■ 国際会計研究学会 年報 2016 年度第 1・2 合併号
Ⅲ

韓国セッション報告

Liquidity, Information Asymmetry and the Role of
IFRS: In case of Korea

Hyuk Shawn
Keimyung University

Jae-gyung Jung
Tongmyong University

Abstract
This study investigates the relation between accounting liquidity andinformation asymmetry. Firms with greater portion of non-current assets
are likely to have severe information asymmetry because market
participants do not know the intrinsic value of non-current assets. We findevidence that bid-ask spreads, the empirical measure of information
asymmetry used in this study, are inversely related to accounting liquidity.
Meanwhile, a firm’s manager with high information asymmetry can choose
the new accounting method or disclosure to maximize the value of assets.
Korean firms used the current arrangement method (CAM) mandatorily
presenting the statement of financial position before the International
Financial Reporting Standards (IFRS) era. Under IFRS, however, they can
select either CAM or the non-current arrangement method (NCAM). We
find that firms with large proportion of non-current assets using NCAM
mitigate the level of information asymmetry proxies. This result indicatesthat simply changing the order of presentation in the statement of financial
positionarousethematerialityof

non-current

assetstomarketparticipants. We suggest that this result can be associate with order effect,
especially primacy effect.

Key words: Liquidity, Information Asymmetry, Bid-ask Spread, IFRS, Arrangement Method85informative to investors (Bartov and Bodnar

1. Introduction

1996). Managers also improve quantity and

Liquidity in accounting field means how

quality of disclosure, so that stock price ofeasy assets are converted to cash. The

their

firm

is

higherliquidity of an asset is reflected in the level

informationof easiness in buying or selling it. The more

Verrecchia 1991).

due

asymmetrytoreduced(Diamondandliquid a firm’s assets, the faster they can be

For example, the adoption of International

sold. Asset liquidity is, therefore, generally

Financial Reporting Standards (IFRS) is

considered being easier to finance (Myers

expected to not only enhance the quantity or

and Rajan 1998). In contrast, financial

quality of disclosure but also improve theliquidity indicates how quickly securities

reliability of financial information (Barth etissued by a firm can be converted into cash

al. 2008; Christensen et al. 2012). IFRS

in the stock market. The liquidity of a stock

based on the principle-based accounting cancan be measured by transaction cost because

also give discretion to firm’s manager so thatmarket illiquidity means that it is difficult tothey can present market participants withtrade the stock (Amihud and Mendelson

more information reflecting substance of the1986).

firm compared to the previous local GAAP.

An important component of transaction

In other words, IFRS enable firms to give a

cost of an asset is the spread between buyers’

chance to reduce the degree of informationand sellers’ prices. Manager who is aware ofasymmetry between insiders and outsiders

the intrinsic value of an asset wants to sellby delivering sufficient and informativeat that price to a minimum, while outsider

disclosure

who may not know the information can

Armstrong et al. 2010).

(Leuz

and

Verrecchia

2000;

hesitate to purchase at the manager’s ask

We extract all the data used in this study

price. Information asymmetry can stem fromfrom Korean stock market. Actually, Korean

private information of managers because

stock market may be a better tool for our

they observe changes in productivity andpurposevalue on each asset directly (Aboody and Lev

environments

2000). Thus, financial liquidity as well asasymmetry between insiders and outsiders

accounting liquidity represents information

for the following reasons. First, listed firms

asymmetry about the private information ofin Korea have adopted IFRS since 2011. This

assets or stocks.

isMeanwhile, managers have incentives tomaximizefirms’

value

andreduceabecausetoremarkable

it

has

examinechangefavorable
informationofaccounting

standards in Korea. For example, Korean
local

GAAP

are

rule-based

accounting

information asymmetry by switching tostandards, while IFRS are principle-based

newly available accounting technique or

ones. IFRS also allow managers discretion toprinciples which financial statements more

provide outsiders with information more86Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea

relevant to firms' economic substance thanSecond, we examine whether accounting

Korean local GAAP. Accordingly, managers

liquidity implied by a firm’s disclosure inwith high information asymmetry can choose

CAM versus NCAM has an impact on

the new accounting method or disclosure offinancial liquidity. In

IFRS to maximize the value of assets

investigate whether a firm with greater(Bartov and Bodnar 1996; Armstrong et al.

portion of non-current assets, which changes

2010; Christensen et al. 2012).

from CAM to NCAM after IFRS adoption,

Second, listed firms in Korea used thecurrent

arrangement

methodother words, we

can reduce information asymmetry.
For

(CAM)

a

sampleof

5,734

firm-year

mandatorily in reporting the statement ofobservations drawn from KIS-value databasefinancial position before IFRS era. Underover six fiscal years from 2007 to 2012, we

IFRS, however, managers can select either

find a strong positive association between

CAM

arrangement

the non-current asset ratio (i.e. accounting

method (NCAM).(1) Shawn et al. (2012) findliquidity) and two measures of the bid-ask

that firms with large proportion of non-spread (i.e. financial liquidity). This finding

current assets change from CAM to NCAM

is in line with prior studies (e.g., Aboody andafter IFRS adoption, and that the value of

Lev 2000; Barth et al. 2001) that examine

non-current assets of NCAM firms is more

relation between the size of intangible assets

relevant than that of firms using CAM is.

