ContentslistsavailableatScienceDirect
Journal of Financial Stability
journalhomepage:www.elsevier.com/locate/jfstabil
The effect of the financial crisis on default by Spanish households 夽
Carlos Aller
a,∗, Charles Grant
baUniversidadCEUCardenalHerrera,C/Carmelitas,3,03203Elche,Spain
bBrunelUniversityLondon,KingstonLane,Uxbridge,Middlesex,UB83PHLondon,UnitedKingdom
a r t i c l e i n f o
Articlehistory:
Received12December2016 Receivedinrevisedform2July2017 Accepted15February2018 Availableonline16February2018
JELclassification:
D14 G21 Keywords:
Spanishfinancialcrisis Household-debt Arrears
a b s t r a c t
WeanalysethedefaultbehaviourofSpanishhouseholdsimmediatelybeforeandaftertherecentfinancial crisis.UsingseveralwavesoftheSurveyofHouseholdFinances(atri-annualsurveyoffinancialposition ofSpanishhouseholds),weshowthatyounger,poorerandlesswelleducatedhouseholdsaremost likelytodefault.Akeycontributionistoexplainthechangeinarrearssincetheonsetofthecrisis.
Usinginformationoncreditapplicationsandacceptanceswedecomposethechangeinarrearsamongall householdsintoacontributionfromfourparts:(i)changesincharacteristics;(ii)changesinapplications;
(iii)changesinacceptances;(iv)changesinarrearsamongborrowers.Weshowthelastisthemost importantcontribution.
©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
Theaimofthispaperistoexploretheborrowingandrepay- mentbehaviourofSpanishhouseholdssince2002usinghousehold data.Therecentinternationalfinancialcrisishasaffectedanum- berofdevelopedeconomiesandSpainconstitutesaparticularly interestingcountrytostudyduetotheseverityofthecrisisand itsaftermath.Duringthespanofthisstudy,Spainexperienceda boomfollowedbyaseverecrashensuingfromthesub-primecri- sis.Unemploymentmore thandoubledfrom2007to2009,and householdsdefaultratesexperiencedevenlargerincreasesinthese years.BernardinoandGutiérrez(2012)andIganetal.(2014)show householdcreditinSpainhasmirroredthesechangesinthemacro- economy.Crook(2006)showsthatcredittothehouseholdsector hasexpandedmorerapidlythaninotherEUcountriesintheyears priortothecrisis,asSpanishhouseholdshavebecomeasheavily indebtedashouseholdsinNorthernEurope(seeCecchettietal.,
夽AuthorsaregratefulforhelpfulcommentstoparticipantsatXVIII(Alicante)and XIX(Seville)AppliedEconomicsMeeting,EconometricResearchinFinance(ERFIN) Workshop(Warsaw),FirstCatalanEconomicSocietyConference(Barcelona)and seminarparticipantsatUniversityofBalearicIslandsandMiddlesexUniversity London.WealsothankIftekharHasan(editor)andthreeanonymousrefereesfor commentswhichhavegreatlyimprovedthepaper.Allremainingerrorsareour own.FinancialsupportfromGeneralitatValencianagrantPrometeo/2017/158and from‘ObraSocialLaCaixa’aregratefullyacknowledged.
∗Correspondingauthor.
E-mailaddresses:carlos.allerarranz@uchceu.es(C.Aller), charles.grant@brunel.ac.uk(C.Grant).
2011;orBoveretal.,2016).Defaultratesonmortgagesandcon- sumerloansincreaseddramaticallyoverthisperiod,andakeyaim ofthisstudyistoexplorethecausesofthisincrease.Itwillinves- tigatewhethertheincreasewasduetochangesatthehousehold levelinincomeandunemployment,andwhetheritwastheresult ofcreditbeingextendedtopreviouslyexcludedhouseholds.
ThispaperwillusetheSurveyofHouseholdFinances(EFF),a householdleveldatasetavailableforfourdifferentwavesinthe period 2002–2011.Thissurvey wascommissionedby theBank ofSpaintocollectdetailedinformationaboutthefinancialposi- tionofSpanishhouseholdsandhenceitprovidesarichsourceto studythedebtholdingandrepaymentbehaviourofarepresenta- tivesampleofSpanishfamilies.Usinghouseholddataenablesusto understandthedifferencesacrosshouseholdsintheirresponsesto thecrisis.Thispaperwillalsodiscussthechangesintheborrowing andarrearsbehaviourofSpanishhouseholdsbeforeandafterthe financialcrisis.
BybuildingontheapproachofGrantandPadula(2016),wewill useadecompositionexercisetounderstandthechangesinarrears amongSpanishhouseholdssince2002(whichrosesharplyoverthe surveyperiod).Christelisetal.(2013)similarlyemployadecom- positionexercisewhenlookingatdifferencesinassetholdingin EuropeandtheUS.Theirexerciseinvestigateswhethercharacter- isticsorcoefficientsexplainthesedifferences.Inourdecomposition exercise, we willnote that betweenany two years theoverall changeinarrearsinthepopulationcanbesplitintofourparts:(i) changesincharacteristics;(ii)changesinapplications;(iii)changes inacceptances;(iv)changesinarrearsamongborrowers.Wewill
https://doi.org/10.1016/j.jfs.2018.02.006
1572-3089/©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.
0/).
investigatetherelativeimportanceofeachinexplainingtherisein arrearssince2002.Thusourexerciseinvestigateswhetherchanges incharacteristics(suchasunemploymentandincomechanges)can explaintheincrease inarrears duringtheGreat Recession.And sincetherewillbeseparateregressionsforcreditapplications,for bankacceptances,andforarrearsamongborrowers,theeffectof changesinthecoefficientsineachofthesethreeregressionscanbe separatelyexplored.Thuswewillbeabletoinvestigatewhether theriseinarrearswascausedbyanincreaseinapplicationsfor loanswhichwasaccommodatedbylenders,orwhetheritcaused byaweakeninginlendingstandards.
We proceed byfirst describing existing literature and some backgroundinformationabouttheSpanishcreditmarketinSec- tion2beforeproceedingwiththemainpartofthepaper.Section3 describestheSurveyofHouseholdFinances,thehouseholddataset whichwillbeusedforthemainanalysisinthepaper.Theresults arereportedinSection4.InSection5weproposeadecomposition exercisewhichwewillusetounderstandthecauseofthechange inarrears.OurconclusionsarereportedinSection6.
