i

OWNERSHIP, CORPORATE

GOVERNANCE AND TIMELINESS OF PRICE

DISCOVERY: AUSTRALIAN EVIDENCE

Wenxuan Liu Bachelor of Economics, Shandong University of Finance

Submitted in fulfilment of the requirements for the degree of

Master of Business (Research)

The School of Economics and Finance Faculty of Business

Queensland University of Technology Brisbane, Australia

January 2012

i

Keywords and Abbreviations

Timeliness of price discovery

Large shareholding

Ownership structure

Corporate governance

BB06: Beekes and Brown (2006)

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Abstract

This study investigates whether and how a firm’s ownership and corporate

governance affect its timeliness of price discovery, which is referred to as the speed

of incorporation of value-relevant information into the stock price. Using a panel

data of 1,138 Australian firm-year observations from 2001 to 2008, we predict and

find a non-linear relationship between ownership concentration and the timeliness of

price discovery. We test the identity of the largest shareholder and find that only

firms with family as the largest shareholder exhibit faster price discovery. There is

no evidence that suggests that the presence of a second largest shareholder affects

the timeliness of price discovery materially. Although we find a positive association

between corporate governance quality and the timeliness of price discovery, as

expected, there is no interaction effect between the largest shareholding and

corporate governance in relation to the timeliness of price discovery. Further tests

show no evidence of severe endogeneity problems in our study.

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Table of Contents

Keywords and Abbreviations .................................................................................... i Abstract ......................................................................................................... ii Table of Contents .................................................................................................. iii List of Tables iv Statement of Original Authorship ........................................................................... v Acknowledgements ................................................................................................ vi Chapter 1: Introduction ...................................................................................... 1 1.1 Introduction ................................................................................................................. 1 1.2 Research aims and summary of results ....................................................................... 3 1.3 Contributions ............................................................................................................... 6 1.4 Thesis outline ............................................................................................................... 7 Chapter 2: Literature Review ............................................................................. 8 2.1 Introduction ................................................................................................................. 8 2.2 The Ball and Brown’s (1968) measure ......................................................................... 8 2.3 Intra-period timeliness (IPT) ......................................................................................10 2.4 The timeliness metric .................................................................................................12 2.5 Chapter summary .......................................................................................................13 Chapter 3: Hypotheses Development .............................................................. 15 3.1 Introduction ...............................................................................................................15 3.2 Large shareholdings and the timeliness of price discovery .......................................15 3.3 Identity of the largest shareholder and the timeliness of price discovery ................20 3.4 Corporate governance and the timeliness of price discovery ...................................23 3.5 Chapter summary .......................................................................................................25 Chapter 4: Data and Research Method ............................................................ 27 4.1 Introduction ...............................................................................................................27 4.2 Data .......................................................................................................................27 4.3 Research method .......................................................................................................29 4.4 Variable measurements .............................................................................................33 4.5 Chapter summary .......................................................................................................36 Chapter 5: Empirical Results ........................................................................... 37 5.1 Introduction ...............................................................................................................37 5.2 Univariate analysis .....................................................................................................37 5.3 Multivariate analysis ..................................................................................................40 5.4 Endogeneity ...............................................................................................................46 5.5 Chapter summary .......................................................................................................54 Chapter 6: Summary and Conclusion .............................................................. 55 References ........................................................................................................ 58 Appendices ........................................................................................................ 67

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List of Tables

Table 4.1 Frequency distribution ............................................................................................. 29

Table 4.2 Descriptive statistics ................................................................................................ 35

Table 5.1 Correlation coefficients between test variables ....................................................... 38

Table 5.2 Univariate test of the difference in the mean and median ....................................... 39

Table 5.3 Random effect panel regressions ............................................................................. 41

Table 5.4 Fixed effect panel regression ................................................................................... 48

Table 5.5 2SLS regression ....................................................................................................... 51

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Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet

requirements for an award at this or any other higher education institution. To the

best of my knowledge and belief, the thesis contains no material previously

published or written by another person except where due reference is made.

Signature: _________________________

Date: _________________________

vi

Acknowledgements

I gratefully acknowledge invaluable guidance and encouragement of my supervisors,

Professor Janice How and Associate Professor Peter Verhoeven. I also appreciate my

family for their love, support and understanding.

I would also like to thank Queensland University of Technology (QUT) for their

financial support during my two-year study.

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Chapter 1: Introduction

1.1 Introduction

The accounting literature refers to timeliness as making financial information

available to decision makers while it can still be used. Undue delays in value-

relevant information not only increase the likelihood that the decision will have to be

made without the benefit of the information but also compromise regulators’ ideal of

equal access to information among market participants (Hakansson, 1977; Chambers

and Penman, 1984; Bamber et al., 1993) as they allow some investors to acquire and

trade on the private information at the expense of other less informed investors.1

Ball and Brown (1968) pioneer the string of research on the capital market’s

response to corporate disclosure of accounting information. They investigate the

association between accounting income numbers and share price, where they

describe the accounting income numbers in term of “relevance” and “timeliness”. An

implication of Ball and Brown (1968) is that a firm’s financial reporting and

disclosure regime have a direct impact on the timeliness of its price discovery, which

is referred to as the extent to which the firm’s stock price reflects information in the

income number prior to its release.

Following Ball and Brown (1968), Beekes and Brown (2006) define the

timeliness of price discovery as the speed at which value-relevant private

information is reflected in a stock’s publicly observable market price. They propose

a firm level measure of timeliness of price discovery and examine its relationship

with corporate governance quality. Using a sample of 250 Australianz firms rated in

1 Late announcements of earnings are also more often associated with lower abnormal returns than early announcements (Givoly, 1982; Chambers and Penman 1984; Kross and Schroeder 1984).

2

the 2002 Horwath Corporate Governance report, they find better-governed firms

make more informative disclosure and are timelier in terms of price discovery.

An implication of the findings in Beekes and Brown (2006) is that agency

problem plays an important role in the timeliness of price discovery. In essence, the

level of information asymmetry depends on the agency problem inherent in the

separation of ownership and control in public companies (Jensen and Meckling,

1976). 2 Insofar as ownership structure can provide an effective mechanism for

solving the agency problem (Shleifer and Vishny, 1986) as well as in determining

the nature of the agency conflict (Bebchuk and Hamdani, 2009), it is conceivable

that the timeliness of price discovery can vary with the ownership structure of the

firm. For example, information asymmetry is exacerbated when insiders withhold

value-relevant information in an attempt to hide potential expropriation of outside

minority shareholders.

In this study, we investigate how the timeliness of price discovery relates to

ownership concentration and structure. In particular, we focus on the large

shareholders due to their ability in mitigating or exacerbating agency problem

(Shleifer and Vishny, 1986; Holderness, 2003; Bebchuk and Hamdani, 2009). We

test how the timeliness of price discovery varies with the percentage shareholding

and identity of the large shareholders, as well as the presence of multiple large

shareholdings. We also replicate Beekes and Brown’s (2006) work on the

relationship between timeliness of price discovery and corporate governance quality

using panel data. More importantly, we extend their study to provide the first

2 Jensen and Meckling (1976) define the agency relationship as a contract under which one party (the principal) engages another party (the agent) to perform some service on her behalf. Agency problems arise from a conflicts of interest between two parties to a contract, and as such, are almost limitless in nature. Jensen and Meckling (1976) argue that this inefficiency is reduced as managerial incentives to take value maximising decisions are increased. As with any other costs, agency problems will be captured by financial markets and reflected in a company’s share price.

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evidence on how large shareholdings and firm level corporate governance quality

interact to affect the speed of price discovery. This is the main motivation behind

this study.

Our research is set in Australia where a continuous disclosure regime requires

publicly listed companies to immediately notify the Australian Securities Exchange

(ASX) of any price-sensitive information as it arises. A comparison of differences in

the timeliness of price discovery “in a setting where material information is required

by law to be disclosed as soon as it becomes known” (Beekes and Brown, 2006, p.1)

is interesting since it can provide an insight of determinates of speed of price

discovery beyond the strong law requirement.

1.2 Research aims and summary of results

The first aim of this thesis is to examine how ownership concentration and

structure relate to the speed of price discovery. We begin by examining large

shareholdings and predict a non-linear relationship between the percentage

shareholding by the large shareholders and the timeliness of price discovery. At low

levels of ownership, we argue that large shareholders can reduce the agency problem

since they have the incentive to collect information and monitor the management

(Shleifer and Vishny, 1986). More specifically, the presence of large shareholders

reduces information asymmetry through their ability to pressure the firm to improve

transparency by disclosing information in a timelier manner. This results in an

increased timeliness of price discovery. The entrenchment effect arises at high levels

of shareholding where the large owners gain controlling rights and may use their

power to consume corporate resources and enjoy private benefits that are not shared

with minority shareholders (Holderness, 2003). The agency conflict between the

controlling owners and outside minority shareholders thus dominates the agency

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problem in highly concentrated firms (Bebchuk and Hamdani, 2009). In an attempt

to hide any potential private benefits of control, we predict that large shareholders

impede the speed of price discovery.

Both the alignment and entrenchment arguments therefore suggest that the

relationship between the largest percentage shareholding and the timeliness of price

discovery is a non-linear one (Morck, Shleifer and Vishny, 1988). Empirically, we

test how the timeliness of price discovery varies with the percentage shareholding by

the largest shareholder and ownership concentration; the latter is measured by the

sum of all shareholdings in excess of 5 percent. The results in general support our

prediction.

The role of large shareholders on the mitigation of agency problem depends in

part on who they are. Large shareholders differ in their motivation, abilities, and

knowledge in preventing and reducing concealment of value-relevant information.

All these have an impact on corporate disclosure policy and thus the timeliness of

price discovery. Therefore, we also examine whether the identity of the largest

controlling owner matters to the timeless of price discovery.

We identify two controlling owner groups. The first is institutional

shareholders – we predict a more speedy price discovery if the largest owner belongs

to this group. It has been well documented that institutional investors are effective

monitors (Gillan and Starks, 2003; Hawley and Williams, 1997) and are associated

with greater corporate disclosure (Bushee and Noe, 2000; El-Gazzar, 1998; Bange

and DeBond, 1998). Nevertheless, our results show the speed of price discovery for

firms whose controlling shareholders are financial institutions is not significantly

different from other firms. Although contrary to our prediction, this finding is

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consistent with the literature which is yet to converge on the internal agency problem

and the relative role of institutional owners.

The second group is families. The effect of family ownership on the timeliness

of price discovery is an empirical one. In an attempt to ensure survivability, we argue

that family-controlled firms are more likely to do the “right thing”, which includes

increasing transparency because all decisions and their consequences affect not only

themselves, but also future generations. This is further substantiated by the fact that

family owners have more to lose than the “average” owner in the event of financial

distress. For example, family owners in general, and family managers in particular,

have large and undiversified investments of wealth and human capital in the

company and are affected adversely by the company’s idiosyncratic risk (Firth,

1995). DeAngelo and DeAngelo (1985) also show that family members earn higher

wages than would otherwise be paid absent the personal relationship, thus increasing

the cost of losing their employment. On the other hand, the expropriation hypothesis

predicts that the high level of family ownership concentration increases the

propensity for expropriation of minority shareholders by the family-owner. Our

results support the former view as we find that family ownership can effectively

mitigate the agency problem; family-controlled firms are associated with timelier

price discovery.