(e.g., R&D) and insider trading as well as

These results indicate that NCAM firms cananalystshow the materiality of information on theirliteratures focus on the uncertain disclosure

financial position by using new presentationof intangible asset. In comparison, ourorder of IFRS, and that outsiders can befinding indicates that the liquidity of a firm’s

affected by the presentation order.

assets is closely related to the level of

or

the

non-current

In this study, we first investigate therelation between accounting liquidity andcoverage.

information

However,

asymmetryprevious

inferredfromtrading of its shares in the stock market.

financial liquidity. Accounting liquidity is

However, isolating NCAM firms from thedefined as the ratio of non-current assets

whole sample, we find that the non-current

divided by total assets. A firm with greater

asset ratios of NCAM firm are negatively

portion of non-current assets is predicted torelated to information asymmetry proxies ofbe more likely to have severe informationthese firms. This result indicates that simply

asymmetry between insiders and outsiders

changing the presentation order of a firm’s

because market participants do not know theassets in the statement of financial position

intrinsic

arouse the materiality of non-current assets

value

of

non-current

assets.

Consequently, outsiders who are interested

tomarketparticipants.

Results

fromin the firm’s share are reluctant to purchaseadditional analyses, including the control for

it at the market price.

other information asymmetry proxies such87

as volatility of stock prices and tradingbid-ask spread. This result implies thatvolume, consistently support these main

uncertainty of information can decrease

findings.

market liquidity. Diamond and Verrecchia

Our findings are closely related to the(1991) make theoretical models to explain aresults of Shawn et al. (2013). In that paper,

firm’s disclosure has an impact on market

they elucidate a NACM firm’s characteristics

liquidity. Managers’ disclosure can affectandmarkethiddenintention

to

send

positive

liquidity

becauseinformation

information to outsiders by using NACM.

asymmetry between managers and outside

Our paper is an extension of Shawn et al.

investors increase transaction costs and(2013)

ofreduce market liquidity. Bartov and Bodnar

mandatory IFRS adoption on information(1996) document that a manager whose firm

asymmetry.

has

has greater information asymmetry is likely

additional contributions in several respects.

to switch to more informative accounting

First, we identify the consequence of NCAM.

techniques. Aboody and Lev (2000) reportThat is, our findings indicate that thisthat the sources of private information suchprovision of discretion after IFRS adoption

as research and development disclosure leadpresents outsiders with a firm’s substance at

to information asymmetry. Barth et al. (2001)

a glance. Second, we shed light on thealso

unexpected role of IFRS. In other words, oursignificantly

findings

discretion

assets. Thus, these studies suggest that

granted by IFRS can mitigate information

disclosure policy is a major contributor toasymmetry.

information asymmetry between insiders

byinvestigating
However,suggest

that

the
our

effectspaper

simplyThe reminder of the paper proceeds as

find

that

analystassociatedcoveragewithisintangible

and outsiders.

follows: In Section 2 we provide backgroundManagers know intrinsic value of assets

and develop hypotheses; Section 3 lays out

better than outsiders by using internal

our empirical model and describes theinformation, i.e. fair value of each asset.

sample; Section 4 provides empirical results;

However, outsiders cannot help depending

Section 5 concludes.

on the disclosure (e.g. financial statements)
reported

2. Hypothesis development

bymanagers.

