52 2018, XXI, 1
Ekonomie
DOI: 10.15240/ ul/001/2018-1-004
In oduc ion
Tax sys ems o de eloped coun ies con ain
p o isions ha gi e a p e e ed s a us o
housing and homeowne ship. A signi i can
elie is p o ided especially by he combina ion
o non- axa ion o impu ed en al income and
mo gage in e es paymen deduc ibili y. Real
use cos s o owne -occupied housing a e
educed (see Po e ba & Sinai, 2008) and hus
a bias in a ou o he homeowne ship is c ea ed
when households a e encou aged o buy a he
han o en hei dwellings. Al hough he e is
a p ope y ax, ha is le ied o ax he impu ed
en , he elie o he mo gage in e es paymen
can be so gene ous ha i mi iga es he e ec
o he p ope y ax (C owe, Dell’A iccia, Igan,
& Rabanal, 2011). The ac is ha he p ope y
ax in many coun ies is no high enough o be
a pe ec subs i u e o he impu ed en axa ion
(Hemmelga n & Nicodéme, 2010). Fu he mo e,
homeowne ship is mo e a ac i e when capi al
gains a e no axed in a neu al manne . And
p o i s om home sales a e no usually axed.
The housing- ela ed ax allowances a e one o
main ax expendi u e i ems in EU coun ies (see
Eu opean Communi ies [EC], 2013).
The p o-homeowne ship ax policy is
jus i i ed by ma ke ailu es and a desi e o
enhance housing oppo uni ies a ailable
o ci izens (And ews, Calde a Sánchez, &
Johansson, 2011). Howe e i seems ha o
he ime being economis s a he conclude ha
he ax ad an ages p o ided o homeowne s
a e no e y e i cien a achie ing gi en
objec i es. A gene al goal in p ac ice is o boos
he homeowne ship o o inc ease housing
demand and consump ion. Cecche i, Mohan y,
and Zampolli (2011) claim ha he gene ous ax
elie o mo gage in e es paymen could ha e
played a ole in expanding he homeowne ship
in some coun ies. Howe e acco ding o
And ews, Calde a Sánchez, and Johansson
(2011) he e is no clea c oss-coun y
ela ionship be ween he ex en o he mo gage
in e es deduc ibili y and he homeowne ship
a es. Ne e heless hey admi ha households’
p e e ence o he homeowne ship can be
in l uenced also by ax policy. Bou assa and
G igsby (2000) o Glaese and Shapi o (2002),
based on empi ical e idence on U.S. si ua ion,
concluded ha impac o he mo gage in e es
deduc ibili y on he homeowne ship a e was
minimal. And C owe e al. (2011) e en asse
ha he homeowne ship a es a e nega i ely
ela ed o he ex en o he ad an ageous ax
ea men o homeowne ship.
An a gumen in a ou o a highe a e o
he homeowne ship is exis ence o posi i e
ex e nali ies, e. g. enjoymen o neighbou s
and passe sby gene a ing h ough home
main enance and ga dening, be e ou comes
o child en, and long- e m p ospec s o
a communi y (Bou assa & G igsby, 2000 o
Glaese & Shapi o, 2002). Glaese and Shapi o
(2002) hink ha e idence on ex e nali ies is
weak bu sugges i e. Bu Hilbe and Tu ne
(2013) belie e ha he homeowne ship
gene a e ew o no posi i e ex e nali ies.
Mo eo e , he e could be nega i e ex e nali ies
ela ed o housing consump ion, e. g. lea ing
small ci y apa men s o la ge places on
he inge o a ci y, inc easing seg ega ion by
income o en y inci ed by ancy homes (Glaese
& Shapi o, 2002). A lowe labou mobili y
and highe unemploymen among owne -
occupan s in compa ison wi h he mobili y
and unemploymen o en e s can be ha m ul
e ec o he homeowne ship as well (And ews,
Calde a Sánchez, & Johansson, 2011). Finally,
he homeowne s could u ilize hei poli ical
powe o cu o new house cons uc ion in
o de o aise hei house p ices (Glaese &
Shapi o, 2002). As O’Sulli an and Gibb (2012)
summed i up, he homeowne ship does no
DOES THE TAX RELIEF FOR
HOMEOWNERSHIP HAVE EFFECT
ON HOUSEHOLD MORTGAGE LEVERAGE?
Ba bo a Slin áko á, S anisla Klaza
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53
1, XXI, 2018
Economics
gene a e economic bene i s o he mac o-
economy o speci i c households which would
jus i y a gene al p og amme o ax concessions
o homeowne s.
As an a gumen suppo ing he owne -
occupa ion we could p esen ha accumula ed
housing weal h could se e as means o p i a e
insu ance (Ansell, 2013) o ha home equi y
could p o ide an addi ional sou ce o e i emen
income beyond pensions, i.e. e e se
mo gages (Toussain , 2013). Howe e we a e
no amilia so a wi h any e idence ha he
owne -occupa ion se es well as an ins umen
o pension secu i y. On he o he hand, wha is
al eady a subjec o examina ion is co ela ion
be ween he mo gage in e es deduc ibili y
and g ow h o house p ices o inc eased house
p ices ola ili y. O ganisa ion o Economic Co-
ope a ion and De elopmen [OECD] (2009) o
And ews, Calde a Sánchez, and Johansson
(2011) o e some e idence o a posi i e
co ela ion be ween he ax elie on mo gage
in e es and a iabili y in house p ices. Keen,
Klemm, and Pe y (2010), And é (2010),
Su he land, Hoelle , Me ola and Ziemann
(2012) o u he au ho s poin ou ha he ax
subsidy is likely, depending on a p ice elas ici y
o housing supply, o be capi alised in o house
p ices. In addi ion he ax incen i e o deb -
i nancing o e o he sou ces o i nancing o
own dwellings could esul in o e in es men
in housing and misalloca ion o capi al s ock
wi h nega i e e ec s on a long- e m economic
g ow h (see e.g. Saa imaa, 2009; And é, 2010;
Hemmelga n & Nicodéme, 2010; Ven y, 2010).