The monitoring role of multiple large shareholdings through control

contestability has recently been explored in the literature (Demsetz and Lehn, 1985;

Anderson and Reeb, 2003; Ali et al., 2007). To the extent that the presence of a

second large shareholder can monitor the controlling shareholder, we therefore

predict that the second large shareholder is positively related to the speed of price

discovery. However, we find no such association, suggesting that the second largest

6

shareholder may in fact be collaborating with the controlling shareholder to share

private benefits.

The second aim of this thesis is to examine how large shareholding interacts

with corporate governance in relation to the timeliness of price discovery. In the

spirit of Morck, Sheifer and Vishny (1988), the positive incentive effect at low levels

of ownership concentration suggests that the ultimate owner monitors managers and

oversees the firm’s internal corporate governance. In this case, large shareholding

complements internal corporate governance mechanisms to improve transparency

and therefore the speed of price discovery. However, at high levels of ownership

concentration, the controlling shareholder moderates the effectiveness of corporate

governance and this weakens the association between corporate governance quality

and timeliness of price discovery. Therefore, we predict that the largest shareholder

moderates the relationship between corporate governance quality and timeliness of

price discovery. However, we find no evidence of an interaction effect between the

large shareholding and corporate governance quality on the speed of price discovery.

This is likely due to the high correlation between the ownership and corporate

governance variables, with our results showing ownership subsuming the

explanatory power of governance.

1.3 Contributions

This thesis contributes to the literature on the timeliness of price discovery in

the following important ways. Past studies have identified certain factors which can

influence the speed of price discovery such as firm size, the industry sector that the

firm operates in, the quality of the firm’s corporate governance, the nature of the

corporate news announced, and so forth. This thesis contributes to this line of

research by providing the first evidence that ownership concentration and structure

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also matter to the timeliness of price discovery. We also investigate this relationship

through the prism of agency conflict, providing evidence on the effect of agency

conflict on corporate disclosure and speed of price discovery.

Our study provides some insights into the interaction between ownership and

corporate governance in the context of the price discovery process. Bebchuk and

Hamdani (2009) argue that the degree of ownership concentration affects the nature

of agency problem. The conflict of interest between outside shareholders and

managers is the main corporate governance concern in firms without controlling

shareholders. In firms with controlling shareholders, however, the fundamental

governance concern is the controlling shareholder’s opportunism at the expense of

minority shareholders. Our study provides an empirical test of the argument of

Bebchuk and Hamdani (2009) that the effectiveness of many governance

arrangements critically hinges on whether the company has a controlling

shareholder.

1.4 Thesis outline

The remainder of the thesis is organised as follows. Chapter 2 reviews the

related literature and Chapter 3 develops the testable hypotheses. Chapter 4 describes

our data and research method. Chapter 5 presents the main empirical results. Chapter

6 summarises and concludes the thesis.

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Chapter 2: Literature Review

2.1 Introduction

This chapter provides a literature review on the timeliness of price discovery,

referred to as the speed at which value-relevant information becomes embedded in

the share price. Since most of these measures have their origin in the seminal work

of Ball and Brown (1968), we discuss Ball and Brown’s (1968) study and their

replications in Section 2.2. Studies in this section use profile-based timeliness

measure and focus on earnings numbers. Sections 2.3 and 2.4 discuss the intra-

period timeliness measure (IPT) and the Beekes and Brown’s (2006) measure

respectively, both of which are firm-level timeliness measures and capture the

timeliness of price discovery of all value-relevant information regardless of the

nature of the information that is priced. Section 2.5 summarises and concludes.

2.2 The Ball and Brown’s (1968) measure

The debate on the extent to which accounting earnings numbers are related to

stock return has its origin in Ball and Brown (1968). In their seminal paper, Ball and

Brown (1968) discuss the association between accounting income numbers and stock

returns in term of both the “relevance” and “timeliness” of earning reports. In their

study, earnings timeliness refers to the speed of incorporation of accounting

earnings-related information into stock price. Their measure of timeliness is based on

abnormal performance indexes (APIs) for portfolios of stocks.

Using a sample of 261 U.S. firms over the period from 1957 to1965, Ball and

Brown (1968) find that, even though annual earnings numbers are highly value-

relevant, the annual income report is not a timely medium since most of its content

(about 85 to 90 percent) is captured by stock prices before the earnings

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announcement month. They suggest (p.17) “not only that the market begins to

anticipate forecast errors early in the 12 months preceding the report, but also that it

continues to do so with increasing success throughout the year.”

Nichols and Wahlen (2004) replicate Ball and Brown’s (1968) study using

more current U.S. data. Their sample consists of 31,923 firm reports for the period

1988 to 2001. Compared with the finding of Ball and Brown (1986), Nichols and

Wahlen (2004) show an even stronger relationship between the annual stock return

and the sign of the annual earnings change. They extend the earnings measures and

find the magnitude of the earnings changes and annual changes in cash flows from

operations are also related to annual stock returns.

Brown (1970) replicates the Ball and Brown’s (1968) study using a sample of

118 Australian companies reporting from 1959 and 1968. He finds earnings are

anticipated in the U.S. to a greater extent than in Australia. Around 75% to 80% of

the price effects of the annual income number are captured prior to the month of the

preliminary financial statement (PFS) release in Australia, compared to 85% to 90%

in the U.S. This result can be explained by the higher frequency of report releases in

the U.S.. Financial reports are released typically once every 6 months in Australia,

compared to once in every 3 months in the U.S.. Brown (1970) also reports good

news in Australia ‘gets out’ earlier than bad news.

Based on the work of Ball and Brown, Alford et al. (1993) conduct an

international study. They use the U.S. as the benchmark in their comparison of the

information content and timeliness of accounting information in 17 countries

between 1983 and 1990. They test whether differences in capital markets, accounting

standards, disclosure practices, and corporate governance, lead to significant

differences in the usefulness of accounting earnings. In this international study,

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Alford et al. (1993) form two hedge portfolios for each country to measure

timeliness. The earnings-based hedge portfolio is an equally-weighted portfolio that

is long in firms with the highest 40% income change and short in firms with the

lowest 40% income change in that country. The return-based hedge portfolio is an

equally-weighted portfolio that is long in firms with the highest 40% market-

adjusted returns and short in firms with the lowest 40% market-adjusted return in

that country. For both portfolios, a 15-month time horizon ending 3 months after a

firm’s fiscal year end is used to calculate returns. The ratio of the earnings-based

portfolio cumulative return to the return-based hedge portfolio 15-month return

“measures the proportion of all information impounded in stock prices that is

captured by accounting earnings” (Alford et al. (1993), p. 200). Their results show

differences in accounting standards and disclosure practices impact on the timeliness

of accounting earnings. Annual accounting earnings from Australia, France, the

Netherlands, and the U.K. are timelier than accounting earnings from the U.S. In

contrast, annual accounting earnings from Denmark, Germany, Italy, Singapore, and

Sweden contain less timely information. The results for Belgium, Canada, Hong

Kong, Ireland, Japan, Norway, South Africa, and Switzerland are inconclusive.

The measures of timeliness in the above studies are portfolios-based. Firm

level measures of timeliness are discussed below.

2.3 Intra-period timeliness (IPT)

Bulter et al. (2007) use intra-period timeliness (IPT) to measure how quickly

earnings information is reflected in price during the current reporting period.

Following Ball and Brown (1968) and Alford et al. (1993), they use a portfolio-

based measure and design a firm’s individual IPT to capture the speed at which all

information related to the firm is impounded into price. IPT is calculated as the sum

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of the firm’s buy-and-hold return from month 1 through month m divided by the

buy-and-hold return from month 1 through month 12, for each of month m from 1 to

11, plus 0.5:

𝐼𝑃𝑇 =12� (𝐵𝐻𝑚−1 + 𝐵𝐻𝑚 )12

𝑚=1

/𝐵𝐻12 = � (𝐵𝐻𝑚/𝐵𝐻12 )11

𝑚=1

+ 0.5

where BHm-1, BHm, and BH12 are respectively the buy-hold return from month 1 to

month m-1, month m, and month 12. Timelier firms have a larger IPT. Even though

earnings information is not used directly in their formula, the individual IPT is

indirectly affected by earnings information through the change in the monthly and

cumulative monthly buy-and-hold returns.

Using this measure, they examine whether the frequency of financial reporting

affects the speed at which accounting information is reflected in security prices. For

a sample of 28,824 reporting-frequency observations from 1950 to 1973 in the U.S.,

they find a positive association between voluntarily increased reporting frequency

and timeliness of earnings, but not for firms that were mandated by the SEC to

increase their reporting frequency.

In a later study, also using the intra-period timeliness (IPT) measure, Bushman

et al. (2010) focus on how private information and information dissemination by

loan syndicated participants affect the timeliness of price discovery. Based on 7,350

traded loans over the period 1998-2006, they find that stock returns of firms

identified with earlier private information dissemination to lenders exhibit faster

price discovery in the stock market, but only when institutional investors are

involved in the firm’s syndicated loans. Additionally, the positive relationship

between institutional lending and the speed of price discovery is more pronounced in

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firms with relatively weak public disclosure by the borrower (i.e., no management

forecasts and below-the-median number of firm-initiated press releases).

2.4 The timeliness metric

Also inspired by Ball and Brown (1968), Beekes and Brown (2006), hereafter

BB06, construct a new metric of the timeliness of price discovery to capture the

speed at which share price reflects value-relevant information throughout the year

leading up to the release of the firm’s earnings result. It addresses the question of

how accurately does the share price observed throughout the year approximate the

market valuation of the share two weeks after the preliminary final statement has

been released. To further explore this measure of timeliness, Beekes and Brown

(2007) examine the relationship between the timeliness of price discovery and

analogous concepts based on corporate disclosure and analysts’ earnings forecasts.

Their results show a positive correlation between the timeliness of price discovery

and analyst forecasts and corporate disclosure.

Jackson (2010) also reports a positive association between accounting quality

and this concept of timeliness. Jackson (2010) expects that information

imperfections associated with low accounting quality potentially delay stock price

adjustment to information and hinder timely price discovery. Using three proxies of

accounting quality,3 Jackson (2010) finds that price discovery is more timely for

firms with higher quality financial reporting. These findings suggest BB06’s

timeliness metric captures important information and is positively associated with

the volume and quality of corporate disclosure.

3 The three proxies of accounting quality are material accounting misstatements; accrual quality; and earnings smoothness.

