Vasileiou, E angelos; Hadad, El oi; Melekos, Geo gios
A icle
Wha d i es he eal es a e ma ke ? Could beha io al
indica o s be use ul in house p icing models?
EconomiA
P o ided in Coope a ion wi h:
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Sugges ed Ci a ion: Vasileiou, E angelos; Hadad, El oi; Melekos, Geo gios (2024) : Wha d i es he
eal es a e ma ke ? Could beha io al indica o s be use ul in house p icing models?, EconomiA, ISSN
2358-2820, Eme ald, Bingley, Vol. 25, Iss. 1, pp. 157-174,
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Wha d i es he eal es a e
ma ke ? Could beha io al
indica o s be use ul in house
p icing models?
E angelos Vasileiou
Depa men o Financial and Managemen Enginee ing, Uni e si y o he Aegean,
Chios, G eece
El oi Hadad
Depa men o Indus ial Enginee ing and Managemen ,
Shamoon College o Enginee ing, Bee -She a, Is ael, and
Geo gios Melekos
Depa men o Financial Managemen Enginee , Uni e si y o he Aegean,
Chios, G eece and
Facul y o Tu kish S udies and Mode n Asian S udies,
Na ional and Kapodis ian Uni e si y o A hens, A hens, G eece
Abs ac
Pu pose –The objec i e o his pape is o examine he de e minan s o he G eek house ma ke du ing he
pe iod 2006–2022 using no only economic a iables bu also beha io al a iables, aking ad an age o
a ailable in o ma ion on he olume o Google sea ches. In o de o quan i y he beha io al a iables, we
implemen a Py hon code using he Py ends 4.9.2 lib a y.
Design/me hodology/app oach –In ou s udy, we asse ha models elying solely on economic a iables,
such as GDP g ow h, mo gage in e es a es and in la ion, may lack p ecision compa ed o hose ha in eg a e
beha io al indica o s. Recognizing he impo ance o beha io al insigh s, we inco po a e Google T ends da a
as a key beha io al indica o , aiming o enhance ou unde s anding o ma ke dynamics by cap u ing online
in e es in G eek eal es a e h ough sea ches ela ed o house p ices, sales and ela ed opics. To quan i y ou
beha io al indica o s, we u ilize a Py hon code le e aging Py ends, enabling us o ex ac ele an que ies o
global and local sea ches. We employ he EGARCH(1,1) model on he G eek house p ice index, es ing se e al
mac oeconomic a iables alongside ou Google T ends indexes o explain housing e u ns.
Findings –Ou indings show ha in some cases he ela ionship be ween economic a iables, such as
in la ion and mo gage a es, and house p ices is no always consis en wi h he heo y because we should
highligh he special condi ions o he examined coun y. The coun y o ou sample, G eece, p esen s he
special case o a coun y wi h se e e so e eign deb issues, which a he same ime has he p i ilege o ha e a
s ong cu ency and he suppo and he obliga ions o being an EU/EMU membe .
P ac ical implica ions –The esul s sugges ha Google T ends can be a aluable ool o academics and
p ac i ione s in o de o unde s and wha d i es house p ices. Howe e , u he esea ch should be ca ied ou
on his opic, o example, causali y ela ionships, o gain deepe insigh in o he possibili ies and limi a ions o
using such ools in analyzing housing ma ke ends.
O iginali y/ alue –This is he i s pape , o he bes o ou knowledge, ha examines he bene i s o Google
T ends in s udying he G eek house ma ke .