Finally, he e is ag eemen among au ho s
ha he housing ax elie is eg essi e, i.e.
i a ou s ich households. Highe -income
households bene i om he ad an ageous ax
ea men o housing, namely om he mo gage
in e es deduc ibili y, mo e han lowe -income
households because hey ha e highe a es o
he homeowne ship, hey buy mo e expensi e
houses, and hei ma ginal ax a es a e highe
(see Bou assa & G igsby, 2000; And é, 2010;
Keen, Klemm, & Pe y, 2010; Ma saganis, 2014;
Ven y, 2010; And ews, Calde a Sánchez, &
Johansson, 2011).
The e is ano he impo an eason why
he housing axa ion, especially he mo gage
in e es deduc ibili y, a ac a en ion o
economis s. I is because i migh suppo
deb c ea ion. Jo da, Schula ick, and Taylo
(2014) ound ha household le e age a ios
ha e inc eased subs an ially in many coun ies
o e he 20 h cen u y: abou wo hi ds o
bank lending oday consis s o he loans o
he household sec o o he pu chase o eal
es a e, acco ding o Eu opean Cen al Bank
[ECB] (2014) he majo i y o he Eu opean
household bo owing is comp ised by loans o
house pu chase. Fu he mo e hey showed ha
con empo a y business cycles a e inc easingly
shaped by he dynamics o he mo gage
c edi and ha he mo gage c edi became
a speci i c sou ce o i nancial ins abili y in
ad anced economies a e he Second Wo ld
Wa . And Jo da, Schula ick, and Taylo (2015)
demons a ed ha he c edi - i nanced housing
p ice bubbles a e mo e dange ous o i nancial
sec o and eal economy han he unle e aged
bubbles. How indeb edness can a ec
mac oeconomic pe o mance and households,
see Su he land e al. (2012) o McGowan
(2013). The household indeb edness impac on
economic g ow h ha e been analysed by Izák
(2012).
A ques ion aises whe he he housing
axa ion, and he p esupposed deb bias
embedded in i , does a ec he household
indeb edness, and whe he he nega i e
consequences o high le els o deb could
be, pa ly, ex a cos o he axa ion a ou ing
housing. Hemmelga n and Nicodéme (2010),
Keen, Klemm, and Pe y (2010), Be na di
(2011), Cecche i, Mohan y, and Zampolli
(2011), Hemmelga n, Nicodéme, and Zanga i
(2011), Su he land e al. (2012) o Ga nie e al.
(2013) sugges ha he ax ea men o owne -
occupied housing may ha e played a ole.
Households ha e been p obably encou aged
by he mo gage in e es elie o p e e
bo owing. As a esul he household deb may
be highe han i would be o he wise. Wolswijk’s
(2005) simple g aphical analysis shows ha he
lowe he i nancing cos s, dec eased by he ax
subsidy, he highe he deb -GDP a io. Keen,
Klemm, and Pe y (2010) a i m ha coun ies
o e ing mo e a ou able ax ea men o he
homeowne ship ha e highe a ios o mo gage
deb . On he o he hand C owe e al. (2011)
do no see a signi i can ela ion be ween he
ax ea men o housing and he a io o he
mo gage deb o GDP. I is necessa y o be
ca e ul, e.g. Ellis (2006, p. 11) wa ns ha i is
no easy o p o e he co ela ion be ween he
ax ad an ages o he homeowne ship and he
household deb since “ he ax egime in e ac s
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54 2018, XXI, 1
Ekonomie
wi h o he aspec s o he housing- i nance
sys em in some imes complex ways”. OECD
(2009) poin s ou ha home-equi y loans and
eal house p ices ha e isen in many coun ies
despi e he ac ha ax incen i es a ied
conside ably. I sugges s ha o he ac o s
a ec hese phenomenons. Howe e OECD
(2009) also admi s ha he high ax elie on
mo gage in e es co ela es wi h he high
a iabili y in house p ices which can lead o
se ious household c edi p oblems.
Deepe insigh in o he ela ionship be ween
he ax incen i e and household deb can be
p o ided by s udies conce ning indi idual
coun ies. Dunsky and Follain (2000) o Mun oe
(2014) analysed he Uni ed S a es da a and
ound ou ha he demand o home mo gage
deb esponded o he mo gage in e es
deduc ion. Hende sho , P yce, and Whi e
(2002) e ealed ha he homeowne le e age
in he Uni ed Kingdom was sensi i e o he
deduc ibili y o mo gage in e es . Alan and Le h-
Pe e sen (2006) examined he 1987 ax e o m
in Denma k which made he holding o deb less
a ac i e. Rouwendal (2007) iden i i ed he ax
incen i e o i nancing he homeowne ship wi h
a mo gage as impo an d i ing o ce behind
he inc ease in equency o mo gage use in
he Ne he lands. Acco ding o Somme oll
(2007) No wegian households educed hei
deb as a esponse o less gene ous in e es
deduc ions a e he ax e o m. Finally,
Saa imaa’s (2009) esul s om he s udy o he
impac o he ax e o m in Finland indica e ha
high income households wi h high ma ginal ax
a es esponded o he ax incen i e educ ion
by clea ly dec easing hei mo gage bo owing.