2. Literaturereview
Thereisalreadyanextensiveliteratureonhouseholdarrears aswellastherole ofarrearsinexplaining theGreat Recession.
Forexample,Gerlach-KristenandLyons(2015)exploretheroleof
‘affordability’andnegativeequityinexplainingmortgagearrears among Europeanhouseholds. For Spain, Ampudia et al. (2016) arguethatunemployment andlow wealthareamongthemost importantdeterminantsofdefault,whileSánchez-Martínezetal.
(2016)findthatSpanishhouseholdswhosefamilyheadisfemale, marriedorself-employedareathigherriskofmissingmortgage payments.Moreinterestingistoexplorehowchangesincharac- teristicsexplainsthecrisis.Forexample,Footeetal.(2009)and Eluletal.(2010)arguethatunemploymentandunexpectedfallsin incomehavedriventheincreaseindefaultamongUShouseholds.
SimilarlyBlancoandGimeno(2012)havearguedthatchangesin unemployment explain thesurge in Spanish household default between2007and2009.
Notallpapershaveattributedtheincreaseinarrearstochanges inhouseholdscharacteristics.MuchoftheUSliteraturehasfocused ontheexpansionofcreditpriortothecrisis.MianandSufi(2009), DemyanykandVanHemert(2011)andMayeretal.(2009)argue thattherecordsofUSlendersshowthattherewasadeteriorationof lendingstandardswhichprecipitatedthesub-primecrisis,which Keysetal.(2010)attributedtothereduced incentivetoscreen applicantswhicharosewiththesecuritizationofmortgagelend- ingintheUSmarket.Similarly,bothCrook(2006)andDuyganand Grant(2009),incross-Europeanstudies,showedtherehadbeen alargeincreaseinborrowingbySpanishhouseholdsintheyears priortothecrisis.UsinglendingrecordssuppliedbyaSpanishreal estatecompany,Akinetal.(2014)andDíaz-Serrano(2015)showed therewassofteningoflendingstandardsintheSpanishmarket, whileMaddaloni and Peydró (2011) reacha similarconclusion (especiallyformortgageloans)analysingtheBankLendingSurvey, aquarterlysurveyofEuroareabanksontheirlendingpractisesfor 2002–2008.
Thisreviewoftheliteraturesuggeststwodifferentexplanations oftheriseinarrearsduringthecrisis.Inthefirst,theriseinarrearsis theconcomitantconsequenceofthedeteriorationinlabourmarket conditions;whileinthesecond,theincreaseinarrearsistheconse- quenceoftheincreaseinlendingtohouseholdshithertoexcluded fromborrowingduetolowincomeandpoorcreditscores.While thesearethetwomostpopularexplanationsoftheriseinarrears duringtheGreatRecession,twootherrarerargumentshavealso beensuggestedintheliteratureonUShouseholds.Dell’Arriciaetal.
(2012),bylookingatthepoolofmortgageapplicants,arguethere wasanincreaseincreditdemandwhichwasatleastasimportantas changesinlendingpolicyintheUS.WhileGuisoetal.(2013)argue thatsurveyevidencesuggeststhatAmericanhouseholdsbecame morewillingtodefaultregardlessoftheircircumstancesduringthe sub-primecrisis.
2.1. TheSpanishcreditmarket
Thisstudycoverstheperiod2002–2011,theyearsimmediately priortoand followingtheoutbreakof the2008financial crisis.
ThiscrisishadsevereeffectsontheSpanishfinancialsectorand theSpanisheconomy,withimportantconsequencesforthehouse- holdsector.Spanishhouseholdstypicallyhold25-yearor30-year variableraterepaymentmortgages(whichmovewiththeEuro- zoneinterestrate),andthishasnotchangedoverthecrisisyears.
BernardinoandMartíndeVidales(2014)discusshowintheyears precedingthecrisistherewasarapidexpansionincredittothe householdsector, which theyassociated withtheliberalisation oftheregulationofsavingsbankswhich startedin1990.How- ever,theseorganisationswerenewlyregulatedfollowingthecrisis whenitbecameapparentthatmanysavingsbankswereunder- capitalized.
Fig.1aprovidesinformationonthehouseholddefaultratefor the mortgage(housing) loans and for consumer (non-housing) loans.CampbellandCocco(2015),inaUScontext,showthathouse- holdsarelikelytodefaultontheirmortgagewhentheyhavelittle ornoequityintheproperty(whichwillbeduringthefirstfew yearsof themortgageagreement).Schwartzand Torous(1993) provideevidence thatmortgage defaultsamong US households peakwithin16quartersoftheinitiationoftheloan(thehousehold wouldhaveenteredarrearsconsiderablyearlier).Themostimpor- tantconstituentsofconsumerloansamongSpanishhouseholdsare
“unsecuredpersonalloans”,“creditlines”and“creditcards”.The firstisanagreedloanwithanagreedrepaymentplan,typically overaperiodofuptothreeyears;thesecondisanagreedbor- rowinglimit,whichisrepayableondemand; whilecreditcards debtistypicallyrepayableoverseveralmonthswhenmakingmin- imumrepayments.Saurina(2009),classifyingloanstotheSpanish householdsectorbytheirriskiness,showsmortgagesaretheleast riskyloantype(especiallythosewithaloan-to-valueratiobelow 80percent),whilecreditcardsandcreditlinesarethemostrisky.
Thefigureshowsthatthedefaultrateonconsumerloansisconsid- erablyhigherthanonmortgages,butthatthedefaultrateforboth mortgages(solidline)andconsumerloans(dashedline)increased during2007and2008,whichplateauedbetween2009and2011, beforeagainincreasinginthefollowingyears.Fig.1bshowsasharp increaseinmortgagedisclosuresratesduringthesurveyperiod, whiletheInstituto NacionaldeEstadísticareporta several-fold increaseinindividualinsolvencyproceduressince2004.
