Haa Pukuri Housig loa rae margis i Filad Bak of Filad Research Discussio Papers 0 200
Suome Pakki Bak of Filad PO Box 60 FI-000 HESINKI Filad +358 0 83 hp://www.bof.fi E-mail: Research@bof.fi
Bak of Filad Research Discussio Papers 0 200 Haa Pukuri* Housig loa rae margis i Filad The views expressed i his paper are hose of he auhor ad do o ecessarily reflec he views of he Bak of Filad. * Email: haa.pukuri@bof.fi I would like o hak Mai Viré, Esa Jokivuolle, Jouko Vilmue, Pekka Ilmakuas ad workshop paricipas a he Bak of Filad for heir valuable commes ad suggesios.
hp://www.bof.fi ISBN 978-952-462-594-4 ISSN 0785-3572 (pri) ISBN 978-952-462-595- ISSN 456-684 (olie) Helsiki 200
Housig loa rae margis i Filad Bak of Filad Research Discussio Papers 0/200 Haa Pukuri Moeary Policy ad Research Deparme Absrac This paper examies how housig loa raes are deermied, usig daa o ew housig loas i Filad. Filad is a example of a bak-based euro area coury where he majoriy of loas are graed a variable raes. The paper exeds he earlier ieres rae pass-hrough lieraure by akig explicily io accou he chagig of ledig rae margis. A sadard ledig rae pass-hrough model, empirically specified as a error-correcio model, is exeded wih variables prediced by a heoreical bak ieres rae seig model. The resuls show ha, sice he mid-990s, shor-ru movemes i housig loa raes ca be largely explaied by chages i moey marke raes, ad ha log-ru developmes have also bee affeced by less volaile cos ad credi risk facors. The roles of loa compeiio ad capial regulaio are also cosidered, bu hese effecs are more difficul o ideify empirically. Keywords: housig loa, ledig rae, ledig rae margi, error-correcio model JE classificaio umbers: G2, E43 3
Asuolaiamargiaali Suomessa Suome Paki keskuselualoieia 0/200 Haa Pukuri Rahapoliiikka- ja ukimusosaso Tiiviselmä Tässä yössä arkasellaa uusie asuolaioje korkoje määräyymisä Suomessa, jossa rahoiusjärjeselmä o pakkikeskeie ja laia ova valaosi vaihuvakorkoisia. Tukimus laajeaa aiempaa korkoje läpimeoa koskevaa kirjallisuua oamalla laiamargiaalie muuumise eksplisiiisesi huomioo. Virheekorjausmallia esieyä avaomaisa laiakorkomallia äydeeää muuujilla, joka johdeaa pakkikorkoje määräyymisä kuvaavasa eoreeisesa mallisa. Tulose mukaa asuolaiakorkoje lyhye aikaväli vaihelu seliyy lähiä markkiakorkoje muuoksilla, ku aas pikällä aikavälillä 990-luvu puolivälisä alkae myös vähemmä vaiheleva kusaus- ja riskiekijä ova vaikuaee korkoje kehiyksee. Työssä arkasellaa myös pakkie välise laiakilpailu ja vakavaraisuussääely vaikuuksia, mua iiä o vaikeampi ideifioida empiirisesi. Avaisaa: asuolaia, laiakorko, laiamargiaali, virheekorjausmalli JE-luokielu: G2, E43 4
Coes Absrac... 3 Tiiviselmä (absrac i Fiish)... 4 Iroducio... 7 2 Relaed lieraure... 9 2. Bak ledig rae pass-hrough... 9 2.2 Bak ieres margis... 0 2.3 Evidece o Fiish housig loa raes... 3 Theoreical model... 3 3. Basic se-up ad assumpios... 3 3.2 Profi-maximisaio... 4 3.3 Equilibrium ledig rae... 6 4 Empirical model... 7 4. Implicaios of he heoreical model ad empirical specificaios... 8 4.2 Variables ad daa descripio... 9 4.3 og-ru equilibrium relaioship... 25 4.4 Error-correcio model... 28 5 Coclusios... 3 Refereces... 32 Appedix... 37 5
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Iroducio The impac of chages i marke ieres raes o bak ledig raes, furher o spedig ad fiacig decisios, ad fially o iflaio ad ecoomic growh is a key chael of moeary policy rasmissio. This is paricularly rue for couries wih bak-based fiacial sysems ad he majoriy of bak loas graed a variable raes. The euro area is geerally cosidered as a example of a bak-based fiacial sysem, while Filad sads ou wih roughly 90% of ousadig loas o he public beig ied o variable raes. Moreover, as o housig fiace, close o 95% of housig loas i Filad have variable ieres raes ad hey are for he mos par graed by domesic deposi baks. This geeral picure is also suppored by empirical evidece showig ha he ieres rae chael plays a subsaial role i moeary rasmissio i almos all euro area couries ad a predomia role i Filad ad a few oher couries (Ageloi e al, 2003). Give hese fidigs, he ledig rae pass-hrough is likely o be a impora mechaism i he Fiish ecoomy i geeral ad he housig marke i paricular. Recely, he bak ieres rae pass-hrough has draw icreasig aeio due o he excepioally srog ad rapid decrease i moey marke raes sice he sar of he global fiacial crisis i auum 2008. Durig he firs year of he crisis, he ECB mai refiacig rae was lowered by 3.25 perceage pois o a hisorically low level of %. A he same ime, he 2-moh Euribor decreased by almos 4 perceage pois from 5.25% i Ocober 2008, o average, o.26% i Sepember 2009. Over he same period, he average ieres rae o ew housig loas i Filad decreased by 3.4 perceage pois o as low as 2.2%, amog he lowes i he euro area. The degree o ad he speed a which bak ieres raes respod o chages i marke ieres raes are key facors of he moeary rasmissio mechaism. A body of lieraure has show ha he respose of bak ledig raes is sluggish ad icomplee i he shor ru, while i he log ru he pass-hrough ca be less ha, equal o or eve more ha oe-o-oe. The sesiiviy of ledig raes o chages i marke ieres raes has bee ierpreed o reflec various cyclical, srucural ad isiuioal facors bu mos ofe i is ake o idicae he degree of compeiio bewee baks. A quesio ha has bee less explored i he ieres rae pass-hrough lieraure is he deermiaio of bak ledig rae margis. The same facors ha affec he degree ad speed of pass-hrough of marke ieres raes may also direcly ifluece he level of ledig rae margis. Durig he pas decade ad a half, he differece bewee he ieres rae o ew housig loas ad he 2- moh moey marke rae, radiioally he mos commo referece rae i Filad, has reded dow from he level of 2 perceage pois o less ha 0.5 a 7
he lowes. The emergece of he global fiacial crisis ad he ecoomic depressio i Filad fially reversed his red. Agais his backgroud, my purpose i his paper is o examie he housig loa rae pass-hrough i Filad ad, i specific, o disiguish bewee he passhrough of marke ieres raes ad chages i he deermias of ledig rae margis. The key deermias operaig coss, credi risk, marke power, ad he miimum capial requiremes are derived from a exeded versio of he oligopolisic Moi-Klei model of baks ieres rae seig behaviour. Whe omied i he empirical aalysis, chages i hese cyclical ad srucural facors may show up eiher as a high or low degree of pass-hrough of marke ieres raes, while he deermiaio of margis remais a black box. The key resul of he paper is ha, sice he mid-990s, shor-ru movemes i he Fiish housig loa raes are largely explaied by chages i marke ieres raes, ad ha log-ru developmes are also affeced by less volaile cyclical ad srucural facors. Two easily measured variables, he raio of baks admiisraive expeses o oal asses ad he uemployme rae, combie o capure chages i he average ledig rae margi. Give hese wo addiioal facors, he pass-hrough from marke ieres raes o housig loa raes is foud o be sluggish i he shor ru bu complee i he log ru. The laer fidig is i lie wih he fac ha mos of he housig loas i Filad are ied o variable ieres raes, while he former, by ad large, reflecs he fac ha i he shor ru borrowers ca affec he degree ad speed of pass-hrough by choosig bewee differe referece raes, ie moey marke raes ad more sicky prime raes, depedig o he direcio of marke raes. The evidece o he roles of loa marke compeiio ad capial adequacy regulaio is less robus or saisically isigifica. The resul may i par be caused by a lack of releva idicaors for chages i hese wo facors. The loa marke coceraio, as measured by he Herfidahl-Hirschma idex, is ofe used as a proxy for he degree of compeiio, bu here he variable is o sigifica i he preferred fial model. The same is rue for a smooh dummy variable aempig o capure he adjusme owards lower capial requiremes of housig loas alog wih Basel II. The res of he paper is orgaised as follows. Secio 2 summarises releva lieraure o he wo issues i focus: bak ledig rae pass-hrough ad deermias of bak ieres margis. Secio 3 lays he heoreical foudaio of he paper by exedig a oligopolisic Moi-Klei model of baks' ieres rae seig behaviour. Secio 4 describes he empirical approach of he paper ad he daa ad variables used. The secio also repors he key esimaio resuls. Fially, secio 5 cocludes. 8