On he o he hand Jappelli and Pis a e i (2004)
ound no e idence ha he ax ea men
shaped he demand o mo gage deb in I aly.
I is possible o sum up ha ax e o ms, ha
educed alue o he mo gage in e es elie
(which is a ec ed also by a ma ginal ax a e)
and hus weakened he incen i e o bo ow
in o de o own home, mos ly led o lowe
household le e age. This could p o e he
ole o he ax incen i e a ou ing he deb -
i nanced homeowne ship (see he Eu opean
Commission axa ion pape s abou ax e o ms
published in 2011-2014). A e all, he Eu opean
Commission ecommends o he EU Membe
S a es o educe he deb bias in hei housing
axa ion and subsequen ly maps changes in
axa ion ules in he membe coun ies, see e.g.
(EC, 2014). Ga nie e al. (2013) con i m ha
majo changes in he housing axa ion in many
coun ies conce ned he deb bias and ocused
on limi ing he deduc ibili y o mo gage in e es .
Ne e heless Somme oll (2007) poin s ou
ha e ec s o ax e o ms on housing ma ke s
can be o se by o he ac o s in he economy.
O cou se, he housing axa ion is no
he only ac o in l uencing he household
demand o mo gage. In e es a es, i nancing
condi ions (i.e. i nancial de egula ion and
inno a ion on i nancial ma ke ), income and
demog aphy ha e been iden i i ed in bo h
heo e ical and empi ical s udies as impo an
de e minan s o he household indeb edness.
In addi ion, ac o s cha ac e ising housing
ma ke , especially house p ices, should be
aken in o conside a ion, oo – see e.g. Debelle
(2004), Jacobsen and Naug (2004), Gi oua d,
Kennedy, and And é (2006), Dynan and Kohn
(2007), ECB (2009), And é (2010) o Bokha i,
To ous, and Whea on (2013).
Aim o ou esea ch was o explo e whe he
he e is he ela ion be ween he income ax
incen i e o homeowne s, i.e. he mo gage
in e es deduc ibili y and exemp ed impu ed
en income, and he household indeb edness.
To he con a y o s udies men ioned abo e,
which analysed mic oda a, we conduc ed
a c oss-coun y s udy like Wolswijk (2005)
who analysed impac o he housing axa ion
on he mo gage deb g ow h in EU coun ies
on assump ion ha he axa ion may ha e
a po en ially la ge ole in a ec ing he household
le e age. The emainde o he pape is di ided
in o h ee sec ions and a conclusion. In he nex
sec ion we ocus on he cons uc ion o ou
key explana o y a iable ep esen ing he ax
ea men o he owne -occupied housing which
is supposed o be deb encou aging. Then we
desc ibe b ie l y he o he explana o y a iables
we wo ked wi h. The econome ic me hods we
used a e discussed in sec ion 2 and sec ion 3
epo s esul s.
1. Va iables Used in he Household
Mo gage Le e age Reg ession
Model
We ollowed Wolswijk’s (2005) wo k in ou
esea ch. Wolswijk applied a mul iple (panel)
eg ession analysis in o de o measu e he
e ec o he i scal ins umen s on he mo gage
deb g ow h in he EU coun ies. We also
employed he eg ession analysis whe e
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55
1, XXI, 2018
Economics
he dependen a iable was he household
mo gage le e age. The mo gage le e age
was measu ed by he a io o o al ou s anding
esiden ial loans (on lende ’s books a he
end o he yea , in EUR million) o household
g oss disposable income (in EUR million). The
da a on bo h loans and income we e p o ided
by he HYPOSTAT 2014 published by he
Eu opean Mo gage Fede a ion – Eu opean
Co e ed Bond Council (EMF-ECBC) – see he
webpage h p://www.hypo.o g/Con en /de aul .
asp?PageID=524. The e ec o he income ax
incen i e o homeowne s was measu ed by
a special a iable – see sec ion 1.1. Conside ing
li e a u e and da a a ailabili y we p oposed
a numbe o he o he a iables which migh
explain he household deb – see sec ion 1.2.
1.1 Cons uc ion o he Homeowne
Tax Relie Va iable
Wolswijk (2005) cons uc ed he i scal
ins umen s a iable as he a e - ax capi al
cos s which cap u ed he deduc ibili y o
mo gage in e es paymen . The capi al cos s
we e de i ed om a nominal mo gage in e es
a e and amoun o mo gage. Then hey we e
adjus ed by he ele an ax a e which e l ec ed
whe he he mo gage in e es was deduc ible
om he income ax and whe he i was
deduc ible ully o wi h a limi . The cos s we e
exp essed as he pe cen age o a house p ice.
Since we assumed ha indi iduals conside
he mo gage in e es and he elie p o ided
by he income ax law a he sepa a ely when
hey make decision on bo owing we decided
o include wo explana o y a iables in o
ou eg ession model. We used he a iable
ep esen ing he impac o he income ax
ea men o housing on he homeowne capi al
cos s besides he mo gage in e es paymen
as ano he a iable.
Ou key explana o y a iable ( he
homeowne ax elie ) was de i ned as he a io
o he p e- ax capi al cos s (CC0) o he a e - ax
capi al cos s (CC1):
(1)
whe e is nominal mo gage in e es a e; M is
mo gage alue; TW is ax wedge.
