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8/11/2019 Hillary Dissertation
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National University of Science and Technology
Faculty of Applied Sciences
DEPARTMENT OF APP!ED MAT"EMAT!#S
An Econo$etric Analysis of the Effects of Macroecono$ic Funda$entals on the Stoc% Mar%et
Perfor$ance
By
Hillary A Mataruka (N006 1187X)
Supervised by Mr. Ciyaka
Su&$itted in partial fulfill$ent of the re'uire$ents of the (achelor of Science "onors Degree in Operations Research and Statistics
June 2009
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ABS!"AC!
!is resear# paper e$a%i&es te 'e&eral relati&sip betee& te be%ark *&dustrial
*&de$ + ,i%babe St#k -$#a&'e a&d %a#re#&%i# +u&da%e&tals i& ,i%babe
+r% 10 t /00.
!e autr utilied 2rdi&ary 3east S4uare %etd i& is a&alysis a&d +u&d ut tat
despite s%e +lu#tuati&s i& te i&dustrial i&de$ sie 105 tis a&alysis i&di#ates tat
te ,S- as bee& per+r%i&' e$#epti&ally ell duri&' te perid u&der revie.
!e %ve%e&ts i& %&etary a''re'ates5 i&terest rates5 i&+lati& rate5 a&d dru't #a&
best e$plai& te re#e&t irease i& te *&dustrial *&de$. However, given the current
macroeconomic climate, which is typically characterized by run-away inflation rate, a
rapid increase in money supply, declining economic growth and socio-political
environment, it is extremely difficult to judge whether the current macroeconomic
conditions, which supports high increase in industrial index, are sustainable. !us5 it
%ay be ise +r te pli#y%akers t take s%e pre#auti&s a'ai&st te risk + d&side
si+t i& st#k pri#es.
!erei& lies te parad$ + ,i%babe s#e&ari. espite te e#&%i# dile%%a5 te ,S-
as bee& re#rdi&' e$#epti&al retur&s. Suld e tere+re dis#ard te idely eld
isd% + psitive #rrelati& betee& a #u&trys e#&%i# per+r%ae a&d te
per+r%ae + its st#k %arket A&d t at e$te&t des %a#re#&%i# variables like
*&+lati& rate5 M&ey Supply a&d *&terest "ates deter%i&e te per+r%ae + te
/
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,i%babe St#k -$#a&'e This particular study )ill atte$pt to ans)er this
'uestion*
#ONTENTS
#"APTER ONE****************************************************************************************************************+
1.0 *N!"29C!*2N.....................................................................................................
1.1 Histry + st#k e$#a&'e.....................................................................................1./ Nature + ,S- eali&'s.........................................................................................:
1.; *-?...........................................................................................8
/.1 *&trdu#ti&............................................................................................................8/./ -#&%etri#s.........................................................................................................8
/.; *&+lati&..................................................................................................................8
/. *&terest rates.........................................................................................................../.: !ereti#al literature..............................................................................................
/.6 -%piri#al literature..............................................................................................10
/.7 "e'ressi& a&alysis..............................................................................................1/
/.7.1 Assu%pti&s 9&derlyi&' "e'ressi& A&alysis.................................................1/7./ Assu%pti&s 9&derlyi&' Multiple re'ressi& A&alysis......................................1/
/.8 Ceptual A&alysis + Multiple li&ear "e'ressi&s...........................................1
/.11 Sluti& !e#&i4ues.........................................................................................../1/.1/ Steps i& Mdel Buildi&'..................................................................................../1
/.1; Ce#ki&' te assu%pti& + te re'ressi& %etd........................................../;
/.1 !esti&' !e
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;.6 ia'&sti# #e#ki&'.............................................................................................;1
;.7 *&+eree..............................................................................................................;1
#"APTER +*********************************************************************************************************************/.
.1 A!A ANA3S*S AN "-S93!S
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#"APTER ONE
2*8 !NTRODU#T!ON
Several e%piri#al i&vesti'ati&s ave bee& #arried ut s as t +i&d ut te deter%i&a&t
variables & te st#k %arket per+r%ae. Mu# e%pasis as bee& put & te i&vestrs
perspe#tive by lki&' at st#k pri#es a&d retur&s t te detri%e&t + e++e#ts +
%a#re#&%i# variables. espite te pr e#&%i# per+r%ae + te ,i%babea&
e#&%y sie 105 te ,i%babe st#k e$#a&'e (,S-) as bee& rated te best
per+r%i&' e%er'i&' st#k %arket5 bt i& ter%s + retur&s & i&vest%e&ts i& 9S llar
ter%s a&d sare pri#e ireases5 surpassi&' ;; ter e%er'i&' st#k %arket tat ere
surveyed by a& A%eri#a& "ati&' A'e&ts5 Sta&dard a&d
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&ly. 2ter st#k e$#a&'es ere subse4ue&tly establised i& @eru a&d Mutare. !ey
ere #lsed i& 1/. !radi&' & te ,S- is 'ver&ed by te ,i%babe St#k -$#a&'e
A#t (#apter /E18). !e a#t sets te ri'ts a&d bli'ati&s + i&vestrs & ,S-.
2*. Nature of 9SE Dealings
!e ,S- deali&' syste% is ttally %a&ual. !radi&' takes pla#e & a #all ver syste%. !is
##urs ti#e a day5 at 000 urs a&d at 1/00 urs5 M&day t riday e& st#k
brkers %eet at te ,S- +lr. Buyi&' a&d rders are satis+ied at tese ti%es. !e
st#kbrkers e&sure tat all tra&sa#ti&s are re#rded i& teir tradi&' bks. -a# pa'e i&
te bk is #arb&ied t %ake t r %re #pies. !e tradi&' sip is te& passed &t
,S- represe&tative +r #leari&'.
2*/ Purpose of the Stoc% E1change in 9i$&a&)e
A +u&da%e&tal prble% is best t all#ate s#ar#e e#&%i# resur#es available i& a&
e#&%y. Be#ause e#&%i# resur#es are s#ar#e5 tey suld be used as prdu#tively as
pssible. !is e&sures e#&%i# e++i#iey i& te syste%.
!e rate + e#&%i# 'rt depe&ds & te rate + #apital +r%ati& by te private
se#tr. !is als depe&ds & i&vest%e&t by prdu#ers + e#&%i# 'ds i& %a#i&ery5
buildi&'s5 +a#tries a&d skilled labr trai&i&' (u%a& #apital +r%ati&). !e ,S- is able
t +a#ilitate te dire#ti& + savi&'s t te #%peti&' i&vest%e&t pprtu&ities. Capital
+r%ati& by te publi# se#tr re+ers t i&vest%e&t i& te i&+rastru#ture + te e#&%y
su# as airprts5 e&er'y pla&ts5 spitals5 railay li&es5 rads a&d u&iversities.
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Be#ause + te s#ar#e supply + savi&'s5 te &eed t deter%i&e at #apital pr=e#ts are
t be +i&aed +r% te li%ited +u&ds is + vital i%prtae. *t is esse&tial tat #apital be
dire#ted t tse prdu#ers are 'i&' t use it %st prdu#tively. Sie te ,S-
#reate value +r a #%pa&ys sare5 bt te #%pa&y a&d te i&vestr #a& #al#ulate a
+i&aial retur& r #st i+ te #%pa&y %akes a& additi&al issue + sares t +i&ae its
#apital develp%e&t pla&s.
