Երևան քաղաքի բնակելի անշարժ գույքի գների փոփոխությունների վրա ազդող մակրոտնտեսական ֆինանսական գործոնների տնտեսամաթեմատիկական վերլուծությունը Текст научной статьи по специальности «Экономика и бизнес»

ЬркшЬ pbm^bi^ qnLjg| qfobp|

4рш шqцnц iUul||iiuiiiiuihuiul|iuii к l|>|iiiiuiiuiul|iuii qnp6nfofobp| тЬтЬишйшрЬйшт||ш|шЬ 4bpinL6nLpjnLbp

UmpqujmU Цйцршй^Ц

Цищ^р^шйш, щЪшшЦшй тЬтЬишд^тш^шЬ hшйшluшp,шй (Ъркшй,

and.sargsyan@yahoo.com 330.4 - ишрЫшт^ш^шЬ mbmhumq^rnnLpjnLb: t^nbn^hrnp^^m •<шhqnLgшpшnhp" РЬш^Ьф шh2шpd qnijf^ qhbp, ^ш^рптЬтЬиш^шЬ qnp&nhhbp, ^Ъи, h^фnpb£шфh 4шр^ш4прп1^, 2^ЬшpшpnLpJnLЬ, ^pbh^bpfr щштбшпш^шЬтр^Ь:

Экономико-математический анализ макроэкономических и финансовых факторов

влияющих на изменение цен жилой недвижимости в Ереване

Саргсян Андраник О.

Аспирант, Армянский Государственный Экономический Университет (Ереван, РА)

and.sargsyan@yahoo.com

Аннотация. В данной статье делается попытка выявить основные макроэкономические и финансовые факторы влияющие на изменение цен на жилую недвижимость в Ереване. Для проведения анализа были выбраны несколько экономические и финансовые временные ряды с ежеквартальной периодичностью. Для определения предсказательной силы выбранных переменных использовался тест причинности Грейнджера. Результаты проведенных тестов показали, что основными факторами, «вызывающими» изменение цен на жилье, являются ВВП, процентная ставка по ипотеке, средняя номинальная заработная плата и индекс цен на строительство. Затем с использованием полученных значимых факторов была построена регрессионная модель и был проведен анализ оцененных параметров.

Ключевые слова: цены жилой недвижимости, макроэкономические факторы, ВВП, ипотечное кредитование, строительство, причинность Грейнджера.

Economic and mathematical analysis of macroeconomic and financial factors influencing on

housing price changes in Yerevan

Sargsyan Andranik S.

Postgraduate student, Armenian State University of Economics (Yerevan, RA)

and.sargsyan@yahoo.com

Abstract. This paper attempts to reveal the main macroeconomic and financial factors influencing changes in residential property prices in Yerevan. For performing the analysis a number of economic and financial time series variables were selected with quarterly frequency. Granger causality test was used for determining the predictive power of the selected variables. Results of the conducted tests showed that the main factors "causing" housing price changes were the GDP, the mortgage interest rate, the average nominal salary and the construction price index. Then, using the obtained significant factors, a regression model was constructed, and analyses of the estimated parameters were performed.

Key words: housing prices, macroeconomic factors, GDP, mortgage lending, construction, Granger causality.

ЪЪршд^вд^Ь

РЬшЦЬф шh2шpd qnLjgh 2п^шЬ пщрш^Ь Цшй шЬпщршЦЬ &hnd t mhrnburnp^h

tfjrnu ub^mnphbph hhm: РЬшЦЬф шh2шpd qnijgp ^phnp qbp rnhh hшmhшщbu фЬЬшЬишЦшЬ 2тЦщ|пЫ, np Щ|Ь тЬщфЬ mhmbunLpjnLh-hbphh mpшtfшqpdnp hhфnpb£шфh h шд ^phhph шtfhhшmшpш&dш& шщшhndnLpJшh tfh?ngh t hшhqhuшhnLй [7, t?bp 3-25]: Ц|ищЬипф рЬшЦЬф шh2шpd qnLjfp 2пгЬш|пЫ mbph nLhb-gnp qhmjhh фnфn^nLpJnLhhbpp шЫ^ш^ш-hnpbh шqqnLtf bh pшhhbph h шд фЬЬшЬишЦшЬ ^qtohbp^nLpjnLhhbph hш2dшчшhшhшh

hш2dbh2hпhbph hhp, 2пгЦшф шhpшpb-

Ьщшит фnфn^nLpJnLhhbph qb^grntf ^pnp t hшhqbghbl mjq ^qtohbp^nLpjrnhhbph ФЬЬшЬ-ишЦшЬ hmirnhnLp^h ^шpшptfшhp:

