Income Volatility and Residential Mortgage Delinquency: Evidence from 12EU Countries

Income Vola ili y and Residen ial Mo gage Delinquency: E idence om 12 EU coun ies Luis Diaz-Se ano Na ional Uni e si y o I eland Maynoo h IZA Bonn, CREB Ba celona Co esponding au ho : Luis Diaz-Se ano Na ional Uni e si y o I eland Maynoo h Depa men o Economics (Rhe o ic House) Maynoo h, Co. Kilda e, I eland Tel: +353 1 7083793 Fax: +353 1 7083934 Email: [email protected] 1 Abs ac : We in es iga e he socio-economic de e minan s o mo gage delinquency in 12 EU coun ies and obse e ha income ola ili y signi ican ly inc eases he mo gage delinquency isk. This pa e n e en holds o bo owe s wi h highe -income p o iles i ola ili y in income is high enough. F om his esul we can d aw he ollowing conclusions: i) mo gage p o ec ion insu ance policies migh be ailing o co e hose bo owe s mos in need; ii) he exis ence o c edi ma ke impe ec ions, and; iii) he inabili y o a numbe o bo owe s mos a income isk o accumula e p ecau iona y sa ings in o de o mee mo gage paymen s when shocks in income a ise. JEL classi ica ion: D1, R0, J0 Keywo ds: Income ola ili y, mo gage delinquency, mo gage insu ance, homeowne ship, paymen - o-income a io, c edi ma ke impe ec ions, p ecau iona y sa ings. 2 1. In oduc ion Du ing he second hal o he 1990s and ea ly 2000s he a es o mo gage delinquency ha e allen d ama ically in mos o he EU-151 coun ies. These downwa d ends coincide wi h alling in e es a es and imp o ing pe o mances in mos o he EU-15 economies. Pa adoxically, his decline in he mo gage delinquency a es has also coincided wi h upwa d ends in he p ices o housing, which in coun ies as I eland, Spain, UK o The Ne he lands has been d ama ic. Besides he a o able economic condi ions men ioned abo e, a g ea e e o by he lending indus y o make mo gage ake-up mo e a o dable has been necessa y o mi iga e such a d ama ic inc ease in housing p ices. Despi e he decline in mo gage delinquency a es, his phenomenon s ill exis and aises issues no only o lende s bu also o bo owe s. Fo he o me g oup, apa o m he ob ious well documen ed economic losses ha a de aul would suppose, he e a e some s udies ha epo heal h p oblems associa ed wi h he unsus ainable housing and he mo gage a ea s (see e.g. Bu ows, 1998; Ne le on and Bu ows, 1998, in he UK; Be y e al., 1999, in Aus alia; Doling and Ruona aa a, 1996, in Finland). In andem wi h he upwa d ends in mo gage ake-up he e exis a g owing indus y de o ed o p o iding sa e y-ne s o mo gage bo owe s ia he same lending ins i u ions o insu ance companies. The objec i e o he mo gage insu ance policies is o coun e ac he po en ially de as a ing e ec o he un o eseen e en s ha cause luc ua ions in he mo gago ’s income. The e o e, in he e en o in olun a y unemploymen , sickness o o he unexpec ed shock in he mo gago ’s income, he mo gage paymen is co e ed. Howe e , he g owing li e a u e in his issue, mainly 1 We e e o EU-15 as he 15 EU coun ies be o e he ex ension o 25 coun ies execu ed in May-2004. 3 ocused on he UK mo gage ma ke , p o ide e idence on he ine iciency and inadequa eness o he p i a e mo gage p o ec ion insu ance (MPI) policies in bo h he low ake-up om hose bo owe s mos a income isk and he poo co e age o he isks (see P yce and Keoghan, 2002; Fo d and Quilga s, 2001). In his pape we examine he de e minan s o mo gage delinquency in 12 o he EU-15 coun ies. We ocus on he socio-economic ac o s a he han hose ega ding he cha ac e is ics o he mo gage o he mo gaged p ope y. In his con ex , we belie e ha ola ili y in household’s income is he a iable ha , in a isky wo ld, bes p oxies he wide ange o un o eseen e en s ha migh cause mo gage delinquency o mo gage a ea s. Addi ionally, o he socio-economic ac o s such as di e en ypes o employmen , unemploymen and income a e conside ed. To some ex en , we belie e ha examining he e ec o all hese ac o s on he esiden ial mo gage delinquency isk is also a plausible es on he pe o mance o he mo gage insu ance indus y, he po en ial exis ence o capi al ma ke impe ec ions, o he (in)abili y o hose households mos a income isk o accumula e p ecau iona y sa ings o mee he mo gage paymen s when a shock in income a ises. On he one hand, an e icien mo gage insu ance ma ke would be ha capable o emo ing he e ec o mos o hese ac o s om he mo gage delinquency p opensi ies by p o iding bo h a sui able co e age o he isk as well as co e ing hose mos in need. On he o he hand, in he absence o a mo gage insu ance households suscep ible o expe ience shocks in income a e supposed o sa e om posi i e shocks o ace he nega i e ones, o o bo ow i he e exis a pe ec capi al ma ke . Unde his scena io we should expec income ola ili y o exe an insigni ican e ec on he likelihood o mo gage delinquency once we con ol o he le el o income. 