Ayuning yas, Eka Sa i; Ha ymawan, Iman
A icle
Risk managemen commi ee and ex ual isk disclosu e
Risks
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Sugges ed Ci a ion: Ayuning yas, Eka Sa i; Ha ymawan, Iman (2022) : Risk managemen commi ee
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Ci a ion: Ayuning yas, Eka Sa i, and
Iman Ha ymawan. 2022. Risk
Managemen Commi ee and Tex ual
Risk Disclosu e. Risks 10: 30.
h ps://doi.o g/10.3390/ isks
10020030
Academic Edi o : Mogens S e ensen
Recei ed: 14 Decembe 2021
Accep ed: 18 Janua y 2022
Published: 1 Feb ua y 2022
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4.0/).
isks
A icle
Risk Managemen Commi ee and Tex ual Risk Disclosu e
Eka Sa i Ayuning yas and Iman Ha ymawan *
Depa men o Accoun ing, Facul y o Economic and Business, Uni e si as Ai langga, Su abaya 60115, Indonesia;
[email p o ec ed].ac.id
*Co espondence: [email p o ec ed].ac.id
Abs ac :
This esea ch examines he ela ionship be ween he isk managemen commi ee and
ex ual isk disclosu e. Tex ual isk disclosu e is measu ed using he use o a isk-con ained one in
he annual epo . We employed empi ical analysis o he Indonesian lis ed i ms o he pe iod 2010
o 2018. The indings o his esea ch sugges ha he exis ence o he isk managemen commi ee
gi es mo e isk disclosu e. This inding implica es ha i ms wi h a isk managemen commi ee will
gi e mo e isk disclosu e, because hey ha e a speci ic commi ee which ha e abili ies conce ning
i m isk. The i s addi ional analysis sugges s ha he esul s a e mo e p onounced o i ms wi hin
he pe iod a e he egula ion o ha e a isk managemen commi ee was applied in Indonesia. We
also make second addi ional analysis o di e en le el o echnology wi hin indus y. The exis ence
o isk managemen commi ee o managing isk disclosu e is mo e p onounced o company wi hin
high le el o echnology indus y. We p o ide se e al con ibu ions o he use s o he inancial
s a emen s such as sha eholde s and o he s akeholde s, especially egula o y bodies in Indonesia.
Keywo ds: isk managemen commi ee; isk disclosu e; one; MD&A
1. In oduc ion
Awa eness o isk managemen is inc easing, due o many ecen co po a e business
ailu es and scandals (Walke e al. 2002). Se e al p e ious s udies ha e shown ha he isk
managemen commi ee has a unc ion o con ol, de ec , and p e en i m isk (Abdullah
and Said 2019;La asa i e al. 2019;Ha ymawan e al. 2021). Fi m isk is di ided in o wo
ca ego ies. They a e he inancial isk and non- inancial isk. Bo h o hese isks a e essen ial
o he s akeholde o be conside ed in hei decision-making. The e o e, companies should
pay balanced a en ion o bo h o hem. P e ious s udies by (Abdullah and Shuko 2017)
p o ed empi ical e idence ha exis ence o a s and-alone isk managemen commi ee is
posi i ely ela ed o isk managemen disclosu e (Abdullah and Shuko 2017). Besides, he
isk managemen commi ee also has an impac on non-exis ence o any inancial c ime
incidence (Abdullah and Said 2019). Ha ymawan e al. (2021) added ha RMC plays a ole
in moni o ing he ac i i ies o he company and p o ides a b oade scope o iden i ying
isks wi hin he company. Howe e , o ou knowledge, he e is lack o empi ical e idence
on how he exis ence o a s andalone isk managemen commi ee a ec s he i m’s isk o
ex ual disclosu e.
As is well known, co po a e disclosu e is one o he c ucial hings and he e o e,
moun ing s udies ha e ocused on examining he quali y o co po a e disclosu e (Ha y-
mawan e al. 2020;Pu a e al. 2020). Resea ch on quali a i e disclosu e has exis ed since he
ea ly eigh ies (F azie e al. 1984) and has con inued o de elop un il now. The quali a i e
disclosu es ha e impo an ules o gi e a wide pe spec i e o and in o ma ion o s ake-
holde s, such as in es o s abou he company, especially in o ma ion ha canno be w i en
in he o m o a numbe . Ad ances in echnology ha e made his opic mo e esea ched.