As part + its i&ter&al #&trls5 te ,S- %ai&tai&s a ti't #&trl ver te a#tivity +
4uted #%pa&ies a&d is able t de%a&d a& e$pla&ati& +r a&yti&' tat %i't i&di#ate a
treat & te viability r per+r%ae + te #%pa&y.
!e ,S- is tere+re able t satis+y te &eed +r prte#ti& a'ai&st a&y +i&aial +ailure
+r te i&vest%e&t %ade by te publi# r a&y i&ability t %eet bli'ati&s5 a&d tis
e&da&'ers #&+idee & te part + i&vestrs.
2*+ Pro&le$ State$ent
*t is vieed tat e& a #u&try is e$periei&' a& e#&%i# b%5 its st#k %arket
+lurises r a rise i& e4uity pri#es is e$perieed5 but e& te #u&try is +a#ed it a
re#essi&F te st#k %arket per+r%ae eake&s (Si&' a&d ?eisse5 18). espite
deterirati&' e#&%i# per+r%ae5 te ,S- as bee& as bee& re#rdi&' e$#epti&al
retur&s. !is parado1led t te #%pilati& + tis pie#e + rk t i&vesti'ate te
e++e#ts + %a#rDe#&%i# +u&da%e&tals & te st#k %arket per+r%ae i& ,i%babe.
Als te as#ertai&%e&t + te real relati&sip betee& i&dustrial i&de$ a&d tese everD
#a&'i&' variables is very vital i& pli#y +r%ulati& a&d is te essee + tis study.
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2*7 Ai$ of the Study
! %del te dy&a%i#s + %a#re#&%i# +u&da%e&tals a&d tey deter%i&e st#k
%arket per+r%ae (i&dustrial i&de$).
2*: O&;ectives of the study
1. ! deter%i&e te (e#&%etri#) relati&sip a&d dire#ti& + #ausality betee&
i&dustrial i&de$ a&d te %a#r e#&%i# variables.
/. ! a&alye te beavir + st#k pri#es i& relati& t %a#rDe#&%i# variablesF i.e.
%&ey supply 'rt (MS@)5 i&+lati& rate (*N3) a&d i&trest rates (*N!).
;. ! prvide su%%ary & te relati&sip tat e$ists betee& st#k %arket
per+r%ae a&d %a#rDe#&%i# e&vir&%e&t.
. ! esti%ate te e#&%etri# %del tat #uld be used t predi#t te i&dustrial i&de$
tre&d.
2*< "ypothesis
!ere is a psitive relati&sip betee& st#k %arket per+r%ae a&d %a#re#&%i#
+u&da%e&tals.
2*- Organi=ation of the study
!e rest + te paper pr#eeds as +lls. Capter revies te perti&e&t tereti#al a&d
e%piri#al literature. Capter ; utli&es te %etdl'y t be used te e%piri#al result
prese&tati& a&d data a&alysis is d&e i& #apter . !e paper e&ds by %aki&' a#ade%i#
ar'u%e&ts a&d +i&di&'s & te e++e#ts + %a#re#&%i# +u&da%e&tals & te st#k
%arket per+r%ae i& #apter :.
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#"APTER T,O
.*8 !TERATURE RE0!E,
.*2 !ntroduction
*& tis #apter te autr revies teries a&d ter studies tat ave bee& #arried ut i&
te si%ilar +ield. irstly5 e de+i&e key rds a&d =usti+i#ati&s + te #se& variables as
tey a++e#t i&dustrial i&de$ i& a develpi&' #u&try like ,i%babe.
.*. Econo$etrics
-#&%etri#s is a #%bi&ati& + e#&%i# tery5 %ate%ati#al e#&%i#s a&d
statisti#s but #a& &t be redu#ed t a&y + its #&stitueies.
!ere are tree %ai& 'als + e#&%etri#sE
re#asti&' G 9si&' te &u%eri#al esti%ates + te #e++i#ie&ts i& rder t +re#ast te
+uture values + te e#&%i# %a'&itudes.
A&alysis G testi&' + e#&%i# tery
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"ate + i&+lati&
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brri&' als rises. !ere is %i$ed skepti#is% abut ter i&vest%e&t su# as %&ey
%arket due t vlatility a&d uertai&ty + retur&s.
3evi&e a&d ,ervs (18) yptesis purprts tat +i&aial liberaliati& as be&e+i#ial
e++e#ts & e#&%ies + develpi&' #u&tries be#ause real depsit rates are alled t be
ireasi&'ly psitive iti& te ra&'e + #&duit e++e#t i.e. %re +i&aial savi&'s are
#lle#ted5 i&vest%e&t is ireased5 all#ative e++i#iey + #apital %arkets is ireased
a&d 'rt results. !e u&derlyi&' priiple is tat a& irease i& i&trest rates ill %ake
savers save %re a&d te savi&'s ill be #a&&eled i&t i&vest%e&t. *& tis #&te$t Sa
said +i&aial se#tr re&der a valuable servi#e i& leri&' te real #sts t i&vestrs.
.*: E$pirical literature
Breede& (17) re#'&ied tat &t &ly as te st#k %arket ireased relative t te
e#&%y but als it appears tat te i&terrelati&sip betee& te t as stre&'te&ed.
*t as alays bee& re#'&ied tat te st#k %arket re+le#ts t s%e e$te&t te 'i&'s &
i& te rest + te e#&%y.
Mre re#e&tly ever tere as bee& idespread re#'&iti& tat dra%ati# eve&ts i& te
st#k %arket are likely t ave a substa&tial i%pa#t up& te ider real e#&%y a&d it
as be#%e appare&t tat %a#re#&%i# pli#y %akers are payi&' #&siderable
atte&ti& t st#k %arket i& teir evaluati& + te e#&%y task i# +r%s part + te
pr#ess + +r%ulati&' %&etary pli#y. !e tre&d is due5 at least i& part t e$isti&'
evidee su''esti&' tat st#k pri#es te&d t lead e#&%i# a#tivity (e.'. a%a 105
Ce& et al 11). !e 'ri&' i&terest i& te relati&sip betee& a#tual a&d arra&ted
+ +u&da%e&tal sare pri#es.
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!suysi ! (/001)5 a&alyed te 'e&eral relati&sip betee& st#k pri#es a&d
%a#re#&%i# variables i& ,i%babe5 did a study tat is s parti#ular t ,i%babe. He
&ted tat by usi&' errr #rre#ti& %del t st#k retur&s s tat te relati&sip
betee& st#k retur& a&d 'rt + %&ey a&d treasury bill rates as bee& 4uite stable
sie 105 e$#ept duri&' te perid + partial #apital a##u&t liberaliati&. A& a&alysis
+ i&dividual st#k retur&s i&di#ates tat te ,S- assi%ilates #a&'es i& te
%a#re#&%i# variables 4uite #&sta&t.