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Using the BB06 timeliness metric, some studies focus on the relationship

between the timeliness of price discovery and corporate governance. BB06

themselves examine exactly that for a sample of 250 Australian firms and they find

better governed firms are timelier in their price discovery. The authors view the

faster price discovery in better-governed firms as the consequence of more frequent

disclosure of information and greater analyst following. Beekes et al. (2007)

replicate BB06 using a sample of Canadian firms over period 2000 to 2005, and find

some evidence that firms with good news, larger firms, and firms with good

corporate governance have faster price discovery.

Aman et al. (2011) test the association between corporate governance and the

timeliness of price discovery in Japan. Their sample consists of 1,411 unique firms

or 5,011 firm-year observations for the years 2004 to 2007. Contrary to their

expectation, they find better-governed firms have less timely price discovery. They

find that more traditional forms of corporate governance in Japan such as bank

ownership, close shareholdings, and insider membership of the board of directors are

associated with greater timeliness of price discovery. This may be due to greater

information sharing within business groups (i.e. keiretsu) and reduced need to

consult with parties external to the groups, which can delay the release of

information and thus price discovery.

2.5 Chapter summary

This chapter provides a literature review on the timeliness of price discovery.

We group the studies according to the measure of timeliness employed in the

research. A number of studies focus on the quality corporate governance in

explaining cross-sectional differences in timeliness. Others also find the timeliness

14

of price discovery varies with corporate disclosure, regulation and enforcement, firm

size, and the nature of the news. Insofar as the effectiveness of many governance

arrangements critically hinges on whether the company has a controlling shareholder

(Bebchuk and Hamdani, 2009), we argue that ownership concentration and structure

are also important determinants of the timeliness of price discovery. To our

knowledge, this has not been addressed in the literature. We aim to fill this gap in the

literature.

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Chapter 3: Hypotheses Development

3.1 Introduction

This chapter develops the testable hypotheses on the relationships between

ownership concentration and structure, corporate governance, and the timeliness of

price discovery. The hypothesis on how large shareholdings relate to the timeliness

of price discovery is outlined in Section 3.2. The identity of the largest shareholder

and how it relates to the timeliness of price discovery are the focus of Section 3.3.

Section 3.4 looks at the relationship between corporate governance and the

timeliness of price discovery, and the interaction effect between ownership structure

and corporate governance on the timeliness of price discovery. A chapter summary is

provided in Section 3.5.

3.2 Large shareholdings and the timeliness of price discovery

In firms where the ownership of capital is dispersed among shareholders,

control tends to be concentrated in the hands of professional managers who own

little or none of the equity of the firm they manage. The agency problem that arises

from the separation of ownership and control in this situation stems from the conflict

of interest between outside shareholders and the managers. The manager controls the

firm and has significant discretion to potentially expropriate resources for private

benefit at the expense of shareholders (Berle and Means, 1932; Jensen and Meckling,

1976; Roe, 1994). For example, the manager can distort corporate disclosure and

exploit the information asymmetry to act in a manner that is contrary to the interests

of shareholders. As argued by Ajinkya et al. (2005), managers are likely to act in

16

their self interest and withhold information to a certain degree for various reasons,

including insider trading opportunities and reputational risks of erroneous.

Concentrated ownership can mitigate this agency problem and reduce the

information asymmetry between management and shareholders. Large shareholders

have the economies of scale and incentives to collect information and monitor the

management since the benefits from these activities accrue mostly to them. Also,

they have enough voting right to put pressure on the management to make more

corporate disclosure (Shleifer and Vishny, 1997; Denis and McConnell, 2003). This

suggests that the presence of large shareholders can increase transparency and thus

enhance firm value.

We therefore propose that large shareholdings positively impact on the

timeliness of price discovery. To reduce the agency conflict between shareholders

and managers, large shareholders compel managers to disclose more corporate

information so that a more accurate evaluation of the firm’s performance can be

achieved. Healy et al. (1999) also propose that substantial shareholders can

strengthen corporate governance by actively monitoring the firm and influencing the

disclosure level. Haniffa and Cooke (2002) report a positive relationship between the

proportion of shares held by the 10 largest shareholders and the extent of voluntary

disclosure in Malaysia. Luo et al. (2006) find that the existence of outside block

ownership significantly increases voluntary corporate disclosure in Singapore. El-

Gazzar (1998) also shows a positive association between the percentage of

institutional ownership and the extent of voluntary disclosure.

However, if ownership is concentrated at a level where the owner can obtain

effective control over the firm, the nature of the agency problem shifts away from

the manager-shareholders conflict to a conflict between the controlling owner and

17

minority shareholders (Bebchuk and Hamdani, 2009). In this case, ownership can

entrench controlling shareholders who can use their power to consume corporate

resources or to expropriate corporate benefits that are not shared with minority

outside shareholders. These are private benefits of control (Denis and McConnell,

2003). Therefore, there is an entrenchment effect at high levels of shareholdings.

We propose a number of reasons to expect why the speed of price discovery is

lower at high levels of shareholdings. First, we expect firms with highly concentrated

ownership have poorer disclosure since the opacity allows the controlling owners to

hide potential expropriation of minority outside shareholders (Makhija and Patton,

2004). Further, since controlling shareholders typically have easy and quick access

to the information they need, there is less demand for corporate disclosure in firms

with highly concentrated ownership (Cormier et al., 2005).

Second, controlling shareholders may also influence the quality of accounting

information, which in turn is positively related to the timeliness of price discovery

(Jackson, 2010). Controlling shareholders are typically involved in overseeing the

financial reporting process (Brown et al., 2011) and this allows them to prevent

information flows to the market as well as making the earnings less transparent. Fan

and Wong (2002), for example, find lower earnings informativeness, defined as the

correlation between earnings and returns, in East Asian firms where concentrated

ownership is relatively common. Their results are consistent with controlling

shareholders taking actions that expropriate minority shareholders’ interests and

limiting the quality of information disclosed to the market. Similarly, Liu and Lu

(2007) show earnings management is more prevalent in the presence of agency

conflicts between controlling and minority shareholders.

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Third, firms with controlling shareholders are less susceptible to the forces of

the market for control due to the “lock-in” the shareholders have on control. This in

turn leads to less informative stock prices by discouraging the collection of and

trading on private information. The timeliness of price discovery is thus lower for

these firms. Using idiosyncratic risk as an index of information flow, Ferreira and

Laux (2007) find a tight link between openness to the market for corporate control

and openness of private information to the market in a way that is not captured by

the openness of a firm’s financial reporting. Also, they argue that openness to the

market for corporate control and informed trading by institutions interacts to

influence the extent to which stock price incorporates information in an accurate and

timely fashion.

In sum, at low ownership levels, large shareholders can monitor the manager

and improve information disclosure. This ensures that more firm-specific

information is available and thus improves investors’ prediction. Therefore the price

discovery is timelier for these firms. The reverse holds true at high ownership levels

since the controlling shareholders have less demand for public information

disclosures and are more likely to want to hide potential expropriation of outside

shareholders. Accounting information in highly concentrated ownership firms is also

less informative, thus reducing the timeliness of the price discovery.

Based on the discussion above, we propose that there is a non-linear

relationship between ownership concentration and the timeliness of price discovery:

H1: There is a non-linear relationship between concentrated shareholding and

the timeliness of price discovery.

19

We have two measures of ownership concentration and they are the sum of all

shareholdings in excess of 5 percent and the largest percentage shareholding. Details

on variable measurements are discussed in the next chapter.

We also examine the existence of a second largest shareholder since multiple

large shareholders can provide valuable monitoring through control contestability.

Pagano and Roell (1998) suggest that having multiple large shareholders is effective

in mitigating the expropriation problem. Gomes and Novaes (2005) consider the

bargaining problem and argue that the presence of multiple controlling shareholders

protects minority shareholders of firms with large blockholders because

disagreements among controlling shareholders can prevent them from taking actions

that hurt minority shareholders. All large shareholders perform a monitoring role and

compete for the votes of minority shareholders by committing to reduce their private

benefit. Gutierrez and Tribo (2004) also find that the presence of more than one

controlling shareholder substantially decreases private benefit extraction because of

the bargaining process that occurs among large shareholders who are forced to share

control.

The presence of a second largest shareholder may also moderate the negative

effect that a single largest shareholder has on the quality of accounting information.

For example, Boubaker and Sami (2011) find control contestability of the largest

controlling shareholder mitigates the information asymmetry problem thereby

enhancing earnings informativeness. Also, Attig et al. (2008) document that when

other large shareholders intervene in the preparation of financial information, it is

more costly and difficult for the largest shareholder to conceal or manipulate

earnings.

20

We therefore predict that the presence of a second largest shareholder will

effectively monitor the largest controlling shareholder, thereby reducing the agency

cost and information asymmetry. Since the presence of a second largest shareholder

makes it more difficult for the controlling shareholder to withhold value-relevant

information, we therefore hypothesize that the presence of a second largest

shareholder increases firm transparency and the speed of price discovery.

H2: The presence of a second largest shareholder increases the timeliness of

price discovery.

3.3 Identity of the largest shareholder and the timeliness of price discovery

The commitment of the controlling owners and their willingness to intervene

in corporate activities crucially depend on their identity. That is, whether controlling

shareholders enhance or diminish firm value depends on who they are (Claessens et

al., 1998; Gibson, 2003). Controlling shareholders differ in their motivation, abilities,

and knowledge in preventing and reducing the concealment of value-relevant

information. It thus follows that the identity of the controlling shareholder matters to

the timeliness of price discovery.

We identify two important controlling owner groups in this study and they are

institutional investors and families. The role of institutional shareholders in a firm’s

activities is the subject of continuing debate. Institutional investors have the potential

to influence management’s activities directly through ownership and indirectly by

trading their shares. Wahab et al. (2007) note the participatory role of institutional

investors – internally, they take an active role in the management through the board

of directors and other committees, and externally, they pressure firms by means of

litigation, media pressure, private negotiations, shareholder proposals, and proxy

21

voting. Gillan and Starks (2003) view institutional investors as an increasingly

important external control mechanism affecting corporate governance and argue that

their presence in the firm leads to more informative prices and lower monitoring cost.

Relative to other types of large shareholders, financial institutions have more

important implications for corporate governance because they have fiduciary duties

and are legally obliged to act prudently and loyally in the best interests of their

beneficiaries (Hawley and Williams, 1997). Another potential role for large

institutional investors is to provide a credible mechanism for transmitting

information to the financial markets. According to Chidambaran and John (2000),

large institutional investors can convey private information that they obtain from

management to other shareholders.

Having a controlling institutional investor can positively impact on the volume

and quality of corporate disclosure. First, corporate disclosure is a low-cost

mechanism for monitoring manager performance. Therefore, institutional investors

have incentives and power to put pressure on managers to disclose more relevant

information. Bushee and Noe (2000) find that institutions with a large number of

portfolio stocks prefer high quality disclosures as a way of offsetting monitoring cost.