2 Relaed lieraure There are wo closely relaed srads of lieraure ha boh aalyse he deermiaio of bak ieres raes. Oe examies he pass-hrough of marke ieres raes o bak ledig ad deposi raes, while he oher aalyses he deermias of bak ieres margis. My focus is o he pass-hrough of marke ieres raes o bak ledig raes (secio 2.) ad he facors deermiig he margi bewee he wo (secio 2.2), i paricular i he case of housig ledig i Filad (secio 2.3). 2. Bak ledig rae pass-hrough The pass-hrough of marke ieres raes o bak ledig raes has bee sudied from wo differe perspecives. Firs, accordig o he radiioal moey view of moeary rasmissio, ieres raes are he key chael hrough which moeary policy affecs ivesme ad fiacig decisios ad furher iflaio ad ecoomic growh. From his moeary policy perspecive, he key research quesio is he degree ad speed a which chages i policy raes are passed o o marke ieres raes ad furher o ledig ad deposi raes. Secod, i he idusrial orgaisaio lieraure, baks are see as profimaximisig firms ha se ledig ad deposi raes i proporio o heir margial coss, approximaed by marke ieres raes. Accordig o his cos-of-fuds approach, he exe o which chages i marke ieres raes are passed hrough o bak ieres raes reflecs, firs ad foremos, he marke srucure of he bakig sysem ad he iesiy of compeiio bewee baks. The geeral fidig i he lieraure is ha he respose of bak ledig raes o chages i marke ieres raes is sluggish ad icomplee i he shor ru. Coarelli ad Kourelis (994) were amog he firs o esimae he exe o which ad he speed a which bak ledig raes respod o chages i moey marke raes. They foud he respose o be sicky bu quie differe across couries, paricularly i he shor ru, ad explaied his heerogeeiy by srucural differeces i he aioal fiacial sysems. Sice he, a body of lieraure has emerged providig furher evidece of ad explaaios for he sluggish ledig rae pass-hrough. Ye here is o cosesus o wheher he passhrough is complee i he log ru. The resuls vary across ypes of loas, couries ad ime periods aalysed. 2 There is also a body of lieraure o he sickiess of deposi raes, may spurred by he semial papers by Haa ad Berger (99) ad Neumark ad Sharpe (992), bu furher deails o he dyamics of deposi raes are beyod he scope of his paper. 2 For a survey, see eg de Bod (2005). 9
Previous sudies have also foud heerogeeiy i he degree ad speed of pass-hrough across reail marke segmes ad bewee baks wihi a sigle coury. Corporae loa raes ypically respod more quickly ha housig ad cosumer loa raes (eg de Bod, 2005, Kok Sørese ad Werer, 2006). Furhermore, baks wih he larges marke shares price heir loas leas compeiively, supporig a relaive marke power hypohesis, while wellcapialized ad highly liquid baks are leas resposive o chagig marke codiios, as prediced by a bak ledig chael (de Graeve e al, 2007). Moreover, he respose of bak ledig raes o chages i marke ieres raes ca be asymmeric wih respec o he ieres rae cycle (eg Gropp e al, 2007), bu compeiio bewee baks reduces his asymmery by limiig baks abiliy o smooh ieres rae margis (Mojo, 2000). A disicio ca also be made bewee bak ledig raes below or above heir equilibrium levels (Sader ad Kleimeier, 2004) ad bewee expeced ad uexpeced moeary policy shocks (Kleimeier ad Sader, 2006). The evidece is mixed o wheher he degree ad speed of pass-hrough has icreased i he euro area sice he adopio of he sigle moeary policy. Maroa (2009) fids srucural breaks i he corporae ledig rae pass-hrough bu is cauious i associaig hem o he iroducio of he euro. I fac, he fids ha he pass-hrough has become more icomplee, possibly due o reduced compeiio ad higher risk premiums, he laer i accordace wih Basel II. 2.2 Bak ieres margis Bak ieres margis have bee modelled usig wo differe frameworks, a firm-heoreical model by Klei (97) ad Moi (972) ad a dyamic dealership model by Ho ad Sauders (98). The former approach reas baks as risk-eural profi-maximisig firms, while he laer views hem as risk-averse dealers. The Moi-Klei model is discussed ad exeded i he heoreical par of he paper (secio 3), while he laer srad of lieraure is briefly reviewed here. The semial paper by Ho ad Sauders (98) shows boh heoreically ad empirically ha he differece (spread) bewee ledig ad deposi raes resuls, firs ad foremos, from he rasacios uceraiy of baks ad depeds o he followig four facors: he degree of risk aversio, he size of bak rasacios, he srucure of he bakig marke, ad he variace of ledig ad deposi raes. McShae ad Sharpe (985) show broadly similar evidece bu argue ha he key ieres rae risk is relaed o he volailiy of moey marke raes. Furhermore, Alle (988) exeds he Ho-Sauders model by cosiderig differe ypes of 0
loas wih ierdepede demads ad shows ha bak ieres margis may be reduced as a resul of cross-elasiciies of demad. aer exesios of he models have show ha bak ieres rae margis may also deped o he defaul risk (Agbazo, 997), regulaio (Sauders ad Schumacher, 2000), operaig coss ad he degree of bak compeiio (Maudos ad Ferádez de Guevara, 2004, Maudos ad Solís, 2009), he presece of foreig baks (Mariez Peria ad Mody, 2004), he degree of specialisaio (Carbó Valverde ad Rodríguez Ferádez, 2007) ad diversicaio (epei e al, 2008), ad macroecoomic fudameals (Barea ad Kim, 2007, Juselius e al, 2009). 2.3 Evidece o Fiish housig loa raes Previous empirical evidece o he housig loa rae pass-hrough i Filad origiaes from cross-coury sudies ha focus maily o he heerogeeiy bewee couries as o he degree ad speed of he pass-hrough. The exisig sudies differ i erms of ime periods, specificaios ad esimaio mehods used, bu he resuls geerally idicae ha i Filad he pass-hrough from moey marke raes o housig loa raes is relaively high ad rapid i he Europea compariso. The key fidigs are discussed below (see able for a summary). Doay ad Degryse (200), de Bod e al (2005), Kleimeier ad Sader (2006) ad Sader ad Kleimeier (2006) all fid ha i Filad he degree of immediae ad shor-ru pass-hrough of moey marke raes o housig loa raes is amog he highes i he euro area. For example, Doay ad Degryse esimae ha he oe-moh pass-hrough is 0.8 perceage pois, which is a he higher ed of he rage of 0.02 0.9 i oher sample couries. The sudies ha aalyse also he log-ru dyamics ypically fid ha he pass-hrough is, by ad large, complee i he log erm. Based o he exisig evidece, i also seems ha he pass-hrough has acceleraed over ime i ha he speed of adjusme is he higher, he more rece daa is used. Moreover, he esimaed speed of adjusme seems o deped o which marke ieres rae is used i he aalysis. Kok Sørese ad Werer (2006) advocae usig a compouded marke ieres ha has he same mauriy srucure as he ousadig sock of loas, bu a he same ime hey oe ha his approach may uderesimae he rue speed of adjusme i couries where he majoriy of loas are graed a variable raes. For example i Filad, he esimaed speed of adjusme is higher, whe a shor-erm marke rae is used isead of a compouded rae.