I he a io is highe han 1, housing and
homeowne s a e subsidised by he income ax
sys em. The a io smalle han 1 means axa ion
o housing, i.e. impu ed en is axed since i
exceeds he mo gage in e es paymen . The
di e ence be ween he p e- ax capi al cos s
and he a e - ax capi al cos s is called he
ax wedge and i is used as an indica o o he
ex en o he ax elie on deb i nancing o he
owne -occupied housing (see e.g. And ews,
2010). The ax wedge has been calcula ed also
by an den Noo d (2003) when he es ima ed
he eal i nancing cos s o housing.
To es ima e he capi al cos s be o e and
a e axa ion and he ax wedge i is necessa y
o model a axpaye who migh ep esen he
popula ion aking ou mo gages. The e we e
wo inspi a ions a ailable o be used. Fi s ,
we ollowed Keen, Klemm, and Pe y (2010),
who used he In e na ional Mone a y Fund
me hodology, see Hemmelga n, Nicodéme and
Zanga i (2011) o In e na ional Mone a y Fund
(2009), espec i ely, in o de o calcula e e ec i e
ax a es on he owne -occupied housing o
he pu pose o in e na ional compa ison. We
made he ollowing assump ions abou ou
model axpaye : he is an unma ied pe son
wi h no child in he op income ax b acke
who pu chased his p ima y dwelling o a p ice
i nanced 80% wi h a mo gage a a ce ain
in e es a e. The assump ion abou he op
income axpaye was suppo ed by Gi oua d,
Kennedy, and And é (2006) acco ding o whom
he mos indeb ed households a e hose wi h
he highes incomes. The op income was
de i ned as double he a e age wage which is
he h eshold o he op income ax b acke in
he mos EU-15 coun ies. The a e age wages
da a we e d awn om he OECD Taxing Wages
publica ions. The p ice o dwelling was es ima ed
as 5-mul iple o he op income. The mo gage
in e es a e was app oxima ed by he annual
a e age o ep esen a i e in e es a es on new
esiden ial loans p o ided by he HYPOSTAT
2014. Mo eo e , we used he nominal a e like
Wolswijk (2005) who a gued ha i is mo e
ele an o indi idual’s decision-making on he
mo gage. Second, since an den Noo d (2003)
calcula ed his ax wedge o a single ea ne
couple wi h wo child en and Wolswijk (2005)
es ima ed he ele an ax a e o an a e age
amily, we c ea ed an al e na i e model axpaye .
We modi i ed he model axpaye ’s amily s a us:
he is ma ied wi h wo child en. We p o ide
esul s o eg ession analysis o bo h single and
amily axpaye s in he sec ion 3.
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56 2018, XXI, 1
Ekonomie
Like Wolswijk (2005) we wan ed o include
he o me 15 EU membe s a es in o ou
analysis bu due o a lack o da a ou coun y
sample does no con ain G eece. We co e ed
he pe iod om 2004 o 2013, i.e. we s a ed
when Wolswijk ended. To calcula e he a e -
ax capi al cos s we had o es ima e he ax
wedge o e e y coun y and each yea using
e ec i e income ax law p o isions. We ook
in o accoun he mo gage in e es deduc ibili y
as well as axa ion o impu ed en jus as an
den Noo d (2003). Fu he mo e we explici ly
dis inguished di e en ax elemen s used in
income ax codes o a ou he owne -occupied
housing and deal wi h limi s on he deduc ible
amoun mo e exac ly han Wolswijk (2005).
The e we e di e en o ms o he ax elie
in he EU coun ies in he gi en pe iod. Aus ia,
Belgium, Denma k, Luxembou g and he
Ne he lands applied a deduc ion om income
o a ax base. When he deduc ion is used he
amoun , which a axpaye could sa e, depends
no only on he mo gage in e es paymen bu
also on a ma ginal ax a e ( he ma ginal ax
a es we e gained om he OECD Taxing Wages
publica ions). Mo eo e , Belgium, Luxembou g
and he Ne he lands axed he impu ed en – hen
he in e es is deduc ible i s agains his income.
The impu ed en was se ei he as a ac ion
o he house p ice (i.e. o he Ne he lands,
acco ding o he Eu opean Commission axa ion
pape s) o as a pe cen age o household income
(i.e. o Belgium and Luxembou g, acco ding o
Eu os a (2013)). A c edi lowe ing a ax liabili y
was applied in Finland, F ance, I eland, I aly,
Po ugal, Spain and Sweden. The ax wedge
in his case is easie o es ima e because i is
equal o he in e es . The e was no ax elie in
Ge many and he Uni ed Kingdom in he pe iod
2004-2013.
In ac we applied complica ed o mulas
o he ax wedge es ima ions because he e
we e a ious limi s on he amoun s o he
deduc ions o c edi s. The amoun s we e
usually de i ed om he mo gage in e es
paymen as a ce ain pe cen age and hey we e
mos ly capped wi h a ceiling which somewhe e
depended on axpaye ’s cha ac e is ics, e.g.
income. Especially, he p esence o wi e and
child en inc eased he ceiling on he c edi in
Finland, F ance and I eland.
The ax wedge should be equal o he sum
o annual amoun s sa ed du ing he pe iod o
epaying a mo gage. Howe e since ou model
axpaye s in all he coun ies we e assumed
o epay a mo gage o he same ime we
could simpli y he calcula ion. The sa ings on
he ax liabili y we e es ima ed as he amoun
sa ed in he i s yea o he epaymen pe iod.