They suggest that greater institutional ownership is positively associated with

disclosure quality. Similarly, El-Gazzar (1998) argues that large institutional

ownership may induce a higher level of voluntary disclosure prior to earnings

announcements. Irrespective of the direction of the causality, the literature shows a

positive relationship between institutional shareholdings and corporate disclosure.

Second, institutional investors have the ability and incentive to improve

disclosure quality. Chung et al. (2002) find less opportunistic earnings management

in firms with greater institutional ownership because institutional investors can either

22

put pressure on the firm to adopt better accounting policy or unravel the earnings

management ruse so it will not benefit the managers. Bange and DeBond (1998) also

find that there is less earnings management (related to research and development

investment) when institutional investors own a larger stake in the firms. Since

improvements in the quality of accounting information increase the speed of price

discovery (Jackson, 2010), we predict firms controlled by an institutional investor

are timelier in their price discovery.

H3: Firms with institutional investors as the largest shareholder have greater

timeliness of price discovery.

The literature identifies two types of agency problem in family-controlled

firms. The first is the manager-shareholder agency problem that arises from the

separation of ownership and management and the second is the agency problem that

arises between the controlling family and minority shareholders. On the one hand,

controlling families can effectively monitor managers and reduce the agency conflict

between shareholders and managers. They hold undiversified and concentrated

equity and thus have strong incentives to monitor the managers (Demsetz and Lehn,

1985). As they have good knowledge about the firm’s activities (Anderson and Reeb,

2003), their monitoring is likely to be more effective. Consistent with these

arguments, Ali et al. (2007) find family firms have better corporate disclosure and

earnings quality,4 and are more likely to warn the market of bad news through the

release of management earnings forecasts. They also find that family firms have

greater analyst following, a lower dispersion in analyst forecasts, a smaller forecast

error, a less volatile forecast revision, and a smaller bid-ask spread. This suggests

that family-owned firms are expected to have greater timeliness of price discovery.

4 Earnings quality is measured as discretionary accruals, a greater ability of earnings components to predict cash flow, and a larger earnings response coefficient.

23

On the other hand, family firms have more severe agency problems that arise

between controlling and non-controlling shareholders (Gilson and Gordon, 2003).

Controlling families who hold large stock ownership tend to dominate the firm’s

board of directors (Anderson and Reeb, 2003), and the control gives the family the

power to seek private benefits at the expense of other shareholders. Family owners,

for example, may retain information to hide their opportunistic behavior, such as

related-party transactions (Anderson and Reeb, 2003) and managerial entrenchment

(Shleifer and Vishny, 1997). This potential expropriation of outside shareholders is

further facilitated by the fact that most senior positions in the firm are filled by

family members so that the demand for information is relatively low since the

controlling family members already have access to the information (Chau and Gray,

2002). Since family firms have little incentive to disclose information to the public,

under this view, family-owned firms are expected to have a lower speed of price

discovery.

To summarize, the agency conflict between managers and shareholder is less

severe in family firms but the agency problem between the controlling family and

other shareholder is more severe. Thus, the relationship between having a family as

the controlling shareholder and the timeliness of price discovery is an empirical one.

We therefore do not predict a direction for the relationship:

H4: There is a relationship between timeliness of price discovery and having a

family as the largest shareholder.

3.4 Corporate governance and the timeliness of price discovery

Corporate governance is a set of control mechanisms that is specially designed

to monitor and ratify managerial decisions. We expect firms with better corporate

24

governance have less agency problem and are thus less likely to withhold

information. Indeed, Arcay and Vazquez (2005) document that better governed firms,

as proxied by the proportion of independent directors on the board, are associated

with greater voluntary disclosure. Using various measures of governance, the

evidence in Cheng and Courtenay (2006), Lim et al. (2007), Beekes and Brown

(2006), Beekes et al. (2006), and Ferreira and Laux (2007) find governance and

disclosure informativeness are positively related. Therefore, we hypothesize the

following:

H5: There is a positive relationship between the quality of corporate governance

and the timeliness of price discovery.

We also consider the interaction between ownership concentration and

corporate governance on the timeliness of price discovery. The empirical evidence

suggests the existence of both shared benefits and private benefits of control, and

both of them motivate large-block ownership (Holderness, 2003; Barclay and

Holderness, 1989). The concentration of ownership would vary with the magnitude

of the benefit of control. Lamba and Stapledon (2001) argue that a firm is more

likely to have a large blockholder if the private benefit of control potentially

available to the block holder is large. If the private benefit of control is the

motivation for and the determinant of a concentrated ownership structure, insiders

are less likely to voluntarily adopt effective corporate governance arrangements that

will prevent them from expropriating the private benefits. This is especially so if the

dominant shareholder can “lock in” control and is thus able to influence corporate

decisions on the corporate governance arrangement. Controlling shareholders have

enough votes to determine the voting outcome as well as the ability to elect directors

and thus have their preference followed by the board (Bebchuk and Hamdani, 2009).

25

Concentrated ownership can thus provide a mechanism for controlling shareholders

to protect their benefit of control.

More important, the effectiveness of many governance arrangements critically

hinges on whether the firm has a controlling shareholder (Bebchuk and Hamdani,

2009). Many corporate governance arrangements designed to address traditional

agency problem between management and shareholders cannot address controlling

shareholders’ opportunism. For example, since the controlling shareholders would

typically have enough votes to prevent replacement of the management team, hostile

takeovers and proxy contests are largely irrelevant to firms with controlling

shareholders (Bebchuk and Hamdani, 2009). In this respect, controlling shareholders

have the chance to strategically choose corporate governance arrangements which do

not prevent them from seeking private benefits.

Due to the reduced effectiveness of internal corporate governance mechanisms

in firms with controlling shareholders, disclosure and thus transparency of these

firms are less likely to be improved by having better corporate governance.

Therefore, compared to widely-held firms, the association between internal corporate

governance and the timeliness of price discovery is expected to be weaker in closely-

held firms. We thus predict the following:

H6: Controlling shareholders moderate the positive relationship between

corporate governance and the timeliness of price discovery.

3.5 Chapter summary

This chapter develops the hypotheses on how large shareholdings and

corporate governance relate to the timeliness of price discovery. We predict a non-

linear relationship between ownership concentration and the timeliness of price

26

discovery. We also hypothesize that the identity of the largest shareholder matters to

the speed of price discovery. Since multiple large shareholders can provide valuable

monitoring, we hypothesize that the presence of a second largest shareholders

increases the timeliness of price discovery.

In line with the literature, we expect firms with better corporate governance

have less agency problem and information withholding, and so hypothesize a

positive relationship between corporate governance and the timeliness of price

discovery. We extend this line of argument by predicting that controlling

shareholders moderate the positive relationship between corporate governance and

the timeliness of price discovery.

27

Chapter 4: Data and Research Method

4.1 Introduction

This chapter presents the data and research method. It begins with a discussion

of the various data sources and the sample selection criteria in Section 4.2. Section

4.3 outlines the measurement of the test variables, and the research method is

discussed in Section 4.4. Section 4.5 provides a chapter summary.

4.2 Data

Our initial sample consisted of the top 250 companies (by market

capitalization) listed on the Australian Securities Exchange (ASX) from 2001 to

2008. To compute the timeliness metric, data on daily closing stock price and market

index, and preliminary financial statement (PFS) dates were sourced from

Bloomberg and Securities Industry Research Centre of Asia Pacific (SIRCA).

Financial characteristics of the firms such as total debt, total assets, and price to book

ratio are obtained from the Aspect Fin Analysis database.

Ownership data were taken from the Bureau Van Dyk (BVD) Osiris database.

We extract the percentage shareholding and identity of shareholders with more than

5% direct ownership in the firm. We then construct the following ownership

variables: Largest_Shareholding is the percentage direct shareholding of the largest

shareholder; Closeheld is the total percentage shareholding of all shareholders with

more than 5% ownership; Second_Shareholder is a dummy which indicates the

presence of a second largest shareholder; and Second_Shareholding is the percentage

shareholding of the second largest shareholder. Additionally, we categorize the

largest and second largest shareholders according to whether they are a family or

28

financial institution and these are denoted by Family(Largest);

Financial_Insitution(Largest); Family(Second); and Financial_ Insitution(Second).

We obtain corporate governance data from various issues of the Horwath

Corporate Governance reports. These reports provide data on corporate governance

quality for the top 250 companies (by market capitalization) listed on the ASX from

2001 to 2008. The governance quality rankings and ratings are based on information

about the board and its principle committees taken from the company annual reports

and related party disclosures. A five-star rating indicates outstanding corporate

governance structure and a one-star rating indicates the company’s corporate

governance structures are lacking in several areas (2002 Horwath Report, p. 23).

Companies with a five-star rating would have an independent board of directors and

associated board committees which meet on a regular basis as well as full disclosure

of transactions with related parties.

The Horwath reports also provide the rankings of each firm based its corporate

governance practice. As these are finer measures of corporate governance quality

than the ratings, we use Horwath governance rankings in our analysis. The variable

Governance denotes the company’s ranking in the Horwath reports, which we re-

scale to a range between 0 and 1, with a higher value of Governance representing

higher quality corporate governance. We also generate a dummy variable,

High_Governance, which takes a value of one if Governance is above the sample

average and zero otherwise. Our final (unbalanced) panel data consists of 1,318 firm-

year observations for 355 unique firms. The frequency distribution in Table 4.1

shows that our sample is evenly distributed across the years.

29

Table 4.1

Frequency distribution by year for the final sample of 1,318 firm-years, 2001-2008

4.3 Research method

To test the various determinants of the timeliness of price discovery, we

estimate the following regression model:

titititi

tititi

tititi

ControlsGovernanceHighngShareholdiestLGovernancerShareholdeSecondestLnInstitutioFinancialestLFamily

ngShareholdiestLngShareholdiestLMetricTimeliness

,,8,7,6

,5,4,3

,2,10,

__arg_)arg(_)arg(

2^_arg_arg_

εβββ

βββ

βββ

++×++

+++

++=

.

(4.2)

We include in the equation the squared term for the largest percentage shareholding

due to suspected non-linearity in its relationship with the timeliness of price

discovery. If there is an inverted U-shape between the timeliness of price discovery

and the largest shareholding, then we would expect β1 to be positive and β2 to be

negative. Although not shown in the equation, we also include alternative measures

of large shareholdings discussed earlier, i.e., Closeheld and Second_Shareholding

and their squared terms. Family(Largest) and Financial_ Institution(Largest) denote

that the largest shareholder is a family and a financial institution respectively. A

positive β3 and β4 coefficient would suggest that firms with family and financial

institutions as the largest shareholder are less timely in their price discovery.