Intherestofthepaperwewillexplorethisincreaseinhousehold default,andassesshowhouseholdarrearsdiffersbetweenhouse- holdtypes.Wewillalsoinvestigatetheextenttowhichtheoverall changeinarrearsthatcanbeattributedtochangesincreditappli- cationsand/orcreditacceptances(aswellasexploringotherfactors thatmayhavecontributedtochangesinarrears).Thiswillenable ustoassessbyhowmuchmoretheincreaseinarrearswouldhave beeniftherehadnotbeenchangeinthesupplyand/orthedemand forcredit.
3. Data
ThedatausedinthispaperistakenfromtheSurveyofHouse- holdFinances(EFF)developedbytheBankofSpain.Thisisasurvey ofSpanishhouseholdswhichiscollectedeverythreeyearsstart-
Fig.1.(a)Households’defaultrate.Note:Bothratesaredefinedastheratiobetweenthetotaldoubtfulloans(Loansinwhichsomeinstalmenthasnotbeenpaidforaperiod ofmorethan90days,andthoseexposuresinwhichtherearereasonabledoubtsastototalrepaymentunderthetermsagreed)andtotallendingtohouseholdsatSpanish economy.Source:BankofSpain.(b)Numberofforeclosures.Note:TotalnumberofforeclosuresatcourtsoffirstinstanceinSpain,2007–2012.Source:CGPJ:Estadística Judicial.
ingin2002(e.g.wehavedatafor2002,2005,2008and2011).The surveycollectsdetailedinformationonthefinancialpositionand financialdecisionsadoptedbyarepresentativesampleofSpanish householdsaswellasquestionsaboutthecomposition,income, housingandlabourmarketparticipationofhouseholdmembers.In thedesignofthesurvey,richerhouseholdswereover-represented inorder tocollectinformation onavariety ofassetswhich are mainlyheldbywealthyhouseholds.1
1Theparticipationrateisnotparticularlyhigh,asistypicalamongthesetypesof surveys.Theoverallparticipationrate,althoughdecreasingwithwealth,was47.3%
We restrict attentiontohouseholds whose head is between 30 and75 years oldand excludethose householdswithmulti- pleunrelatedadults(wherewedefinethehouseholdheadasthe mainearner).Aftermakingtheseselections,thereareover4000 householdsincludedineachyearoftheanalysis.
Household-relatedvariablesareobtainedusingseveralques- tions asked to the household respondent. We utilize variables containinginformationonthelevelofeducation,maritalstatus, houseownership, labourmarketstatus, ageand thenumberof
(2002),47.3%(2005),61.9%(2008)and50.8%(2011)(seeBoveretal.,2014,and referencescontainedtherein).
Table1
Summarystatistics.
2002 2005 2008 2011
mean sd mean sd mean sd mean sd
Income 40.6 0.72 38.3 0.82 38.6 0.95 36.7 0.97
Age 50.9 0.27 50.9 0.29 50.6 0.31 50.9 0.35
Couple(%) 77.0 0.86 73.7 0.97 72.3 1.04 71.9 1.14
No.children 0.5 0.02 0.5 0.02 0.5 0.02 0.5 0.02
male(%) 78.9 0.83 77.8 0.91 77.1 0.95 74.2 1.08
University(%) 17.3 0.78 19.3 0.89 19.0 0.98 21.6 1.10
Employed(%) 57.8 1.01 58.4 1.07 56.4 1.17 54.7 1.28
Unemployed(%) 5.0 0.47 4.9 0.50 8.0 0.64 10.9 0.79
Retiree(%) 26.4 0.85 26.8 0.92 24.7 0.93 23.6 0.97
Self-employed(%) 10.8 0.66 9.9 0.65 10.8 0.79 10.7 0.86
Homeowner(%) 83.3 0.79 84.5 0.79 83.9 0.91 83.5 1.05
Applicant(%) 54.2 1.02 59.3 1.07 59.5 1.16 60.7 1.23
Borrow(%) 52.7 1.03 57.1 1.08 56.4 1.18 55.8 1.27
Arrears(%) 9.2 0.63 8.3 0.59 9.4 0.73 11.1 0.94
No.observations 4047 4701 4836 4684
Authorsowncalculationsusing2002,2005,2008and2011wavesofSurveyofHouseholdsFinances.Householdheadage:30–75years.“Borrow”isthepercentageof householdsholdinganykindofdebt(includingcreditcardoutstandingbalancesfor2005,2008and2011)inthemomentoftheinterview.“Applicant”comprisesdebt holdersandthosethatappliedforaloanorrefusedtodosobecauseofsurerejecting(discourage)inthelasttwoyears.“Arrears”isadummyvariablerecordedasa1when thehouseholddelayedthepaymentofanyofitsdebtsinthelast12months.Fiveimputations(followingRubin,1987)andweightsareused.
childrenliving inthehouse.We alsoincludevariables contain- inginformation onhouseholdincome(adjustedbythemonthly consumerpriceindexfromInstitutoNacionaldeEstadística).
Themainfocusofthepaperwillbetoexploitquestionsondebt holding.Thefirstkeyvariableisthedummy“apply”forwhether thehouseholdapplied for a loanduring thelast two years (or wasdiscouragedfromdoingsobecausetheybelievedtheywould havebeenrejected).Thesurvey alsoallowsustoconstructthe dummy“accept”whichtakesthevalueoneiftheapplicationfor creditwasacceptedandzeroifitwasrejected(wherediscour- agedhouseholdsareincludedwiththerejectedhouseholds).Lastly, householdsreportwhethertheywereunabletopayasscheduled anyoftheirdebtpaymentsinthelastyear,forwhichweagain constructadummycalled“arrears”.
Thequestiononarrearscoversawide-rangeofdifferentout- comes,since,atoneextreme,thehouseholdmaybefacingcourt actionfortherecoveryofthedebt(orthehouseholdmaybefiling forbankruptcybecauseitisunabletopay),whiletheotherextreme, itmayhavebeenafewdayslateonasinglepaymentandotherwise haveanexemplaryrepaymentrecord.Moreover,thequestionson applicationsandacceptances,unfortunately,coversadifferenttime periodthanthequestiononarrearssincethequestiononapplica- tionsreferstothelasttwoyears,whilearrearsarereportedduring thelastyear.
Table1providessummarystatisticsforeachwaveofthesurvey forthevariablesincludedintheanalysisandforthefullsample ofhouseholds(including thosehouseholdswho donotborrow) wherethesecalculations,andtheregressions,useallfiveimpu- tations(seeRubin,1987,foradiscussionofmultipleimputation).