РшдЬ тЬтЬит^шЬ ub^mnphbph hbm пШЬдшй фn^шqqbgnLpJnLhhbph ^phnpnL-pjnLhpg, рЬшЦЬ^Ь шh2шpd qnijgp rnhp Ьшк ипдрш^шЦшЬ Ь2шЬшЬпгр]пгЬ: Q-pшhшhnLpJшh tfb? bh phшhшpшhh ubфшhшhшmbp

фЬЬрг тЬтЬишЦшЬ h ипдрш^шЦшЬ pшqtfшph4 hbmhшhghbp, hh^huhf bh" mhmjhh mhmburn-pjmhhbph щ^тфпфпф Цшппгд^ш&ЕР, 2шpdnL-hшhnLpJnLhp, £шpш£шhшh h unghшLшhшh

Регион u Mup, 2022, № 2

m^m^nLpjnLtp, qbtfnqpm^mt k mj]t [8, t?bp 401-450]: Uju hmtfmmbpumnLtf mthpmdb2m t tmk ptm^b^ mt2mpd qnygfr" mtmbunLpjmt ^pm qtmj^t ^n^n^mpjnLttbp^ mqqbgnLpjnLtp «hmpummpjmt tffengn^ [6, t?bp 522-

541] :

Uju^^un^, mntbp^ ptm^b^ mt2mpd

qnLjg^ ^m^p mtmbunLpjmt k ung^m-

jm^mt qnp&ptpmgtbp^ hbm, mthpmdb2mnL-pjnLt t mnm^m&niJ pmgmhmjmbi ptm^bj^ mt2mpd qnijg^ qtbp^ ^n^n^mpjnLttbp^ ^pm mqqnq tfm^pnmtmbum^mt qnp&nttbpp, frtp mnm^frt pmjit t hmtq^umtnLtf ^mtfammb-unLtfmj^t tfnqbjtbp ^mnnLgb^u: ^■pm^mbnLpjmb rn^brnp^ Stmbumq^mm^mt qpm^mtmpjnLtp hm-pnLus t ptm^b^ m&2mpd qnLjg^ qtbp^ ^n^n^mpjnLttbp^ ^pm mqqnq qnp&nttbpp pt^bu mnmt&pt bp^ptbpk mjt^bu tl tfp£-bp^pmj^t nLunLtftmu^pnLpjnLttbpn^: Unmt&pt bp^ptbp^ ^mtf pmqmptbp^ ptm^bjp mt2mpd qnLjpp 2nL^mj^ ^pm mqqnq qnp&nttbpp ^bpmpbpjmi mtmbumtfmpbtfmmp^m^mt ^bppL-&nLpjnLttbp ppm^mtmgtbipu hbqptm^tbpp hmfim^ ^ppmn^nLtf bt ufamjtbpp fi2qpmtfmt tfnqbjtbp (error correction models) [10, t?bp 27-62, 3]: fru^ tfp^bp^pmjpt ^mtf tfp^Emqmpmjpt hbmmqnmnLpjnLttbpp ppm^mtmgtfmt qb^pnLtf oqmmqnp&^nLtf bt ^mtbimjpt nbqpbupmjp tfnqbitbp [4, t?bp 163-204]:

Um^mjt mmppbp hbqptm^tbpp ^nqtfpg ummg^m& mpqjnLtptbpp hmfim^ ^bt hmtfpt^tnLtf: Opptmk Upt -njpp k bmmm2m Sntup ^nqtfpg ppm^mtmg^m& ^bppL&nLpjnLtp, hptft^m& tfp 2mpp bp^mp dmtfmtm^mjpt 2mppbpp ^pm, ^murnnL^ t, np UtqipmjnLtf ptm^bjp mt2mpd qnijgp qtbpp ^n^n^nL-pjnLttbpp ^pm mqqnq hptftm^mt qnp&ntp mtmjpt mtmbunLpjnLttbpp ppm^mt b^mtfnLmt t [9, t?bp 549-565]: Uitpt^, ^mnppm knhbtp k Lptm ^mpm^m^nLmbp ^nqtfpg Lpm^mjp ptm^bjp mt2mpd qnijgp qtbpp, -UU-k qnp&mqp^nLpjmt tfm^mpqm^k qtmfip k mpmmqmqpp mbtf^bpp ^n^n^mpjnLttbpp

^bppL&nLpjmt mpqjnLtpnLtf np^bu ptm^bjp mt2mpd qnijgp qtbpp ^n^n^nLpjnLttbp mnm-^mgtnq qnp&nttbp ummg^b bt -UU-p k qnp&mqp^nLpjmt tfm^mpqm^p ^n^n^nLpjnLt-tbpp [2, t?bp 49-63]:

Gum Smgmpntpu knummup k QdnL -mppptp tfp^bp^pmjpt ttf^ppp^ hbmmqnmnL-pjnLttbpk np^bu ptm^bjp mt2mpd qnijgp qtbpp ^pm mqqnq hptftm^mt qnp&nttbp bt qtmfip, ^mpmmmntfubpp b^mtfmmpbpnLpjmt ^npp k pmt^mj^t ^mpUfr mn^numqpnLjgp [13]: U^t^qbn Sp^^mp^ Umpjmum^ ^nqtf^g ^pm^mtmg^mft tf^gbp^pmj^t hbmmqnmnLpjnLtp mnm^mp^nLtf t, np ptm^bj^ mt2mpd qnLjg^ ^mp&m^minLpjmt tf^^^t q^tp, q^t-^mp& hmpm-pbpnLpjnLtp, q^t-b^mtfnLm hmpmpbpnLpjnLtp, nLppmt^qmg^mj^ tfm^mpqm^p, tfb^ hm2^n^ ^UU-t, 15-64 mmpb^mt ptm^^nLpjmt tfmutm-pmd^tp, ^nq^ qmtq^mftp k mpmmpdnLjp^ ^n^mpdbgp t2mtm^mj^ mqqbgnLpjnLt nLtbt ptm^bj^ mt2mpd qnLjg^ qtbp^ ^pm [12, t?bp 229-238]:

HLunLtftmu^pbp^ hbq^tm^tbp^ ^nqtf^g ummg^mft mpqjnLtgtbp^ mthmtfm&mjtnLpjnLtp" ^mpbj^ t bqpm^mgtbi, np ptm^bj^ mt2mpd qnLjg^ qtbp^ ^n^n^nLpjnLttbp^ ^pm mqqnq ummg^mft qnpftnttbpp ^mpnq bt smppbp i^tbi nLunLtftmu^pnLpjmt opjb^m hmtq^umgnq mmp-pbp bp^ptbp^ qb^gnLtf, Umpnq bt l^tbi

nLunLtftmu^pnLpjmt tfbpnq^ ptmpnLpjnLt^g, ^t^^bu tmk Umpnq bt ^n^n^^bl dmtfmtm^^ ptpmgpnLtf:

^hpnqmpmbnLpjnLb

^bpinL&nLpjmt ^pm^mtmgtfmt hmtfmp ptmp^bi t bpkmt gmqmg^ ptm^bi^ mt2mpd

qnLjg^ mnnL^mfimng^ 2nL^mt: bitb^n^ nLunLtf-tmu^p^mft qpm^mtnLpjnLtnLtf ptm^bj^ mt2mpd qnLjg^ qtbp^ ^n^n^nLpjnLttbp^ ^pm mqqnq mnm^mp^^nq h^tftm^mt qnpftnttbp^g, k hm2^^ mntb^n^ hbmmgpgpnLpjnLt tbp^mjmgtnq mj]_ qnpftnttbp" unLjt nLunLtftmu^pnLpjmt hmtfmp ptmp^bi bt mqjnLum^ 1-nLtf tbp^mjmg^mft ^n^n^m^mttbpp:

