172 2019, XXII, 1
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DOI: 10.15240/ ul/001/2019-1-012
In oduc ion
The adi ional in e p e a ion o co po a e
i nance is cha ac e ized by owne ship.
Al hough, hei igh s a e widely dis ibu ed
among indi idual s ockholde s, bu can be
managed by ew manage s. Hence, con l ic
o in e es is a isen among manage s and
sha eholde s and his esul s in an agency
p oblem (Fama, 1980; Fama & Jensen,
1983). A numbe o empi ical s udies also
con i med he owne ship concen a ion o
i ms, especially hose domina ed by ew la ge
owne s o block-holde s (La Po a e al., 1999).
The concen a ed s uc u e o owne ship also
con ibu es owa ds agency con l ic be ween
block-holde s and mino i y sha eholde s.
F om ano he pe spec i e, he block-holde s
can bene i mino i y sha eholde s by hei
ole in moni o ing manage s and also can be
haza dous i hey s i e o achie e hei own
p i a e goals (Shlei e & Vishny, 1997).
The h ee main aspec s o owne ship,
which ha e been widely discussed in he
pas h ee decades, include concen a ed
owne ship by block-holde s, amilies and o he
g oups, manage ial owne ship, and ins i u ional
owne ship. The hi d aspec has gained
impo ance as sha eholding by ins i u ional
in es o s has inc eased in he US om 17%
in 1970 o nea ly 70% in he p e ious decade
(Bushee & Noe, 2000). Meanwhile, in he case
o Pakis an, nea ly 25% o he common s ock is
owned by local and o eign ins i u ional in es o s
(Eas e ly, 2001). Ins i u ional owne ship is
de i ned in he li e a u e as he pe cen age o
i m’s sha es owned by ins i u ional in es o s and
i can also be de i ned as one minus pe cen age
o sha es held by indi idual in es o s (Fi h e al.,
2016). Consequen ly, ins i u ional in es o s play
an e ec i e moni o ing ole in he in es ed i ms.
Ini ially, ea ly esea ch mainly ocused on he
analysis o he ela ionship be ween concen a ed
owne ship and i m pe o mance (McConnell &
Se aes, 1990; Duggal & Milla , 1999). La e on,
he ela ionship be ween ins i u ional owne ship
and di e en domains o co po a e go e nance
ha e opened addi ional esea ch ho izon, i.e.
Ka po e al. (1996), Johnson and G eening
(1999), Mak and Li (2001).
Ins i u ional in es o s ha e di e se
p e e ences o he i ms in which hey in es .
A numbe o s udies ca ied ou o de e mine
he p e e ences o ins i u ional in es o s in
e ms o i ms’ co po a e go e nance and
o he policies. Bad ina h, Kale, and Ryan
(1996) in es iga e he idea ha ins i u ional
in es o s a o s ocks ha ha e highe ma ke
liquidi y and lowe e u n ola ili y. O he s also
con i med ha ins i u ional in es o s alue he
s ocks o companies wi h supe io disclosu e
(Bushee & Noe, 2000), hose ha would pay
cash di idends o epu chase sha es (G ins ein
& Michaely, 2005), and also hose demons a e
be e manage ial pe o mance (Pa ino e al.,
2003). Ne e heless, Cull and Xu (2005) ha e
s essed he ole o ins i u ional in es o s in
in es men decisions, G ins ein and Michaely
(2005) claimed he e ec s o di idend policy
decisions and o he s in le e age o capi al
s uc u e decisions (Bokpin & A ko, 2009;
Chung & Wang, 2014). Mos impo an ly, his
s udy aims a de e mining he simul aneous
e ec s o ins i u ional owne ship on i ms’
s a egic i nancial decisions.
Thus, he in e dependence o i ms’ s a egic
decisions se a p oblem o endogenei y, leading
INSTITUTIONAL OWNERSHIP AND
SIMULTANEITY OF STRATEGIC FINANCIAL
DECISIONS: AN EMPIRICAL ANALYSIS
IN THE CASE OF PAKISTAN STOCK
EXCHANGE
Rabeea Sada , Judi Oláh, Józse Popp, Domicián Má é
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o a causal wo-way ela ionship be ween
hem. Le e age o capi al s uc u e decisions
a e a ec ed by di idend decisions and
hese choices also ha e an in l uence on he
le e age decisions o a i m (Al-Najja & Taylo ,
2008). Howe e , s udies ha e conside ed he
endogenei y be ween ins i u ional owne ship
and payou policy (Chang, Kang, & Li, 2016),
owne ship and i ms’ alue (A za & Nazi ,
2015) and i ms’ pe o mance (Maquiei a,
Espinosa, & Viei o, 2011), his phenomenon
seems o be pa icula ly in e es ing in he case
o he Pakis ani, whe e he le el o ins i u ional
owne ship is high and conside able.
