加州-充電站和購車補(bǔ)貼投資對電動車滲透率的影響研究-2024-07-新能源

ATaleofTwoInvestments:

ChargingStationsand

PurchaseSubsidiesforEV

Adoption

Yanjun(Penny)Liao,BeiLuo,andBeiaSpiller

WorkingPaper24-12

July2024

AbouttheAuthors

Yanjun(Penny)LiaoisaneconomistandfellowatResourcesfortheFuture(RFF).

Herresearchprimarilyfocusesonissuesofnaturaldisasterriskmanagementand

climateadaptation.Shehasstudiedtheimpactsofdisastersonlocalgovernment

budgets,housingmarkets,anddemographicchanges.Herongoingworkinvestigateshowdisasterinsuranceinteractswiththehousingandmortgagesector,aswellastheeconomicandfiscalimpactsofadaptationpoliciesonlocalcommunities.LiaoearnedherPhDineconomicsfromUCSanDiegoin2019andconductedherpostdoctoral

researchduring2019–21attheWhartonRiskCenteratUniversityofPennsylvania.

BeiLuoisaneconomistatAmazonwhoearnedherPhDfromtheUniversityofCalifornia,SanDiego,in2023.

BeiaSpillerisafellowandthedirectorforRFF’sTransportationProgram.Priorto

joiningRFF,shewasLeadSeniorEconomistatEnvironmentalDefenseFund,where

sheworkedforalmostadecade.SheisalsoaBoardmemberfortheAssociation

ofEnvironmentalandResourceEconomists.Spillerisanenergyeconomist,with

experienceworkingonelectricityandtransportationissues.DuringhertimeatEDF,

sheparticipatedinmanyelectricutilityproceedingsinNYandCA,withagoalof

usheringinacleaner,moreefficientandequitableenergysystem.Shealsohasmanyyearsofexperienceworkinginthetransportationsector.Hermorerecenteffortshavefocusedaroundelectricvehiclesandenvironmentaljustice,exploringsomeofthemostpressingissuesaroundelectriccar,truckandbusadoption.Herpublicationsrange

acrosstheenergyspace,withalargefocusonidentifyingenvironmental,communityandhealthimpactsofrenewableenergyresourcesandenergypolicies.

AbouttheProject

ThispaperwaswrittenbeforeBei’semploymentatAmazon.

Acknowledgements

WethankSophiePesekforoutstandingresearchassistance.

AboutRFF

ResourcesfortheFuture(RFF)isanindependent,nonprofitresearchinstitutionin

Washington,DC.Itsmissionistoimproveenvironmental,energy,andnaturalresourcedecisionsthroughimpartialeconomicresearchandpolicyengagement.RFFis

committedtobeingthemostwidelytrustedsourceofresearchinsightsandpolicysolutionsleadingtoahealthyenvironmentandathrivingeconomy.

Workingpapersareresearchmaterialscirculatedbytheirauthorsforpurposesof

informationanddiscussion.Theyhavenotnecessarilyundergoneformalpeerreview.TheviewsexpressedherearethoseoftheindividualauthorsandmaydifferfromthoseofotherRFFexperts,itsofficers,oritsdirectors.

SharingOurWork

OurworkisavailableforsharingandadaptationunderanAttribution-

NonCommercial-NoDerivatives4.0International(CCBY-NC-ND4.0)license.Youcancopyandredistributeourmaterialinanymediumorformat;youmustgive

appropriatecredit,providealinktothelicense,andindicateifchangesweremade,andyoumaynotapplyadditionalrestrictions.Youmaydosoinanyreasonable

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.

1

ATaleofTwoInvestments:ChargingStationsand

PurchaseSubsidiesforEVAdoption*Yanjun(Penny)Liaot1,BeiLuo?2,andElishebaSpiller§.1

1ResourcesfortheFuture

2UniversityofCaliforniaSanDiegoJuly17,2024

Abstract

Thispaperstudiestheinteractionbetweenfinancialpurchasesubsidiesandcharg-inginfrastructuredevelopmentinpromotingelectricvehicle(EV)adoption.LeveragingsurveydatafromtheCleanVehicleRebateProject(CVRP)inCaliforniaandspatialinformationonchargingstations,wefindasignificantpositiveimpactofhighercharg-ingstationdensityonself-reportedimportanceofCVRPrebatesinEVpurchasedeci-sions.Theresultsexhibitsubstantialheterogeneitybetweenlower-andhigher-incomeindividuals,likelyduetotheirdifferentchargingneeds.Ourfindingsrevealacomple-mentaryrelationshipbetweenimprovingchargingprevalenceandprovidingpurchasesubsidies,whichsuggeststhatahybridpolicycombiningthesetwotypesofincentivesmighthelpoptimizetheoverallcost-effectivenessinacceleratingEVadoption.

