Description
This paper aims to examine whether firms with high information asymmetry disclose more
information under a continuous disclosure regime, and, second, the paper examines whether continuous
disclosures reduce information asymmetry.
Accounting Research Journal
Continuous disclosure and information asymmetry
Mark Russell
Article information:
To cite this document:
Mark Russell , (2015),"Continuous disclosure and information asymmetry", Accounting Research
J ournal, Vol. 28 Iss 2 pp. 195 - 224
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Continuous disclosure and
information asymmetry
Mark Russell
UQ Business School, The University of Queensland, St. Lucia, Australia
Abstract
Purpose – This paper aims to examine whether frms with high information asymmetry disclose more
information under a continuous disclosure regime, and, second, the paper examines whether continuous
disclosures reduce information asymmetry.
Design/methodology/approach – The study models relations between continuous disclosures and
information asymmetry using ordinary least squares regression and two-stage least squares
regression.
Findings – The study fnds frms with high information asymmetry disclose more information.
Further, the study fnds that disclosure in the presence of high information asymmetry increases
asymmetry. Finally, while bad news increases information asymmetry, the disclosure of frm-specifc
good and bad news is associated with reduced information asymmetry.
Originality/value – The paper identifes conditions under which Continuous Disclosure Regime
increases information in markets and infuences information asymmetry.
Keywords Information asymmetry, Continuous disclosure, Firm performance expectations
Paper type Research paper
1. Introduction
This paper evaluates whether frms with higher information asymmetry disclose more
information under the Australian Continuous Disclosure Regime (CDR), and second,
whether continuous disclosures reduce information asymmetry. Regulators require
continuous disclosure from companies in an expanding number of countries and stock
exchanges: Australia, Canada, New Zealand, Germany, New Zealand, Singapore, Hong
Kong Stock Exchange, London Stock Exchange, New York Stock Exchange, American
Stock Exchange and NASDAQ (Oesterle, 1998; Table I).
The study is motivated by the increased regulation of disclosure in markets to
alleviate information asymmetry. Information asymmetry leads to the ineffcient
allocation of investment resources, adverse selection, insider trading and other negative
outcomes (Lev, 1988; Verrecchia, 2001). The limited CDR studies produce mixed
empirical evidence on the effect of continuous disclosure on information asymmetry
(Brown et al., 1999; Poskitt, 2005). This CDR evidence refects the multifaceted
relation between disclosure and information asymmetry in international studies
The author is grateful for helpful comments on this paper from Pete Clarkson, Greg Clinch, Dan
Collins, Robert Czernkowski, Dan Dhaliwal, Jere Francis, Zoltan Matolcsy, Stephen Taylor, Terry
Walter, Joe Weber, Peter Wells, Anne Wyatt and participants at the AFAANZ Conference 2010 in
Christchurch, the American Accounting Association Annual Meeting 2010 in San Francisco, and
the University of Technology Sydney seminar series. The author acknowledges fnancial support
fromthe UTS School of Accounting and FIRN. Data supplied by the Securities Industry Research
Centre Asia-Pacifc on behalf of the ASX and Aspect Financial.
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1030-9616.htm
Disclosure
and
information
asymmetry
195
Received26 November 2013
Revised31 May2014
Accepted15 August 2014
Accounting Research Journal
Vol. 28 No. 2, 2015
pp. 195-224
©Emerald Group Publishing Limited
1030-9616
DOI 10.1108/ARJ-11-2013-0085
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Table I.
Comparison of
market disclosure
regulations across
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197
Disclosure
and
information
asymmetry
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(Van Buskirk, 2012). Nevertheless, Australian CDR provides a data-rich environment to
reconcile conficting disclosure studies and clarify the unknown effects of continuous
disclosure.
The key contribution from this paper is to identify conditions under which CDR
reduces information asymmetry and increases disclosure. First, the study provides
evidence that frms with high information asymmetry disclose more information.
Second, the study indicates that disclosure in the presence of high information
asymmetry increases asymmetry. Finally, while bad news is likely to increase
information asymmetry, the disclosure of frm-specifc good and bad news is associated
with reduced information asymmetry.
The remainder of the paper is organized as follows. Section 2 reviews the Australian
setting for continuous disclosure, the background literature and develops the
hypotheses. Section 3 describes the research design, the empirical models and variables.
The results are presented in Section 4, and Section 5 fnishes the paper with conclusions.
2. Institutional background and hypothesis development
2.1 Continuous disclosure regulation
The Australian CDR commenced in September 1994 following prominent corporate
failures that involved delayed disclosure and a perceived lack of transparency in
the Australian stock market (Commonwealth Government Report of the Australian
House of Representatives Standing Committee on Legal and Constitutional Affairs,
1991). The continuous disclosure rules are contained in ASXListing Rule 3.1 as follows:
Once an entity is or becomes aware of any information concerning it that a reasonable person
would expect to have a material effect on the price or value of the entity’s securities, the entity
must immediately tell the ASX that information.
A reasonable person would be taken to expect information to have a material effect on
the price or value of securities if the information would, or would be likely to, infuence
persons who commonly invest in securities in deciding whether or not to subscribe for,
or buy or sell, the frst mentioned securities (Section 677, Corporations Act 2001 (Cth)).
Listing Rule 3.1B provides exceptions to continuous disclosure which require
confdentiality, reasonableness and one or more of the following conditions:
• a breach of law to disclose;
• an incomplete proposal or negotiation;
• matters of supposition;
• information generated for the internal management purpose; and
• the information is a trade secret.
The Australian CDR is principle-based and differs from the bright-line specifcation of
classes of information to be disclosed under other regimes. As illustrated in Table I, a
number of countries and stock exchanges have continuous disclosure regimes.
2.2 CDR and managerial disclosure incentives
Despite disclosure regulation, managers have incentives to selectively disclose
information. For example, managers disclose timely good news but delay or withhold
bad news (Kothari et al., 2009). The selective disclosure of information and CDR
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“exception” clauses have raised questions about the operation of the CDR (Cassidy and
Chapple, 2003; Hsu, 2009). Applying the CDR requires management judgment on
price-sensitivity and price discovery in at least three dimensions. First, management
must decide what information is price-sensitive and second whether information is
exempt from disclosure. Third, management must decide the content and presentation
of the information to be disclosed.
A number of studies consider the possibility that managers retain discretion in CDR
disclosure (Brown et al., 1999; Hsu, 2009; Hsu et al., 2012). It is likely that CDR operates
in line with earlier evidence that frms disclose by reference to their economic
characteristics rather than strictly following disclosure rules (Frost and Pownall, 1994).
Notwithstanding management incentives to selectively disclose, studies also suggest
that CDR increased disclosure to change the Australian information environment. Hsu
et al. (2012) study the properties of analyst forecasts under the CDR as it evolved from
1988 to 2001. Hsu et al. (2012) fnd evidence suggesting changes in analyst forecast
properties, and after 1998, forecast dispersion deteriorated for small frms. Nevertheless,
Corlett et al. (2000) suggest that CDR increased the disclosure of information. More
specifcally, Neagle and Tyskin (2001) examine regulatory activity and fnd small frms,
loss frms and some industries are more likely to receive ASX price queries. Chan et al.
(2007) and Dunstan et al. (2010) both fnd management earnings forecasts are associated
with CDR.
The discretionary content and format of disclosure available to managers under
CDR, and the conficting incentives to disclose, potentially infuence the impact of a
mandatory disclosure regime on frms. Nevertheless, the study expects the economic
benefts to the frm from increased disclosure and lower information asymmetry (Jung
and Kwon, 1988; Healy et al., 1999), and CDR compliance pressure, to give management
incentives to disclose under CDR:
H1. Firms with higher information asymmetry disclose more information under
CDR.
2.3 Implications of the continuous disclosure regime for information asymmetry
The disclosure benefts for the frm from lower information asymmetry include the
convergence of investor beliefs, stock liquidity increases and lower price volatility
(Lev, 1988). Nevertheless, higher day-to-day information asymmetry will persist for
frms with more uncertain investments, longer-term projects and transactions
(Affeck-Graves et al., 2002; Miller, 2002). Furthermore, disclosure may increase
short-term information asymmetry for many frms. For example, disclosures may be
costly for investors to process, or induce additional uncertainties and divergent opinions
(Lee et al., 1993; Krinsky and Lee, 1996; Bamber et al., 2011). Unexpectedly, disclosure
may also increase the information advantage of sophisticated investors (Indjejikian,
1991).
Australian studies are mixed on whether CDR disclosure reduces information
asymmetry (Brown et al., 1999; Poskitt, 2005). Brown et al. (1999) fnd a signifcant
association between CDR disclosure and information asymmetry but only for small
companies and for companies performing relatively poorly. However, Brown et al. (1999)
recognize data sample limitations of the 1994-1996 post-CDR data available for their
study. To study the effects of disclosure on informed trading, Poskitt (2005) uses the
probability of informed trading (PIN) model (Easley et al., 1996). He fnds no evidence
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that price-sensitive disclosures are associated with lower information based trading in
the post-2002 period.
Consistent with the economic theory of disclosure consequences in markets (Leuz
and Verrecchia, 2000), the study expects CDR disclosure to reduce information
asymmetry. Nevertheless, in line with event studies (Krinsky and Lee, 1996), the study
also expects CDRdisclosure events to conditionally increase information asymmetry for
frms with high pre-existing information asymmetry. This leads to the following
hypotheses:
H2. Price-sensitive disclosure under CDR reduces information asymmetry.
H3. Price-sensitive disclosure under CDR for frms with high information
asymmetry increases information asymmetry.
3. Empirical analysis
3.1 Sample and data
The initial sample includes all companies listed on the Australian Securities Exchange
(ASX) between 1996 and 2006 with at least one year of market trading data. The sample for
each test is determined by the model and measure of information asymmetry. Information
asymmetry is measured annually and daily. The daily measurement of information
asymmetry is affected by the large number of small frms in the ASX with thinly traded
shares andzerotradingdays. Toaddress these adverse tradingeffects, adailysub-sample is
based on the largest 500 ASX-listed frms over the period of 1996-2006, selected to exclude
the frm-days with zero trading, zero price volatility and abnormally large bid-ask spreads
(where a bid or ask has no corresponding ask or bid, respectively).
Price-sensitive disclosures come from the Securities Industry Research Centre of
Asia-Pacifc (SIRCA) signal Gdatabase. Financial andother companydata andequitybetas
are fromAspect Huntley’s Fin Analysis database. Stock price and trading data for the ASX
Securities Exchange Automated Trading System(SEATS) are fromSIRCAdatabases. The
bid-ask spreads for the ASX’s order-driven market come from SIRCA’s ASX Intra-day
database, while the daily trading volume data and prices come from SIRCA’s ASX Daily
database. Financial analyst data comes from I/B/E/S. The ASX’s industry classifcation is
used until September 2002, after which the study uses the Standard and Poor’s Global
Industry Classifcation System(GICS) as adopted by ASXin 2002.
3.2 Price-sensitive disclosure measure
The SIRCA Signal G database maintains ASX company announcements. The ASX
announcements include those labeled price-sensitive, and other regulated and voluntary
announcements. The announcements are categorized by the ASXusing 19 primary codes:
(1) takeover announcements;
(2) shareholder details;
(3) periodic reports;
(4) quarterly activities report;
(5) quarterly cash fow report;
(6) issued capital;
(7) asset acquisition and disposal;
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(8) notice of meeting;
(9) stock exchange announcement;
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(11) progress report;
(12) company administration;
(13) notice of call (Contributing shares);
(14) other;
(15) chairman’s address;
(16) letter to shareholders;
(17) ASX query;
(18) structured products; and
(19) commitments test entity quarterly reports.
Similar to Brown et al. (1999), the study measures price-sensitive disclosure (Disclosure
i
)
as the number of price-sensitive disclosures recorded by the ASX for frm i aggregated
for day d and year t.
3.3 Information asymmetry measures
Information asymmetry measures include the bid-ask spread, trading volume and price
volatility, as used in the fnancial literature (Leuz and Verrecchia, 2000).
Bid-Ask Spread – bid-ask spread is measured as the ratio of the quoted bid-ask
spread to the quoted midpoint price for day d for frm i:
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted where the weighting procedure is based on the number of
seconds the quotation exists in each interval. Glosten and Milgrom (1985) model
information asymmetry as a function of the bid-ask spread with a market maker. In
markets such as the ASX that use electronic orders instead of a market maker,
information asymmetry is also captured by the bid-ask spread (Brockman and Chung,
1999). The literature suggests that disclosure is positively associated with a lower
bid-ask spread (Healy et al., 1999; Leuz and Verrecchia, 2000). A negative association is
expected between bid-ask spread and price-sensitive disclosure under CDR.
Stock Price Volatility – Lower stock return volatility is associated with lower levels of
private information held by insiders refecting lower uncertainty associated with the
stock (French and Roll, 1986). Price volatility is measured with the standard deviation of
daily stock returns (RET_Volatility). A negative association is expected between stock
price volatility and price-sensitive disclosures.
Trading Volume – Diamond and Verrecchia (1991) showthat when investors’ beliefs
converge, trading volume in the frm’s stock increases. Easley et al. (1996) present
complementary evidence that high volume stocks have lower information-based
trading. Trading volume is measured with the natural logarithm of the share volume
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traded for frm i (Ln(Volume)). A positive association is expected between trading
volume and price-sensitive disclosures.
3.4 Empirical models
3.4.1 H1 – continuous disclosure. Disclosure Model (1) is tested jointly with information
asymmetry Model (3) using a two-stage least squares regression model (2SLS):
Disclosure
i,t
? ?
0
? ?
1
Info_Asymmetry
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
4
Issue
i,t
? ?
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Performance
i,t
? ?
6
Leverage
i,t
? ?
7
Analyst
i,t
? ?
8
Earn_Chg
i,t
?
?
?
j
Industry
i,t
? ?
i
(1)
Where:
Disclosure
i,t
?the annual number of price-sensitive frmdisclosures for frm i
for year t;
Info_Asymmetry
i,t
?the annual average of bid-ask spread, stock return volatility or
annual aggregate of trading volume for frm i;
bid-ask spread (Bid-ask spread) is measured as the ratio of the
quoted bid-ask spread to the quoted midpoint price:
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted, where the weighting procedure
is based on the number of seconds the quotation exists in each
interval, measured for frm i for day d, averaged annually;
? trading volume (Ln(Volume)) equals the natural logarithm of
the aggregate stock trading volume for frm i, measured for
year t;
? stock price volatility (RET_Volatility) equals the standard
deviation of time-weighted trade to the trade price for frmi for
day d where standard deviation ?(1/(n ?1) ?[Price ?Mean
Price]2)1/2; n ? the number of stock prices for frm i, mean
stock price ?mean stock price for frmi calculated for day d on
a time-weighted basis;
Ln(Size)
i,t
? the natural logarithm of the market value of equity computed
as ordinary shares on issue multiplied by daily stock price for
frm i at year-end t;
Issue
i,t
?the yearly change in the number of outstanding common shares,
scaled by the average total shares outstanding for years t and t ?