The main pu pose o his s udy is o analyze
ela ionships among ins i u ional owne ship
and he i ms’ s a egic decisions ela ing o
he le e age, he capi al s uc u e, di idend
decisions and ela ed in es men decisions.
This pape is o ganized as ollows. Sec ion II
highligh s p e ious li e a u e and p oposes ou
hypo heses. Sec ion III de ails he sample and
esea ch design used o analysis. Sec ion IV
includes he esul s o empi ical examina ion
and he discussion o i s consequences. Sec ion
V concludes and highligh s he impo ance o
ins i u ional owne ship in i ms’ decision.
1. Li e a u e Re iew and Hypo hesis
De elopmen
The agency heo y sugges s ha op imal
in es o s ha e a s ong in e es in moni o ing
i ms’ managemen capi al s uc u e and
owne ship s uc u e, which suppo i ms o
minimize hei agency cos s (Jensen, 1986).
Agency cos s a e a ibu ed o he a ise con l ic
o in e es . Jensen and Meckling (1976)
iden i i ed wo main ypes o con l ic s, i.e.
con l ic s o in e es be ween he sha eholde s
and manage s, and con l ic s be ween he
sha eholde s and deb holde s. Keeping
manage s’ absolu e in es men in i ms’
cons an , an inc ease in he a io o deb
i nancing inc eases he manage s’ sha e o
equi y and he e o e, i educes he loss om any
con l ic be ween manage s and sha eholde s.
Mo eo e , since he deb equi es he i m o
pay ou cash as a cos o deb , his educes
he amoun o ee-cash a ailable o manage s
and in u n educes he con l ic o in e es .
P e ious li e a u e on ins i u ional owne ship
has p oposed hese solu ions in o de o gain
bene i s by enhancing i ms’ alue (Shlei e
& Vishny, 1997). Ne e heless, ins i u ional
in es o s and deb can be subs i u ed one
ano he as an al e na i e o moni o ing i ms.
This hypo hesis is con i med by a numbe o
empi ical s udies in he li e a u e (Li, Yue, &
Zhao, 2009). Consis en ly, ag eeing wi h Al-
Najja and Taylo (2008), we will p opose ha
he ela ionship be ween ins i u ional owne ship
and i ms’ le e age can be exp essed:
H1: The deg ee o s ock owne ship by
ou side ins i u ions is nega i ely ela ed o he
le e age o he i ms.
Since, Mille and Modigliani (1961) a gued
ha di idend policy does no a ec he alue o
he i m, di e en empi ical s udies ha e been
conduc ed o in es iga e he di idend puzzle.
T uong and Heaney (2007) also epo ed ha
he i ms pay di idends and a e inclined o pay
mo e di idends when hey ha e high le els
o p o i abili y and low le els o in es men
oppo uni ies. The classical agency heo y
pe spec i e holds he iew ha i ms a e likely o
sha e mo e o hei p o i s wi h in es o s when
hey ace lowe moni o ing cos s (Jensen, 1986).
I also holds ha he la ges sha eholde may
educe agency cos s by educing he amoun
o ee cash l ow o manage ial disc e ion by
inc easing i ms’ payou s. Meanwhile, he
li e a u e p o ides some e idence on he
ela ionship be ween ins i u ional owne ship
and he di idend decisions o i ms. Fi h e
al. (2016) and Sho e al. (2002) con i med
a posi i e co ela ion be ween ins i u ional
sha eholding and he di idend payou s o i ms.
G ins ein and Michaely (2005) ound a posi i e
ela ionship be ween sha e epu chases and
ins i u ional holdings. Acco ding o hei i ndings,
i ms ha epu chase mo e sha es a ac mo e
ins i u ional in es men s. Thei esul s also
sugges ha ins i u ional in es o s p e e i ms
ha epu chase sha es egula ly. Based on his
discussion, ou second p oposi ion ega ding
he ela ion be ween ins i u ional owne ship and
di idend is he ollowing:
H2: The pe cen age o s ock owne ship by
ins i u ional in es o s is posi i ely ela ed o he
di idend paymen o he i ms.
Bushee (1998) demons a es ha he
sho - e m ocus o many ins i u ional in es o s
induces some i ms o educe R&D when
ea nings a e expec ed o decline. On he basis
o he in es men ho izon and p e e ences,
ins i u ional in es o s a e classi i ed as
‘ ansien ins i u ions’, highligh ed manage s’
myopic beha io . The o he wo ypes o hese
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ins i u ions a e ‘dedica ed 1 and ‘quasi-indexe ’
ins i u ions. These ins i u ional in es o s ha e
s able owne ship in i ms and a e less ocused
on sho - e m ea nings. The ela ion be ween he
in es men decisions o i ms and ins i u ional
owne ship as p oposed in he li e a u e is no
so s aigh o wa d. Howe e , in es men is one
o he mos impo an aspec s h ough which
ins i u ional owne s can a ec a i m. A posi i e
ela ion be ween in es men and owne ship was
con i med by Pindado and To e (2006), whe eas
Richa dson (2006) epo s ha manage s o
i ms wi h la ge ins i u ional owne ship a e less
likely o o e in es su plus cash, due o he
moni o ing go e nance ac i i ies o ins i u ions.
