Dau, Nam Huong; Nguyen, Duy Van; Diem, Hai Thi Thanh
A icle
Annual epo eadabili y and i ms’ in es men decisions
Cogen Economics & Finance
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Annual epo eadabili y and fi ms’ in es men
decisions
Nam Huong Dau, Duy Van Nguyen & Hai Thi Thanh Diem
To ci e his a icle: Nam Huong Dau, Duy Van Nguyen & Hai Thi Thanh Diem (2024) Annual
epo eadabili y and fi ms’ in es men decisions, Cogen Economics & Finance, 12:1,
2296230, DOI: 10.1080/23322039.2023.2296230
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FINANCIAL ECONOMICS | RESEARCH ARTICLE
Annual epo eadabili y and i ms’in es men decisions
Nam Huong Dau
a
, Duy Van Nguyen
b
and Hai Thi Thanh Diem
c
a
Cen e o In e na ional Knowledge Sha ing, Ho Chi Minh Na ional Academy o Poli ics, Hanoi, Vie nam;
b
Facul y o
Business and Economics, Phenikaa Uni e si y, Hanoi, Vie nam;
c
FPT Uni e si y, G eenwich Vie nam, Hanoi, Vie nam
ABSTRACT
An easy- o- ead epo may ca y posi i e in o ma ion o decision making and con-
e sely. In ha spi i , his pape in es iga es he ela ionship be ween he eadabili y
o companies’annual epo s, de ined as he easiness o ead, unde s and, and ex ac
in o ma ion om he epo s, and in es men decisions o Singapo e companies.
Empi ical esul s wi h an DGMM analysis on 251 domes ic companies lis ed on he
Singapo e S ock Exchange (SGX) show a posi i e ela ionship be ween he eadabili y
o annual epo s his yea and in es men s nex yea . As such, epo s’ eadabili y can
se e as a signal signi ican o p edic companies’ u u e in es men s. Ou indings a e
consis en wi h signaling heo y and con ibu e signi ican ly o he li e a u e o
empi ical in es iga ions on he ela ionship o annual epo s’ eadabili y and i ms’
in es men decisions.
ARTICLE HISTORY
Recei ed 10 Augus 2023
Re ised 24 Oc obe 2023
Accep ed 13 Decembe 2023
KEYWORDS
Readabili y; in es men
decision; in es men
olume; annual epo ;
Singapo e s ock exchange
REVIEWING EDITOR
Da id McMillan, Uni e si y
o S i ling, UK
SUBJECTS
Finance; Co po a e Finance;
In es men & Secu i ies
JEL
A1; G1; M40
1. In oduc ion
Annual epo s, which a e legally equi ed o be published by all lis ed companies, a e a means o com-
munica ion o companies’leade ship o capi al ma ke pa icipan s such as in es o s, c edi o s, and o he
s akeholde s (E ug ul e al., 2017); hey a e a c i ical sou ce o in o ma ion o he la e . The ela ed
ole o he epo s’ eadabili y, de ined as he ease o unde s anding gi en in o ma ion based on a
epo (Ba ne & Leo le , 2016), is unde lined by a ious esea ch indings (Cazie & P ei e , 2016,2017;
Hudda e al., 2007; Lim e al., 2018; Lough an & Mcdonald, 2014; Yu & Mille , 2010). The eadabili y o
he annual epo is ound o ha e a signi ican impac on he e ec i e communica ion o in o ma ion
o s akeholde s (Lough an & Mcdonald, 2014). The e a e also e idences ha in es o s and/o s akehold-
e s ely on he in o ma ion in annual epo s o make decisions (buy o sell, in es o no , lend o con ol
lending) (Cazie & P ei e , 2016,2017; Hudda e al., 2007; Lim e al., 2018). De ailed epo s wi h low
deg ee o eadabili y may imply less in o ma ion and con usion o eade s; his can limi eade s’judg-
men and e alua ion, and hence decision-making abili y (Li, 2008; Lim e al., 2018; You & Zhang, 2008;
Yu & Mille , 2010).