1;
Performance
i,t
? net proft after tax before abnormal items for year t scaled by
average total assets for years t and t ?1;
Leverage
i,t
?the total non-current liabilities for year t divided by average total
assets for years t and t ?1;
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Analyst
i,t
?analysts’ following is an indicator variable taking the value of 1 if
sell-side analysts provide a public stock recommendation (buy,
hold or sell) for the stock at fnancial year-end t;
Earn_Chg
i,t
? change in net proft after tax before abnormal items for year t
scaled by average total assets for years t and t ?1 for frmi; and
Industry
i,t
?an indicator variable equal to 1 for an ASX industry group up to
2002 and GICS classifcation after 2002, and 0 otherwise for frmi
for year t.
The dependent variable in Model (1) is the fnancial-year aggregate of frmi price-sensitive
disclosures. The independent variables in Model (1) include determinants of disclosure
measured at fnancial-year end: frm size (Size) (Lang and Lundholm, 1993); fnancing
transactions proxied by Leverage and Issue (Myers and Majluf, 1984); Analysts’
following (Analyst) (Bhushan, 1989); performance (Performance) (Lang and Lundholm,
1993); changes in performance (Earn_Chg); and industry (Clinch and Sinclair, 1987). The
variables earnings change and information asymmetry refect the evidence that when
perceived investor information asymmetry is high, a frms’ disclosure increases (Lang
and Lundholm, 1993).
3.4.2 H2 and H3 – information asymmetry and continuous disclosure parsimonious
model. The parsimonious information asymmetry Model (2) is tested using ordinary
least squares (OLS) regression. In Model (2), information asymmetry is measured on day
d ?1 and price-sensitive disclosure is measured on day d. The study also runs Model (2)
with information asymmetry measured on day d, to examine the speed of any
adjustment in the frm’s information asymmetry metrics, and found (untabulated)
weaker but qualitatively similar results.
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
k
Controls
i,d
? ?
i
(2)
Where:
Info_Asymmetry
i,d
? Information asymmetry is measured using three methods:
bid-ask spread, trading volume and stock return volatility;
daily bid-ask spread is measured as the ratio of the quoted
bid-ask spread to the quoted midpoint price.
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted, where the weighting procedure
is based on the number of seconds the quotation exists in each
interval, measured for frm i for day d, d ?1 and d ?1;
Trading volume (Ln(Volume)) equals the natural logarithmof
the daily share volume for frm i, measured for day d, d ? 1
and d ?1; and
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Stock price volatility (RET_Volatility) equals the standard
deviation of time-weighted trade to the trade price for frm i
for day d where standard deviation ? (1/(n ? 1) ?[Price ?
Mean Price]2)1/2; n ?the number of stock prices for frm i.
The dependent variable in Model (2) is the bid-ask spread, trading volume or price
volatility, measured for frm i at day d ? 1. MODEL (2) includes the number of
price-sensitive disclosures (Disclosure) for day d, and an interaction term(Disclosure
i,d
?
Info_Asymmetry
i,d
?1). Model (2) also includes day d trading volume (Ln(Volume
i,d
))
and stock return volatility (RET_Volatility
i,d
) in some estimations as control variables
because of the correlations between the market-based variables (Brown et al., 1999; Leuz
and Verrecchia, 2000).
3.4.3 H2 and H3 – information asymmetry and continuous disclosure full model.
Information asymmetry Models (3) and (4) are tested with OLS regressions. Second, to
evaluate the possibility of bias from the non-random sampling of endogenous frm
disclosure, the study tests Model (3) with Model (1) in a two-stage least squares
regression.
Info_Asymmetry
i,t
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
i
(3)
Info_Asymmetry
i,t
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
g
Disclosure
i,t
? FirmExpectationProxies
i,t
? ?
i
(4)
Where the additional variables are measured as:
MBV
i,d
? the market value of the equity for frm i using the stock price at
fnancial year-end t, divided by the accounting book value of equity
measured for frm i for year t;
E_P
i,d
?the earnings to price ratio equals the company’s reported earnings
per share before abnormal items for frm i at fnancial year-end t
divided by stock price at fnancial year-end t for frm i;
SalesGrowth
i,t
?sales growth equals the change in operating revenue for frm i for
year t scaled by the average total assets for years t and t ?1;
AssetGrowth
i,t
? asset growth equals the change in total assets for frm i for year t
scaled by average total assets for years t and t ?1;
Accrual_Chg
i,t
?the change in accruals equals the change in earnings before tax, net
interest, abnormal and signifcant items minus Cash Flow from
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Operations for frm i for year t, scaled by average total assets for
years t and t ?1;
OwnConc
i,t
? ownership concentration is the percentage of common shares on
issue held by the top 20 shareholders measured at fnancial
year-end t for frm i;
Beta
i,t
? beta is the equity beta measured as the standard deviation of
market adjusted share returns over 2 years for frm i for year t as
computed by Aspect Huntley; and
RET_Mkt
i,d
? market return is the annualized value-weighted average price return
on all stocks in the SIRCAshare price and price relatives dataset.
Information asymmetry is modeled as a function of the frm’s growth rate, performance
and information environment (Affeck-Graves et al., 2002; Brown et al., 2009). The
information environment includes frm size, leverage and investment opportunities
(Lang and Lundholm, 1993; Leuz and Verrecchia, 2000). Following Penman (1996) and
Tasker (1998), investment opportunities and growth are measured using the
market-to-book value of equity ratio (MBV), sales growth (Sales Growth) and asset
growth (Asset Growth). Expectations of earnings growth are measured using the
price-earnings ratio, inverted to earnings-price ratio (E_P) to avoid small or zero values
in the denominator (Penman, 1996). Earnings changes are included because earnings
that change may be less informative than persistent earnings (Earn_Chg). Changes in
accruals (Accruals_Chg) are defned as the change in the difference between earnings
and operating cash fows scaled by total assets. The divergence between earnings and
cash fow is linked to earnings management (Lee et al., 1999).
Finally, studies suggest that frms with volatile earnings have disclosure incentives
to reduce information asymmetry (Miller, 2002). Model (4), therefore, includes
interactions between disclosure and performance expectations measured by the
market-to-book value of equity ratio, earnings-to-price ratio and changes in earnings
and accruals as proxies for risk and growth (Disclosure ? frm performance
expectations).
Leuz and Verrecchia (2000) and Brown et al. (1999) fnd specifc information
environment associations between trading volume, frm size, stock return volatility,
market index inclusion and ownership concentration. The study therefore includes
stock beta (Beta), ownership concentration (OwnConc) and stock market return
(RET_Mkt) in some estimations of Models (3) and (4).
3.5 Descriptive statistics
Table II presents descriptive statistics for the variables in Models (1) and (3) using the
sample of all ASX-listed companies. The disclosure and frm size Ln(Size) variables
show wide variation. Leverage also varies widely between 0 and 82 per cent of average
total assets. Owner concentration varies from 13.5 per cent of ordinary stock held by
the top 20 shareholders to 96.5 per cent. The MBV minimum refects a negative book
value of equity up to a maximum value of 21.3. The mean MBV of 2.2 indicates the
average sample frm is expected to grow while a small number of frms have very high
expected future growth.
Table III presents descriptive statistics for the disclosure and information
asymmetry variables in Model (2). The daily data sample contains the largest 500
ASX-listed companies by size. Table III indicates that 90 per cent of all frm days have
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zero price-sensitive disclosures, while 9 per cent of the frmdays have one price-sensitive
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Table IV reports correlations among the variables in the disclosure Model (1).
Price-sensitive disclosure is negatively correlated with bid-ask spread consistent
with disclosure-reducing information asymmetry (Leuz and Verrecchia, 2000).
However, continuous disclosures are positively correlated with return volatility,
indicating that information may also exacerbate uncertainty (Lee et al., 1993).
Table II.
Descriptive statistics
for the variables in
models (1), (3)-(4)
Variable Mean Median SD Minimum Maximum
Disclosure 4.706 3.000 6.781 1.000 118.000
Bid-Ask Spread 5.955 3.104 8.411 0.048 75.879
Ln(Size) 17.933 17.648 2.103 10.998 25.428
Issue 0.152 0.038 0.409 ?2.000 2.000
Leverage 0.166 0.115 0.167 0.000 0.824
Performance ?0.011 0.036 0.190 ?1.955 0.663
Earn Chg 0.003 0.005 0.124 ?0.564 0.798
MBV 2.199 1.421 2.521 ?0.950 21.293
E_P ?0.008 0.040 0.192 ?1.355 0.313
Sales Growth 0.083 0.030 0.309 ?1.493 1.575
Asset Growth 0.089 0.058 0.308 ?0.963 1.328
Accrual Chg 0.002 ?0.002 0.165 ?0.733 1.015
RET_Volatility 0.013 0.011 0.011 0.000 0.176
Ln(Volume) 16.586 16.738 2.141 5.421 22.381
OwnConc 65.601 67.580 18.419 13.440 96.560
Beta 1.124 0.960 1.169 ?7.980 8.380
RET_Mkt 0.130 0.127 0.099 ?0.316 0.391
Notes: Disclosure is the number of annual price-sensitive disclosures announced by frm i to the ASX
under the Continuous Disclosure regulations for frm i Bid-Ask Spread is the annual average bid-ask
spread divided by the mid-point price computed by summing intraday quoted spreads; Ln(Size) is the
natural logarithm of the market value of equity computed as ordinary shares on issue for frm i at
fnancial year-end t multiplied by stock price at t; Issue is change in ordinary shares on issue divided by
average ordinary shares for years t and t ?1; Leverage is total non-current liabilities for year t scaled by
the average total assets for years t and t ?1; performance is net proft after tax before abnormal items
divided by average total assets for years t and t ?1; Earn_Chg is the change in net proft after tax before
abnormal items scaled by average total assets for frm i for years t and t ?1; MBV is the market value
of frm i at t divided by the book value of equity for year t; E_P is reported earnings per share before
abnormal items scaled by share price at t; Sales_Growth is the change in operating revenue scaled by the
average total assets for frmi for year t; Asset_Growth is the change in total assets scaled by the average
total assets for frm i for year t; Accrual_Chg is the change in income before tax, net interest, abnormal
items minus cash fows from operations scaled by the average total assets for frm i for year t;
RET_Volatility is the annual average standard deviation of the stock return; Log(Volume) is the natural
logarithm of annual stock volume trade for frm i; OwnConc is the shares held by the top twenty
shareholders divided by the total issued ordinary shares for year x; Beta is the monthly equity rate of
return divided by the market return index measured as deviation fromrisk free rate for the previous 20
months; RET_Mkt is the annualized value-weighted average price return on all stocks in the SIRCA
share price and price relatives dataset. All outliers deleted at 1 and 99% level except for disclosure
Ln(Size), Issue, Ln(Volume), Performance, Beta and RET mkt; sample of ASX frms based over the
period 1996-2006 comprising approximately 5,249 frm-year observations
ARJ
28,2
206
D
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Table III.
Descriptive statistics
for the measures
used to estimate
model (2) bid-ask
Variable Mean Median SD Minimum Maximum
Disclosure
i,d
0.049 0.000 0.248 0.000 13.000
Bid-Ask Spread
i,d
1.901 1.114 2.371 0.026 18.833
Ln(Volume)
i,d
10.777 11.564 3.733 0.000 19.410
RET_Volatility
i,d
0.015 0.012 0.019 0.000 5.295
Notes: Disclosure
i,d
is price-sensitive disclosure measured as the daily number of price-sensitive frm
disclosures announced by ASX for frm i for day d; Info_Asymmetry
i,d
is measured daily using three
different variables: Bid-Ask Spread, trading volume and stock return volatility; daily bid ask spread
(Bid-Ask Spread) as defned in Section 3.3 is measured as the ratio of the quoted bid-ask spread to the
quoted midpoint price and then time-weighted, where the weighting procedure is based on the number
of seconds the quotation exists in each interval, measured for frm i for day d; trading volume
(Ln(Volume)) equals the natural logarithmof the daily share volume for frmi, measured for day d; stock
price volatility (RET_Volatility) equals the standard deviation of the time-weighted trade to the trade
price for frmi and day d where standard deviation ?(1/(n ?1) ?[Price – Mean Price]2)1/2 and n ?the
number of stock prices for frmi; samples are based on the largest 500 ASX-listed frms over the period
1996-2006, selected to exclude the frm-days with zero trading, zero price volatility, and abnormally
large bid-ask spreads (where a bid or ask has no corresponding ask or bid respectively). The descriptive
statistics of model (2) comprise approximately 859,432 frm-days; pooled data for the largest 500 ASX
frms for 1996-2006, n ?859,432
Table IV.
Correlations for the
measures used to
estimate model (1)
Pearson
correlations
Spearman
correlation A B C D E F G H I
A. Disclosure 1 ?0.239 0.237 0.395 0.343 0.076 0.045 0.153 0.038
B. Bid-Ask Spread ?0.493 1 ?0.286 ?0.513 ?0.589 ?0.111 ?0.169 ?0.144 ?0.014
C. RET_Volatility 0.452 ?0.310 1 0.675 0.058 0.076 ?0.291 ?0.023 ?0.071
D. Ln(Volume) 0.532 ?0.598 0.775 1 0.509 0.083 ?0.095 0.168 ?0.009
E. Ln(Size) 0.430 ?0.882 0.160 0.463 1 0.074 0.337 0.361 0.044
F. Issue 0.145 ?0.147 0.215 0.174 0.071 1 0.008 0.090 ?0.006
G. Performance 0.065 ?0.384 ?0.256 ?0.069 0.430 ?0.040 1 0.205 0.336
H. Leverage 0.182 ?0.342 ?0.046 0.152 0.402 0.029 0.244 1 0.025
I. Earn Chg 0.074 ?0.122 ?0.082 ?0.002 0.123 0.021 0.477 0.063 1
Notes: Disclosure is the number of annual price-sensitive disclosures announced by frm i to the ASX
under the Continuous Disclosure regulations for frm i Bid-Ask Spread is the annual average bid-ask
spread divided by the mid-point price computed by summing intraday quoted spreads; RET_Volatility
is the annual average standard deviation of the stock return; Log(Volume) is the natural logarithm of
annual stock volume trade for frm i; Ln(Size) is the natural logarithm of the market value of equity
computed as ordinary shares on issue for frmi at fnancial year-end t multiplied by stock price at t; Issue
is change in ordinary shares on issue divided by average ordinary shares for years t and t ? 1;
performance is net proft after tax before abnormal items divided by average total assets for years t and
t ?1; Leverage is total non-current liabilities for year t scaled by the average total assets for years t and
t ?1; Earn_Chg is the change in net proft after tax before abnormal items scaled by average total assets
for frm i for years t and t ? 1; sample of ASX frms based over the period 1996-2006 comprising
approximately 5,249 frm year observations
207
Disclosure
and
information
asymmetry
D
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Consistent with the determinants of disclosure literature, disclosure is positively
correlated with frmsize and leverage (Myers and Majluf, 1984; Lang and Lundholm,
1993).