The con en analysis me hod is easie o use wi h ce ain applica ions o so wa e. Se e al
ecen s udies ha e examined he one in company disclosu e, especially he MD&A epo ,
among o he s (Li 2008;Feldman e al. 2010;Da is and Tama-Swee 2012;Huang e al. 2014).
Risks 2022,10, 30. h ps://doi.o g/10.3390/ isks10020030 h ps://www.mdpi.com/jou nal/ isks
Risks 2022,10, 30 2 o 15
These s udies examined whe he he one o a ious co po a e disclosu es is ela ed o,
o example, he cos o capi al, he ola ili y o e u ns, and analys s’ o ecas s (Ko ha i
e al. 2009), sha eholde li iga ion (Roge s e al. 2011), inancial epo ing e o s (La cke
and Zakolyukina 2012), ea nings quali y (Li 2008), and ma ke p ices (e.g., Hen y 2008;
Li 2008;Feldman e al. 2010;Da is and Tama-Swee 2012). Kah eci (2016) ound ha
he e is a posi i e ela ionship be ween company one and pe o mance. Howe e , he e is
s ill li le esea ch conce ning how in e nal ac o s o a company, such as hei co po a e
go e nance, a ec he quali a i e disclosu e. Fu he esea ch needs o be done o ind ou
how he ela ionship be ween he wo a iables is clea , especially in he case o companies
in Indonesia.
The p epa a ion o annual epo s in Indonesia is egula ed by he Financial Se ices
Au ho i y Regula ion Numbe 29/POJK.04/2016 conce ning Annual Repo s o Go-Public
Companies. In he annual epo , he e a e se e al sec ions ha con ain di e en in o -
ma ion. One o he impo an sec ions is Managemen Discussion and Analysis (MD&A).
MD&A is one pa ha is manda o y o mus be included in he annual epo . This
sec ion speci ically discusses he analysis and managemen ’s iews on he company’s pas
pe o mance and u u e plans. Th ough his epo , in es o s can ind ou he condi ion
o he company om he manage ’s poin o iew. In e ms o con eying in o ma ion,
he e a e se e al hings ha need o be conside ed, one o which is how o w i e a na -
a i e ex . The choice o wo ds and he a angemen o sen ences in a epo will a ec
he mindse and poin o iew o he eade in unde s anding he in o ma ion con ained
he ein (Chung and Pennebake 2011). This is an in e es ing opic o esea ch. The one
ha a ec s he in es o ’s pa adigm in unde s anding in o ma ion will la e ca y o e o
he decision-making p ocess and can a ec he company’s u u e pe o mance.
Based on he Linguis ic Theo y, a g oup o wo ds can gene ally a ec he way eade s
hink. In o he wo ds, he s uc u e and he use o ce ain wo ds in a sen ence in he ex
can a ec he eade ’s pa adigm in in e p e ing he meaning o he ex . In connec ion wi h
his heo y, he e is ano he heo y, namely, he Signaling Theo y, which says ha he way
companies con ey in o ma ion is in luenced by he objec i es o be achie ed, one o which
is o gi e signals o he ma ke . Thus, ha one and eadabili y a e impo an o measu e
he quali y o in o ma ion in a epo .
The one in a epo ex is di ided in o wo ypes, namely, posi i e and nega i e. Posi-
i e leads mo e o company op imism, while nega i e ends o e lec company pessimism.
In his s udy, i will ocus on he nega i e one ha leads o quali a i e isk disclosu e
ollowing p e ious s udies (K a e and Muslu 2013;Bonsall and Mille 2016). Disclosu e o
co po a e isk in p e ious s udies has shown i s e ec on in es o decisions and company
pe o mance (Oye ogba 2019). Risk is usually analyzed using inancial analysis, bu s ill,
less esea ch analyzes isk disclosu e h ough one analysis in epo ing ex s. Mos p e-
ious s udies examined he ela ionship be ween co po a e go e nance and bank up cy
isk (F aile and F adejas 2012;Da a e al. 2016;Manzaneque e al. 2016;See ha aman e al.
2017). Howe e , mos p e ious s udies discussed limi ed samples and examined he e ec s
o se e al i ms’ a ibu es o go e nance (such as boa d size and di ec o independence),
bu no hose speci ic o managing isk. To ill his gap in he li e a u e, we examine he
ela ionship be ween he isk managemen commi ees and bank up cy isk. In his s udy,
he esea che wan ed o examine whe he he exis ence o isk managemen commi ee
a ec s he use o nega i e one as a o m o e bal isk disclosu e.