Acco ding o signaling heo y and ela ed esea ch, h ough annual epo s, a company’s owne s and
manage s may disclose some signals o business s a egy (Lim e al., 2018; You & Zhang, 2008).
Acco ding o s udies ela ed o eading comp ehension, eadabili y a ec s he abili y o unde s and
published/disclosed in o ma ion, which in u n impac s eade s’judgmen s (Kin sch & an Dijk, 1978;
Masson & Wald on, 1994; Rennekamp, 2012). In ui i ely, he clea e and easie he in o ma ion om he
ß2024 The Au ho (s). Published by In o ma UK Limi ed, ading as Taylo & F ancis G oup.
This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0/), which
pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly ci ed. The e ms on which his a icle has been
published allow he pos ing o he Accep ed Manusc ip in a eposi o y by he au ho (s) o wi h hei consen .
CONTACT Hai Thi Thanh Diem [email p o ec ed],[email p o ec ed] FPT Uni e si y, Hanoi 12116, Vie nam
COGENT ECONOMICS & FINANCE
2024, VOL. 12, NO. 1, 2296230
h ps://doi.o g/10.1080/23322039.2023.2296230
epo is o ead and comp ehend, he be e i is o in es o s as well as o he s akeholde s o unde -
s and he i m pe o mance and make mo e accu a e decisions (Lim e al., 2018; Rennekamp, 2012; Shah
& Oppenheime , 2007).
In his pape , we conduc empi ical esea ch, wi h da a o Singapo e inancial ma ke , o in es iga e
he ela ionship be ween annual epo eadabili y and i m in es men decisions. In his esea ch we
de ine he eadabili y o a epo as he easiness o ead he epo ; a low eadabili y le el means he
epo is di icul o ead, and con e sely, a highe le el o eadabili y means ha he epo is mo e
eadable, i.e. easie o ead and unde s and. Speci ically, his pape seeks o answe he ques ions wha
he ela ionship be ween a i m’s annual epo eadabili y and i s in es men s is, and u he i he ead-
abili y o he epo is a signal, which can help in es o s and/o s akeholde s p edic he company’s
u u e in es men iabili y—hence, i is a channel ha eade s (in es o s, s akeholde s) can ely on o
eac p omp ly and make decisions, including in es men ones.
Singapo e is a coun y wi h a de eloped economy and an ad anced inancial ma ke ; also, i can be
conside ed a inancial cen e o he Asia Paci ic egion (Chow & Pei, 2018). The Global Financial Cen e s
Index upda ed o 2021 anks Singapo e as he i h mos in luen ial inancial cen e in he wo ld, a e
New Yo k, London, Shanghai, and Hong Kong (Wa dle & Mainelli, 2021). The Singapo e S ock Exchange
(SGX) is he la ges in e na ionalized exchange in Asia wi h mo e han 40% o companies lis ed on he
pla o m o igina ing ou side o Singapo e; i has abou 800 companies and is also he la ges Real Es a e
In es men T us (REIT) a e Japan (Chow & Pei, 2018). The e o e, he lis ed companies’annual epo s
a e deemed o mee high s anda ds o comple eness and anspa ency o a de eloped inancial ma ke
(Au, Thompson, & Yeung 2006). Consequen ly, co po a e epo ing se es as a signi ican and meaning-
ul indica o o s akeholde s.
Conduc ing an empi ical analysis, using he Flesh Kincaid G ade (FKG) and Simple Measu e o
Gobbledygook (SMOG) as indica o s o eadabili y, whe e lowe he alues o he indica o s indica ing a
highe le el o eadabili y o a documen , and employing Di e ence Gene alized Me hod o Momen s
(DGMM) model o add ess endogenei y and da a o domes ic companies lis ed on he Singapo e S ock
Exchange (SGX), we ind ha epo eadabili y ca ies signals signi ican o p edic ing i ms’in es -
men s; mo e speci ically, when epo s a e conside ed easy o ead, companies in es mo e and con-
e sely; as such in es o s can ely on he eadabili y o he epo as a p edic o o in es men iabili y.