Table V reports correlations among the variables in the parsimonious Model (2).
The information asymmetry measures for the bid-ask spread (bid-ask spread) for day
d, d ?1 and d ?1 are all negatively correlated with price-sensitive disclosures for day
d (Disclosure), while the trading volume (Ln(Volume)) and return volatility
(RET_Volatility) measures are all positively correlated with price-sensitive disclosures
for day d.
Table VI reports correlations among the variables in the information asymmetry
Model (3).
The bid-ask spread is negatively correlated with price-sensitive disclosure, trading
volume, size, leverage and earnings price ratio, consistent with prior evidence of higher
information asymmetry for frms with lower disclosure (Welker, 1995), lower trading
volume (Leuz and Verrecchia, 2000), smaller size (Hasbrouck, 1991) and negative or
ambiguous information about performance (Brown et al., 2009; Ng et al., 2010). Trading
volume (Ln(Volume)) is positively correlated with price-sensitive disclosure and size
and leverage, consistent with lower information asymmetry for frms with more
price-sensitive disclosure and greater frm size and leverage.
4. Results
4.1 Information asymmetry and price-sensitive disclosure 2SLS tests of Models (1)
and (3)
Table VII presents the 2SLS regression results of testing Models (1) and (3) (Table VIII).
The disclosure Model (1) results give preliminary support for H1. Continuous
disclosure is positively associated with bid-ask spread; hence, frms with higher
information asymmetry are likely to increase disclosure (Lang and Lundholm, 1993).
The additional frst-stage results showcontinuous disclosure is associated with trading
volume but not with stock return volatility. Return volatility has many infuences, and
frms with high price volatility may not possess enough information to continuously
disclose, as indicated by the low median of the disclosure variable in the descriptive
statistics. Untabulated OLS regression results of testing Model (1) are consistent with
2SLS results.
The second-stage 2SLS results of using information asymmetry Model (2) are mixed
with bid-ask spread, return volatility and trading volume, all positively associated with
continuous disclosure. While the Ln(Volume
d?1
) regression result is predicted, the other
two results are unexpected. The overall effect of disclosure appears to be an increase in
information asymmetry. The literature indicates that conditioning further disclosure
tests on the frm’s level of information asymmetry or uncertainty may reconcile mixed
results (Rogers et al., 2009; Brown et al., 2009).
Table VII also shows that information asymmetry is a function of the frm’s
information environment. The results show signifcant coeffcient estimates for frm
size, leverage and growth expectations measured by the market value to book value of
equity ratio, earnings to price ratio, sales and asset growth rates (Smith and Watts, 1992;
Lang and Lundholm, 1993; Penman, 1996; Affeck-Graves et al., 2002).
ARJ
28,2
208
D
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measures used to
estimate model (2)
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209
Disclosure
and
information
asymmetry
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6
(
P
T
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Table VI.
Correlations for the
measures used to
estimate models
(3)-(4)
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ARJ
28,2
210
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
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N
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R
S
I
T
Y
A
t
2
0
:
5
3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Table VII.
Two-stage least
squares estimates of
disclosure and
information
asymmetry
disclosure model
2
S
L
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s
t
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(
c
o
n
t
i
n
u
e
d
)
211
Disclosure
and
information
asymmetry
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
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t
2
0
:
5
3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Table VII.
2
S
L
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s
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y
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8
(
c
o
n
t
i
n
u
e
d
)
ARJ
28,2
212
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
0
:
5
3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Table VII.
2
S
L
S
E
s
t
i
m
a
t
e
s
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n
f
o
a
s
y
m
m
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d
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k
S
p
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a
d
R
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T
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l
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t
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l
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y
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n
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d
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(
3
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213
Disclosure
and
information
asymmetry
D
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(
P
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4.2 Information asymmetry and continuous disclosure tests from parsimonious
Model (2)
Table IX presents results from parsimonious Model (2) which regress information
asymmetry measures on disclosure, and on interactions between disclosure and day
d ?1 information asymmetry.
In columns one and two of Table IX, bid-ask spread and trading volume are
negatively and positively associated with disclosure, respectively, consistent with H2.
In column three, stock price volatility is not associated with disclosure. Table IXfurther
reports the interaction coeffcients in Model (2). The study fnds positive and signifcant
coeffcient estimates for Disclosure
d
? Bid-AskSpread
d?1
and Disclosure
d
?
RET_Volatility
d?1
, and a negative and signifcant coeffcient estimate for Disclosure
d
?
Ln(Volume)
d?1
. The interaction effect is adverse to the disclosure effect, and is
consistent with frms of high pre-existing information asymmetry, exhibiting higher
information asymmetry after disclosure. This result is in line with increased
information asymmetry in the presence of pre-existing uncertainty surrounding frm
performance (Brown et al., 2009; Rogers et al., 2009).
4.3 Information asymmetry and continuous disclosure tests of Model (4)
Table X presents the results from Model (4), which includes interactions between
disclosure and measures of the performance expectations: MBV ratio, earnings to
price ratio and changes in earnings and accruals (Disclosure ? performance
expectations).
Table VIII.
GICS industry group
variables and their
2SLS estimates
reported below for
Disclosure model (1)
with the Bid-Ask
Spread measure of
information
asymmetry
GICS industry Coeffcient t-statistic Pr ?t
Energy 9.510 16.190 ?0.0001
Materials 1.094 2.050 0.0407
Capital_Goods ?0.189 ?0.330 0.739
Commercial_Professional_Services ?0.279 ?0.440 0.6604
Transportation 0.544 0.700 0.4867
Automobiles_Components ?0.873 ?1.030 0.3028
Consumer_Durables_Apparel ?0.903 ?1.160 0.247
Consumer_Services ?0.284 ?0.430 0.6695
Media ?1.012 ?1.560 0.1194
Retailing ?0.753 ?1.140 0.2523
Food_Staples_Retailing ?0.291 ?0.290 0.7721
Food_Beverage_Tobacco ?0.501 ?0.820 0.4101
Household_Personal_Products 0.177 0.120 0.908
Health_Care_Equipment_Services ?0.547 ?0.800 0.421
Pharmaceuticals_Biotech_Sciences 0.844 1.130 0.2584
Banks ?2.380 ?2.920 0.0035
Diversifed_Financials ?0.290 ?0.490 0.6273
Insurance ?3.354 ?3.090 0.002
Real_Estate ?0.687 ?1.120 0.2623
Software_Services 0.828 1.290 0.1971
Technology_Hardware_Equipment 0.864 1.070 0.2825
Semiconductors_and_Equipment ?0.423 ?0.140 0.8848
Telecommunication_Services 0.190 0.220 0.8269
Utilities 0.427 0.470 0.6391
ARJ
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Table Xresults showan increase in bid-ask spread when disclosure interacts with MBV
and E-P. This evidence is consistent with Table IX results that frms with more
uncertain investments and growth have information asymmetry increased by
price-sensitive disclosure. The results in Table IXalso showthat while bid-ask spread is
positively associated with earnings change as expected, the change in asymmetry is
reduced by disclosure which is consistent with H2.
The Table Xresults further confrmthat disclosure increases returnvolatility, consistent
with 2SLS regression results, but that disclosure also interacts with MBVand E-Pto reduce
volatility. Overall, the results confrmthat the effect of disclosure oninformationasymmetry
is conditional on the frm’s pre-existing asymmetry and performance expectations.
Table IX.
Information
asymmetry and
price-sensitive
disclosure tests from
parsimonious model
(2) bid-ask
Variable
Information asymmetry measures
Expected
sign
Bid-Ask
Spread
i,d?1
Expected
sign Ln(Volume)
i,d?1
Expected
sign RET_Volatility
i,d?1
Intercept 0.422 3.373 ?0.00002
203.58*** 373.63*** ?0.43
Disclosure
i,d
? ?0.063 ? 1.217 ? 0.00001
?7.80*** 27.210*** ?0.17
Bid-Ask Spread
i,d?1
? 0.774
1,145.54***
Disclosure
i,d
?Bid-Ask Spread
i,d?1
? 0.0113
3.53***
Ln(Volume)
i,d?1
? 0.659
797.92***
Disclosure
i,d
?Ln(Volume)
i,d?1
? ?0.062
?17.19***
RET_Volatility
i,d?1
? 0.330
321.05***
Disclosure
i,d
?RET_Volatility
i,d?1
? 0.163
39.05***
Ln(Volume)
i,d
0.001
179.84***
RET_Volatility
i,d
18.180
113.73***
Adjusted R
2
0.615 0.478 0.187
F-statistic 452,501 196,391 49,480
Observations 851,344 858,054 858,045
Notes: Disclosure
i,d
is price-sensitive disclosure measured as the daily number of price-sensitive frmdisclosures announced
by ASX for frm i for day d; daily bid ask spread (Bid-Ask Spread) as defned in Section 3.3 is measured as the ratio of the
quoted bid-ask spread to the quoted midpoint price and then time-weighted, where the weighting procedure is based on the
number of seconds the quotation exists in each interval, measured for frm i for day d; trading volume (Ln(Volume)) equals
the natural logarithm of the daily share volume for frm i, measured for day d; and stock price volatility (RET_Volatility)
equals the standard deviation of the time-weighted trade to the trade price for frm i and day d where standard deviation ?
(1/(n ? 1) ?[Price ? Mean Price]2)1/2 and n ? the number of stock prices for frm i. Coeffcient ? reported above
t-statistic. *** signifcant at 1%level; samples for tests of model (2) comprise the largest 500 ASX-listed frms over the period
1996-2006, selected to exclude the frm-days with zero trading, zero price volatility and abnormally large bid-ask spreads
(where a bid or ask has no corresponding ask or bid, respectively)
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
k
Controls
i,d
? ?
i
(1)
215
Disclosure
and
information
asymmetry
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To examine the association between information asymmetry and price-sensitive
disclosure at different levels of pre-existing information asymmetry, Table XI presents
the results of testing Model (2) with the data sample partitioned into deciles ranked on
day d ?1 stock return volatility.
Table X.
Information
asymmetry and
price-sensitive
disclosure tests from
model (4)
Variable
Information asymmetry measures
Expected
sign
Bid-Ask
Spread
Expected
sign RET_Volatility
Expected
sign Ln(Volume)
Intercept ? 45.300 ? ?0.016 ? 9.848
42.500*** ?11.980*** 41.840***
Disclosure ? ?0.017 ? 0.000 ? 0.077
?0.820 4.890*** 14.420***
Ln(Size) ? ?1.954 ? ?0.002 ? 0.479
?33.010*** ?27.220*** 37.620***
Leverage ? 2.642 ? 0.000 ? 0.405
4.780*** 0.390 2.800***
MBV ? ?0.113 ? 0.000 ? 0.045
?2.530** 7.940*** 3.870***
E_P ? ?8.440 ? ?0.002 ? ?1.856
?13.420*** ?2.700*** ?11.410***
Sales Growth ? ?1.138 ? 0.001 ? ?0.071
?3.970*** 1.320 ?0.950
Asset Growth ? ?1.048 ? 0.001 ? ?0.041
?3.540*** 2.620*** ?0.530
Earns Chg ? 3.283 ? ?0.005 ? 0.671
3.370*** ?3.450*** 2.640***
Accrual Chg ? 0.679 ? 0.001 ? ?0.081
0.960 1.200 ?0.440
RET_Volatility ? ?94.642 ?
?7.960***
Ln(Volume) _ ?0.535 _ 0.004
?7.420*** 52.420***
OwnConc ? 0.085 ? 0.000 ? ?0.035
16.730*** ?6.900*** ?28.480***
Beta 0.002
12.440***
RET_Mkt ?0.005
?4.330***
Disclosure ? MBV 0.022 0.000 ?0.007
3.400*** ?3.030*** ?4.060***
Disclosure ? E_P 0.847 ?0.001 ?0.085
7.270*** ?5.220*** ?2.800***
Disclosure ? EarnChg ?0.298 0.000 ?0.050
?2.080** 0.850 ?1.330
Disclosure ? Accrual_Chg 0.042 0.000 0.014
0.360 ?0.020 0.450
Adjusted R
2
0.478 0.607 0.447
(continued)
ARJ
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In column 1 of Table XI, for the lowest two deciles of price volatility aggregated,
price-sensitive disclosure is positively and signifcantly associated with bid-ask spread
at day d ? 1. For columns “2” to “9” inclusive of increasing levels of volatility,
price-sensitive disclosure is negatively associated with bid-ask spread.
Turning to the interaction results (Disclosure
d
?Bid-Ask Spread
d?1
), in deciles 1 and
2, there is a negative relation between bid-ask spread and price-sensitive disclosure.
Hence, at lower levels of pre-existing stock return volatility, the frms providing more
(less) daily price-sensitive disclosure have relatively lower (higher) information
asymmetry on day d ? 1. Higher up the volatility deciles, the conditional relation
(Disclosure
d
?Bid-Ask Spread
d?1
) becomes positive consistent with the earlier results.
That is, level of uncertainty about future performance is a likely factor in the effect of
disclosure on information asymmetry.
Table X.