The deermias of bak ledig rae margis have o bee widely sudied usig Fiish daa. A sadard pass-hrough model assumes a cosa margi, hough i he case of Filad i seems o o be he case, i paricular i he log erm. Accordig o Kauko (2005), i 993 2003, he squeeze i he margi bewee he ieres rae o ew loas o he public ad he moey marke rae ca be explaied by he decrease i he umber of bakrupcies, reflecig lower credi risk, ad by he EMU membership which reduced ieres rae risk ad possibly icreased compeiio. Table. Previous evidece o housig loa rae passhrough i Filad Time period Impac i he shor ru Impac i he log ru Model Shorererm og- Speed of Shor- og- adjusererm rae rae me* rae rae SVAR 0.8 b,g 0.39 b,i ECM 0.38 b,h 0.08 e,h -0.05 0.54 0.52 Doay Degryse (200) 92M0 00M05 de Bod e al 94M04 (2005) 02M2 99M0 ECM 0.39 b,h 0.8 e,h -0.08 0.99 02M2 Kleimeier 99M0 STD 0.57 a,g Sader (2006) 03M05 0.6 a,i Sader 98M0 ECM* 0.36 a,f 0.98 Kleimeier (2006) 03M09 Kok Sørese 99M0 ECM.a. -0.0.6 c Werer (2006) 04M06 99M0 ECM.a. -0.20.08 d 04M06 03M0 ECM.a. -0.34.09 b 05M0 SVAR deoes a srucural vecor auoregressive model, ECM a error-correcio model, STD a sadard firs-differece model, ad ECM* a error-correcio model wih a momeum hreshold auoregressive (M-TAR) error-correcio erm. Pass-hrough from (a) -moh moey marke rae, (b) 3-moh moey marke rae, (c) weighed average of shor- ad log-erm marke raes, (d) mos correlaed marke rae, or (e) 0-year goverme bod yield, ad he impac (f) immediaely, (g) afer oe moh, (h) afer wo mohs, or (i) afer hree mohs..a. idicaes o muliplier was repored i he paper. * Speed of adjusme o log-ru equilibrium. 2
3 Theoreical model I he heoreical par of he paper, I ake a idusrial orgaisaio approach o bakig by applyig a oligopolisic exesio of he Moi-Klei model. The model builds o he role of baks as profi-maximisig firms, while absracig from he ecoomics of iformaio. The origial model of a moopolisic bak was pu forward i he semial papers by Klei (97) ad Moi (972), bu laer o he model has bee exeded ad esed i several ways i he lieraure. 3 I ake a saic Freixas-Roche (2008) versio of he model as a sarig poi ad exed i by addig a simple bak capial requireme ad by iroducig credi risk i lie wih Wog (997) ad Corvoisier ad Gropp (2002) (secio 3.). The profi-maximisig behaviour of a represeaive bak is aalysed uder Couro compeiio bewee a fiie umber of baks (secio 3.2). Fially, he opimal bak ledig rae is derived from he loa marke equilibrium codiio (secio 3.3). Paricular aeio is paid o he impac of various cos ad risk facors ad he degree of compeiio o he equilibrium ledig rae. 3. Basic se-up ad assumpios There are hree ypes of ages: baks, he ceral bak ad privae borrowers (eg households). The bakig idusry is oligopolisic wih N baks, idexed by =,, N. A represeaive bak is a fiacial iermediary ha akes deposis (D ), gras loas ( ) ad holds equiy capial (K ). 4 The remaiig e asses or liabiliies (M ) he bak eiher leds or borrows i he ierbak moey marke. By he balace shee ideiy, he bak's oal asses ad liabiliies are equal + M = D + K (3.) The moey marke rae (r M ) is se by he ceral bak, ad bak akes i as give. Assumig ha he cos of holdig capial (r K ) is higher ha he risk-free marke rae of reur, he bak holds is capial a he miimum regulaory level of k per ce of loas, required by he ceral bak K = k (3.2) 3 See eg Sealey (980), Zarruk (989), Zarruk ad Madura (992), Wog (997), Corvoisier ad Gropp (2002) ad Gropp e al (2007). 4 Cash reserves are igored, because hey do o affec he opimal ledig rae. 3
All baks use he same echology, represeed by a sricly icreasig cos fucio C (, D) C(, D) = γ + γ DD = (for all ) (3.3) i which parameers γ ad γ D, reaed here as cosas, deoe he separable margial coss of maagig loas ad deposis, respecively ( ) C,D γ ad ( ) C,D γ D wih D 2 (,D) C (,D) 2 C D = D = 0 (3.4) Baks have some degree of marke power i he imperfecly compeiive loa ad deposi markes. Baks face a dowward-slopig demad for loas (r ) ad a upward-slopig supply of deposis D(r D ). ad D deoe he oal amou of loas ad deposis ad r ad r D he correspodig ledig ad deposi raes. Baks face credi risk, measured by parameer μ(μ [0,]). The parameer is he same for all baks ad i ca be ierpreed eiher as a proporio of operformig loas a he ed of he period (Wog, 997) or as a defaul probabiliy of loas (Corvoisier ad Gropp, 2002). 3.2 Profi-maximisaio I a saic Couro game, baks compee hrough quaiies boh i he loa ad deposi markes, choosig heir acios simulaeously ad idepedely. Give he quaiy choices, he ledig ad deposi raes adjus accordigly o he levels r () ad r D (D) ha clear he markes. Here, r () = - (r ) ad r D (D) = D - (r D ) deoe he iverse demad ad supply fucios (wih r () < 0 ad r D () > 0 a all, D 0). Bak chooses ad D o maximise is expeced ed-of-period profi, akig he volumes of loas ad deposis of oher N- baks as give. The profi fucio of he bak is equal o he expeced e ieres icome less capial coss ad operaig expeses max Eπ (, D ) = ( μ)r () + r M r (D)D r K C(, D ) (3.5),D M D K subjec o he balace shee cosrai (3.). By expressig M, K ad C(, D ) i erms of (3.), (3.2) ad (3.3) respecively, he objecive fucio (3.5) ca be rewrie as 4
Eπ = (( μ)r () r γ γ D D M ) (r (D) r D M )D (r K r M )k (3.6) A Couro-Nash equilibrium of he bakig idusry is a N-uple of vecors ( *, D * ) =,,N such ha for every, ( *, D * ) solves he decisio problem defied by fucio (3.5). Assumig ha he profi fucio is sricly cocave i ad D ad wice differeiable, he firs-order codiios for he profimaximisaio of bak are give by he followig margial reveue ad cos fucios Eπ Eπ D = ( μ)r ( ) (r = r (r (D ) + γ M D M D + (r r ) r (D )D D K M )k + γ = 0 ) + ( μ)r ( ) = 0 (3.7a,b) The firs wo erms o he righ had side of equaios (3.7a) ad (3.7b) describe he profiabiliy of a exra ui of loas ad deposis, respecively, while he hird erm represes he effec of his exra ui o he profiabiliy of loas ad deposis already produced. Uder separabiliy (3.4), he equilibrium of he loa marke (3.7a) is idepede of he equilibrium of he deposi marke (3.7b). For he purpose of his sudy, i is eough o focus o he opimal volume of loas ( * ) (rm + (r K rm )k + γ ) ( μ)r ( ) = (3.8) ( μ)r ( ) Sice equaio (3.8) is idepede of, here is a uique symmeric equilibrium, i which each bak chooses * = * /N. Cosequely, he equilibrium codiio (3.8) ca be rewrie i he form i which for each bak he expeced margial reveue from ledig * /N equals he oal margial cos of fudig, holdig capial ad maagig he sock of loas ( μ) r ( ) + r ( ) = rm + (r K rm ) k + γ N (3.9) By rearragig ad iroducig he price (here, ledig rae) elasiciy of demad for loas (ε (r )), he codiio (3.9) ca be rewrie i he erer idex form (price mius margial cos divided by price) 5