Year N % Cum. %2001 167 13% 13%2002 172 13% 26%2003 176 13% 39%2004 175 13% 52%2005 163 12% 65%2006 169 13% 78%2007 155 12% 89%2008 141 11% 100%Total 1,318 100%

30

Second_Shareholder indicates the presence of a second largest shareholder with at

least 5% shareholding. A negative β5 would suggest that the presence of a second

largest shareholder increases the timeliness of price discovery. Although not shown

in the equation, we also test for the identity of the second largest shareholder using

Family(Second) and Financial_Institution(Second), which indicate that the identity

of the second largest shareholder is a family or a financial institution respectively.

If corporate governance quality can improve the timeliness of price discovery

as predicted, β6 should be significant and have a positive sign.

Largest_Shareholding× High_Governance is the interaction term between the

largest percentage share ownership and corporate governance. If there is an

interaction effect between the largest percentage ownership and corporate

governance on the timeliness of price discovery, β7 would be significant. We predict

that controlling shareholders moderate the positive relationship between governance

quality and the timeliness of price discovery and thus β7 would be positive.

In the tests, we also control for firm size, leverage, and growth opportunity.

Firm size has been reported to be a factor influencing the quality and quantity of firm

disclosure (Johnson et al., 2001; Lang and Lundholm, 1993). Specifically, because

larger firms have a greater exposure to litigation than their smaller counterparts and

because of their ability to capitalize on the economies of scale in the production and

dissemination of firm-specific information, larger firms have a richer information

environment. Their greater propensity to disclose information (e.g., Kasznik and Lev,

1995; Brown et al., 2005) and their shorter reporting lags (Chambers and Penman,

1984) suggest a timelier price discovery for larger firms. Size is the natural logarithm

of market capitalization at the end of fiscal year.

31

The importance of leverage as a determinant of timeliness is related to its

monitoring role. Leverage can act as a disciplining mechanism in curbing

management opportunistic use of excess cash (Jensen, 1986). The fact that highly

levered firms are under greater scrutiny by creditors suggests that highly levered

firms have better disclosure, which in turn suggests greater timeliness of price

discovery. Leverage is measured as total debt divided by total assets.

Information asymmetry can constrain a firm’s access to lower cost external

financing (Verrecchia, 2001). Thus we argue that firms with a higher growth

opportunity set, which are in greater need of external funding, will improve

disclosure to mitigate information asymmetry. This suggests that there is a positive

relationship between the timeliness of price discovery and growth opportunities. To

control for growth opportunities, we include Price_to_Book, calculated as the

closing share price on the last day of the company’s financial year divided by the

share equity per share.

BB06 show that good news tends to be reflected in the share price sooner,

suggesting that the timeliness of price discovery is related to the nature of the news

released. Therefore, we employ a good news dummy (Good_News) to indicate

whether the share price rose (Good_News=1) or fell (Good_News=0) relative to the

market over the 365 days ending 14 days after the PFS release. Following BB06, an

industry dummy for the natural resource sector is included in the tests. Year

dummies are also included.

Since the sample has both a cross-sectional and a time series dimensions, we

need to choose the appropriate regression model. First, we conduct the Breusch and

Pagan LM test for random effects and compare cross-section and panel regression

models. The null hypothesis for this test is that there is no random effect, i.e., the

32

unit specific errors are not correlated. If the null can be rejected at the 5% significant

level, this suggests the unit specific errors are correlated and a panel regression

model is more appropriate than the classical linear regression model.

Second, we test whether the panel regression model should be fixed or random.

Fixed effect models assume unobservable variables and explanatory variables are

correlated and they control for all time-invariant differences. However, fixed effect

models cannot be used to investigate time-invariant causes of the dependent

variables. In contrast, random effect models assume that the entity’s error term is not

correlated with the predictors, which allows for time-invariant variables as

explanatory variables.

To test whether the unit specific errors are correlated with the explanatory

variables, we use the Hausman test. The null hypothesis is that the preferred model is

a random effect model and the alternative is the fixed effects model. It basically tests

whether the unique errors are correlated with the regressors. If the null can be

rejected at the 5% significant level, we use a fixed effect model; otherwise, a random

effect model will be employed. Additional, we estimate our model using robust

standard errors clustered by firm to control for heteroskedasticity and within-firm

correlation in the error term.

To address potential endogeneity between timeliness and our two main

explanatory variables of interest, i.e., ownership and corporate governance, we

implement commonly used methods, fixed-effect panel regressions and instrumental

variables approach. In running the 2SLS regression, we use the first-stage F-statistic

to test if the instrument is weak. The Wu-Hausman F-statistic and Durbin Chi-

squared-statistic are used to test whether ownership and corporate governance

variables are endogenous and whether a 2SLS is appropriate. The hypothesis of these

33

two tests is for exogeneity. If the null is rejected, then OLS is inconsistent and we

should employ instruments. The results from these tests are reported in Chapter 5.

4.4 Variable measurements

Our dependent variable is the timeliness of price discovery, denoted by

Timeliness_Metric. This measure is proposed by BB06, who describe it as the speed

at which a firm’s share price reflects the net effect of all value-relevant information

over the year, where the year is defined to be 365 calendar days ending two weeks

after the release date of the firm’s preliminary financial statement (PFS):

Timeliness_Metric = (∑ |(𝑙𝑛(𝑃0) − 𝑙𝑛(𝑃𝑡)) − (𝑙𝑛(𝐼0) − 𝑙𝑛 (𝐼𝑡))|𝑡=0𝑡=−364

�)/365 (4.1)

where P is the share price and I is the market index (i.e., Australian All Ordinaries

Accumulation Index ), both observed at daily intervals from day -364 until day 0,

where day 0 is two weeks after the release of the firm’s PFS date. P0 and I0 are

respectively the share price and the market index at day 0. The intuition behind this

measure is that the larger the value of Timeliness_Metric, the longer it takes for a

firm’s share price to impound information and converge to price P0. That is, a

smaller value of Timeliness_Metric is associated with faster price discovery. The

baseline timeliness metric focuses on pricing outcomes and pays no attention to the

means by which price discovery occurs (BB06).

According to Beekes and Brown (2007), one concern about the timeliness

measure is that idiosyncratic share price volatility tends to inflate the measure when

calculated at the individual firm year level. When timeliness is measured by the

mean squared deviation of the daily price from the benchmark price, there is a

simple relationship between the volatility of price and the timeliness of price

discovery. This is due to timeliness being equal to the volatility of price plus the

square of the bias in price relative to the benchmark price (Beekes and Brown, 2007).

34

To address this issue, Beekes and Brown (2006) deflate the timeliness measure by

one plus the absolute value of the stock’s return over the period which timeliness is

calculated. In this study, we also investigate the model using the deflated timeliness

metric.

Descriptive statistics of the final sample reported in Table 4.2 show that the

timeliness metric5 ranges from 0.002 to 1.374, has a mean (median) of 0.198 (0.151)

with a standard deviation of 0.168. These statistics are similar to those provided by

Brown and Hsu (2008) for the years 1980 to 2006 and Jackson (2010) for the years

1991 to 200. However, both the mean and median timeliness metrics are lower than

those of the earlier studies, suggesting that the speed of price discovery has increased

in recent years, due perhaps to the heightened enforcement legislations and activity

by Australian Securities and Investments Commission (ASIC) since 2004, and the

introduction of corporate governance code by the ASX in 2003.

The principal explanatory variables in our analysis are corporate ownership

and governance quality. There are 94.2% (971 out of 1,031) firm-year observations

with direct shareholdings in excess of 5%. As shown in Table 4.2, the largest

shareholder owns an average (median) of 21.6% (15.4%) of the outstanding shares,

with their percentage ownership ranging from 5% to 100%. Families and financial

institutions as the controlling (largest) shareholder account for 3.10% and 43.0% of

the sample respectively. About 81.2% firm-year observations (837 out of 1,031)

have a second largest shareholder who holds an average (median) of 11.5% (10.5%)

of the shares. These second largest shareholders are mostly financial institutions

(48.4%), with families comprising a much smaller proportion (2.13%).

5 The deflated timeliness metric ranges from 0.002 to 1.287, has a mean (median) of 0.202 (0.156) with a standard deviation of 0.167.

35

Table 4.2Descriptive statistics for 1,318 firm-year observations, 2001-2008

Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1). Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_Institution(Second) are dummies indicating families or financial institutions as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalization at the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. Natural_Resource indicates firms belonging to the natural resource sector.

Variable Mean Median Min P25 P75 Max SDTimeliness_Metric 0.209 0.161 0.002 0.096 0.255 1.374 0.175Largest_Shareholding 0.216 0.154 0.050 0.109 0.246 1.000 0.172Closeheld 0.526 0.547 0.050 0.291 0.744 1.000 0.279Second_Shareholding 0.115 0.105 0.050 0.080 0.137 0.500 0.059Governance 0.501 0.500 0.000 0.260 0.740 0.996 0.285Size 8.861 8.760 6.810 8.410 9.230 11.390 0.624Leverage 0.220 0.218 0.000 0.076 0.321 1.556 0.178Price_to_Book 3.716 2.250 0.000 1.400 4.050 84.700 5.291Second_Shareholder 0.812 1.000 0.000 1.000 1.000 1.000 0.391Family(Largest) 0.031 0.000 0.000 0.000 0.000 1.000 0.174Financial_Institution(Largest) 0.430 0.000 0.000 0.000 1.000 1.000 0.495Family(Second) 0.021 0.000 0.000 0.000 0.000 1.000 0.145Financial_Institution(Second) 0.484 0.000 0.000 0.000 1.000 1.000 0.500High_Governance 0.379 0.000 0.000 0.000 1.000 1.000 0.485Good_News 0.546 1.000 0.000 0.000 1.000 1.000 0.498Natural_Resource 0.284 0.000 0.000 0.000 1.000 1.000 0.451

36

The statistics on Closeheld show that our average (median) firm has 52.6%

(54.7%) of its outstanding shares held by shareholders with at least 5% direct

ownership in the firm. Governance ranges between 0.000 and 0.996, and has a mean

of 0.501 and a median of 0.500.

Firm size, as measured by market capitalization, ranges from AUD 1.085

billion to AUD 88.432 billion, with a mean (median) of AUD 8.824 (6.374) billion.

Leverage and Price_to_Book have a mean (median) of 0.220 (0.218) and 3.716

(2.250) respectively. Up to 54.9% of our sample observations have good news

relative to the market during the sample period and 28.4% of them belong to the

natural resource sector.

4.5 Chapter summary

This chapter discusses the data source and sample selection, variables

measurements, and research method. Selecting from the top 250 firms list on the

ASX from 2001 to 2008, our final sample consists of 1,318 firm-year observations

for 355 firms. The two main explanatory variables are ownership and corporate

governance, and the control variables include firm size, leverage, growth

opportunities, the nature of the news released (i.e., good or bad news) and the natural

resources sector.

Various tests are outlined to find the most appropriate regression model, including

the test for potential endogeneity.

37

Chapter 5: Empirical Results

5.1 Introduction

This chapter discusses the empirical results. Section 5.2 describes the

univariate analysis and section 5.3 focuses on the multivariate analysis. Section 5.4

addresses the potential endogeneity issue that may arise in our data and Section 5.5

summarizes and concludes.