Variable
Information asymmetry measures
Bid-Ask Spread RET_Volatility Ln(Volume)
F-statistic 301.44 363.04 304.41
Observations 5,249 3,980 5,249
Notes: Bid-Ask Spread is the annual average bid-ask spread divided by the mid-point price
computed by summing intraday quoted spreads; RET_Volatility is the annual average standard
deviation of the stock return; Ln(Volume) is the natural logarithm of annual stock volume trade for
frm i; Disclosure is the number of annual price-sensitive disclosures announced by frm i to the
ASX under the Continuous Disclosure regulations for frm i; Ln(Size) is the natural logarithm of the
market value of equity computed as ordinary shares on issue for frm i at fnancial year-end t
multiplied by stock price at t; Leverage is total non-current liabilities for year t scaled by the
average total assets for years t and t ?1; MBV is the market value of frm i at t divided by the book
value of equity for year t; E_P is reported earnings per share before abnormal items scaled by share
price at t; Sales_Growth is the change in operating revenue scaled by the average total assets for
frm i for year t; Asset_Growth is the change in total assets scaled by the average total assets for
frm i for year t; Earn_Chg is the change in net proft after tax before abnormal items scaled by
average total assets for frm i for years t and t ?1; Accrual_Chg is the change in income before tax,
net interest, abnormal items minus cash fows from operations scaled by the average total assets
for frm i for year t; OwnConc is the shares held by the top twenty shareholders divided by the total
issued ordinary shares for year x; Beta is the monthly equity rate of return divided by the market
return index measured as deviation from risk free rate for the previous 20 months; RET_Mkt is the
annualized value-weighted average price return on all stocks in the SIRCA share price and price
relatives dataset. Coeffcient ? reported above t-statistic. ***signifcant at 1% level; **signifcant
at 5% level; annual pooled sample of ASX listed frms for the period 1996-2006
Info_Asymmetry
i,t?1
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
g
Disclosure
i,t
? Firm Expections
i,t
? ?
i
(4)
217
Disclosure
and
information
asymmetry
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Table XI.
Estimates for
parsimonious model
(2) for deciles of
lagged stock price
volatility bid-ask
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4.3 Robustness tests
A number of tests are performed to check the robustness of the earlier results. The
parsimonious Model (2) is tested with all ASX stocks; Model (3) is regressed on
changes in information asymmetry; and, in Model (2), clustered standard errors are
adjusted. These test results are discussed below, although untabulated due to space
constraints.
The study runs parsimonious Model (2) using the full sample of all ASX-listed
companies for 1996-2006, with variables winsorized at 1 and 99 per cent percentiles to
remove outliers. The Model (2) results for all-frm sample differ in two ways from the
reported results in Table IX for the largest 500 ASX frms. The study fnds the
coeffcient for price-sensitive disclosure changes froma negative sign (as in Table IX) to
a positive sign, refecting the inclusion of frms with relatively higher level of
information asymmetry. The study also fnds the sign of the Disclosure
d
? Bid-Ask
Spread
d?1
interaction changes from positive (as in Table IX) to negative. This evidence
confrms earlier results that the pre-existing level of information asymmetry is an
important factor in tests of disclosure effects under CDR.
Second, Model (3) is run with a change of information asymmetry measure, rather
than the level of information of asymmetry, as the dependent variable. The results
show that the change of information asymmetry models has a lower adjusted
R-square than the levels of asymmetry models. Nevertheless, for changes of bid-ask
spread and trading volume, the Model (3) results are consistent with earlier results
reported in Table VII.
Third, the study examines whether there are standard error biases from clustering
effects. Following Liang and Zeger (1986) and Petersen (2009), the standard errors are
adjusted to account for a possible correlation within clusters of observations using
the Generalized Estimating Equations (GEE) approach of Liang and Zeger (1986).
For the (parsimonious) Model (2), the price-sensitive disclosure variable is no longer
signifcant. However, the interaction Disclosure ?Bid-Ask Spread is signifcant and
negative. This result is consistent with H2. The study fnds the GEE results for the
re-estimated Model (3) are the same as the results reported in Table VII using OLS
standard errors. The market-sensitive disclosure coeffcient estimate is positive and
signifcant, while the control variables remain signifcant except for MBV and the
accruals changes variables.
4.4 Additional tests
The study performs three additional tests of H2and H3using parsimonious Model (2) as
follows: coding disclosures by ASXprimary code; sampling only frmi disclosure days;
and adding disclosure interaction variables for good news and bad news.
First, the study uses ASX primary code classifcation of disclosures, described in
Section 3.2, and examines information asymmetry in Model (2). Multiple disclosure
observations were omitted from the sample, except for the periodic fnancial-report
releases commonly supplemented by procedural disclosures. In untabulated results, the
study fnds signifcant negative associations between bid-ask spread and disclosure of
periodic fnancial reports and company administration. Further, the study fnds
signifcant positive associations between bid-ask spread and takeover announcements
and issued capital disclosure. In the positive associations, the disclosure – lag
information asymmetry interaction variable is also signifcant and negative. Hence, the
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overall effect of takeover and issued capital disclosures is a function of the pre-existing
asymmetry, while periodic fnancial reports and company administration disclosures
reduce information asymmetry.
Second, the study tests Model (2) with a sample of frm i disclosure days, and uses
an indicator variable with price-sensitive disclosures taking a value of 1, and
non-price-sensitive disclosures taking the value of 0. In untabulated results, the
study fnds similar results to those of the full ASXfrmsample: a signifcant positive
association between bid-ask spread and price-sensitive disclosure and a signifcant
negative association between bid-ask spread and the interaction variable between
the lag of bid-ask spread and disclosure. The results confrm the importance of
pre-existing information asymmetry in assessing the reaction to disclosure.
Third, to Model (2), the study adds disclosure interaction variables for good and bad
news, being the market-adjusted daily stock return. Table XII reports signifcant
negative associations between bid-ask spread, disclosure and both good news and bad
news interaction variables. The results highlight evidence that, while bad news
increases bid-ask spread, the incremental effect of frmdisclosure of good and bad news
decreases information asymmetry. The results are consistent with H2 and CDR
operating as intended by regulators.
5. Conclusion
This study examines whether frms with high information asymmetry disclose more
information under the Australian Continuous Disclosure Regime (CDR), and whether
continuous disclosures reduce information asymmetry.
This study provides initial evidence under CDR that frms with high information
asymmetry disclose more information. Further, the results indicate that frms disclose
according to their economic characteristics rather than strictly following prescriptive
disclosure rules (Frost and Pownall, 1994). These results are consistent with the
argument that management retains disclosure discretion under CDR(Brown et al., 1999;
Hsu et al., 2012), nevertheless, the benefts of disclosure provide managerial incentives to
comply with the CDR.
Second, the study fnds evidence that disclosures increase information asymmetry
for frms with high information asymmetry. Those frms with high information
asymmetry are arguably the subset of frms targeted by CDR. Nevertheless, these
results are consistent with prior evidence of disclosure increasing information
asymmetry in the presence of uncertainty or high information asymmetry (Brown et al.,
2009; Rogers et al., 2009). More broadly, the effect of CDR disclosure on asymmetry
is conditional on the frm’s economic characteristics, particularly performance
expectations and growth measured by E_P and MBV ratios.
Finally, the study identifes new evidence under CDR that information
asymmetry is infuenced by the nature of the news. Although bad news creates
information asymmetry, frm-specifc good and bad news reduce the information
asymmetry. In particular, news events such as fnancial report releases and
company administration announcements are likely to reduce information
asymmetry. Overall, the results contribute a deeper understanding of the nuanced
interaction between frm disclosure and information asymmetry in the CDR
information environment.
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The results have several implications for regulators, frm disclosure practices and
investors. First, the study provides evidence that CDR is operating as intended by
the regulators to target frms with high information asymmetry. For frms
possessing information and exercising discretion, the results suggest that
frm-specifc disclosure of both good and bad news is optimal during the market
reaction to bad news. For investors, the results confrm that frm characteristics
enable investors to anticipate CDR disclosure and the effect of CDR disclosure on
information asymmetry.
Table XII.
Estimates for
parsimonious model
(2) with good news
and bad news
disclosure interaction
effects
Information asymmetry Expected sign Bid-ask spread
d?1
Intercept ? 0.374
163.150***
Disclosure
id
?/? ?0.039
?4.290***
Bid-Ask Spread
id?1
? 0.769
1115.590***
Disclosure ?Bid-Ask Spread
id?1
?/? 0.015
4.710***
Good News
id
?0.105
?0.990
Bad News
id
7.847
75.100***
Disclosure ? Good News
id
?0.861
?3.330***
Disclosure ? Bad News
id
?2.902
?10.050***
Adjusted R
2
0.618
F-statistic 195,849.0
Observations 848,566
Notes:
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
5
Good_News
i,d
? ?
6
Bad_News
i,d
? ?
7
Disclosure ? Good News
i,d
? ?
8
Disclosure ? Bad News
i,d
? ?
i
(1)
Info Asymmetry is daily bid-ask spread measured as the ratio of the quoted bid-ask spread to the quoted
midpoint price and then time-weighted, where the weighting procedure is based on the number of
seconds the quotation exists in each interval, measured for frm i for day d; Disclosure
i,d
is
price-sensitive disclosure measured as the daily number of price-sensitive frm disclosures announced
by ASXfor frmi for day d; Good News is the market-adjusted daily share return greater than zero where
the market return is the daily rate of return on the ASX All Ordinaries Index; Bad News is the absolute
market-adjusted daily share return equal to or less than zero where the market return is the daily rate of
return on the ASXAll Ordinaries Index. Coeffcient ?is reported above t-statistic; ***signifcant at 1%
level
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Verrecchia, R. (2001), “Essays on disclosure”, Journal of Accounting and Economics, Vol. 32
Nos 1/3, pp. 97-180.
Welker, M. (1995), “Disclosure policy, information asymmetry, and liquidity in equity markets”,
Contemporary Accounting Research, Vol. 11 No. 2, pp. 801-827.
Further reading
ASX (Australian Securities Exchange), Listing Rules, Australian Securities Exchange, Sydney,
available at: www.asx.com.au/regulation/rules/asx-listing-rules.htm (accessed 1 August
2015).
Verrecchia, R. (1983), “Discretionary disclosure”, Journal of Accounting and Economics, Vol. 5,
pp. 179-194.
Corresponding author
Mark Russell can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
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ARJ
28,2
224
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doc_830175467.pdf
This paper aims to examine whether firms with high information asymmetry disclose more
information under a continuous disclosure regime, and, second, the paper examines whether continuous
disclosures reduce information asymmetry.
Accounting Research Journal
Continuous disclosure and information asymmetry
Mark Russell
Article information:
To cite this document:
Mark Russell , (2015),"Continuous disclosure and information asymmetry", Accounting Research
J ournal, Vol. 28 Iss 2 pp. 195 - 224
Permanent link to this document:
http://dx.doi.org/10.1108/ARJ -11-2013-0085
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Continuous disclosure and
information asymmetry
Mark Russell
UQ Business School, The University of Queensland, St. Lucia, Australia
Abstract
Purpose – This paper aims to examine whether frms with high information asymmetry disclose more
information under a continuous disclosure regime, and, second, the paper examines whether continuous
disclosures reduce information asymmetry.
Design/methodology/approach – The study models relations between continuous disclosures and
information asymmetry using ordinary least squares regression and two-stage least squares
regression.
Findings – The study fnds frms with high information asymmetry disclose more information.
Further, the study fnds that disclosure in the presence of high information asymmetry increases
asymmetry. Finally, while bad news increases information asymmetry, the disclosure of frm-specifc
good and bad news is associated with reduced information asymmetry.
Originality/value – The paper identifes conditions under which Continuous Disclosure Regime
increases information in markets and infuences information asymmetry.
Keywords Information asymmetry, Continuous disclosure, Firm performance expectations
Paper type Research paper
1. Introduction
This paper evaluates whether frms with higher information asymmetry disclose more
information under the Australian Continuous Disclosure Regime (CDR), and second,
whether continuous disclosures reduce information asymmetry. Regulators require
continuous disclosure from companies in an expanding number of countries and stock
exchanges: Australia, Canada, New Zealand, Germany, New Zealand, Singapore, Hong
Kong Stock Exchange, London Stock Exchange, New York Stock Exchange, American
Stock Exchange and NASDAQ (Oesterle, 1998; Table I).
The study is motivated by the increased regulation of disclosure in markets to
alleviate information asymmetry. Information asymmetry leads to the ineffcient
allocation of investment resources, adverse selection, insider trading and other negative
outcomes (Lev, 1988; Verrecchia, 2001). The limited CDR studies produce mixed
empirical evidence on the effect of continuous disclosure on information asymmetry
(Brown et al., 1999; Poskitt, 2005). This CDR evidence refects the multifaceted
relation between disclosure and information asymmetry in international studies
The author is grateful for helpful comments on this paper from Pete Clarkson, Greg Clinch, Dan
Collins, Robert Czernkowski, Dan Dhaliwal, Jere Francis, Zoltan Matolcsy, Stephen Taylor, Terry
Walter, Joe Weber, Peter Wells, Anne Wyatt and participants at the AFAANZ Conference 2010 in
Christchurch, the American Accounting Association Annual Meeting 2010 in San Francisco, and
the University of Technology Sydney seminar series. The author acknowledges fnancial support
fromthe UTS School of Accounting and FIRN. Data supplied by the Securities Industry Research
Centre Asia-Pacifc on behalf of the ASX and Aspect Financial.
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1030-9616.htm
Disclosure
and
information
asymmetry
195
Received26 November 2013
Revised31 May2014
Accepted15 August 2014
Accounting Research Journal
Vol. 28 No. 2, 2015
pp. 195-224
©Emerald Group Publishing Limited
1030-9616
DOI 10.1108/ARJ-11-2013-0085
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Table I.
Comparison of
market disclosure
regulations across
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(Van Buskirk, 2012). Nevertheless, Australian CDR provides a data-rich environment to
reconcile conficting disclosure studies and clarify the unknown effects of continuous
disclosure.
The key contribution from this paper is to identify conditions under which CDR
reduces information asymmetry and increases disclosure. First, the study provides
evidence that frms with high information asymmetry disclose more information.
Second, the study indicates that disclosure in the presence of high information
asymmetry increases asymmetry. Finally, while bad news is likely to increase
information asymmetry, the disclosure of frm-specifc good and bad news is associated
with reduced information asymmetry.
The remainder of the paper is organized as follows. Section 2 reviews the Australian
setting for continuous disclosure, the background literature and develops the
hypotheses. Section 3 describes the research design, the empirical models and variables.
The results are presented in Section 4, and Section 5 fnishes the paper with conclusions.
2. Institutional background and hypothesis development
2.1 Continuous disclosure regulation
The Australian CDR commenced in September 1994 following prominent corporate
failures that involved delayed disclosure and a perceived lack of transparency in
the Australian stock market (Commonwealth Government Report of the Australian
House of Representatives Standing Committee on Legal and Constitutional Affairs,
1991). The continuous disclosure rules are contained in ASXListing Rule 3.1 as follows:
Once an entity is or becomes aware of any information concerning it that a reasonable person
would expect to have a material effect on the price or value of the entity’s securities, the entity
must immediately tell the ASX that information.