Thetableshowsthataverageannualrealhouseholdincome(mea- suredinthousands)felloverthesurveyperiod.Whilethefallin incomebetween2005and2011isconsistentwiththerecession duringthoseyears,thefallbetween2002and2005ismoresur- prising.Neverthelessitcanbeexplainedbynotingthechangein householdstructure:therewasanincreaseinthenumberofsin- gleadulthouseholdsfrom40.9%in2002to44.4%in2005anda reductionintheproportionofcouplehouseholdsoverthisperiod.
Thetablealsoshowsthattheproportionofhouseholdsthathave appliedforaloanoverthelasttwoyears(thevariable“applicant”) hassteadilyincreasedbetween2002and2011.Butdespitethis increase,theproportionofhouseholdscurrentlyborrowingatfirst increasedbetween2002and2005,butthenslowlyfellbetween 2005and2011(suggestingtherewasanincreaseintheproportion
ofhouseholdsthathadtheirloanrejected).Thepatternovertime ofhouseholdarrearsdisplaystheoppositepattern;atfirstitfell, andthenbetween2005and2011itsteadilyincreased.
4. Regressionresults
Animportantaimofthepaperistoinvestigatehowtherepay- ment behaviour of Spanish households has changed since the onsetof therecent financialcrisis,andtoprovidesomeinsight astowhathascausedthischange.Thisrequiresnotonlystudy- ingarrears,but alsohouseholds’applicationbehaviour,andthe lendingbehaviourofcredit institutions.We willinvestigatethe determinantsofwhetherthehouseholdappliedforaloan;whether theirloanapplicationwasaccepted;andwhethertheyrepaidthe debtsonscheduleorenteredarrears.Fundamentally,wewishto understandhowarrearschangedovertime.Consequently,weper- formseparatelogitestimationsforeachwaveofthedatawhich enablesustounderstandhowthehouseholdcreditmarketdiffers overtime,andparticularlyhowitdiffersbeforeandafterthefinan- cialcrisis.Asexplanatoryvariables,weincludeasetofhousehold characteristicsincluding:dummiesfordifferentagestrataofthe household,genderofthehead,whetherthehouseholdisheaded byacouple,dummiesforlevelofincome(separatedintosixroughly equallysizedgroups),whetherthehouseholdheadhasauniversity degree,numberofchildrenlivinginthehouse,adummyforhouse ownershipandthreedifferentdummiestoindicatewhetherthe headisself-employed,retiredorunemployed(employedhouse- holdsaretheleft-outgroup).2
4.1. Therateofarrears
Table2reports resultsforarrearsoverthelastyearforeach waveofthesurvey.Theregressionsinthecolumns2–5includeall households(where,clearly,non-borrowerswillnotreportarrears).
Theresultsforthe2002wave(thesecondcolumninTable2)show thateachagegroupissignificantlydifferentfromtheleft-outgroup (householdsbetween 70 and 74).However, theLR test forthe differentagedummiesshowsthatdifferencesbetweenthediffer- entage-groupsisnotstatisticallysignificant(seeMengandRubin,
2Ofcourse,theeffectage,timeandyear-of-birtharenotseparatelyidentifiable.
Wehavereportedthechangesbyage-groupandyearandhavenotattributedthe changesinarrearstoyear-of-birthcohorteffects.
Table2
LogitestimationresultsI.
Pr(Arrears) Pr(Arrears/Borrow)
2002 2005 2008 2011 2002 2005 2008 2011
Age30–34 0.967* 1.861*** 1.588*** 2.158*** −0.609 0.677 0.423 0.470
(0.496) (0.510) (0.468) (0.460) (0.572) (0.559) (0.498) (0.487)
Age35–39 0.821* 1.796*** 1.739*** 1.741*** −0.435 0.697 0.596 0.363
(0.482) (0.505) (0.445) (0.448) (0.564) (0.557) (0.474) (0.470)
Age40–44 1.123** 1.842*** 1.685*** 1.964*** −0.148 0.794 0.722 0.587
(0.477) (0.500) (0.437) (0.434) (0.560) (0.552) (0.465) (0.460)
Age45–49 0.957** 1.796*** 1.537*** 1.822*** −0.178 0.768 0.646 0.619
(0.479) (0.494) (0.429) (0.424) (0.563) (0.542) (0.456) (0.447)
Age50–54 1.008** 1.730*** 1.456*** 1.736*** −0.187 0.689 0.675 0.602
(0.474) (0.497) (0.430) (0.422) (0.561) (0.544) (0.456) (0.442)
Age55–59 0.840* 1.244** 1.361*** 1.514*** −0.434 0.259 0.684 0.751*
(0.466) (0.494) (0.423) (0.424) (0.543) (0.539) (0.454) (0.448)
Age60–64 0.762* 0.605 1.010*** 1.088*** 0.035 −0.221 0.539 0.311
(0.425) (0.497) (0.394) (0.397) (0.512) (0.532) (0.431) (0.425)
Age65–69 0.789*** 0.775** −0.144 0.469 0.291 0.505 −0.389 −0.040
(0.303) (0.390) (0.415) (0.401) (0.394) (0.424) (0.439) (0.429)
Couple −0.073 0.307 0.195 0.314* −0.389* −0.007 −0.146 0.064
(0.197) (0.198) (0.175) (0.166) (0.224) (0.215) (0.194) (0.182)
Income15–25 −0.695*** −0.421** 0.224 −0.153 −1.209*** −0.668*** −0.195 −0.601***
(0.233) (0.184) (0.208) (0.176) (0.291) (0.201) (0.231) (0.200)
Income25–35 −0.712*** −0.835*** 0.367* −0.374* −1.364*** −1.255*** −0.256 −0.893***
(0.262) (0.240) (0.206) (0.196) (0.278) (0.253) (0.227) (0.215)
Income35–45 −0.797*** −0.936*** −0.332 −0.701*** −1.440*** −1.321*** −0.917*** −1.303***
(0.279) (0.254) (0.313) (0.247) (0.310) (0.261) (0.331) (0.263)
Income45–57 −0.841*** −1.320*** −0.411 −1.047*** −1.439*** −1.646*** −1.153*** −1.708***
(0.289) (0.365) (0.288) (0.285) (0.328) (0.370) (0.303) (0.297)