( μ)r () (rm + (r K r ( μ)r () M )k + γ ) = Nε (r ) (3.0) i which he iverse of he price elasiciy is equal o he quaiy elasiciy of iverse demad for loas (φ ()) ε (r = φ ) r () () = r () (3.) Accordig o equaio (3.0), he higher is he umber of baks or he higher is he ieres rae elasiciy of demad for loas, he lower is he marke power of he bak, ad he lower he erer idex. 3.3 Equilibrium ledig rae Fially, equaio (3.0) ca be rewrie o give a more sraighforward formula for he equilibrium ledig rae r () = (r μ Nε (r ) = μ Nε (r = β 0 + β r M, ) M + (r K (( k)r r M M + kr )k + γ K +γ ) ) (3.2) where β0 = (kr K+ γ ) μ Nε (r ) ad β = ( k). μ Nε (r ) Accordig o his model, he sesiiviy (β ) of he opimal ledig rae o chages i he moey marke rae depeds posiively o he level of credi risk (μ) ad he marke power of baks (iverse of N ad ε ) ad egaively o he required capial-o-loas raio (k). The margi (β 0 ) depeds, i addiio, posiively o he operaig coss (γ ) ad he cos of capial (r K ). Give he assumpios made, he key comparaive saics of he model ca also be summarised as follows (see also able 2): The ledig rae is he higher, he higher he fudig coss or operaig expeses are, or he higher he credi risk, marke power or bak capial requireme is. 6
Table 2. Comparaive saics of he heoreical model Effec o he opimal ledig rae (r * ) Deposi rae r D 0 Moey marke rae r M + Cos of capial r K + Margial cos of maagig loas γ + Probabiliy of defaul μ + Number of baks N Price elasiciy of demad for loas ε Miimum capial-o-loas raio k + I he Freixas-Roche (2008) bechmark case, where he elasiciy (ε ) is assumed o remai cosa ad here is o credi risk (μ = 0) or bak capial requiremes (k = 0), he sesiiviy of he ledig rae o chages i he moey marke rae depeds oly o he umber of baks, ierpreed o reflec he degree of compeiio. 4 Empirical model I he empirical par of he paper, I es some of he key predicios of he heoreical model by esimaig a model for he average ieres rae o ew housig loas i Filad. Takig a macro-level approach ad reaig he bakig secor as a sigle decisio maker omis differeces bewee baks. The mai ieres i his paper is, however, o he role of log-ru developmes i macrolevel facors such as he marke cos of fudig, chages i he operaig coss (eg due o echological chage), credi risk, bakig compeiio ad he regulaory evirome. The variables of he empirical ledig rae model are moivaed (i secio 4.) by he precedig heoreical model. The saic aure of he heoreical model gives, however, lile guidace o he dyamics of he empirical specificaio. Therefore, I sar he aalysis by firs describig he daa ad esig he variables for heir order of iegraio (secio 4.2). I fid he variables iegraed of order oe, which is a prerequisie for esig wheher he levels of he series are coiegraed. Coiegraio is foud, which meas ha he osaioary series form a saioary liear combiaio ha ca be ierpreed as a log-ru equilibrium relaioship bewee he variables (secio 4.3). Fially, he model is esimaed i he error-correcio form, i which he shor-ru dyamics of he variables are iflueced by he deviaio from he log-ru equilibrium (secio 4.4). 7
4. Implicaios of he heoreical model ad empirical specificaios The oligopolisic Moi-Klei model preses a very simplified approach o bakig, ye, as advocaed by Freixas ad Roche (2008), i provides several coclusios ha ca be esed empirically. Mos of he ieres rae pass-hrough sudies esimae he equilibrium ledig rae ( r *, ) by applyig he las specificaio of equaio (3.2), assumig a cosa margi or markup (β 0 ) over he marke ieres rae (r M, ) ad a iid error erm (u ) a each ime period r = β + β r + u, 0 M, (4.) The advaage of he model is is iuiive ierpreabiliy as a simple margial cos pricig model (eg Rousseas, 985, ad de Bod, 2005), i which he margial fudig coss are approximaed by he releva marke ieres rae. Give he heoreical backgroud, he size of he pass-hrough coefficie (β ) is usually ierpreed i erms of baks marke power. Icomplee pass-hrough (β < ) is ake as a sig of imperfec compeiio (or ielasic demad for loas), whereas complee pass-hrough (β = ) is i lie wih perfec compeiio (or fully elasic demad for loas). The case of over-shooig pass-hrough (β > ) is usually aribued o credi risk (de Bod, 2005). I he heoreical model, here are o coss o baks of chagig heir ledig ad deposis raes. However, due o such adjusme coss, baks do o i pracice se heir ieres raes equal o heir equilibrium levels i every period. Furhermore, borrowers ca eiher accelerae or decelerae he pass-hrough by choosig bewee differe referece raes, depedig o wheher marke ieres raes are decreasig or icreasig. I he empirical model, rigidiies i he price seig are iroduced hrough parial adjusme accordig o a mechaism r r +,, = γ(r, r, ) v (4.2) i which he adjusme parameer γ(0 < γ < ) idicaes he proporio of he deviaio from he equilibrium ha ca be correced i oe period (eg Davidso ad MacKio, 993). Solvig equaio (4.2) for r, ad subsiuig (4.) for ( r *, ) yields a auoregressive disribued lag model r, = α + α r + α r + ε (4.3) 0 M, 2, i which α 0 = γβ 0, α = γβ, α 2 = -γ, ad ε = γu + v. Equaio (4.3) ca also be wrie i he error-correcio form 8