A reasonable person would be taken to expect information to have a material effect on
the price or value of securities if the information would, or would be likely to, infuence
persons who commonly invest in securities in deciding whether or not to subscribe for,
or buy or sell, the frst mentioned securities (Section 677, Corporations Act 2001 (Cth)).
Listing Rule 3.1B provides exceptions to continuous disclosure which require
confdentiality, reasonableness and one or more of the following conditions:
• a breach of law to disclose;
• an incomplete proposal or negotiation;
• matters of supposition;
• information generated for the internal management purpose; and
• the information is a trade secret.
The Australian CDR is principle-based and differs from the bright-line specifcation of
classes of information to be disclosed under other regimes. As illustrated in Table I, a
number of countries and stock exchanges have continuous disclosure regimes.
2.2 CDR and managerial disclosure incentives
Despite disclosure regulation, managers have incentives to selectively disclose
information. For example, managers disclose timely good news but delay or withhold
bad news (Kothari et al., 2009). The selective disclosure of information and CDR
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“exception” clauses have raised questions about the operation of the CDR (Cassidy and
Chapple, 2003; Hsu, 2009). Applying the CDR requires management judgment on
price-sensitivity and price discovery in at least three dimensions. First, management
must decide what information is price-sensitive and second whether information is
exempt from disclosure. Third, management must decide the content and presentation
of the information to be disclosed.
A number of studies consider the possibility that managers retain discretion in CDR
disclosure (Brown et al., 1999; Hsu, 2009; Hsu et al., 2012). It is likely that CDR operates
in line with earlier evidence that frms disclose by reference to their economic
characteristics rather than strictly following disclosure rules (Frost and Pownall, 1994).
Notwithstanding management incentives to selectively disclose, studies also suggest
that CDR increased disclosure to change the Australian information environment. Hsu
et al. (2012) study the properties of analyst forecasts under the CDR as it evolved from
1988 to 2001. Hsu et al. (2012) fnd evidence suggesting changes in analyst forecast
properties, and after 1998, forecast dispersion deteriorated for small frms. Nevertheless,
Corlett et al. (2000) suggest that CDR increased the disclosure of information. More
specifcally, Neagle and Tyskin (2001) examine regulatory activity and fnd small frms,
loss frms and some industries are more likely to receive ASX price queries. Chan et al.
(2007) and Dunstan et al. (2010) both fnd management earnings forecasts are associated
with CDR.
The discretionary content and format of disclosure available to managers under
CDR, and the conficting incentives to disclose, potentially infuence the impact of a
mandatory disclosure regime on frms. Nevertheless, the study expects the economic
benefts to the frm from increased disclosure and lower information asymmetry (Jung
and Kwon, 1988; Healy et al., 1999), and CDR compliance pressure, to give management
incentives to disclose under CDR:
H1. Firms with higher information asymmetry disclose more information under
CDR.
2.3 Implications of the continuous disclosure regime for information asymmetry
The disclosure benefts for the frm from lower information asymmetry include the
convergence of investor beliefs, stock liquidity increases and lower price volatility
(Lev, 1988). Nevertheless, higher day-to-day information asymmetry will persist for
frms with more uncertain investments, longer-term projects and transactions
(Affeck-Graves et al., 2002; Miller, 2002). Furthermore, disclosure may increase
short-term information asymmetry for many frms. For example, disclosures may be
costly for investors to process, or induce additional uncertainties and divergent opinions
(Lee et al., 1993; Krinsky and Lee, 1996; Bamber et al., 2011). Unexpectedly, disclosure
may also increase the information advantage of sophisticated investors (Indjejikian,
1991).
Australian studies are mixed on whether CDR disclosure reduces information
asymmetry (Brown et al., 1999; Poskitt, 2005). Brown et al. (1999) fnd a signifcant
association between CDR disclosure and information asymmetry but only for small
companies and for companies performing relatively poorly. However, Brown et al. (1999)
recognize data sample limitations of the 1994-1996 post-CDR data available for their
study. To study the effects of disclosure on informed trading, Poskitt (2005) uses the
probability of informed trading (PIN) model (Easley et al., 1996). He fnds no evidence
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that price-sensitive disclosures are associated with lower information based trading in
the post-2002 period.
Consistent with the economic theory of disclosure consequences in markets (Leuz
and Verrecchia, 2000), the study expects CDR disclosure to reduce information
asymmetry. Nevertheless, in line with event studies (Krinsky and Lee, 1996), the study
also expects CDRdisclosure events to conditionally increase information asymmetry for
frms with high pre-existing information asymmetry. This leads to the following
hypotheses:
H2. Price-sensitive disclosure under CDR reduces information asymmetry.
H3. Price-sensitive disclosure under CDR for frms with high information
asymmetry increases information asymmetry.
3. Empirical analysis
3.1 Sample and data
The initial sample includes all companies listed on the Australian Securities Exchange
(ASX) between 1996 and 2006 with at least one year of market trading data. The sample for
each test is determined by the model and measure of information asymmetry. Information
asymmetry is measured annually and daily. The daily measurement of information
asymmetry is affected by the large number of small frms in the ASX with thinly traded
shares andzerotradingdays. Toaddress these adverse tradingeffects, adailysub-sample is
based on the largest 500 ASX-listed frms over the period of 1996-2006, selected to exclude
the frm-days with zero trading, zero price volatility and abnormally large bid-ask spreads
(where a bid or ask has no corresponding ask or bid, respectively).
Price-sensitive disclosures come from the Securities Industry Research Centre of
Asia-Pacifc (SIRCA) signal Gdatabase. Financial andother companydata andequitybetas
are fromAspect Huntley’s Fin Analysis database. Stock price and trading data for the ASX
Securities Exchange Automated Trading System(SEATS) are fromSIRCAdatabases. The
bid-ask spreads for the ASX’s order-driven market come from SIRCA’s ASX Intra-day
database, while the daily trading volume data and prices come from SIRCA’s ASX Daily
database. Financial analyst data comes from I/B/E/S. The ASX’s industry classifcation is
used until September 2002, after which the study uses the Standard and Poor’s Global
Industry Classifcation System(GICS) as adopted by ASXin 2002.
3.2 Price-sensitive disclosure measure
The SIRCA Signal G database maintains ASX company announcements. The ASX
announcements include those labeled price-sensitive, and other regulated and voluntary
announcements. The announcements are categorized by the ASXusing 19 primary codes:
(1) takeover announcements;
(2) shareholder details;
(3) periodic reports;
(4) quarterly activities report;
(5) quarterly cash fow report;
(6) issued capital;
(7) asset acquisition and disposal;
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(8) notice of meeting;
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(12) company administration;
(13) notice of call (Contributing shares);
(14) other;
(15) chairman’s address;
(16) letter to shareholders;
(17) ASX query;
(18) structured products; and
(19) commitments test entity quarterly reports.
Similar to Brown et al. (1999), the study measures price-sensitive disclosure (Disclosure
i
)
as the number of price-sensitive disclosures recorded by the ASX for frm i aggregated
for day d and year t.
3.3 Information asymmetry measures
Information asymmetry measures include the bid-ask spread, trading volume and price
volatility, as used in the fnancial literature (Leuz and Verrecchia, 2000).
Bid-Ask Spread – bid-ask spread is measured as the ratio of the quoted bid-ask
spread to the quoted midpoint price for day d for frm i:
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted where the weighting procedure is based on the number of
seconds the quotation exists in each interval. Glosten and Milgrom (1985) model
information asymmetry as a function of the bid-ask spread with a market maker. In
markets such as the ASX that use electronic orders instead of a market maker,
information asymmetry is also captured by the bid-ask spread (Brockman and Chung,
1999). The literature suggests that disclosure is positively associated with a lower
bid-ask spread (Healy et al., 1999; Leuz and Verrecchia, 2000). A negative association is
expected between bid-ask spread and price-sensitive disclosure under CDR.
Stock Price Volatility – Lower stock return volatility is associated with lower levels of
private information held by insiders refecting lower uncertainty associated with the
stock (French and Roll, 1986). Price volatility is measured with the standard deviation of
daily stock returns (RET_Volatility). A negative association is expected between stock
price volatility and price-sensitive disclosures.
Trading Volume – Diamond and Verrecchia (1991) showthat when investors’ beliefs
converge, trading volume in the frm’s stock increases. Easley et al. (1996) present
complementary evidence that high volume stocks have lower information-based
trading. Trading volume is measured with the natural logarithm of the share volume
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traded for frm i (Ln(Volume)). A positive association is expected between trading
volume and price-sensitive disclosures.
3.4 Empirical models
3.4.1 H1 – continuous disclosure. Disclosure Model (1) is tested jointly with information
asymmetry Model (3) using a two-stage least squares regression model (2SLS):
Disclosure
i,t
? ?
0
? ?
1
Info_Asymmetry
i,t
? ?
2
Ln
(
Size
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i,t ? ?
4
Issue
i,t
? ?
5
Performance
i,t
? ?
6
Leverage
i,t
? ?
7
Analyst
i,t
? ?
8
Earn_Chg
i,t
?
?
?
j
Industry
i,t
? ?
i
(1)
Where:
Disclosure
i,t
?the annual number of price-sensitive frmdisclosures for frm i
for year t;
Info_Asymmetry
i,t
?the annual average of bid-ask spread, stock return volatility or
annual aggregate of trading volume for frm i;
bid-ask spread (Bid-ask spread) is measured as the ratio of the
quoted bid-ask spread to the quoted midpoint price:
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted, where the weighting procedure
is based on the number of seconds the quotation exists in each
interval, measured for frm i for day d, averaged annually;
? trading volume (Ln(Volume)) equals the natural logarithm of
the aggregate stock trading volume for frm i, measured for
year t;
? stock price volatility (RET_Volatility) equals the standard
deviation of time-weighted trade to the trade price for frmi for
day d where standard deviation ?(1/(n ?1) ?[Price ?Mean
Price]2)1/2; n ? the number of stock prices for frm i, mean
stock price ?mean stock price for frmi calculated for day d on
a time-weighted basis;
Ln(Size)
i,t
? the natural logarithm of the market value of equity computed
as ordinary shares on issue multiplied by daily stock price for
frm i at year-end t;
Issue
i,t
?the yearly change in the number of outstanding common shares,
scaled by the average total shares outstanding for years t and t ?
1;
Performance
i,t
? net proft after tax before abnormal items for year t scaled by
average total assets for years t and t ?1;
Leverage
i,t
?the total non-current liabilities for year t divided by average total
assets for years t and t ?1;
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Analyst
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?analysts’ following is an indicator variable taking the value of 1 if
sell-side analysts provide a public stock recommendation (buy,
hold or sell) for the stock at fnancial year-end t;
Earn_Chg
i,t
? change in net proft after tax before abnormal items for year t
scaled by average total assets for years t and t ?1 for frmi; and
Industry
i,t
?an indicator variable equal to 1 for an ASX industry group up to
2002 and GICS classifcation after 2002, and 0 otherwise for frmi
for year t.
The dependent variable in Model (1) is the fnancial-year aggregate of frmi price-sensitive
disclosures. The independent variables in Model (1) include determinants of disclosure
measured at fnancial-year end: frm size (Size) (Lang and Lundholm, 1993); fnancing
transactions proxied by Leverage and Issue (Myers and Majluf, 1984); Analysts’
following (Analyst) (Bhushan, 1989); performance (Performance) (Lang and Lundholm,
1993); changes in performance (Earn_Chg); and industry (Clinch and Sinclair, 1987). The
variables earnings change and information asymmetry refect the evidence that when
perceived investor information asymmetry is high, a frms’ disclosure increases (Lang
and Lundholm, 1993).
3.4.2 H2 and H3 – information asymmetry and continuous disclosure parsimonious
model. The parsimonious information asymmetry Model (2) is tested using ordinary
least squares (OLS) regression. In Model (2), information asymmetry is measured on day
d ?1 and price-sensitive disclosure is measured on day d. The study also runs Model (2)
with information asymmetry measured on day d, to examine the speed of any
adjustment in the frm’s information asymmetry metrics, and found (untabulated)
weaker but qualitatively similar results.
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
k
Controls
i,d
? ?
i
(2)
Where:
Info_Asymmetry
i,d
? Information asymmetry is measured using three methods:
bid-ask spread, trading volume and stock return volatility;
daily bid-ask spread is measured as the ratio of the quoted
bid-ask spread to the quoted midpoint price.
AskPrice
i,d
? BidPrice
i,d
1
2
(AskPrice
i,d
? BidPrice
i,d
)
The measure is time-weighted, where the weighting procedure
is based on the number of seconds the quotation exists in each
interval, measured for frm i for day d, d ?1 and d ?1;
Trading volume (Ln(Volume)) equals the natural logarithmof
the daily share volume for frm i, measured for day d, d ? 1
and d ?1; and
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Stock price volatility (RET_Volatility) equals the standard
deviation of time-weighted trade to the trade price for frm i
for day d where standard deviation ? (1/(n ? 1) ?[Price ?
Mean Price]2)1/2; n ?the number of stock prices for frm i.
The dependent variable in Model (2) is the bid-ask spread, trading volume or price
volatility, measured for frm i at day d ? 1. MODEL (2) includes the number of
price-sensitive disclosures (Disclosure) for day d, and an interaction term(Disclosure
i,d
?
Info_Asymmetry
i,d
?1). Model (2) also includes day d trading volume (Ln(Volume
i,d
))
and stock return volatility (RET_Volatility
i,d
) in some estimations as control variables
because of the correlations between the market-based variables (Brown et al., 1999; Leuz
and Verrecchia, 2000).
3.4.3 H2 and H3 – information asymmetry and continuous disclosure full model.
Information asymmetry Models (3) and (4) are tested with OLS regressions. Second, to
evaluate the possibility of bias from the non-random sampling of endogenous frm
disclosure, the study tests Model (3) with Model (1) in a two-stage least squares
regression.
Info_Asymmetry
i,t
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
i
(3)
Info_Asymmetry
i,t
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
g
Disclosure
i,t
? FirmExpectationProxies
i,t
? ?
i
(4)
Where the additional variables are measured as:
MBV
i,d
? the market value of the equity for frm i using the stock price at
fnancial year-end t, divided by the accounting book value of equity
measured for frm i for year t;
E_P
i,d
?the earnings to price ratio equals the company’s reported earnings
per share before abnormal items for frm i at fnancial year-end t
divided by stock price at fnancial year-end t for frm i;
SalesGrowth
i,t
?sales growth equals the change in operating revenue for frm i for
year t scaled by the average total assets for years t and t ?1;
AssetGrowth
i,t
? asset growth equals the change in total assets for frm i for year t
scaled by average total assets for years t and t ?1;
Accrual_Chg
i,t
?the change in accruals equals the change in earnings before tax, net
interest, abnormal and signifcant items minus Cash Flow from
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Operations for frm i for year t, scaled by average total assets for
years t and t ?1;
OwnConc
i,t
? ownership concentration is the percentage of common shares on
issue held by the top 20 shareholders measured at fnancial
year-end t for frm i;
Beta
i,t
? beta is the equity beta measured as the standard deviation of
market adjusted share returns over 2 years for frm i for year t as
computed by Aspect Huntley; and
RET_Mkt
i,d
? market return is the annualized value-weighted average price return
on all stocks in the SIRCAshare price and price relatives dataset.