This s udy uses an obse a ion o 4359 i ms lis ed in he Indonesian S ock Exchange
yea s 2010–2018 and go 2136 samples h ough pu posi e sampling. This s udy employs
o dina y leas squa e eg ession analysis o p o e ou hypo hesis. Ou main inding
sugges s ha i ms wi h a s andalone isk managemen commi ee a e signi ican ly ela ed
o he i m’s ex ual disclosu e. I occu s since he isk managemen commi ee, as pa o a
boa d which is highly conce ned abou he i m’s isk, can disclose mo e isk o in es o s
o ge posi i e eedback. We also ha e se e al addi ional analyses using sub-samples
o he inance indus y and high- ech indus y. Ou indings can be an inpu o policy-
Risks 2022,10, 30 3 o 15
make s ega ding he implemen a ion o s and-alone isk managemen commi ees on
public companies o be e i m isk disclosu e o any ela ed s akeholde s.
The nex sec ion o his pape has he ollowing s uc u e: Sec ion 2will explain he
de elopmen o he hypo hesis; Sec ion 3will explain he sample and a iables used in he
s udy; Sec ion 4will explain he esul s; and Sec ion 5will p o ide conclusions o he s udy.
2. Hypo hesis De elopmen
As echnology de elops, con en analysis me hods a e also g owing. By using he he
ex mining me hod, he cha ac e is ics o a ex can be easily assessed. Se e al p e ious s udies
ha e shown posi i e esul s ha one (Lang and Lundholm 2000;Hen y 2008;Da is e al.
2015;Roge s e al. 2011) can in luence s akeholde economic decisions. The decisions aken
by hese s akeholde s can ce ainly ha e an impac on he company’s u u e pe o mance,
posi i ely o nega i ely. Se e al s udies ha e a gued ha nega i e ones illus a e company
pessimism (Lough an and McDonald 2011;Roge s e al. 2011). Fu he mo e, he nega i e one
is conside ed o con ain isks o in es o s o e he unce ain y o he company’s pe o mance
in he u u e (K a e and Muslu 2013;Bonsall and Mille 2016) which, in his s udy, is called he
isk-con ained one. On he o he hand, he e is esea ch ha s a es ha he e is no ela ionship
be ween he one and pe o mance o he company (Tailab and Bu ak 2018) because acco ding
o he s udy, he inancial s a emen s made by he company a e only a o mali y, wi hou
paying oo much a en ion o he cu en s a e o he company.
Ideally, i he company exposes oo much isk in i s epo s, i will inc ease in es o s’
knowledge abou he isks o he company ha we e no p e iously exposed. In es o s will
conside hese isks when making decisions. Risks ha canno be handled p ope ly can
ha e an impac on he company’s pe o mance in he u u e. Company pe o mance i sel
is a measu e o see he ex en o which he company’s achie emen s a e in good condi ion a
a ce ain ime. (Memon e al. 2012) added ha he company’s pe o mance is a desc ip ion
o he achie emen s ha he company has achie ed wi h he aim o gaining us om
ou side pa ies. In addi ion, in es o s’ economic decisions ha a e less suppo i e can also
ha e an impac on company pe o mance.
The exis ence o a isk managemen commi ee has become mo e impo an since he
pos - inancial c isis, as well as he bank up cy phenomenon in he pas . A wo ldwide
su ey showed ha 85 pe cen o inancial ins i u ions epo ed pe iodic e iews o he
en i y’s asse managemen epo s by hei boa d o di ec o s in 2010, a 12 pe cen inc ease
compa ed o 2008 (Deloi e 2011). This sugges s ha mo e boa d membe s a e cu en ly
ac i e wi hin he company in isk managemen ac ions. To o e come his p oblem, company
boa d membe s began o c ea e new s uc u es in he o ganiza ion o suppo he company’s
isk-moni o ing p ocess (Beasley e al. 2009). Risk managemen is one o he specialized skills
ha businesses need o c ea e be e managemen o ice s who ha e he g ea es esponsibili y
o o e seeing he company’s s a egic policies and ac i i ies, and ha means he g ea es
esponsibili y o con olling he p ope implemen a ion o co po a e isk managemen . The
sys em elies hea ily on he commissione s (KNKG 2012). The isk managemen commi ee
(RMC) can be o med by he Boa d o Commissione s o ensu e ha he implemen a ion o
isk managemen unc ions p ope ly and minimizes he isk o bank up cy.