Mo eo e we assumed ha he ax ea men o
he mo gage in e es and impu ed en would
be s able o e he whole epaymen pe iod. In
ac , he ax ea men o he owne -occupied
housing signi i can ly changed in Belgium,
F ance, I eland, Po ugal o Spain du ing he
pe iod 2004-2013.
P ecision o ou ax wedges es ima es
was in l uenced by quali y o a ailable da a.
We had o ely on in o ma ion abou axa ion
p o ided by seconda y sou ces. We compiled
he in o ma ion om he Taxes in Eu ope
da abase (see he webpage h p://ec.eu opa.
eu/ axa ion_cus oms/ axa ion/gen_in o/in o_
docs/ ax_in en o y/index_en.h m), he OECD
Taxing Wages publica ions and he Eu opean
Commission axa ion pape s published in
2011-2014. Quali y o he da a di e ed ac oss
coun ies: some coun ies did no p o ide so
much de ails and some imes di e en sou ces
did no p o ide he same da a abou he same
coun ies.
Nei he an den No d (2003) no Wolswijk
(2005) included he p ope y ax o he
homeowne in o hei calcula ions o he ax
wedge o he a e - ax capi al cos s, espec i ely.
We also igno ed his ax on he assump ion ha
he e is no di e ence in he use cos s be ween
own and en ed housing since he p ope y ax
bu den is assumed o be ully bo ne by he
indi idual using he dwelling (i.e. an owne o
a enan ). Fu he mo e, Wolswijk (2005) used
a modi i ed i scal ins umen s a iable, which
included axa ion o expec ed capi al gains
om he house sale, in ano he speci i ca ion
o his eg ession model bu wi h no sa is ac o y
esul s. We igno ed he capi al gain axa ion
( he capi al gain is usually ax-exemp ) as well
as ansac ion axes on assump ion ha he
model axpaye s do no conside selling hei
dwelling in u u e. A e all he mo gage in e es
deduc ibili y combined wi h he non- axa ion
o impu ed en a e he p o isions which a e
assumed o il households o bo owing he
mos .
1.2 The O he Explana o y Va iables
D awing om li e a u e and checking a ailabili y
o s a is ical da a we iden i i ed he ollowing
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57
1, XXI, 2018
Economics
a iables which migh impac on he household
indeb edness and which would be sui able o
he eg ession analysis. On assump ion ha
weal hie households a e able o bo ow mo e
money in o de o buy houses we used he
GDP and i nancial wo h pe capi a a iables
ep esen ing weal h. Financial wo h pe capi a
was de i ned as he household i nancial ne
wo h pe capi a o annual household income
pe capi a a io. Supposing ha he unemployed
people ha e limi ed oppo uni ies o bo ow he
unemploymen ( a e) a iable was added, oo.
Mo gage in e es paymen as a po ion
o household income cons i u ed he a iable
ep esen ing cos s o bo owing in ou analysis.
The in e es paymen was de i ed om he
annual a e age o ep esen a i e in e es a es
on new esiden ial loans.
Fu he unde lying d i e o he housing
deb a e house p ices. We supposed ha he
p ices could impac on he mo gage demand
bo h nega i ely and posi i ely. I he p ices
inc ease households ha e o ake ou la ge
mo gages. On he o he hand inc eased p ices
can educe demand on he housing ma ke and
hus a lowe amoun o mo gage is necessa y
o acqui e dwellings. The house p ices
de elopmen was app oxima ed by he nominal
house p ices index om he HYPOSTAT 2014
which e l ec s he changes in house p ices
obse ed o e he gi en pe iod. In addi ion o
his “p ice” a iable we included he indica o o
he di e ence be ween he HYPOSTAT house
p ices index and he ha monised index o ac ual
en s om he EUROSTAT s a is ics, he ea e
he home- en wedge a iable. The e ec o he
home- en wedge on he mo gage le e age
was supposed o be nega i e, i. e. i he own
housing p ice inc eases in ela ion o he en al
housing p ice he amoun o mo gage deb
aken up is supposed o dec ease because
households p e e he en al housing.
To cap u e he in l uence o popula ion
s uc u e which migh de e mine he demand o
housing we wo ked wi h bo h he young and old
dependency a ios. Since senio s ha e al eady
secu ed hei housing he le el o he household
mo gage le e age should dec ease wi h
a highe po ion o olde people in popula ion.
On he o he hand we assumed a posi i e e ec
o he young dependency a io because young
people should ha e a highe need o secu e
hei shel e . Mo eo e hei i nancial si ua ion
p esumably allows hem o bo ow.
Finally, since he e we e changes in
measu ing he da a necessa y o ou dependen
a iable in di e en yea s o di e en coun ies
we used a dummy a iable o con ol o he
ime se ies b eaks.
Da a o he independen a iables we e
ob ained om a ious sou ces, i.e. om
he HYPOSTAT 2014, he OECD s a is ics,
EUROSTAT s a is ics and he ILO s a is ics.