Information asymmetry is modeled as a function of the frm’s growth rate, performance
and information environment (Affeck-Graves et al., 2002; Brown et al., 2009). The
information environment includes frm size, leverage and investment opportunities
(Lang and Lundholm, 1993; Leuz and Verrecchia, 2000). Following Penman (1996) and
Tasker (1998), investment opportunities and growth are measured using the
market-to-book value of equity ratio (MBV), sales growth (Sales Growth) and asset
growth (Asset Growth). Expectations of earnings growth are measured using the
price-earnings ratio, inverted to earnings-price ratio (E_P) to avoid small or zero values
in the denominator (Penman, 1996). Earnings changes are included because earnings
that change may be less informative than persistent earnings (Earn_Chg). Changes in
accruals (Accruals_Chg) are defned as the change in the difference between earnings
and operating cash fows scaled by total assets. The divergence between earnings and
cash fow is linked to earnings management (Lee et al., 1999).
Finally, studies suggest that frms with volatile earnings have disclosure incentives
to reduce information asymmetry (Miller, 2002). Model (4), therefore, includes
interactions between disclosure and performance expectations measured by the
market-to-book value of equity ratio, earnings-to-price ratio and changes in earnings
and accruals as proxies for risk and growth (Disclosure ? frm performance
expectations).
Leuz and Verrecchia (2000) and Brown et al. (1999) fnd specifc information
environment associations between trading volume, frm size, stock return volatility,
market index inclusion and ownership concentration. The study therefore includes
stock beta (Beta), ownership concentration (OwnConc) and stock market return
(RET_Mkt) in some estimations of Models (3) and (4).
3.5 Descriptive statistics
Table II presents descriptive statistics for the variables in Models (1) and (3) using the
sample of all ASX-listed companies. The disclosure and frm size Ln(Size) variables
show wide variation. Leverage also varies widely between 0 and 82 per cent of average
total assets. Owner concentration varies from 13.5 per cent of ordinary stock held by
the top 20 shareholders to 96.5 per cent. The MBV minimum refects a negative book
value of equity up to a maximum value of 21.3. The mean MBV of 2.2 indicates the
average sample frm is expected to grow while a small number of frms have very high
expected future growth.
Table III presents descriptive statistics for the disclosure and information
asymmetry variables in Model (2). The daily data sample contains the largest 500
ASX-listed companies by size. Table III indicates that 90 per cent of all frm days have
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zero price-sensitive disclosures, while 9 per cent of the frmdays have one price-sensitive
disclosure.
Table IV reports correlations among the variables in the disclosure Model (1).
Price-sensitive disclosure is negatively correlated with bid-ask spread consistent
with disclosure-reducing information asymmetry (Leuz and Verrecchia, 2000).
However, continuous disclosures are positively correlated with return volatility,
indicating that information may also exacerbate uncertainty (Lee et al., 1993).
Table II.
Descriptive statistics
for the variables in
models (1), (3)-(4)
Variable Mean Median SD Minimum Maximum
Disclosure 4.706 3.000 6.781 1.000 118.000
Bid-Ask Spread 5.955 3.104 8.411 0.048 75.879
Ln(Size) 17.933 17.648 2.103 10.998 25.428
Issue 0.152 0.038 0.409 ?2.000 2.000
Leverage 0.166 0.115 0.167 0.000 0.824
Performance ?0.011 0.036 0.190 ?1.955 0.663
Earn Chg 0.003 0.005 0.124 ?0.564 0.798
MBV 2.199 1.421 2.521 ?0.950 21.293
E_P ?0.008 0.040 0.192 ?1.355 0.313
Sales Growth 0.083 0.030 0.309 ?1.493 1.575
Asset Growth 0.089 0.058 0.308 ?0.963 1.328
Accrual Chg 0.002 ?0.002 0.165 ?0.733 1.015
RET_Volatility 0.013 0.011 0.011 0.000 0.176
Ln(Volume) 16.586 16.738 2.141 5.421 22.381
OwnConc 65.601 67.580 18.419 13.440 96.560
Beta 1.124 0.960 1.169 ?7.980 8.380
RET_Mkt 0.130 0.127 0.099 ?0.316 0.391
Notes: Disclosure is the number of annual price-sensitive disclosures announced by frm i to the ASX
under the Continuous Disclosure regulations for frm i Bid-Ask Spread is the annual average bid-ask
spread divided by the mid-point price computed by summing intraday quoted spreads; Ln(Size) is the
natural logarithm of the market value of equity computed as ordinary shares on issue for frm i at
fnancial year-end t multiplied by stock price at t; Issue is change in ordinary shares on issue divided by
average ordinary shares for years t and t ?1; Leverage is total non-current liabilities for year t scaled by
the average total assets for years t and t ?1; performance is net proft after tax before abnormal items
divided by average total assets for years t and t ?1; Earn_Chg is the change in net proft after tax before
abnormal items scaled by average total assets for frm i for years t and t ?1; MBV is the market value
of frm i at t divided by the book value of equity for year t; E_P is reported earnings per share before
abnormal items scaled by share price at t; Sales_Growth is the change in operating revenue scaled by the
average total assets for frmi for year t; Asset_Growth is the change in total assets scaled by the average
total assets for frm i for year t; Accrual_Chg is the change in income before tax, net interest, abnormal
items minus cash fows from operations scaled by the average total assets for frm i for year t;
RET_Volatility is the annual average standard deviation of the stock return; Log(Volume) is the natural
logarithm of annual stock volume trade for frm i; OwnConc is the shares held by the top twenty
shareholders divided by the total issued ordinary shares for year x; Beta is the monthly equity rate of
return divided by the market return index measured as deviation fromrisk free rate for the previous 20
months; RET_Mkt is the annualized value-weighted average price return on all stocks in the SIRCA
share price and price relatives dataset. All outliers deleted at 1 and 99% level except for disclosure
Ln(Size), Issue, Ln(Volume), Performance, Beta and RET mkt; sample of ASX frms based over the
period 1996-2006 comprising approximately 5,249 frm-year observations
ARJ
28,2
206
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(
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Table III.
Descriptive statistics
for the measures
used to estimate
model (2) bid-ask
Variable Mean Median SD Minimum Maximum
Disclosure
i,d
0.049 0.000 0.248 0.000 13.000
Bid-Ask Spread
i,d
1.901 1.114 2.371 0.026 18.833
Ln(Volume)
i,d
10.777 11.564 3.733 0.000 19.410
RET_Volatility
i,d
0.015 0.012 0.019 0.000 5.295
Notes: Disclosure
i,d
is price-sensitive disclosure measured as the daily number of price-sensitive frm
disclosures announced by ASX for frm i for day d; Info_Asymmetry
i,d
is measured daily using three
different variables: Bid-Ask Spread, trading volume and stock return volatility; daily bid ask spread
(Bid-Ask Spread) as defned in Section 3.3 is measured as the ratio of the quoted bid-ask spread to the
quoted midpoint price and then time-weighted, where the weighting procedure is based on the number
of seconds the quotation exists in each interval, measured for frm i for day d; trading volume
(Ln(Volume)) equals the natural logarithmof the daily share volume for frmi, measured for day d; stock
price volatility (RET_Volatility) equals the standard deviation of the time-weighted trade to the trade
price for frmi and day d where standard deviation ?(1/(n ?1) ?[Price – Mean Price]2)1/2 and n ?the
number of stock prices for frmi; samples are based on the largest 500 ASX-listed frms over the period
1996-2006, selected to exclude the frm-days with zero trading, zero price volatility, and abnormally
large bid-ask spreads (where a bid or ask has no corresponding ask or bid respectively). The descriptive
statistics of model (2) comprise approximately 859,432 frm-days; pooled data for the largest 500 ASX
frms for 1996-2006, n ?859,432
Table IV.
Correlations for the
measures used to
estimate model (1)
Pearson
correlations
Spearman
correlation A B C D E F G H I
A. Disclosure 1 ?0.239 0.237 0.395 0.343 0.076 0.045 0.153 0.038
B. Bid-Ask Spread ?0.493 1 ?0.286 ?0.513 ?0.589 ?0.111 ?0.169 ?0.144 ?0.014
C. RET_Volatility 0.452 ?0.310 1 0.675 0.058 0.076 ?0.291 ?0.023 ?0.071
D. Ln(Volume) 0.532 ?0.598 0.775 1 0.509 0.083 ?0.095 0.168 ?0.009
E. Ln(Size) 0.430 ?0.882 0.160 0.463 1 0.074 0.337 0.361 0.044
F. Issue 0.145 ?0.147 0.215 0.174 0.071 1 0.008 0.090 ?0.006
G. Performance 0.065 ?0.384 ?0.256 ?0.069 0.430 ?0.040 1 0.205 0.336
H. Leverage 0.182 ?0.342 ?0.046 0.152 0.402 0.029 0.244 1 0.025
I. Earn Chg 0.074 ?0.122 ?0.082 ?0.002 0.123 0.021 0.477 0.063 1
Notes: Disclosure is the number of annual price-sensitive disclosures announced by frm i to the ASX
under the Continuous Disclosure regulations for frm i Bid-Ask Spread is the annual average bid-ask
spread divided by the mid-point price computed by summing intraday quoted spreads; RET_Volatility
is the annual average standard deviation of the stock return; Log(Volume) is the natural logarithm of
annual stock volume trade for frm i; Ln(Size) is the natural logarithm of the market value of equity
computed as ordinary shares on issue for frmi at fnancial year-end t multiplied by stock price at t; Issue
is change in ordinary shares on issue divided by average ordinary shares for years t and t ? 1;
performance is net proft after tax before abnormal items divided by average total assets for years t and
t ?1; Leverage is total non-current liabilities for year t scaled by the average total assets for years t and
t ?1; Earn_Chg is the change in net proft after tax before abnormal items scaled by average total assets
for frm i for years t and t ? 1; sample of ASX frms based over the period 1996-2006 comprising
approximately 5,249 frm year observations
207
Disclosure
and
information
asymmetry
D
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Consistent with the determinants of disclosure literature, disclosure is positively
correlated with frmsize and leverage (Myers and Majluf, 1984; Lang and Lundholm,
1993).
Table V reports correlations among the variables in the parsimonious Model (2).
The information asymmetry measures for the bid-ask spread (bid-ask spread) for day
d, d ?1 and d ?1 are all negatively correlated with price-sensitive disclosures for day
d (Disclosure), while the trading volume (Ln(Volume)) and return volatility
(RET_Volatility) measures are all positively correlated with price-sensitive disclosures
for day d.
Table VI reports correlations among the variables in the information asymmetry
Model (3).
The bid-ask spread is negatively correlated with price-sensitive disclosure, trading
volume, size, leverage and earnings price ratio, consistent with prior evidence of higher
information asymmetry for frms with lower disclosure (Welker, 1995), lower trading
volume (Leuz and Verrecchia, 2000), smaller size (Hasbrouck, 1991) and negative or
ambiguous information about performance (Brown et al., 2009; Ng et al., 2010). Trading
volume (Ln(Volume)) is positively correlated with price-sensitive disclosure and size
and leverage, consistent with lower information asymmetry for frms with more
price-sensitive disclosure and greater frm size and leverage.
4. Results
4.1 Information asymmetry and price-sensitive disclosure 2SLS tests of Models (1)
and (3)
Table VII presents the 2SLS regression results of testing Models (1) and (3) (Table VIII).
The disclosure Model (1) results give preliminary support for H1. Continuous
disclosure is positively associated with bid-ask spread; hence, frms with higher
information asymmetry are likely to increase disclosure (Lang and Lundholm, 1993).
The additional frst-stage results showcontinuous disclosure is associated with trading
volume but not with stock return volatility. Return volatility has many infuences, and
frms with high price volatility may not possess enough information to continuously
disclose, as indicated by the low median of the disclosure variable in the descriptive
statistics. Untabulated OLS regression results of testing Model (1) are consistent with
2SLS results.
The second-stage 2SLS results of using information asymmetry Model (2) are mixed
with bid-ask spread, return volatility and trading volume, all positively associated with
continuous disclosure. While the Ln(Volume
d?1
) regression result is predicted, the other
two results are unexpected. The overall effect of disclosure appears to be an increase in
information asymmetry. The literature indicates that conditioning further disclosure
tests on the frm’s level of information asymmetry or uncertainty may reconcile mixed
results (Rogers et al., 2009; Brown et al., 2009).
Table VII also shows that information asymmetry is a function of the frm’s
information environment. The results show signifcant coeffcient estimates for frm
size, leverage and growth expectations measured by the market value to book value of
equity ratio, earnings to price ratio, sales and asset growth rates (Smith and Watts, 1992;
Lang and Lundholm, 1993; Penman, 1996; Affeck-Graves et al., 2002).
ARJ
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208
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Disclosure
and
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asymmetry
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Table VI.
Correlations for the
measures used to
estimate models
(3)-(4)
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ARJ
28,2
210
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
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N
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R
S
I
T
Y
A
t
2
0
:
5
3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Table VII.
Two-stage least
squares estimates of
disclosure and
information
asymmetry
disclosure model
2
S
L
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(
c
o
n
t
i
n
u
e
d
)
211
Disclosure
and
information
asymmetry
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
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R
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2
0
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3
2
4
J
a
n
u
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2
0
1
6
(
P
T
)
Table VII.
2
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(
c
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t
i
n
u
e
d
)
ARJ
28,2
212
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
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N
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S
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t
2
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3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Table VII.
2
S
L
S
E
s
t
i
m
a
t
e
s
I
n
f
o
a
s
y
m
m
e
t
r
y
B
i
d
-
A
s
k
S
p
r
e
a
d
R
E
T
_
V
o
l
a
t
i
l
i
t
y
L
n
(
V
o
l
u
m
e
)
D
e
p
e
n
d
e
n
t
v
a
r
i
a
b
l
e
D
i
s
c
l
o
s
u
r
e
B
i
d
-
A
s
k
S
p
r
e
a
d
D
i
s
c
l
o
s
u
r
e
R
E
T
_
V
o
l
a
t
i
l
i
t
y
D
i
s
c
l
o
s
u
r
e
L
n
(
V
o
l
u
m
e
)
F
-
s
t
a
t
i
s
t
i
c
5
7
.