Conside ing Bushee’s (1998) myopic in es o
hypo hesis o be mo e ele an in he con ex o
Pakis ani ins i u ional in es o s (in e ms o he
sho - e m ho izon and lack o in o ma ion), he
ela ionship is p oposed as,
H3: The pe cen age o s ock owne ship by
ins i u ional in es o s is nega i ely ela ed o
he in es men o he i ms.
Deb and di idend can subs i u e o
complemen one ano he in educing agency
cos s. These kinds o s a egies auxilia y well
i con e gence o in e es is s ong (Roze ,
1982). I he en enchmen hypo hesis o
Fa inha (2002) is e ec i e hese decisions
a e complemen . Belie ing on his, ou s udy
p oposes a nega i e ela ion be ween le e age
and di idends.
H4: The le e age o he i m is nega i ely
ela ed o he di idend.
Some ea ly s udies examined how i ms’
op imum deb p e e ence a ec s in es men
decisions. Smi h and Wa ne (1979) a gued
ha deb can bound a i m’s abili y o employ
an asse subs i u ion, while Be ko i ch and
Kim (1990) discuss ha p ojec i nance and
secu ed deb suppo o esol e in es men
incen i e p oblems. Hackba h, Hennessy
and Leland (2007) indica ed ha placing
bank deb a he op o he i m’s p io i ies
ully exploi s ax shield bene i s o in e es s.
S udying in e ac ions be ween in es men s
and i nancing decisions, hey examined he
idea ha a dynamic ade-o be ween p io i y,
capi al s uc u e and in es men incen i es
yields impo an addi ional insigh s and u he
empi ical p edic ions. Based on he li e a u e
we assumed ha :
H5: Le e age is nega i ely ela ed o i ms’
in es men decisions.
Howe e , he in es men o i ms also
a ec s hei di idend policy decisions.
The ela ionships among he di idend and
in es men decision policies a e e idenced
om he heo e ical backg ound o Mille and
Modigliani (1961). This heo y a gues ha in
a pe ec capi al ma ke , op imal in es men
decisions by a i m a e independen o how
such decisions a e i nanced. This co e heo y
has also an impo an ou come as in es men
decisions should no be de e mined by
di idends, and di idend decisions need no
be a ec ed by in es men decisions. In his
pe spec i e, Fama (1974) p o ided empi ical
e idence o iolence o his heo em. Since
hen, he e is no e idence o an exis ed ela ion
be ween di idend and in es men decisions
ha equi e ea ing hem ia simul aneous
equa ions models (SEM). Fo hose i ms
which ha e g ea in es men oppo uni ies,
paymen o di idends mus be balanced wi h
he long- e m goals o i ms (Mye s & Majlu ,
1984). C u chley e al. (1999) ound a nega i e
wo-way ela ionship be ween di idend and
in es men decisions. An inc eased di idend
can lead o educed unds a ailable o
in es men and hence esul s in a dec eased
di idend p obabili y o he u u e (Cye e al.,
1996). Hence, we can also assume ha :
H6: The di idend is nega i ely ela ed o he
in es men decisions o i ms.
Ou co esponding hypo hesis ega ding
he ela ion among ins i u ional owne ship and
le e age, di idend and in es men decisions
a e summa ized in Fig. 1.
2. Sample and Resea ch Design
The da a used o his s udy is comp ised
o a sample aken om non- i nancial i ms
lis ed on he Pakis an S ock Exchange (PSE).
To al s a is ics o his s udy include all lis ed
i ms in 33 di e en sec o s. A sample o 170
i ms belonging o eigh di e en sec o s we e
conside ed o analysis be ween 1994 and
2014. The selec ion o he sample depends
upon he a ailabili y o all he equi ed da a.
Financial i ms, i ms wi h nega i e equi y and
i ms whose ele an da a is incomple e o
no a ailable a e excluded om his sample.
Mo eo e , ou analyses a e based on annual
equency o da a, in o de o align i nancial
s a emen s esul s and ins i u ional owne ship
a iables. In his s udy, a sec o al app oach is
also used, ollowing King and San o (2008).