4 T adi ionally, he econome ic analysis o he de e minan s o he p obabili y o mo gage delinquency o de aul has been ca ied ou using he s anda d logi o p obi model. Howe e , i he p e ious enu e choice p ocess is no accoun ed o , es ima es coming om his model a e biased. To sol e his we es ima e a bi a ia e model wi h sample selec ion whe e bo h he homeowne ship and mo gage delinquency p opensi ies a e conside ed simul aneously. The pape is s uc u ed as ollows: Sec ion 2 o e s and o e iew o he li e a u e on mo gage delinquency and de aul In sec ion 3 we b ie ly discuss some o he main de e minan s o mo gage delinquency. In sec ion 4 we desc ibe he da ase and he empi ical amewo k. Sec ion 5 shows ou main indings. And sec ion 6 summa izes and concludes. 2. O e iew o he li e a u e: Mo gage delinquency, de aul and insu ance The li e a u e on mo gage delinquency is qui e sca ce and mos o he s udies ocus on mo gage de aul . Howe e , gi en ha mo gage delinquency in i sel usually is he p ecu so o he ul ima e de aul , i seems in e es ing o s udy his aspec o he mo gage ma ke . Also mos o he p e ious s udies ocus on he cha ac e is ics o he mo gage and he mo gaged p ope y as he de e minan s o de aul , and lea e bo owe ’s socio-economic cha ac e is ics as a esidual elemen . Two s udies ha explici ly examine mo gage delinquency in he US a e G een and Fu s enbe g (1975) and Sp inge and Walle (1993). The i s obse ed ha in neighbo hoods wi h inc easing black popula ion he p opensi y o mo gage delinquency is highe . The second ocused on he lende ’s side and examined he ac o s de e mining he iming o he lende ’s o eclosu e decision wi h delinquen mo gages. They obse ed ha he 5 du a ion o he delinquency pe iod and he inal lende ’s o eclosu e decision depend on he bo owe ’s equi y posi ion. Ande son and Vande Ho (1999) also ocused on he bo owe ’s ace and obse ed ha black mo gago s a e mo e likely o de aul . Also in he con ex o he US housing ma ke Kau and Keenan (1999) s udied he p obabili y o mo gage de aul and he se e i y loss o his de aul , and obse ed ha he dis ibu ion o he de aul se e i y is c i ical in de e mining he bo owe ’s decision o de aul . Vandell and Thibodeau (1985) examined he likelihood o mo gage de aul using US indi idual loan his o y da a. These au ho s obse ed ha bo h he loan- o- alue (LTV) a io and he di e ence be ween he ma ke alue o he mo gaged p ope y and he pa alue o he mo gage a e posi i ely ela ed o he p obabili y o de aul , and su p isingly, he paymen - o-income (PTI) a io is nega i ely ela ed. They jus i y such a s iking esul by a guing ha highe PTI a ios a e associa ed wi h bo owe s who ha e ample addi ional esou ces o o e come a de aul . Deng e al. (1996) also ound e idence o he ele ance o he LTV a io on he p obabili y o mo gage de aul . They also obse ed ha un o eseen si ua ions as unemploymen and di o ce ac as igge e en s on he p obabili y o de aul . Ross (2000) s udied de aul p opensi ies con olling o he sample selec ion caused by he app o al p ocess p e ious o he mo gage ake-up. Ou side he US he numbe o s udies examining he de e minan s o he mo gage de aul isk a e mo e limi ed. Chinloy (1995) ea s de aul as a h ee s age sequen ial p ocess, ini ial delinquency, long- e m non-paymen and ul ima e de aul . He applied his mul is a e mo gage de aul model o he UK and ound ha income and liquidi y cons ain s de e mine he bo owe ’s decision o keep a mo gage e en when he home equi y becomes nega i e. Eichhol z (1995) in es iga ed he e ec o egional economic 6 s abili y in he egional a es o de aul in he Ne he lands. This au ho concludes ha he egional employmen cha ac e is ics a e good p edic o s o he egional le els o mo gage de aul . The li e a u e on mo gage insu ance is apidly g owing, hough he e a e s ill ela i ely ew heo e ical s udies. B ueckne (1985) cons uc ed a wo-pe iod model o analyze he bo owe ’s choice o he op imal ime pa e n o mo gage paymen s assuming u u e house alues as unce ain. The amoun o he p emium will depend on he iskiness o he mo gage and he ini ial down paymen . P yce (2002) de eloped a heo e ical model o he mo gage p o ec ion insu ance decision aking in o accoun he wel a e sys em and he consump ion los in a o o he insu ance p emiums. The e a e many mo e empi ical s udies, hough mos o hem ocus on he UK mo gage ma ke . All o hese s udies emphasize he inadequa eness and he ailu e o he MPI policies. P yce and Keoghan (2001, 2002) and Fo d and Quilga s (2001) ound e idence ha he main consume s o such an insu ance policies we e no hose bo owe s mos a income isk. Bu cha d and Hill (1997, 1998) ound ha MPI-holde s did no ha e signi ican ly g ea e unemploymen isks han he uninsu ed mo gago s. Fo d e al. (1995) indeed ound ha only a qua e o he insu ed mo gago s in a ea s ied o claim. Kempson e al. (1999) obse ed ha hose bo owe s wi h uns able wo k his o ies and ill-heal h a e sys ema ically p ecluded om being eligible o he MPI policies. 