regressivity in public natural hazard insurance: a quantitative analysis … · 2018. 7. 10. · 1...
TRANSCRIPT
1
1
RegressivityinPublicNaturalHazardInsurance:AQuantitativeAnalysisoftheNewZealandCaseSallyOwen(MotuEconomicandPublicPolicyResearch)IlanNoy(VictoriaUniversityofWellington)
Abstract:Naturalhazardinsuranceisalmostalwaysprovidedbythepublicsector(directly,or
indirectlythroughpublic-privatepartnerships).Giventhisdominantroleofthepublicsectorin
hazardinsurance,andtheimportanceofshocksineconomicdynamics,itissurprisingthatequity
issueshavenotfacedmorescrutinywithrespecttothedesignofhazardinsurance.Thenatureof
theregressivitywequantifyhasnotbeenpreviouslyidentified.Weprovideadetailedquantification
ofthedegreeofregressivityoftheNewZealandearthquakeinsuranceprogram–asystemthatwas
designedwithanegalitarianpurpose.Wemeasurethisregressivityasitmanifestedinthehalfa
millioninsuranceclaimsthatresultedfromtheCanterburyearthquakesof2011.Wesuggesthow
thisregressivitycanberemediedwithmodificationstotheprograms’structure,andpointtohow
otherinsuranceschemesinternationallyarelikelytoalsoberegressive.
WethankQuakeCoreandtheResilienceNationalScienceChallengeforsupportingthiswork.Noy’sresearchispartiallyfundedbytheEarthquakeCommission(EQC),whichisanalysedinthiswork.
2
2
1.Introduction
Privatenaturalhazardinsurancemarketsseldomsucceedinprovidingwidespreadcoverage
(KunreutherandPauly,2009;Noy,Cuong,andKusuma,2017).1Therearemultipleexamples
offailedattemptstoprovidefinancialnaturalhazardrisktransfer(insurance)through
privatemarkets,floodandearthquakeinsuranceintheUnitedStatesbeingtwoprominent
cases.Infact,nocountryhasaprivatemarketforfloodinsurancethatprovidesaffordable
andaccessiblecoverforhigh-riskhouseholdswithoutsomeformofgovernment
involvement(ABI2011).
Agoodinsurancesystemincentivizesriskreductionandenablestheinsuredpartytotake
onbeneficialandprofitablebusinessrisksandinvestexante;expost,itallowstheinsured
partytoevadeatleastsomeofthefinancialloss,avoiddestitution,andrecovermore
quicklyandmorefully.O’Neill&O’Neill(2012)furtherarguethatinsuranceshould
guaranteethesecurityofrequiredbasicgoods,accordingtosocialjusticecriteria,
independentlyoftherisksinvolvedandtherisk-takingbyindividuals—housingbeinga
primeexamplefora‘basicgood’.
Fromacommunitarianratherthananindividualistperspective,theinabilityofsome
householdstorebuildtheirpre-disasterlivesinflictsadditionalharmontherestofthe
community.But,evenfromanindividualistperspective,ifthereisnoprovisionofnatural
hazardinsurancebytheprivatemarket,governmentsfindapolitical-electoralrationalefor
interventiontofacilitateinsurancecoverageforall.Governmentscanchoosetopursuethis
aimbyeitherinsuringdirectlyorsubsidizingtheprivateinsurancesector,andhavechosen
1Naturalhazardinsuranceisalsoknownascatastropheinsurance,disasterinsurance,ornaturaldisasterinsurance,dependingonthecontext.Weusenaturalhazardinsuranceforspecificity.
3
3
todosoinmanycountries.2Giventhecomplexityofinsuringextremerisks,private-sector
insurersandgovernmentstendtocooperateinpublic-private-partnership(PPP)schemes.3
Mostdisastereconomistsalsoarguethatinsurancepremiumsshouldberiskbased(e.g.,
Bin,Bishop&Kousky,2010andKunreuther,2015).Risk-basedinsurancepremiumssignalto
residentsandbusinessesthehazardstheyfaceandenableinsurerstolowerpremiumsfor
propertiesforwhichstepshavebeentakentoreducerisk.Risk-basedpremiums,however,
doraiseequityconcerns,andthereissomerecognitionthatafullyrisk-sensitiveinsurance
regimemaybesociallyorpoliticallyunacceptableifitimposesveryhighcostsonsome
groups(Houstonetal.,2011).4
Giventhedominantroleofthepublicsectorintheprovisionofnaturalhazardinsurance,
andtheevidentconcernworldwideaboutgrowingincomeandwealthinequality,itis
surprisingthatequityissueshavenotfacedmorescrutinywithrespecttopubliclyprovided
naturalhazardinsurance.Forexample,thisaspectoftherecentlylaunchedUKgovernment
FloodReprogramhasreceivedalmostnoattention,inspiteofthepotentiallyvery
regressivestructureofthatprogram.
Inthispaper,weprovide—possiblyforthefirsttime—adetailedquantificationofthe
degreeofregressivityofapublicnaturalhazardinsuranceschemeandthechannelthrough
whichitisgenerated.WechosetofocusontheNewZealand(NZ)earthquakeinsurance
schemeforfourmainreasons:(1)Theavailabilityofclaimsrecordsafteralargeevent(the
2Belgium,France,Japan,NewZealand,Spain,Switzerland,Turkey,UK,andtheUSAtonameonlyafew.3Paudel(2012)providesninerecommendationsfordesigningsuchPPPschemes.Hisrecommendationsinclude:mandatoryparticipation;adequateenforcementtoensurecompliance;publicresponsibilityfortheextremerisk(thecatastrophicend)oftheinsuredrisk,privatesectoradministeringofpolicies;publicprovisionofsubsidiesthrough,forexample,taxexemptions;publicinvestmentinriskmitigation;a(publiclyprovided)detailedassessmentandmappingofrisk;andtheprovisionoffinancialincentivesforpolicyholderstotakeriskmitigationmeasures.4Kunreuther(2015)suggeststhattoaddressissuesofequityandfairness,homeownerswhocannotaffordinsurancecouldbegivenvoucherstiedtoloansforinvestinginlossreductionmeasures,butthiskindofvoucherprogramisyettobeimplementedanywhere.
4
4
seriesofCanterburyearthquakesin2010–2011thatledtoaverylargenumberofclaims);
(2)Thewell-establishedsuccessofthisprograminachievingwide-spreadcoverage–the
Canterburyearthquakeswerethemostinsuredlarge-scaleseriesofeventsever5;(3)The
egalitarianaimofthisscheme(alldwellingspayidenticalpremiumsandreceivethesame
amountofcover);and(4)Thecomparativelyegalitariandistributionalpolicyofpastand
presentNZgovernments.
Inspiteofboth(3)and(4),wefindthatthecurrentNZschemeisstronglyregressive,and
wereportontheexactextentofthisregressivityasitmanifestedinthehalfamillion
insuranceclaimsthatresultedfromtheCanterburyearthquakes.
2.RegressivityandNaturalhazardinsurance
Fairnesshaslongbeendiscussedintheevaluationoftaxation(e.g.,Simons,1938;Goode,
1980).Economistshavegenerallyrecognisedtwoprincipalconceptsoffairtaxation:benefit,
andtheabilitytopay.Fromabenefitperspective,taxesshouldbeleviedsuchthatbenefits
receivedbythepayersareproportionaltotheirtaxburden.Underthisconceptoffairness,
thereislittlescopeforredistribution.Anexampleismotorfuelexcisetax,whichisusedto
payforroadwayconstructionandmaintenance.Theabilitytopayprinciplefocusesonlyon
thecostside,whileignoringthedistributionofbenefits.Itviewstaxationasimposingacost
thatshouldbeallocatedinsuchawaythatittaxesthosewithequalabilitytopayequally
5ThethreehighestcostearthquakesintheCanterburysequenceareamongthetop10costliestearthquakesfor1980–2015(byinsuredlosses).Relativetodamages,theseeventswereatleasttwiceaswellinsuredasanyoftheothersonthelist(MunichRe,2016).