In Indonesia, he o ma ion o RMC is manda ed o companies engaged in he banking
sec o because his sec o has mo e complex isks compa ed o o he sec o s. Mos o he
academic li e a u e on RMC was also conduc ed in he banking sec o (Aebi e al. 2012;
Hines and Pe e s 2015). Fo o he sec o s, he es ablishmen o he RMC is s ill olun a y.
Howe e , many companies ou side he banking sec o appea o ha e RMCs o imp o e he
quali y o hei isk managemen . B own e al. (2009) showed ha due o he inc easingly
complex business isk condi ions ha also occu in he non- inancial indus y, he e is
a need o co po a e go e nance ha ocuses speci ically on isk managemen p ac ices,
such as h ough he es ablishmen o an RMC. I is hoped ha he o ma ion o a special
commi ee such as he RMC which ocuses speci ically on isk managemen is expec ed o
be illed wi h mo e skilled membe s who ha e in-dep h knowledge o isk managemen
Risks 2022,10, 30 4 o 15
(Choi 2013;F ase and Hen y 2007). The es ablishmen o an RMC can imp o e boa d isk
moni o ing because he RMC can dedica e i s esou ces o e alua ing isk appe i e, isk
p o iling, and alida ing he company’s in e nal con ols (Moo e and B auneis 2008). This
esea ch will show ha he exis ence o a managemen commi ee will be ela ed o i m
ex ual isk disclosu e. I will be highe since he RMC will gi e mo e isk disclosu e and
assessmen , o lowe since he exis ence o RMC can manage he isk disclosu e o mi iga e
he s akeholde ’s isk pe cep ion.
Hypo hesis 1 (H1).
The e is a ela ionship be ween he isk managemen commi ee and isk-
con ained one in he company’s MD&A epo .
3. Resea ch Design
3.1. Sample and Sou ce o Da a
The sample in his s udy co e s he pe iod 2010–2018 and consis s o companies
lis ed on he Indonesian S ock Exchange (IDX). The in o ma ion was collec ed h ough he
company’s annual epo by hand-collec ion and he ORBIS da abase. De ail ega ding he
da a esou ces is a ailable in Table 1. We applied sample selec ion c i e ia o each ou inal
sample. We excluded all o he missing a iables. A e applying hese c i e ia, ou inal
sample included 2136 i m-yea obse a ions.
Table 1. Sample selec ion c i e ia.
Desc ip ion To al
Ini ial obse a ions 4359 obse a ions
Excluded: Fi ms wi h missing da a 2223 obse a ions
Final Obse a ions 2136 obse a ions
We p o ide he sample dis ibu ion o his esea ch in Table 2. O e all, he e a e s ill
big gaps o each company wi hin indus ies which ha e a isk managemen commi ee
and hose which do no . The e a e s ill 70.11% o companies in Indonesia which do no
ha e isk managemen commi ees, al hough he egula ion is al eady applied. Fi ms in
an indus y wi h high complexi y a e mo e likely o ha e RMC o show hei se osi y o
conduc good co po a e go e nance.
Table 2. Sample dis ibu ion.
Indus y RMC Non-RMC To al
N % N % N %
(SIC 0) Ag icul u e, Fo es y and Fishe ies 19 38.00 31 62.00 50 100
(SIC 1) Mining 69 32.70 142 67.30 211 100
(SIC 2) Cons uc ion Indus ies 71 24.40 220 75.60 291 100
(SIC 3) Manu ac u ing 43 22.99 144 77.01 187 100
(SIC 4) T anspo a ion, Communica ions
and U ili ies 56 35.22 103 64.78 159 100
(SIC 6) Finance and Real Es a e 102 35.22 233 64.78 159 100
(SIC 5) Wholesale & Re ail T ade 28 36.36 49 63.64 77 100
(SIC 7) Se ice Indus ies 23 43.40 30 56.60 53 100
(SIC 8) Heal h, Legal, and Educa ional
Se ices and Consul ing 1 11.11 8 88.89 9 100
To al 510 29.89 1626 70.11 2136 100

Risks 2022,10, 30 5 o 15
3.2. Ope a ional De ini ion and Va iable Measu emen
The independen a iable o his esea ch is he isk managemen commi ee (RMC). In
Indonesia, he o ma ion o a isk managemen commi ee is s ill olun a y o companies
ou side he banking indus y. The e o e, some companies ha e RMC and some do no .