!e study priipally used se%iDa&&ual series + brad %&ey (M;)5 0Dday !reasury bill
rates a&d te t series tat are relatively btai&able a&d satis+y te #&diti& i& %a&y
#u&tries +r pr$y +r #rprate i%e stea%s a&d dis#u&t rate. !e sa%ple perid
as set +r% te +irst al+ + 10 t te se#&d al+ + /00 s as t #ver te +ull perid
i&trest rate liberaliati&. A u&it rt sed tat %&ey supply a&d st#k i&de$ are #
i&te'rated + rder t a&d !B + rder &e.
*t suld be &ted5 ever5 tat te su##ess+ul +uti&i&' + a&y e#&%y de%a&ds te
%biliati& + #apital resur#es available a&d teir prdu#tive utiliati& i& te
develp%e&t + all se#trs + te e#&%y. *& ,i%babe5 it is presu%ed tat te ,S-
plays te rle + raisi&' +u&ds betee& e&trepre&eurs a&d te i&vesti&' publi#.
!e survey #&du#ted by Sta&dard a&d
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r% te abve illustrati&5 it is #rystal #lear tat ,S- as bee& per+r%i&' e$#epti&ally
ell as s& i& te 'rap bel.
9SE Perfor$ance Since 2444
0
/00000
00000
600000
800000
1000000
1/00000
1NN1...
;N//N1...
6N8N1...
8N/:N1...
11N:N1...
1N/:N/000
N6N/000
6N/7N/000
.N8N/000
11N/1N/000
/N7N/001
N/:N/001
7N10N/001
.N/1N/001
1/NN/001
/N1.N/00/
:N8N/00/
7N1.N/00/
10N;N/00/
1/N16N/00/
;NN/00;
:N/0N/00;
8N8N/00;
10N/;N/00;
1N.N/00
;N/;N/00
6N.N/00
8N/N/00
!ndustrial!nde
0
:0000
100000
1:0000
/00000
/:0000
Mining!nde
*&dustrial *&de$ Mi&i&' *&de$
espite te 'd per+r%ae by ,S-5 te e#&%y as bee& deterirati&'. ,i%babe
as bee& e$periei&' ars e#&%i# a#tivity i# #ara#teried by i' i&+lati& rate
i# rea#ed a& all ti%e i' + 6//.8 i& a&uary /00 (CS2 G ebruary /00)5
+rei'& #urrey srta'es5 u&e%ply%e&t l levels + prdu#ti&5 ever ireasi&'
prdu#ti& #st a&d de#li&i&' 'rt rate.
.*< Regression analysis
.*
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.*
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b1 is #alled te #e++i#ie&t +x15 b/ is te #e++i#ie&t +x/5 a&d s +rt. !e #e++i#ie&t
+ ea# i&depe&de&t variable tells us at relati& tat variable as it y5 te depe&de&t
variable5 when all the other independent variables are held constant. S5 i+ b1 is i' a&d
psitive5 tat %ea&s tat i+x/5x; a&d s & up tx& d &t #a&'e5 te& ireases i&x1
ill #rresp&d t lar'e ireases i&y.
.*-*/ Regression Diagnostic
!is is te %st i%prta&t tl i& te %del +r%ulati&' usi&' Multiple 3i&ear
"e'ressi& (M3") a&d it e&tails te ri'rus #e#ki&' + te abve %e&ti&ed
assu%pti&s t see eter tey ave &t bee& vilated a&d t asses te a##ura#y + te
#%putati&s + re'ressi&s + re'ressi& a&alysis. Ce#ki&' te beavir + te residual
usually des tese dia'&sti#s.
i. Multiple li&ear re'ressi& a&alysis builds & u&ivariate a&d bivariate a&alysis.
!is is +lled by a des#riptive statisti#s a&d bivariate a&alysis i& i# te
relati&sip betee& te resp&se a&d te e$pla&atry variables are +urter e$a%i&ed.
2e tis i&+r%ati& as bee& #%plied5 te relati&sip betee& several e$pla&atry
variables a&d resp&se variables #a& be +urter e$plred. Multiple re'ressi&s ill
prvide te i&depe&de&t #&tributi& + ea# e$pla&atry variable t te predi#ti& +
te ut#%e ile #&trlli&' +r te i&+luee +r te i&+luee + te ter
e$pla&atry variables.
ii. Multiple li&ear re'ressi&s e$plre te value + te i&depe&de&t variable as
depe&de&t & several i&depe&de&t variables.
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iii. *& additi& t des#ribi&' te relati&sip betee& te i&depe&de&t a&d te
depe&de&t variables5 %ultiple re'ressi&s #a& be used t =ud'e te relative i%prtae
+ di++ere&t i&depe&de&t variables by #%pari&' teir tDratis.
iv. Cate'ri#al variables #a& be iluded i& te re'ressi& e4uati& it values like
01.!is is a& adva&ta'e be#ause &e #a& lk at te pssible variati& i& ut#%e i&
te presee r absee + a #ate'ri#al variable.
!us e als #e#k te beaviur + te residuals t d te dia'&sti#s.
.*-*+ Residual Analysis
A %del is satis+a#try i+ &&e + its assu%pti&s are ('rssly) vilated. !us be+re a
%del #a& be used t %ake i&+erees it %ust be sub=e#t t dia'&sti# #e#ki&' +r %del
ade4ua#y. *+ te assu%pti&s + re'ressi& a&alysis ld te beavir + te residuals
btai&ed a+ter +itti&' te %del suld &t deviate +r% tat + te %del errrs. !e
essee + tis a&alysis is t see i+ -(e=) 0 a&d -(e ) (ere is pltti&' +
residuals a'ai&st +itted values #e#k i+ te assu%pti&s + li&earity5 i&depe&dee5 e4ual
variae a&d &r%ality5 tat is 5 all basi# assu%pti&s + 'e&eral li&er %del. !e plt
suld be #ara#teried by s%all residuals it & appare&t stru#ture r patter&.
C&stru#ti&' te ist'ra% + residuals #a& be used t #e#k te assu%pti&s +
&r%ality. !e plt + te residuals suld s a& apprpriately &r%al distributi&
#urve it %ea& er.
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.*-*7 Autocorrelation
!is is a situati& ereby tere is a &&Der #rrelati& betee& su##essive values +
te sa%e variables r series5 s%eti%es re+erred t as serial #rrelati&. *t is te
relati&sip5 &t betee& t (r %re) di++ere&t variables but betee& te su##essive
values.
.*-*: Sources of Auto#orrelation
1. MisDspe#i+i#ati& + te +r% + te %delE
*+ e ave adpted a %ate%ati#al +r%5 i# di++ers +r% te true +r% + te
relati&sip5 tere %ay s serial #rrelati&. r e$a%ple i+ e ave #se& a li&aer
+uti& ile te true relati& betee& a&d Xs is + #y&i#al +r%5 te values + e ill
be te%prarily i&depe&de&t.
/. 2%itted e$pla&atry variablesE
*+ aut #rrelated e$pla&atry variables su# as #y#li# variables are %itted r e$#luded
+r% te re'ressi& %del te& tey are absrbed i& te errr ter%55 i# ill te& be
als be aut #rrelated.
;. Misspe#i+i#ati& + te true ra&d% ter% E
*t %ay ell be e$pe#ted i& %a&y #ases +r te su##essive values + te true e t be
#rrelated.