Income>57 −1.690*** −1.520*** −0.716*** −1.041*** −2.433*** −1.881*** −1.397*** −1.649***
(0.310) (0.302) (0.261) (0.236) (0.363) (0.313) (0.275) (0.250)
Homeowner −0.763*** −0.690*** −0.345** 0.161 −1.165*** −1.012*** −0.771*** −0.360**
(0.155) (0.147) (0.156) (0.167) (0.187) (0.161) (0.169) (0.183)
Univ −0.934*** −0.818*** −0.987*** −1.044*** −0.993*** −0.752*** −0.880*** −0.998***
(0.237) (0.214) (0.202) (0.193) (0.252) (0.218) (0.207) (0.201)
Unemployed 1.048*** 0.489** 0.865*** 0.660*** 1.225*** 0.738*** 1.134*** 0.986***
(0.232) (0.246) (0.189) (0.171) (0.292) (0.285) (0.213) (0.194)
Retiree −0.297 −0.271 0.194 −0.234 −0.138 0.068 0.361 −0.081
(0.371) (0.368) (0.314) (0.304) (0.410) (0.408) (0.330) (0.316)
Self-employed −0.354 −0.189 0.539*** 0.315* −0.242 −0.131 0.584*** 0.327*
(0.240) (0.204) (0.175) (0.171) (0.260) (0.214) (0.186) (0.182)
Male −0.467** −0.235 −0.381** −0.179 −0.448** −0.095 −0.241 −0.170
(0.185) (0.185) (0.167) (0.160) (0.212) (0.205) (0.187) (0.175)
No.children 0.442*** 0.310*** 0.324*** 0.227*** 0.292*** 0.236*** 0.263*** 0.205**
(0.091) (0.080) (0.078) (0.077) (0.100) (0.088) (0.084) (0.084)
Constant −1.773*** −2.882*** −3.549*** −3.679*** 1.413** −0.622 −1.036** −0.808*
(0.462) (0.495) (0.438) (0.450) (0.562) (0.549) (0.474) (0.486)
LRtest(age) 0.2714 0.0016 0.0066 0.0002 0.6299 0.3181 0.5462 0.6322
LRtest(income) 0.0004 0.0000 0.0004 0.0010 0.0000 0.0000 0.0000 0.0000
Observations 4047 4701 4836 4685 1724 2318 2296 2181
Standarderrorsinparentheses.Columns2–5estimatealogitregressionmodelofwhetherthereportedarrearsduringthelastyearusingthewholesampleofhouseholds.
Columns6–9estimatealogitregressionmodelofwhetherthereportedarrearsduringthelastyearusingthesampleofhouseholdswhohavealoan.Referenceage:70–75.
Referenceincome:lessthan15,000realeuros.Likelihoodratio(LR)testfilesreportp-valueofthejointsignificancetestofthedummies,followingMengandRubin(1992).
*p<0.1.
**p<0.05.
***p<0.01.
1992,foradiscussionoftheLRtest).Universityeducatedhouse- holdsarealsomorelikelytorepay,whilethenumberofchildren increasestheincidenceofarrears.Householdswithamalehead arelesslikelytobeinarrearsthanhouseholdswithafemalehead whileunemployedhouseholdsaresignificantlymorelikelytobe inarrears.However,coupleisnotsignificantinthe2002wave.As couldbeexpected,highincomehouseholdsaremorelikelytorepay onschedulethanmiddleincomehouseholds,whointurnaremore likelytorepaythanlowincomehouseholds;ajointsignificancetest rejectsthattheseincome-dummiesareallequal.Owningahouse reducesarrears.
Theresultsaresimilarintheremainingthreewaves.Theeffectof auniversityeducation,ofbeingunemployedandofchildrenremain significant;however,maleisonlysignificantinthe2008wave.The effectofbeingself-employedgetslargerovertime,andissignifi- cantinthelasttwowavesofthesurvey.Similarly,thecoefficient
oncouplehaschangedsign,andinthelastwave,hasbecomesig- nificant.Theeffectoftheagedummiesremainssignificantinthe laterwaves.Theslopeeffectofage,however,isnowbiggersince thecoefficientsontheage-dummiesarelarger.Moreover,unlikein 2002,theLRtestwhichtestswhetherthecoefficientsaredifferent (atthebottomofthetable)isnowsignificantinthe2005,2008and 2011wavesofthesurvey.Theincomecoefficientsarealsosignifi- cantinthesewaves(exceptforthelowerincomegroupsinthelast twowaves);thejoint-testagainrejectsthatallthecoefficientsare thesame.
Columns6–9ofTable2looksattherepaymentbehaviourof borrowers.3Theresultsforthesub-sampleofborrowersaremostly
3GrantandPadula(2016)estimatewhattheydescribeas“thetruepropensity torepay”whichtheyarguecanbeboundedbetweentheestimatesonthewhole
Fig.2. Therateofarrearsbyincomeandage.Note:Thetwoleft-handfiguresreportthepredictedprobabilityofthehouseholdenteringarrearsduringthelastyearusing thewholesample,whilethetworight-handfiguresreportthepredictedprobabilityofthehouseholdenteringarrearsduringthelastyearwherethesampleisrestrictedto householdswhoborrow.Predictedvaluesobtainedfromlogitestimations(Table2)appliedtoareferencehousehold:headedbyaman,45–49yearsoldthatlivesincouple, houseowneremployed,houseowner,nochildrenandtotalhouseholdincomesumsupbetween15,000and25,000euros(in2010realterms)peryear.
similartotheresultsforthewholesample.Theyshowthatuni- versityeducationconsistentlyreducesarrears,butthenumberof childrenraisesarrears.Inthesampleofborrowers,ageisnotsig- nificantinanywave (the LRtestnever rejects thenullthat all age-groupsdefaultatthesamerate);thisfindingdiffersfromthe regressionsusingthewholesample.Incontrasttheeffectofincome intheregressionsisnowstronger,sincethereisalargerdiffer- encebetweenthelowestincomeandhighestincomehouseholdsin theirrepaymentbehaviour.Similarlyunemployedhouseholdsare significantlylesslikelytorepay,andtheeffectisslightlystronger.