We measu e RMC using a dummy a iable, coded 1 i companies disclose he exis ence o
s and-alone RMC, and 0 i o he wise (Abdullah and Shuko 2017;Ya im 2009).
The dependen a iable o his s udy is isk-con ained one da a. We use a lis o
wo ds ha end o be nega i e and ca ego ized as isk (K a e and Muslu 2013;Bonsall and
Mille 2016) which is con ained in he MD&A epo using he ex -mining me hod. Those
isk-con ained ones migh indica e some possible isk o i m pe o mance. In his esea ch,
we ollow he app oach o K a e and Muslu (2013), which was also used by Bonsall and
Mille (2016) o ecognize and con ol he p opo ion o e ms used in s a emen s con aining
isk by looking a how much nega i e one was used in he ex (RISKDISC).
Acco ding o K a e and Muslu (2013), RISKDISC is de ined as he exis ence o isk
sen ences wi h a nega i e one. Fi s , he sen ences a e ca ego ized in o isk sen ences, hen
hose isk sen ences a e selec ed again and ca ego ized as isk disclosu e i hey con ain
a nega i e one. The numbe o nega i e ones om selec ed isk sen ences will be used
as a iables. We p edic ha mo e in ensi e use o nega i e one will be associa ed wi h a
highe cos o deb . The comple e s eps o measu e he nega i e one o con en analysis is
explained in he Appendix B.
Based on p e ious li e a u e, we use se e al con ol a iables (Abbo e al. 2003;
Duellman e al. 2015;Hay e al. 2008;Ka im e al. 2016). The con ol a iables a e he boa d
o commissionai e size (COM); boa d o di ec o size (DIR), he p opo ion o independen
commissionai e (INDCOMM), BIG 4 audi o s using dummy a iables (BIG4), i m sizes
om he na u al loga i hm o he o al asse (FIRMSIZE), i m age om he numbe o
yea s since he inco po a ion da e un il he obse ed yea , i m pe o mance om e u n
on asse s (ROA), i m le e age (LEVERAGE), and loss using he dummy a iable (LOSS).
Be o e analyzing he da a, we winso ized ou inancial a iables a 1% and 99% le els. The
de ail ope a ional de ini ion o a iable is included in Appendix A.
3.3. Me hodology
This s udy uses wo eg ession models, namely, he o dina y leas squa e (OLS) and
OLS, wi h a clus e model app oach by Pe e sen (2009). The esea che s also use yea
and indus y ixed-e ec s o con ol o di e ences in economic condi ions and indus y
cha ac e is ics. The so wa e used in his esea ch is S a a 14.0. To es ou hypo heses, we
use he ollowing esea ch models:
RISKDISC = β0 + β1RMC + β2COM +β3DIR + β4INDCOM + β5BIG4 + β6FIRMSIZE + β7AGE + β8ROA
+β9LEVERAGE + β10LOSS + β11IFE + β12YFE + e (1)
Desc ip ion:
β0−β0 = Coe icien
RMC = Risk Managemen Commi ee (Dummy)
RISKDISC
= Risk Disclosu e (Nega i e Tone)
COM = Boa d o Commissionai e Size
DIR = Boa d o Di ec o Size
INDCOM = P opo ion o Independen Commissionai e
BIG4 = BIG 4 Audi o (Dummy)
FIRMSIZE
= Na u al Loga i hm o To al Asse
AGE = Fi m Age
ROA = Re u n on Asse
LEVERAGE
= To al Deb / To al Asse
LOSS = Fi m Loss (Dummy)
IFE = Indus y Fixed E ec
YFE = Yea Fixed E ec
Cons = Cons an a.
Risks 2022,10, 30 6 o 15
4. Resul
4.1. Desc ip i e S a is ics and Uni a ia e Compa ison
Table 3shows he desc ip i e s a is ics o all a iables used in ou models. Table 3
shows he desc ip i e s a is ics o all a iables used in ou models. The mean alue o
RISKDISC is 3.016. The median alue o RMC is 0, which means mo e han hal o he
obse a ions ha e ze o alue o no isk managemen commi ee. Fu he mo e, he mean
alue o se e al con ol a iables, such as COM is 4.387, DIR is 4.965, INDCOM 0.367,
LEVERAGE 0.527, FIRMSIZE 28.661, AGE 31.361, LOSS 0.198, ROA 6.406, and BIG4 0.426.
