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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
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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: _________________________
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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).
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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
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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
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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
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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
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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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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