TheresultsforageandincomearealsoshowninFig.2.Itplots howarrearschangesasincomechanges(inthetoppanel)andas agechanges(inthebottompanel),holdingothervariablesattheir medianvalue.4Thetop-leftpanelplotstherateofarrearsforsix differentincomegroups.Itshowsthatineachsurveyyear,therate ofarrearswashigherforlow-incomegroupsandlowerforhigher incomegroups.Italsoshowsthatarrearstendedtobelowerinthe 2002waveofthesurveythaninlaterwaves,withtheincreasein arrearsmostlybeinggreaterforlowerincomegroups.Thebottom- leftpanellooksatarrearsamong differentage-groups.It shows thattherateofarrearsishighestamongyoungerhouseholds,but loweramongolderhouseholds.Thefigurealsoshowsthatarrears atyoungeragesincreasedbetween2002and2005,andincreased againbetween2008and2011.Thisresultsintheage-profilebeing muchsteeperattheendofthesampleperiodthanatthebeginning.
population,andtheestimatesonthepopulationofborrowers,e.g.,betweenthe estimatesincolumns2–5andcolumns6–9.
4 Themedianvaluesaretakenbypoolingallwavesofthesurveytogether.The resultingrepresentativehouseholdisaged45–49,hasnochildren,isheadedbya coupleandtheheadisanemployedman.Totalhouseholdincomeisbetween15,000 and25,000eurosperyear(in2010realterms).
Thetworighthandpanelsshowarrearsamongborrowers.The toppanelshowshowarrearsfallswithincome.Itshowsthediffer- encesbetweenlowincomeandhighincomehouseholdsareeven sharperthantheinthepanelontheleftwhichincludesallhouse- holds.Thebottom-rightpanelofFig.2looksatage,andshowsthat thereseemstobenoclearpatterntotheage-profileofarrears.This isincontrasttothebottom-leftpanelwherethereisaclearage- profiletoarrearsfor2005–2011.However,forhouseholdsbelow 60,therateofarrearsincreasedsteadilybetweenwavesatasimilar amountforeachage-group(thepatternislessclear-cutforolder households).
4.2. Applicationsandacceptances
Table2 showedthere are somedifferences betweenarrears amongborrowersandarrearsinthewholepopulation.Thissug- geststhatwhetheracreditapplicationismadeandacceptedmight havearoleinexplainingarrearsamongthewholepopulationof Spanishhouseholds. Furthermore,changes in arrears over time maybepartlyexplainedbychangesinthepoolofborrowers.The firstfourcolumnsofTable3reportthedeterminantsofloanappli- cants,wheretheleft-hand-sidevariableisadummyforwhether thehouseholdreportsthattheyappliedforaloanduringthelast twoyears.Forthemostpart,theresultsshowtherehavebeenfew changesintheeffectofthesevariablesovertime.Theresultsshow thatcoupledhouseholdsaresignificantlymorelikelytoapplyfor aloanthansinglehouseholds;auniversityeducationreducesthe demandforloans;home-ownersaremorelikelytoapply;while havingchildrenincreasesthedemandforloans.Theseresultshelp toexplaintherateofarrearsamonguniversitygraduates:thefirst fourcolumnsofTable2showedgraduatesarelesslikelytobein arrears,whileherewehaveshownthatthesehouseholdsareless
Table3
LogitestimationresultsII.
Pr(Application) Pr(Accept/Apply)
2002 2005 2008 2011 2002 2005 2008 2011
Age30–34 2.339*** 1.959*** 2.073*** 2.659*** 1.376 1.730** 1.058 1.647***
(0.234) (0.212) (0.222) (0.259) (1.182) (0.830) (0.849) (0.576)
Age35–39 2.019*** 1.711*** 2.203*** 2.141*** 1.349 1.239 1.385 1.269**
(0.222) (0.202) (0.209) (0.209) (1.168) (0.796) (0.846) (0.523)
Age40–44 1.693*** 1.379*** 1.598*** 1.828*** 1.671 2.093** 1.691* 1.894***
(0.218) (0.194) (0.191) (0.193) (1.193) (0.883) (0.867) (0.550)
Age45–49 1.484*** 1.397*** 1.528*** 1.611*** 0.889 1.612** 1.746** 1.579***
(0.208) (0.179) (0.179) (0.172) (1.117) (0.807) (0.854) (0.508)
Age50–54 1.513*** 1.284*** 1.220*** 1.381*** 1.437 1.381* 1.360* 2.024***
(0.202) (0.179) (0.171) (0.160) (1.147) (0.767) (0.804) (0.547)
Age55–59 1.500*** 1.068*** 0.957*** 1.021*** 1.812* 2.365*** 1.957** 0.982**
(0.194) (0.166) (0.166) (0.158) (1.090) (0.918) (0.859) (0.480)
Age60–64 0.914*** 0.699*** 0.648*** 0.706*** 1.634* 1.608** 1.245 1.298***
(0.180) (0.154) (0.146) (0.138) (0.989) (0.664) (0.759) (0.437)
Age65–69 0.574*** 0.444*** 0.125 0.401*** 0.870* 0.506 0.962** 0.583*
(0.148) (0.129) (0.127) (0.123) (0.470) (0.352) (0.474) (0.336)
Couple 0.361*** 0.426*** 0.438*** 0.184** −0.413 1.084*** 0.667** 0.707***
(0.104) (0.096) (0.090) (0.090) (0.472) (0.349) (0.319) (0.252)
Income15–25 0.132 0.197* 0.277** 0.095 0.817 0.324 1.083*** 0.919***
(0.146) (0.116) (0.122) (0.123) (0.505) (0.304) (0.300) (0.242)
Income25–35 0.280* 0.407*** 0.671*** 0.191 1.200* 1.018*** 1.780*** 1.612***
(0.151) (0.120) (0.122) (0.123) (0.683) (0.393) (0.405) (0.317)
Income35–45 0.344* 0.376*** 0.425*** 0.200 1.875** 1.424** 1.836*** 2.812***
(0.177) (0.139) (0.138) (0.140) (0.934) (0.672) (0.507) (0.693)
Income45–57 0.229 0.276 0.748*** 0.480*** 0.963 2.022* 2.336*** 2.852***
(0.172) (0.168) (0.145) (0.147) (0.938) (1.089) (0.640) (0.675)
Income>57 0.463*** 0.331*** 0.692*** 0.334*** 2.002*** 3.170*** 3.967*** 3.261***