*WethankSophiePesekforoutstandingresearchassistance.Allerrorsareourown.tContact:

yliao@.

?Contact:

b7luo@.

ThispaperwaswrittenbeforeBei’semploymentatAmazon.§Contact:

bspiller@

2

1Introduction

Thedirectemissionofcarbondioxidefromtheglobaltransportationsectorwasalmost8Gtin2022accordingtotheInternationalEnergyAgency,representingasignificantcon-tributortoglobalwarmingandclimatechange.Transportationactivitiesarealsoprimarysourcesofcriteriaairpollutants,

1

worseninglocalairqualityandthreateninghumanhealth.Toreducegreenhousegasemissionsandairpollution,governmentsemployawidearrayofpoliciestodecarbonizethetransportationsector,withafocusonpromotingenergyefficiencyandencouragingtheadoptionofzero-emissionvehicles(ZEVs),suchasbatteryelectricve-hicles(BEVs)orfuelcellelectricvehicles(FCEVs).InCalifornia,theOfficeoftheGovernorissuedExecutiveOrderB-48-18,whichsetsanambitioustargetof1.5millionZEVsontheroadby2025and5millionby2023,followingthelong-termobjectiveofnetzerocarbonemissionsby2050.Tomeettheseessentialmilestones,thestategovernmentsoughttoac-celeratetheZEVmarketbyloweringthecostofEVpurchases,increasingtheavailabilityofchargingstations,andprovidingothernonmonetaryincentives,suchashigh-occupancyvehicle(HOV)laneaccessandpriorityparking.

Awidevarietyofsubsidyprogramsaimtoincreasetheaffordabilityofzero-orlow-emissionvehiclesallovertheworld.Atthefederallevel,theInflationReductionActprovidedupto$7,500intaxcreditsfornewEVpurchases

2

andupto$2,500forusedEVpurchases.Atthestatelevel,California’sCleanVehicleRebateProject(CVRP)offerssubsidiesfrom$1,000to$7,500forthepurchaseorleaseofplug-inelectricvehicles(PEVs)(includingBEVsandplug-inhybridelectricvehicles(PHEVs)andfuelcellvehicles.TheCleanCars4All(CC4A)program(formerlytheEnhancedFleetModernizationPlus-UpProgram)grantsupto$9,500forincome-qualifiedcustomerstoreplacetheirolder,high-pollutingvehicleswithnewer,low-emittingvehicles.Theseprogramsareimportantforadoption,astheliteraturehasfoundpositiveassociationsbetweenfinancialpurchaseincentivesandhigherEVmarketshares(

Hardmanetal.,

2017;

Jennetal.,

2018

).

However,providingextensivepurchaseincentivesforEVadoptionimposesasubstan-tialfinancialburdenonlocalgovernments.Accordingtoa2022reportbytheLegislativeAnalyst’sOffice(LAO),theCVRPandCC4Anecessitateinvestmentpackagesof$525mil-lionand$400million,respectively,forfiscalyear2021–2022.Anincreaseinchargingsupply

1Accordingtostandardsassociatedwithhumanhealthandtheenvironment,theEPAhasidentifiedsixcriteriaairpollutants:carbonmonoxide,lead,nitrogenoxides,ground-levelozone,particlepollution(alsocalled”particulatematter”),andsulfuroxides.

2Themagnitudeofthetaxcreditdependsonthecountryoforiginofthemineralswithinthebatteryandthebatterymanufacturingandhasbothincomeandvehiclepricelimits.Formoreinformationonthesetaxcredits,see

thisblog.