5
5
(horizontalequity),andimposesagreaterburdenonthosewithgreaterabilitytopay
(verticalequity).6
Theconceptofregressivitywasoriginallyappliedtoincometaxsystems.Asdefinedin
Kakwani(1977),ifT(x)isthetaxpaidbyanindividualwithincomex,thetaxsystemis
proportionalwhentheelasticityofTwithrespecttoxisequaltooneforallx,thetax
systemisprogressivewhentheelasticityexceedsone,andregressivewhentheelasticityis
lessthanone.Thisisequivalenttosayingthatataxsystemisprogressive,proportional,and
regressivewhenthemarginaltaxrateisgreater,equal,andlessthantheaveragetaxrate,
respectively.7
MusgraveandThin(1948)createdamoreuniversalmeasureofprogressivitybycomparing
theinequalityofincomedistributionspre-taxandpost-tax.Aprogressivetaxsystemwill
thencreateadecreaseinincomeinequality,whileregressivetaxrateswillbereflectedby
increasesinincomeinequality.TheauthorswereabletoconcludethatiftheGiniindexis
usedtomeasureinequality,theratiooftheGiniindicesofthebefore-taxandafter-tax
incomesprovidesasinglemeasureoftaxprogressivity.8
Previousworkhaslookedattheregressivityofexplicittaxschemes;examplesinclude“sin”
taxes9andcarbontaxes.10Thistypeofmeasurementofprogressivityhasalsobeenusedto
studyimplicittaxesandsubsidies.Forexample,DavisandKnittel(2016)investigatewhether
6Abilitytopayisgenerallymeasuredbyannualincome.Thereisnoagreeduponstandardtodeterminewhatverticaldifferentiationintaxliabilitiesismostfair(JointCommitteeonTaxation,2015).7Slitor(1948)usedthistypeofdefinitiontoproposeameasureofprogression:dt(x)/dx=[m(x)-t(X)]/x;wheret(x)istheaveragetaxrateattheincomelevelxandm(x)isthemarginaltaxrateatthatlevelofincome.8Kakwani(1977),however,pointedoutthatbydoublingthetaxratesatallincomelevels,thetaxprogressivitywouldmechanicallyincreasewhenusingtheMusgrave-Thinratio.Thisisproblematicbecauseprogressivity(orregressivity)issupposedtomeasurethedeviationofataxsystemfromproportionality.KakwaniproposestousetheGiniindexonlytomeasurethedistributionaleffectsoftaxation,andpresentsanalternativemeasureusingtheLorenzCurvetocreateameasurethataccountsforboththedistributionalandproportionalelementsofataxsystem.9Poterba(1991a),Lyon&Schwab(1991),Bentoetal.(2012),andBorren&Sutton(1992).10Wieretal(2005),andPoterba(1991b).
6
6
fuelefficiencystandardsareregressive,andJohnson(2006)looksatpublicspendingon
highereducation.
Whilethepotentialdistributionalaspectofpublicnaturalhazardinsurancehasbeennoted
intheliterature,thepracticalimplicationsintermsofbenefits(expectedpaymentofclaims)
relativetocosts(premiumspaid)havenotpreviouslybeenquantified.
Ben-ShaharandLogue(2015)examineFlorida’sstate-ownedCitizens'PropertyInsurance
Corporation(“Citizens”)anditscoverageforwind-damage(hurricanes).Theirworkrelieson
Citizens’owncalculationsoftheactualriskittakesonwhenprovidinginsurance,andonthe
premiumsitcharges.Theyfindthatthehighersubsidiesareprovidedforareasincurring
morerisk,andthattheseareasaregenerally(statistically)wealthier,mostlikelybecause
theyarelocatedclosertothecoast.Asecondpaperthatinvestigatesasimilarprogram,by
Bin,Bishop,andKousky(2012),studiestheU.S.NationalFloodInsuranceProgram(NFIP).It
focusesonthedeparturefromtheproportionalitymeasureofprogressivity.Aprogressive
departurefromproportionalityrequiresthateverypremiumdecilebenolargerthanthe
correspondingincomedecile.Theauthorsshowthatthedeparture-from-proportionality
indexisnotsignificantlydifferentfromzeroforpremiums,implyingtheyareproportionalto
income.Theyconsiderpremiumsandpaymentsseparately,andnotethatneithereffectis
extremeandthattheseeffectsaresmoothedovertime.
Howard(2016)examinesthenetsocialbenefitsoftheNFIP,usingdataonpremiums,
claims,policies,andgrantsfrom1996–2010.Inhismorecomprehensiveanalysis(thanBin
etal.,2012)hefindsthatthissystemis“moderatelyregressive.”Accordingtothesethree
analysesofthenaturalhazardinsuranceintheU.S.,itisplausiblethatthedistributional
aspectarisessolelyfromthedifferentiatedexposureofwealthierhouseholds,duetotheir
7
7
locationonthecoastsandthefocusonhurricanedamage,asmanyoftheNFIPclaimsarise
fromstorm-generatedwavesurges.Inmanycases,andinmostcountries,however,itis
generallythepoorerhouseholdsthataremoreexposed(KarimandNoy,2016).
Surminski(2016)andDavey(2015)discussvariousdistributionalaspectsofFloodRe,the
UK’snewfloodreinsuranceprogrammethatisdesignedtomaintainaffordablypricedflood
insurance.BothpapersidentifyseveralwaysinwhichFloodRemayhavedistributional
consequences,butdonotquantifythem.O’Neill&O’Neill(2012)discussfloodinsurancein
theUK(beforethelaunchofFloodRe)andargueforasolidarity-basedschemeonfairness
grounds,acknowledgingthatriskbasedpremiumswouldunfairlypenalisehouseholdswho
couldnotreasonablybefoundtohavechosentoliveinfloodproneareasoftheirownwill.
Theynotethat“choiceisvoluntaryonlyifitcanbereasonablyforeseenandtheagentshave
realandacceptablealternativestoit.”Thisstatementraisesinterestingequityquestions,as
itislikelythatthosehouseholdsfacinghigherrisksarewealthier,inwhichcasethefairness
principletheyadvocatemayleadtotheinsurancetransferringriskfromrichtopoor
households,andtherebythepoorsubsidisingtherich.11
Here,wequantifythedistributionaleffectofpublicnaturalhazardinsuranceinaNZcase,
andidentifytheunfortunateregressivityofoneofthetheoreticallymostequitablydesigned
publicnaturalhazardinsurancesystemsglobally.Itiseasytoarguethatmanyoftheother
publicnaturalhazardinsurancesystemsestablishedglobally(seeTable1)arelikelytobeat
leastasregressive.Thenextsectiondescribesthedataweuseforourquantitativeanalysis.
11Thequestionoffairnessbecomesevenmorecomplicatedifthehazardbeinginsuredisclimate-relatedanditsfrequencyorintensityischangingbecauseofclimatechange.Inthiscase,insurancesystemsprovideacertaindegreeofcollectiveprotectionwithsomedistributionalconsequences,buttheinsuredeventwasoutcomeofactionsforwhichthereisanuneven,sharedresponsibility.Forflooding,itistheoutcomeofactionsforwhichthosewhoaremostvulnerableoftenareatleasthypotheticallytheleastresponsible.Thereisadoubleinjusticeifthosewithlowincomeswhoareleastresponsibleforanthropogenicglobalwarmingarefacedwiththelargestburdensofdamages(Thumimetal.,2011,Lindleyetal.,2011).
8
8
Section3explainsthemethodology,inSection4weexplainourresults,andSection5
concludes.
3.Data
InNZ,publicnaturalhazardinsuranceisprovidedtoresidentialhomeownersbythe
EarthquakeCommission(EQC).Inordertoaccessthisinsurance,homeownersneedonly
haveprivatefireinsurance(whichover90%do).ThepublicEQCpremiumsarecollected
throughprivatefireinsurers,andareidenticalforbuildingcoverofalldwellingsinsuredfor
morethanNZ$100,000(asalmostallare).