Keywo ds In la ion, Google T ends, Real es a e, Beha io al indica o s
Pape ype Resea ch pape
Beha io al
house p icing
models
157
© E angelos Vasileiou, El oi Hadad and Geo gios Melekos. Published in EconomiA. Published by
Eme ald Publishing Limi ed. This a icle is published unde he C ea i e Commons A ibu ion (CC BY 4.0)
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The cu en issue and ull ex a chi e o his jou nal is a ailable on Eme ald Insigh a :
h ps://www.eme ald.com/insigh /1517-7580.h m
Recei ed 10 Oc obe 2023
Re ised 29 Janua y 2024
Accep ed 4 Ma ch 2024
EconomiA
Vol. 25 No. 1, 2024
pp. 157-174
Eme ald Publishing Limi ed
e-ISSN: 2358-2820
p-ISSN: 1517-7580
DOI 10.1108/ECON-10-2023-0166
1. In oduc ion
The dynamics o he eal es a e ma ke s ha e puzzled inancial economis s and schola s o
decades due o he subs an ial impac o house p ices on economic ac i i y. P e ious
li e a u e has p edominan ly linked housing p ices wi h adi ional economic ma ke s, such
as GDP, income le els, popula ion ends and in e es a es (Bjø nland & Jacobsen, 2010;
Case, Shille , & Thompson, 2012;Gup a, Ju gilas, Mille , & Van Wyk, 2011;Plakanda as,
Gup a, Ka akilidis, & Woha , 2020;Simo-Kengne, Mille , Gup a, & Balcila , 2016). Majo
economic shi s, like al e a ions in mone a y policies o luc ua ions in in e es a es, ha e
been pinpoin ed as signi ican d i e s o housing p ices (De San is & Su ico, 2013;Dema y,
2010;E e e , de Haan, Jansen, McQuade, & Sama ina, 2021;Plakanda as e al., 2020;Rahal,
2016;Simo-Kengne e al., 2016). Economic g ow h and house p ices p esen a posi i e
co ela ion (Leung, 2003;Simo-Kengne e al., 2012,2016), as economic g ow h aises wages
and inc eases consump ion, ul ima ely aising house p ices as well (Kisho , 2007;Le au &
Lud igson, 2004). A posi i e change in in e es a es, in pa icula , which leads o highe
mo gage a es and housing cos s, has a nega i e impac on housing demand and exe s
downwa d p essu e on house p ices (De San is & Su ico, 2013;Dema y, 2010;E e e e al.,
2021;Rahal, 2016). Addi ionally, he in la ion channel sugges s a nuanced impac ; while
in la ion may s imula e esiden ial in es men due o eal es a e’s ole as an in la ion hedge
(Fama & Schwe , 1977), i could also lead o highe in e es a es, po en ially supp essing
eal es a e demand and ad e sely a ec ing house p ices (Dema y, 2010).
Howe e , mo e ecen s udies show con adic o y indings, highligh ing he limi ed
signi icance o Mac oeconomic, Mone a y, and Banking (MMB) undamen als on housing
p ices (Alkay, Wa kins, & Keskin, 2018). Hoesli, Lizie i, and MacG ego (2008) indica e ha
eal es a e o e s a minimal hedge agains high in la ion. Addi ionally, o he esea ch
sugges s ha changes in in e es a es ha e a limi ed impac on housing p ices (Glaese ,
Go lieb, & Gyou ko, 2015;Shi, Jou, & T ipe, 2014;Taylo , 2009), implying ha inc eases in
he policy a e may no e ec i ely dep ess eal housing p ices, pa icula ly du ing pe iods o
high in la ion. Real es a e can se e as a hedge agains in la ion (Fama & Schwe , 1977),
leading o inc eased demand o housing o mi iga e in la ion isks, consequen ly d i ing up
house p ices (Shi e al., 2014).
One po en ial explana ion o he limi ed impac o MMB ac o s on housing p ices lies in
he psychological dimension o eal es a e in es men , whe e consume beha io plays a
pi o al ole (Be acha, Lang, & Hausle , 2019;Clay on, Ling, & Na anjo, 2009;Hausle ,
Ruscheinsky, & Lang, 2018). Recen s udies highligh how op imis ic ou looks and shi s in
sen imen , de ached om economic undamen als, can ins iga e ‘bubble-bu s ing’
phenomena in housing ma ke s, leading o p ice luc ua ions (Ab aham & Hende sho ,
1996;Muellbaue & Mu phy, 2008;Shille , 2008). Op imis ic sen imen , d i en by
expec a ions o u u e housing e u ns, ends o a ac mo e homebuye s in o he ma ke
(Dong, Hui, & Yi, 2021), boos ing ansac ion olumes (Fische & S amos, 2013) and d i ing
up housing p ices (Asal, 2019;Hong, Kim, & Ahn, 2022;Tsai & Peng, 2011). Residen ial
p ope y’s dual ole as bo h a consume good and an in es men asse (G anzie a & Kozicki,
2015;Ma a ia, And
e, & Gup a, 2022), signi ican ly in luences demand o du able goods
and shapes in es o s’ isk pe cep ions owa d inancial asse s (Fuh e , 1993;Mishkin, Hall,
Sho en, Jus e , & Lo ell, 1978;Th oop, 1992;Van Raaij & Giano en, 1990). Gi en ha
housing sen imen impac s housing p ices, especially du ing pe iods o economic unce ain y
(Anas asiou, Kapopoulos, & Zeken e, 2021;De Band , Ba houmi, & B uneau, 2010), i is
essen ial o conside he beha io al e ec on housing ma ke s.