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The a iables ex ac ed om he Balance
Shee Analysis (BSA) publica ion o he S a e
Bank o Pakis an (SBP) (2018) include capi al
s uc u e decisions cap u ed by he ollowing
ac o s:
 le e age (LEV), which measu ed by deb o
equi y a io (Hassan & Bu , 2009),
 di idend payou s (DPO), as he a io o
di idend pe sha e o ea nings pe sha e
(A za & Nazi , 2015),
 in es men decisions (INV) measu ed
by he a io o Change in Fixed Asse s o
To al Asse s in place o R&D expendi u es
(Jensen e al., 1992),
 Re u n on Equi y (ROE), as he a io o ne
income o sha eholde s’ equi y (Hillman &
Dalziel, 2003),
 size o i m (Size) equals wi h he na u al
loga i hm o he book alue o o al asse s
is used (Lin & Chang, 2011),
 angibili y (TANG) o asse s is measu ed as
he a io o i xed asse s o he o al asse s o
i m (Liu e al., 2011),
 Sales g ow h (Sales_GR) is calcula ed as
he annual pe cen age change in sales o
a company (Lin & Chang, 2011),
 age o i m (Age) is de i ned as he log o
numbe o yea s elapsed since a i m was
lis ed (Roy, 2015),
 ins i u ional owne ship (INST), as he
pe cen age o sha es owned by ins i u ional
in es o s o he o al numbe o sha es
ou s anding (Michaely & Vincen , 2013). INST
is aken om annual epo s o indi idual
companies, epo ed unde he Code o
Co po a e Go e nance o Pakis an (CCGP),
 and he di idend decisions o i ms a e
cap u ed by di idend yield (DY), as he a io
o he di idend pe sha e o ma ke p ice
pe sha e (B ad o d e al., 2013).
In he me hod iden i i ed o his s udy, he e is
a po en ial causali y o endogenous ela ionship
among le e age decisions, di idend decisions
and in es men decisions. A simple o dina y
leas squa e (OLS) es ima ion o cap u e he
ela ionship among hese a iables will c ea e
biased and inconsis en es ima es, as gi en
by (Demse z & Villalonga, 2001). Hence, he e
is a need o explo e a mo e sophis ica ed
econome ics echnique o analysis. The e a e
di e en ways o add ess he issue o biased
and inconsis en es ima es. One o hem is
2SLS, he o he s a e 3SLS and GMM. 3SLS
has ad an ages o e 2SLS, as wi h he o me
o cap u e c oss equa ion impac s o e o e ms
and he sys em o equa ion is supposed o be
co ela ed in 3SLS (Zellne & Theil, 1962).
Fig. 1: The in e ela ion amewo k among ins i u ional owne ship and s a egic
le e age, di idend and in es men decisions o i ms
Sou ce: own based on he au ho ’s assump ions
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This s udy is based on he 3SLS me hodology
in o de o analyze he simul aneous
de e mina ion o i nancial decisions and hei
possible wo-way causali y. 3SLS is always
p e e ed in e m o he inhe en e i ciency o i s
es ima es o e 2SLS (Kap eyn & Fiebig, 1981).
3SLS is he mos app op ia e echnique o his
da a se i a sys em es ima o is conside ed
a he han one equa ion. This me hod is
designed o cap u e a ela ion whe e equa ions
in a model ha e endogenous a iables as
exogenous. Since some o he explana o y
a iables a e endogenous a iables, he e o
e ms o he equa ions a e co ela ed, which
simply iola es he assump ions o O dina y
Leas Squa e (Bal agi, 2008).
In o de o analyze he impac o ins i u ional
owne ship on a ious s a egic decisions o
i ms, he ollowing eg ession models a e
speci i ed as:
(1)
(2)
(3)
whe e le e age (LEV), di idend yield (DY) and
in es men (INV) a e dependen a iables in
hese equa ions, showing a possible causali y
( wo-way) ela ionship among hem, since hey
also appea on he igh side o he equa ion as
exogenous a iables. (e) ep esen s he e o
e ms o he equa ions 1, 2 and 3, and hey
a e also assumed o be co ela ed. ROE, Size,
TANG, Sales_GR, Size and Age a e addi ional
con ol a iables in hese equa ions, as o e ed
Bokpin and A ko (2009); Chang e al., (2016).
In o de o con i m he obus ness o ou
esul s, he abo e equa ions a e speci i ed wi h
some dummy a iables o cap u ing he c oss
indus y-e ec s (T uong & Heaney, 2007).
Indus y speci i c dummies a e combined wi h
he o mal Code o Co po a e Go e nance o
Pakis an in 2002, and all lis ed companies in
Pakis an should ollow a ull ep esen a ion o
he CCGP. Conside ing he ime e ec s, a ious
yea dummies a e also added o accoun o he
impac o ins i u ional owne ship and s a egic
decisions o e ime.
3. Empi ical Analysis and Resul s
Tab. A.1 epo s in Appendix he desc ip i e
s a is ics o all a iables. This able epo s
he mean o a e age alue, he s anda d
e o o he mean, he median, he s anda d
de ia ion, skewness and ku osis o 1,502
obse a ions. The mean o a e age alue o
LEV is 1.69 wi h a s anda d de ia ion o 1.48.