Information

asymmetry in non-current assets, moreover,is greater than current assets for several

disclosure,reasons. First, most of current assets can beinformation asymmetry and market liquidity

measured by fair value accounting, while

have been established in prior literature.

non-current assets cannot. Second, the non-Amihud and Mendelson (1986) identify thecurrent assets take time to be converted tosignificant association between average risk-

cash because managers who know theadjusted returns on the stock market andintrinsic value of the non-current assets

The

88

relationsamong

Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea

want to sell at that price to a minimum,

2007; Defond et al. 2011; Florou and Pope

while outsiders who may not know the2012).

information can hesitate to purchase at the

Furthermore, IFRS allow all the listed

managers’ ask price. A firm’s stocks reflectfirms to select their arrangement method intheConsequently,

the statement of financial position (IFRS

non-current

1001 'Presentation of financial statements'

assets will bring the difference between

paragraph 57, paragraph 60-64). Thus, IFRS

selling price and the purchase price of theenablestocks. Based on the above, we present thearrangement method (CAM) or non-current

following hypothesis:arrangement

firm'sinformation

information.
asymmetry

of

firms

to

choosemethodeither(NCAM).

currentTobeconcrete, CAM is that current assets or
Hypothesis 1: Firms with greater portion

liabilities are listed ahead of non-currentof non-current assets are more likely toassets or liabilities. This is the method thathave severe information asymmetry.

assets or liabilities are listed in the order ofdescending liquidity. On the other hand,

IFRS adoption has advantages for several

NCAM means that non-current assets or

reasons in that IFRS are expected to reduce

liabilities are listed ahead of current assets

information asymmetry between insiders

or liabilities in the ascending order ofand outsiders. First, IFRS can improve theliquidity.

quality of financial statements by reflecting

In the Pre-IFRS era (i.e. under Korean

firms’ economic substance, hence providing

local GAAP), Korean firms have used CAM

outsiders with more relevant information

mandatorily. After IFRS adoption in 2011,

such as fair value accounting (Barth et al.

however,2008). Second, outsiders prefer to expand thearrangement method on the statement of

quantity of firms’ disclosure per se because it

financial position from CAM to NCAM. Thisis difficult for them to access internalchange implies that IFRS based on theinformation on their firms (Daske et al. 2013;

principle-based

Christensen et al. 2015). As a result, IFRS

outsiders with more informative substance ofadoption can also have a positive impact on

the firm than Korean local GAAP by giving

the quantity of voluntary disclosure because

discretion to firm’s manager (Shawn et al.

of increased demand for transparency from2013).

firms

canaccountingchangecan

theirprovideoutsiders (Li and Yang 2016). Third, IFRS

Several studies document that auditors,

adoption increases comparability of firms

financial analysts as well as information

across countries (DeFond

et al.

2011).

users can be affected by the reporting

Improved

comparability

candecreaselocation in the financial statements (Hirst

transaction

cost

therebyand Hopkins 1998; Bonner 2003). There are

increasing capital outflows (Covrig et al.

two kinds of order effects, primacy effect,ofoutsiders,89and recency effect. When information is
given

consecutively,

the

most

recently

3. Research Designpresented information can be remembered

3.1 Multivariate Modelthe best. This is called recency effect. In

We use regression analysis in order to

given

identify the relation between accounting

concurrently, firstly presented information

liquidity (i.e. ratio of non-current assets) andwill be more important in making decision

information asymmetry, and to examine(Miller and Campbell 1959; Asare 1992;

whether the difference in reporting methods

Hogarth and Einhorn 1992; Trotman andon

Wright 1996). This is called primacy effect.

decreases

contrast,

Shawn

when

et

informational.

(2013)

isdocument

that

the

statementofinformation

financial

position

asymmetry.

Our

regression model is as follows:

outsiders are presented with information of
the statement of the financial position at theIAit = γ0 + γ1RNCAit + γ2NCAMit +same time. As a result, the decision making

γ3RNCAit*NCAMit + γ4SIZEit + γ5LEVit +process of outsiders is affected by primacy

γ6ALTMANit + γ7GROWTHit + γ8RMSit +effect. Therefore, a manager whose firm has

γ9RFSitmore

γ12NEGEit + γk∑YEARit + γk∑INDit + εit (1)importantnon-current

assets+γ10MTBit+

γ11BIG4it+

quantitatively as well as qualitatively has anincentive to use NCAM. Also, outsiders canIAit: proxies of information asymmetry; bid-

evaluate non-current assets much important

ask spread (SP01), effective spread (SP02),

and examine them carefully when they arevolatility

presented first in the statements of financial(VOLU)

position. Taken together, this array of IFRS

SP01it: bid–ask spread for firm i in year t;

can

SP02it: effective spread for firm i in year t;

mitigate

information

asymmetry(VOLA),

andtrading

volumebetween insiders and outsiders by giving

VOLAit: volatility of stock price for firm i inmore informative discretion of the statement

year t;of financial position. To sum it up, our

VOLUit: volume of common stock for firm isecond hypothesis is stated below.

in year t;
RNCAit: ratio of the non-current assets

Hypothesis 2: NCAM Firms with greater

divided by total assets for firm i in year t

portion of non-current assets are more

NCAMit: 1 if firm i's arrangement method of

likelythe statement of financial position in 2011 istoasymmetry.