In his con ex , p io s udies e eal ha G eek homeowne s pe cei e houses as in es men
asse s a he han pu ely consump ion goods (Gounopoulos, Me ikas, Me ika, &
T ian a yllou, 2012) and iew housing as a c ucial in es men decision o he a e age
G eek ci izen (Papageo giou, Loulis, E s a hiades, & Ness, 2020). This s ands in con as o
ECON
25,1
158
he home owne ship a e in he Eu o a ea, which expe ienced a decline o e he las decade,
p ima ily a ibu ed o diminishing owne ship a es among young adul s and low-income
g oups (Calab ia & Calde , 2019) o escala ing housing p ices (
Ce m
ako
a & H omada, 2022).
Fu he mo e, G eece has aced se e e economic challenges, including a no able inancial
c isis (Lekkos, S aggel, Ke alas, & Vlachou, 2014), high le el o deb (Leschinski & Be am,
2017), inancial ins abili y (Anas asiou & Kapopoulos, 2023), de la ion p essu es (Lekkos
e al., 2014) and high ola ili y in housing p ices (Gounopoulos e al., 2012;Pe opoulos, Liapis,
& Thalassinos, 2023). These economic challenges po en ially in luence in es o beha io ,
con ibu ing o he impac on housing p ices beyond ma ke undamen als, as no ed by
Ma a ia e al. (2022). Gi en ha he G eek housing ma ke s ands ou wi h homeowne ship
a es (Gounopoulos e al., 2012), high impac om changes in consume beha io (Pe opoulos
e al., 2023) and is highly sensi i e o changes in inancial s ess condi ions (Anas asiou &
Kapopoulos, 2023), i is in iguing o s udy how hese unique cha ac e is ics in e ac wi h he
dynamics o he G eek housing ma ke , p o iding aluable insigh s o in es o s,
policymake s and esea che s alike.
In his s udy, we examine he in luence o beha io al sen imen a iables and
mac oeconomic undamen als on he a iabili y o G eek house p ices. Employing
EGARC(1,1) model (Nelson, 1991), we explo e how beha io al and MMB undamen als
impac housing ma ke ola ili y, using he House P ices Index (HPI) da a spanning om
2006 o 2022. Ou MMB undamen als encompass changes in GDP, in la ion and mo gage
in e es (MI) a es, ac o s known o signi ican ly a ec housing demand and p ices
(Bjø nland & Jacobsen, 2010;Case e al., 2012;E e e e al., 2021;Leung, 2003;Plakanda as
e al., 2020;Simo-Kengne e al., 2012,2016), especially in he G eek ma ke (Ape gis & Rezi is,
2003;Gounopoulos e al., 2012).
Fo beha io al sen imen a iables, we in eg a e Google sea ch-based sen imen da a
om Google T ends. No ably, Google T ends has ga ne ed a en ion among schola s o i s
eliabili y in measu ing economic and inancial unce ain y (Bilgin, Demi , Gozgo ,
Ka abulu , & Kaya, 2019;B odeu , Cla k, Fleche, & Powd ha ee, 2021;Choi & Va ian,
2012;P eis, Moa , & Eugene S anley, 2013;Vasileiou, 2021a,2023), and is ecognized as a
leading sen imen indica o in inancial analysis. Howe e , while sen imen no ably
in luences housing p ices (Abildg en, Hansen, & Kuchle , 2018;Hong e al., 2022;Ling,
Ooi, & Le, 2015;Muellbaue & Mu phy, 2008;Tsai & Peng, 2011), especially in he G eek
housing ma ke (Anas asiou e al., 2021;Anas asiou & Kapopoulos, 2023), eal es a e esea ch
has no ex ensi ely u ilized beha io al indica o s based on Google T ends. The ew
excep ions include Die zel (2016), who demons a es ha Google sea ch olume da a can ac
as a leading sen imen indica o and p edic u ning poin s in he US housing ma ke , and
Bulczak (2021), who employs Google T ends o p edic he UK eal es a e ma ke . While some
s udies on he G eek housing ma ke u ilize su ey-based sen imen indexes o elucida e
house p ice a ia ion (Anas asiou e al., 2021;Anas asiou & Kapopoulos, 2023), we ind no
e idence o s udies u ilizing Google T ends o cap u e beha io al sen imen .