Conduc ing a quan ile eg ession, we de ec a posi i e ela ionship be ween he epo s’ eadabili y and
companies’in es men s wi h medium o high in es men olumes (insigni ican in a company wi h a
low in es men olume), he eby con i ming he abo e inding. To ou bes knowledge, his pape , wi h
he esea ch ques ions posed and empi ical analysis wi h da a om SGX, ills in he gap o li e a u e o
empi ical in es iga ions on he ela ionship o epo eadabili y and in es men decisions o en e p ises.
This pape can be conside ed a no el s udy on annual epo eadabili y and in es men decisions.
2. Li e a u e e iew
2.1. Readabili y o epo s and in es men decisions
The signaling heo y Spence (1978) p oposes explana ion o he beha io o wo pa ies who di e in
abili y o ecei e and ansmi in o ma ion. A pa y as an in o man ( he pa y making a epo ) mus
choose, whe he o no , o p o ide in o ma ion ha is comple e and unde s andable (Washbu n, 2017)
and his can be done ei he in en ionally o unin en ionally. On he one hand, ecipien s o in o ma ion
om he epo including sha eholde s, in es o s, and o he s akeholde s, choose how o in e p e he
signals hey ecei e (Washbu n, 2017). The signal gi en by he manage will be he in o ma ion o
in es o s and s akeholde s o make hei decisions. Fo lis ed companies, he publica ion o annual
epo s is a way o educe in o ma ion asymme y in he ma ke (Asa e & W igh , 2012). Howe e , hese
disclosu es can posi i ely o nega i ely impac in o ma ion use s, including sha eholde s, in es o s,
depending on i he signals hey ca y a e posi i e o nega i e (Connelly e al., 2011). P e ious s udies
ha e p ima ily employed signal heo y o explain he ela ionship be ween annual epo eadabili y and
inancial pe o mance (Eugene-Bake & Ka e, 1992; Dalwai e al., 2021) o annual epo eadabili y and
2 N. H. DAU ET AL.
ea nings managemen (Li, 2008; Lo e al., 2017). The e o e, esea ch u ilizing signal heo y o elucida e
he ela ionship be ween annual epo eadabili y and in es men decisions emains limi ed.
Rela ed heo e ical and empi ical esul s also show ha eadabili y and ela ed aspec s can in luence
he pe cep ion and decisions o a eade (Lim e al., 2018; Rennekamp, 2012; Shah & Oppenheime ,
2007). In making judgmen s, luen , o easy o p ocess, in o ma ion is weighed mo e hea ily han dis lu-
en in o ma ion (Shah & Oppenheime , 2007). Rela ed esea ch also inds ha mo e eadable disclosu es,
which acili a e p ocessing luency, can a ec in es o s’ alua ion judgmen s. In ui i ely, p ocessing lu-
ency om a mo e eadable epo can se e as a subconscious hin and ein o ce in es o s’belie s
whe he hey should ely on he epo ; as mo e speci ic inding, small in es o s eac mo e s ongly o
mo e eadable epo s, wi h mo e posi i e changes in alua ion judgmen s when news is good and con-
e sely (Rennekamp, 2012). Consis en ly, i i is easy o a ecipien eads and unde s ands in o ma ion in
a epo , i can be conside ed a posi i e signal help ul o he eade ’s decision making (Connelly e al.,
2011). Complex in o ma ion equi es in es o s and o he s akeholde s o make mo e conscious e o s.
This unde mines ecipien s’unde s anding and abili y o assess a company’s p ospec s based on he
in o ma ion and hence may dampen hei decision-making capaci y (Lee, 2012; Lim e al., 2018).