Le e age alue is highe and i shows a g ea e
eliance o i ms lis ed in he PSE on ex e nal
sou ces o i nancing, as epo ed ea lie by
A za and Nazi (2015). Thus, he a e age alue
o INV is .006%, wi h a s anda d de ia ion o
.00046. The a e age ins i u ional owne ship
in Pakis ani i ms is epo ed as 32.14% o
o al sha es ou s anding wi h a s anda d e o
o 0.63. Ne e heless, in o de o check he
he e oscedas ici y, a ious Whi e es s a e
applied. The esul s o hese es s a e epo ed
in Tab. A.2 (Panel A) and he chi-squa e alues
con i m he p esence o he e oscedas ici y
in ou model. Panel B also he p obabili y o
es s a is ics con i ms he p esence o se ial
co ela ion. The co ela ion be ween he
a iables (Tab. A.3) o he sample selec ed is
analyzed using he Pea son co ela ion. The
esul shows a posi i e co ela ion be ween
ins i u ional owne ship and di idend yield. Thus,
ins i u ional owne ship shows a sligh nega i e
co ela ion wi h le e age, whe eas i seemed
no co ela ion wi h in es men .
The ollowing Tab. 1 epo s he co esponding
esul s a e 3SLS analysis o each models. The
ou comes lead o he ollowing implica ions.
In model 1, he coe i cien o di idend payou s
(DPO) a io (-0.711) is also nega i e and
signi i can a one pe cen . This con i ms he
simul aneous de e mina ion o di idend and
le e age. Consequen ly, we also claimed ha
i ms use le e age and di idend as al e na i e
moni o ing de ices. In o he wo ds, i ms paying
highe di idends i nd deb a less a ac i e sou ce
o i nancing (Ogden & Wu, 2013). Mo eo e ,
i ms wi h highe i nancial cos s a e no eady o
pay di idends. A highe i m le e age will lowe
he po en ial di idend payou o sha eholde s
(T uong & Heaney, 2007).
The le e age o i ms (LEV) is nega i ely
ela ed o ins i u ional owne ship and he esul
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is highly signi i can . This esul shows ha
ins i u ional owne s, ega dless o hei ype,
a e hesi an o in es subs an ial s akes in
i ms ha a e highly le e aged. This nega i e
and signi i can ela ionship also suppo s
he a gumen ha ins i u ional owne s may
ac as a subs i u e o he moni o ing ole o
deb in he capi al s uc u e o i ms (Moh’d
e al., 1998; Chung & Wang, 2014). In his
pe spec i e, he eluc ance o ins i u ional
owne s o in es in highly le e aged i ms
may be due o hei in en ion o a oid isk
(C u chley e al., 1999).
The p o i abili y o a i m is also nega i ely
ela ed o he i m’s le e age, and he coe i cien
is signi i can a 95%. This esul is in line wi h
he pecking o de heo y (Mye s & Majlu ,
1984), sugges ing a nega i e ela ion due o
he eliance o i ms’ in e nally gene a ed unds.
Essen ially, i ms’ size has a posi i e ole in
de e mining he le el o le e age. Consequen ly,
bigge i ms a e mo e le e aged han smalle
ones. The sales g ow h has posi i e and
signi i can esul s, as claimed Al-Najja and
Taylo (2008). These i ndings con adic agency
heo y, suppo ing he nega i e ela ion be ween
Va iables LEV (Model 1) DY (Model 2) INV (Model 3)
Cons an 1.3430*** -0.00467 -0.0001
SE -0.3358 -0.0093 -0.0001
INV -0.0009 -0.0000
SE -0.0010 0.0000
LEV -0.00010 0.0000
SE -0.0002 0.0000
DY 0.0000
SE -0.0005
DPO -0.711*** -0.711*** 0.0744*** 0.0744***
SE -0.1402 -0.1402 -0.0039 -0.0039
INST -0.0041*** -0.0041*** 0.0008* 0.0008* -0.0003
SE -0.0014 -0.0014 0.0000 0.0000 -0.0001
ROE -0.0154*** -0.0154*** 0.0004*** 0.0004*** -0.0000
SE -0.0016 -0.0016 0.0000 0.0000 0.0000
Size 0.1827*** 0.1827*** -.00006 -.0000
SE -0.0261 -0.0261 -0.0007 0.0000
SALES_GR 0.0017** 0.0017** 0.0000 0.0000*** 0.0000***
SE -0.0009 -0.0009 -0.0001 0.0000 0.0000
TANG -0.4372*** -0.4372*** 0.0022 0.0001** 0.0001**
SE -0.1808 -0.1808 -0.0050 -0.0001 -0.0001
Age -0.2489 0.0142*** 0.0142*** 0.0001*** 0.0001***
SE -0.1857 -0.0051 -0.0051 0.0000 0.0000
Adj. R-squa ed 0.1030 0.3213 0.0580
Chi-Sq. 172.29*** 710.87*** 92.70***
Hausman Tes S a is ics: Chi-Sq.= 1.41, P ob.>Chi-Sq.= 0.9941
Sou ce: own based on (S a e Bank o Pakis an, 2018) and au ho ’s own calcula ions
No e: *** deno es 1%, ** 5% and * 10% le el o signi i cance. SE is obus s anda d e o . Model 1, 2 and 3 co esponds
o equa ions 1, 2 and 3 espec i ely.