(0.150) (0.120) (0.128) (0.127) (0.760) (1.118) (1.061) (0.528)
Homeowner 0.263** 0.222** 0.151 .0218** 1.629*** 0.837*** 1.994*** 1.492***
(0.104) (0.098) (0.102) (0.104) (0.340) (0.285) (0.253) (0.206)
Univ −0.197** −0.291*** −0.325*** −0.285*** 0.108 0.206 0.546 0.066
(0.089) (0.081) (0.080) (0.081) (0.507) (0.389) (0.439) (0.288)
Unemployed 0.216 0.113 −0.013 0.040 −0.347 −1.415*** −1.290*** −0.932***
(0.180) (0.177) (0.140) (0.130) (0.670) (0.414) (0.328) (0.276)
Retiree −0.158 −0.491*** −0.139 −0.171 −0.853 −0.858 −0.091 −0.351
(0.150) (0.134) (0.134) (0.126) (0.989) (0.684) (0.742) (0.414)
Self-employed −0.169 −0.088 0.021 0.095 −0.281 −0.203 −0.372 −0.471
(0.105) (0.099) (0.099) (0.101) (0.677) (0.529) (0.433) (0.337)
Male −0.167 −0.071 −0.156* 0.091 0.837* −0.140 −0.275 −0.081
(0.102) (0.095) (0.091) (0.088) (0.453) (0.360) (0.327) (0.260)
No.children 0.328*** 0.297*** 0.250*** 0.284*** 0.119 0.052 0.326* 0.040
(0.059) (0.056) (0.057) (0.060) (0.266) (0.180) (0.175) (0.140)
Constant −2.133 −1.518 −1.741 −1.600 0.274 0.399 −1.045 −1.175
(0.230) (0.198) (0.196) (0.192) (1.064) (0.751) (0.812) (0.499)
LRtest(age) 0.0000 0.0000 0.0000 0.0000 0.4628 0.0658 0.2827 0.0776
LRtest(income) 0.0699 0.0476 0.0004 0.0575 0.1520 0.0007 0.0000 0.0000
Observations 4047 4701 4836 4685 1773 2405 2399 2349
Standarderrorsinparentheses.Referenceage:70–75.Referenceincome:lessthan15,000realeuros.Likelihoodratio(LR)testfilesreportp-valueofthejointsignificance testofthedummies,followingMengandRubin(1992).
*p<0.1.
**p<0.05.
***p<0.01.
likelytowantaloan.Similarly,childrenraisethedemandforloans and increasetherateof arrears.However, couplesdonot have higherarrearseventhoughtheyhavehighercreditdemand.The observedeffectof maleonapplicationsis consistentwiththeir arrearsin Table2since thetwo waveswhere maleshadlower arrearsarealsothetwowavesinwhichtheyarelesslikelytoapply foraloan.Theeffectofageisstronglysignificant;youngerage- groupsaremorelikelytoapplyforcredit(theLRtestreportedatthe bottomofthetableshowsthatthedifferencesacrossage-groups arestatisticallysignificant).Theresultsforunemploymentarenot significant.Thisshowsthehighrateofarrearswefoundearlieris notduetotheirhighdemandforloanssinceunemployedhouse- holdsarenomorelikelytoapplyforaloanthanothertypesof household.
ThelastfourcolumnsinTable3lookatwhetherthecreditappli- cationwasacceptedorrejectedbythelender(e.g.whetherthe
applicantis creditconstrained)ineachwave ofthesurvey.The regressionrunsaLogitregressionmodelwheretheleft-handside variableisadummyvariableforwhethertheloanisaccepted,and theregressionisrunusingthesampleofapplicanthouseholds.The estimatedcoefficientsontheage-dummiessuggestahumpshape tocreditconstraints:middle-agedhouseholdsaremorelikelyto beacceptedthaneithertheyoungestortheoldesthouseholds(the left-out groupisthe70–74group,andthelargestcoefficientis alwaysforhouseholdsintheirfifties).Thisisslightlysurprising sincewefoundthattheoldesthouseholdshavethelowestrate of arrears. Coupleis positive and significantin allbut thefirst wave, whilethenumber ofchildren issignificantonlyin 2008, eventhoughTable2suggestschildrenincreasearrears.Similarly universityeducatedarejustaslikelytoberefusedcreditasother householdsdespitetheirlowerarrears.
Thetablesuggeststhattherearesomedifferencesacrossincome groupsintheacceptancerateonloans.Middleandhighincome householdsseemtobemorelikelytohavetheirapplicationfor creditacceptedthanlowincomehouseholds(althoughtheLRtest doesnotrejectthenullinthe2002wave).Thisisconsistentwith thefactourresultsshowedthesehouseholdsaretheleastlikely toenterarrears.Similarly,exceptin2002,unemployedhouseholds aremorelikelytoberefusedcredit;Table2showsthesehouseholds aresignificantlymorelikelytobeinarrears.
Fig.3plotsthepredictionofthelevelofapplicationsandaccep- tances for a representative household through the four waves consideredin this study (taken,as before, at the median).We considertwoexplanatoryvariables:ageand income.Thefigure suggeststhatyoungerhouseholdsaremorelikelytoapplyforcredit thanolderhouseholds.Thefigurealsosuggeststhatapplications among youngerhouseholds (below 60)are noticeablylower in 2002thaninlater years,andthatapplicationsfromhouseholds over50peakedin2005,beforefallingbackinthelasttwowaves.
Wefoundthatdifferencesbetweenage-groupsintheirrejection ratesbylenderswasnotsignificant,butthefiguresuggeststhere maybeaslightincreaseinrejectionattheoldestages.Thefigure moreclearlysuggests,however,therewasadeclineinacceptance ratesinthe2011wave,particularlyconcentratedamongtheoldest households.Thefinalpictureforthelastwaveseemsparadoxical:
thosehouseholds(theoldesthouseholds)withthebestpropensity torepayinTable2aretheoneswhobecamemorerationedinthe loanmarket.