Mo e di ec ly ela ed o annual epo eadabili y, he e a e indings ha easy- o- ead epo s help
eade s make imely decisions (Libby, Bloom ield, & Nelson, 2001; G ossman, 1980); and ha d- o- ead
epo s dis ac o con use he eade s (Cou is, 1998; Lim e al., 2018; Ru he o d, 2003). In ui i ely, he
in o ma ion om annual epo s helps in es o s and s akeholde s wi h de ailed, anspa en in o ma ion,
hus s eng hening hei unde s anding o a company’s po en ial and posi ion (Lee, 2012; Lim e al.,
2018). Some s udies also show ha he eadabili y o epo s is ela ed o i m pe o mance (Eugene
Bake & Ka e, 1992; Biddle e al., 2009; Cou is, 1995,1998; Hassan e al., 2018; Lee & Tweedie, 1975;
Smi h e al., 2006); o example, companies wi h highe annual epo eadabili y ha e highe p o i s and
lowe agency cos s (Hassan e al., 2018; Smi h e al., 2006); companies wi h annual epo s ha a e eas-
ie o ead ha e posi i e ea nings which a e mo e pe sis en (Li, 2008). Readabili y and one ambigui y
o a i m’s inancial disclosu es a e also p o ed o be ela ed o manage ial in o ma ion hoa ding; and
less eadable and mo e ambiguous annual epo s a e associa ed wi h an inc eased cos o ex e nal
inancing (E ug ul e al., 2017). Some o he s udies sugges ha epo s’ eadabili y can a ec he igh -
ening o en e p ises’bo owing (Hudda e al., 2007).
2.2. Measu ing annual epo eadabili y
Fo he sake o cla i y, i s le ’s make i clea ha he eadabili y o a epo is unde s ood as he easi-
ness o di icul o ead, unde s and and ex ac in o ma ion om he epo . The e a e di e en indica-
o s o epo eadabili y as p oposed by esea ch in compu a ional linguis ics, such as Flesch Kincaid
G ade (FKG) and Simple Measu e o Gobbledygook (SMOG) Index; each indica o has a di e en calcula-
ion me hod. As will be cla i ied below, mo e accu a ely, FKG and SMOG a e in ac in e p e ed di ec ly
as measu es o non- eadabili y o epo s, in he sense ha hey ep esen how di icul a ex is o ead;
mo e speci ically, he highe he alues o he indica o s, he lowe he eadabili y o a epo , and con-
e sely (The FKG, SMOG is la ge , he annual epo is mo e di icul o ead). The au ho s desc ibe and
use bo h indica o s in his esea ch.
The FKG index as an indica o o epo eadabili y (Li, 2008; Solnyshkina e al., 2017; Wo all e al.,
2020), also known as he Kincaid index, is calcula ed using he ollowing o mula:
FKG ¼0:398 wo ds
sen ences
þ11:8syllables
wo ds
−15:59
FKG indica es he numbe o yea s o educa ion gene ally equi ed o unde s and a epo . Hence, he
highe he FKG sco e o a epo , he mo e di icul i is o ead he epo . As such, we can also in e -
p e FKG as a measu e o non- eadabili y o epo s, whe e a highe FKG sco e o a epo implies a
highe non- eadabili y le el he epo assumes.
The SMOG (Simple Measu e o Gobbledygook) index was in oduced by Mc Laughlin (1969) o assess
eadabili y. I is a wo- a iable o mula, as ollowed:
COGENT ECONOMICS & FINANCE 3
SMOG ¼1:0430 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
30 complex wo ds
sen ences
sþ3:1291
whe e complex wo ds a e wo ds wi h 3 o mo e syllables (Mc Laughlin, 1969). The index is an es ima e
o he educa ion le el a eade needs o ensu e a ho ough comp ehension o a ex , o example SMOG
G ades 13-16 indica e he need o college educa ion (Mc Laughlin, 1969). Like he FKG index, SMOG o
a epo can also be in e p e ed mo e di ec ly as a measu e o non- eadabili y - he eading di icul y -
o he epo .
