setia SPSB:MK TA Global TAGB:MK Talam Corporation TA:MK Tanco Holdings TANC:MK Tebrau Teguh TEB:MK UEM Land Holdings ULHB:MK YNH Property YNHB:MK YTL Land & Development YTLL:MK Malaysian REITs Name Bloomberg Ticker Al-Aqar APJ REIT AQAR:MK Al-Hadharah REIT BIRT:MK AmanahRaya REIT AARET:MK AmFirst REIT ARET:MK Atrium REIT ATRM:MK Axis REIT AXRB:MK CapitaMalls Malaysia Trust REIT CMMT:MK Hektar REIT HEKT:MK Quill Capita REIT QUIL:MK Tower REIT TRET:MK UOA REIT UOAR:MK Singapore Stocks Name Bloomberg Ticker Allgreen Properties AG:SP Bonvests Holdings BVEST:SP Brothers Holdings BRO:SP Bukit Sembawang Estates BS:SP Capitaland CAPL:SP Centraland CTL:SP China New Town Development CNTD:SP City Developments CIT:SP Debao Property Development DEBAO:SP Fragrance Group FRAG:SP Global Logistics Properties GLP:SP Goodland Group GOOD:SP Guocoland GUOL:SP Heeton Holdings HTON:SP Hiap Hoe HIAP:SP Ho Bee Investment HOBEE:SP Hong Fok Corporation HFC:SP Hongkong Land Holdings HKL:SP Indiabulls Properties Investment IPIT:SP IPC Corporation IPC:SP Keppel Land KPLD:SP LC Development LCD:SP Orchard Parade Holdings OPH:SP Roxy-Pacific Holdings ROXY:SP SC Global Developments SCGD:SP


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Sim Lian Group SLG:SP Sinarmas Land AFP:SP Sing Holdings SING:SP Singapore Land SL:SP Sunshine Holdings SUNS:SP UOL Group UOL:SP United Overseas Australia UOA:SP Wheelock WP:SP Wing Tai Holdings WINGT:SP Ying Li YINGLI:SP Yoma YOMA:SP Singapore REITs Name Bloomberg Ticker AIMS-AMP Industrial REIT AAREIT:SP Ascendas REIT AREIT:SP Ascott REIT ART:SP Cambridge Industrial Trust CREIT:SP CapitaCommercial Trust CCT:SP CapitaMall Trust CT:SP CapitaRetail China Trust CRCT:SP CDL Hospitality Trusts CDREIT:SP First REIT FIRT:SP Fortune REIT FRT:SP Frasers Centerpoint Trust FCT:SP Frasers Commercial Trust FCOT:SP K-REIT Asia KREIT:SP Lippo-Mapletree Indonesia Retail LMRT:SP Mapletree Logistics Trust MLT:SP Parkway Life REIT PREIT:SP Sabana REIT SSREIT:SP Starhill Global REIT SGREIT:SP Suntec REIT SUN:SP


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APPENDIX B: Descriptive statistics for subsamples.

N Min Max Mean Median Std. dev.