On^nfarn^rnh On^nfarn^rnhfr b^mpqpnLpjnLb U^PinLp

Y bpkmtnLtf ptm^mpmttbp^ mnnL^mfimng^ tf^^^t qtbp^ ^&qbfup (1 tf2 tfm^bpbu^ hm2^mp^n^) ^^ kmqmump^ ^ntf^mb

NUM_TR bpkmtnLtf ptm^mpmttbp^ mnnL^mfimng^ qnpftmpftbp^ fmtm^p

GDP ^mtfm^mnt tbpf^t mpqjnLtf ^ntf^mb

CONSTR IND G^tmpmpnLpjmt qtbp^ ^&qbfu

CONSTR VOL G^tmpmpnLpjmt 6m^m]

CPI U^mnnqm^mt qtbp^ ^tqbfu

SALARY U^p^t mt^mtm^mt m2^mmm^mp&

RETAIL VOL Umtpmftm^ mnkmp^ 2p?mtmnnLpjnLt

MR_AMD ^pqphm^mh mh&mhg ^^ ppmün^ mpmümppdmö hp^nphpmjph dmphhpp üppph mn^numppnLjp

MR_USD ^pqphm^mh mh&mhg pn]_mpnd mpmümppdmö hp^nphpmjph dmphhpp üppph mn^numppnLjp

DR_AMD ^^ ppmünd mhmhunLpjnLhpg hhpqpmddmö m^mhphhpp üppph mn^numppnLjp ^^ ^hhmpnhm^mh pmhh

DR_USD UU^ pn]mpnd mhmhunLpjnLhpg hhpqpm^dmö m^mhphhpp üppph mn^numppnLjp

TD_VOL_AMD Shmjph mhmhunLpjnLhhhpp" ^^ ppmün^ dmü^hmmjph m^mhphhpp öm^mjp

TD_VOL_USD Shmjph mhmhunLpjnLhhhpp" UUu pnimpn^ dmü^hmmjph m^mhphhpp öm^mjp

USD PRICE 1 UUu pnjmpp qphp ^^ ppmünd

Pnpp ^n^n^m^mhhhpp hmtfmp hmdw-^msmufamh mppjmphhppg [14, 15, 16] hmdmpmqpdhi hh, 2003-2020 pdmhmhhhpp hnmtfujmhmjph gnLgmhp2hhpp k ushp&dkl t sdjmjhhpp pmqm: £mhp np GDP, CONSTR_VOL, CPI, SALARY, RETAIL_VOL ^n^n^m^mhhhpp nLhhh uhqnhmjph phmjp, tfph hhsmqm dhpinL&nLpjnLhhhpp ppmhmhmgrntfp ppmhp hhpmphdkl hh uhqnhmjph hmpphgtfmh: Uhqnhmjph hmpphgtfmh hmtfmp oqsmqnp&dhl t Phm^nLpjmh tfmppmhmtfmpp pjmpnjp hnptfpg Census X13 tfhpnpp:

UjhnLhhsk dmtfmhmhmjph 2mpphpp hhpmphdhl hh pqmppptfmhmh ftkm^n^nLpjmh, k hpmhgpg hhnmgdhl t sphhpmjph pmpmppp^p" oqsm-qnpfthin^ ^nqppk^phuhnsp $pjspp:

Usmg^mft dmtfmhmhmjph 2mpphpp urnm-gpnhmpnLpjrnhp usnLqhpL hmtfmp oqsm-qnpftdbl hh ^ppp ^nL^hpp phpimjhdmft phusp (Augmented Dickey-Fuller (ADF) test), npp ph^pnLtf qpnjm^mh hp^nphqp usmgpnhmpnL-pjmh pmgmhmjrnpjnLhh t, k ^dpmm^ndu^p-foplp^u-Gtfpqs-Gph phusp (Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test), npp pk^prntf qpnjm^mh hp^nphqp usmgpnhmpnLpjmh mn^mjnLpjnLhh t:

Ghsp^mft mh^mfa ^n^n^m^mhhhpp hnptfpg mnnL^mfimngp tfp^ph qhhpp ^mh^m-shuhpL nLhm^nLpjnLhp ^mpqhpL hmtfmp oqsmqnp&dhl t ^phh^hpp qmmfimnm^m&nL-pjmh phusp: ^husp ppmhmhmgrntfp ^mhmh-^mtf t hhskjmi hp^nL nhqphupnh hm^m-

umpmtfhhpp qhmhmsrntf.

p p

Vt

i = 1 ]'=!

p+j

p p

Xt = ßi.o ßi.i yt-i ßi,p+j xt-j ¿ = 1 ]'=!

npmbp p-h ^n^n^m^mhp qphmüp^mjp

ünph]mdnpümh hmümp ^mhmhgdnq pm^mpmp imqhpp ppdh t, npp ph^prnü hmdhjmi jmqhpp hhpmnnLÜp dpfim^mqpnphh h2mhm^mip ^t, puh ep u^pmmh mpünL^ t [11]: bph qhmhmmdmö pnjnp ßi,p+j ^mpmühmphpp üpmdmümhmh h2mhmhm]p hh, m^m «x-p qphh^hp ^mmfimn ^p hmhppumhnLÜ y-p hmümp» qpnjm^mh dmphmöp hmphjp t ühpdhj; "uümhm^hu, hph qhmhmmdmö pnjnp ß2,p+j ^mpmühmphpp h2mhm^m|p hh, m^m hmphjp t ühpdhi «y-p qphh^hp qmmfimn ^p hmhppumhnLÜ x-p hmümp» qpnjm^mh dmphmöp: Q-phh^hpp ^mmfimnmhmhnLpjmh phumhpp ppmhmhmgümh hmümp o^mpüm^ jmqhpp gmhmhp phmpnLpjmh hmümp hppmndh t Eviews ^mphpnLÜ mn^m jmqhpp hphmprnpjmh ^m^mhp2p phump: Lmqhpp o^mpümi hphmpnLpjmh phmpnLpjnLhp ppm^mhmgdhi t Gdmpgp rnhph^mm^m^mh ^m^mhp2p üp^ngn^ (Schwarz Information Criterion, SIC): Ujp ^m^m-hp2p phmpnLpjnLhp ^mjümhmdnpdmö t qnpöhm-hmhnLÜ ppm üp^ngn^ phmp^mö tfnpk]hhpp m^hip ^mpq iphhinL hmmhmhp2nd [5, t?hp 187-195]:

Phm^hip mh2mpd qnLjpp qhhpp ^n^n^nL-pjnLhhhpp h2mhm^m|p «^mmfimn» hmhppumgnp qnpönhhhpp mqphgnLpjnLhhhpp qhmhmmümh hmümp oqmmqnpödhl t ^mpq qömjph nhqph-upmjp ünphip.

Yt=ß0 + YJßiXi +

+ e

2, t

¿ = 1

npmhp Yt-h phm^hjp mh2mpd qnLjpp qhhpp ^n^n^nLpjnLhp hhphmjmghnp ^n^n^m^mhh t dmümhmhp t-^mhph, n-p" ünqhjp hmnnLgümh hmümp phmp^mö mh^mfa ^n^n^m^mhhhpp ppdp, Xi-p" phmp^mö i-pp. qnpönhp, puh e-p" ummhpmpm hnpüm]_ pm2^nLÜ nLhhgnp ^mmmhm^mh ^n^n^m^mh t: Unphjp ßi ^mpmühmphpp qhmhmm^hi hh ^nppmqnLjh pmnm^nLuphhpp ühpnpn^: ^hpi_nLÖnLpjnLÜ