Fo obus ness, we in oduced ou sen imen measu e in addi ion o ou MMB
undamen als indi idually. Ou main indings show ha media-based in o ma ion om
Google T ends is highly signi ican in elucida ing a ia ions in G eek housing p ices, beyond
he adi ional MMB undamen als. Ou analysis demons a es he po ency o ou sen imen
measu e in cap u ing he dynamics o he G eek housing ma ke , he eby enhancing he
unde s anding o he in e play be ween consume sen imen and adi ional economic
indica o s. These indings unde sco e he pi o al ole o media-based in o ma ion and
sen imen in shaping housing ma ke dynamics.
Ou s udy makes signi ican con ibu ions o he exis ing li e a u e in se e al key ways.
Fi s , we pionee he use o Google T ends da a in conjunc ion wi h mac oeconomic a iables
o elucida e a ia ions in house p ices. By le e aging Google T ends indices, which se e as
Beha io al
house p icing
models
159
beha io al indica o s o public in e es and sen imen (Vasileiou, 2021a,b), we a gue ha
in es iga ing media-based in o ma ion and sen imen is pa amoun o achie ing a mo e
nuanced unde s anding o G eek house p ice ola ili y. This inno a i e app oach no only
en iches he cu en body o esea ch bu also o e s a no el pe spec i e on he d i e s o
housing ma ke dynamics. Second, agains he backd op o economic unce ain y in G eece
and he p onounced sensi i i y o housing p ices o inancial ins abili y, ou s udy p o ides
comp ehensi e insigh s in o he impac o bo h beha io al pa e ns and economic s ess
condi ions. By employing a no el model-based app oach, we o e a de ailed examina ion o
he in e play be ween consume sen imen and MMB undamen s.
Ou indings no only enhance he unde s anding o he G eek housing ma ke dynamics
bu also se e as a aluable empla e o policymake s, egula o s and esea che s g appling
wi h economic challenges elsewhe e. By adap ing ou me hodology, policymake s and
egula o s can gain deepe insigh s in o he ac o s shaping housing ma ke s and de elop
mo e e ec i e s a egies o mi iga e isks and p omo e s abili y in housing sec o s ac oss
a ious economic con ex s. Thus, ou s udy no only ad ances economic li e a u e bu also
holds signi ican implica ions o policymake s and s akeholde s seeking o na iga e
u bulen economic landscapes and os e sus ainable housing ma ke s.
The es o his pape goes as ollowing: Sec ion 2 p esen s he a iables and he
p elimina y da a o ou s udy. Sec ion 3 analyses he econome ic model and p esen s he
empi ical esul s, and Sec ion 4 concludes he s udy, discusses he indings and sugges s
some ideas o u he esea ch.
2. Da a and a iables
In his pape , we use da a om he Bank o G eece o he HPI and he MI, and we ga he he
GDP yea on yea change (GDP_yoy) and In la ion (I) om he Hellenic S a is ical Au ho i y.
These a iables will be he MMB a iables ha a e usually used in simila s udies (Ape gis &
Rezi is, 2003).
F om beha io al s andpoin , he easy pa is ha i somebody is in e es ed in buying a
house, he/she sea ches he in e ne o p ope ies and p ices. In e ne sea ches a e a e y
use ul ool o schola s because hey enable us o inco po a e wha people a e in e es ed in
and his may be an indica ion o hei ac ions (Vasileiou, 2021b). The di icul pa is o ind
which a e he mos ep esen a i e e ms aking in o conside a ion speci ic ac o s ha could
in luence each ma ke . Fo example, du ing he las decade, he e has been conside able
discussion in G eece abou he in e es o o eigne s in buying G eek p ope ies, as well as he
impac o such ansac ions on he domes ic eal es a e ma ke and he economy as a whole
[1]. Fo eign buye s a e looking o pu chase aca ion homes o sea ching o in es men
oppo uni ies, whe eby hey buy houses o con e hem in o Ai bnb uni s. Non-EU na ionals
a e also seeking o ob ain a Golden Visa, which hey can do by buying p ope y (Lekkos e al.,
2014;Papageo giou e al., 2020).