Δr, = αδrm, γ(r, ( β0 + βrm, )) + ε (4.4) i which γ = α2, α 0 = ad γ β 0 α =. The model discrimiaes bewee he γ β shor-ru dyamics (firs-differece erms deoed by Δ) ad he adjusme owards he log-ru equilibrium (i levels). I follow his widely applied modellig approach bu es wheher he sadard pass-hrough model (4.) ca be improved by exedig i wih variables suggesed by he heoreical model. I specific, I es wheher chages i he key deermias of ledig rae margis should be beer accoued for whe assessig he exe o ad he speed a which ledig raes respod o chages i marke ieres raes, i paricular i he log erm. 4.2 Variables ad daa descripio Based o he heoreical model preseed i secio 3, bak ledig raes are affeced by he followig five facors: () marke ieres rae level, (2) baks operaig coss, (3) credi risk faced by he baks, (4) baks marke power, ad (5) baks miimum capial requiremes. I he empirical par of he paper, I defie he variables as follows (see able 3 for a summary). Firs of all, I cocerae o he ew housig ledig i Filad. The key variable of ieres is he average ieres rae (HRATE) o ew housig loas o households by he Fiish moeary fiacial isiuios. The housig fiace i Filad is domiaed by deposi baks, while specialised morgage credi baks sill play a relaively mior role. Focusig o oe coury ad oe ype of loas ca be reasoed by subsaial differeces i he characerisics of loas boh across couries ad by differe purposes of loas. Morgage ieres raes sill differ across couries boh i erms of levels ad chages, ad hese differeces ca be parly explaied by differeces i he aioal demad ad supply codiios ad coury-specific isiuioal facors (Kok Sørese ad icheberger, 2007). Accordig o he ECB (2009), oe of he key differeces relaes o he ypical ieres rae likage of loas. Filad sads ou as oe of he few euro area couries, where more ha 90% of ew housig loas are ypically graed a variable raes. From Jauary 995 o Sepember 2009, approximaely 58% of ew housig loas i Filad were liked o moey marke raes (Helibor prior o 999 ad Euribor from 999 owards), 37% o bak-specific referece raes (called prime raes) ad oly less ha 5% o fixed or oher raes. Neverheless, he relaive shares of moey marke 9
ad prime rae likages i ew housig loas ca vary cosiderably from a moh o aoher (figure ). Prime raes ed o become more popular i imes of risig marke ieres raes, while he use of ierbak raes ypically icreases whe marke ieres raes are decreasig. This regulariy is relaed o he fac ha prime raes usually follow moey marke raes wih a shor lag, while households ypically choose he oe ha is lower a he ime of raisig a loa. Figure. New housig loas i Filad, by ieres rae likage 00 90 80 70 60 50 40 30 20 0 0 oas liked o Euribor (or Helibor) raes 2 oas liked o bak-specific referece raes (prime raes) 3 oas wih fixed ad oher raes 4 2-moh Euribor (or Helibor) - average prime rae* % % 3 2 995 997 999 200 2003 2005 2007 2009 Daa o ieres rae likages was o colleced i 2003 ad 2004. * Average of prime raes of hree larges baks i Filad. Source: Bak of Filad. 4 2.5 2.0.5.0 0.5 0.0-0.5 -.0 -.5-2.0-2.5 As o he marke ieres rae level, I focus o he 2-moh moey marke rae (MRATE), which has bee he sigle mos commo referece rae for housig loas sice he mid-990s. 5 I he previous sudies, he selecio of comparable marke ieres raes has usually bee made o he basis of correlaio (eg de Bod, 2005) or by machig mauriies (Kok Sørese ad Werer, 2006). The differece bewee he average housig loa rae ad he 2-moh moey marke rae (HRATE-MRATE) ca be used as a rough proxy for he 5 There is some aecdoal evidece ha he average ieres rae fixaio period amog ew housig loas has shoreed sice he srog drop i moey marke raes i auum 2008, as households have icreasigly re-liked heir loas o shorer-erm marke raes, i paricular o he 3-moh Euribor rae. 20
average housig loa rae margi. A beer esimae of he margi ca, however, be obaied by replacig MRATE by he weighed average of key referece raes amog he ew loas. Figure 2 depics he differece bewee he housig loa rae ad he weighed average of wo variable referece raes, amely he 2- moh moey marke rae ad he average prime rae of he hree larges baks operaig i Filad. 6 I he shor erm, he differece seems o be iflueced maily by he volailiy of key referece raes, whereas i he log erm i may also reflec chages i he uderlyig deermias of margis: baks operaig coss, risks relaed o ledig, compeiio bewee baks ad regulaio. The proxy for he margi has arrowed for he mos of he period cosidered, bu he deepeig of he global fiacial crisis i 2008 fially reversed his red. Figure 2. Proxy for he housig loa rae margi* 2.4 2.0.6.2 0.8 0.4 0.0 996 998 2000 2002 2004 2006 2008 * Ieres rae o ew housig loas mius weighed average of variable referece raes. Sources: Bak of Filad, Reuers ad calculaios by he auhor. Developmes i baks operaig coss ca be capured by he raio of admiisraive expeses o average oal asses (COST). Oher operaig expeses are excluded due o some sigifica o-recurre iems ha are difficul o remove from he daa. Over he period cosidered, he cos-o-asses raio has reded dow i lie wih he decrease i he umber of bak braches ad he decliig employee-o-brach raio. This developme is relaed o exesive 6 Due o he lack of daa o he shares of differe ieres rae likages i 2003 ad 2004, weighs i 2003M0 2004M2 are replaced by he average of weighs i 2002M2 ad 2005M0. 2
echological ad srucural chages ha he Fiish bakig secor has udergoe sice he depressio ad he severe bakig crisis of he early 990s. Furhermore, he rise i oal asses (he deomiaor of he idicaor) reflecs a sigifica icrease i he average size of loas, which has i par compesaed baks for he decrease i he margis i perceage erms. Risks relaed o household ledig are geerally coige o he developme of ieres raes, icome ad housig prices bu he combied effec of he risks is difficul o gauge. For example, durig he curre fiacial ad ecoomic crisis, marke ieres raes have falle o hisorically low levels, easig he deb servicig burde of hose wih variable rae loas. A he same ime, he labour marke codiios have deerioraed ad icreased households icome uceraiy. I he empirical aalysis, I emphasize he icome-relaed risks ad use he uemployme rae as a macro-level proxy for he riskiess of housig ledig (RISK). The use of his idicaor is also suppored