Table 3. Desc ip i e s a is ics.
N Mean S d. De Median Minimum Maximum
RISKDISC 1037 20.565 1.226 20.516 17.910 24.334
RMC 1037 0.299 0.458 0.000 0.000 1.000
COM 1037 2.829 6.754 4.000 2.000 8.000
DIR 1037 2.225 4.323 2.197 2.000 9.000
INDCOM 1037 0.367 0.125 0.360 0.000 0.667
LEVERAGE
1037 0.490 0.219 0.482 0.073 1.266
FIRMSIZE 1037 29.023 1.491 28.948 25.401 32.339
AGE 1037 3.371 0.595 3.466 1.386 4.727
LOSS 3505 0.230 0.421 0.000 0.000 LOSS
ROA 1037 4.192 8.745 3.189 −20.313 37.049
BIG4 1037 0.502 0.500 1.000 0.000 1.000
CEOAGE 1037 0.246 0.431 0.000 0.000 1.000
Table 4shows he Pea son co ela ion ma ix among he a iables used in his s udy.
The exis ence o a isk managemen commi ee (RMC) shows a signi ican nega i e ela ion-
ship o isk disclosu e (RISKDISC). This occu ed acco ding o he expec a ions we buil ,
ha he isk managemen commi ee will impac he i m’s isk disclosu e.
Table 4. Pea son co ela ions.
Panel A: F om Va iable RMC o FIRMSIZE
(1) (2) (3) (4) (5) (6) (7)
[1] RMC
[2] RISKDIC 0.170 ***
[3] COM 0.518 *** 0.155 ***
[4] DIR −0.013 0.026 -0.019
[5] INDCOM 0.337 *** 0.068 ** 0.320 *** -0.079 **
[6] BIG4 −0.159 *** 0.216 *** −0.085 *** 0.094 *** −0.201 ***
[7] FIRMSIZE 0.069 ** 0.021 −0.012 −0.048 0.105 *** 0.026
[8] AGE 0.695 *** 0.198 *** 0.604 *** −0.003 0.434 *** −0.121 *** 0.170 ***
[9] ROA 0.094 *** −0.069 ** 0.228 *** −0.026 0.079 ** 0.055 * −0.006
[10] LEVERAGE 0.269 *** 0.032 0.191 *** 0.027 0.157 *** −0.017 −0.178 ***
[11] LOSS 0.061 ** −0.015 −0.054 * −0.096 *** 0.042 −0.067 ** 0.023
Panel B: F om Va iable FIRMSIZE o MTB
[8] [9] [10] [11]
[8] FIRMSIZE
[9] FIRMAGE 0.071 **
[10] OCF 0.175 *** 0.070 **
[11] MTB −0.047 −0.091 *** 0.224 ***
p- alues in pa en heses. * p< 0.1, ** p< 0.05, *** p< 0.01.
4.2. Risk Managemen Commi ee and Risk Disclosu e
Table 5p esen s he esul s o OLS eg ession o es he associa ion be ween he isk
managemen commi ee (RMC) and he isk disclosu e (RISKDISC) o i ms using he one
Risks 2022,10, 30 7 o 15
o he ex wi h all con ol a iables. The exis ence o a isk managemen commi ee in a i m
is posi i ely ela ed o he isk disclosu e, wi h a coe icien o 0.153 and 0.01 signi icance
le el. I means ha he isk managemen commi ee is bene icial o assess and disclose
mo e isk h ough he company’s epo . This esul is in line wi h p e ious esea ch by
Abdullah and Shuko (2017) ha he exis ence o a s andalone isk managemen commi ee
is posi i ely ela ed o isk managemen disclosu e. This esul suppo s he hypo hesis.
Table 5. Risk managemen commi ee and nega i e one.
RISKDISC
RMC 0.153 ***
(2.63)
COM 0.014
(1.10)
DIR −0.020 *
(−0.177)
INDCOMM −0.003 *
(−2.15)
BIG4 0.090 *
(2.20)
FIRMSIZE 0.133 ***
(8.68)
AGE 0.002
(1.30)
ROA −0.005 **
(−2.47)
LEVERAGE −0.006
(−0.12)
LOSS −0.041
(−0.74)
Indus y Fixed E ec Included
Yea Fixed E ec Included
_cons −1.022 **
(−2.48)
2 0.470
2_a 0.464
N2136
-s a is ics in pa en heses. * p< 0.1, ** p< 0.05, *** p< 0.01.