3. Me hod
3.1. Resea ch hypo hesis and model
To add ess he esea ch ques ions and deciphe he ela ionship be ween he eadabili y o i ms’annual
epo s and i ms’in es men s, he pape o mula es he ollowing esea ch hypo hesis.
Hypo hesis: A highe eadabili y o a company’s annual epo s p edic s a highe u u e in es men le el o he
company, and con e sely.
To es he hypo hesis and add ess he esea ch ques ion posed, we conside he ollowing he
econome ic model:
In es men i ¼aiþcNonReadabili yi −1þdCon ol Va iablesi −1þei (1)
whe e, dis a coe icien ec o , aiis ime-in a ian unobse ed a iable ( i m ixed e ec ), and ei ,is
e o e m.
The a iables a e desc ibed in de ail in Table 1.
In his s udy, in es men is ep esen ed by he CAPEX index (Capi al Expendi u e). The FKG and
SMOG in his s udy ep esen he non- eadabili y o he annual epo s; speci ically, he lowe he FKG
and SMOG alues, he mo e eadable a epo is and con e sely, as elabo a ed abo e. As such, an
expec ed nega i e sign associa ed wi h each o hese a iables is in e p e ed as a posi i e ela ionship
be ween he eadabili y and he dependen a iable (in es men s).
The le e age, e enue g ow h, and i m size a e he con ol a iables in his esea ch. Le e age is
measu ed by he a io o deb o o al asse s. The highe he le e age o a company, he g ea e he
isks associa ed wi h in e es expenses i he company is no as e icien as expec ed (Nguyen, Nguyen
e al., 2021). The e o e, wi h a la ge le e age a io, a company would end o educe i s in es men ol-
ume o con ol po en ial issues ela ed o in e es expenses (e.g. an inc ease in he bo owing cos s, a
business isk dampening he company’s e enue o an unexpec ed cos unde mining he company’s
epaymen plan e c.). The loga i hm o o al asse s is he p oxy o he i m size in his s udy. The size o
a company may con ain in o ma ion abou he company’s de elopmen s a egy (Nguyen e al., 2020;
Nguyen, Ho e al., 2021). Finally, he e enue g ow h is also included o con ol he impac o epo
eadabili y on he in es men olume. A highe e enue g ow h a e o a company may indica e a
highe de elopmen cycle o he company (Nguyen, Nguyen e al., 2021). This, in gene al, would help
companies o be mo e con iden wi h hei in es men decisions.
Table 1. The a iable de ini ion.
Va iable name Con en Expec ed
Dependen a iables (In es men )
LnCAPEX ¼Ln (Capi al Expendi u e)
Independen a iables (Non-Readabili y)
a
FKG Annual epo eadabili y (Flesch Kincaid G ade) –
SMOG Annual epo eadabili y (Simple Measu e o Gobbledygook) –
Con ol a iables
SIZE ¼Ln (To al asse s) þ
LEV ¼Liabili y/ o al asse s –
GROWTH ¼(Re enue
- e enue
-1
)/ e enue
-1
þ
aFKG and SMOG a e indica o s o eadabili y; by de ini ion o he eadabili y, we make clea abo e o his esea ch, FKG and SMOG a e di -
ec ly measu e o non- eadabili y, as he highe he alues o hese indica o s, he mo e di icul i is o ead and unde s and a documen .
4 N. H. DAU ET AL.
3.2. Da a
Singapo e is one o he wo ld’s i e la ges inancial ma ke s. Lis ed companies on he Singapo e
Exchange (SGX) a e equi ed o p o ide mo e s ingen in o ma ion, leading o mo e eliable da a collec-
ion. Da a is collec ed o he sample o domes ic companies (o Singapo e) lis ed on he Singapo e
S ock Exchange (SGX) om 2016 o 2021. Ou o 443 companies wi h da a collec ed om he SGX, he
esea ch excludes inancial companies and companies wi h incomple e epo ing da a, namely hose
wi h 2 consecu i e yea s wi hou annual epo s. A e da a cleaning and il e ing, he e a e 251 compa-
nies emained, and hey a e all non- inancial.