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.*-*- Assu$ptions
*& te re'ressi& #&te$t te #lassi#al li&ear %del assu%es tat aut#rrelati& des &t
e$ist i& te disturbaes5 5 (errr ter%) tat is - (ei5 e=) Q 0 +r i Q =. *+ tere is
depe&dee e ave aut#rrelati& tat is - (ei5 e=) Q 0 +r i Q =.
.*-*4 "etrocedasticity
!is is a situati& ere te variae + te errr ter%s are u&e4ual. !e presee +
Hetr#edasti#ity i& te %del i%plies te +lli&'E
D!ere is a& i&tera#ti& e++e#t betee& a %easured i&depe&de&t variable a&d a&
u&%easured i&depe&de&t variable &t i& te %del r s%e i&depe&de&t variables are
skeed ile ters are &t.
D-rrr variae / is u&deresti%ated by te rdi&ary least s4uares esti%ati&.
D!e esti%ated %del as l +re#asti&'.
!ere+re e&ever tere is aut#rrelati& a&d eters#edasti#ity i& errr ter%s all
i&+eree5 &a%ely esti%ati&5 yptesis testi&' a&d +re#asti&' %ust take i&t a##u&t
te abve e++e#ts +r te #lusi&s t be valid. ?e& etrs#edasti#ty is ide&ti+ied &
te basis + a&y test5 te apprpriate sluti& is t tra&s+r% te ri'i&al %del i& su# a
ay as t btai& a +r% tat as a #&sta&t variae. !e ad=ust%e&t + te %del
depe&ds & te +r% + te relati&sip betee& te variae a&d te values + te
e$pla&atry values ($).
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*& 'e&eral te tra&s+r%ati& + te ri'i&al %del #&sists + dividi&' te ri'i&al
relati&sip by te s4uare rt + te ter% resp&sible +r etrs#edasti#ity.
.*4 #auses of "etroscedasticity
1. MisDspe#i+i#ati&E
Hetrs#edasti#ity due t %isspe#i+i#ati& by e$#lusi& + i%prta&t variables5 r by
assu%i&' a li&ear relati&sip e& i& +a#t a &&Dli&ear relati&sip e$ists is 4uite
#%%&. !e sluti& t te prble% is si%ply #rre#ti&' te spe#i+i#ati&.
/.ata !reat%e&tE
ata %a&ipulati& su# as data a''re'ati& a&d 'rupi&' te#&i4ues te&d t prdu#e
%arked eter'e&eity.
;.ata #lle#ti& pr#eduresE
Sa%pli&' pr#edure su# as #luster sa%pli&' #a& easily 'e&erate u&e4ual variaes.
. Ad%i&istratve i&ter+ereeE
S%eti%es statisti#al data is i&ter+ered it s tat s%e +i'ures are #a&'ed s as t
%ake te% appear lar'er r s%aller ta& at tey really are. Satisti#al a#ts a&d teir
e&+r#e%e&ts #a& result i& %arked di++eree i& data5 espe#ially +r data #lle#ted
iti& di++ere&t perids. !ere+re it is &t alays sa+e t assu%e tat errr ter%s are
%'e&eus ver all e#&%i# u&its bei&' bserved.
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.*28 Multicolinearity
!is is te presee + li&ear relati&sip a%&' te e$pla&atry variables. As a result +
te st#asti# &ature + %st re'ressrs #rrelati& a&d i&terrelati&sips are bu&d t
e$ist a%&' te% %aki&' %ulti#lli&earity i&ere&t i& %st e$pla&atry variables. *t as
te e++e#t + %aki&' te &r%al e4uati& X1X X1 i&deter%i&ate> tat is it5 be#%es
i%pssible t btai& &u%eri#al values +r para%eter a&d te least s4uares %etd
breaks d& sie te %%e&t %atri$ X1X is te& si&'ular r && i&vertible. ?e& a&y
t e$pla&atry variables are #a&'i&' &early te sa%e ay it be#%es e$tre%ely
di++i#ult t establis te i&+luee + ea# &e re'ressr5 say Xi & te depe&de&t variable
separately. !e presee + %ulti#lli&earity #a& be dete#ted by a&alyi&' te
re'ressi& results +rE
a) Sta&dard errrs + para%eter esti%ates
b) Hi' partial #rrelati&
#) Hi' " s4uared statisti# i# %easures te prpsiti& + variati& #aused by
te %del i& #ases ere "/ "e'ressi& su% + s4uares (SS-)!tal su% +
s4uares (SS!). *+ "/ is i& e$#ess + 0.8 te test i& %st #ases ill re=e#t te
yptesis tat te partial slpe #e++i#ie&ts are si%ulta&eusly e4ual t er5 but
i&dividual tDtests ill s tat &&Dr very +e + te partial slpe #e++i#ie&t are
statisti#ally di++ere&t +r% er.
d) 3 t statisti# values
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e) Se&sitivity + para%eter esti%atesDi+ a +e bservati&s are drpped a&d reD
esti%ati& + te %del yields si'&i+i#a&tly di++ere&t para%eter esti%ates tis
#uld i&di#ate te presee + %ulti#lli&earity.
.*28*2#auses of Multicollinearity
1) 9se + la''ed variables
!e use + la''ed variables su# as tD1 re'ressrs is & #%%& i& %a&y studies
a&d as 'e&erally 'ive& satis+a#try results i& %a&y resear#ers. Hever te risk +
i&trdu#i&' %ulti#lli&earity is i'er e& tese la''ed variables are used. !us
#auti& %ust be e$er#ised e&ever la''ed variables are used.
/) CDi&te'rati&
!is is ere e#&%i# variables %ve t'eter ver ti%e a&d appare&tly is te %ai&
#ause + %ulti#lli&earity. -#&%i# variables are +te& i&+lueed by te sa%e
+a#trs s tat te variables s te brad patter& + beaviur ver ti%e. r
e$a%ple5 e#&%i# b%s a++e#t a &u%ber + e#&%i# variables5 i# te& te&d t
#a&'e5 tat is te irease r de#rease t'eter altu' s%e variables %ay la'
bei&d (r lead) ter.
;) 3a#k + e$peri%e&tal #&trl
3a#k + e$peri%e&tal #&trl5 i& parti#ular ad%i&istrative i&ter+eree is a
+u&da%e&tal #ause + %ulti#li&earity.
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#) !e %ate%ati#al +r% + te %del be it li&ear r && li&ear (s#atter plts are
used t deter%i&e te +r%)
/) -sti%ati&
A+ter te +r%ulati& + te %del5 esti%ates + its para%eters by apprpriate %ea&s are
+u&d.
;) ia'&sti# Ce#ki&'
2e te %del as bee& esti%ated5 its ade4ua#y suld be evaluated usi&' statisti#al
tls su# as 'd&ess + +it tests5 'e&eral likelid tests a&d te Bartletts tests be+re
i&+eree su# as +re#asti&' #a& b d&e.
) . *&+erei&'
!e +i&al sta'e is #er&ed it %aki&' i&+eree a&d r evaluati& + te +re#asti&'
validity + te %del. !e %dels +re#asti&' per %ust be tested be+re te %del #a&
be used t %ake real +re#asts
.*2/ #hec%ing the assu$ption of the regression $ethod
"e'ressi& dia'&sti#s are te#&i4ues tat are e%plyed t #e#k i+ te assu%pti&s are
&t vilated a&d t assess te a##ura#y + te #%putati&s + re'ressi& a&alysis.