4
6
3
2
1
.
3
3
4
8
.
6
8
4
2
7
.
7
7
5
8
.
6
8
0
3
.
2
7
O
b
s
e
r
v
a
t
i
o
n
s
4
,
5
9
4
4
,
5
9
4
3
,
7
2
6
3
,
7
2
6
4
,
5
9
4
4
,
5
9
4
N
o
t
e
s
:
D
i
s
c
l
o
s
u
r
e
i
s
t
h
e
n
u
m
b
e
r
o
f
a
n
n
u
a
l
p
r
i
c
e
-
s
e
n
s
i
t
i
v
e
d
i
s
c
l
o
s
u
r
e
s
a
n
n
o
u
n
c
e
d
b
y
f
r
m
i
t
o
t
h
e
A
S
X
u
n
d
e
r
t
h
e
C
o
n
t
i
n
u
o
u
s
D
i
s
c
l
o
s
u
r
e
r
e
g
u
l
a
t
i
o
n
s
f
o
r
f
r
m
i
B
i
d
-
A
s
k
S
p
r
e
a
d
i
s
t
h
e
a
n
n
u
a
l
a
v
e
r
a
g
e
b
i
d
-
a
s
k
s
p
r
e
a
d
d
i
v
i
d
e
d
b
y
t
h
e
m
i
d
-
p
o
i
n
t
p
r
i
c
e
c
o
m
p
u
t
e
d
b
y
s
u
m
m
i
n
g
i
n
t
r
a
d
a
y
q
u
o
t
e
d
s
p
r
e
a
d
s
;
R
E
T
_
V
o
l
a
t
i
l
i
t
y
i
s
t
h
e
a
n
n
u
a
l
a
v
e
r
a
g
e
s
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
o
f
t
h
e
s
t
o
c
k
r
e
t
u
r
n
;
L
n
(
V
o
l
u
m
e
)
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
a
n
n
u
a
l
s
t
o
c
k
v
o
l
u
m
e
t
r
a
d
e
f
o
r
f
r
m
i
;
I
s
s
u
e
i
s
c
h
a
n
g
e
i
n
o
r
d
i
n
a
r
y
s
h
a
r
e
s
o
n
i
s
s
u
e
d
i
v
i
d
e
d
b
y
a
v
e
r
a
g
e
o
r
d
i
n
a
r
y
s
h
a
r
e
s
f
o
r
y
e
a
r
s
t
a
n
d
t
?
1
;
P
e
r
f
o
r
m
a
n
c
e
i
s
n
e
t
p
r
o
f
t
a
f
t
e
r
t
a
x
b
e
f
o
r
e
a
b
n
o
r
m
a
l
i
t
e
m
s
d
i
v
i
d
e
d
b
y
a
v
e
r
a
g
e
t
o
t
a
l
a
s
s
e
t
s
f
o
r
y
e
a
r
s
t
a
n
d
t
?
1
;
A
n
a
l
y
s
t
i
s
a
n
i
n
d
i
c
a
t
o
r
v
a
r
i
a
b
l
e
t
a
k
i
n
g
t
h
e
v
a
l
u
e
o
f
1
i
f
s
e
l
l
-
s
i
d
e
a
n
a
l
y
s
t
s
p
r
o
v
i
d
e
a
p
u
b
l
i
c
s
t
o
c
k
r
e
c
o
m
m
e
n
d
a
t
i
o
n
(
b
u
y
,
h
o
l
d
o
r
s
e
l
l
)
f
o
r
t
h
e
s
t
o
c
k
a
t
f
n
a
n
c
i
a
l
y
e
a
r
-
e
n
d
t
,
a
n
d
t
a
k
i
n
g
t
h
e
v
a
l
u
e
o
f
0
o
t
h
e
r
w
i
s
e
;
L
n
(
S
i
z
e
)
i
s
t
h
e
n
a
t
u
r
a
l
l
o
g
a
r
i
t
h
m
o
f
t
h
e
m
a
r
k
e
t
v
a
l
u
e
o
f
e
q
u
i
t
y
c
o
m
p
u
t
e
d
a
s
o
r
d
i
n
a
r
y
s
h
a
r
e
s
o
n
i
s
s
u
e
f
o
r
f
r
m
i
a
t
f
n
a
n
c
i
a
l
y
e
a
r
-
e
n
d
t
m
u
l
t
i
p
l
i
e
d
b
y
s
t
o
c
k
p
r
i
c
e
a
t
t
;
L
e
v
e
r
a
g
e
i
s
t
o
t
a
l
n
o
n
-
c
u
r
r
e
n
t
l
i
a
b
i
l
i
t
i
e
s
f
o
r
y
e
a
r
t
s
c
a
l
e
d
b
y
t
h
e
a
v
e
r
a
g
e
t
o
t
a
l
a
s
s
e
t
s
f
o
r
y
e
a
r
s
t
a
n
d
t
?
1
;
M
B
V
i
s
t
h
e
m
a
r
k
e
t
v
a
l
u
e
o
f
f
r
m
i
a
t
t
d
i
v
i
d
e
d
b
y
t
h
e
b
o
o
k
v
a
l
u
e
o
f
e
q
u
i
t
y
f
o
r
y
e
a
r
t
;
E
_
P
i
s
r
e
p
o
r
t
e
d
e
a
r
n
i
n
g
s
p
e
r
s
h
a
r
e
b
e
f
o
r
e
a
b
n
o
r
m
a
l
i
t
e
m
s
s
c
a
l
e
d
b
y
s
h
a
r
e
p
r
i
c
e
a
t
t
;
S
a
l
e
s
_
G
r
o
w
t
h
i
s
t
h
e
c
h
a
n
g
e
i
n
o
p
e
r
a
t
i
n
g
r
e
v
e
n
u
e
s
c
a
l
e
d
b
y
t
h
e
a
v
e
r
a
g
e
t
o
t
a
l
a
s
s
e
t
s
f
o
r
f
r
m
i
f
o
r
y
e
a
r
t
;
A
s
s
e
t
_
G
r
o
w
t
h
i
s
t
h
e
c
h
a
n
g
e
i
n
t
o
t
a
l
a
s
s
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t
s
s
c
a
l
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d
b
y
t
h
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a
v
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a
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t
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t
a
l
a
s
s
e
t
s
f
o
r
f
r
m
i
f
o
r
y
e
a
r
t
;
E
a
r
n
_
C
h
g
i
s
t
h
e
c
h
a
n
g
e
i
n
n
e
t
p
r
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f
t
a
f
t
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r
t
a
x
b
e
f
o
r
e
a
b
n
o
r
m
a
l
i
t
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m
s
s
c
a
l
e
d
b
y
a
v
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r
a
g
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t
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a
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a
s
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s
f
o
r
f
r
m
i
f
o
r
y
e
a
r
s
t
a
n
d
t
?
1
;
A
c
c
r
u
a
l
_
C
h
g
i
s
t
h
e
c
h
a
n
g
e
i
n
i
n
c
o
m
e
b
e
f
o
r
e
t
a
x
,
n
e
t
i
n
t
e
r
e
s
t
,
a
b
n
o
r
m
a
l
i
t
e
m
s
m
i
n
u
s
c
a
s
h
f
o
w
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f
r
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m
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p
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r
a
t
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o
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s
s
c
a
l
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d
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a
v
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t
a
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a
s
s
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t
s
f
o
r
f
r
m
i
f
o
r
y
e
a
r
t
;
O
w
n
C
o
n
c
i
s
t
h
e
s
h
a
r
e
s
h
e
l
d
b
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p
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w
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d
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d
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d
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r
d
i
n
a
r
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s
h
a
r
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s
f
o
r
y
e
a
r
x
;
B
e
t
a
i
s
t
h
e
m
o
n
t
h
l
y
e
q
u
i
t
y
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r
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d
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d
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a
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p
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v
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o
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s
2
0
m
o
n
t
h
s
;
R
E
T
_
M
k
t
i
s
t
h
e
a
n
n
u
a
l
i
z
e
d
v
a
l
u
e
-
w
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g
h
t
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d
a
v
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r
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p
r
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c
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t
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r
n
o
n
a
l
l
s
t
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c
k
s
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n
t
h
e
S
I
R
C
A
s
h
a
r
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p
r
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c
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a
n
d
p
r
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c
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l
a
t
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v
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s
d
a
t
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s
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t
.
C
o
e
f
f
c
i
e
n
t
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r
e
p
o
r
t
e
d
a
b
o
v
e
t
-
s
t
a
t
i
s
t
i
c
;
*
*
*
s
i
g
n
i
f
c
a
n
t
a
t
1
%
l
e
v
e
l
;
*
*
s
i
g
n
i
f
c
a
n
t
a
t
5
%
l
e
v
e
l
.
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n
d
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s
t
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d
u
m
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y
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a
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2
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d
;
a
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a
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D
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(
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9
A
c
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0
R
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T
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t
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1
L
n
(
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o
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4
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(
3
)
213
Disclosure
and
information
asymmetry
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4.2 Information asymmetry and continuous disclosure tests from parsimonious
Model (2)
Table IX presents results from parsimonious Model (2) which regress information
asymmetry measures on disclosure, and on interactions between disclosure and day
d ?1 information asymmetry.
In columns one and two of Table IX, bid-ask spread and trading volume are
negatively and positively associated with disclosure, respectively, consistent with H2.
In column three, stock price volatility is not associated with disclosure. Table IXfurther
reports the interaction coeffcients in Model (2). The study fnds positive and signifcant
coeffcient estimates for Disclosure
d
? Bid-AskSpread
d?1
and Disclosure
d
?
RET_Volatility
d?1
, and a negative and signifcant coeffcient estimate for Disclosure
d
?
Ln(Volume)
d?1
. The interaction effect is adverse to the disclosure effect, and is
consistent with frms of high pre-existing information asymmetry, exhibiting higher
information asymmetry after disclosure. This result is in line with increased
information asymmetry in the presence of pre-existing uncertainty surrounding frm
performance (Brown et al., 2009; Rogers et al., 2009).
4.3 Information asymmetry and continuous disclosure tests of Model (4)
Table X presents the results from Model (4), which includes interactions between
disclosure and measures of the performance expectations: MBV ratio, earnings to
price ratio and changes in earnings and accruals (Disclosure ? performance
expectations).
Table VIII.
GICS industry group
variables and their
2SLS estimates
reported below for
Disclosure model (1)
with the Bid-Ask
Spread measure of
information
asymmetry
GICS industry Coeffcient t-statistic Pr ?t
Energy 9.510 16.190 ?0.0001
Materials 1.094 2.050 0.0407
Capital_Goods ?0.189 ?0.330 0.739
Commercial_Professional_Services ?0.279 ?0.440 0.6604
Transportation 0.544 0.700 0.4867
Automobiles_Components ?0.873 ?1.030 0.3028
Consumer_Durables_Apparel ?0.903 ?1.160 0.247
Consumer_Services ?0.284 ?0.430 0.6695
Media ?1.012 ?1.560 0.1194
Retailing ?0.753 ?1.140 0.2523
Food_Staples_Retailing ?0.291 ?0.290 0.7721
Food_Beverage_Tobacco ?0.501 ?0.820 0.4101
Household_Personal_Products 0.177 0.120 0.908
Health_Care_Equipment_Services ?0.547 ?0.800 0.421
Pharmaceuticals_Biotech_Sciences 0.844 1.130 0.2584
Banks ?2.380 ?2.920 0.0035
Diversifed_Financials ?0.290 ?0.490 0.6273
Insurance ?3.354 ?3.090 0.002
Real_Estate ?0.687 ?1.120 0.2623
Software_Services 0.828 1.290 0.1971
Technology_Hardware_Equipment 0.864 1.070 0.2825
Semiconductors_and_Equipment ?0.423 ?0.140 0.8848
Telecommunication_Services 0.190 0.220 0.8269
Utilities 0.427 0.470 0.6391
ARJ
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Table Xresults showan increase in bid-ask spread when disclosure interacts with MBV
and E-P. This evidence is consistent with Table IX results that frms with more
uncertain investments and growth have information asymmetry increased by
price-sensitive disclosure. The results in Table IXalso showthat while bid-ask spread is
positively associated with earnings change as expected, the change in asymmetry is
reduced by disclosure which is consistent with H2.
The Table Xresults further confrmthat disclosure increases returnvolatility, consistent
with 2SLS regression results, but that disclosure also interacts with MBVand E-Pto reduce
volatility. Overall, the results confrmthat the effect of disclosure oninformationasymmetry
is conditional on the frm’s pre-existing asymmetry and performance expectations.
Table IX.
Information
asymmetry and
price-sensitive
disclosure tests from
parsimonious model
(2) bid-ask
Variable
Information asymmetry measures
Expected
sign
Bid-Ask
Spread
i,d?1
Expected
sign Ln(Volume)
i,d?1
Expected
sign RET_Volatility
i,d?1
Intercept 0.422 3.373 ?0.00002
203.58*** 373.63*** ?0.43
Disclosure
i,d
? ?0.063 ? 1.217 ? 0.00001
?7.80*** 27.210*** ?0.17
Bid-Ask Spread
i,d?1
? 0.774
1,145.54***
Disclosure
i,d
?Bid-Ask Spread
i,d?1
? 0.0113
3.53***
Ln(Volume)
i,d?1
? 0.659
797.92***
Disclosure
i,d
?Ln(Volume)
i,d?1
? ?0.062
?17.19***
RET_Volatility
i,d?1
? 0.330
321.05***
Disclosure
i,d
?RET_Volatility
i,d?1
? 0.163
39.05***
Ln(Volume)
i,d
0.001
179.84***
RET_Volatility
i,d
18.180
113.73***
Adjusted R
2
0.615 0.478 0.187
F-statistic 452,501 196,391 49,480
Observations 851,344 858,054 858,045
Notes: Disclosure
i,d
is price-sensitive disclosure measured as the daily number of price-sensitive frmdisclosures announced
by ASX for frm i for day d; daily bid ask spread (Bid-Ask Spread) as defned in Section 3.3 is measured as the ratio of the
quoted bid-ask spread to the quoted midpoint price and then time-weighted, where the weighting procedure is based on the
number of seconds the quotation exists in each interval, measured for frm i for day d; trading volume (Ln(Volume)) equals
the natural logarithm of the daily share volume for frm i, measured for day d; and stock price volatility (RET_Volatility)
equals the standard deviation of the time-weighted trade to the trade price for frm i and day d where standard deviation ?