5.2 Univariate analysis

We start our empirical analysis by testing the Pearson-product moment

correlation between the continuous variables. Table 5.1 shows that only one of the

ownership variables, Closeheld, is highly correlated with the timeliness metric,

providing some preliminary evidence that ownership concentration does matter to

the timeliness of price discovery. The timeliness metric is also correlated with

governance, firm size, leverage, and growth opportunities. Specifically, as predicted,

better governed firms have timelier price discovery. So are larger firms that have

higher leverage but lower growth potential. The table also shows governance is

highly correlated with all the ownership variables, suggesting potential

multicollinearity. To minimize this problem, we will include only one of these

variables in the regression at the same time.

Next, we test the difference in mean (and median) timeliness metric across

subsamples of firms, as shown in Table 5.2: high vs low corporate governance

quality; whether there is a second largest shareholder present in the firm; whether the

largest and the second largest shareholder is a family or a financial institution; and

the nature of the news (good vs bad news). As Table 5.2 shows, the timeliness of

price discovery is significant faster in the presence of a second largest shareholder,

38

Table 5.1 Correlation coefficients between test variables for 1318 firm-year observations, 2001-2008

Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1). Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Governance is the corporate governance ranking in Horwath report. Size is the natural logarithm of market capitalization at the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. * indicates significance at the 5% level.

Timeliness_Metric 1.000Largest_Shareholding 0.003 1.000Closeheld -0.070 * 0.597 * 1.000Second_Shareholding -0.031 0.306 * 0.686 * 1.000Governance -0.136 * -0.114 * 0.117 * 0.095 * 1.000Size -0.220 * 0.066 * 0.216 * 0.180 * 0.311 * 1.000Leverage -0.138 * 0.019 0.073 * 0.043 0.155 * 0.190 * 1.000Price_to_Book 0.095 * -0.030 -0.037 -0.043 -0.082 * 0.076 * -0.063 * 1.000

Price_to_

Book

Timeliness_

Metric

Leverage

Largest_

Shareho

lding

Size

Governa

nce

Second_

Shareho

lding

Closehel

d

39

Table 5.2 Univariate test of the difference in the mean and media of timeliness metric

This table shows the difference test for both non-parametric (Mann-Whitney test) and parametric (t test) in timeliness of price discovery. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_Institution(Second) are dummies indicating the family and financial institution as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalisation (in AUD million) at the fiscal year end. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. P-values are in brackets.

Count Meant_stat

(p_value) Medianz_stat

(p_value)Second_ShareholderNo 148 0.223 2.330 0.179 1.811Yes 685 0.191 (0.020) 0.146 (0.070)

Family(Largest)No 810 0.198 1.409 0.153 1.358Yes 23 0.151 (0.159) 0.140 (0.175)

Financial_Institution(Largest)No 460 0.202 1.077 0.152 0.574Yes 373 0.190 (0.282) 0.153 (0.566)

Family(Second)No 818 0.197 0.587 0.152 -0.286Yes 15 0.173 (0.558) 0.169 (0.775)

Financial_Institution(Second)No 409 0.209 2.280 0.166 2.322Yes 424 0.184 (0.023) 0.141 (0.020)

High_GovernanceNo 788 0.226 4.383 0.172 3.937Yes 530 0.183 (0.000) 0.143 (0.000)

Good_NewsNo 598 0.195 -2.670 0.147 -3.544Yes 720 0.221 (0.008) 0.171 (0.000)

40

suggesting that the second largest shareholder can monitor the controlling shareholder and thus

reduce the information asymmetry. In most case, the identity of the largest and second largest

shareholders, i.e., whether it is a family or a financial institution, makes no difference to the

timeliness of price discovery. The only exception is when a financial institution is the second

largest shareholder, which is positively related to the speed of price discovery. Consistent with

the evidence in BB06, firms with better corporate governance have a timelier price discovery

process. However, contrary to their finding, we find bad news tends to get out earlier during our

study period. We are intrigued by this finding and will investigate it further later.

5.3 Multivariate analysis

The above results are univariate and thus do not allow for possible interactions between the

independent variables in relation to the timeliness of price discovery. We therefore conduct a

multivariate analysis which will consider the relationships between the timeliness of price

discovery and ownership structure, corporate governance quality, and control variables all at

once.

To choose the appropriate regression model, we conduct the Breusch and Pagan LM (BP

LM) test for random effects and compare cross-section and panel regression models. As shown

in Table 5.3, the null hypothesis of no random effects is rejected, implying that a panel

regression model is more appropriate than a classical linear regression model. To decide whether

the panel regression model should be fixed or random, we use the Hausman test. The null could

not be rejected, implying that the preferred model is a random effects one. Therefore, we employ

random panel regression models in our analysis. Robust standard errors clustered by firms are

used to control for heteroskedasticity and within-firm correlations in the error term.

41

Table 5.3 Random Effect Panel Regressions of the Timeliness of Price Discovery, Corporate Ownership, and Governance

Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1). Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_ Institution(Second) are dummies indicating families or financial institutions as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalization at the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. Natural_Resource indicates firms belonging to the natural resource sector. P-values are in brackets.

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Largest_Shareholding -0.221 -0.212 -0.227 -0.224 -0.214

(0.043) (0.053) (0.035) (0.034) (0.044)Largest_Shareholding^2 0.266 0.246 0.270 0.299 0.278

(0.092) (0.117) (0.084) (0.081) (0.105)Closeheld -0.145 -0.138

(0.038) (0.044)Closeheld^2 0.098 0.096

(0.131) (0.133)Family(Largest) -0.065 -0.060 -0.064

(0.001) (0.001) (0.001)Financial_Institution(Largest) -0.008 -0.005 -0.007

(0.444) (0.663) (0.541)Second_Shareholder -0.022

(0.246)Second_Shareholding -0.345

(0.040)Second_Shareholding^2 0.915

(0.023)Family(Second) -0.015 -0.014

(0.522) (0.547)Financial_Institution(Second) -0.006 -0.003

(0.664) (0.812)Governance -0.051 -0.014

(0.036) (0.548)High_Governance 0.005 0.005

(0.785) (0.790)Largest_Shareholding×High_Governance -0.078 -0.074

(0.288) (0.314)

42

Table 5.3 (Continued)

Size -0.054 -0.053 -0.050 -0.050 -0.051 -0.051 -0.066 -0.052 -0.051 -0.051(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Good_News 0.030 0.029 0.029 0.029 0.028 0.029 0.023 0.030 0.030 0.029(0.003) (0.004) (0.003) (0.004) (0.004) (0.004) (0.004) (0.003) (0.003) (0.003)

Natural_Resource 0.092 0.092 0.093 0.092 0.091 0.091 0.045 0.091 0.091 0.091(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.009) (0.000) (0.000) (0.000)

Leverage -0.027 -0.032 -0.020 -0.025 -0.026 -0.024 -0.138 -0.026 -0.026 -0.031(0.430) (0.354) (0.569) (0.469) (0.445) (0.481) (0.002) (0.451) (0.439) (0.358)

Price_to_Book 0.003 0.004 0.003 0.004 0.004 0.004 0.002 0.003 0.003 0.004(0.008) (0.005) (0.009) (0.005) (0.008) (0.008) (0.206) (0.008) (0.009) (0.005)

Constant 0.863 0.857 0.834 0.833 0.824 0.818 0.884 0.850 0.833 0.829(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Observations 825 825 825 825 825 825 1309 825 825 825R-squared overall 0.168 0.171 0.169 0.171 0.166 0.170 0.104 0.168 0.168 0.171Wald Chi2 105.973 116.959 106.302 117.161 106.115 111.324 126.666 106.392 110.238 121.210

BP LM test for random effectChi2 11.147 11.998 12.057 12.672 11.087 9.246 30.637 11.137 11.702 12.490

(0.001) (0.001) (0.001) (0.000) (0.001) (0.002) (0.000) (0.001) (0.001) (0.000)Hausman test for fixed effectChi2 5.421 5.928 4.117 5.191 3.976 5.864 17.467 5.859 10.496 11.306

(0.942) (0.968) (0.981) (0.983) (0.991) (0.970) (0.133) (0.951) (0.725) (0.790)

43

Table 5.3 shows the estimated coefficients with their p-values stated in brackets.

Specifications (1) and (3) test Hypothesis 1 using alternative measures of ownership.

Specification (1) shows the estimated coefficient of Largest_Shareholding is significant

and negative, suggesting that price discovery is quicker for firms with more

concentrated ownership, as captured by the percentage of the largest shareholding. This

finding is consistent with our expectation that large shareholdings mitigate agency

problem and reduce information asymmetry, and thus improve the timeliness of price

discovery. There is some evidence of non-linearity in the relationship, as indicated by

the positive coefficient of the squared term, Largest_Shareholding^2. That is, the

entrenchment effect at high ownership levels implies less timely price discovery as the

controlling shareholder attempts to obscure potential expropriation of outside minority

rights through lower disclosure. Similar results are found when we use Closeheld as the

ownership measure in Specification (3) although there is only weak evidence of non-

linearity in the relationship using this variable.

We expect the presence of a second largest shareholder effectively monitors the

controlling shareholder and makes it more difficult for the latter to withhold value-

relevant information. Therefore, we predict a positive relationship between the presence

of a second largest shareholder and the timeliness of price discovery in Hypothesis 2.

However, Specification (5) shows no association between Second_Shareholder and

Timeliness_Metric, Specification (6) shows a non-linear relationship between the second

largest percentage shareholding and the timeliness of price discovery. At low

shareholding levels, Second_Shareholding is negatively related to Timeliness_Metric,

presumably due to the monitoring role of the second largest shareholder. However, at

44

high shareholding levels, the second largest shareholder appears to collude with the

controlling owner to share private benefits (Bloch and Hege, 2001).

The role of large shareholders in agency model in part depends on who they are –

therefore we test the identity of the largest shareholder in Specifications (2) and (4).

Surprisingly, the results show no evidence that having a financial institution as the

largest shareholder relates to the timeliness of price discovery. We also test the

interaction effect between Financial_Institution(Largest) and Largest_Shareholding on

Timeliness_Metric and find no significant result (not reported in the table for the sake of

brevity). This is contrary to Hypothesis 3, which predicts institutional investors can

provide better monitoring and disclosure and thereby improve the timeliness of price

discovery. The question of what is the appropriate role of institutional shareholders is

yet to be resolved in the literature and this may explain our (non) finding. For example,

how are financial institutions, which are monitoring agents, to be themselves monitored?

Gorton and Kahl (1999) argue that institutional investors may be imperfect monitors due

to their own internal agency problem. Moreover, the relative roles of institutional

investors and large shareholder are not well understood (Gillan and Starks, 2003). Not

much is known about differences that may exist between the monitoring abilities and

incentives of institutional investors and those of large non-institutional shareholder.