Ce#ki&' te beaviur + te residuals usually des tese dia'&sti#s.
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.*2+ Testing The Para$eters of the Model
A+ter esti%ati& te para%eters + te %del are tested +r teir ade4ua#y a&d
%ate%ati#al plausibility. !ere are several tests tat #a& be used a&d te #i#e + te
test is usually deter%i&ed by te ease t use te test a&d relevae + te test t te
%del. !e tests t be used i& te pr=e#t are as +llsE
1) ?ald !est
!is test is used t test i+ tere is a&y li&ear relati&sip betee& variables. !is test is
available & -D>ies S+tare pa#ka'e. !e test is #&du#ted u&der te +lli&'
yptesisE
H0 E R 0 >s H1 E R Q 0
H0 is re=e#ted e& te 'ive& prbability is e4ual t er a&d i+ te #iDs4uared a&d te
Dvalues are te sa%e.
.*27 Model Appropriateness
*& testi&' te para%eters e is t s tat tere is a li&ear relati&sip betee& te
depe&de&t variable a&d te i&depe&de&t variables. !ere is tere+re &eed t assess te
4uality + te %del +it a&d te #riteria +r =ud'i&' te apprpriate&ess + a %del #a& be
d&e usi&' te %dels bel.
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.*2: R. #oefficient of Deter$ination
!e #e++i#ie&t + deter%i&ati& is te prprti& + variability tat is a##u&ted +r by
te si%ple re'ressi& li&e. *t %easures te #&tributi& + re'ressr variables i&
deter%i&i&' te resp&se variable. *t is a s#ale +ree &u%ber tat %easures te stre&'t +
te li&ear relati&sip betee& te depe&de&t a&d te i&depe&de&t variable. *t #a& be
%easured usi&' te +r%ula bel
"/ SS"SS!DDDDDDDDDDDDDDDDDDD e4uati& (1)
.*2< #orrelation
Crrelati& is a %etd used t %ake i&+erees abut te de'ree + li&ear a&d ass#iated
betee& t ra&d% variables X a&d e& tey ave a =i&t distributi&. !e
para%eters + te distributi& are te prdu#t %%e&t #rrelati& #e++i#ie&t r =ust te
Crrelati& Ce++i#ie&t. *t is a di%e&si&less 4ua&tity tat lies betee& G1 a&d P1
ilusive.
.*2- Root Unit Test
heoretical bac!ground for "ugmented #ic!ey-Fuller ("#F) est
! illustrate te i#key uller tests5 #&sider +irst a& A"(1) pr#essE
P TtD1PUt
?ere a&d T are para%eters a&d is assu%ed t be ite &ise. is a stati&ary series i+
D1VTW1. *+ T15 y is a &&Dstati&ary series (a ra&d% alk it dri+t)5 i+ te pr#ess is
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started at s%e pi&t5 te variae + y ireases steadily it ti%e a&d 'es t i&+i&ity. *+
te abslute value + T is 'reater ta& &e5 te series is e$plsive. !ere+re te
yptesis + a stati&ary series #a& be evaluated by testi&' eter te abslute value +
T is less ta& &e. i#keyDuller tests te u&it rt as te &ull yptesis H0 E T1.Sie
e$plsive series d &t %ake %u# e#&%i# series5 tis &ull yptesis is tested a'ai&st
te &eD sided alter&ative H1E TV1. !e test is #arried ut by esti%ati&' te e4uati&E
PPtD1PUt
?ere TD1 a&d Ut are errr ter%s
?ile it %ay appear tat te test #a& be #arried ut per+r%i&' a tDtest & te esti%ated5
te tDstatisti# u&der te &ull yptesis + a u&it rt des &t ave te #&ve&ti&al t G
distributi&. i#key a&d uller sed tat te distributi& u&der t &ull yptesis is
&&Dsta&dard5 a&d si%ulated te #riti#al values +r te sele#ted sa%ple sies. Mre
re#e&tly5 M#Ki&&& (11) as i%ple%e&ted a %u# lar'er set + si%ulati&s ta& tse
tabulated by i#key a&d uller. *& additi&5 M#Ki&&& esti%ates te resp&se sur+a#e
usi&' te si%ulati& results5 per%itti&' te #al#ulati& + i#key G uller #riti#al values
+r a&y &u%ber + ri'ts Ga&d variables. !e si%ple u&it rt test des#ribed abve is
valid &ly i+ te series is a& A" (1) pr#ess. *+ te series is #rrelated at i'er rder la's5
te assu%pti& + ite &ise disturbaes is vilated.
A& i%prta&t result btai&ed by uller is tat te asy%ptti# distributi& + te t statisti#
is i&depe&de&t + te &u%ber + la''ed +irst di++erees iluded i& te A re'ressi&.
Mrever5 ile te para%etri# assu%pti& tat y +lls a& autre'ressive (A") pr#ess
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%ay see% restri#tive5 Said a&d i#key (18) de%&strated tat te A test re%ai&s
valid eve& e& te series as a %vi&' avera'e (MA) #%p&e&t5 prvided tat e&u'
la''ed di++eree ter%s are au'%e&ted t te re'ressi&.
.*2- 5oodness of fit in $ultiple regression
*& %ultiple re'ressi&5 tis is deter%i&ed by rki&' ut a value +r$/. Hever5 every
ti%e e add a&ter i&depe&de&t variable5 e &e#essarily irease te value + $/.
!ere+re5 i& assessi&' te 'd&ess + +it + a re'ressi& e4uati&5 e usually rk i&
ter%s + a sli'tly di++ere&t statisti#5 #alled$/Dad=usted r$/ad=. !is is #al#ulated as
$/ad= 1 D (1D$/)(%DnD1)(%D1)
ere%is te &u%ber + bservati&s i& te data set a&d nte &u%ber + i&depe&de&t
variables r re'ressrs. !eFstatisti# is als a&ter ay + assessi&' 'd&ess + +it i&
%ultiple re'ressi&.
.*24 Prediction
"e'ressi& e4uati&s #a& als be used t btai& predicted r fitted values + te
depe&de&t variable +r 'ive& values + te i&depe&de&t variable. *+ e k& te values +
x15x/5 ...x&5 it is bviusly a si%ple %atter t #al#ulate te value + yi#5 a##rdi&'
t te e4uati&5 suld #rresp&d t te%E e =ust %ultiply x1 by b15 x/ by b/5 a&d s
&5 a&d add all te prdu#ts t a. ?e #a& d tis +r #%bi&ati&s + i&depe&de&t
variables tat are represe&ted i& te data5 a&d als +r &e #%bi&ati&s.
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#"APTER T"REE
/*8 MET"ODOO56
!ntroduction
Be+re #&du#ti&' te study5 te resear#er ill i'li't te resear# desi'&5 te %del
t be used a&d =usti+i#ati& + variables. !e study %akes use + biDa&&ual data #lle#ted
+r% publi#ati&s a&d e#&%i# bulleti&s.