3. The de e minan s o mo gage delinquency Mo gage delinquency ep esen s a ele an p oblem o lende s. As men ioned ea lie , hough mo gage delinquency does no sys ema ically lead o a de aul , 7 undoub edly i ends o be he p ecu so o he ul ima e de aul . Hence, he de e minan s o he ini ial delinquency will also in luence he inal mo gage de aul . Howe e , analyzing he p obabili y o de aul is somewha mo e complica ed since he o eclosu e p ocess can be sys ema ically delayed because o go e nmen egula ions o he lende s olun a ily allowing he leng hen o he delinquency pe iod. Al hough a iables such as he LTV a io is one o he p ima y ac o s a ec ing he isk o de aul and hence also he ini ial mo gage delinquency, in his s udy we a he ocus mo e on he bo owe ’s socio-economic ac o s. The mo gago ’s le el o income and he a iables de e mining his income (occupa ion, educa ion, he ype o employmen , e c.) a e expec ed o exe a signi ican e ec on he mo gage delinquency isk. As men ioned ea lie , in a pe ec wo ld we e households do no ace bo owing cons ain s o can sa e du ing posi i e shocks o mee he nega i e ones, we should expec income ola ili y o ha e an insigni ican e ec on mo gage delinquency once we con ol o income le el. Howe e , he p e ious in e na ional empi ical e idence on hese issues does no allow us o admi he exis ence o “such a pe ec wo ld”. One he one hand, he exis ence o c edi ma ke impe ec ions is well documen ed. Fo ins ance, Jappelli and Pagano (1989) obse ed o a selec ed g oup o OECD coun ies (Sweden, USA, UK, Japan, I aly, Spain and G eece) ha he sensi i i y o consump ion o cu en income luc ua ions was e y high. They ound his esul o be caused by he exis ence o capi al ma ke impe ec ions. On he o he hand, con adic ing he p ecau iona y mo i e o sa ings assumed in he heo e ical li e a u e, he e exis li le empi ical e idence suppo ing ha weal h accumula ion and sa ings a ise as a p ecau ion agains u u e income isk. (Guiso e al. ,2002, in I aly; A ondel ,2002, in F ance; Skinne ,1988, and Lusa di ,1998, in he US). In his con ex , we belie e ha income ola ili y, 8 a he han income le el, migh be mo e sui able o cap u ing he bo owe ’s abili y o ace he pe iodical mo gage paymen s. The e o e, we ocus on his a iable as he main de e minan o mo gage delinquency. Unexpec ed si ua ions such as in olun a y unemploymen o job mobili y, sickness, demand shocks o any o he un o eseen e en ha cause luc ua ions in household’s income may also aise he isk o mo gage delinquency. To cap u e hese e ec s we conside he unemploymen his o y o he household head du ing he las 5 yea s p e ious o he su ey and his/he sel - epo ed heal h s a us du ing las 12 mon hs p e ious o he su ey. As men ioned abo e, in o de o a oid mo gage delinquency all hese isks migh be co e ed by he mo gago ’s own inancial esou ces. The e o e, we also es he ole o sa ings as a de e minan o mo gage delinquency. Addi ionally o he LTV a io, he loan- o-income (LTI) a io is also an impo an de e minan o mo gage delinquency isk. Clea ly, i he LTV and LTI a ios a e oo high his may signi ican ly a ec he paying capaci y o he bo owe . Howe e , he e ec o hese a iables can be smoo hed h oughou ime by con ac ing a mo gage wi h longe du a ion. This would be he case o some no hwes e n EU coun ies as Denma k o The Ne he lands whe e high LTV (abo e 80-90 pe cen ) and high LTI (abo e 3) a ios a e combined wi h longe mo gage du a ions (30-35 yea s). These igu es con as wi h o he EU coun ies as I aly, Belgium o Aus ia whi LTV a ios bellow 50 pe cen and LTI alues bellow 1 combined wi h mo gage du a ions ha ange o m he 10-15 yea s in I aly o he 15-20 yea s in Belgium o Aus ia2. The e o e, since he a loan wi h a gi en size migh become mo e a o dable wi h a longe paymen pe iod, he paymen - o-income (PTI) a io is p obably he a iable ha bes measu es 2 See Neu eboom (2003) o an ex ensi e analysis o he isks associa ed o he LTV and LTI a ios in a selec ed g oup o EU coun ies. 15 incomes han homeowne s, and only in I eland and Aus ia a e he le els o income ola ili y simila be ween bo h enu e ypes. Ma ked di e ences a e also obse ed in mos o he coun ies conce ning he le els o household income ola ili y be ween mo gage delinquen s and non-delinquen s. Excep in F ance and Finland, income ola ili y ends o be subs an ially la ge o mo gage delinquen