HK STOCKS 46

TOBINS_Q 46 .31 3.21 1.31 1.16 .76

BOARD_SIZE 46 7 24 10.93 10 3.26

MARKET_CAP 46 686876 43470140 5581211 2690247 8442906

DEBT_EQUITY 46 .01 3.34 .73 .68 .56

HK REITS 6

TOBINS_Q 6 .65 .99 .79 .73 .16

BOARD_SIZE 6 6 12 8.50 8.50 2.35

MARKET_CAP 6 372156 8560560 2569505 1095745 3144743

DEBT_EQUITY 6 .19 .54 .40 .46 .14

MK STOCKS 38

TOBINS_Q 38 .16 2.83 .73 .44 .57

BOARD_SIZE 38 5 13 7.74 7 2.13

MARKET_CAP 38 14244 3599922 358494 89630 .33

DEBT_EQUITY 38 .00 1.64 .40 .33 .33

MK REITS 11

TOBINS_Q 11 .75 1.18 .98 1.01 .12

BOARD_SIZE 11 5 10 7.55 7 1.75

MARKET_CAP 11 52298 612468 243641 201580 149520

DEBT_EQUITY 11 .00 .85 .50 .52 .25

SP STOCKS 36

TOBINS_Q 36 .07 2.81 .86 .74 .54

BOARD_SIZE 36 5 15 8.39 8 2.53

MARKET_CAP 36 24778 17841571 2455009 924670 3839873

DEBT_EQUITY 36 .02 3.45 .82 .52 .80

SP REITS 19

TOBINS_Q 19 .59 1.37 .96 .95 .22

BOARD_SIZE 19 6 11 7.89 8 1.63

MARKET_CAP 19 438648 6686400 2058148 1214389 1932480 DEBT_EQUITY 19 .00 .78 .46 .48 .19

APPENDIX C: Correlations stock subsample and REIT subsample.

ALL STOCKS TOBINS_Q DATE BOARD_SIZE MARKET_CAP DEBT_EQUITY

TOBINS_Q 1 .334** (.000)

.348** (.000)

.268** (.003)

.301** (.001)

DATE .334** (.000)

1 .013 (.884)

-.075 (.414)

.339** (.000)

BOARD_SIZE .348** (.000)

.013 (.884)

1 .623** (.000)

-.071 (.443)

MARKET_CAP .268** (.003)

-.075 (.414)

.623** (.000)

1 -.069 (.452)

DEBT_EQUITY .301** (.001)

.339** (.000)

-.071 (.443)

-.069 (.452)

1

** correlation is significant at the .01 level (2-tailed) * correlation is significant at the .05 level (2-tailed)


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ALL REITS TOBINS_Q DATE BOARD_SIZE MARKET_CAP DEBT_EQUITY

TOBINS_Q 1 x .030 (.866)

.090 (.608)

.107 (.541)

DATE x

x x x X

BOARD_SIZE .030 (.866)

x 1 .602** (.000)

.128 (.464)

MARKET_CAP .090 (.608)

x .602** (.000)

1 -.132 (.450)

DEBT_EQUITY .107 (.541)

x .128 (.464)

-.132 (.450)

1

** correlation is significant at the .01 level (2-tailed) x correlation cannot be computed since DATE is constant

APPENDIX D: Regression coefficient estimates for other subsamples.

Hong Kong Stocks

Dependent variable is TOBINS_Q Variable OLS estimates

DATE (dummy variable, equals 0 for December 31, 2009; and 1 for December 31, 2010)

.456* (.011)

BOARD_LOG (natural logarithm of board size)

.357* (.050)

MARKET_CAP (market capitalization in thousands of Singapore dollars)

.058 (.735)

DEBT_EQUITY (ratio of total debt to total equity)

.091 (.588)

Sample size 46 F-statistic (p-value) 4.170 (.006) R-squared .289

* significant at the .05 level (2-tailed)

Hong Kong REITs



-.861 (.401)


.837 (.345)


-.500 (.564)

Sample size 6 F-statistic (p-value) .798 (.598) R-squared .545

DATE not included since variable is constant


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Malaysian Stocks



-.047 (.692)


.100 (.386)


.764** (.000)


.026 (.817)


** significant at the .01 level (2-tailed)

Malaysian REITs



-.218 (.569)


.543 (.179)


.253 (.457)


DATE not included since variable is constant Singapore Stocks



.046 (.777)


.119 (.485)


.162 (.351)


.480** (.006)

Sample size 36 F-statistic (p-value) 2.589 (.056)


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R-squared .250

** significant at the .01 level (2-tailed) Singapore REITs



-.442 (.238)


.421 (.210)


.289 (.325)