by is high correlaio wih he share of aggregae operformig loas i oal loas of he Fiish bakig secor sice he mid-990s. 7 Neverheless, housig loas are ypically well-secured by borrowers resideial propery, ad baks losses o household ledig have so far bee very small, eve durig he bakig crisis of he early 990s. There are o direc measures for he degree of compeiio i housig fiace bu differe marke coceraio raios ad idexes are ofe used as idicaors for compeiio i reail bakig (eg Carbó e al, 2009). The Herfidahl- Hirschma idex (HHI) is oe of he mos widely-used measures, ad i is calculaed as he sum of he squared marke shares of he baks operaig i he marke. Basically, he higher is he idex, he higher is he degree of coceraio, he more he baks have marke power, ad he lower is he iesiy of compeiio bewee baks. Accordig o he Herfidahl-Hirschma idex, he Fiish bak loa marke is highly coceraed bu, more imporaly, he degree of coceraio has decreased as compared o he mid-990s. Based o aecdoal evidece, bak compeiio has bee raher iese over he pas years, i paricular i housig ledig. The samp duy o ew bak loas was abolished i Filad i April 998, which made i less cosly for cusomers o reegoiae loa coracs ad o swich from a bak o aoher. There is also some aecdoal evidece of crosssubsidisaio i ha arrow housig loa rae margis have bee used o arac loa cusomers ad o iduce hem o buy oher bakig services as well. The pricig of bak loas ca also be affeced by regulaory chages. Alog wih he implemeaio of he New Basel Capial Accord (Basel II) i he begiig of 2007, he risk-weigh of resideial morgage ledig decreased o 7 Daa o operformig household or housig loas are o available for he correspodig ime period. 22
35% from he former 50%. Cosequely, baks eed o hold less capial agais heir housig loas. Baks mos likely adjused heir loa pricig up fro, afer he chage i he risk-weigh was firs published i April 2003 (Basel Commiee o Bakig Supervisio, 2003). Cosequely, a smooh dummy variable (CAP) is cosruced i a aemp o capure he gradual chage i pricig. The variable akes he value of zero up o March 2003 ad he value of oe from Jauary 2007 owards, ad icreases liearly bewee he wo pois i ime. Table 3. Variable descripio ad expeced impac o he depede variable Variable Noaio Descripio Expeced impac Daa source(s) Housig loa rae HRAT E Average ieres rae o ew housig loas o households by Fiish MFIs, % Depede variable Bak of Filad (BoF) Marke ieres rae MRATE 2-moh Euribor (Helibor prior o 999), % + BoF ad Reuers Operaig coss COST Fiish baks' admiisraive expeses per average oal asses, ierpolaed from quarerly daa, % Credi risk RISK Uemployme rae, seasoally adjused, % Bakig HHI Herfidahl-Hirschma idex for compeiio claims o he public ad public secor eiies, ier-polaed from Bak capial requiremes CAP quarerly daa, divided by 00. Dummy for baks adjusme o Basel II framework + Fiacial Supervisory Auhoriy (FIN-FSA) + Saisics Filad + FIN-FSA - Cosruced by auhor The daa covers he period from March 995 o Sepember 2009, as show i figure 3. The begiig of he sample is resriced o he mid-990s for wo reasos. Firs ad foremos, here is prior evidece ha he behaviour of Fiish baks as ieres rae seers seems o have chaged permaely ad fudameally durig he bakig crisis of he early 990s (Kauko, 995). Secod, he bakig daa used i cosrucig COST ad HHI variables is readily available oly sice he firs quarer of 995. 8 8 The Fiish bakig group daa covers he followig deposi baks ad bakig groups: idividual commercial baks, oal of savigs baks, oal of member baks of he amalgamaio of he cooperaive baks, ad oal of local cooperaive baks. 23
Figure 3. Variables 9 8 7 6 5 4 3 HRATE 8 7 6 5 4 3 2 MRATE 2 996 999 2002 2005 2008 996 999 2002 2005 2008 3 2 0 HRATE-MRATE 45 40 35 30 25 20 COST - 996 999 2002 2005 2008 5 996 999 2002 2005 2008 8 6 4 2 0 8 6 RISK 3,00 3,000 2,900 2,800 2,700 2,600 2,500 HHI 4 996 999 2002 2005 2008 2,400 996 999 2002 2005 2008 Noaio: HRATE = ieres rae o ew housig loas (%), MRATE = 2-moh moey marke rae (%), COST = baks admiisraive expeses as a perceage of average oal asses (%), RISK = uemployme rae (%), HHI = Herfidahl-Hirschma idex for oal ledig. 24
Accordig o he augmeed Dickey-Fuller (ADF) es, all five ime series (HRATE, MRATE, COST, RISK, HHI) are foud o be iegraed of order oe, I(), usig a es equaio ha coais a iercep bu o red as suggesed by Hamilo (994). 9 Accordig o his resul, shocks ca have permae effecs o he variables, ulike i he case of saioary, I(0), variables. Ieresigly, he differece bewee he housig loa rae ad he 2-moh moey marke rae (HRATE-MRATE) is also a I() variable. This fidig also suggess ha i is o reasoable o rea he margi as cosa whe modellig he ledig rae pass-hrough over he log erm. 4.3 og-ru equilibrium relaioship I wha follows, osaioary variables are esed for coiegraio by usig wo differe approaches, he OS-based Egle-Grager (987) mehod ad he maximum likelihood (M) based Johase (99, 995) procedure. Oe of he key differeces bewee he approaches is ha he Johase VAR procedure reas all variables as poeially edogeous, while he Egle-Grager sigle-equaio mehod requires makig a a priori resricio ha oly oe of he variables is edogeous. I his secio, I firs use he Egle-Grager mehod by akig all variables bu he housig loa rae as exogeous. The model has a very iuiive ierpreaio as a exeded margial cos pricig model. Fially, I compare he resuls wih hose of he correspodig Johase es. To apply he Egle-Grager wo-sep es mehod, I firs esimae he possible log-ru equilibrium relaioship as a saic regressio bewee he variables (sep ) ad he es he residual for is order of iegraio usig he ADF es ad MacKio (99) criical values (sep 2). To eable coefficie esig based o sadard errors, I also esimae a Sock-Waso (993) dyamic OS (DOS) versio of he model, which correcs for poeial edogeeiy ad small sample biases. As a bechmark, I firs esimae a sadard log-ru model i which he margi bewee he housig loa rae (HRATE) ad he 2-moh moey marke rae (MRATE) is assumed o remai cosa (β 0 ) i he log erm. This assumpio is commoly made i he empirical ieres rae pass-hrough lieraure. Table 4 summarises he esimaio resuls of boh OS (Model ) ad DOS (Model ) regressios 0 HRATE = β + β MRATE + ε (Model ) 0 9 The ull hypohesis of a ui roo i he firs differeces of he series ca be rejeced a he 5 per ce sigificace level. The deailed resuls of he ADF ess are repored i he appedix. 0 Oe lead ad lag i he DOS model were chose based o iformaio crieria. 25