The summa y s a is ics o da a on eadabili y a e desc ibed in de ail in Table 2. The esul s show ha
he FKG index akes alues be ween 0.1 (min) and 10.4 (max); he a e age alue o he FKG index is
3.56. I means ha , on a e age, he le el o non- eadabili y/di icul y o ead o he documen s in he
sample is a he low, i.e. he documen s a e a he easy o ead. Simila ly, he mean SMOG index o 4.34
also indica es ha he annual epo s a e a a ela i ely easy le el o ead and comp ehend. The de ails
o compa ison be ween annual epo eadabili y indica o s o e yea s in Figu e 1.
The Table 3 desc ibes he a iables abou i ms’cha ac e is ics, con ol a iables o he esea ch
model.
Wi h 251 companies included in he analysis, desc ip i e s a is ics o esea ch a iables show ha he
mean o CAPEX is $60 million; i.e. on a e age, companies end o in es mo e ins ead o wi hd awing
hei in es men s o selling asse s. In addi ion, he mean o LEV (Liabili y/ o al asse s) is 0.496, he mean
o GROWTH is 0.057 (5.7%) and he mean o SIZE o he whole pe iod is 19.84. Summa y s a is ics o
he a iables a e p esen ed in de ail in Table 3.
3.3. Da a analysis
This s udy uses panel da a o 251 companies collec ed om he Singapo e S ock Exchange (SGX) o he
pe iod 2016 o 2021. Con en ional Fixed e ec model (FEM) and Random e ec model (REM) a e used
o in es iga e he p edic abili y o annual epo eadabili y o companies’in es men s. The FEM is a
u he de elopmen o O dina y leas squa es (OLS) o add ess he unobse ed ime-in a ian he e oge-
nei ies ac oss he indi iduals; REM es ima es bo h he wi hin-indi idual and be ween-indi idual a ian-
ces, allowing o handling unobse ed he e ogenei y and also mo e gene alizable esul s. The e is no
ela ionship be ween he esiduals and he model’s independen a iables in he REM. Howe e , bo h
Fixed E ec s Model (FEM) and Random E ec s Model (REM) ha e some limi a ions when i comes o
add essing endogenei y, which can lead o less eliable es ima ion esul s. The e o e, in his case, he
Table 2. Desc ip i e a iables – he indica o s (FKG and SMOG) o annual epo eadabili y.
Va iable Obs Mean S d. De Min Max
FKG 1,530 3.56 2.67 0.10 10.40
SMOG 1,530 4.34 2.28 3.2 10.8
Figu e 1. The Annual epo eadabili y.
COGENT ECONOMICS & FINANCE 5
Di e ence Gene alized Me hod o Momen s (DGMM) model is employed. In addi ion, no e ha in simila
se ups, endogenous phenomena a e o en encoun e ed. Fu he mo e, he DGMM model employs di e -
encing o elimina e endogenei y issues wi hou ocusing on iden i ying s ic ly exogenous a iables.
The e o e, i can be said ha DGMM is a s aigh o wa d me hod sui able o esea ch da a wi h a small
T and a la ge N. This model is used o add ess he endogenei y, by adding he lagged a iable o he
dependen a iable o he eg ession model and aking he i s di e ence. (see oo no e o a de ailed
explana ion o he mechanism).
1
We also conduc quan ile eg essions a 25%, 50%, 75%, and 95% o examine he e ec o epo
eadabili y on in es men decisions in i ms wi h di e en le els o in es men .
4. Resul s
As men ioned, he eg ession analysis wi h DGMM is used in his s udy o deal wi h endogenei y; how-
e e , he wo models FEM and REM a e also pe o med o compa e wi h he DGMM. Table 4 summa izes
he eg essions esul s o al e na i e models: (1) and (2) a e FEM models, (3) and (4) a e REM models,
Table 3. Desc ip i e a iables – i ms’cha ac e is ics –con ol a iables o he model.