s. These esul s sugges ha bo h he homeowne ship and mo gage delinquency pa e ns migh be in luenced by his a iable. Inse able 2 a ound he e Table 3 epo s he econome ic es ima ion o he bi a ia e p obi wi h sample selec ion on mo gage delinquency. Recall ha gi en he nonlinea na u e o he econome ic model, he es ima ed coe icien s lack o any economic in e p e a ion and a e jus used o de e mine he di ec ion o he ela ionship. Howe e , since we a e no in e es ed in compa ing he magni ude o he es ima ed e ec s ac oss coun ies, he sign and signi icance o he es ima ed coe icien s a e enough o d aw ou conclusions. I is wo h no ing ha excep o Belgium, he co ela ion be ween bo h equa ions is highly signi ican ( 0 ρ ≠). This esul indica es ha con olling o sample selec ion is c i ical o ob ain unbiased es ima es in he mo gage delinquency equa ion. Fo he sake o simplici y we will ocus on he es ima es conce ning he a iables we conside as impo an de e minan s o he mo gage p o ec ion insu ance ake-up. These a iables indica e which households a e mos a income isk, and hence mos in need o he MPI. These a e household income, income ola ili y, sa ings, household’s 16 head unemploymen his o y and his/he sel - epo ed heal h s a us. We assess signi icance a 5 pe cen . As expec ed, household income is highly signi ican in bo h he homeowne ship and he mo gage delinquency equa ion, and wi h he expec ed sign in all coun ies. Ou key a iable, income ola ili y, u ns ou o be signi ican in bo h he homeowne ship and he mo gage delinquency p opensi ies o mos o he coun ies. We obse e a nega i e e ec on homeowne ship5 and a posi i e one on mo gage delinquency. Excep ions o his gene al esul a e Po ugal and Aus ia whe e he e ec on homeowne ship is insigni ican , Luxembou g whe e he e ec on mo gage delinquency is insigni ican , and I eland wi h an insigni ican e ec on bo h he homeowne ship and he mo gage delinquency p opensi ies. Household heads ha we e unemployed a leas once du ing he i e yea s be o e he su ey also shows a signi ican nega i e e ec on homeowne ship, and posi i e on mo gage delinquency in mos o he coun ies. An insigni ican e ec on homeowne ship is only obse ed in Spain and Luxembou g, while an insigni ican e ec on mo gage delinquency is obse ed in he UK, Po ugal and Luxembou g. The sel - epo ed bad-heal h o he household head also e eals i sel as an impo an a iable, hough in I eland, Spain and Aus ia he e ec is no signi ican in ei he he homeowne ship o mo gage delinquency equa ions, and no signi ican o Belgium in he mo gage delinquency equa ion. We obse e ha in all coun ies he a iable sa ings exe s a signi ican nega i e e ec on he p obabili y o mo gage delinquency, while he e ec is posi i e on homeowne ship o all coun ies excep o F ance, I aly and Finland. 5 This esul coincides wi h he p e ious empi ical e idence analyzing he e ec o income unce ain y on he p obabili y o homeowne ship (Hau in, 1991; Robs e al., 1999, in he US; Diaz-Se ano, 2004a, in Ge many and Spain; Diaz-Se ano, 2004b, in I aly). 17 Consis en wi h he p e ious e idence in he US, we also obse e ha in “bad neighbo hoods”, p oxied as he exis ence o c ime o andalism, homeowne ship is less likely and he e exis a g ea e p opensi y o mo gage delinquency. Howe e , in con as wi h wha G een and Fu s enbe g (1975) obse ed, we ind li le e idence han mo gage delinquency is less likely in he ea lie yea s o he mo gage ake-up and wi h inc easing p obabili y a la e s ages. This e ec is only obse ed in Belgium, while he opposi e holds o Denma k, Luxembou g, UK, I eland and Finland. In he es o coun ies he e ec o he age o he mo gage on he mo gage delinquency isk has u n ou o be unimpo an . Inse able 3 a ound he e We ha e also ca ied ou sepa a e es ima es o ou bi a ia e p obi model wi h sample selec ion including he PTI a io as explana o y a iable in he mo gage delinquency equa ion. Resul s a e epo ed in able 4. We ollow his p ocedu e in o de o a oid he po en ial inconsis ency ha he endogenous na u e o his a iable migh cause in ou es ima es. Howe e , in all he coun ies examined hese new es ima es a e simila o he ones shown in able 3 conce ning he sign, he size and he signi icance o he o he explana o y a iables. In all coun ies excep in Denma k, UK, I eland and Aus ia, he PTI a io exe s a signi ican and posi i e e ec on he mo gage delinquency isk. This esul con as s Vendell and Thibodeau (1985) in he US, who obse ed he opposi e. Inse able 4 a ound he e 18 Finally, we shall poin ou ha o a sui able unde s anding o he e ec o income ola ili y on bo h he homeowne ship and mo gage delinquency p opensi ies, his a iable should be ela ed wi h he le el o income i sel . One may be emp ed