The challenging aspec o he beha io al analysis lies in he iden i ica ion and
quan i ica ion o pe inen beha io al indices. Py ends acili a es he c ea ion o
beha io al indica o s by le e aging i s unc ionali ies o ex ac ing ela ed opics, que ies
and sugges ions. To cons uc hese indica o s, we explo e a ious sea ch e ms, as Py ends
allows he use o up o i e e ms simul aneously. The e icacy o di e en e m combina ions
is es ed o asce ain which combina ion bes encapsula es he sough -a e in e es .
The esul s a e no p esen ed in aw olumes; a he , hey a e no malized and indexed on
a scale om 0 o 100. To gauge in e na ional in e es , English e ms such as “G eece Golden
Visa,”“House Sales in G eece,”e c., a e employed. In con as , o domes ic in e es
o igina ing om G eek use s, e ms like «Π
ω
λή
σεις
Σ
πιτι
ώ
ν
»and «E
ν
o
ι
κ
ι
ά
σεις
Σ
πιτι
ώ
ν
»
( ansla ed as “House Sales”and “Homes o Ren ”in G eek, espec i ely) a e es ed.
ECON
25,1
160
Addi ionally, he ac o isi ing eal es a e websi es, spanning om eal es a e agen s o
pla o ms o house en als and sales, se es as an indica o o a p ospec i e willingness o
pu chase p ope y.
Gi en he abundance o sugges ed and ela ed e ms, and he my iad possible
combina ions, a new code is implemen ed o de e mine he mos ep esen a i e e m
combina ion o he speci ied objec i e. Consequen ly, a Local Sea ch (LS) index is in oduced
o encapsula e he in en ion o G eek indi iduals o acqui e a p ope y. Wo ld Sea ches Index
is de ised o quan i y global in e es in G eek eal es a e.
Figu e 1 isually ep esen s he ela ionship be ween each a iable, including MMB and
he beha io al indices, wi h he Housing P ice Index (HPI). This g aphical ep esen a ion aids
in comp ehending he in e play be ween hese a iables.
We should no e ha house p ices in G eece dec eased om he end o 2008 up un il he end
o 2017, which closely coincides wi h he G eek so e eign deb c isis and GDP decline ha
las ed om 2009 o 2017. These yea s cons i u e a la ge pe iod o ou sample, bu since 2017
house p ices ha e isen. We p esen he ela ionship o he explana o y MMB a iables (MI, I,
GDP_yoy) and he beha io al indices (Wo ld_Sea ches, LSs) wi h he dependen a iable
(HPI) in Figu e 1, and we cla i y he ollowing poin s:
(1) In la ion p esen s a nega i e ela ionship o he HPI, which means ha in es men s in
house p ope y we e no a way o hedge agains in la ion du ing he en i e examined
pe iod. This uns coun e o wha in e na ional heo y sugges s in he case o a small,
eme ging and open economies ha do no ha e a e y s ong cu ency (Assibey-
Yeboah & Mohsin, 2014;Tho n on & Vasilakis, 2016). A possible explana ion o
hese p elimina y esul s could be ha G eece may be a small and open economy, bu
i belongs o he Eu opean Union (EU) and he Eu opean Mone a y Union (EMU), and
i has s ong cu ency. I G eece we en’ a membe o he EU/EMU, i s cu ency would
ha e p obably dep ecia ed du ing he so e eign c isis and in la ion issues would
ha e eme ged (e.g., cos in la ion due o p ice inc eases in oil, impo ed goods, e c.). In
such a case, house p ices in a so cu ency would be highe . The ac ha G eek
house p ices dec eased du ing he deb c isis, and in la ion was no so high due o EU/
EMU and o he Eu o.