Next, we examine the timeliness of price discovery of family-controlled firms.

Specification (2) shows that firms with family as the largest shareholder have faster

price discovery. This evidence suggests that controlling families can effectively monitor

managers (Demsetz and Lehn, 1985; Ali et al., 2007).

45

Specification (7) examines the relationship between corporate governance and

timeliness, and is pretty much a replication of the specification in BB06. Results show

that, consistent with Hypothesis 5 and BB06, corporate governance quality is

significantly and positively related to the timeliness of price discovery. This result

supports our argument that higher corporate governance quality is associated with lower

agency problem and lower information asymmetry. Consequently, better-governed firms

have timelier price discovery.

We include both the ownership and governance variables in Specification (8),

which shows that only the ownership variable (Largest_Shareholding) is significant.

This is likely due to the high correlation between the ownership and corporate

governance variables, as identified earlier in Table 5.1. Our results show that ownership

subsumes the explanatory power of governance. We find no evidence of an interaction

effect between the largest percentage shareholding and corporate governance quality

(Largest_Shareholding×High_Governance) on the speed of price discovery, contrary to

Hypothesis 6 in specification (9).

Specification (10) is the augmented regression, which includes the largest

percentage shareholding, the identity of the largest shareholder, corporate governance,

as well as the interaction between ownership and governance. We do not include the

second largest shareholding as it is highly correlated with Largest_Shareholding and

Closeheld. As shown in the table, the results for Largest_Shareholding and

Largest_Shareholding^2 remain intact, as before. Therefore, the timeliness of price

discovery increases with the largest percentage shareholding at the low level, and the

relationship is non-linear. However, neither corporate governance nor its interaction

46

term with the largest shareholding is significant in the augmented regression. In term of

the identity of the largest shareholder, only family is significant.

Apart from Leverage, we find robust and significant results for all the control

variables. Size has a negative and significant coefficient, suggesting that larger firms

have speedier price discovery due to their richer information environment. Contrary to

our prediction, high growth firms, as represented by a higher Price-to-Book ratio, are

more sluggish in their speed of price discovery, probably because of the high risk

inherent in high growth firms which may slow down the price discovery process.

Contrary to our expectation and BB06, the Good_News dummy is significantly positive,

suggesting that bad news gets out earlier. One possible explanation for this is the

introduction of corporate governance recommendation by the ASX in 2003, which

requires a more balanced disclosure of both good and bad news.6

5.4 Endogeneity

There is a growing literature that recognizes models containing corporate

governance or ownership variables suffer from endogeneity problems (see for example,

Hermalin and Weisbach (1991); Himmelberg et al. (1999); Weir et al. (2002); Zhou

(2001); and Coles et al. (2005)). If endogeneity is present, ignoring it will yield

inconsistent estimates. The particular form of endogeneity faced in governance and

ownership models is simultaneity – in our case, this means that the timeliness of price

discovery, ownership, and governance may be simultaneously determined. For example,

firms with a timelier price discovery process may attract certain large shareholders and

this will result in an endogeneity in the relationship between the largest shareholding

6 We also investigate the model using the deflated timeliness metric as the dependent variable. The results are qualitatively similar and are provided in the appendix.

47

and the speed of price discovery. In a similar vein, in an attempt to improve the

timeliness of price discovery, firms may take actions to improve their corporate

governance. Some studies argue that the firm’s disclosure policy may substitute for

inadequate governance practices (for example, Eng and Mak (2003)), implying that a

simultaneous causality may well exist between corporate governance and firm level

disclosure, which in turn affects the timeliness of price.

The literature provides two commonly methods to address the endogeneity

problem. They are the fixed effect estimation method and the instrumental variables (IV)

approach (Brown et al., 2011). We use both of these methods in this study. Although the

fixed effect panel regression model is not more efficient than the random effects model,

according to the Hausman test in Table 5.3, the fixed effects model controls for all time-

invariant differences. Therefore, we use the fixed effect model to address the potential

endogeneity issue and to see whether the results from the random effect model can hold

in face of endogeneity. Of course, the success of this method hinges on the presence of

longitudinal variation in the variables. The results are reported in Table 5.4.

Table 5.4 shows that the results for the various ownership variables are mostly

intact although we observe that the non-linearity in the relationship between the large

shareholding and the timeliness of price discovery is more significant in the fixed effects

model. However, contrary to the results from the random effects model (Table 5.3),

specification (7) shows that Governance is not significant. Interestingly, we find an

interaction effect between corporate governance and ownership

(Largest_Shareholding× High_Governance) on the timeliness of price discovery in

Specification (9). The results suggest the positive relationship between the largest

48

Table 5.4

Fixed Effect Panel Regressions Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1). Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_Institution(Second) are dummies indicating families or financial institutions as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalizationat the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. P-values are in brackets.

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Largest_Shareholding -0.423 -0.411 -0.424 -0.360 -0.348

(0.010) (0.012) (0.011) (0.018) (0.020)Largest_Shareholding^2 0.510 0.487 0.512 0.516 0.493

(0.060) (0.068) (0.060) (0.050) (0.058)Closeheld -0.232 -0.226

(0.007) (0.006)Closeheld^2 0.158 0.155

(0.045) (0.041)Family(Largest) -0.049 -0.044 -0.050

(0.031) (0.056) (0.032)Financial_Institution(Largest) -0.014 -0.012 -0.013

(0.394) (0.489) (0.428)Second_Shareholder -0.027

(0.212)Second_Shareholding -0.480

(0.027)Second_Shareholding^2 1.062

(0.044)Family(Second) -0.005 -0.002

(0.864) (0.954)Financial_Institution(Second) -0.007 -0.003

(0.697) (0.876)Governance -0.053 0.015

(0.139) (0.740)High_Governance 0.025 0.024

(0.365) (0.384)Largest_Shareholding×High_Governance -0.219 -0.217

(0.048) (0.049)

49

Table 5.4 (Continued)

Size -0.135 -0.134 -0.127 -0.126 -0.131 -0.130 -0.085 -0.134 -0.139 -0.138(0.002) (0.002) (0.004) (0.004) (0.003) (0.004) (0.005) (0.002) (0.001) (0.001)

Good_News 0.031 0.030 0.028 0.027 0.028 0.028 0.028 0.031 0.030 0.030(0.007) (0.008) (0.013) (0.014) (0.011) (0.014) (0.001) (0.007) (0.007) (0.008)

Leverage 0.022 0.020 0.039 0.037 0.034 0.037 -0.137 0.022 0.022 0.020(0.781) (0.800) (0.627) (0.646) (0.670) (0.646) (0.074) (0.785) (0.780) (0.801)

Price_to_Book 0.003 0.003 0.003 0.003 0.004 0.004 0.000 0.003 0.004 0.004(0.144) (0.166) (0.134) (0.154) (0.130) (0.123) (0.843) (0.154) (0.127) (0.148)

Constant 1.397 1.397 1.332 1.332 1.341 1.332 1.044 1.389 1.432 1.430(0.000) (0.000) (0.001) (0.001) (0.001) (0.001) (0.000) (0.000) (0.000) (0.000)

Observations 825 825 825 825 825 825 1309 825 825 825Adjusted R-squared 0.106 0.107 0.108 0.107 0.093 0.096 0.070 0.105 0.115 0.115F-statistic 3.653 3.779 3.923 4.094 2.846 3.009 5.084 3.445 4.167 4.140

50

percentage shareholding and the timeliness of price discovery is stronger in better-

governed firms.

However, the major drawback of the fixed effects approach is that it relies solely

on within-firm variation to drive the results and is thus impractical in corporate

governance research due to the stickiness of corporate governance (Hermalin and

Weisbach, 1991; Brown et al., 2011). Therefore, we also use the instrumental variables

approach. The challenge in using this approach is in finding the correct instrument.

Knyazeva (2007) proposes governance at the industry level as an exogenous

source of firm level corporate governance. Industry practices offer a benchmark of

governance quality which firm may seek out. At the same time, it does not have the

direct link to the bottom line or firm behavior apart from firm governance. Following

this approach, we calculate the industry average corporate governance by year and use it

as the instrumental variable.

By the same reasoning, we also use the industry average ownership by year as the

instrumental variable for the ownership variables, Largest_Shareholding and Closeheld.

We expect similar ownership structure for firms in the same industry, however, we do

not expect the error term in the regression model to be directly related to the average

industry ownership concentration, as denoted by Largest_Shareholding_Industry and

Closeheld_Industry. Since it is difficult to find an appropriate instrumental variable for

the squared ownership variable, we exclude it from the test of endogeniety. In light of

the high correlation between governance and ownership variables, we test the

governance and ownership variables separately. Table 5.5 provides the results.

51

Table 5.5 2SLS Regressions

Governance is the corporate governance ranking in Howth report. Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of share directly owned by all shareholders with more than 5% shareholding. Governance_Industry, Governance (Ratings)_Industry, Largest_Shareholding_Industry and Closeheld_Industry are the industry averages of the corresponding variable by year. P-values are in brackets.

Panel A: First Stage Regression

Dependent: Governance Laregest_Shareholding Closeheld(1) (2) (3)

Governance_Industry 1.183(0.000)

Largest_Shareholding_Industry 0.951(0.000)

Closeheld_Industry 0.795(0.000)

Constant -1.560 -0.157 -0.587(0.000) (0.120) (0.000)

Controls Included Included Included

Observations 1,296 825 825Adjusted R-squared 0.15 0.05 0.25F-statistic 63.259 38.538 21.061

52

Panel B: Comparison of OLS and 2SLS

.

Dependent(1) (2) (3) (4) (5) (6)

OLS 2SLS OLS 2SLS OLS 2SLSGovernance -0.037 -0.133

(0.033) (0.102)Governance(Ratings)

Largest_Shareholding -0.014 -0.233(0.629) (0.095)

Closeheld -0.037+ -0.177(0.057) (0.159)

Constant 0.676 0.669 0.561 0.817 0.549 0.750(0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Controls Included Included Included Included Included Included

Observations 1,309 1,296 825 825 825 825Adjusted R-squared 0.10 0.09 0.15 0.09 0.15 0.10Chi-squared 161.856 154.147 155.060

Wu_Hausman test of endogeneityF-statistic 1.439 2.717 1.323

(0.231) (0.100) (0.250)Durbin test of endogeneityChi-squared 1.454 2.758 1.345

(0.228) (0.097) (0.246)

Timeliness_Metric

53

In the first stage, we regress governance and ownership variables on their

respective industry average by year and control variables respectively. The results are

provided in Panel A of Table 5.5. Specifications (1) – (3) show the instrument variables

are significant. The adjusted R-squared is relatively high, implying that we do not have a

weak instrument problem. Also, the F-statistic from the Wald test rejects the null

hypothesis that the instruments are weak. In the second stage, we run an OLS using the

fitted value from the first stage regression as our instrument for Governance and

Largest_Shareholding (or Closeheld) respectively.