TofullyappreciatetheroleEQCplays,wemustconsiderhowitdeveloped.In1906San
Franciscowashitbyadevastatingearthquake,hittingGermaninsurersespeciallyhard.In
thewakeofthisevent,muchoftheglobalinsuranceindustryrespondedbyexcluding
earthquakeandrelatedfiredamagefromtheirpolicies(Henderson,2010).In1931,NZwas
struckbyanearthquakecenteredonNapier.Atthistime,privateearthquakeinsurancewas
availableinNZ,butwasvoluntary(NZNSEE,1993).Then,in1937,withWorldWarII
looming,wardamagewasexcludedfrommostprivateinsurancecontracts.Again,in1942,
NZwashitbyanotherdamagingearthquakenotfarfromthecapital,andin1944,the
EarthquakeandWarDamageCommissionwasestablished;itisthehistoricalprecursorto
theEQC.12
12Partofthemotivationforthiswastheslowratesofrepairfollowingthe1931and1942events(NZTreasury2015).IntheyearsthatfollowedNZwashitbyanumberofdisastersincludinganearthquaketriggeredtsunamiin1944,anearthquakein1968andamajorlandslipin1979.TheEarthquakeCommissionActof1993redesignedthescheme.Amajordevelopmentwasthephase-outofcommercialproperties.ItalsoamalgamatedtheWarDamageandEarthquakeFundandtheDisasterandLandslipFundastheNaturalDisasterFund.ThisisthefundEQCdrawsfromtopayoutonclaims.
9
9
TheEQCcurrentlyprovidesthreeformsofinsurancecovertoresidentialpropertyowners:
structure,land,andcontents.Theseareinsuredtoreplacementvalueagainstnatural
hazardssuchasearthquake/tsunami,volcaniceruption,andlandslip.Since1980,outof
543,531claims,94.9%havebeenrelatedtoearthquakes.Thecoverforresidentialbuildings
providesthefirstNZ$100,000ofreplacementvalueforeachinsureddwelling.13Ifthelossis
greater,theprivateinsurerisresponsibleforanyover-caprepaircosts.Aswewillfocusthe
analysisbelowexclusivelyonstructuraldamageclaims(andnotoncontentsorland),we
onlydescribethisaspectofEQCpolicy.14ForeachNZ$100ofpropertyinsuredbytheEQC,
alevyischargedbytheprivateinsurerandsenttoEQC.Thesepremiumshadbeensetat
0.0005%oftheamountinsuredin1993,andweretripledaftertheCanterburyearthquakes
of2010–11to0.0015%.Morethan99%ofhomesarevaluedatmorethanNZ$100,000,so
thatineffectallpaythesameamounttoEQCforthebuildinginsuranceitprovides(NZ$150
perannum).15
InordertoquantifytheregressivityoftheEQCbuildingcover,werequiredameasureofthe
benefitdeliveredbytheEQCscheme.Thereisvalueinthecertaintyofknowingoneis
insuredregardlessofwhetherthatinsuranceiseverrequired,andsomevalueinthe
indirectfacilitationoftheover-capprivatenaturalhazardinsurancemarket.Ouranalysis
assumesthatthisvalueisequalforallparticipantsintheschemeandwethereforeignoreit.
Forthepurposesofthisanalysis,thebenefitisdefinedasactualpayouttotheownerfor
disasterdamage.ThisisaplausiblemeasuresincevirtuallyallhomesinChristchurchwere
damagedintheCanterburyearthquakesequence,andifanything,homeownersofweaker
13Amulti-unitresidentialbuildingcoveredforfiredamagewouldbeinsuredthroughEQCforthefirstNZ$100,000timesthenumberofdwellingsinthebuilding.14Thedetailsaboutlandcover,uniquelycoveredinNZ,aresignificantlymorecomplicated.15RecallthebuildingcoverfromEQCiscappedatNZ$100,000perdwelling.
10
10
socioeconomicbackgroundswerelocatedclosertotheepicentreoftheearthquake.Thus,
theredistributivequestionis:HavewealthierhomeownersreceivedmoremoneyfromEQC
forbuildingrepairthantheirlesswell-offcounterparts.Toanswerthisquestion,we
combinedtwodatasets:EQCinsuranceclaimdatafromtheCanterburyEarthquakeseriesof
2010–2011,16andcensusdatafromStatisticsNZ.Table2reportsthesummarystatisticsof
thedwelling-leveldatasetweusedinouranalysis.
Table2:SummaryStatistics-PropertyleveldatafortheCanterburyEQSeriesDataset (1) (2) (3) (4)VARIABLES mean sd min max TotalDwellingPayout 45,774 58,207 0 358,381DwellingPayout/#ofClaims 26,254 31,503 0 344,101AssessedBldgRepairCosts 63,370 139,215 0 1.498e+07#claimsmadeonthataddress 1.538 0.734 1 7#dwellingsclaimedforonthataddress 1.066 1.014 1 102BuildingValue10 319,991 240,102 43,844 2.091e+07DwellingadjustedBuildingValue2010 303,682 150,233 1,120 1.752e+07Note:Thistablecontainssummarystatisticsforthe94,687propertiesforwhichwehaveinsuranceclaimdatarelatingtotheCanterburyEarthquakeSeries.Therewerefiveearthquakesassociatedwithasignificantnumberofpayments(04/09/2010,26/12/2010,22/02/2011,13/06/2011,23/12/2011).Mostareassociatedwiththefirstandthirdevents.7.2%ofdwellingsareintheruralmeshblocks.AllmonetaryamountsinNZ$.WealsomadeuseofStatisticsNewZealanddata—itprovidedmeshblocklevelinformation
fromtheNewZealandCensus,conductedin2001,2006and2013.17Theaveragenumberof
peopleresidinginameshblockinCanterburywasabout105.Wewereabletomatcheach
propertytoameshblock,whichallowedustomatchtheproperty-leveldatatothe
meshblock-levelsocioeconomicdataavailablefromtheCensus.Forourinitialanalysis,we
includedanumberofexplanatoryvariablesgeneratedfromthe2006Census(sinceit
precededtheearthquakes).Weuseddatapertainingtothepersonalandhousehold
sectionsofthecensus,specifically;theproportionofthemeshblockwhoidentifiedasMāori
(theindigenouspeopleofNZ)orPacifika(PacificIslanders),ofindividualswhoself-reportas
16OnSeptember4th,2010,Canterburywashitbyamagnitude7.1earthquake.Thiswasfollowedbyaseriesofaftershocks,themostdevastatingofwhichwasa6.3earthquakeonFebruary22nd,2011,whichtook185lives.17AmeshblockisthesmallestunitforwhichStatisticsNewZealandcollectsdata,withboundariesrelatedtopopulation.Censusesareconductedevery5years.The2011censuswaspostponedto2013becauseoftheearthquakes.
11
11
havingbeenbornoverseas,andwhoself-reportashavingcompletedtertiarylevel
education;themedianhouseholdincomepermeshblock;18thechangeinthemedian
householdincomebetween2001and2006,themeannumberofhouseholdmembers,and
theproportionofthemeshblockresidentswhichself-reportasnotowningtheirhouse.
ThesedataaresummarizedinTable3.InCanterbury,4,516meshblockshaveatleastone
valuedpropertywithfullyrecordedclaimsrelatingtothe2010–2011sequenceof
earthquakes,aswellasthecorrespondingcensusinformation.
AsafirststepininvestigatingthedistributionalimplicationsoftheEQCcover,infigure1,we
graphedthepayoutdatabypropertydecileandincomedecileforalltheclaimsarisingout
oftheCanterburyEarthquakeSeriesdataset.Inthefigure,weseethatastheproperty
decileincreases,theaveragetotalbuildingpayoutforthedecileincreasesaswell,witha
sharpestincreaseforthetenthdecile.Thispatternisrepeatedinthepanelontheright
whereweusemedianhouseholdincomedeciles.
18Thetopincomeiscensoredat$100,000.In2006,therewere0.03%ofmeshblockswheretheMedHHIncometopcensoredat$100,000,andin20010.01%.
Figure 1: Distribution of Adjusted Building Payouts by Property Value and Income deciles. Canterbury dataset only, excludes zero value payouts. Distribution of payouts per property adjusted by number of dwellings insured by deciles of either dwelling adjusted modelled building value as at mid-2010, or meshblock level median household income as at 2006. Whiskers indicate 0.5 times the IQR, to better show the median values (version with standard whiskers in appendix).