S a iona i y o da a is eques ed o a p ope
calcula ion o p- alues in eg ession models o
panel da a. We used he Le in-Lin-Chu es
(LLC), assuming ha he e was a common uni
oo p ocess iden ical ac oss c oss-sec ions,
as well as Dickey–Fulle es (ADF-GLS),
allowing o indi idual uni oo p ocesses o
a y ac oss c oss-sec ions, in o de o unco e
he p esence o uni oo s in ime se ies o da a
o he a iables desc ibed abo e o all he
coun ies in ou sample. The es designed by
Le in, Lin, and Chu (2002) was applied wi h
he cons an including 0 lags. The ADF es
was done using he GLS p ocedu e sugges ed
by Ellio , Ro henbe g, and S ock (1996) wi h
a g ea e powe han he s anda d Dickey–
Fulle app oach. Mo eo e , he o e all es wi h
null hypo hesis, ha he se ies in ques ion had
a uni oo o all he panel uni s, was calcula ed
using he me hod o Im, Pesa an, and Shin
(2003). Resul s o he in e se chi-squa e,
in e se no mal and logi es s we e agg ega ed
using he Choi me a- es (see Choi, 2001;
Co ell & Lucche i, 2016) – i nal esul s a e
shown in he las column o Tab. 1. The same
null hypo hesis (H0) and al e na i e hypo hesis
(H1) we e o mula ed o bo h es s: H0 was
ha all o he indi idual ime se ies exhibi a uni
oo , and H1 was ha none o he se ies has
a uni oo . Fu he mo e i he p- alue was low
he null hypo hesis was ejec ed which mean
ha a ime se ies was s a iona y. Resul s o he
s a iona i y es s a e in Tab. 1.
The p- alues showed ha he i nancial
wo h pe capi a and nominal house p ices index
se ies we e non-s a iona y. The da a o he
i nancial wo h pe capi a exhibi ed he uni oo s
and he s a iona i y o hese da a was ob ained
by i s di e ences. The p oblem wi h non-
s a iona i y o he nominal house p ices index
se ies was sol ed by using da a on (annual and
ela i e) changes in his index which we e also
a ailable in he HYPOSTAT 2014. The change
in nominal house p ices indices se ies was
al eady s a iona y and a new a iable, labelled
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58 2018, XXI, 1
Ekonomie
“house p ices”, was se up. See he p- alues o
he adjus ed se ies in he bo om o he Tab. 1.
Values o he LLC es o he GDP pe capi a
a iable we e ambiguous, ne e heless we
decided o conside he se ies as s a iona y. All
he o he se ies we e s a iona y.
Tab. 2 p esen s desc ip i e s a is ics o all
he a iables used in a eg ession analysis,
a iable
LLC ADF-GLS
coe i cien - a io z-sco e [p- alue] Me a- es s p- alue
household mo gage le e age -0.303110 -8.524 -6.40937 [0.0000] < 0.00
single homeowne ax elie -0.607120 -6.050 -2.98838 [0.0014] NA
amily homeowne ax elie -1.012400 -10.698 -6.9322 [0.0000] NA
GDP pe capi a -0.223060 -3.771 -1.18036 [0.1189] < 0.00
i nancial wo h pe capi a -0.021903 -0.567 1.58079 [0.9430] 0.735
unemploymen -0.606710 -9.791 -5.65002 [0.0000] < 0.00
mo gage in e es paymen -0.231590 -4.070 -1.48657 [0.0686] < 0.01
nominal house p ices index -0.092375 -2.230 0.24923 [0.5984] < 0.00
home- en wedge -0.679620 -8.305 -5.3787 [0.0000] < 0.00
young dependency a io -0.115020 -8.512 -7.70736 [0.0000] < 0.00
old dependency a io -0.116960 -7.551 -6.9874 [0.0000] < 0.00
b eak-poin dummy -0.154430 -4.144 -2.74214 [0.0031] < 0.00
adjus ed se ies
i nancial wo h pe capi a (1s -di .) -0.661910 -8.286 -4.09091 [0.0000] < 0.00
house p ices (change in %) -0.495910 -7.848 -5.21249 [0.0000] < 0.00
Sou ce: own
Tab. 1: S a iona i y es s esul s
Va iable Mean Median Minimum Maximum S d. De .
household mo gage le e age 0.990606 0.886642 0.190009 2.26104 0.519354
single homeowne ax elie 1.1738 1.1269 0.98624 2.6178 0.23242
amily homeowne ax elie 1.2650 1.1401 0.98624 2.6178 0.34274
GDP pe capi a 35,193 33,462 14,534 87,231 13,302
i nancial wo h pe capi a (1s -di .) 1.1167 1.0687 0.38264 2.2013 0.40244
unemploymen (%) 7.81508 7.53600 2.75100 26.0920 3.79661
mo gage in e es paymen 0.30541 0.30469 0.11224 0.84372 0.10831
house p ices (change in %) 2.5528 2.5337 -18.776 30.769 6.6330
home- en wedge -0.26071 0.0000 -18.700 20.000 3.3553
young dependency a io (%) 22.685 23.123 18.138 28.236 2.3741
old dependency a io (%) 4.4620 4.5180 2.6265 6.1160 0.79377
Sou ce: own
Tab. 2: Desc ip i e s a is ics o non-bina y a iables, obse a ions o 14 EU coun ies,
2004-2013
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1, XXI, 2018
Economics
i.e. he dependen a iable as well as he
independen a iables.
2. Discussion o Econome ic
Me hods
Ou analysis was based on panels which can be
desc ibed as balanced. The e was an obse a ion
o e e y yea (2004-2013, i.e. 10 yea s) and o
e e y uni (i.e. 14 coun ies).
In ou pilo wo k (see Slin áko á & Klaza ,
2015a o Slin áko á & Klaza , 2015b) we
used he pooled OLS me hod because o i s
wo ad an ages. Fi s , we gained in e i ciency
because i was no necessa y o allow o
non-exis en wi hin-g oups au oco ela ion.