ad HRATE = β 0 + β MRATE 2 + β ΔMRATE + β ΔMRATE 3 + β ΔMRATE 4 + + ε (Model ) The pass-hrough coefficie (β ) of he DOS model (Model ) is o sigificaly differe from oe, implyig a complee log-ru pass-hrough. The residual (ε ) of he more parsimoious OS model (Model ) is, however, esed o be osaioary, which idicaes ha o coiegraio bewee he wo ieres raes is foud ad he regressio resuls of he firs sep may be spurious (for deailed es resuls, see appedix). This fidig suppors he oio, suggesed boh by heory ad descripive daa, ha i may o be reasoable o rea he housig loa rae margi as cosa over ime. To ake beer io accou he chagig of he margi, I exed he model wih he four key variables (COST, RISK, HHI ad CAP) suggesed by he heoreical model. Agai, he model is esimaed usig OS (Model 2) ad DOS (Model 2 ) o allow boh he residual ad coefficie esig HRATE = β 0 + β MRATE 2 + β COST + β RISK + β 3 4 HHI + β CAP + ε 5 (Model 2) ad HRATE = β 0 + β MRATE 2 6 9 2 5 8 + β COST + β RISK + β + β ΔMRATE + β ΔCOST + β + β + β ΔRISK ΔHHI ΔCAP 3 + β + β 6 9 0 3 7 ΔHHI 4 ΔRISK HHI + β ΔMRATE + β ΔCOST + β + β + β 7 + β ΔCAP + β 20 4 + β CAP 5 + β ΔMRATE ΔHHI 8 ΔCOST ΔRISK + ΔCAP + + + + ε + (Model 2 ) Accordig o he resuls, he exeded OS model (Model 2) has a saioary residual, idicaig ha he esimaed model ca be ierpreed as a log-ru equilibrium relaioship. As expeced, he higher is he cos raio, he risk level or he degree of marke coceraio, he higher is he housig loa rae. The log-ru pass-hrough coefficie of he moey marke rae is sigificaly less ha oe, implyig ha he pass-hrough of he moey marke rae o he housig loa rae is less ha complee i he log erm (Model 2 ). The fidig may reflec measureme errors or omied facors, such as bakig compeiio o fully capured by he HHI variable. 26
The dummy variable (CAP) ryig o describe baks gradual adjusme o he Basel II framework did o have sufficie saisical sigificace, so he variable is excluded from he preferred log-ru models (Models 2 ad 2 repored i able 4). Table 4. Resuls of Egle-Grager wo-sep coiegraio es Sep : Depede variable: HRATE Sadard log-ru relaioship Exeded log-ru relaioship Model Model Model 2 Model 2 Cosa 0.85 0.73 [0.25]*** -4.30-3.44 [0.3]*** MRATE.08. [0.08]*** 0.80 0.84 [0.0]*** COST 0.02 0.03 [0.00]*** RISK 0.4 0.3 [0.0]*** HHI 0.6 0. [0.02]*** ΔMRATE(-) -0.78 [0.4]* -0.22 [0.07]*** ΔMRATE -0.59 [0.28]** -0.38 [0.08]*** ΔMRATE(+) 0.2 [0.4] -0.2 [0.07] ΔCOST(-) -0.0 [0.03] ΔCOST -0.04 [0.04] ΔCOST(+) 0.03 [0.03] ΔRISK(-) -0.09 [0.04]** ΔRISK -0.4 [0.04]*** ΔRISK(+) 0.00 [0.04] ΔHHI(-) -0.03 [0.2] ΔHHI -0.04 [0.4] ΔHHI(+) 0.5 [0.2] Adjused R 2 0.77 0.77 0.98 0.99 SEE 0.70 0.66 0.9 0.4 DW 0.04 0.05 0.36 0.42 Mehod OS DOS OS DOS Sample 995M03 2009M09 995M05 2009M08 995M03 2009M09 995M05 2009M08 Sep 2: Residual I(d) I() No coiegraio I(0) Coiegraio Esimaed models are of he form: () HRATE = β 0 + β MRATE + ε, (2) DOS versio of (), (3) HRATE = β 0 + β MRATE + β 2 COST + β 3 RISK + β 4 HHI + ε, (4) DOS versio of (3), i which HRATE deoes he ieres rae o ew housig loas, MRATE he 2-moh moey marke rae, COST he bakig secor s admiisraive-cos-o-asses raio, RISK he uemploy-me rae, HHI he Herfidahl- Hirschma idex for oal ledig (divided by 00), ad Δ is he differece operaor. *** Coefficie saisically sigifica a he % level, ** 5% level, * 0% level usig Newey-Wes heeroskedasiciy ad auocorrelaio cosise sadard errors [i square brackes]. I(d) deoes iegraio of order d based o MacKio (99) criical values (see appedix). 27
The Johase es shows evidece i favour of oe coiegraig vecor boh i he wo-variable case (HRATE, MRATE) ad amog he exeded se of variables (HRATE, MRATE, COST, RISK, HHI). Boh he race es ad maximum eigevalue es rejec he ull hypohesis of o coiegraio, while he hypohesis of oe coiegraio vecor cao be rejeced (see appedix). To sum up, I fid he evidece of coiegraio srog eough o esimae he housig loa rae model i he error-correcio form. Based o he log-ru equilibrium regressios, he exeded se of variables is eeded o capure o oly he pass-hrough of marke ieres raes bu also he chagig of he ledig rae margi. 4.4 Error-correcio model Aalogously o esig for coiegraio, he error-correcio model ca be esimaed usig wo differe echiques, he Egle-Grager mehod for sigleequaio error-correcio models (ECMs) ad he Johase sysem approach for vecor error-correcio models (VECMs). Sarig wih he Egle-Grager mehod, he model ca be wrie i he form, i which he shor-ru dyamics bewee he variables (firs-differece erms) are esimaed wih he lagged residual (ECT) of he log-ru equilibrium regressio as a addiioal explaaory variable ΔHRATE = α 0 + α ΔHRATE 4 + α ΔRISK 5 + α ΔHHI + α ΔMRATE 2 + γect + ε + α ΔCOST 3 (ECM ) Here, he lagged residual, also called a error correcio erm, is equal o HRATE - -(β 0 + β MRATE - + β 2 COST - + β 3 RISK - + β 4 HHI - ), which is calculaed usig he parameers of Model 2 repored i secio 4.3. The coefficie (γ) of he error-correcio erm measures he speed a which he housig loa rae adjuss owards is log-ru equilibrium level. Accordig o he OS esimaio (ECM i able 5), shor-ru movemes i he housig loa rae (ΔHRATE) ca be largely explaied by he pas chage i he ledig rae, he chage i he moey marke rae (ΔMRATE) ad he pas deviaio from he equilibrium (ECT), while chages i he operaig coss (ΔCOST), credi risk (ΔRISK) ad coceraio (ΔHHI) do o play ay saisically sigifica role i he shor erm. The coefficie of he errorcorrecio erm is egaive ad highly sigifica supporig he error-correcio represeaio. Furhermore, he absolue value of he coefficie is raher large (0.23) i he ligh of ieraioal evidece, implyig a high speed of adjusme i Filad. 28