12
12
Intheboxplots,themiddlelineindicatesthemedian,theshadedboxindicatesthe
interquartilerange(IQR),and“whiskers"indicate0.5timestheIQR.Anotableobservation
istheincreaseinthespreadofthetotalpayoutperdwellingasthedecilesincrease.This
reflectshigher-valuepropertiesrequirehighercostofrepairs.Itisworthremindingthe
readerherethatthesepayoutsonlytakeintoaccountthepayoutsfromthepublicinsurer,
andsignificantlydamagedhomeswouldverylikelyhavealsoreceivedrepairpayoutsfrom
theirprivateinsurancecompany.
3.Methodology
GiventheidenticalpremiumspaidforEQCcoverbyhomeowners,weexpectedsome
redistributiontooccur.Wehypothesizedtwodifferentmechanismsfortheregressivityin
thisscheme:
1. Wealthierhouseholdsmayliveinriskierareas(suchasonhillsidesorbythewater),
leadingtoahigherlikelihoodofnaturalhazardexposure,andthustoahigherlikelihood
ofdamage.
2. The100Kcaponbuildingpaymentspereventislikelytobemoredrawnonforwealthier
homessincethesehomeshavethecapacitytoincurmoredamage.Giventhehigher
valueofeachcomponentofthehome,allelseconstant,highvaluehomeswillincur
moredamage.
Thefirstmechanismisfrequentlymentionedasaplausibleonefordamagesfromfloods,
bothfromstormsurgesthathitcoastalpropertiesandfromriverinefloodsthathit
propertiesonriverbanks.Thisreasonhasbeensuggestedascausingsignificantregressivity
intheU.S.andUKfloodinsuranceprograms.Whileadmittedlythishasnotyetbeen
13
13
quantifiedineitherofthesefloodinsuranceprograms,itislessinterestingfromour
perspective.Itislessrelevantforearthquakes,whoseexactlocationandseismic-wave
propagationaremorerandomandlessorientedwithobviousexternalcharacteristics
determiningthespatialdistributionofhousing.InthecaseoftheCanterburyearthquakes,
the22/2/2011earthquake’sepicentrewaslocatedtothesoutheastofthecity;ingeneral
theeasternsuburbsarelesswealthywhilethenorth-westernsuburbs,furtherawayfrom
theepicentreoftheearthquake,havethehighervaluepropertiesandhigher-income
households.
ThefocusofouranalysisoftheCanterburyexperiencewashencethesecondmechanism.
Thehypothesisweexaminedwasthatwealthierhomeownersownpropertiesthatarelikely
tobecostliertorepairthantheirlesswell-offcounterparts.Forexample,alargerhouse
usuallyhasmoreinteriorfloorsthatmaycrack,andthesefloorsmaybemadefrommore
expensivematerials.Naturally,therearealsopossiblemechanismsthatcanleadtothe
oppositeoutcome:perhapsnewerorbetter-maintainedhousesarelessvulnerableto
earthquakesastheywerebuilttohigherseismicstandards.
Toidentifytheeffectofthe100Kcap,wefirstlookedatwhetherhigher-valuehomesin
CanterburysustainedhigherdamagesfromtheCanterburyEarthquakeSeries.Inthiscase,
wealthierhomeownerswereidentifiedeitherbythevalueofthehomeorbytheaverage
socioeconomicstatusoftheresidentsintherespectivemeshblock.19Weregressedthe
19Duetothenatureoftheavailabledata,wecouldnotidentifywhetherasinglehomeownerownedmultipleproperties.Giventhismissingindicatoroftheparticularlywealthy,ourresultsarelikelytobeconservative.Theidentificationbasedonaproxyforwealth(thevalueofthehome)ispotentiallymoreinformativethanthedistinctionbasedonaverageincome(permeshblock).Thelattersuffers,potentially,fromtheEcologicialFallacy(Robinson,1950)–thatthestatisticalcorrelationbetweentwovariableswhentheyaregroupedmightbedifferentfromthestatisticalcorrelationoftheindividualmembersofthesegroups.Furthermore,althoughthepropertyvaluationspokesomewhatdirectlytothewealthofthehomeowner,thecensusincomedatarelatedtotheresidentsofthesemeshblocksratherthanthehomeowners.Thus,forexample,a“slumlord”whoownedanumberofcheaperpropertiesinlowsocioeconomicareascouldnotbeidentifiedcleary.However,theseareunlikelytobeveryimportantconsiderationsasthemajorityofhouseswereowneroccupied(67%ofthe2006Censusstatedoccupiedprivatedwellingswereowneroccupied).
14
14
assessedrepaircostonthemostrecentvaluationoftheproperty,aswellasanumberof
indicatorsofthesocioeconomiclevelofresidents,asindicatedbelow:
!" = $ + &'()*+,)-./012," + &34,566789*:," + ;<" + =" (1)
where!" = >*-01?,+0@)"isthesumofallassessedrepaircostsmadeforpropertywefor
claimsrelatedtoearthquakeeventsduringthespecifiedlocation(Canterbury)andtime
period(2010–2011).Theerrorterm,=",isclusteredatthemeshblockleveltoaccountfor
someofourexplanatoryvariablesonlyvaryingatthisaggregatelevel.20Inasecond
specification,whichbettercapturestheregressivityoftheEQCschemeasitiscurrently
structured,thedependent(LHS)variableisthetotalpayoutonapropertyagainstthesame
covariates,includingthemostrecentvaluationofthepropertyandanumberofcontrol
variablesatthemeshblocklevel(!" = >*-01BCD+0.*2-").Weestimatedseveralalternative
specificationstotesttherobustnessofourresultsandtoattempttoidentifyareasof
variationthatmightrequirefurtheranalysis.
GivenourfocusonthedistributionalimpactofEQCover,wealsoperformquantile
regressionontheCanterburydataset,asbelow:
!" = $ + &'()*+,)-./012," + &34,566789*:," + ;<" + =" (2)
4.ResultsandDiscussion
ResultsareshowninTable3.Incolumns1–3,weusedTotalActualAssessedRepairCostsas
thedependentvariable,andincolumns4–6weusedAdjustedTotalDwellingPayout.
20Weestimatethiswithheteroscedasticandclusterrobuststandarderrors(Cameron&Miller,2015).Wealsoperformedthisanalysisattheclaimlevel(ratherthansummingallclaimsforasingleproperty).Theresultswereverysimilar,andareavailableuponrequest.
15
15
Columns1and4showourcomprehensivespecifications.Thefirstclearresultisthatthe
coefficientsofinterest(thoseonpropertyvalueormedianhouseholdincome)arealways
positiveandstatisticallysignificantatthe1%level.Theirmagnitudeissuchthatforevery
NZ$1,000ofhigherdwellingvalue,wefoundapproximatelyaNZ$62.70increaseinTotal
ActualAssessedRepaircost,holdingotherfactorsconstant,includingmedianhousehold
incomeinthemeshblock.Further,foreveryNZ$1,000ofhigherbuildingvalue,wefound
approximately$28.30moretohavebeenpaidoutfromEQCtothehomeowner.The
associationofhighervaluesinthesewealth/incomeindicatorswasmorethantwiceaslarge
forassessedrepaircoststhanfortheactualEQCpayouts.