Va iable Mean S d. De Min Max
CAPEX 60 300 0 5000
LEV 0.496 0.408 0.022 8.875
GROWTH 0.057 0.562 −1.000 8.962
SIZE 19.846 1.737 11.249 24.796
Obse a ion ¼1,530
Table 4. The esul o eg essions –FEM, REM an DGMM models: Es ima ion o he ela ionship be ween measu es o
eadabili y (FKG, SMOG) and i ms’in es men s.
(1) (2) (3) (4) (5) (6)
Va iables Fixed e ec model Fixed e ec model Random e ec model Random e ec model DGMM DGMM
LnCAPEX
-1
0.657 0.652
(0.0790) (0.0784)
FKG
-1
−0.0281 −0.0275 −0.0405
(0.0106) (0.0106) (0.0115)
SMOG
-1
−0.0239 −0.0264 −0.0448
(0.0121) (0.0121) (0.0125)
LEV
-1
−0.566 −0.562 −0.405 −0.400 −3.199 −3.113
(0.172) (0.173) (0.161) (0.161) (1.192) (1.195)
GROWTH
-1
0.292 0.291 0.287 0.287 0.221 0.229
(0.0529) (0.0530) (0.0528) (0.0528) (0.0676) (0.0674)
SIZE
-1
0.454 0.440 0.790 0.787 0.412 0.413
(0.134) (0.134) (0.0632) (0.0633) (0.0933) (0.0927)
Cons an 6.334 6.603 −0.456 −0.382 −1.380 −1.298
(2.662) (2.663) (1.261) (1.263) (0.653) (0.640)
Obse a ions 1,229 1,229 1,229 1,229 1,223 1,223
Numbe o i ms 251 251 251 251 251 251
Hausman es 0.000
AR(1) 0.000 0.000
AR(2) 0.803 0.858
Hansen es 0.377 0.388
S anda d e o s in pa en heses.
p<0.01, p<0.05, p<0.1.
1
The ea u e o he DGMM model is o add he lagged a iable o he dependen a iable o he eg ession model. Speci ically, he ini ial
equa ion in DGMM model is as ollows:.
Yi ¼b0þ i
ðÞ
þb1Yi −1þb2Xi þei (2).
Eq (2) is ans o med in o i s -di e ence o m o supp ess po en ial ixed e ec s assumed in panel da a.
DYi ¼b1DYi −1þb2DXi þDei (3).
Whe e:.
i ¼miþei D i ¼miþei
ðÞ
−miþei −1
ðÞ
¼Dei
Taking he di e ence would help elimina e he endogenei y p oblem in he model.
6 N. H. DAU ET AL.
and (5) and (6) a e DGMM models; in each pai o models, ei he FKG o SMOG is he used as he a i-
able p oxied o he epo eadabili y. The Hausman es wi h p- alue ¼0.000 shows FEM is mo e sui -
able han REM. The e o e, co ela ion o esiduals and independen a iables occu s. Wi h p- alue o
AR(1) <0.05 and AR(2) >0.05, he DGMM shows he au oco ela ion is co ec ed. The eg ession esul s
show a consis ency be ween DGMM and FEM o REM models. FKG
-1
and SMOG
-1
a e bo h signi ican
signals o p edic in es men olumes (b
FKG
¼−0.0405 and signi ican a 1%; b
SMOG
¼−0.0448 and sig-
ni ican a 1%). The esul s also show ha LEV
-1
has a nega i e e ec on in es men (b
LEV
¼−3.199 and
signi ican a 1%); GROWTH
-1
has a posi i e e ec on in es men (b
GROWTH
>0 and signi ican a 1%);
SIZE
-1
has a posi i e impac on in es men (b>0 and signi ican ). The FEM, REM, and DGMM eg ession
esul s a e p esen ed in de ail in Table 4.