o associa e mo e ola ile incomes o low-income p o iles, howe e , i is no necessa ily ue. The e a e a numbe o s udies in he labo economics li e a u e whe e he isk- e u n ade-o in indi iduals’ income is well documen ed6. To es o wha ex en his inding i s ou da a, we ha e ca ied ou eg essions aking ou measu e o income ola ili y (CV) as he endogenous a iable. The esul s a e shown in able 5. A e con olling o a numbe o ac o s we obse e ha mo e ola ile incomes a e associa ed o highe le els o income in all coun ies excep in he UK and he sou he n EU coun ies (I aly, Spain and Po ugal). This esul is qui e e ealing since i indica es ha highe -income p o iles a e also suscep ible o incu in mo gage delinquency i he le el o ola ili y in income is high enough. The coun ies we e his pa e n does no hold a e hose ha epo ed he highe le els o income ola ili y (see able 2). Inse able 5 a ound he e 6. Discussion and concluding ema ks In his pape we examine he p obabili y o mo gage delinquency in 12 EU coun ies. To a oid he bias caused by he homeowne ship selec ion p ocess we use he bi a ia e p obi model wi h sample selec ion. To examine he de e minan s o he mo gage delinquency isk we ocus on he mo gago ’s socio-economic cha ac e is ics 6 King, 1975; McGold ick (1995), Ha og and Vi ej e g (2002), in he US and Ha og e . al. (2003), o a selec ed g oup o EU coun ies obse ed ha mo e a iable ea nings dis ibu ions end o possess also a highe mean. 19 a he han on he mo gaged p ope y and he cha ac e is ics o he mo gage, as usual in he de aul isk li e a u e. We pay special a en ion o hose a iables ha a e likely o cause shocks in he mo gago ’s income, and hence a e also likely as de e minan s o he mo gage insu ance ake-up. Ou key a iable is household’s income ola ili y p oxied as he coe icien o a ia ion o ne annual household income, which u ns ou o be c ucial in explaining bo h he homeowne ship and he mo gage delinquency pa e ns. O he a iables as unemploymen , sa ings and he ill-heal h s a us o he household head also ha e signi ican e ec s. To some ex en , one migh ind su p ising ha he same esul pe sis en ly holds o such di e en coun ies in e ms o bo h hei housing and hei mo gage ma ke s7. Howe e , i sugges s ha hough he e a e ma ked di e ences among hem, unsus ainable homeowne ship and lende ’s a i ude owa ds he mo gage delinquency isk is a common elemen ac oss mos o he coun ies examined in his s udy. The ac ha income ola ili y signi ican ly inc eases he mo gage delinquency isk sugges s he exis ence o c edi ma ke impe ec ions and he low abili y o hose households mos a income isk o accumula e p ecau iona y sa ings. Hence, when a nega i e shock in income a ise mo gage delinquen s eac s educing housing consump ion i he size o shock is big enough. Addi ionally, he signi icance o he o he s ac o s lis ed abo e also sugges s ha MPI policies a e no adequa e in co e ing hose households mos in need o he ange o isks co e ed. As obse ed in he UK, a la ge p opensi y o a low-income mo gago p o ile o be a mo gage delinquen sugges s ha p obably o his popula ion s a um he low MPI ake-up is d i en by he non-a o dabili y o he p emiums. Howe e , in his pape we no only obse e ha 7 See Me ce Oli e Wyman’s (2003) epo o an ex ensi e analysis o he mo gage ma ke s in a selec ed g oup o EU-15 coun ies. 20 income ola ili y inc eases signi ican ly he p obabili y o mo gage delinquency, bu also ha mo e ola ile incomes a e associa ed o highe -income p o iles. This esul sugges s ha e en being a o dable, he low MPI ake-up om he bo owe s wi h highe income-p o iles and wi h la ge income ola ili y is p obably d i en by he limi ed co e age o he isks associa ed wi h he mo gago ’s income. Undoub edly, bo h lende s and insu e s a e in business, he e o e, e iciency and adequa eness mus be sac i iced o he sake o p o i abili y. In he UK he e is e idence ha MPI p emiums do ise du ing slumps and all du ing booms (Goodman, 1998). And in Walke e al. (1995) he e a e lis ed a numbe o clauses in he MPI con ac s ha p eclude a la ge numbe o claims. Hence, he numbe o e en s sensible o cause shocks in mo gago ’s income co e ed by MPI policies is ce ainly limi ed. Ou esul s sugges ha simila analyses o he EU coun ies examined he e using MPI ake-up da a will p obably p o ide he same indings. I seems ha bo h insu e s and lende s play mo e wi h mo gago ’s isk a e sion han wi h his/he needs. Al hough his li e a u e is g owing, we ind his issue is s ill unde - esea ched. Gi en i s impo ance and implica ions o bo h lende s and bo owe s mo e esea ch in hese lines would be necessa y. 21 Re e ences Ande son, R., Vande Ho , J., 1999. Mo gage de aul a es and bo owe ace. J. Real Es a e Res. 18, 279-289. A