Tab. 1: Resul s o 3SLS Reg essions Based on Equa ion 1, 2 and 3
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owne ship and g ow h due o ac ha g owing
i ms end no o ans e hei weal h o c edi o s.
Thus, angibili y has a nega i e and signi i can
ela ionship wi h le e age. The nega i e ela ion
can be a ibu ed o he p esence o ins i u ional
o block-holde owne ship which esul s in
close ies wi h lende s, hus educing he need
o mo e colla e al (Deesomsak e al., 2004).
The esul s o second models highligh
ha he coe i cien o in es men (INV) and
deb (LEV) wi h di idend is al hough nega i e,
bu insigni i can in ou models. Thus, he
coe i cien s o ins i u ional owne ship (INST)
a e posi i ely and signi i can ly co ela ed wi h
di idend yield (DY). The eason o inc eased
di idend le els can be he ole o ins i u ional
sha eholde o ing igh s o highe di idends
o enhance manage ial moni o ing (Fa inha,
2002). Thus, one uni inc ease in p o i abili y
a ios inc eased he le el o di idends. This
suppo s ha mo e p o i able i ms wi h ce e is
pa ibus highe le els o ins i u ional owne ship
end o pay mo e di idends han he less ones
(T uong & Heaney, 2007). Examining he
signi i can con ol a iables, only Age shows
a posi i e and subs an ial coe i cien a 1%.
These i ndings consis en wi h he i ndings
o Thana awee (2012) ega ding he i ms’
endency o paying inc eased di idends.
Ne e heless, he ela ionship o ins i u ional
owne ship (INST) and he i m’s in es men (INV),
as sugges ed by he hi d model, is nega i e.
Al hough he esul is s a is ically insigni i can ,
he nega i e coe i cien is in acco dance wi h he
i ndings o Richa dson (2006). The sho e m
ocus o ins i u ional in es o s may cons ain he
manage o educe in es men (Bushee, 1998)
o a oid misp icing caused by disappoin ed
ins i u ional in es o s’ selling.
The posi i e and signi i can ela ion
be ween age and in es men a iables also
p o ides suppo o he same p oposi ion.
The coe i cien o angibili y is signi i can and
posi i e, indica ing ha capi al-in ensi e i ms
a e s ill in he p ocess o expansion. The same
phenomenon is con i med by he signi i can
and posi i e ela ionship be ween sales g ow h
and in es men . The esul s indica e high sales
g ow h equi es he i m o place mo e money
in expansion o p ojec /p oduc ion acili ies.
This consequence co esponds o he i ndings
o Jensen e al. (1992). Howe e , he e is no
e idence o simul anei y in di idend and
in es men decisions o i ms, bu esul s a e
seemed o consis en wi h he i ndings o Fama
(1974).
Tab. 2 demons a es he esul s o
simul aneous equa ions whe e indus y speci i c
dummies a e inco po a ed in o he model. The
omi ed con ol dummy a iable ep esen s
Enginee ing, which becomes a e e ence o
all o he indus ies. All he epo ed esul s
emain he same in e ms o hei sign and
signi i cance, wi h some excep ions. The
coe i cien o age in he i s le e age (LEV)
model becomes signi i can a e he addi ion
o dummies. In o he wo ds, one uni inc ease
in age o i ms seemed o dec ease deb o
equi y a io. The e o e, ageing i ms a e less
le e ed in Pakis an. Thus, he nega i e impac
o ins i u ional owne ship on i ms’ le e age
becomes mo e p onounced a e including
indus y speci i c dummies. O e all esul s a e
consis en wi h bo h analyses, sugges ing ha
he speci i ca ions o ou models a e obus .
The explana o y in l uence o he models has
also inc eased a e including indus y speci i c
a iables.