/*2 ?ustification of varia&les
a. *&+lati&
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*&+lati& as a dire#t i%pa#t & te st#k %arket per+r%ae sie i&vestrs use te
st#k %arket t ed'e a'ai&st i&+lati& risk& " priori5 i&+lati& is &e'atively related t te
i&dustrial i&de$ tereby a++e#ti&' st#k %arket per+r%ae. Hi'er i&+lati& rate
dis#ura'es savi&'s +r% te %&ey %arket a&d i&vestrs ill +ld te st#k %arket
ere tere are i'er a&d attra#tive retur&s. A##rdi&'ly5 e a&ti#ipate te #e++i#ie&t +
tis variable t be &e'ative.
b. *&terest rate
*&terest is te #st + brri&' r reard + le&di&' %&ey t varius e#&%i# a'e&ts.
3er i&trest rates dis#ura'e savi&'s i& te %&ey %arket. !is i&du#es i&vestrs t
%ve +r% te %&ey %arket t te st#k %arket5 as a ed'e a'ai&st i&+lati&. *& si%ple
ter%s5 ler i&trest rates dis#ura'e i&vestrs +r% savi&' tus pre+erri&' te st#k
%arket. ?e e$pe#t te #e++i#ie&t t be &e'ative sie a& irease i& i&trest rates attra#ts
i&vestrs t te %&ey %arket a&d redu#es te verall yield i& te st#k %arket.
#. M&ey Supply @rt
!e series + brad %&ey supply 'rt is relatively btai&able a&d a#ts as a 'd
pr$y +r #rprate i%e strea%s. !ere+re %&ey supply suld be iluded i& te
%del. As %e&ti&ed earlier5 !suysi ! (/001) iluded te variable a&d it as
statisti#ally si'&i+i#a&t i& is a&alysis. !e si'& is e$pe#ted t be psitive. r% te
tery te irease i& %&ey supply5 ldi&' i&terest rates #&sta&t5 ill #%pel i&vestrs
t de%a&d %re + prdu#ts a&d tis iludes srtDter% i&vest%e&t prt+lis i& e4uities
d. -#&%i# re+r%
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releva&t i& te deter%i&ati& + te i&dustrial i&de$ as evideed by te varius +i&aial
=ur&als. !is pr=e#t iluded a& a''re'ated i&de$ + e#Dpliti#al +a#tr as a du%%y
variable +r te i&dustrial i&de$ #al#ulati&.
/*+ Mathe$atical tools
!e 2rdi&ary 3east S4uare %etd as e%plyed t prdu#e te results utli&ed i& te
&e$t #apter. ia'&sti# tests ere als ru& & te %del.
/*7 Model Specification
Havi&' &ted te abve literature revie5 te resear#er esti%ated a& e#&%etri# %del
usi&' rdi&ary least 23S. !e re'ressi& %del is built by setti&' te i&dustrial i&de$
(depe&da&t variable) a&d te +lli&' e$pla&atry variablesE i&+lati&5 i&trest rates (!B
rates)5 M&ey Supply @rt (M;).
*N 0 P 1MS@ P /*N3 P ;*N! P 9M
?ereE
*N *&dustrial *&de$ @rt
*N3 ear & year i&+lati& as %easured by all ite%s C
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Aut#rrelati& !est
?alds !est +r #e++i#ie&ts
Multi#lli&earity
/*< !nference
!e last #apter #er&s te %aki&' + i&+eree a&d evaluati& + te validity + te
%del.
#"APTER +
+*2 DATA ANA6S!S AND RESUTS PRESENTAT!ON
!is #apter i'li'ts te +i&di&'s + te resear#. !e sele#ted data su%%aried i&
appe&di$ A ere pr#essed usi&' -Dvies. !e #apter +#uses & %del esti%ati& a&d
i&terpretati& + te si'&i+i#ae + te %del. Si%ple %di+i#ati&s su# as di++erei&'
ere e%plyed i& te bid t i%prve te 4uality + te results.
+*. Tests for stationarity
*& tis se#ti& * used u&it rt tests it -Dvies t #e#k stati&arity + te +ur
variables. As s& bel te *&dustrial *&de$ (*N) as stationary at level data5
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*N35 *N! a&d MS@ ere stati&ary at +irst di++eree. S& bel are te results +
te Au'%e&ted i#keyDuller (A) tests
+*.*2 ADF Tests
!NDADF Test Statistic 4.918538 1% Critical Value* -2.6453
5% Critical Value -1.9530 10% Critical Value -1.6218
!NFADF Test Statistic -1.231238 1% Critical Value* -2.6453
5% Critical Value -1.9530 10% Critical Value -1.6218
1ST DIFF ADF TestStatistic
-2.33962 1% Critical Value* -2.6486
5% Critical Value -1.9535 10% Critical Value -1.6221
!NTADF Test Statistic -1.69635 1% Critical Value* -2.6453
5% Critical Value -1.9530
10% Critical Value -1.6218
1ST DIFF ADF TestStatistic
-1.69635 1% Critical Value* -2.6453
5% Critical Value -1.9530 10% Critical Value -1.6218
MS5ADF Test Statistic -0.620228 1% Critical Value* -2.6453
5% Critical Value -1.9530 10% Critical Value -1.6218
1ST DIFF ADF TestStatistic
-3.461148 1% Critical Value* -2.6486
5% Critical Value -1.9535 10% Critical Value -1.6221
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+*/ Esti$ation and results
A+ter deter%i&i&' te stati&arity + te variables5 te resear#er e&t & t use te
stati&ary data t #%e up it te +lli&' results.
Varia!le C"e##icie$t St. &rr"r t-Statistic 'r"!.
C -1016.998 462.989 -2.196639 0.035I(F) 4.54513 2.095025 2.169508 0.0398I(T 10.10454 2.489 4.0869 0.0004
S+ 35.81166 11.90065 3.009219 0.0059D, -51.2113 535.0004 -1.404132 0.126
-suare 0.98023 ea$ e/e$e$t ar 1353.1Auste -suare 0.94511 S.D. e/e$e$t ar 1896.506S.&. "# reressi"$ 95.4691 Aaie i$#" criteri"$ 16.148Su suare resi 2291869 Scar7 criteri"$ 16.95101
)" lieli"" -245.621 F-statistic 22.19439Dur!i$-ats"$ stat 1.66522 'r"!F-statistic: 0.000000
&stiati"$ C"a$;
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+*+ Discussion of results
!e +lli&' results (as s&) i& te table abve 'e&erated by -Dvies are s& i&
su%%ary +r easy i&terpretati&F
"/ 0.80/7;
Ad=usted "/ 0.:117
urbi&D ?ats& Stat 1.76://7
D Statisti# //.1;
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; ;:.8166F 'eteris paribus,a si&'le per#e&t pi&t irease i& %&ey supply 'rt
as a si'&i+i#a&t ;:.8/ irease i& te i&dustrial i&de$ 'rt. !is is y te Ce&tral
Ba&k is battli&' t keep te %arket srt s as t de#rease te i&+lated #apitaliati& +
te st#k %arket.