(2) GDP has posi i e beha io o he house p ices, as he heo y sugges s. One easily
obse ed excep ion is du ing he COVID-19 pe iod when he GDP alls, bu he house
p ices emain almos he same. This can be a ibu ed o he s imulus packages ha
ga e liquidi y and income du ing he isola ion and no e y p oduc i e yea s
(Vasileiou, 2023).
(3) MI a es seem o be highe when he house p ices we e highe and lowe when he
p ices declined. This posi i e ela ionship could be explained by he ac ha bank
in e es s ollowed he Eu opean a es when G eece su e ed om i s so e eign c isis
(2009–2017), due o i s s ong cu ency (Eu o) and he assis ance o EU/EMU. When
house p ices ell, MI a es we e as low as hose in he Eu o a ea. Low in e es s educe
he cos o a house and make he in es men case mo e an alizing, and usually he
lead o an inc ease o he demand and o he p ices. Howe e , in G eece, local and
o eign in e es in buying p ope y in he coun y inc eased when p ices and
mo gage a es inc eased.
(4) Wo ld in e es in G eek p ope ies seems o ha e a posi i e ela ionship wi h house
p ices in he las HPI ise pe iod, bu i has a seasonali y [2].
(5) The LSs o G eek p ope y seem o ha e a smoo he ime se ies (wi hou seasonali y)
and a posi i e ela ionship wi h he HPI.
Beha io al
house p icing
models
161
Table 1 depic s he co ela ion ma ix, e ealing pi o al insigh s in o he in ica e
ela ionships among key a iables wi hin ou da ase . No ably, he HPI exhibi s a obus
posi i e co ela ion wi h in e es a es (MI) (0.881), unde sco ing he signi ican in luence o
in e es a es on housing p ices. Con e sely, he HPI demons a es a mode a e nega i e
co ela ion wi h in la ion (I) (0.504), sugges ing a po en ial in e se ela ionship be ween
in la ion and housing p ices. In la ion also mani es s s ong nega i e co ela ions wi h MI
(0.566) and LSs (0.744), hin ing a he po en ial impac o in la ion on mo gage a es and
(con inued)
Figu e 1.
House P ice index and
he Explana o y
Va iables
ECON
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(con inued)Figu e 1.
Beha io al
house p icing
models
163
local in e es in housing. Conside ing he beha io al a iables, Google T ends Wo ldwide
Sea ches (Wo ld_Sea ches) demons a e a weak posi i e co ela ion wi h HPI; howe e , he
LSs (Local_Sea ches) exhibi s ong posi i e co ela ions wi h HPI (0.818) and MI (0.823),
highligh ing he subs an ial in luence o local sen imen and in e es on housing ma ke
dynamics. These co ela ions unde sco e he complex in e play be ween mac oeconomic
ac o s, consume sen imen and housing ma ke ends.
Las ly, Table 2 p esen s he desc ip i e s a is ics o ou s udy. We use he i s di e ences
o hese a iables because many o hem a e no s a iona y when we es hem a le el [3].
No able obse a ions include ma ginal dec eases in HPI e u ns, jux aposed wi h mode a ely
posi i e in la ion a es, hin ing a po en ial shi s in ma ke dynamics. Howe e , he high
s anda d de ia ions o hese a iables indica e signi ican a ia ions in housing p ices and
in la ion, possibly a ibu ed o ecen economic challenges aced by G eece. The GDP change
ho e s ma ginally abo e 0.00, indica ing s able economic g ow h o e he pe iod, albei wi h
po en ial ou lie s ha unde sco e economic esilience. The nega i e mean o MI signi ies a
HPI I GDP_yoy MI Wo ld_Sea ches Local_Sea ches
HPI 1.000 0.504 0.156 0.881 0.189 0.818
I0.504 1.000 0.145 0.566 0.256 0.744
GDP_yoy 0.156 0.145 1.000 0.081 0.352 0.302
MI 0.881 0.566 0.081 1.000 0.328 0.823
Wo ld_Sea ches 0.189 0.256 0.352 0.328 1.000 0.126
Local_Sea ches 0.818 0.744 0.302 0.823 0.126 1.000
Sou ce(s): Table by au ho s
Figu e 1.
Table 1.
Co ela ion ma ix o
ou a iables
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6. I somebody has he money o buy a house, s/he can buy i quickly, bu in e es ed pa ies ha eside
ab oad will need o a leas isi he p ope y on si e and his akes longe .
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