hillary dissertation

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$pla&atry values ($).

1


20/52

*& '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.

/0


21/52

.*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

/1


22/52

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.

//


23/52


24/52

#) !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.

/


25/52

.*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.

/:


26/52

.*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

/6


27/52

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

/7


28/52

%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.

/8


29/52

#"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&

/


30/52

*&+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%

;0


31/52


32/52

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


33/52

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

;;


34/52

*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


1ST DIFF ADF TestStatistic

-2.33962 1% Critical Value* -2.6486


!NTADF Test Statistic -1.69635 1% Critical Value* -2.6453

5% Critical Value -1.9530

10% Critical Value -1.6218


-1.69635 1% Critical Value* -2.6453


MS5ADF Test Statistic -0.620228 1% Critical Value* -2.6453



-3.461148 1% Critical Value* -2.6486


;


35/52

+*/ 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$;


36/52

+*+ 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;


37/52

; ;:.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&.

;7


38/52

+*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:


39/52

?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:


40/52

&uati"$; ,$title

(ull >?/"tesis; C4:?/"tesis; C5:


41/52

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


!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&.

8


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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

hillary dissertation

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