16
16
Table4:RegressionResults-CanterburyEarthquakeSeries
(1) (2) (3) (4) (5) (6)
VARIABLES TotalAssessedRepairCosts TotalDwellingPayout
DwellingadjustedBuildingValue'10 0.0577*** 0.0671*** 0.0257*** 0.0304***
(0.0145) (0.0163) (0.00653) (0.00747)
MedianHouseholdIncome‘06 1.297*** 1.404*** 0.662*** 0.710***
(0.149) (0.147) (0.0713) (0.0707)
Dif.inMedHHIncome‘01-‘06 -0.839*** -0.0790 -0.896*** -0.364*** 0.0235 -0.390***
(0.161) (0.132) (0.161) (0.0775) (0.0655) (0.0776)
ProportionTertiaryEducated‘06 93,461*** 178,205*** 95,614*** 77,588*** 120,855*** 78,459***
(18,081) (17,336) (18,144) (9,370) (8,856) (9,388)
ProportionNotHomeowners‘06 -23,626** -55,219*** -25,703*** -14,901*** -31,031*** -15,852***
(9,344) (9,579) (9,316) (4,835) (4,824) (4,810)
MeanNumberofHouseholdMembers‘06 -32,364*** -12,728*** -31,872*** -15,895*** -5,869*** -15,671***
(4,100) (3,599) (4,101) (2,084) (1,915) (2,083)
ProportionMāori‘06 102,156*** 65,041** 92,382*** 84,528*** 65,579*** 80,172***
(27,231) (27,339) (27,055) (15,261) (15,275) (15,194)
ProportionPasifika‘06 110,083*** 81,959** 105,593*** 79,400*** 65,041*** 77,281***
(37,144) (37,533) (37,110) (20,728) (20,948) (20,705)
ProportionBornOverseas‘06 -22,657 -46,174*** -22,376 -19,178** -31,185*** -19,023**
(16,017) (16,277) (15,999) (8,899) (9,037) (8,879)
RuralMeshblock -46,007*** -45,428*** -44,539*** -28,920*** -28,624*** -28,259***
(2,733) (2,721) (2,699) (1,394) (1,392) (1,384)
Constant 61,067*** 70,917*** 72,808*** 38,727*** 43,757*** 43,941***
(10,575) (10,855) (10,137) (5,427) (5,536) (5,243)
Observations 94,723 94,723 94,799 94,723 94,723 94,799
R-squared 0.040 0.032 0.036 0.079 0.066 0.074
Robuststandarderrorsinparentheses.***p<0.01,**p<0.05,*p<0.1.
ThistablecontainsresultsfromOLSregressionswithmeshblocklevelclusteredstandarderrors.ThedatasetincludesinformationonallclaimsmadetotheNZEQCrelatedtoinsured
damagesfollowingtheearthquakesintheCanterburyregionforeventsfrom2010-09-04to2012-02-11.Thedatasetisatthepropertylevelandexcludeszerovalueclaims(thosewhichdid
notreceiveEQCfundedrepairs).Therawclaimsandportfoliodataisconfidentialbecauseofprivacyconcerns.Theotherexplanatoryvariablesareallgatheredfrompubliclyavailable
CensustabulationfromStatisticsNZ.Thesearemeshblocklevelvariablesascollectedfromthe2006(andforMedianHouseholdIncome,2001)Census.21
21ThereaderwillnotelowR-squaredvalues.However,thisresearchdidnotsetouttoaccuratelypredictdamagesorpayouts,buttoidentifyvariationscorrelatedwithsocioeconomiccharacteristics.AlowR-
squaredisthereforenotofconcerninthiscontext.
17
17
Theeffectsofthemeshblock-levelexplanatoryvariableswerequalitativelythesamefor
bothdependentvariables,andconsistentlyaffectedthedependentvariablesinthe
expecteddirections.ThegrowthinmedianHHincome(2001to2006)hadanegativeeffect
whenstatisticallysignificant;sothatthe“newer”thewealthinthearea,thelowerthe
assesseddamageandEQCpayout.Ithasbeensuggestedinnumerousmediareportsthat
becauseofthebureaucraticcomplexityoftheinsurancesystem,moreeducatedclaimants
finditeasiertonavigatethesystemandsuccessfullyclaimforhigherdamages.This
hypothesisjustifiesthetertiaryeducationmeasureweincludedasanexplanatoryvariable.
Ashypothesized,thecoefficientwaspositiveandstatisticallysignificant.Ithasalsobeen
suggestedthathomeownerthatliveinthehousearemorelikelytonegotiatewiththe
insurertoexpeditetheprocess(thusputtingrenterswhosepropertywasdamagedata
disadvantage).Thisvariablewasstatisticallysignificantandnegativeashypothesized.
Anotherpossiblefactorwasthenumberofhouseholdmembers.Ashypothesizedlarger
householdsize,anotherimperfectproxyforsocioeconomicstatus,wasalsonegativeand
statisticallysignificant.
Wealsoincludedanumberofethnicityvariablesatthemeshblocklevel.TheProportion
MaoriandProportionPasifikaareincludedtocheckiftheschemeishavinganadverse
effectontheseminorities,whichareofparticularimportancetoNewZealand.InNZ,both
ethnicitiesareidentifiedwithlowerincome,onaverage,thoughthePasifikapopulation
(thoseoriginatingfromotherPacificIslands)aregenerallymoredisadvantaged,witha
significantproportionusingEnglishasasecondlanguage.However,aftercontrollingfor
income,education,andfamilysize,whichalsoproxyforsocioeconomics,theseethnicities
arestatisticallyidentifiedwithpositiveeffectsonbothdamagesandpayouts.Finally,we
alsoincludedtheproportionofthepopulationbornoverseas,astabulatedinthe2006
18
18
census,incasetheclaimprocessismoredifficultforthisgrouptonavigatebecauseof
languagebarriers,fewerlocalsocialties,lackofcommunicationwithassessorsabout
deadlines,etc.Theassessedrepaircostsarenotsignificantlyaffectedbythismeasure.
However,theredoesappeartobeanegativeeffectontotaldwellingpayouts.Finally,ifthe
propertyisinaruralmeshblock,weseenegativeeffectsonbothdamagesandtotal
payouts;likelybecausemostruralmeshblockswerefurtherawayfromthequake’s
epicentre.
19
19
Table5:Regressionspecificationtesting-CanterburyEarthquakeSeries (1) (2) (3) (4) (5) (6)VARIABLES TotalDwellingPayout DwellingadjustedBuildingValue‘10 0.0257*** 0.0269*** 0.0269*** 0.0282*** 0.0264*** 0.0264*** (0.00653) (0.00678) (0.00678) (0.00700) (0.00647) (0.00644)MedianHouseholdIncome‘06 0.662*** 0.473*** 0.491*** 0.729*** 0.507*** 0.504*** (0.0713) (0.0591) (0.0582) (0.0553) (0.0502) (0.0450)Dif.inMedHHIncome‘01-‘06 -0.364*** (0.0775) ProportionTertiaryEducated‘06 77,588*** 85,462*** 77,979*** (9,370) (9,353) (8,549) ProportionNotHomeowners‘06 -14,901*** -18,594*** -21,511*** -8,876** 512.2 (4,835) (4,858) (4,540) (4,428) (4,317) MeanNumberofHouseholdMembers‘06 -15,895*** -14,299*** -15,102*** -17,301*** (2,084) (2,087) (2,041) (2,066) ProportionBornOverseas‘06 -19,178** -20,625** (8,899) (8,933)
ProportionMāori‘06 84,528*** 80,825*** 89,274*** 60,879***
(15,261) (15,262) (14,413) (14,018) ProportionPasifika‘06 79,400*** 75,247*** 71,703*** 52,096** (20,728) (20,814) (20,799) (20,778) RuralMeshblock -28,920*** -28,863*** -28,077*** -31,257*** -34,118*** -34,147*** (1,394) (1,399) (1,379) (1,350) (1,329) (1,249)Constant 38,727*** 40,524*** 39,145*** 42,908*** 13,849*** 14,133*** (5,427) (5,455) (5,467) (5,514) (3,847) (2,555) Observations 94,723 94,723 94,723 94,723 94,725 94,725R-squared 0.079 0.076 0.075 0.064 0.053 0.053Robuststandarderrorsinparentheses.***p<0.01,**p<0.05,*p<0.1.ThistablecontainsresultsfromOLSregressionswithmeshblocklevelclusteredstandarderrors.ThedatasetincludesinformationonclaimsmadetotheNewZealandEarthquakeCommissionrelatedtoEarthquakesorFiresfollowingEarthquakesintheCanterburyregionofNewZealandforeventsfrom2010-09-04to2012-02-11.Thedatasetisatthepropertylevelandexcludesunfundedclaims.Rawdataconfidential.Datasource:EQC.Totaldwellingpayoutisanaggregatevariableincludingbothanycashsettlementmadetothepropertyandanypayoutformanagedrepairs,dividedbythenumberofdwellingsinsuredonthatproperty.AdjustedBuildingValue10isthebuildingvaluefortheportfolio,dividedbythenumberofdwellingsinsuredontheproperty.TheotherexplanatoryvariablesareallgatheredfrompubliclyavailableCensusdatafromStatisticsNewZealand.Thesearemeshblocklevelvariablesascollectedinthe2006(andforMedianHouseholdIncome,2001)Census.