Whenwelookattheestimateofapplicantsfordifferentincome groups,we observethatin 2002therewere significantlyfewer householdsapplyingforloansateveryincomelevel,withappli- cationratescontinuingtodriftupwardsforhigherincomegroups in2008beforefallingslightlyin2011.Thefigurealsoshowsthat acceptancerateswerehigherforhigherincomegroups.Moreover, acceptanceratesfelldramaticallyforlowerincomehouseholdsin the2008and2011waves.
5. Explainingthechangeinarrears
Theregression resultsinTable 2shows which factorsaffect arrears in each year.While theresults for unemployment and incomeseemplausibleandintuitive,otherresults,suchastheeffect ofmalehouseholds,aresurprising.However,theobservedpattern ofarrearsmightbebecause,forinstance,low incomeorunem- ployedhouseholdsdonothavecredit,andhencecannotthusenter arrears.Theresultsalsoshowthattheeffectofsomeofthevariables seemstohavechangedoverthesampleperiod.Earlier,inTable1, wefoundthat therateofarrearsincreasedduringthefinancial crisis,andwealsofoundthattherewasanincreaseinthepro- portionofhouseholdsthatwerecreditconstrained.Wewouldlike tounderstandhowchangesinborrowerandinlenderbehaviour hascontributedtothechangeinarrearsduringtheyearsbefore andafterthecrisis.Recallthatforahouseholdtoenterarrearsit mustfirstapplyforaloan;itmustthenhavetheloanapplication accepted;andthenitmustfailtorepaytheloanwhenrequired todoso.Achangeinthearrearsbehaviourofahouseholdwith somegivencharacteristics(wewilldenotethesetofcharacteris- ticsasX)couldbetheconsequenceof achangeinanyofthese threethings.Itwouldbeusefultodisentanglethesethreedifferent possibleexplanationsfortheresultsweobserve.Figs.2and3pro- videdsomeindicationoftheeffectofageandincomeonarrears;
inthissectionwewillexploretheroleofage,income,andother characteristicsinexplainingarrearsinmoredetail.
5.1. Designofthedecompositionexercise
LetDidenoteadummyforwhetherhouseholdirepaysitsdebts onschedule(ittakesthevalueoneifthehouseholdisinarrears andzerootherwise).Similarly,letAidenoteadummyvariablethat takesthevalueoneofthehouseholdhasappliedforaloan(and zerootherwise),andletCibeadummythattakesthevalueoneif thehousehold’sapplicationforcreditwasaccepted(andzerooth- erwise).Ineachwavet(wherewehaveseparateestimatesin2002, 2005,2008and2011)wecanestimatetheprobabilityofarrearsof householdi,givencharacteristicsXiasPrt(Di=1|Xi).Andwecan comparehowthearrearsbehaviourofhouseholdsdiffersindif- ferentwaves.Note,however,wecanonlyobserveahouseholdin arrearsifitborrows,thatisifAi=1andCi=1,hencewecanmake thefollowingdecomposition
Prt(Di=1|Xi)=Prt(Di=1|Ai=1,Ci=1,Xi)
·Prt(Ci=1|Ai=1,Xi)·Prt(Ai=1|Xi)
(1)
whereeachoftheprobabilitieshasalreadybeenestimatedand isreportedinTables2and 3.Usingthecoefficientsreportedin Tables2and3andusingEq.(1),wecancomputetheprobabilityof arrearsforeachhouseholdinthesample,giventheircharacteris- tics.Wecanthencalculatethearrearsrateinthewholepopulation inwavetbytakingtheweightedaverageofeachindividualhouse- hold probability of arrears in that wave. Consequently we can investigatehowthearrearsratehaschangedovertime.
Offundamentalinterest,however,istounderstandwhathas causedthechangeinarrearsratesovertime.Firstnotethatthe arrearsratebetweentwoperiodscanchangebecausethedistri- butionof underlyinghouseholdcharacteristics haschanged.To calculatehow changes in characteristicsaffect arrears between two waveswe cantakethehousehold characteristicsfor wave t+1butusetheestimatedprobabilityfunctionforwavet(where, slightlyabusingnotation,wewritethisasPrt(D|Xt+1)).Arrearscan alsochangebecausethecompositionofborrowershaschanged.
UsingEq.(1),wecandecomposetheoverallchangeinthearrears ratebetweentwoperiodsforahouseholdwithcharacteristicsX,to changesinthearrearsbehaviourofborrowers,tochangesinaccep- tancebehaviouroflenders,andtochangesinapplicationbehaviour ofhouseholdsbetweenthosewaves.Eq.(1)haswrittentheprob- ability of arrears in wave t as Prt(D|A=1, C=1, Xt)·Prt(C|A=1, Xt)·Prt(A|Xt).Thisformulationusestheestimatesforapplication, acceptanceandborrowerbehaviour(orarrearsbehaviourofbor- rowers)forwavetthathavealreadybeenestimated.Ameasure oftheeffectofchangesinapplicationbehaviourofhouseholdscan beobtainedbyusingtheperiodt+1estimatedapplicationregres- sionbutwiththeperiodt characteristics.Thatis,toinvestigate howchangesinapplicationsaffectstheoveralllevelofarrearswe cancalculatePrt(D|A=1,C=1,Xt)·Prt(C|A=1,Xt)·Prt+1(A|Xt)andsee howtheestimatedarrearsratechangeswhenPrt(A|Xt)isreplaced byPrt+1(A|Xt).Similarly,wecaninvestigatetheeffectofchangesin lenders’acceptancebehaviourandoftherepaymentbehaviourof borrowersby,inturn,usingthenextperiodestimateforlenders’
acceptancebehaviourPrt+1(C|A=1,Xt),andarrearsamongborrow- ersPrt+1(D|A=1,C=1,Xt).Resultsfromthisthoughtexperimentare reportedinthenextsection.
5.2. Resultsofthedecompositionexercise 5.2.1. Allsample
Thetop rowofTable4 reportsthepredictedarrears ratein each wave of thedata(compiled asthe weightedsumof each household’s predicted arrears rate using the logit estimates in Tables2and3).Thetableshowsthatpredictedarrearsfellfrom 9.3%to8.3%between2002and2005,beforeincreasingto9.5%in