Panel B of Table 5.5 compares the estimated coefficients from OLS and 2SLS.

Specification (1) shows Governance is significant in the OLS model but not in the 2SLS.

Conflicting results are obtained for different measures of ownership. Specifications (3)

and (4) show that Largest_Shareholding is more significant in the 2SLS regression

model. In contrast, Specifications (5) and (6) report that Closeheld is significant in the

OLS model but not in the 2SLS model.

Before interpreting the 2SLS regression result, we obtain Wu-Hausman and

Durbin chi-squared-statistics to find out whether it is necessary to use an instrumental

variable approach, i.e., whether the parameters obtained by OLS are consistent or not.

Panel B shows that the null hypothesis of exogeneity cannot be rejected for both tests.

This result suggests there are no severe endogeneity problems in our study.7

7 We also conduct two stage panel regressions with random effects and fixed effects. However, we find no reliable endogeneity test results.

54

5.5 Chapter summary

The empirical results are discussed in this chapter, including those obtained from

univariate analysis and multivariate analysis. We also test for potential endogeneity but

find no evidence of severe endogeneity problems in our data suggesting that our results

are robust to this potential problem.

55

Chapter 6: Summary and Conclusion

This thesis tests how ownership concentration and structure as well as corporate

governance relate to the timeliness of price discovery. Since timely disclosure of

informative accounting information is key to price discovery, the agency problem is

expected to influence the timeliness of price discovery through its effect on information

asymmetry. We therefore predict that the speed of price discovery varies with

concentrated shareholding and corporate governance, both of which play an important

role in determining a firm’s agency problem.

We predict and find a non-linear relationship between the concentrated

shareholding, as proxied by the sum of all shareholdings in excess of 5 percent and the

largest percentage shareholding, and the timeliness of price discovery. We argue that

large shareholders can effectively monitor managers and mitigate the agency problem,

and thus reduce information asymmetry. Therefore, all else equal, firms with large

shareholdings experience faster price discovery. However, at high levels of ownership

concentration, the agency problem shifts from a conflict between shareholders and

managers to a conflict between controlling shareholders and minority shareholders. In

this case, the agency problem and inherent information asymmetry increase with the

percentage shareholding by controlling owners, so that the relationship between

concentrated shareholdings and the timeliness of price discovery is negative at high

levels of ownership. Results support a non-linear relationship between large

shareholdings and the timeliness of price discovery, irrespective of whether a random or

fixed effects panel regression model is used.

56

The role of large shareholders in agency problem and corporate disclosure, and

thus the timeliness of price discovery, depends in part on the identity of the large

shareholders. We examine two major controlling owners and they are institutional

investors and families. Contrary to our prediction, we do not find any association

between firms with controlling institutional investors and the timeliness of price

discovery. However, we find family-controlled firms are associated with quicker price

discovery. Despite the potentially more severe conflict between controlling families and

outside shareholders, our finding shows that family ownership is an effective

mechanism in mitigating the agency problem between shareholders and managers and

thus positively affects the timeliness of price discovery.

We predict that the second largest shareholder can potentially monitor the

controlling owner so that firms with a second largest shareholder have timelier price

discovery. However, we fail to find such an association. In further tests, we find there is

a non-linear relationship between the second largest percentage shareholding and the

speed of price discovery, suggesting that at low levels of shareholding, the second

largest shareholders are effective monitors of the controlling shareholder but at high

levels of shareholding, the second largest shareholder colludes with the largest owner to

extract potential benefits from outside shareholders.

Consistent with the extant evidence (Cheng and Courtenay, 2006; Lim et al.,

2007; Beekes and Brown, 2006; Beekes et al., 2006), we find corporate governance

quality is positively related to the timeliness of price discovery in the random effect

panel regression model but not in the fixed effect model. This may be due to the high

stickiness of most corporate governance mechanisms over time (Hermalin and Weisbach,

57

1991; Brown et al., 2011). Contrary to our prediction, we do not find any evidence of an

interaction effect between ownership concentration and corporate governance quality on

the timeliness of price discovery.

Finally, we address potential endogeneity problem using both the fixed effects

regression model and the instrumental variables approach. In general, we find no

evidence showing that there are severe endogeneity problems in our study. Our attempt

at addressing the endogeneity problem does not significantly change the main

conclusion of this study.

58

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67

Appendices

APPENDIX A: RANDOM EFFECT PANEL REGRESSIONS USING DEFLATED TIMELINESS

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Largest_Shareholding -0.215 -0.206 -0.221 -0.218 -0.208

(0.044) (0.054) (0.035) (0.033) (0.043)Largest_Shareholding^2 0.252 0.233 0.257 0.287 0.267

(0.103) (0.131) (0.095) (0.087) (0.112)Closeheld -0.142 -0.135

(0.036) (0.041)Closeheld^2 0.093 0.091

(0.135) (0.138)Family(Largest) -0.063 -0.058 -0.062

(0.000) (0.001) (0.001)Financial_Institution(Larges -0.008 -0.004 -0.007

(0.419) (0.668) (0.525)Second_Shareholder -0.022

(0.232)Second_Shareholding -0.325

(0.041)Second_Shareholding^2 0.811

(0.028)Family(Second) -0.014 -0.013

(0.540) (0.559)Financial_Institution(Second -0.004 -0.002

(0.720) (0.829)Governance -0.049 -0.015

(0.033) (0.513)High_Governance 0.006 0.005

(0.762) (0.767)Largest_Shareholding×High -0.084 -0.080

(0.232) (0.257)

68

(Continued)

Deflated Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1) and deflated by one plus the absolute value of the stock’s log return over the 365-day period. Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_ Institution(Second) are dummies indicating families or financial institutions as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalization at the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. Natural_Resource indicates firms belonging to the natural resource sector. P-values are in brackets.

Size -0.051 -0.050 -0.047 -0.047 -0.048 -0.047 -0.062 -0.049 -0.048 -0.047(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Good_News 0.028 0.028 0.028 0.027 0.027 0.027 0.022 0.029 0.029 0.028(0.003) (0.004) (0.004) (0.005) (0.005) (0.005) (0.004) (0.003) (0.003) (0.004)

Natural_Resource 0.090 0.090 0.091 0.090 0.089 0.089 0.046 0.089 0.089 0.089(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.006) (0.000) (0.000) (0.000)

Leverage -0.029 -0.034 -0.022 -0.027 -0.028 -0.026 -0.132 -0.027 -0.028 -0.033(0.391) (0.321) (0.523) (0.429) (0.400) (0.428) (0.002) (0.412) (0.397) (0.323)

Price_to_Book 0.003 0.004 0.003 0.004 0.003 0.003 0.002 0.003 0.003 0.004(0.007) (0.004) (0.008) (0.005) (0.007) (0.007) (0.152) (0.007) (0.008) (0.005)

Constant 0.817 0.811 0.788 0.787 0.780 0.774 0.833 0.803 0.784 0.781(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)

Observations 825 825 825 825 825 825 1309 825 825 825R-squared overall 0.169 0.172 0.170 0.173 0.167 0.170 0.105 0.169 0.169 0.172Wald Chi2 106.625 117.377 107.145 117.620 106.104 111.131 127.885 107.333 114.547 124.600

69

APPENDIX B: FIXED EFFECT PANEL REGRESSIONS USING DEFLATED TIMELINESS METRIC

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Largest_Shareholding -0.410 -0.399 -0.411 -0.345 -0.335

(0.011) (0.012) (0.011) (0.019) (0.022)Largest_Shareholding^2 0.488 0.467 0.490 0.494 0.473

(0.066) (0.074) (0.066) (0.055) (0.063)Closeheld -0.227 -0.221

(0.006) (0.006)Closeheld^2 0.152 0.149

(0.044) (0.040)Family(Largest) -0.044 -0.038 -0.044

(0.039) (0.078) (0.040)Financial_Institution(Large -0.013 -0.011 -0.012

(0.388) (0.498) (0.423)Second_Shareholder -0.027

(0.201)Second_Shareholding -0.456

(0.028)Second_Shareholding^2 0.978

(0.048)Family(Second) -0.003 0.000

(0.916) (0.997)Financial_Institution(Second -0.005 -0.002

(0.753) (0.903)Governance -0.053 0.012

(0.119) (0.781)High_Governance 0.025 0.024

(0.356) (0.373)Largest_Shareholding×High -0.222 -0.220

(0.042) (0.043)

70

(Continued)

Deflated Timeliness_Metric is the timeliness of price discovery measure estimated as in equation (4.1) and deflated by one plus the absolute value of the stock’s log return over the 365-day period. Largest_Shareholding is the percentage of shares directly owned by the largest shareholder. Closeheld is the total percentage of shares directly owned by all shareholders with more than 5% shareholding. Second_Shareholding is the percentage of shares directly owned by the second largest shareholder. Second_Shareholder is a dummy indicating the presence of a second largest shareholder with at least 5% shareholding. Family(Largest), Financial_Institution(Largest), Family(Second), and Financial_Institution(Second) are dummies indicating families or financial institutions as the largest or second largest shareholder respectively. Governance is the corporate governance ranking in Horwath report. High_Governance indicates Governance above sample average. Size is the natural logarithm of market capitalizationat the fiscal year end. Leverage is total debt divided by total assets. Price_to_Book is the ratio of closing share price at the end of financial year to shareholder equity per share. Good_News is a dummy indicating firms that outperformed the market over the 365 days ending 14 days after the PFS release date. P-values are in brackets.

Size -0.119 -0.118 -0.112 -0.111 -0.115 -0.115 -0.076 -0.118 -0.123 -0.122(0.004) (0.004) (0.006) (0.006) (0.005) (0.006) (0.007) (0.004) (0.002) (0.002)

Good_News 0.029 0.029 0.026 0.026 0.027 0.026 0.026 0.029 0.029 0.028(0.008) (0.009) (0.014) (0.015) (0.011) (0.014) (0.001) (0.008) (0.008) (0.009)

Leverage 0.017 0.016 0.034 0.032 0.029 0.031 -0.127 0.017 0.017 0.015(0.821) (0.839) (0.662) (0.679) (0.706) (0.687) (0.076) (0.825) (0.821) (0.840)

Price_to_Book 0.003 0.003 0.003 0.003 0.004 0.004 0.001 0.003 0.003 0.003(0.158) (0.180) (0.147) (0.166) (0.142) (0.134) (0.766) (0.168) (0.139) (0.159)

Constant 1.251 1.252 1.189 1.189 1.195 1.189 0.959 1.244 1.286 1.285(0.001) (0.001) (0.001) (0.001) (0.001) (0.002) (0.000) (0.001) (0.000) (0.000)

Observations 825 825 825 825 825 825 1309 825 825 825Adjusted R-squared 0.100 0.101 0.103 0.102 0.087 0.089 0.068 0.100 0.111 0.111F-statistic 3.633 3.808 3.931 4.146 2.813 2.968 5.143 3.448 4.167 4.159