Second, we ook ad an age o he i ni e-sample
p ope ies ins ead o elying on he asymp o ic
p ope ies o andom e ec s (see Doughe y,
2007). In case he unobse ed e ec is
weak, i. e. he e a e no ele an unobse ed
cha ac e is ics, he pooled eg ession is
he bes me hod o desc ibe a ela ionship
be ween an explained a iable and explana o y
a iables. We belie ed ha we iden i i ed such
explana o y a iables on he basis o li e a u e
s udy and he da a a ailabili y examina ion
ha we could suppose ha he unobse ed
componen would no in l uence ou analysis
signi i can ly. Howe e we could no be su e
ha he e we e any di e ences among he
coun ies in ou sample. Tha is why we decided
o es sui abili y o he panel da a analysis
(see Doughe y, 2007 o Guja a i, 1995). The
es o di e ing g oup in e cep , implemen ed
in he g e l so wa e, was pe o med wi h he
null hypo hesis ha g oups (coun ies) ha e
a common in e cep . The es esul ed wi h
he ollowing es s a is ic: Welch F(13, 48.1)
= 139.847 o he single axpaye model and
288.331 o he amily axpaye model, bo h
wi h p- alue nea ze o. The null hypo hesis
was ejec ed and we concluded ha he panel
da a analysis was mo e sui able ool han he
pooled OLS me hod. The panel da a me hod
would enable o con ol o he di e en le el
o he ela ionship be ween he explained and
explana o y a iables due o di e en coun y
cha ac e is ics.
The e a e wo basic panel da a echniques:
i xed e ec s and andom e ec s. We ollowed
he economic undamen als (a less o mal hin )
as well as mo e o mal ( echnical) econome ic
es s in o de o decide which echnique should
be p e e ed. The less o mal decision was
based on he ecommenda ion o Doughe y
(2007) who, in case ha an obse a ion canno
be desc ibed as being a andom sample om
a gi en popula ion, ecommends using he i xed
e ec s. We supposed ha ou selec ed coun ies
sample could no be a andom sample. We
belie ed ha economic na u e o ou da a was
no compa ible wi h he p esence o andom
e ec s. The mo e o mal es s o B eusch-
Pagan and Hausman we e pa ly in con l ic . The
B eusch-Pagan es (wi h he null hypo hesis
ha he a iance o he uni -speci i c e o is ze o
e sus he al e na i e hypo hesis o exis ence
o andom e ec s) deli e ed asymp o ic es
s a is ic: Chi-squa e(1) = 426.747 o he single
axpaye and 496.52 o he amily axpaye
wi h bo h p- alue nea ze o. The non- andom
e ec s hypo hesis was ejec ed a he 5% le el.
Howe e he Hausman es sugges ed ha he
andom e ec s es ima o s we e inconsis en
and hus he i xed e ec s should be used
ins ead. The Hausman es esul s a e shown
below he Tab. 3. To sum up, econome ic es s
and he na u e o he analysed da a p o ed
ha he i xed e ec s would be mo e sui able
me hod o analyse he ela ionship be ween
he explained and explana o y a iables in ou
case.
We epo esul s om bo h he i xed e ec s
and andom e ec s models in he Tab. 3 in
he sec ion 3. Compa ison showed ha he
coe i cien alues om he i xed e ec s models
we e no , in gene al, signi i can ly di e en han
he coe i cien alues om he andom e ec s
models. The e o e he i xed e ec s models
esul s can be conside ed being obus .
Fu he mo e, since he explana o y
a iables e ec s migh di e no only ac oss
coun ies bu also o e ime he pe iod i xed
e ec s we e es ed by Wald es o join
signi i cance o ime dummies (H0 said ha
he e we e no signi i can pe iod e ec s). On
he basis o he es esul s (see no es below
he Tab. 3) we included ime dummies in ou
eg ession models.
Acco ding o Doughe y (2007)
a eg ession model can be buil ei he om
speci i c o gene al o om gene al o speci i c.
On he basis o his summa y o p os and
cons i seemed ha he om speci i c o
gene al app oach would be mo e sui able
o ou analysis. We de o ed a lo o e o o
s udy ac o s in l uencing he household deb
and s a ing wi h he mos impo an ac o s
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60 2018, XXI, 1
Ekonomie
men ioned in li e a u e (i.e. GDP, i nancial
wo h and in e es paymen ) and adding o he
po en ially less impo an ac o s seemed o
be mo e app op ia e app oach. Some au ho s
ecommend his app oach in he case ha signs
o coe i cien s a e co ec , see And ews (2010).
We cons uc ed he sequen ial model and we
pe o med sui able diagnos ic checks in e e y
s ep. We belie e ha ou heo e ical analysis
allowed us o cope wi h he p oblem o model
misspeci i ca ion. We es ima ed he models o he
household mo gage le e age wi h he panel da a
analysis wi h bo h he i xed and andom e ec s. To
ackle he p oblem o he e oskedas ici y we used
obus s anda d e o s, a ian HC1 and A ellano
app oach (Co ell, 2003). The mul icollinea i y
was con olled by he Va iance In l a ion Fac o s
(VIF) me hod (Adkins, 2012). VIF alues lowe
han he bo de alue 10 ( he highes alue 2.2
was de i ed o he old dependency a io a iable)
indica ed he e was no collinea i y p oblem in
ou se o he explana o y a iables. We used
he s anda d signi i cance le els and he es o
no mali y o esiduals based on he Ja que –
Be a p ocedu e. The i nal models, p esen ed in
he Tab. 3 in he nex sec ion, passed all he es s.