ondel, L., 2002. Risk managemen and weal h accumula ion beha io in F ance. Econ. Le e s 74, 187-194. Be y, M., Dal on, T., Engels, B., Whi hing, K., 1999. Falling ou o Home Owne ship. Uni e si y o Queensland P ess, B isbane. B ueckne , J.K., 1985. A simple model o mo gage insu ance. AREUEA J. 13, 129- 142. Bu cha d , T., Hills, J., 1997. Mo gage paymen p o ec ion: eplacing s a e p o ision. Housing Finance 33, 24-31. Bu cha d , T., Hills, J., 1998. F om pubic o p i a e: he case o mo gage paymen insu ance in G ea B i ain. Housing S ud. 13, 311-323. Bu ows, R., 1998. Mo gage indeb edness in England: an ‘epidemiology’. Housing S ud. 13, 5-22. Chinloy, P., 1995. P i a ized de aul isk and eal es a e ecessions: he UK mo gage ma ke . Real Es a e Econ. 23, 401-402. Deng, Y., Quigley, J.M., Van O de , R., Mac, F., 1996. Mo gage de aul and low downpaymen loans: he cos s o public subsidy. Reg. Sci. U ban Econ. 26, 263- 285. Diaz-Se ano, L., 2004a. Labo Income Unce ain y, Skewness and Homeowne ship: a Panel Da a S udy o Spain and Ge many. IZA Discussion Pape 1008, IZA, Bonn. 22 Diaz-Se ano, L., 2004b. On he nega i e ela ionship be ween income unce ain y and homeowne ship: isk-a e sion s. c edi cons ain s. IZA Discussion Pape 1208, IZA, Bonn. Doling, J., Ruona aa a, H., 1996. Home owne ship unde mined: an analysis o he Finnish case in he ligh o he B i ish expe ience. J. o Housing Buil En . 11, 31- 46. Eichhol z, P.M.A., 1995. Regional economic s abili y and mo gage de aul isk in he Ne he lands. Real Es a e Econ. 23 (4), 421-439. Fo d, J., Kempson, E., Wilson, M., 1995. Mo gage a ea s and possessions; pe spec i es om bo owe s, lende s and he cou s. Depa men o en i onmen , HMSO, London. Fo d, J., Quilga s, D., 2001. Failing home owne s? The e ec i eness o public and p i a e sa e y-ne s. Housing S ud. 16, 147-162. Guiso, L., Jappelli, T., Te lizzese, D., 1992. Ea nings unce ain y and p ecau iona y sa ings. J. Mone . Econ. 30, 307-338. G een, R.J., Fus enbe g, G.M., 1975. The e ec s o ace and age o housing on mo gage delinquency isk. U ban S ud. 12, 85-89. Ha og, J., Plug, E.J.S., Diaz-Se ano, L., Viei a, A.J.C., 2003. Risk compensa ion in wages: a eplica ion, Empi ical Econ. 28, 639-647. Ha og, J., Vij e be g, W., 2002. Do wages eally compensa e o isk a e sion and skewness a ec ion, IZA discussion pape #426, IZA, Bonn. Hau in, D.R., 1991. Income a iabili y, homeowne ship, and housing demand. J. Housing Econ. 1, 60-74. 23 Jappelli, T., Pagano, M., 1989. Consump ion and capi al ma ke impe ec ions: an in e na ional compa ison. Ame . Econ. Re . 79, 1088-1105. Lusa di, A., 1998. On he impo ance o he p ecau iona y sa ings mo i e. Ame . Econ. Re . 88, 449-453. Kau, J.B., Keenan, D.C., 1999. Pa e ns o a ional de aul . Reg. Sci. U ban Econ. 29, 765-785. Kempson, E., Fo d, J., Quilga s, D., 1999. Unsa e sa e y ne s?. Cen e o Housing Policy, Uni e si y o Yo k. King, A., 1974. Occupa ional choice, isk a e sion, and weal h. Ind. Lab. Rela . Re ., July, 586-596. McGold ick, K., 1995. Do women ecei e compensa ing wages o ea nings unce ain y?, Sou he n Econ. J. 62, 210-222. MERCER OLIVER WYMAN, 2003. S udy on he inancial in eg a ion o Eu opean mo gage ma ke s. Ne le on, S., Bu ows, R., 1998. Mo gage deb , insecu e home owne ship and heal h: and explana o y analysis. In: Ba ley, M., Blane, D., Da ey-Smi h, g., (Eds.), The Sociology o Heal h Inequali ies, Blackwell P ess, Ox o d. P yce, G., Keoghan, M., 2001. De e minan s o mo gage p o ec ion insu ance ake-up. Housing S ud. 16, 179-198. P yce, G., 2002. Theo y and es ima ion o he mo gage paymen p o ec ion insu ance decision. Sco . J. Poli . Economy 49, 216-234. P yce, G., Keoghan, M., 2002. Unemploymen insu ance o mo gage bo owe s: is i iable and does i co e hose mos in need?. Eu . J. Housing Policy 2, 87-114. 24 Robs , J., Dei z, R., McGold ick, R., 1999. Income a iabili y, unce ain y and housing enu e choice. Reg. Sci. U ban Econ. 29, 219-229. Ross, S.L., 2000. Mo gage lending, sample selec ion and de aul . Real Es a e Econ. 28, 581-621. Ross, S.L., Too ell, G.M.B., 2004. Redlining he communi y ein es men ac , and p i a e mo gage insu ance. J. U ban Econ. 55, 278-297. Skinne , J., 1988. Risky income, li e cycle consump ion and p ecau iona y sa ings. J. Mone . Econ. 22, 237-255. Sp inge , T.M., Walle , N.G., 1993. Lende o ebea ance: e idence om mo gage delinquency pa e ns. AREUEA J. 21 (1), 27-46. Vandell, K.D., Thibodeau, T., 1985. Es ima ion o mo gage de aul s using disagg ega e loan his o y da a. AREUEA J. 13 (3), 292-316. 31 Table 3 (con inua ion) F ance UK I eland I aly Owne ship Mo age del. Owne ship Mo age del. Owne ship Mo age del. Owne ship Mo age del. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Cons an e m -3.747 -31.78 -2.071 -4.23 -1.019 -4.64 -4.714 -5.51 -2.179 -10.58 -0.197 -0.65 -2.491 -17.17 -0.774 -2.27 Income ola ili y -0.330 -6.69 0.261 2.54 -0.390 -3.43 0.716 2.29 -0.098 -0.90 0.215 1.81 -0.304 -5.37 0.489 4.24 Household income/1000 0.113 8.14 -0.138 -4.32 0.348 18.80 -0.164 -3.06 0.297 15.93 -0.172 -13.39 0.505 13.77 -0.138 -4.59 Sa ings 0.008 0.677 -0.710 -8.00 0.379 9.65 -0.644 -4.21 0.213 5.22 -0.505 -9.46 -0.002 -0.06 -0.452 -5.85 Household size 0.031 3.73 0.108 5.87 -0.050 -2.97 0.026 0.53 -0.136 -11.62 0.103 7.64 0.031 3.15 0.113 5.11 Job mobili y -0.787 -18.87 -0.622 -7.47 -0.749 -5.52 -0.463 -5.99 C ime in he a ea -0.252 -12.03 0.281 5.86 -0.436 -8.26 0.129 0.63 -0.408 -10.14 0.294 5.98 -0.121 -4.55 0.186 3.48 Mo gage age -0.008 -0.56 0.091 2.00 0.023 1.93 0.018 1.25 Mo gage age squa ed 0.001 1.48 -0.004 -1.68 -0.001 -2.26 -0.001 -1.02 Household head Age 0.152 30.14 0.019 0.88 0.046 6.65 0.139 3.73 0.122 13.89 -0.038 -2.69 0.077 13.00 -0.033 -2.56 Age squa ed -0.002 -29.79 0.000 -0.80 -0.001 -8.63 -0.002 -3.65 -0.001 -13.68 0.000 2.93 -0.001 -14.01 0.000 2.78 Seconda y educa ion 0.185 8.46 -0.092 -1.79 0.275 4.60 -0.154 -0.79 0.328 8.55 -0.270 -6.30 0.288 10.98 -0.217 -4.14 Highe educa ion 0.108 3.40 -0.191 -2.69 0.217 4.70 -0.225 -1.44 0.394 6.30 -0.229 -3.38 0.122 2.57 -0.369 -3.40 32 Female -0.222 -8.11 0.163 2.11 -0.053 -1.33 -0.160 -1.12 -0.239 -5.39 0.273 5.00 -0.061 -1.63 0.189 2.43 Sel -employed 0.095 2.53 -0.053 -0.75 0.535 6.15 -0.037 -0.19 0.216 3.60 -0.019 -0.33 0.038 1.16 0.214 3.57 Public employee -0.144 -6.31 0.014 0.25 0.178 2.79 -0.501 -1.96 0.130 2.65 -0.150 -2.84 0.035 1.23 -0.001 -0.02 Occupa ion dummies Yes No Yes No Yes No Yes No Unemployed las 5 yea s -0.369 -13.63 0.449 8.45 -0.179 -3.92 0.183 1.28 -0.523 -13.81 0.415 9.62 -0.249 -7.44 0.227 3.39 Bad Heal h -0.165 -4.91 0.219 2.96 -0.339 -5.51 0.573 2.81 -0.098 -1.28 0.181 1.78 -0.139 -3.73 0.305 4.22 Ma ied 0.708 30.71 0.014 0.23 0.359 7.80 -0.151 -1.50 0.965 17.73 0.276 3.43 0.273 6.93 -0.190 -2.44 Yea dummies Yes Yes Yes Yes Rho 0.568 -0.146 0.906 0.516 Tes ho=0 186.638 8.922 53.163 122.877 Log-likelihood -15,027 -3,250 -4,061 -9,742 Sample size 27,639 6,571 9,426 16,125 33 Table 3 (con inua ion) Spain Po ugal Aus ia Finland Owne ship Mo age del. Owne ship Mo age del. Owne ship Mo age del. Owne ship Mo age del. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Coe . Z- al. Cons an e m -1.245 -8.57 -0.981 -3.29 -1.515 -10.79 -0.989 -2.04 -3.225 -18.38 -5.137 -3.51 -2.190 -11.07 -1.686 -5.26 Income ola ili y -0.247 -3.97 0.556 5.15 -0.103 -1.54 0.521 3.07 -0.103 -1.38 0.555 1.98 -0.331 -3.41 0.399 2.99 Household income/1000 0.224 15.58 -0.244 -7.98 0.335 15.16 -0.205 -2.43 0.124 11.93 -0.254 -3.36 0.364 13.44 -0.154 -5.19 Sa ings 1.133 42.09 -0.324 -5.86 -0.196 -5.07 -0.612 -2.25 0.135 4.60 -0.576 -3.94 -0.032 -0.84 -0.618 -9.34 Household size 0.120 6.75 0.041 4.12 0.044 1.76 0.256 19.06 0.010 0.18 0.127 6.86 0.077 3.67 Job mobili y -0.158 -1.90 -1.336 -7.22 -0.805 -8.49 C ime in he a ea -0.637 -8.15 0.257 5.23 -0.060 -1.78 0.055 0.51 -0.615 -10.89 -0.298 -0.95 -0.460 -11.90 0.177 3.08 Mo gage age 0.000 -0.03 0.010 0.46 0.024 0.50 0.048 3.37 Mo gage age squa ed 0.001 0.79 -0.001 -0.75 -0.001 -0.60 -0.002 -2.87 Household head Age 0.056 9.19 -0.022 -1.78 0.035 5.61 -0.030 -1.58 0.083 13.53 0.155 2.58 0.053 7.47 0.025 1.92 Age squa ed -0.001 -12.05 0.000 1.84 -0.001 -8.28 0.000 2.35 -0.001 -13.47 -0.002 -2.85 -0.001 -6.98 0.000 -1.66 Seconda y educa ion -0.086 -2.49 -0.179 -2.59 0.119 2.78 -0.098 -0.84 0.004 0.10 -0.203 -1.32 0.141 3.40 -0.220 -3.87 Highe educa ion -0.040 -1.04 -0.121 -1.66 0.062 0.87 -0.133 -0.60 -0.158 -2.62 0.494 2.32 0.355 6.79 -0.302 -4.58 34 Female 0.066 1.61 0.086 0.94 0.016 0.46 -0.117 -1.00 -0.009 -0.27 -0.112 -0.59 0.102 2.95 0.017 0.36 Sel -employed 0.102 2.83 0.068 1.12 0.320 8.64 -0.037 -0.36 0.018 0.28 0.176 1.00 0.210 3.30 0.066 0.96 Public employee -0.043 -1.15 -0.232 -2.70 0.234 6.90 -0.127 -1.27 0.104 2.75 -0.083 -0.48 -0.028 -0.64 0.022 0.39 Occupa ion dummies Yes No Yes No Yes No Yes No Unemployed las 5 yea s -0.011 -0.38 0.208 3.96 -0.284 -7.82 -0.023 -0.18 -0.229 -5.97 0.515 3.41 -0.188 -5.17 0.240 4.76 Bad Heal h 0.072 1.83 0.090 1.22 -0.156 -4.19 0.255 2.31 -0.088 -1.71 0.094 0.45 0.063 1.14 0.079 1.07 Ma ied 0.471 11.21 -0.037 -0.47 0.352 8.80 -0.105 -0.79 0.143 2.89 -0.137 -1.01 0.203 4.70 0.050 0.81 Yea dummies Yes Yes Yes Yes Rho 0.435 0.548 0.191 0.640 Tes ho=0 84.217 68.884 9.661 154.357 Log-likelihood -8,834 -7,477 -6,301 -4,464 Sample size 13,386 14,393 11,527 7,348 35 Table 4: Es ima es o he bi a ia e p obi model