+*: Statistical significance of the coefficients
!e tDstatisti# +r te #e++i#ie&ts + te %del are abve te #riti#al value ttables/. tis
%ea&s tat5 e re=e#t te &ull yptesis a&d tat te ppulati& value + te releva&t
#e++i#ie&ts is er. *& ter rds te %del spe#i+ied abve is a true appr$i%ati& +
te true ppulati& %del.
+*< Overall significance of the $odel
r% te Dstatisti#5 #al# >tables at : level + si'&i+i#ae. ?e #a& tere+re
#lude tat te verall %del is statisti#ally si'&i+i#a&t.
+*- E1planatory po)er of the $odel
9si&' te %del abve5 Ad=usted "/ value + 0.:117 ss tat te variati& i& te
e$pla&atry variable a##u&ted +r ver 0 i& te variati& i& te depe&de&t variableD
i&dustrial i&de$ 'rt. !is ss tat te %del as a very i' e$pla&atry per.
!e %del is reliable i& esti%ati&' te st#k %arket per+r%ae.
+*4 Testing for Autocorrelation @The Dur&in ,atson Test
A urbi& ?ats& statisti# is used t test +r aut#rrelati&. Sie it is appra#i&' /5 it
i%plies te absee + aut#rrelati&.
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+*28 The Aug$ented Dic%eyBFuller Test E'uation for Stationarity
!e Au'%e&ted i#keyDuller !est -4uati& +r Stati&arity sed tat all te
variables5 te *&terest rate5 %&ey supply 'rt a&d i&+lati&5 e$#ept i&dustrial 'rt
i&de$ ere &&Dstati&ary variables at teir levels. !ese variables &ly be#%e
stati&ary & +irst di++erei&'. *& ter rds tese variables are all i&te'rated + rder
&e.
+*22 Diagnostic tests
+*22*2 Multicollinearity tests
*ts presee is evide&t i& te %del be#ause + te i' "Ds4uared value.
+*22*. Autocorrelation test
A urbi& ?ats& statisti# is used t test +r aut#rrelati&. Sie te urbi& ?ats&
statisti# 1.66://7 is #lser t / (#riti#al value)5 it i%plies te absee + aut#rrelati&.
+*22*/ Tests for coefficients @,aldCs Test
Si'&i+i#ae + te #e++i#ie&ts as d&e usi&' te ?alds test ereE
H0E i 0 vs H1E i 0
Re;ection criteria
?e re=e#t H0 e& te prbability is less ta& te sie + te test5 i# is 0.0:
!ableE ignificance of the constant coefficient
al Test;&uati"$; ,$title
(ull >?/"tesis; C1:
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?e re=e#t H0a&d #lude tat te #&sta&t #e++i#ie&t is statisti#ally si'&i+i#a&t at 1
level.
!ableE ignificance of the coefficient for %F*
al Test;&uati"$; ,$title
(ull >?/"tesis; C2:?/"tesis; C3:
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&uati"$; ,$title
(ull >?/"tesis; C4:?/"tesis; C5:
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0
20
40
60
80
-2.0&=0
-1.0&=0
0.00000
1.0&=0
2.0&=0
Series; esi%uals
Sa/le 1995;01 2005;06
@!serati"$s 126
*ea$ 2.61&-09
*e%ia$ -23393.0
*aiu 1912652
*i$iu -21561656
St%. De. 3693888.
Se$ess -0.32562
Burt"sis 1.53255
arue-era 3.00001
'r"!a!ilit? 0.56000
i'ure .1 Hist'ra% + residuals
!e ist'ra% pai&ts a &r%al distributi& betee& variables. !is is a su++i#ie&t
veri+i#ati& tat te residuals are &r%ally distributed it %ea& er.
"ypothesis
H0E residuals are &r%ally distributed
H1E "esiduals are &t &r%ally distributed
Test statistic3
?ar'ueB(era NB% S. 8*.7@ G /. ..@8*87
"e=e#ti& #riteri&E "e=e#t H0i+ te ar4ueDBera W //(0.0:) 6. B ;.00001V65 s e
a##ept H0a&d #lude tat te residuals are &r%ally distributed.
1
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+*2+ Residual Tests
Actual> Fitted> Residual graph
Fig .&/ "ctual, Fitted, $esidual graph
2000
0
2000
4000
-2000
0
2000
4000
6000
8000
90 92 94 96 98 00 02 04
esi%ual Actual Fitte%
!e abve dia'ra% ss a 'rap +r te a#tual values5 +itted values a&d a 'rap +r te
residuals. Sie te a#tual a&d +itted 'raps are very #lse5 tis supprts tat te %del is
a 'd +it + te bserved values.
/
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+*27 Forecasting
*&dustrial i&de$ +re#ast
Fig .&0 Forecasting graph for ndustrial ndex
-4000
-2000
0
2000
4000
6000
8000
10000
90 91 92 93 94 95 96 9 98 99 00 01 02 03 04
I(DF E 2 S.&.
F"recast; I(DFActual; I(DSa/le; 1990;1 2004;2I$clu%e "!serati"$s; 30
""t *ea$ Suare% &rr"r84.045*ea$ A!s"lute &rr"r 505.323*ea$ A!s. 'erce$t &rr"r 311.4902Teil I$eualit? C"e##icie$t0.19054 ias 'r"/"rti"$ 0.000000 Varia$ce 'r"/"rti"$ 0.061948 C"aria$ce 'r"/"rti"$0.938052
+*27*2 #oBintegration
!is is a test ere e #e#k +r te stati&arity + te residuals at teir level usi&' te
usual u&it rt test. ?e& #Di&te'rati& e$ists te& tere is a l&' ru& relati&sip
betee& te variables u&der study a&d te %del is re&dered t 'ive reliable +re#ast
esti%ates.
N te results +r% -Dvies a&alysis are as +llsE
!ableE"#F test for stationarity of residuals(RES!D)
ADF Test Statistic-4.562398 1% Critical Value* -2.6453
5% Critical Value -1.9530 10% Critical Value -1.6218
!e residual are stati&ary at teir level5 i&di#ati&' #learly te e$istee + #Di&te'rati&.
!us te +re#ast values btai&ed +r% usi&' te %del are statisti#ally a&d e#&%i#ally
reliable +r te l&' ru&.
;
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#"APTER F!0E
7*2 F!ND!N5S AND #ON#US!ON
!e e%piri#al a&alysis #&du#ted su''ests tat %&ey supply 'rt5 i&+lati& ave
psitive relati&sip a&d te presee + e#&%i# re+r%s see% t ave &e'ative
relati&sip. !e %st parad$i#al result is i&+lati&. Altu' literature su''ests tat
tere is &e'ative relati&sip betee& i&+lati& a&d te per+r%ae + te st#k
e$#a&'e5 tis study as s& tat tere is a& ppsite relati&sip. As i&+lati&
irease5 s des te e4uities %arket. 2ter variables ere i& li&e it a priori
e$pe#tati&s.