single axpaye model amily axpaye model
i xed e ec s andom e ec s i xed e ec s andom e ec s
cons . 0.4824
(1.459)
0.3530
(1.259)
0.1670
(1.400)
0.1276
(1.253)
homeowne ax elie 0.04626
(0.09976)
0.05605
(0.1034)
0.08523
(0.06702)
0.08770
(0.06768)
GDP pe capi a 2.293e-05**
(3.800e-06)
2.206e-05**
(4.187e-06)
2.266e-05**
(3.330e-06)
2.199e-05**
(3.548e-06)
mo gage in e es paymen -0.003623
(0.1509)
-0.006298
(0.1537)
-0.02391
(0.1459)
-0.02160
(0.1463)
house p ices -0.003877**
(0.001668)
-0.003618**
(0.001513)
-0.003686**
(0.001678)
-0.003536**
(0.001561)
home- en wedge -0.005812**
(0.002663)
-0.005692**
(0.002602)
-0.005374*
(0.002694)
-0.005288**
(0.002664)
young dependency a io 0.002328
(0.06857)
-0.004443
(0.05684)
0.009766
(0.06408)
0.01263
(0.05544)
old dependency a io -0.09192
(0.05537)
-0.09518*
(0.04900)
-0.09762*
(0.04768)
-0.1000**
(0.04374)
b eak-poin dummy -0.02961
(0.09297)
-0.03281
(0.09480)
-0.01960
(0.08472)
-0.02110
(0.08553)
n140 140 140 140
Adjus ed R-squa ed 0.7205 NA 0.7323 NA
Sou ce: own
No es: S anda d e o s in pa en heses. * indica es signi i cance a he 10% le el, ** indica es signi i cance a he 5%
le el, based on obus (HAC) s anda d e o s. R-squa ed is a measu e o he p opo ion o he a iance in he household
mo gage le e age ha is p edic able om ou se o he independen a iables. NA means ha his measu e is sui able
only o linea models bu no o andom e ec s models (Adkins, 2012). Wald es esul s o join signi i cance o ime
dummies: chi-squa e(9) = 505.436 o he single axpaye model, 327.4 o he amily axpaye model wi h bo h p- alues
nea ze o. Acco ding o hese esul s we decided o include ime dummies in o he models, ne e heless eg ession
coe i cien s a e supp essed. Hausman es wi h H0 ha GLS es ima es a e consis en : Chi-squa e(17) = 74.0062 wi h
p- alue = 4.35784e-009 o he single axpaye model, 35.8286 wi h p- alue = 0.00483423 o he amily axpaye model.
Robus ness o models was es ed by he F es o he omission o a iables wi h H0: pa ame e s a e ze o o he a ia-
bles. Tes s deli e ed F es s a is ics wi h p- alues nea ze o o all models. Resul s o he diagnos ic esidual es s a e
p esen ed only o ou i xed e ec s models. Tes o no mali y o esidual: chi-squa e(2) = 6.84189 o he single axpaye
model, 5.57706 o he amily axpaye model wi h bo h p- alues > 0.01.
Tab. 3: Reg ession models o he household mo gage le e age
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67
1, XXI, 2018
Economics
Abs ac
DOES THE TAX RELIEF FOR HOMEOWNERSHIP HAVE EFFECT ON
HOUSEHOLD MORTGAGE LEVERAGE?
Ba bo a Slin áko á, S anisla Klaza
This a icle p esen s esul s o he analysis o he ela ionship be ween he ax elie o he
homeowne ship and he household mo gage deb . The ad an ageous ea men o housing is
p o ided especially by a pe sonal income ax i owne -occupie s do no epo impu ed en s
as income bu can deduc mo gage in e es cos s. This p e e ed ax s a us is jus i i ed by he
exis ence o posi i e ex e nali ies and a desi e o enhance housing oppo uni ies a ailable o
ci izens. Howe e , e idence ha he housing policy ia he axa ion achie es i s objec i es is s ill
weak. Mo eo e he ax p o isions o he homeowne ship bene i a he highe -income households.
Fu he mo e he e a e indica ions ha he housing axa ion encou ages le e ed p ope y pu chases
and hus con ibu es o he household deb g ow h. Since he household indeb edness can ha e
ad e se e ec s on households and mac oeconomic pe o mance we ocused on he issue
whe he he income ax elie o homeowne s ha i nance hei dwellings ia a mo gage does
a ec he household le e age. We cons uc ed he a iable cap u ing especially he mo gage
in e es paymen s deduc ibili y. We employed he mul iple eg ession and da a o he o me 15
EU membe coun ies (excep G eece) o he pe iod 2004-2013. We es ima ed wo models o
wo ep esen a i e axpaye s who a y in a amily s a us using he panel da a analysis wi h i xed
e ec s. F om ou esul s we in e ed ha he income ax elie o he homeowne ship migh no
ha e in l uenced he mo gage le e age signi i can ly in he selec ed Eu opean coun ies in he
gi en pe iod. The mo gage deb was a ec ed a he by he economic le el, p ice o own housing,
mo gage in e es paymen s o demog aphic s uc u e.
Key Wo ds: Household indeb edness, housing axa ion, mo gage in e es deduc ibili y.
JEL Classi i ca ion: G21, H24.
DOI: 10.15240/ ul/001/2018-1-004
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