mitigate

information

non-current arrangement method and 0
otherwise
SIZEit: natural logarithm of total assets forfirm i in year t
LEVit: total debt divided by total equity for90Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea

firm i in year tinterested parties (DaDalt et al. 2002). We

ALTMANit: Altman (1968) Z score for firm i

use the Altman (1968) Z score to control

in year t

firms’GROWTHit: growth rate of sales for firm i in

distress (Shawn et al. 2013). We also include

year tgrowth ratio of sales (GROWTH) since the

RMSit: ratio of the largest shareholder andgrowth of a firm can increase uncertainty of

the related party ownership for firm i in year

information (Leuz and Verrecchia 2000).

t

Ratio of the largest shareholder and the

RFSit: ratio of foreign investment ownership

related party ownership (RMS) can influence

for firm i in year t

on information asymmetry (Dennis and

MTBit: ratio of market to book value of

Weston 2001). We also include ratio of

equity for firm i in year t

foreign investment ownership (RFS) as

BIG4it: 1 if firm i's auditor is big4 and 0

control variables because information gap

otherwise

between domestic and foreign investors

NEGEit: 1 if firm i's net income is negative

exists (Covrig et al. 2007; Defond et al. 2011).

and 0 otherwise

Market-to-book (MTB) represents a firm's

YEAR: year dummy variable

growth opportunity and financing choice

IND: industry dummy variable(Tang 2009). Auditor size (BIG4) and loss

characteristics

such

as

financial

firm (NEGE) can affect the quality of
If a large proportion of non-current assets

disclosureinfinancialstatements

has an impact on information asymmetry,(Bugstahler and Dichev 1997; Bamber et al.

the coefficient of the ratio of non-current2010).

asset (γ1) will be significantly positive (+).
Also,

if

the

proportion

relationofbetweennon-current

a

large

assetswith

3.2 Estimation
asymmetryofinformation

information asymmetry is attenuated, when

To estimate the level of informationa firm with large proportion of non-current

asymmetry for our sample, we employ two

assets uses NCAM to emphasize non-current

measuresassets, the coefficient of interaction term (γ3)

Bessembinder (2003), which is developed

will be significantly negative (-) respectively.

and widely used in the finance (market

Each of the explanatory variables arecorrelated

withproxiesofofmicrostructure)thebid-askliterature.

spreadTwo

byspreadinformation

measures are the quoted spread and theasymmetry. Natural logarithm of total assets

effective spread. They are defined as follows:(SIZE) and leverage (LEV) are included in
the model because firm size and debt ratio

SP01 = qa - qb / 0.5(qa + qb)

canprivateSP02 = 2D (P - M ) / M = [2D{P - 0.5(qa + qb)}]of/ 0.5(qa + qb)

beaffectinginformation

and

the

level

of

the

number

the

(2)

(3)

91

‫ݍ‬௔ : best (i.e. the lowest) ask price3.3 Sample selection‫ݍ‬௕ : best (i.e. the highest) bid price

Our sample consists of observations from‫ܦ‬: +1 for purchase and -1 for salefiscal years 2007-2010 (pre-IFRS era) andܲ : the price at which a trade is actually

2011-2012 (post-IFRS era) with financial andexecutedaccounting data available from Kis-value
database. We exclude firms in the financial

For each sample firm, we estimate daily

industry, year-end not ending December, andquoted spread and quoted spread for D-1, D0,

issues for administration to maintain theand D+1 where D0 is the day when the audit

homogeneity of our sample. We also remove

report is submitted. Daily spread estimatesfirms

are averaged, and then we take the natural

measures. We winsorize all the variables atlogarithm of the average quoted spreadthe 1st and 99th percentile value to exclude(SP01) and effective spread (SP02).

the effect of outliers. These requirements

withmissingdata

forfinancialresult in a final sample of 5,734 firm-year
observations. Table 1 outlines the sample
selection process.
Table 1. Sample selection and distribution over years and industries
Sample selection criteria

Firm-years

firms traded over Korea Exchange for 2007-2012

9,991

delete banking firms and non-December fiscal years(451)

delete firms with missing data

(2,831)delete firm-years less than eight in each year and each two-digit industry andoutliers lying outside top and bottom one percentile of earnings quality measures(975)

Final sample

5,734

ask spread (SP01) and effective spread

4. Empirical Results
4.1 Descriptive
Correlation

statistics(SP02) are -5.3242 (-5.3643) and -4.6986 (-and4.7033), respectively. The mean (median) of
volatility(VOLA)

andtrading

volumeTable 2 reports the descriptive statistics(VOLU) are 4.0406 (4.0481) and 11.4702

for all variables that represent our samples(11.5563), respectively. The mean (median) of

by the entire time periods of 2007–2012 in

RNCA is 0.3211(0.2939). The ratio of NCAM

regression model. The mean (median) of bid-

firm (NCAM) is 3.56 % of total samples.

92Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea
Table 2. Descriptive statistics
Variable

1st

Std Dev.

Min

SP01

-5.32420.7364-6.9723-5.8517-5.3643-4.8376-2.4679

SP02-4.6986

0.6638-6.8352-5.1529-4.7033-4.2768-1.8482

VOLA

4.0406

0.39482.41063.80724.04814.26927.8088VOLU

11.47021.83054.208410.328111.5563

12.722917.1537

RNCA

0.32110.24990.00000.15530.29390.4437

6.9985SIZE

18.7079

1.434515.5905

17.7606

18.3870

19.321325.3978

LEV

0.93890.90280.04200.32990.68171.23166.8361

ALTMAN

3.40753.6037-7.7025

1.65942.61584.143656.6818

GROWTH

0.13470.3741-0.7417-0.0404

0.08860.23892.9460RMS

0.39930.16660.01900.28180.38970.51071.0000RFS

0.06140.11370.00000.00080.00890.06720.8671MTB

1.2676

1.05230.19400.5961

0.94181.54607.6752BIG4

0.55310.49720.00000.00001.00001.00001.0000NEGE

0.2656

0.44170.00000.00000.00001.00001.0000NCAM

0.03560.10010.00000.00000.00001.00001.0000Quartile

Median

3rd

Mean

Quartile

Max

Table 2 reports Summary statistics. The sample consists of 5,734 non-banking firm-years that are tradedover Korea Exchange for 2007-2012 with non-missing data that are used in empirical analysis andcollected from KIS-Value database. SP01=natural logarithm of bid–ask spread for firm i in year t;
SP02=natural logarithm of effective spread for firm i in year t; VOLA=natural logarithm of volatility ofstock price for firm i in year t; VOLU=natural logarithm of volume of common stock for firm i in year t;
RNCA=ratio of non-current assets in total asset for firm i in year t; SIZE=natural logarithm of total
assets for firm i in year t; LEV=total debt divided by total equity for firm i in year t; ALTMAN=Altman Z
score for firm i in year t; GROWTH=growth rate of sales for firm i in year t; RMS=ratio of the largest
shareholder and related party ownership for firm i in year t; RFS=ratio of foreign investment ownershipfor firm i in year t; MTB=market to book ratio for firm i in year t; BIG4=1 if firm i's auditor is Big 4 and0 otherwise in year t; NEGE=1 if firm i's net income is negative and 0 otherwise in year t. NCAM=1 iffirm i uses non-current arrangement method in disclosing the statements of financial position and 0
otherwise in year t.

93

Table3

presents

Pearsoncorrelation

investment

ownership(RFS),

whichiscoefficients for the relations among the firm-

0.4720. This relation suggests that foreign

specific variables. This table indicates thatinvestors prefer large firms to mitigate

proxies of information asymmetry except

investment risk. Taken altogether, with thetrading

positive

exception of few variables, the correlation

correlated with each other significantly.

between the independent variables in the

What is noticeable is the relation between

model are not generally material.

volume(VOLU)

areassets size (SIZE) and the ratio of foreign
Table 3. Pearson correlations
Variable

SP01

SP01

SP02

VOLA

VOLU

1.0000 0.8107 0.0118 -0.3982

RNCA

SIZE

LEV

ALTMAN GROWTH

RMS

RMF

MTB

BIG4

NEGE

NCAM

0.0123 -0.3583 0.0031 -0.1270-0.0811 0.1750 -0.1585 -0.2718 -0.1418 0.1624 -0.0135

SP02

1.0000 0.0933 -0.2824 -0.0107 -0.3331 0.0143 -0.1279-0.0399 0.1012 -0.1424 -0.2168 -0.1333 0.1736 -0.0178