The esul s indica e ha he mo e di icul he annual epo s a e o ead, he lowe he in es men ol-
umes. In o he wo ds, companies will make he decision o in es mo e when p e ious annual epo s a e
conside ed easy o ead. Wi h he model se up wi h lags in explana o y a iables, he empi ical esul can
be in e p e ed ha he epo s’ eadabili y is a signal signi ican o p edic u u e in es men s o i ms. I
can be showed ha he annual epo ’s eadabili y, whe he i is easy o di icul o ead, may se e as a
signal o a company’s in es men s in he ollowing yea . The e o e, he signaling heo y p o ides a good
explana ion o he ela ionship be ween eadabili y and in es men decisions. By p o iding a eadable
epo , a company demons a es anspa en and easily unde s andable communica ion o in o ma ion.
Consequen ly, s akeholde s a e mo e likely o pe cei e posi i e de elopmen s wi hin he company, as posi-
i e in o ma ion ends o be con eyed mo e clea ly han nega i e in o ma ion. The e o e, he suppo o
s akeholde s o he company’s decisions in he ollowing yea is likely o be highe . As a esul , he com-
pany will ind i easie o inc ease i s in es men s in he nex yea (Cazie & P ei e , 2016,2017; Lim e al.,
2018). In ui i ely, epo s ha a e ha d o ead indica e ha he in o ma ion gi en is no easy o deciphe
and i is di icul o connec o he necessa y in o ma ion (Hudda e al., 2007; Lim e al., 2018); he ambi-
gui y o he wo ding can make in es o s and s akeholde s con used and unce ain abou he pa ame e s
in he epo . This is a nega i e signal holding back he company om making decision o in es mo e in
he u u e (Cazie & P ei e , 2016,2017;Hudda e al.,2007;Lime al.,2018).
In addi ion, le e age has a nega i e impac on in es men s, indica ing ha a highe deb a io makes man-
age s mo e limi ed in in es men . Wi h he isks coming om payables in gene al and loans in pa icula ,
he e a e p essu es on manage s o conside hei in es men s o b ing expec ed i m pe o mance (E ug ul
e al., 2017). The e enue g ow h has no impac on in es men s. This esul indica es ha an inc ease in e -
enue is no a cause o companies’in es men decisions. Finally, o al asse g ow h has a posi i e impac on
in es men s. This esul sugges s ha an inc ease in o al asse s esul s in a highe in es men le el.
I can be seen ha high o low in es men decisions can be di e en ly a ec ed by he eadabili y o
di icul y o eading he epo . We also use quan ile eg essions o elabo a e ou e alua ion o he p e-
dic abili y o eadabili y o in es men decisions in coho s o companies wi h di e en in es men ol-
umes. Wi h quan ile eg ession analysis, he 25% quan iles; 50%; 75% and 95% o he dependen
a iable (in es men decision) a e conside ed in his s udy. The esul s show ha he epo s’ eadabili y
is a sound p edic o o in es men decisions in companies wi h medium and high in es men le els.
Howe e , aking a close look, epo eadabili y is insigni ican as a p edic o o he in es men olume
o companies wi h a low in es men le el. Speci ically, companies wi h in es men olume in quan ile 1
(25%) ha e no ela ionship be ween epo ’s eadabili y and in es men olume (see Table 5).
Table 5. Quan ile eg ession.
(1) (2) (3) (4)
CAPEX q25 q50 q75 q95
FKG
-1
−0.0130 −0.0247 −0.0362 −0.0483
(0.0135) (0.00972) (0.0133) (0.0210)
SMOG
-1
−0.0112 −0.0223 −0.0345 −0.0464
(0.0142) (0.0105) (0.0146) (0.0229)
S anda d e o s in pa en heses.
p<0.01, p<0.05, p<0.1.
COGENT ECONOMICS & FINANCE 7