20
20
InTable5,theconsequencesofprogressivelyremovingsomeoftheexplanatoryvariables
arepresented.Incolumn(1)(identicaltocolumn(4)inTable4)weseethatallthe
explanatoryvariablesarestatisticallysignificantlydifferentfromzeroatthe1%level,with
theexceptionofthepopulationbornoverseas.Wefirstremovedthegrowthinmedian
householdincomefrom2001to2006,asthishadamoretenuoustheoreticaleffecton
payouts;aspresentedincolumn(2).Thisresultedinadecreaseintheeffectof2006
MedianHouseholdIncome,andhadasmallpositiveeffectonthecoefficientforBuilding
Value.Incolumn(3)weremovedtheleaststatisticallysignificantvariable:theproportionof
themeshblockbornoverseas.Thecoefficientonmedianhouseholdincomeincreased
slightlyandbecamemarginallymoreprecise,whiletheeffectofbuildingvalueremained
unchanged.Droppingtheproportionofthetertiaryincolumn(4)ledtoasharpincreasein
theeffectofmedianhouseholdincome,corroboratingthewidelyestablishedobservation
thateducationandincomearepositivelycorrelated,andshowingthatwithoutcontrolling
foreducation,wemightoverestimatetheincomeeffect.
Table6:QuantileRegressionResults (1) (2) (3) (4) QuantileRegressions OLSRegression 0.25 0.5 0.75 TotalDwellingPayout TotalDwellingPayoutVARIABLES AdjustedBuildingValue‘10 0.000322*** 0.0107*** 0.0739*** 0.0245*** (1.83e-06) (0.00182) (0.0106) (0.00613)MedianHHIncome'06 0.106*** 0.370*** 1.433*** 0.802*** (0.00289) (0.0453) (0.0688) (0.0586)Dif.MedHHIncome‘01-'06 -0.0555*** -0.198*** -0.610*** -0.408*** (0.00402) (0.0367) (0.109) (0.0766)Mean#ofHHMembers‘06 -936.2*** -5,380*** -29,969*** -14,667*** (45.35) (527.0) (2,533) (1,951)RuralMeshblockIndicator -2,482*** -7,981*** -59,810*** -32,875*** (72.28) (348.8) (3,249) (1,227)Constant 3,899 9,871*** 72,701*** 41,002*** (0) (2,850) (7,791) (4,473) Observations 94,725 94,725 94,725 94,725R-squared 0.064
21
21
Robuststandarderrorsinparentheses.***p<0.01,**p<0.05,*p<0.1.Thistablecontainsresultsfromquantileregressionswithmeshblocklevelclusteredstandarderrors.ThedatasetincludesinformationonallclaimsmadetotheNZEQCrelatedtoinsureddamagesfollowingtheearthquakesintheCanterburyregionforeventsfrom2010-09-04to2012-02-11.Thedatasetisatthepropertylevelandexcludeszerovalueclaims(thosewhichdidnotreceiveEQCfundedrepairs).Therawclaimsandportfoliodataisconfidentialbecauseofprivacyconcerns.TheotherexplanatoryvariablesareallgatheredfrompubliclyavailableCensustabulationfromStatisticsNZ.Thesearemeshblocklevelvariablesascollectedinthe2006(andforMedianHouseholdIncome,2001)Census.
Thisalsoledtoaslightincreaseintheeffectofbuildingvalue,andinterestingly,also
decreasedtheabsolutevaluesofthecoefficientsontheethnicitymeasures.Incolumn(5)
weremovedethnicityandhouseholdmembercontrols,bringingbuildingvaluedown
marginally,median2006householdincomedownsharply,andremovingallstatistical
significancefortheproportionnothomeowners.Removingthislastproportionincolumn
(6)completedourrobustnesschecks,withnegligibleeffectsonthecoefficientsofinterest.
Ourprimaryresultsremainedrobustthroughoutthesechecks.Tertiaryeducationand
changesinhouseholdincomeappearedthemostcloselycorrelatedwithmedianhousehold
income.Theproportionnothomeownersappearedtoaffectthedependentvariableonly
throughourothercontrols.Therewasclearlysomeculturaleffectatworkaswell,since
controllingforincomeandeducationincreasedtheabsolutevalueofthecoefficientson
ethnicitycontrols.
Columns1-3ofTable6containcoefficientsfromregressionsatdifferentquantiles.In
Column1arethosepertainingtothe25thpercentile.Asthereadercansee,thecoefficients
ofinterestarerathersmallbutsignificant.Onaverage,withathousand-dollarincreasein
AdjustedBuildingValue,wewouldexpectthe25thpercentileofTotalDwellingPayoutto
increasebyonly30c,allelseequal.However,withathousand-dollarincreaseinMedian
HouseholdIncometherewouldbeonaveragea$100increaseinthe25thpercentileofTotal
DwellingPayout.InColumn2seetheeffectonthemedianofTotalDwellingPayout,which
22
22
aresignificantlyhigherthanthoseforthe25thpercentile,andinColumn3theeffectonthe
75thpercentile,whicharehigheragain.InterestinglythecoefficientsofinterestbyOLS
regressionsitbetweenthemedianand75thquantileresults.22
5.Aneasysolutiontotheregressivityproblem
Unfortunately,wecannotdefineanactuariallyfairpremiumstructuregivenwedonot
knowthedistributionoftherisk.However,nonethelesswecandefinepossibleremediesto
theregressivityissue.OnepotentialfixtotheunfortunateregressivityoftheNZdisaster
insurancesystemisremarkablysimple;ratherthanpayingaflatpremiumperyear,
homeownerscouldberequiredtopayasetpercentageoftotalprivatesuminsured.This
wouldreflectthathomeswithalargersuminsuredaremorelikelytoclaimlargeramounts,
evenofthe$100,000perdwelling,asshownintheanalysisthusfar.Thismodification
wouldcorrecttheregressivityissue.
Totestthissuggestion,weperformanumericalsimulationontheCanterburydataset.We
simulatethepremiumsusingthepercentagesadoptedbyEQC,butappliedtotheDwelling-
adjustedbuildingvalueasopposedtothefirst$100,000ofthese.Thiswouldmovethe
schemetowardsamorerisk-based(asopposedtoflat)premiumstructure.
Firstthesuggestedpremiumsforeachproperty(byEQCPropertyGroup)arecreatedas
0.0005x(Dwelling-adjustedbuildingvalueasatmid-2010).Then,thesameprocessisused
butsubstituting0.0005forfirst0.0015andthen0.002.Toexplorewhatthiswouldhave
meantforCanterburybuildingclaimants,webuildthedistributionofthesesuggested
22weshouldnoteherethatquantilecoefficientstellusabouteffectsonthedistribution,notonindividuals.
23
23
premiumswithineachdecileofdwelling-adjustedbuildingvalues.AsshowninFigure2
below,annualpremiumswouldhavebeenslightlyhigherforthosehomeownerslivingin
wealthierareas.However,theyarebynomeansunaffordable.
Usingthe0.0005%measure,forthefirstsixdecilesofpropertiesbyDwelling-adjusted
PropertyValues,suggestedpremiumsperyearwouldactuallylikelybelowerthanthe
current$150perannum,andfornoonedoesthesuggestedpremiumgoabove$400per
annum.Ahomeownerwhosehomewasvaluedat$300,000(andinsuredtothatlevel)
wouldpay$150peryear,whereasahomeownerwhosehomewasvaluedat$1,000,000
wouldpay$500peryear.Withthe0.0015%or0.002%measures,thevastmajorityof
homeownerswouldstillpaylessthan$1000peryear.