Va iables LEV (Model 1) DY (Model 2) INV (Model 3)
Cons an 1.104*** -0.0180* -0.00006
SE -0.3623 -0.0101 -0.0001
LEV -0.00007 -0.0000
SE -0.0002 0.0000
INV -0.0006 0.0000
SE 0.0010 0.0000
DY -0.0005
SE -0.0006
Tab. 2: Resul s o 3SLS Reg essions wi h sec o al dummies (Pa 1)
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Va iables LEV (Model 1) DY (Model 2) INV (Model 3)
DPO -0.5715*** -0.5715*** 0.0820*** 0.0820***
SE -0.1447 -0.1447 -0.0040 -0.0040
INST -0.0044*** -0.0044*** 0.0001** 0.0001** -0.0000
SE -0.0015 -0.0015 0.0000 0.0000 0.0000
ROE -0.0147*** -0.0147*** 0.0005*** 0.0005*** -0.0000
SE -0.0016 -0.0016 0.0000 0.0000 0.0000
Size 0.2043*** 0.2043*** -0.0000 -0.000005
SE -0.0286 -0.0286 -0.0008 0.0000
SALES_GR 0.0016* 0.0016* 0.0000 0.0000*** 0.0000***
SE -0.0009 -0.0009 0.0000 0.0000 0.0000
TANG -0.4607** -.4607** 0.0002 0.0001*** 0.0001***
SE -0.1902 -0.1902 -0.0053 -0.0001 -0.0001
Age -0.3422* -0.3422* 0.0135** 0.0135** 0.0053* 0.0053*
SE -0.1919 -0.1919 -0.0054 -0.0054 -0.0001 -0.0001
CHEM -0.1604 -.00431 0.0000
SE -0.1609 -0.0045 -0.0001
CONS -0.2422 -0.0018 -0.0001* -0.0001*
SE -0.2012 -0.0056 -0.0001 -0.0001
PAPER 0.1432 0.0036 -0.000015
SE -0.2423 -0.0068 -0.0001
ENERGY 0.3315 0.0036 -0.0000
SE -0.2067 -0.0058 -0.0001
FOOD 0.5973*** 0.5973*** 0.0112** 0.01120** -0.0001** -0.0001**
SE -0.1606 -0.1606 -0.0045 -0.0045 -0.0001 -0.0001
PERSONAL 0.3197** 0.3197** 0.0170*** 0.0170*** -0.0000
SE -0.1469 -0.1469 -0.0041 -0.0041 0.0000
MISC -0.6593*** -0.6593*** 0.0063 -0.0000
SE -0.2168 -0.2168 -0.0061 -0.0001
Adj. R-squa ed 0.1479 0.3486 0.0711
Chi-Sq. 260.66*** 803.53*** 112.85***
Hausman Tes S a is ics: Chi-Sq.= 1.31, P obabili y > Chi-Sq.=1.00
Sou ce: based on (S a e Bank o Pakis an, 2018) and au ho ’s calcula ions
No es: *** deno es 1%, ** 5% and * 10% le el o signi i cance. SE is obus s anda d e o . Models co espond o he
equa ions (1, 2 and 3) a e inco po a ing indus y dummies espec i ely. CHEM is chemical indus y; CONS is cons uc i-
on and ma e ial indus y; PAPER is pape & boa d indus y; ENERG is uel and ene gy sec o ; FOOD is ood p oduce
indus y; PERSONAL is pe sonal goods indus y and MISC is miscellaneous indus ies.
Tab. 2: Resul s o 3SLS Reg essions wi h sec o al dummies (Pa 2)
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Essen ially, addi ional ime dummies a e
added o cap u e he e ec s o pa icula yea s
a ec s he di idend equa ion. As a esul , he
size o i ms (Size), he sales g ow h (SALES_
GR) and angibili y (TANG), which we e
p e iously insigni i can , a e subs an ial wi h
he di idend model now, as epo ed in Tab. 3.
Namely, i he sales g ow h is inc eased mo e
di idends seemed o pay o s ockholde s.
Howe e , i he e is one uni inc ease in size
and angibili y o i ms less disbu semen a e
pu chased o he owne s. These esul s a e
simila wi h (Lin & Chang, 2011) i ndings.
Gene ally, ou esul s in he case o LEV
and INV ha e less changed and emained
insigni i can in he second and hi d ables,
sugges ing he obus ness o he esul s.
Adjus ed R-squa ed alues o DY and INV
ha e inc eased, as well. A he bo om o each
epo ed ables a e he app op ia ed adjus ed
R-squa ed and Chi-squa e alues. Mo eo e ,
addi ional Hausman es s a e also epo ed
a each able ega ding 3SLS analysis. These
s a is ics a e pe o med o analyze he expec ed
di e ence be ween he coe i cien s using 2SLS
and 3SLS me hods. The epo ed alues o hem
a e 1.37, 1.39 and 0.69 espec i ely. These
coe i cien s a e insigni i can in all models, and
indica ing no signi i can di e ence be ween he
wo models o pa icula se s o sys em (Bal agi,
2008). P e ious s udies (Chang e al., 2016)
also con i med ha he p esence o ou lie s
a ec s he o e all explana o y powe o he
examined model. This 3SLS me hod applied
on he ‘winso ized’ da ase o elimina e he
e ec o ex eme alues esul s in inconsis ency
(Wilson, 1993). A e emo ing hese ou lie s,
he esul s ecen ly show imp o ed explana o y
powe . Howe e , gene al conclusions a e gi en
only i u he de e minan s will be aken in o
conside a ion o de e mine hei e ec s on i ms’
s a egic decision-making. The e o e, he alidi y
o ou esul s is limi ed by he bias caused by he
exclusion o he omi ed a iables o ou models.