VOLA

1.0000 0.4273 -0.0324 -0.3178 0.1220 -0.0194

0.0507 -0.1975 -0.2198 0.1742 -0.1065 0.2677 0.0219

VOLU

1.0000 -0.0706 0.0895 0.1349 -0.0117

0.0357 -0.4025 -0.0268 0.3023 0.0115 0.1579 0.0477

RNCA

1.0000 0.1776 0.1360 -0.1638

0.0886 0.1150 0.0009 -0.0535 0.0121 -0.0911 0.0338

SIZE

1.0000 0.2118 -0.1086

0.0453 0.0926 0.4720 -0.0270 0.2679 -0.2366 -0.0246

LEV

1.0000 -0.3898

0.0364 -0.0308 -0.0148 0.1421 0.0139 0.2134 -0.0033

1.00000.0580 0.0176 0.0829 0.3384 0.0491 -0.2036 -0.0016

ALTMANGROWTH

1.0000 0.0214 0.0065 0.1100 0.0335 -0.1631 0.0086

RMS

1.0000 0.0017 -0.1638 0.0359 -0.2260 -0.0219

RFS

1.0000 0.0838 0.1801 -0.1516 -0.0481

MTB

1.0000 0.0346 0.0531 -0.0135

BIG4

1.0000 -0.1271 -0.0601

NEGE

1.0000 0.0526

NCAM

1.0000

Table 3 reports Pearson Correlation coefficients for variables used in the regression models. Correlations
in bolds are significant at less than 5% levels. The sample consists of 5,734 non-banking firm-years thatare traded over Korea Exchange for 2007-2012 with non-missing data that are used in empiricalanalysis and collected from KIS-Value database. SP01=natural logarithm of bid–ask spread for firm i inyear t; SP02=natural logarithm of effective spread for firm i in year t; VOLA=natural logarithm ofvolatility of stock price for firm i in year t; VOLU=natural logarithm of volume of common stock for firm
i in year t; RNCA=ratio of non-current assets in total asset for firm i in year t; SIZE=natural logarithmof total assets for firm i in year t; LEV=total debt divided by total equity for firm i in year t;
ALTMAN=Altman Z score for firm i in year t; GROWTH=growth rate of sales for firm i in year t;
RMS=ratio of the largest shareholder and related party ownership for firm i in year t; RFS=ratio of
foreign investment ownership for firm i in year t; MTB=market to book ratio for firm i in year t; BIG4=1
if firm i's auditor is Big 4 and 0 otherwise in year t; NEGE=1 if firm i's net income is negative and 0
otherwise in year t. NCAM=1 if firm i uses non-current arrangement method in disclosing thestatements of financial position and 0 otherwise in year t.

94

Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea

4.2 Test of Hypothesis 1

RNCA indicates that accounting liquidity is

Table 4 provides the test of H1, whichstrong associated with bid-ask spread. In

examine accounting liquidity on information

Model 2 and Model 3, our results are similar

asymmetry. We exclude NCAM and theto Model 1. The coefficient on RNCA isinteraction

significantly

variable(RNCA*NCAM)

of

positive.

In

Model

4,

the

equation (1). We report the results of four

coefficient on RNCA is significantly negative

different regressions using different proxies

because the greater trading volume is, thefor information asymmetry (SP01, SP02,

smaller bid-ask spread. That is, our results

VOLA, and VOLU). We find the evidence

in Table 4 support for the hypothesis 1 thatconsistent with our hypothesis 1. In Model 1,

accounting liquidity is positively associatedthewith the proxies of information asymmetry.

significantly

positivecoefficienton

Table 4. Results of hypothesis 1

Variable

Model 1Model 2Model 3Model 4

DV= SP01

DV=SP02

DV=VOLA

DV=VOLU

Coeffs (t-stat a)

Coeffs (t-stat a)

Coeffs (t-stat a)

Coeffs (t-stat a)

Intercept-1.5546***(-8.36)-1.5896***(-9.16)5.2634***(59.86)

7.1276***(17.50)RNCA

0.1188***(2.89)

0.0917**(2.09)

0.0540***(2.75)-0.3195***(-3.51)SIZE-0.2082***(-22.12)-0.1703***(-19.39)-0.0664***(-15.00)

0.2848***(13.89)LEV

0.0680***(6.33)

0.0568***(5.67)

0.0087***(2.78)-0.0509***(-3.51)

ALTMAN-0.0001(-0.02)-0.0023(-1.28)-0.0011(-1.21)-0.0063(-1.55)GROWTH-0.0062(-0.54)0.0116(1.10)

0.0165***(3.02)

0.0907***(3.59)

RMS

0.6625***(9.50)

0.3322***(5.10)

0.3567***(11.12)-4.0821***(-27.52)

RFS

0.4270***(4.26)

0.3904***(4.17)

0.2532***(5.19)-1.9509***(-8.62)

MTB-0.1144***(-13.64)-0.0826***(-10.55)

0.0107***(4.07)

0.1310***(10.75)BIG4-0.0317(-1.40)-0.0311(-1.47)-0.0210**(-2.02)-0.0633(-1.32)

NEGE

0.1945***(7.25)

0.1766***(7.06)

0.1605***(13.26)0.5181***(9.23)