Withthese94722homes,undertheoriginalpremiumstructureEQCwouldhaveraised
4,736,100inoneyearifallweresingledwellinghomes.Withthesuggestedpremiums,EQC
wouldhaveraised14,100,000withthe5%measure,42,200,000withthe15%or56,200,000
withthe20%.Thus,thepremiumchangewouldlikelyalsohavefinancialbenefitsforEQC.
24
24
Figure2:Distributionofsuggestedpremiums.This figure shows the distribution of suggested premiums. The first is the distribution ofpremiumsas0.0005timesthedwelling-adjustedbuildingvalue,thesecondusing0.0015andthethirdusing0.002.Thebuildingvaluesareasatmid-2010,andadjustedbythenumberofdwellingsrecorded.ThisfigurealsousesonlythebuildingclaimantsfromtheCanterbury2010-2011earthquakeseries.DatasuppliedbyEQC,andconfidential.DollarsareNZ$.
25
25
Figure3:PremiumtoPayoutRatioforsuggestedpremiums,byBuildingValueDecileThisfigureshowsthedistributionofSuggestedPremium/TotalPayout,whereinpanel1thesuggestedpremium iscalculatedas0.0005times thedwelling-adjustedbuildingvalue(prequake),thesecondusing0.0015andthethirdusing0.002.Thebuildingvaluesareasatmid-2010. This figure also uses only the building claimants from the Canterbury 2010-2011earthquakeseries.DatasuppliedbyEQC,andconfidential.DollarsareNZ$.
26
26
ThehopewiththisprogressivepremiumstructureisthattheratioofpremiumtoEQC
payoutbecomesconstantacrossdeciles.InFigure3below,theseratiosofsuggested
premiumsagainstactualpayouts(perdwelling),aregraphedinstandardboxandwhisker
plotsbybuildingvaluedecile.Themedianratioforeachisrelativelyflatacrossdeciles,
supportingthisasapossiblefixtotheregressivityissue.Thesuggestedpremiumstructure
couldbeadjustedtomakeitmoreconstant.AlternategraphsbyMedianHouseholdIncome
decileareincludedintheAppendix,asarethoseshowingtheflatstructureasitoperates
currently.
AnyofthethreesuggestedoptionsofpremiumstructurewouldmakeEQC’sresidential
buildingcoverschemesignificantlylessregressive.Thechoiceofpremiumstructure(using
0.0005,0.0015or0.002)woulddependontherequirementsforincomeraisedperyearand
thecapabilityofhomeownersatthelowerendofthespectrumtoaffordincreased
premiums.The0.0005measurereducesregressivity,increasesEQCrevenueperyear,and
doesnotincreaseannualpremiumsforhomeownersofthelowestdecileofvaluedhomes.
Thismeasureisthereforepreferredbytheauthors.
6.Conclusions
Inalmostallcaseswherehomeownersareexposedtoasignificantriskofsudden-onset
naturalhazards,theprivateinsurancesectorelectsnottoinsureagainstthesehazards.23
Directpublicprovisionorsubsidizationofinsurancearethereforenecessaryifsuchcoveris
perceivedtobesociallydesirable.Unfortunately,publicnaturalhazardinsurancehas
23 The many reasons why this is the case are discussed in Kusuma et al. (2017).
27
27
adversedistributionalconsequencesinalmostallcases.Thispaper’saimisnotonlyto
describethesocioeconomicdirectioninwhichtheseinsurance-relatedfinancialtransfers
areflowing,buttoquantifythem.Themechanismforwealthtransferinpublicearthquake
insuranceanalyzedinthispaperfacilitatesupwardtransfers—thepooraresubsidizingthe
rich.
OuranalysisoftheCanterburyEarthquakeseries,andthefunctioningofNewZealand’s
publicinsurer,offerstwoinsights.First,itclearlysupportsthehypothesisthatmore
expensivehomesreceivehigherpayoutsirrespectiveoftheirexposuretothehazard;i.e.,
highersumsthatareadirectconsequenceofthehighervalueoftheaffectedproperties.
Secondly,itsuggeststhatcappingcoverageandhavingflatpremiums,bothofwhichaimto
deliveramoreequitablescheme,arenotsufficient;eventhesekindsofprogramsendup
transferringriskfromhomeownersofexpensivehomestohomeownersoflower-value
homes(andinsomeothercasestonon-homeowners).OurfindingintheNewZealandcase,
suggeststhatmanyotherseeminglymoreegalitariannaturalhazardinsurancesystemsare
regressiveaswell.
Withthiswork,weaimtoimprovethefunctionalityofpublicnaturalhazardinsurance,by
drawingattentiontothedistributionalfunctionoftheseschemes.IntheNewZealandcase,
theregressiveeffectcanbecounteractedbyasimpleshiftfromeffectivelyflatpremiumsto
asetpercentageofthetotalprivatesuminsured(whilemaintainingthecoveragecap).
Futureresearchshouldextendthistypeofanalysistootherpublicnaturalhazardinsurance
schemesinothercountries,sothattheadversedistributionalcharacteristicofthese
programsisavoided.
28
28
Bibliography:ABI(2011)AssociationofBritishInsurersrespondstoGovernmentupdateonthefutureoffloodinsurancehttp://www.abi.org.uk/Media/ABI_Media_Statements/ABI_Media_Statements_2011.Ben-Shahar,O.,&Logue,K.D.(2015).UndertheWeather:GovernmentInsuranceandtheRegulationofClimateRisks.Bento,A.M.,Goulder,L.H.,Jacobsen,M.R.,&VonHaefen,R.H.(2009).DistributionalandefficiencyimpactsofincreasedUSgasolinetaxes.AmericanEconomicReview,99(3),667-699.Bin,O.,Bishop,J.A.,&Kousky,C.(2012).RedistributionalEffectsoftheNationalFloodInsuranceProgram.PublicFinanceReview,40(3),360-380.Borren,P.,&Sutton,M.(1992).Areincreasesincigarettetaxationregressive?HealthEconomics,1(4),245-253.Cameron,A.C.,&Miller,D.L.(2015).Apractitioner’sguidetocluster-robustinference.JournalofHumanResources,50(2),317-372.CCS(2008).NaturalNaturalhazardinsuranceCover.ADiversityofSystems,Madrid:ConsorciodeCompensaciondeSeguros.Davey,J.(2015).FloodRe:riskclassificationand‘DistortionoftheMarket.’In:Hjalmarsson,Johanna(eds.)FutureDirectionsofConsumerFloodInsuranceintheUK-ReflectionsuponthecreationofFloodRe.UniversityofSouthampton,26-33.EQC(2011)BriefingtotheIncomingMinister:December2011.NewZealandEarthquakeCommission.Freeman,P.K.,&Scott,K.(2005).Comparativeanalysisoflargescalecatastrophecompensationschemes.PolicyIssuesinInsurance,187-234.Hjalmarrsonetal(2015)FuturedirectionsofconsumerfloodinsuranceintheUK-reflectionsuponthecreationofFloodRe,26-33.Davis,L.,&Knittel,C.(2016).AreFuelEconomyStandardsRegressive?(No.w22925).NationalBureauofEconomicResearch.Defra(2011b)Floodingandinsurance:aroadmapto2013andbeyondFinalReportoftheFloodInsuranceWorkingGroups.London:Defra.Dlugolecki,A.(2009).Copingwithclimatechange:risksandopportunitiesforinsurers.CharteredInsuranceInstitute,London.Henderson,A.(2010)'Insurance-Naturalhazardinsurance',TeAra-theEncyclopediaofNewZealand,http://www.TeAra.govt.nz/en/insurance/page-4Howard,J.(2016).SocioeconomicEffectsoftheNationalFloodInsuranceProgram.Springer.Hussain,A.(2008)FloodInsuranceBlacklistSwells.TheSundayTimes,News,p11