Income ola ili y Paymen - o-income Coe . z- alue Coe . z- alue Denma k 0.6537 3.75 0.0598 0.50 The Ne he lands 0.5906 9.19 0.0140 6.26 Belgium 0.5771 4.02 0.6486 3.66 Luxembou g 0.2121 1.02 0.5642 3.60 F ance 0.2602 2.55 0.4946 2.71 UK 0.6860 2.15 0.0854 1.12 I eland 0.2081 1.74 0.3233 1.73 I alia 0.4758 3.88 0.4945 4.92 Spain 0.5321 4.70 0.6507 5.99 Po ugal 0.5170 2.96 0.3530 3.22 Aus ia 0.5512 1.96 0.0322 0.76 Finland 0.3855 2.83 0.1839 3.00 36 Table 5: OLS es ima ion o he de e minan s o income ola ili y (endogenous a iable: CV o household income). Denma k The Ne he lands Belgium Luxembou g F ance UK Coe . - alue Coe . - alue Coe . - alue Coe . - alue Coe . - alue Coe . - alue Cons an 0.545 42.12 0.308 16.85 0.149 7.80 0.226 14.01 0.542 52.12 0.455 27.04 Household Income/1040.090 11.62 0.163 19.96 0.074 13.23 0.075 11.51 0.103 20.44 -0.054 -5.23 Household size -0.027 -20.44 -0.005 -3.98 -0.014 -9.11 -0.005 -3.57 -0.012 -12.84 0.002 0.98 Age -0.011 -21.71 -0.003 -5.45 0.004 5.62 0.002 3.21 -0.008 -20.68 -0.003 -4.98 Age squa ed 0.000 18.00 0.000 4.25 -0.000 -4.66 -0.000 -4.34 0.000 13.51 0.000 1.53 Seconda y educa ion 0.020 6.37 0.003 1.19 0.015 4.01 -0.013 -3.81 -0.024 -9.99 0.008 1.27 Highe educa ion 0.020 5.41 -0.030 -7.25 -0.001 -0.24 -0.003 -0.57 0.000 0.13 0.004 0.92 Female 0.014 5.32 0.011 3.20 0.028 6.24 0.039 9.09 0.020 6.58 0.034 7.95 Sel -employed 0.175 30.64 0.180 31.72 0.197 33.34 0.067 10.31 0.126 28.48 0.054 6.66 Public employee -0.018 -5.35 -0.025 -6.69 -0.047 -9.35 -0.019 -4.45 -0.052 -17.41 -0.011 -1.66 P o essionals -0.030 -6.35 -0.038 -8.18 -0.028 -4.31 -0.037 -5.87 -0.050 -10.66 -0.033 -3.93 Technicians -0.024 -5.53 -0.044 -9.81 -0.020 -2.98 -0.023 -4.27 -0.051 -13.62 -0.068 -8.06 Cle ks -0.034 -6.44 -0.015 -2.57 -0.030 -4.73 -0.015 -2.39 -0.041 -8.51 -0.034 -4.68 Se ices and sales -0.022 -3.83 0.002 0.30 -0.017 -1.98 -0.031 -4.16 -0.036 -6.56 -0.023 -3.11 Skilled p ima y sec o 0.054 4.73 0.030 1.86 0.070 3.61 0.019 1.66 -0.020 -2.82 -0.014 -0.59 37 C a and ade -0.049 -9.09 -0.003 -0.65 -0.027 -3.76 -0.002 -0.32 -0.051 -13.57 -0.074 -8.05 Ope a o s -0.035 -5.81 -0.033 -5.07 -0.050 -5.50 -0.031 -4.72 -0.060 -14.43 -0.078 -8.66 Unemployed 0.013 4.20 0.038 9.32 0.026 5.72 0.100 6.09 0.000 0.14 0.027 5.09 Ma ied -0.015 -4.67 -0.038 -10.09 0.001 0.23 -0.015 -3.54 -0.022 -7.87 -0.048 -9.84 C ime in he a ea 0.010 2.38 0.003 1.05 -0.003 -0.65 0.125 12.44 0.002 0.83 0.037 6.55 Job mobili y 0.065 9.01 0.021 2.14 0.030 2.29 0.085 3.66 0.057 11.65 0.036 3.84 R-squa ed 0.246 0.175 0.203 0.146 0.199 0.211 Sample size 18,783 26,944 20,174 18,296 43,125 9,113 38 Table 5 (con inua ion) I eland I aly Spain Po ugal Aus ia Finland Coe . - alue Coe . - alue Coe . - alue Coe . - alue Coe . - alue Coe . - alue Cons an 0.068 4.49 0.231 18.31 0.093 7.02 0.086 5.68 0.245 14.82 0.502 34.81 Household Income/1040.025 9.37 -0.050 -20.10 -0.038 -4.33 -0.251 -15.59 0.029 3.16 -0.003 -0.28 Household size 0.004 4.48 0.015 17.42 0.020 24.54 0.010 10.56 0.001 0.95 -0.019 -12.44 Age 0.007 13.13 0.002 5.08 0.006 12.40 0.010 19.34 0.001 2.41 -0.009 -13.74 Age squa ed -0.000 -14.37 -0.000 -6.50 -0.000 -13.78 -0.000 -21.40 -0.000 -4.12 0.000 8.24 Seconda y educa ion 0.001 0.38 -0.022 -8.69 0.001 0.24 -0.005 -0.93 -0.008 -2.08 -0.002 -0.42 Highe educa ion -0.010 -2.26 -0.009 -2.00 -0.009 -2.56 0.014 1.78 0.001 0.12 -0.022 -4.66 Female 0.021 5.75 0.023 6.71 0.010 2.69 0.012 3.10 0.005 1.42 -0.008 -2.28 Sel -employed 0.112 26.48 0.156 53.91 0.199 65.19 0.124 34.70 0.160 23.38 0.097 16.78 Public employee -0.041 -10.74 -0.044 -14.87 -0.054 -14.44 -0.060 -14.37 -0.036 -7.72 -0.015 -3.24 P o essionals -0.022 -3.67 -0.045 -7.89 -0.051 -9.39 -0.025 -2.64 -0.031 -3.18 -0.015 -2.45 Technicians -0.018 -3.04 -0.064 -13.98 -0.040 -8.37 -0.068 -10.36 -0.018 -3.04 -0.018 -3.10 Cle ks -0.013 -1.95 -0.061 -15.39 -0.037 -6.34 -0.064 -9.38 -0.043 -6.47 -0.020 -2.72 Se ices and sales 0.015 2.28 -0.031 -7.03 -0.018 -3.79 -0.027 -5.03 -0.014 -2.17 -0.018 -2.56 Skilled p ima y sec o -0.097 -18.43 -0.004 -0.68 0.019 4.12 0.012 1.26 0.018 2.18 39 C a and ade 0.009 1.81 -0.053 -15.62 -0.046 -10.83 -0.054 -9.48 -0.028 -4.19 Ope a o s 0.009 1.70 -0.069 -14.46 -0.029 -6.89 -0.072 -12.70 -0.038 -4.92 -0.030 -3.94 Unemployed 0.036 10.16 0.095 30.62 0.083 31.60 0.029 6.65 0.016 3.67 -0.003 -0.85 Ma ied -0.020 -5.51 -0.007 -2.20 -0.039 -11.16 -0.037 -9.85 -0.034 -8.78 -0.022 -5.55 C ime in he a ea -0.008 -2.18 0.015 5.85 -0.003 -1.35 0.016 4.20 0.007 1.13 -0.007 -1.74 Job mobili y 0.088 5.70 -0.018 -2.00 0.068 7.49 -0.010 -0.86 0.083 5.77 0.103 11.46 R-squa ed 0.196 0.242 0.291 0.219 0.179 0.255 Sample size 19,211 46,708 39,741 34,598 18,907 12,552 40