YEAR

Included

Included

Included

Included

IND

Included

Included

Included

Included

F Value

41.21***

29.39***

47.33***

56.77***

Adj. R2

0.24490.18630.22220.2550

Table 4 reports multivariate test in the regression models. The sample consists of 5,734 non-banking
firm-years that are traded over Korea Exchange for 2007-2012 with non-missing data that are used inempirical analysis and collected from KIS-Value database. aTwo-tailed t-test; *,**, ***significant at lessthan 10%, 5%, and 1% levels, respectively. See appendix for variable definitions. SP01=natural
logarithm of bid–ask spread for firm i in year t; SP02=natural logarithm of effective spread for firm i inyear t; VOLA=natural logarithm of volatility of stock price for firm i in year t; VOLU=natural logarithm95

of volume of common stock for firm i in year t; RNCA=ratio of non-current assets in total asset for firm iin year t; SIZE=natural logarithm of total assets for firm i in year t; LEV=total debt divided by total
equity for firm i in year t; ALTMAN=Altman Z score for firm i in year t; GROWTH=growth rate of sales
for firm i in year t; RMS=ratio of the largest shareholder and related party ownership for firm i in year t;
RFS=ratio of foreign investment ownership for firm i in year t; MTB=market to book ratio for firm i inyear t; BIG4=1 if firm i's auditor is Big 4 and 0 otherwise in year t; NEGE=1 if firm i's net income isnegative and 0 otherwise in year t.

4.3 Test of Hypothesis 2

hypothesis 2 that NCAM firms, even if they

Table 5 presents the results for the test of

have greater portion of non-current assets,

H2, which examine the effects of NCAM on

the relation between accounting liquidity

information asymmetry. In Model 1, theand information asymmetry is attenuated.

significantly negative coefficient on the

Our finding suggests that a simple discretioninteraction term (RNCA*NCAM) suggeststhat choose arrangement method of assetsthat NCAM mitigate information asymmetry.

after IFRS adoption lead to effectiveness in

In Model 3 and Model 4, our results support

capital market.

96

Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea
Table 5. Results of hypothesis 2

Variable

Model 1Model 2Model 3Model 4

DV= SP01

DV=SP02

DV=VOLA

DV=VOLU

Coeffs (t-stat a)

Coeffs (t-stat a)

Coeffs (t-stat a)

Coeffs (t-stat a)

Intercept-1.5345***(-8.24)-1.5648***(-9.00)5.2593***(59.77)7.0878***(17.40)RNCA

0.1149**(2.50)

0.0837*(1.79)

0.0738***(3.39)-0.3507***(-3.47)

NCAM-0.0738(-1.57)-0.0938**(-2.14)-0.0330(-1.46)

0.1994*(1.90)

RNCA*NCAM-0.0270*(-1.91)-0.0463(-1.57)-0.0899**(-2.09)0.0976**(2.09)

SIZE-0.2085***(-22.15)-0.1707***(-19.43)-0.0666***(-15.05)

0.2856***(13.94)LEV

0.0677***(6.30)

0.0565***(5.63)

0.0085***(2.73)-0.0500***(-3.45)

ALTMAN-0.0001(-0.06)-0.0021(-1.18)-0.0011(-1.20)-0.0070*(-1.70)GROWTH-0.0063(-0.55)0.0113(1.07)

0.0169***(3.11)

0.0905***(3.58)

RMS

0.6572***(9.42)

0.3256***(5.00)-0.3559***(-11.10)-4.0744***(-27.48)

RFS

0.4186***(4.17)

0.3799***(4.06)-0.2510***(-5.14)-1.9248***(-8.51)

MTB-0.1143***(-13.63)-0.0825***(-10.54)0.0107***(4.09)

0.1310***(10.76)

BIG4-0.0329(-1.45)-0.0327(-1.55)-0.0207**(-2.00)-0.0570(-1.19)NEGE

0.1966***(7.32)

0.1790***(7.14)

0.1614***(13.31)0.5094***(9.06)