29
29
Johnson,W.(2006).Arepublicsubsidiestohighereducationregressive?Education,1(3),288-315.JointCommitteeonTaxation(2015)FairnessandTaxPolicy(JCX-48-15).Kakwani,N.C.(1977).Measurementoftaxprogressivity:aninternationalcomparison.EconomicJournal,87(345),71-80.Karim,A.Noy,I.(2016).“PovertyandNaturalDisasters:ARegressionMeta-Analysis.”w/AzreenKarim.ReviewofEconomicsandInstitutions,7(2).Kreimer,A.,Arnold,M.,&Carlin,A.(2003).BuildingSaferCities:TheFutureofDisasterRisk.WorldBankPublications.Kunreuther,H.(2015).Theroleofinsuranceinreducinglossesfromextremeevents:Theneedforpublic–privatepartnerships.GenevaPapersonRiskandInsurance:IssuesandPractice,40(4),741-762.Kunreuther,H.,&Pauly,M.(2009).InsuringAgainstCatastrophes.In:F.X.Diebold,N.J.DohertyandR.J.Herring(eds.).TheKnown,theUnknownandtheUnknowableinFinancialRiskManagement.Princeton:PrincetonUniversityPress.Lindley,S.,O’Neill,J.,Kandeh,J.,Lawson,N.,Christian,R.,&O’Neill,M.(2011).ClimateChange,JusticeandVulnerability.JosephRowntreeFoundation,York.Lyon,A.B.,&Schwab,R.M.(1991).Consumptiontaxesinalife-cycleframework:aresintaxesregressive?NationalBureauofEconomicResearchNo.w3932.Marshall,D.(2017).TheCaliforniaEarthquakeAuthority.DiscussionpaperforResourcesfortheFuture–DisasterRiskFinancing.McAneney,J.,Crompton,R.,McAneney,D.,Musulin,R.,Walker,G.&PielkeJr,R.(2013).Market-basedmechanismsforclimatechangeadaptation:Assessingthepotentialforandlimitstoinsuranceandmarketbasedmechanismsforencouragingclimatechangeadaptation,NationalClimateChangeAdaptationResearchFacility,GoldCoast,99pp.Medders,L.A.,&Nicholson,J.E.(2017).Florida’sStateWindPools.DiscussionpaperforResourcesfortheFuture–DisasterRiskFinancing.Michel-Kerjan,E.O.,&Kousky,C.(2010).Comerainorshine:EvidenceonfloodinsurancepurchasesinFlorida.JournalofRiskandInsurance,77(2),369-397.Monti,A.(2009).ClimateChangeandWeather-RelatedDisasters:WhatRoleforInsurance,ReinsuranceandFinancialSectors.HastingsWest-NorthwestJournalofEnvironmentalLawandPolicy15(1),151-172.Musgrave,R.&Thin,T.(1948).Incometaxprogression,1929-48.JournalofPoliticalEconomy,56(6),498-514.Chicago Nelson,T.,Simshauser,P.,&Nelson,J.(2012).Queenslandsolarfeed-intariffsandthemerit-ordereffect:economicbenefit,orregressivetaxationandwealthtransfers?EconomicAnalysisandPolicy,42(3),277-301.
30
30
NZNSEE,(1993)ChangestonaturalhazardinsuranceinNewZealand,BulletinNZNationalSocietyforEarthquakeEngineering,Vol.26,No.4,pp437-444.NZTreasury(2015)NewZealand’sFutureNaturalNaturalhazardinsuranceScheme:ProposedchangestotheEarthquakeCommissionAct1993.KaitohutohuKaupapaRawaTheNewZealandTreasury.OECD(2016),FinancialManagementofFloodRisk,OECDPublishing,Paris.DOI:http://dx.doi.org/10.1787/9789264257689-enOFM(2011)MemorandumtoCabinet:IncreasingtheEarthquakeCommisson’sLevy.OfficeoftheMinisterofFinance.O'Neill,J.,&O'Neill,M.(2012).SocialjusticeandtheFutureofFloodInsurance.Paudel,Y.(2012).Acomparativestudyofpublic—privatenaturalhazardinsurancesystems:lessonsfromcurrentpractices.GenevaPapersonRiskandInsurance:IssuesandPractice,37(2),257-285.Poterba,J.M.(1991a).Isthegasolinetaxregressive?Taxpolicyandtheeconomy5,145-164.Poterba,J.M.(1991b).Taxpolicytocombatglobalwarming:ondesigningacarbontax.In:RudigerDornbuschandJamesM.Poterba(eds.)GlobalWarming:EconomicPolicyResponses.Pp.71-98.Cambridge,MA:MITPress.Robinson,W.S.(1950).EcologicalCorrelationsandtheBehaviorofIndividuals.AmericanSociologicalReview15,3,pp.351-357.Slitor,R.E.(1948).Themeasurementofprogressivityandbuilt-inflexibility.QuarterlyJournalofEconomics,62(2),309-313.Surminski,S.(2014).Theroleofinsuranceinreducingdirectrisk:thecaseoffloodinsurance.InternationalReviewofEnvironmentalandResourceEconomics,7(3-4),241-278.SurminskiS.(2017).Fitforpurposeandfitforthefuture?AnevaluationoftheUK’snewfloodreinsurancepool.ResourcesfortheFutureDiscussionPaper.Schwarze,R.,Schwindt,M.,Weck-Hannemann,H.,Raschky,P.,Zahn,F.,&Wagner,G.G.(2011).NaturalhazardinsuranceinEurope:tailoredresponsestoclimatechangeareneeded.EnvironmentalPolicyandGovernance,21(1),14-30.ThumimJ.,Fahmy,E.andWhiteV.(2011)ThedistributionofUKhouseholdCO2emissions:Interimreport.York:JosephRowntreeFoundation.West,S.(2004).Distributionaleffectsofalternativevehiclepollutioncontrolpolicies.JournalofPublicEconomics,88(3),735-757.Wier,M.,Birr-Pedersen,K.,Jacobsen,H.K.,&Klok,J.(2005).AreCO2taxesregressive?EvidencefromtheDanishexperience.EcologicalEconomics,52(2),239-251.
31
31
Appendix1:SuggestedPremiumtoTotalPayoutratiosbyalternatedeciles
Figure4:PremiumtoPayoutRatioforsuggestedpremiums,byMedianHouseholdIncomeDeciles.Inpanel1thesuggestedpremiumiscalculatedas0.0005timesthedwelling-adjustedbuildingvalue(prequake),thesecond
using0.0015andthethirdusing0.002.TheMedianHoueholdIncomevaluesareatthemeshblocklevel,andasat2006.Thisfigurealsousesonlythe
propertiesofbuildingclaimantsfromtheCanterbury2010-2011earthquakeseries.PropertyandpayoutdatasuppliedbyEQCandconfidential,incomedatacollectedbyStatisticsNewZealandinthe2006Census.DollarsareNZ$.
32
32
Appendix2:$150/TotalPayoutratios,bypropertyvalueandincomedeciles
Figure5:$150/TotalBuildingPayoutbyBuildingValueDecilethenMedianHouseholdIncomeDecile
Inpanel1thesuggestedpremiumiscalculatedas0.0005timesthedwelling-adjustedbuildingvalue(prequake),thesecondusing0.0015andthethirdusing0.002.Thebuildingvaluesareasatmid-2010.TheMedianHouseholdIncomevaluesareatthemeshblocklevel,andasat2006.ThisfigurealsousesonlythepropertiesofbuildingclaimantsfromtheCanterbury2010-2011earthquakeseries.PropertyandpayoutdatasuppliedbyEQCandconfidential,incomedatacollectedbyStatisticsNewZealandinthe2006Census.DollarsareNZ$.“Excludesoutsidevalues"
referstotheoutliersoftheboxandwhiskerplotsbeingomitted.
33
33
Appendix3
Figure6:DistributionofAdjustedBuildingPayoutsbyPropertyValueandIncomedeciles–version2StandardBoxandWhiskerPlots-Canterburydatasetonly,excludeszerovaluepayouts.Distributionofpayoutsperpropertyadjustedbynumberofdwellingsinsuredbydecilesofeitherdwellingadjustedmodelled
buildingvalueasatmid-2010,ormeshblocklevelmedianhouseholdincomeasat2006.