Se e al con ol a iables in his esea ch also showed a signi ican esul . Co po a e
go e nance, including he di ec o size (DIR) and he p opo ion o independen commis-
sione s (INDCOMM) showed a nega i e and signi ican ela ionship o isk disclosu e
(RISKDISC). The company audi o (BIG4) and i m size (FIRMSIZE) shows a posi i e sig-
ni ican ela ionship o i m isk disclosu e (RISKDISC). I indica es ha bigge audi i ms
and bigge companies a e associa ed o highe isk disclosu e. Howe e , i m pe o mance
(ROA) has a nega i e and signi ican ela ionship o isk disclosu e (RISK). I may indica e
ha i ms wi h good pe o mance expose less isk o hei co po a e disclosu e.
4.3. Risk Managemen Commi ee, Risk Disclosu e and Co po a e Go e nance
Fu he mo e, Table 6shows he esul s o he isk managemen commi ee and nega-
i e one mode a ed wi h some go e nance a iables, such as di ec o size, independen
commissione , and i m size. These esul s indica e ha i ms wi h be e co po a e go -
e nance, such as he di ec o size and independen commissione size, s eng hen he
ela ionship be ween he isk managemen commi ee and isk disclosu e, as well as i m’s
size, which indica es ha in a bigge i m, he exis ence o a isk managemen commi ee is
mo e e ec i e han he i m’s isk disclosu e.
Risks 2022,10, 30 8 o 15
Table 6. Risk managemen commi ee, di ec o size, independen di ec o , and i m size.
(1) (2) (3)
RISKDISC RISKDISC RISKDISC
RMC 0.653 *** 0.492 *** 3.561 **
(3.16) (3.99) (2.33)
RMC_DIR −0.095 **
(−2.30)
RMC_INDCOM −0.190 ***
(−2.93)
RMC_FIRMSIZE −0.115 **
(−2.22)
COM 0.015 0.027 ** 0.020
(1.16) (2.10) (1.56)
DIR −0.018 −0.036 *** −0.034 **
(−1.30) (−2.63) (−2.54)
INDCOMM −0.003 ** −0.002 −0.003 **
(−2.11) (−1.20) (−2.08)
BIG4 0.098 ** 0.095 ** 0.090 **
(2.55) (2.48) (2.33)
FIRMSIZE 0.134 *** 0.138 *** 0.150 ***
(7.71) (7.85) (8.34)
AGE 0.001 0.001 0.001
(0.89) (1.02) (0.97)
ROA −0.003 −0.004 * −0.004 *
(−1.62) (−1.95) (−1.77)
LEVERAGE −0.034 −0.045 −0.032
(−0.52) (−0.70) (−0.50)
LOSS −0.004 −0.012 −0.009
(−0.07) (−0.21) (−0.17)
Indus y Included Included Included
Yea Included Included Included
_cons −1.086 ** −1.179 ** −1.472 ***
(−2.25) (−2.44) (−2.96)
2 0.478 0.478 0.477
2_a 0.471 0.471 0.471
N2136 2136 2136
-s a is ics in pa en heses. * p< 0.1, ** p< 0.05, *** p< 0.01.
4.4. Risk Managemen Commi ee, Risk Disclosu e and Indus y Technology
Fo u he analysis, we p o ide an analysis o i ms in a di e en le el o he indus y.
Table 7p esen s he esul s o OLS eg ession in examining he associa ion be ween he isk
managemen commi ee and isk-con ained one be ween ou le els o echnology. Tech 1
is he indus y wi h a low le el o echnology, and Tech 4 is he indus y wi h a high le el o
echnology. All obse a ions in his s udy we e di ided in o he lowes le el o echnology,
which was included in TECH 4 wi h 243 obse a ions, TECH 3 wi h 371 obse a ion, TECH
2 wi h 525 obse a ions, and TECH 1 wi h 1006 obse a ions. Fo sub-sample TECH 4, he
RMC is nega i ely signi ican o isk disclosu e wi h a coe icien o 0.677 and signi ican
le el o 0.05. I indica es ha o i ms in a lowe le el o echnology, isk managemen
commi ees disclose less isk. Howe e , i ms wi h a high le el o echnology in TECH 1
a e posi i ely signi ican , which means ha a high-le el indus y has a highe isk o being
disclosed.
Risks 2022,10, 30 15 o 15
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