(1/(n ? 1) ?[Price ? Mean Price]2)1/2 and n ? the number of stock prices for frm i. Coeffcient ? reported above
t-statistic. *** signifcant at 1%level; samples for tests of model (2) comprise the largest 500 ASX-listed frms over the period
1996-2006, selected to exclude the frm-days with zero trading, zero price volatility and abnormally large bid-ask spreads
(where a bid or ask has no corresponding ask or bid, respectively)
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
k
Controls
i,d
? ?
i
(1)
215
Disclosure
and
information
asymmetry
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To examine the association between information asymmetry and price-sensitive
disclosure at different levels of pre-existing information asymmetry, Table XI presents
the results of testing Model (2) with the data sample partitioned into deciles ranked on
day d ?1 stock return volatility.
Table X.
Information
asymmetry and
price-sensitive
disclosure tests from
model (4)
Variable
Information asymmetry measures
Expected
sign
Bid-Ask
Spread
Expected
sign RET_Volatility
Expected
sign Ln(Volume)
Intercept ? 45.300 ? ?0.016 ? 9.848
42.500*** ?11.980*** 41.840***
Disclosure ? ?0.017 ? 0.000 ? 0.077
?0.820 4.890*** 14.420***
Ln(Size) ? ?1.954 ? ?0.002 ? 0.479
?33.010*** ?27.220*** 37.620***
Leverage ? 2.642 ? 0.000 ? 0.405
4.780*** 0.390 2.800***
MBV ? ?0.113 ? 0.000 ? 0.045
?2.530** 7.940*** 3.870***
E_P ? ?8.440 ? ?0.002 ? ?1.856
?13.420*** ?2.700*** ?11.410***
Sales Growth ? ?1.138 ? 0.001 ? ?0.071
?3.970*** 1.320 ?0.950
Asset Growth ? ?1.048 ? 0.001 ? ?0.041
?3.540*** 2.620*** ?0.530
Earns Chg ? 3.283 ? ?0.005 ? 0.671
3.370*** ?3.450*** 2.640***
Accrual Chg ? 0.679 ? 0.001 ? ?0.081
0.960 1.200 ?0.440
RET_Volatility ? ?94.642 ?
?7.960***
Ln(Volume) _ ?0.535 _ 0.004
?7.420*** 52.420***
OwnConc ? 0.085 ? 0.000 ? ?0.035
16.730*** ?6.900*** ?28.480***
Beta 0.002
12.440***
RET_Mkt ?0.005
?4.330***
Disclosure ? MBV 0.022 0.000 ?0.007
3.400*** ?3.030*** ?4.060***
Disclosure ? E_P 0.847 ?0.001 ?0.085
7.270*** ?5.220*** ?2.800***
Disclosure ? EarnChg ?0.298 0.000 ?0.050
?2.080** 0.850 ?1.330
Disclosure ? Accrual_Chg 0.042 0.000 0.014
0.360 ?0.020 0.450
Adjusted R
2
0.478 0.607 0.447
(continued)
ARJ
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In column 1 of Table XI, for the lowest two deciles of price volatility aggregated,
price-sensitive disclosure is positively and signifcantly associated with bid-ask spread
at day d ? 1. For columns “2” to “9” inclusive of increasing levels of volatility,
price-sensitive disclosure is negatively associated with bid-ask spread.
Turning to the interaction results (Disclosure
d
?Bid-Ask Spread
d?1
), in deciles 1 and
2, there is a negative relation between bid-ask spread and price-sensitive disclosure.
Hence, at lower levels of pre-existing stock return volatility, the frms providing more
(less) daily price-sensitive disclosure have relatively lower (higher) information
asymmetry on day d ? 1. Higher up the volatility deciles, the conditional relation
(Disclosure
d
?Bid-Ask Spread
d?1
) becomes positive consistent with the earlier results.
That is, level of uncertainty about future performance is a likely factor in the effect of
disclosure on information asymmetry.
Table X.
Variable
Information asymmetry measures
Bid-Ask Spread RET_Volatility Ln(Volume)
F-statistic 301.44 363.04 304.41
Observations 5,249 3,980 5,249
Notes: Bid-Ask Spread is the annual average bid-ask spread divided by the mid-point price
computed by summing intraday quoted spreads; RET_Volatility is the annual average standard
deviation of the stock return; Ln(Volume) is the natural logarithm of annual stock volume trade for
frm i; Disclosure is the number of annual price-sensitive disclosures announced by frm i to the
ASX under the Continuous Disclosure regulations for frm i; Ln(Size) is the natural logarithm of the
market value of equity computed as ordinary shares on issue for frm i at fnancial year-end t
multiplied by stock price at t; Leverage is total non-current liabilities for year t scaled by the
average total assets for years t and t ?1; MBV is the market value of frm i at t divided by the book
value of equity for year t; E_P is reported earnings per share before abnormal items scaled by share
price at t; Sales_Growth is the change in operating revenue scaled by the average total assets for
frm i for year t; Asset_Growth is the change in total assets scaled by the average total assets for
frm i for year t; Earn_Chg is the change in net proft after tax before abnormal items scaled by
average total assets for frm i for years t and t ?1; Accrual_Chg is the change in income before tax,
net interest, abnormal items minus cash fows from operations scaled by the average total assets
for frm i for year t; OwnConc is the shares held by the top twenty shareholders divided by the total
issued ordinary shares for year x; Beta is the monthly equity rate of return divided by the market
return index measured as deviation from risk free rate for the previous 20 months; RET_Mkt is the
annualized value-weighted average price return on all stocks in the SIRCA share price and price
relatives dataset. Coeffcient ? reported above t-statistic. ***signifcant at 1% level; **signifcant
at 5% level; annual pooled sample of ASX listed frms for the period 1996-2006
Info_Asymmetry
i,t?1
? ?
0
? ?
1
Disclosure
i,t
? ?
2
Ln
(
Size
)
i,t ? ?
3
Leverage
i,t
? ?
4
MBV
i,t
? ?
5
E_P
i,t
? ?
6
Sales_Growth
i,t
? ?
7
Asset_Growth
i,t
? ?
8
Earn_Chg
i,t
? ?
9
Accrual_Chg
i,t
? ?
10
RET_Volatility
i,t
? ?
11
Ln
(
Volume
)
i,t
? ?
12
OwnerConc
i,t
? ?
13
Beta
i,t
? ?
14
RET_Mkt
i,t
? ?
g
Disclosure
i,t
? Firm Expections
i,t
? ?
i
(4)
217
Disclosure
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asymmetry
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Table XI.
Estimates for
parsimonious model
(2) for deciles of
lagged stock price
volatility bid-ask
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4.3 Robustness tests
A number of tests are performed to check the robustness of the earlier results. The
parsimonious Model (2) is tested with all ASX stocks; Model (3) is regressed on
changes in information asymmetry; and, in Model (2), clustered standard errors are
adjusted. These test results are discussed below, although untabulated due to space
constraints.
The study runs parsimonious Model (2) using the full sample of all ASX-listed
companies for 1996-2006, with variables winsorized at 1 and 99 per cent percentiles to
remove outliers. The Model (2) results for all-frm sample differ in two ways from the
reported results in Table IX for the largest 500 ASX frms. The study fnds the
coeffcient for price-sensitive disclosure changes froma negative sign (as in Table IX) to
a positive sign, refecting the inclusion of frms with relatively higher level of
information asymmetry. The study also fnds the sign of the Disclosure
d
? Bid-Ask
Spread
d?1
interaction changes from positive (as in Table IX) to negative. This evidence
confrms earlier results that the pre-existing level of information asymmetry is an
important factor in tests of disclosure effects under CDR.
Second, Model (3) is run with a change of information asymmetry measure, rather
than the level of information of asymmetry, as the dependent variable. The results
show that the change of information asymmetry models has a lower adjusted
R-square than the levels of asymmetry models. Nevertheless, for changes of bid-ask
spread and trading volume, the Model (3) results are consistent with earlier results
reported in Table VII.
Third, the study examines whether there are standard error biases from clustering
effects. Following Liang and Zeger (1986) and Petersen (2009), the standard errors are
adjusted to account for a possible correlation within clusters of observations using
the Generalized Estimating Equations (GEE) approach of Liang and Zeger (1986).
For the (parsimonious) Model (2), the price-sensitive disclosure variable is no longer
signifcant. However, the interaction Disclosure ?Bid-Ask Spread is signifcant and
negative. This result is consistent with H2. The study fnds the GEE results for the
re-estimated Model (3) are the same as the results reported in Table VII using OLS
standard errors. The market-sensitive disclosure coeffcient estimate is positive and
signifcant, while the control variables remain signifcant except for MBV and the
accruals changes variables.
4.4 Additional tests
The study performs three additional tests of H2and H3using parsimonious Model (2) as
follows: coding disclosures by ASXprimary code; sampling only frmi disclosure days;
and adding disclosure interaction variables for good news and bad news.
First, the study uses ASX primary code classifcation of disclosures, described in
Section 3.2, and examines information asymmetry in Model (2). Multiple disclosure
observations were omitted from the sample, except for the periodic fnancial-report
releases commonly supplemented by procedural disclosures. In untabulated results, the
study fnds signifcant negative associations between bid-ask spread and disclosure of
periodic fnancial reports and company administration. Further, the study fnds
signifcant positive associations between bid-ask spread and takeover announcements
and issued capital disclosure. In the positive associations, the disclosure – lag
information asymmetry interaction variable is also signifcant and negative. Hence, the
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overall effect of takeover and issued capital disclosures is a function of the pre-existing
asymmetry, while periodic fnancial reports and company administration disclosures
reduce information asymmetry.
Second, the study tests Model (2) with a sample of frm i disclosure days, and uses
an indicator variable with price-sensitive disclosures taking a value of 1, and
non-price-sensitive disclosures taking the value of 0. In untabulated results, the
study fnds similar results to those of the full ASXfrmsample: a signifcant positive
association between bid-ask spread and price-sensitive disclosure and a signifcant
negative association between bid-ask spread and the interaction variable between
the lag of bid-ask spread and disclosure. The results confrm the importance of
pre-existing information asymmetry in assessing the reaction to disclosure.
Third, to Model (2), the study adds disclosure interaction variables for good and bad
news, being the market-adjusted daily stock return. Table XII reports signifcant
negative associations between bid-ask spread, disclosure and both good news and bad
news interaction variables. The results highlight evidence that, while bad news
increases bid-ask spread, the incremental effect of frmdisclosure of good and bad news
decreases information asymmetry. The results are consistent with H2 and CDR
operating as intended by regulators.
5. Conclusion
This study examines whether frms with high information asymmetry disclose more
information under the Australian Continuous Disclosure Regime (CDR), and whether
continuous disclosures reduce information asymmetry.
This study provides initial evidence under CDR that frms with high information
asymmetry disclose more information. Further, the results indicate that frms disclose
according to their economic characteristics rather than strictly following prescriptive
disclosure rules (Frost and Pownall, 1994). These results are consistent with the
argument that management retains disclosure discretion under CDR(Brown et al., 1999;
Hsu et al., 2012), nevertheless, the benefts of disclosure provide managerial incentives to
comply with the CDR.
Second, the study fnds evidence that disclosures increase information asymmetry
for frms with high information asymmetry. Those frms with high information
asymmetry are arguably the subset of frms targeted by CDR. Nevertheless, these
results are consistent with prior evidence of disclosure increasing information
asymmetry in the presence of uncertainty or high information asymmetry (Brown et al.,
2009; Rogers et al., 2009). More broadly, the effect of CDR disclosure on asymmetry
is conditional on the frm’s economic characteristics, particularly performance
expectations and growth measured by E_P and MBV ratios.
Finally, the study identifes new evidence under CDR that information
asymmetry is infuenced by the nature of the news. Although bad news creates
information asymmetry, frm-specifc good and bad news reduce the information
asymmetry. In particular, news events such as fnancial report releases and
company administration announcements are likely to reduce information
asymmetry. Overall, the results contribute a deeper understanding of the nuanced
interaction between frm disclosure and information asymmetry in the CDR
information environment.
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The results have several implications for regulators, frm disclosure practices and
investors. First, the study provides evidence that CDR is operating as intended by
the regulators to target frms with high information asymmetry. For frms
possessing information and exercising discretion, the results suggest that
frm-specifc disclosure of both good and bad news is optimal during the market
reaction to bad news. For investors, the results confrm that frm characteristics
enable investors to anticipate CDR disclosure and the effect of CDR disclosure on
information asymmetry.
Table XII.
Estimates for
parsimonious model
(2) with good news
and bad news
disclosure interaction
effects
Information asymmetry Expected sign Bid-ask spread
d?1
Intercept ? 0.374
163.150***
Disclosure
id
?/? ?0.039
?4.290***
Bid-Ask Spread
id?1
? 0.769
1115.590***
Disclosure ?Bid-Ask Spread
id?1
?/? 0.015
4.710***
Good News
id
?0.105
?0.990
Bad News
id
7.847
75.100***
Disclosure ? Good News
id
?0.861
?3.330***
Disclosure ? Bad News
id
?2.902
?10.050***
Adjusted R
2
0.618
F-statistic 195,849.0
Observations 848,566
Notes:
Info_Asymmetry
i,d?1
? ?
0
? ?
1
Disclosure
i,d
? ?
2
Info_Asymmetry
i,d?1
? ?
3
Disclosure
i,d
? Info_Asymmetry
i,d?1
? ?
5
Good_News
i,d
? ?
6
Bad_News
i,d
? ?
7
Disclosure ? Good News
i,d
? ?
8
Disclosure ? Bad News
i,d
? ?
i
(1)
Info Asymmetry is daily bid-ask spread measured as the ratio of the quoted bid-ask spread to the quoted
midpoint price and then time-weighted, where the weighting procedure is based on the number of
seconds the quotation exists in each interval, measured for frm i for day d; Disclosure
i,d
is
price-sensitive disclosure measured as the daily number of price-sensitive frm disclosures announced
by ASXfor frmi for day d; Good News is the market-adjusted daily share return greater than zero where
the market return is the daily rate of return on the ASX All Ordinaries Index; Bad News is the absolute
market-adjusted daily share return equal to or less than zero where the market return is the daily rate of
return on the ASXAll Ordinaries Index. Coeffcient ?is reported above t-statistic; ***signifcant at 1%
level
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Further reading
ASX (Australian Securities Exchange), Listing Rules, Australian Securities Exchange, Sydney,
available at: www.asx.com.au/regulation/rules/asx-listing-rules.htm (accessed 1 August
2015).
Verrecchia, R. (1983), “Discretionary disclosure”, Journal of Accounting and Economics, Vol. 5,
pp. 179-194.
Corresponding author
Mark Russell can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
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