!e reas& bei&d su# a parad$i#al result ste%s +r% te +a#t tat te i&dustrial i&de$
as drive& by asset %a&a'ers ed'ed a'ai&st i&+lati& it a& Labve &r%al
appetite +r te blue #ip #u&ters. i&aial #u&ters ere per+r%i&' ellDabve
%arket e$pe#tati&s be#ause + teir reprted super&r%al pr+its itut a&y psitive
#rrelati& i& a& aili&' e#&%y. !is as drive& by asset bubbles i& te +i&aial se#tr
#u&ters at te e$pe&se + ter #u&ters. Ba&ks ere e&'a'ed i& &&Dba&ki&' a#tivities
a&d used teir ldi&' #%pa&ies t pe&etrate te bla#k %arket +rei'& e$#a&'e syste%
a&d prperties %arket. Sie su# a#tivities i&+lated ba&ks balae seets5 te i&vestr
%arket #ir#u%ve&ted lssD%aki&' e4uities i& +avr + +i&aial #u&ters. !is #reated
e$#essive de%a&d +r te #u&ters as i&vestrs a&d spe#ulatrs alike ere +ldi&' te
%arket.
:
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-$#ess %&ey supply als drve te st#k %arket t re#rd i's. !e "eserve Ba&ks
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it i&+lati& di++ere&tials i& a& atte%pt t #urb spe#ulative a#tivities i& te e4uities
%arket. !is pli#y is duble ed'ed sie & &e a&d it redu#es a#tivity & te st#k
%arket but & te ter te i&trest bill bur&e by te 'ver&%e&t uld be e$tre%ely
elevated. !is %ea&t tat te bud'et de+i#it uld ide& i& te ba#k de%a&d +r !reasury
Bills. !ere+re a pli#y %i$ suld be i%ple%e&ted5 ere te #e&tral ba&k ei's te
#sts a&d be&e+its + redu#i&' st#k %arket per+r%ae it te purpse + #a&&eli&'
tese e$#ess +u&ds +r prdu#tive use r putti&' te #u&trys 'ver&%e&t & pressure t
#urb srt ter% bli'ati&s (te 1 day i&trest bill) tru' issued !Bs 'ive& te
i&+lati&ary pressure i& ,i%babea& e#&%y. !is i&trdu#es %re prble%s +r
'ver&%e&t su# as t restru#ture te d%esti# debt i& rder t %i&i%ie te srtD
ter% bli'ati&s a&d bias it %re t l&' ter% paper.
!e @ver&%e&ts stae t rela$ teir #&trl + i&terests ad severe reper#ussi&s &
st#k %arket per+r%ae sie te %a=rity + te players ere i&stituti&al a&d
i&ter&ati&al i&vestrs. !e dere'ulati& i&trdu#ed severe #%petiti& t attra#t su#
i&vestrs i& #&=uti& it te pre=udi#ial ti%i&' + te re+r%. *&stead + a b% i&
te st#k %arket per+r%ae tere as #apital +li't +r% te burse t ter i&vest%e&t
ubs i& te SAC re'i&. A&ter + su# e#&%i# re+r%s als supprted tis as
pr%ul'ated i& /000E te Mille%iu% "e#very
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A##rdi&'ly5 e#&%i# re+r%s #a& %ake r break st#k %arket per+r%ae. !is
su''ests tat i+ su# re+r%s are e$e#uted prperly5 te e#&%y #a& e&ae its &ati&al
savi&'s. !ese %ay peraps be supple%e&ted by #apital +r% ter i&ter&ati&al
i&vestrs. Hever5 i+ i%ple%e&ted itut prir syr&iati& it ter se#trial
re+r%s5 as t te #urse + te e#&%y5 re+r%s #uld spell disaster +r st#k %arket
per+r%ae.
7*.Policy !$plications and Reco$$endations
r% te a&alysis + results5 dru't see%ed t ave si'&i+i#a&t e++e#ts & te value
+ st#k pri#es. Hee pli#y %akers suld i&te&si+y e++rts t irease #apa#ity +
irri'ati& syste%s a&d da%s as reservirs t ed'e a'ai&st ti%es + dru't.
Sie dru't is &t a #&trllable variable5 te 'ver&%e&t suld %ade available
a&d eura'e +ar%ers t 'r dru't resista&t #rps t redu#e supply side s#ks.
!e "eserve Ba&k + ,i%babe #a& deter%i&e te level + i&trest ratestaki&' i&t
#&siderati& te per+r%ae + te st#k %arket. Hever5 l i&terest rates lead
t l savi&'s a&d tis eve&tually leads t a de#li&e i& i&vest%e&t.
M&ey supply 'rt is psitively related t te i&dustrial i&de$ a&d i&+lati&. Hee
+r te 'rt i& te %&ey supply t #ause 'rt i& te i&dustrial i&de$ itut
+uelli&' i&+lati&5 te "B, ill &eed t #al#ulate te %a'&itude + %&ey supply
'rt tat #a& irease te i&dustrial i&de$ itut tri''eri&' i&+lati&.
!e "B, suld ++er psitive real i&terest rates e& ireasi&' %&ey supply i&
rder t %i&i%ie de%a&dDpull i&+lati&.
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!e results a#tually appre#iate te +a#t tat #ertai& per#e&ta'e #a&'es i& st#k pri#es #a&
be as a result + ter +a#trs i# ave &t bee& #aptured like pliti#al stability5
u&e%ply%e&t a&d bud'et de+i#it. r i&stae te u&predi#table #&tai&s + te Nati&al
Bud'et a&d M&etary
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Appendi1 23 Sa$ple Data
I(D I(F) I(T S+ D,
1990;1 60.3 15.5 11.5 19.1 01990;2 100 20.2 11.5 20.1 0
1991;1 61.6 23.3 14.5 20.4 0
1991;2 91.2 30.9 15.8 21.3 0
1992;1 15.6 42.1 34.6 22.9 1
1992;2 1.1 26.1 35.1 35.2 1
1993;1 3.8 2.6 3.9 43 0
1993;2 90.1 28.1 38.2 45.6 0
1994;1 12.1 22.3 36.4 34.3 0
1994;2 135.8 22.5 36.4 32.1 0
1995;1 14.6 22.6 35 30 0
1995;2 140.2 21 3.1 29.1 0
1996;1 310.1 21.4 33.6 2. 01996;2 42.9 30.1 32.1 28.9 0
199;1 581.9 18.8 34. 34.9 0
199;2 666.6 19.9 41.3 34.3 0
1998;1 355.8 31. 49.3 14 0
1998;2 398.1 26.3 55.5 14.9 0
1999;1 553.4 58.5 66 29.8 0
1999;2 603.1 59.4 5.2 35.6 0
2000;1 944.1 55.9 5.5 60.8 1
2000;2 1102.8 63.5 40.3 65.6 1
2001;1 2326.3 64.4 31.3 3.4 0
2001;2 2994. 11.8 30.2 5. 0
2002;1 312.1 198.9 15.5 8.4 02002;2 4212.5 234.5 15.3 80.8 0
2003;1 4343.3 364.5 26.4 83.5 0
2003;2 42.9 598. 30.1 84.1 0
2004;1 4886.1 394.6 450 40.95 0
2004;2 684.2 132.8 20 24.0 0
:0
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(!(!O5RAP"6
Breede& .!5 (17)5 IA& *&terte%pral Asset
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3ipsey ".@ (11)5 "n introduction to positive 2conomics5 ?ader+ield Y Ni#ls&5
3&d&.
Cipika .!. (16)53asic 2conometrics training 5rogramme5