The correspodig model ca also be esimaed usig he Johase sysem approach. I sar wih a specificaio i which he coiegraig equaio is of he same form as above ad here are o model resricios ΔHRATE = α 0 + α ΔHRATE 4 + α ΔRISK β MRATE + ε 5 2 + α ΔHHI 2 β COST + α ΔMRATE 3 + γ(hrate β RISK + α ΔCOST 3 β β 4 0 HHI ) (VECM ) The umber of lags is deermied empirically by he geeral-o-specific approach. I ed up wih oly oe lag afer sarig wih four lags ad by droppig he oes (ad ay higher oes) ha are o joily sigifica by he Wald es ad he oes for which he ΔMRATE erm has a egaive coefficie. Accordig o he maximum likelihood esimaio, he shor-ru dyamics of he housig loa rae are agai largely explaied by he moey marke rae, while he log-ru equilibrium level depeds also o he cos raio ad he riskiess of ledig (VECM i able 5). The degree of compeiio, as measured by he Herfidahl-Hirschma idex, is o saisically sigifica i he coiegraig equaio. Secodly, I drop he isigifica HHI variable, re-esimae he model ad es hree of he remaiig variables (MRATE, COST ad RISK) for weak exogeeiy wih respec o he coiegraig vecor ΔHRATE = α 0 + α ΔHRATE 2 4 + α ΔRISK β COST 3 + γ(hrate β RISK + α ΔMRATE 2 ) + ε β 0 + α ΔCOST 3 β MRATE (VECM 2) Accordig o he likelihood raio (R) es, he zero resricios imposed o he adjusme coefficies of he models for ΔMRATE, ΔCOST ad ΔRISK (ie coefficies correspodig o γ i VECM 2) cao be rejeced. Thus, variables oher ha HRATE ca be reaed as weakly exogeous (VECM 2 i able 5). These resricios imply ha whe here is a deviaio from he log-ru equilibrium, i is oly he housig loa rae ha adjuss o resore he equilibrium. Thirdly, I impose weak exogeeiy of MRATE, COST ad RISK ad a he same ime es wheher he coefficie of MRATE ca be resriced o oe i he coiegraig vecor (β = ) Models for ΔMRATE, ΔCOST, ΔRISK ad ΔHHI are o repored here. 29
ΔHRATE = α 0 + α ΔHRATE 2 4 + α ΔRISK β COST 3 + γ(hrate β RISK + α ΔMRATE 2 ) + ε β 0 + α ΔCOST 3 MRATE (VECM 3) Agai, he resricios cao be rejeced, suggesig ha he pass-hrough of MRATE ca be cosidered as complee i he log ru (VECM 3 i able 5). Table 5. Resuls of Egle-Grager error-correcio model ad Johase vecor error-correcio model Depede variable: ΔHRATE ECM VECM VECM 2 VECM 3 Cosa -0.0 [0.0]** -0.0 [0.0] -0.02 [0.0]* -0.02 [0.0]* ΔHRATE(- 0.26 [0.04]*** 0.2 [0.08] 0. [0.08] 0. [0.08] ) ΔMRATE 0.45 [0.06]*** ΔMRATE(-) 0.43 [0.07]*** 0.43 [0.07]*** 0.45 [0.07]*** ΔCOST(-) 0.02 [0.02] 0.02 [0.02] 0.02 [0.02] ΔRISK(-) 0.0 [0.03] 0.00 [0.03] 0.0 [0.03] ΔHHI(-) 0.05 [0.07] ECT -0.23 [0.05]*** -0.6 [0.04]*** -0.8 [0.03]*** -0.7 [0.03]*** Coiegraig equaios Model 2 CE CE 2 CE 3 Cosa -4.30-2.5 -.4 -.48 MRATE 0.80 0.95 [0.03]*** 0.96 [0.03]*** [imposed] COST 0.02 0.03 [0.0]*** 0.03 [0.0]*** 0.03 [0.0]*** RISK 0.4 0.7 [0.03]*** 0.8 [0.02]*** 0.8 [0.03]*** HHI 0.6 0.04 [0.04] Coefficie resricios Noe Noe Exogeeiy Exogeeiy, pass-hrough 2 R es prob. 0.54 0.5 Adjused R 2 0.79 0.6 0.6 0.60 SEE 0.08 0.0 0.0 0.0 DW.99 Approach Egle-Grager Johase Johase Johase Mehod OS M M M Sample 995M05 995M05-995M05-995M05-2009M09 2009M09 2009M09 2009M09 HRATE deoes he ieres rae o ew housig loas, MRATE he 2-moh moey marke rae, COST he bakig secor's admiisraive-cos-o-asses raio, RISK he uemployme rae, HHI he Herfidahl-Hirschma idex for oal ledig, ECT he error-correcio erm, ad Δ he differece operaor. *** Coefficie saisically sigifica a he % level, ** 5% level, * 0% level usig Newey-Wes heeroskedasiciy ad auocorrelaio cosise sadard errors [i square brackes]. Weak exogeeiy of MRATE, COST ad RISK. 2 Complee log-ru pass-hrough of MRATE. 30
The esimaed speed of adjusme (γ) varies slighly bewee he models (from 0.6 i VECM o 0.23 i ECM ), bu i ay case i ca be regarded as relaively high. For example, accordig o las model (VECM 3), i akes less ha six mohs ( /0.7) for a deviaio from he log-ru equilibrium o be correced. The sluggishess of he adjusme may, by ad large, reflec he fac ha i he shor ru borrowers ca affec he degree ad speed of pass-hrough by choosig bewee differe referece raes, ie moey marke raes ad more sicky prime raes, depedig o he direcio of marke raes. To sum up, shor-ru movemes i he average ieres rae o ew housig loas i Filad ca be largely explaied by chages i moey marke raes, while i he log ru developmes are also affeced by less volaile cyclical ad srucural facors. Over he period cosidered, he raio of baks admiisraive expeses o oal asses ad he uemployme rae combie o capure he chagig of he average ledig rae margi. 5 Coclusios This paper has examied how housig loa raes are deermied, usig Fiish daa. Filad is a example of a bak-based euro area coury where he majoriy of loas are graed a variable raes. The paper exeds he earlier ieres rae pass-hrough lieraure by akig explicily io accou he chagig of ledig rae margis. A sadard ledig rae model, specified as a error-correcio model, is exeded wih variables prediced by a heoreical bak ieres rae seig model. The empirical resuls show ha, sice he mid-990s, shor-ru movemes i housig loa raes ca be largely explaied by chages i moey marke raes, ad ha log-ru developmes have also bee affeced by less volaile cos ad credi risk facors. The roles of loa compeiio ad capial regulaio are also cosidered, bu he effecs are more difficul o ideify. The pass-hrough of marke ieres raes o bak ledig raes is oe of he key chaels of moeary rasmissio. I he case of ew housig loas i Filad, he esimaed speed of adjusme is raher high, which ehaces he effeciveess of moeary policy. O he egaive side, he rapid pass-hrough may weake fiacial sabiliy by icreasig he volailiy of housig markes. Hisorically, housig prices i Filad have bee highly volaile i he ieraioal compariso (eg ECB, 2003, ad IMF, 2004), bu he role of shor ieres rae fixaio periods has o ye bee explored. Furhermore, due o he high share of variable-rae loas i Filad, chages i marke ieres raes pass hrough o ieres raes of mos of he ousadig loas as well. This mechaism makes he fuure ieres expeses ucerai ad icreases risks bore by he borrowers. 3