YEAR

Included

Included

Included

Included

IND

Included

Included

Included

Included

F Value

38.75***

27.76***

44.53***

53.61***

Adj. R2

0.24520.18710.22250.2561

Table 5 reports multivariate test in the regression models. The sample consists of 5,734 non-banking
firm-years that are traded over Korea Exchange for 2007-2012 with non-missing data that are used inempirical analysis and collected from KIS-Value database. aTwo-tailed t-test; *,**, ***significant at lessthan 10%, 5%, and 1% levels, respectively. See appendix for variable definitions. SP01=natural
logarithm of bid–ask spread for firm i in year t; SP02=natural logarithm of effective spread for firm i inyear t; VOLA=natural logarithm of volatility of stock price for firm i in year t; VOLU=natural logarithmof volume of common stock for firm i in year t; RNCA=ratio of non-current assets in total asset for firm iin year t; SIZE=natural logarithm of total assets for firm i in year t; LEV=total debt divided by total
equity for firm i in year t; ALTMAN=Altman Z score for firm i in year t; GROWTH=growth rate of sales
for firm i in year t; RMS=ratio of the largest shareholder and related party ownership for firm i in year t;
RFS=ratio of foreign investment ownership for firm i in year t; MTB=market to book ratio for firm i inyear t; BIG4=1 if firm i's auditor is Big 4 and 0 otherwise in year t; NEGE=1 if firm i's net income isnegative and 0 otherwise in year t. NCAM=1 if firm i uses non-current arrangement method in
disclosing the statements of financial position and 0 otherwise in year t.

97

4.4 Additional analysis

coefficient on the interaction term (RNCA*NCAM)

Table 6 provides additional test for the test of

indicates

that

NCAM

mitigate

information

hypotheses, which add volatility variable (VOLA)

asymmetry. Therefore, our additional test provides

equation (1) to control for bid-ask spread. In Modelunchanged support for our hypotheses.

1andModel 2,thesignificantly

negative

Table 6. Additional analysis to control for the bid-ask spread

Variable

Model 1Model 2

DV=SP01

DV=SP02

Coeffs (t-stat a)

Coeffs (t-stat a)

Intercept-0.6132**(-2.46)-1.5479***(-6.64)RNCA

0.1262***(2.75)

0.0353*(1.82)

NCAM-0.0643(-1.37)-0.0928**(-2.11)

RNCA*NCAM-0.1072**(-2.08)-0.0946*(-1.85)VOLA-0.1788***(-5.58)-0.1046**(-2.15)SIZE-0.2199***(-22.86)-0.1707***(-18.95)

LEV

0.0713***(6.36)

0.0560***(5.33)ALTMAN-0.0004(-0.21)-0.0021(-1.17)

GROWTH-0.0043(-0.38)0.0116(1.09)

RMS

0.5961***(8.46)

0.3271***(4.96)

RFS

0.3810***(3.80)

0.3809***(4.05)

MTB-0.1089***(-12.91)-0.0824***(-10.43)

BIG4-0.0390*(-1.72)-0.0343(-1.61)NEGE

0.2257***(8.28)

0.1811***(7.10)

YEAR

Included

Included

IND

Included

Included

F Value

38.58***

27.76***

adj. R2

0.25050.1877

Table 6 reports multivariate test in the regression models. The sample consists of 5,734 non-banking
firm-years that are traded over Korea Exchange for 2007-2012 with non-missing data that are used inempirical analysis and collected from KIS-Value database. aTwo-tailed t-test; *,**, ***significant at lessthan 10%, 5%, and 1% levels, respectively. See appendix for variable definitions. SP01=natural
logarithm of bid–ask spread for firm i in year t; SP02=natural logarithm of effective spread for firm i inyear t; VOLA=natural logarithm of volatility of stock price for firm i in year t; RNCA=ratio of noncurrent assets in total asset for firm i in year t; SIZE=natural logarithm of total assets for firm i in yeart; LEV=total debt divided by total equity for firm i in year t; ALTMAN=Altman Z score for firm i in yeart; GROWTH=growth rate of sales for firm i in year t; RMS=ratio of the largest shareholder and related98Liquidity, Information Asymmetry and the Role of IFRS: In case of Korea
party ownership for firm i in year t; RFS=ratio of foreign investment ownership for firm i in year t;
MTB=market to book ratio for firm i in year t; BIG4=1 if firm i's auditor is Big 4 and 0 otherwise in yeart; NEGE=1 if firm i's net income is negative and 0 otherwise in year t. NCAM=1 if firm i uses noncurrent arrangement method in disclosing the statements of financial position and 0 otherwise in year t.

especially primacy effect. Our findings shed

5. Conclusion

light on manager’s intention trying toThis paper examines the relation between

present firm’s substantial financial position

informationby using order effects. Taken together, thisasymmetry, and how NCAM has impact on

study provides an interesting insight into

information asymmetry after IFRS adoption.

the role of IFRS in mitigating information

Our empirical results suggest that a firm

asymmetry between insiders and outsiders.

accounting

liquidity

andwith greater portion of non-current assets
have severe information asymmetry between

Notes

insiders（1）In contrast, Australia, Canada as well as
EU countries have been using NCAM prior to
IFRS adoption.

andoutsiders

becausemarketparticipants do not know the intrinsic valueof non-current assets. Our results revealthat NCAM firms with large proportion ofReferences

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