Article

Year

Tobin’s Q

/ ROA

Significant

Data

period

Country

Sector

Sample

size

Yermack 1996 Tobin’s Q Yes 1984-1991

U.S. All 452

Gertner and Kaplan

1996 N.A. Yes 1987-1993

U.S. All 59

Eisenberg, Sundgren and Wells

1998 ROA Yes 1992-1994

Finland All 879

Mak and Li 2001 Tobin’s Q No 1991-1995

Singapore All 147

Mak and Kusnadi

2005 Tobin’s Q Yes 1999-2000

Singapore, Malaysia

All 460

Shakir 2008 Tobin’s Q Yes 1999-2005

Malaysia Property 81

Cheng 2008 Tobin’s Q Yes 1996-2004

U.S. All 1252

Bennedsen, Kongsted and Nielsen

2008 ROA Yes 1999 Denmark All 6850

Ning, Davidson and Wang

2010 Tobin’s Q Yes 1988-1999

U.S. All 473


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Figure 1. Literature overview

Figure 2. Typical REIT structure

N Min Max Mean Median Std. dev.

TOTAL 155

TOBINS_Q 155 .07 3.21 .98 .91 .61

BOARD_SIZE 155 5 24 8.86 8 2.87

MARKET_CAP 155 14244 43470140 2676695 970055 5418301

DEBT_EQUITY 155 .00 3.45 .61 .49 .55

STOCKS 120

TOBINS_Q 120 .07 3.21 .99 .78 .69

BOARD_SIZE 120 5 24 9.16 9 3.06

MARKET_CAP 120 14244 43470140 2989490 1010175 6027025

DEBT_EQUITY 120 .00 3.45 .65 .49 .61

REITS 35

TOBINS_Q 35 .59 1.37 .94 .98 .19

BOARD_SIZE 35 5 12 7.83 8 1.76

MARKET_CAP 35 52298 8560560 1604253 616980 2075459

DEBT_EQUITY 35 .00 .85 .47 .48 .20

Figure 3. Descriptive statistics of main samples.

TOBINS_Q DATE BOARD_SIZE MARKET_CAP DEBT_EQUITY

TOBINS_Q 1 .259** (.001)

.331** (.000)

.265** (.001)

.298** (.000)

DATE .259** (.001)

1 -.095 (.239)

-.120 (.137)

.202* (.012)

BOARD_SIZE .331** (.000)

-.095 (.239)

1 .623** (.000)

-.031 (.700)

MARKET_CAP .265** (.001)

-.120 (.137)

.623** (.000)

1 -.055 (.495)

DEBT_EQUITY .298** (.000)

.202* (.012)

-.031 (.700)

-.055 (.495)

1

** correlation is significant at the .01 level (2-tailed) * correlation is significant at the .05 level (2-tailed)

Figure 4. Correlations of total sample.


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DATE (equals 0 for December 31, 2009 and 1 for December 31, 2010)

.247** (.004)


.251** (.009)


.169 (.073)


.242** (.005)

Sample size 120

F-statistic (p-value) 11.604 (.000) R-squared .288

** significant at the .01 level (2-tailed)

Figure 5. Regression coefficient estimates for stock subsample.



-.128

(.570)


.182 (.419)


.152 (.421)



Figure 6. Regression coefficient estimates for REIT subsample.



.239** (.001)


.237** (.005)


.182* (.031)


.262** (.000)


** significant at the .01 level (2-tailed) * significant at the .05 level (2-tailed)

Figure 7. Regression coefficient estimates for total sample.


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Sample

Direction of relationship (expected)

Direction of relationship

(regression results)

Significant

ALL STOCKS Negative Positive Yes ALL REITS Negative Negative No TOTAL Negative Positive Yes HK STOCKS Negative Positive Yes HK REITS Negative Negative No MK STOCKS Negative Positive No MK REITS Negative Negative No SP STOCKS Negative Positive No SP REITS Negative Negative No

Figure 8. Findings on relationship BOARD_LOG and TOBINS_Q.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

5 6 7 8 9 10 11 12 13 14 15

Figure 9. Board size (x-axis) and Tobin’s Q (y-axis).

the impact of board size on firm value: evidence from the asian

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