Va iables LEV (Model 1) DY (Model 2) INV (Model 3)
Cons an 0.7010* 0.0442*** -0.0006***
SE -0.3699 -0.0096 -0.0001
LEV 0.0001 -0.0000
SE -0.0002 0.0000
INV -0.0011 0.0000
SE -0.0010 0.0000
DY 0.0004
SE -0.0006
DPO -0.8026*** -0.8026*** 0.0759*** 0.0759***
SE -0.1401 -0.1401 -0.0036 -0.0036
INST -0.0049*** -0.0049*** 0.0001*** 0.0001*** -0.0000
SE -0.0015 -0.0015 0.0000 0.0000 0.0000
ROE -0.0152*** -0.0152*** 0.0005*** 0.0005*** -0.0000
SE -0.0017 -0.0017 0.0000 0.0000 0.0000
Size 0.2131*** 0.2131*** -0.0026*** -0.0026*** -0.0000
SE -0.0267 -0.0267 -0.0007 -0.0007 0.0000
SALES_GR 0.0008 0.0000** 0.0000** 0.00000*** 0.00000***
SE -0.0010 0.0000 0.0000 0.0000 0.0000
TANG -0.610 -0.0097** -0.0097** 0.0001** 0.0001**
SE -0.1819 -0.0047 -0.0047 -0.0001 -0.0001
Tab. 3: Resul s o 3SLS Reg essions wi h ime dummies (Pa 1)
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DY LEV INV INST ROE Size TANG S_GR Age DPO
DY 1
LEV -0.21*** 1
INV -0.05* 0.055** 1
INST 0.062** -0.048* -0.013 1
ROE 0.380*** -0.23*** -0.019 -0.006 1
Size 0.108*** 0.094*** 0.094 0.15*** 0.20*** 1
TANG -0.171*** 0.047* 0.045* 0.009 -0.23*** 0.03 1
S_GR 0.063** 0.011 0.22*** 0.009 0.165*** 0.11 -0.022 1
Age 0.092*** -0.04 0.042 -0.014 0.094*** 0.036 -0.17*** 0.01 1
DPO 0.511*** -0.174 -0.029 .061** 0.310*** 0.15*** -0.23*** -0.003 0.02 1
Sou ce: own based on (S a e Bank o Pakis an, 2018) and au ho ’s own es ima ions
No e: Co ela ion is signi i can * a 0.10 le el, ** a 0.05 le el, *** a 0.01 le el
Tab. A.3: Co ela ion ma ix o he examined a iables
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Abs ac
INSTITUTIONAL OWNERSHIP AND SIMULTANEITY OF STRATEGIC FINANCIAL
DECISIONS: AN EMPIRICAL ANALYSIS IN THE CASE OF PAKISTAN STOCK
EXCHANGE
Rabeea Sada , Judi Oláh, Józse Popp, Domicián Má é
The adi ional in e p e a ion o co po a e i nance is cha ac e ized by owne ship igh s a e widely
dis ibu ed among indi idual s ockholde s, bu can be managed by ew manage s and esul ed in
an agency p oblem. The p ima y objec i e o his esea ch s udy is o in es iga e he ela ionship
be ween ins i u ional owne ship and i ms’ s a egic decisions. These s a egic decisions include i.e.
le e age, di idend and in es men decisions. The examined da a is used om 170 non- i nancial
Pakis ani lis ed i ms, cha ac e ized by a la ge pe cen age o ins i u ional in es o s, wi h a mul iple
equi y s ake in di e en i ms ac oss a wide i eld o indus ies. This s udy is also able o show wo
impo an no el ies. Fi s ly, he ac ha p e ious esea che s ha e al eady concen a ed on he
impac o ins i u ional owne ship on indi idual s a egic decisions, as di idend o le e age policies
and se e al unanswe ed ques ions emain. Consequen ly, he impac o ins i u ional owne ship
has explo ed collec i ely on a ious s a egic decisions. Secondly, his s udy also ecognizes he
de e mina ion o s a egic decisions by conside ing he endogenei y p oblem wi h a Th ee-S age
Leas Squa e (3SLS) me hod. Essen ially, he e ec s o ins i u ional owne ship on i ms’ le e age
becomes mo e p onounced a e including indus y speci i c and ime dummies in eg ession models.
Based on he esul s, he case o inc eased ins i u ional owne ship o i ms has a signi i can nega i e
e ec on le e age, and a posi i e e ec on di idend decisions. Hence, ins i u ional in es o s a e
seemed o p e e low le e aged and high di idend-paying i ms. Mo eo e , his s udy has no able
o i nd signi i can wo-way ela ions be ween ins i u ional owne ship and in es men decisions, so
ins i u ional in es o s a he ocus on co po a e go e nance and in e nal con ol o i ms. Indeed,
ins i u ional in es o s should de elop he e i ciency o i ms’ managemen o suppo mo e adequa e
co po a e go e nance policies, and no only o eme ging ma ke s.
Key Wo ds: S a egic decisions, endogenei y, ins i u ional owne ship, 3SLS.
JEL Classi i ca ion: G31, G32, G11.
DOI: 10.15240/ ul/001/2019-1-012
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