Cum ppm^mhmg^mö ADF k KPSS phumhpp mppjnLhfhhpp" pn^np äkm^n^^mö dmümhm-

(*-p k **-p ADF pbum^ qb^gmtf thp^mjmgbnLtf bt dmtfmtm^mj^t 2mpgff ummg^ntmp yfitlqnL qpnjm^mt h^npbqfi tfbpdnLtfp hmtfmqmmmu^mbmpmp 1% k 5% t2mtm^m]JinLpjmt tfm^mpqm^tbpnLtf, ^u^ KPSS pbum^ qb^gnLtf dmtfmtm^mj^t 2mpp^ ummg^ntmpmpjmt qpnjm^mt h^npbqfi tfbpdtfmt &m^mqnLtfp hmtfmqmmmu^mtmpmp 10% k 5%

^ummhb]JinLpjmt tfm^mpqm^tbp^ qb^gmtf )

Регuон u Mup, 2022, № 2

^mjpt 2mpgbpp ummgpntmp bt pb' mnmtg mnmppt ^mpqp mmppbpnLpjnLttbpp, pb' mnm-ppt ^mpqp mmppbpnLpjnLttbpn^: Um^mjt, pmtp np u^qptm^mt ^n^n^m^mttbppt ptnpn2

t gp^imjtnLpjnLt, npp Umpnq t ^bq& nbqpbupm mnmpmgtbi [1, tpbp 111-120], hbsmqm hm2-^mp^tbpp ppm^mtmg^bi bt mnmppt ^mpqp mmppbpnLpjnLttbpn^:

On^nfam^mb ADF KPSS

Level (t statistic) 1st difference (t statistic) Level (LM statistic) 1st difference (LM statistic)

Y -3.040** -3.462** 0.069* 0.071*

NUM TR -3.504** -4.946* 0.167* 0.176*

GDP -3.793* -10.436* 0.051* 0.067*

CONSTR IND -4.872* -7.736* 0.057* 0.151*

CONSTR VOL -5.375* -7.993* 0.075* 0.240*

CPI -3.811* -8.002* 0.068* 0.034*

SALARY -3.546* -8.774* 0.053* 0.076*

RETAIL VOL -4.083* -11.506* 0.042* 0.090*

MR AMD -3.908* -9.578* 0.048* 0.058*

MR USD -4.659* -4.375* 0.043* 0.044*

DR AMD -4.890* -5.620* 0.046* 0.103*

DR USD -4.863* -10.261* 0.032* 0.054*

TD VOL AMD -4.015* -4.031* 0.037* 0.045*

TD VOL USD -3.199** -8.792* 0.068* 0.046*

USD PRICE -2.942** -5.056* 0.062* 0.034*

UqjnLum^ 3-nLtf tbp^mjmg^mft t jmpm-gmtymp mt^mfa ^n^n^m^mtp hmtfmp hm2^mp^4m& o^mptfm]_ jmqbpp pmtm^p: G^mpgp mbqb^mm^m^mt ^m^mtfon^ ptmp^mft

o^mptfm]_ jmqbpp pmtm^p, pmgmnnLpjmtfp qnp&mpptbpp pmtm^p, 2frtmpmpnLpjmt ptqbpup k 2^tmpmpnLpjmt ftm^mjp ^n^n^m^mttbppg, 1 t:

On^nfam^mb SIC Lmqhpfr gmbm^p On^nfam^mb SIC Lmqhpfr fmbm^p

NUM TR -4.952 3 MR AMD -9.105 1

GDP -8.153 1 MR USD -8.877 1

CONSTR IND -8.344 3 DR AMD -7.089 1

CONSTR VOL -6.688 3 DR USD -5.628 1

CPI -10.385 1 TD VOL AMD -6.128 1

SALARY -9.036 1 TD VOL USD -6.983 1

RETAIL VOL -7.806 1 USD PRICE -9.038 1

Ummg^mft jmqbpp o^mptfmi pmtm^tbpp oqmmqnp&^bl bt ^pbtpbpp ^mmfimnmhbmkmtpmjpt pbumbpp ppm^mtmgtbjpu:

Qpnjm^mb hp^nphq F ^pfim^mbp ■^m^mbm^m-bnLpjnLb

D(NUM_TR) does not Granger Cause D(Y) D(Y) does not Granger Cause D(NUM Tr) 1.264 1.535 0.295 0.215

D(GDP) does not Granger Cause D(Y) D(Y) does not Granger Cause D(GDP) 12.570 0.713 0.001 0.402

D(CONSTR IND) does not Granger Cause D(Y) D(Y) does not Granger Cause D(CONSTR IND) 2.651 0.484 0.042 0.747

D(CONSTR VOL) does not Granger Cause D(Y) D(Y) does not Granger Cause D(CONSTR VOL) 2.825 0.340 0.046 0.797

D(CPI) does not Granger Cause D(Y) D(Y) does not Granger Cause D(CPI) 0.716 0.767 0.401 0.384

D(SALARY) does not Granger Cause D(Y) D(Y) does not Granger Cause D(SALARY) 3.540 0.234 0.003 0.792

D(RETAIL VOL) does not Granger Cause D(Y) D(Y) does not Granger Cause D(RETAIL VOL) 2.146 0.141 0.148 0.708

D(MR_AMD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(MR AMD) 4.435 0.043 0.039 0.835

D(MR_USD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(MR USD) 5.482 0.076 0.022 0.783

D(DR_AMD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(DR AMD) 0.073 0.022 0.787 0.883

D(DR_USD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(DR USD) 5.513 0.026 0.022 0.871

D(TD_VOL_AMD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(TD VOL AMD) 6.673 0.330 0.012 0.568

D(TD VOL USD) does not Granger Cause D(Y) D(Y) does not Granger Cause D(TD VOL USD) 0.395 0.850 0.532 0.360

D(USD PRICE) does not Granger Cause D(Y) D(Y) does not Granger Cause D(USD PRICE) 2.874 3.650 0.095 0.060

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AYt_i 0.573 0.087 6.575 0.000

AGDPt-i 0.118 0.050 2.367 0.021

ACONSTR INDt-6 0.131 0.061 2.140 0.036

ASALARYt-i 0.138 0.084 1.641 0.090

AMR USDt-i -0.127 0.078 -1.624 0.096

= 0.57 *Ayt_1 + 0.12 *AGDPt_1 + 0.13 *ACONSTR_INDt_6 + 0.14 *ASALARYt_1 - 0.13

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1. C. W. J. Granger, P. Newbold, Spurious regressions in econometrics, Journal of Econometrics, 1974, Volume 2, Issue 2, t£ 111-120

2. Cohen, V. and L. Karpaviciute, The Analysis of the Determinants of Housing Prices, Independent

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6. Miller, Norm & Peng, Liang & Sklarz, Michael,

House Prices and Economic Growth, Journal of Real Estate Finance and Economics, 2011, 42, t2 522-541

7. Pashardes, P., & Savva, C. S., Factors affecting house prices in Cyprus: 1988-2008. Cyprus Economic Policy Review, 2009, Vol. 3(1), t2 3-25

8. Robert D. Dietz, Donald R. Haurin, The social and private micro-level consequences of homeownership, Journal of Urban Economics, 2003, Vol 54, Issue 3, t2 401-450

9. Sean Holly, Natasha Jones, House prices since the 1940s: Cointegration, demography and asymmetries, Economic Modelling, 1997, Volume 14, Issue 4, t2 549-565

10. Stephen Malpezzi, A Simple Error Correction Model of House Prices, Journal of Housing Economics, Volume 8, Issue 1, 1999, t2 27-62

11. Stern, David I., From Correlation to Granger Causality. Crawford School Research Paper No. 13, September 30, 2011, Available at SSRN: https://ssrn.com/abstract=1959624

12. Tripathi, Sabyasachi, Macroeconomic Determinants of Housing Prices: A Cross Country Level Analysis, Real Estate Finance, 2020, 36:4, t2 229-238

13. Tsatsaronis, Kostas & Zhu, Haibin, What Drives Housing Price Dynamics: Cross-Country Evidence, BIS Quarterly Review, March, 2004

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