3

equipmentisneededforEVcustomerswithoutaccesstoprivatehomeorworkplacechargingandtoalleviaterangeanxietyofEVdriversforlong-distancetravel.

BothCaliforniaandthefederalgovernmenthaveallocatedbillionsofdollarstofundingchargingstationinvestments.TheCaliforniaEnergyCommissionimplementedtheCalifor-niaElectricVehicleInfrastructureProjecttofacilitatethedevelopmentanddeploymentofcharginginfrastructurethroughoutthestatewithtotalprojectcostsof$50million.Thefederalgovernmenthastwomajorprograms,bothenabledthroughtheInvestmentInfras-tructureandJobsAct.ThefirstistheNationalElectricVehicleInfrastructureProgram(NEVI),whichhasallocated$5billiontostatestoinvestin(primarilyfast)chargingsta-tionsalongmajorhighwaysandconnectedroadways.ThesecondistheChargingandFuelingInfrastructureGrantProgram(CFI),whichprovides$2.5billioninfundingover5yearstolocalcommunities,cities,andtownstoinvestin(primarilyLevel2)chargingstationswithincommunities.TheseprogramsareimportantforEVadoption,asstudieshavedemonstratedtheimportantroleofchargingstationinvestments(

Zhengetal.,

2012;

Lieven,

2015;

Tietge

etal.

,

2016

;

BongesIIIandLusk,

2016;

Mieleetal.,

2020)

.

Giventhetremendousexpensesoftheseprograms,evaluatingthecost-effectivenessofdifferentpoliciesandweighingtheirrelativevaluesfromtheconsumers’perspectiveisvitalforinformingongoingpoliciesthatpromoteEVmarketgrowth.Thisinvolvesunderstand-ingfundamentaldeterminantsintheconsumerdecisionprocessandpotentialinteractionsbetweenvariouspolicies,particularlyfinancialpurchasesubsidiesandchargingnetworkde-velopment.However,robustanalysesofhowtheseincentivesinteracttoaccelerateEVadoptionareverylimited.Itisanopenquestionwhethertheavailabilityofpublicchargingfacilitieswillaltertheimportanceofpurchasesubsidies.

Intheory,theimpactofincreasedaccessibilityofpubliccharginginfrastructureonthecost-effectivenessofEVrebateprogramscouldbetwofold.First,amoreabundantsupplyofrefuelingstationswillincreasecustomers’willingnesstopurchasePEVsbymitigatingconcernsaboutrangelimitationandrechargingchallenges.Asaresult,itcouldnotonlydecreasethesizeofthesubsidyrequiredtoincentivizetheadoptionofEVsbutrenderanyexistingsubsidylesseffective,asfewerindividualsmayrequireittoincentivizeEVpur-chases.Second,agreaterprevalenceofcharginginfrastructureincreasesthesubstitutabilitybetweenPEVsandtraditionalinternalcombustionenginevehicles,attractingmoreofthegeneralpopulationtotransitiontoPEVs.SuchincreasedpurchaseintentionsamongthepublicexpandsthesetofpotentialEVcustomersandtherebymayalsoincreasethenum-berofpotential“additional”participantsinrebateprograms.Therefore,whetherincreasedavailabilityofchargingstationsisadvantageousordisadvantageoustothecost-effectivenessofrebateincentivesistheoreticallyundeterminedandwarrantsempiricalinvestigation.

4

Thisisalsoimportantwhenconsideringdifferencesacrossincome,asavastmajorityofvehiclesubsidieshaveaccruedtohigher-incomehouseholdsthataremuchmorelikelyto

purchaseaPEVcomparedtolower-incomeones(Leeetal.,

2019;

MuehleggerandRapson,

2019

).However,thesewealthieradoptersaretheleastlikelytoconsiderthemonetaryincen-tivesdecisiveintheirEVpurchasedecisions.Asaresult,aconsiderableshareofparticipantsinincentiveprogramstendtobe“nonadditional,”raisingwidespreadconcernsabouttheircost-effectiveness.Severalempiricalstudieshavedirectlyestimatedtheadditionalityofex-istingrebateprograms.Forinstance,

SheldonandDua

(

2019a

)findthatmerely17percentofPEVsalesinthemodelyear2015areattributabletothenondiscriminatingUSfederaltaxsubsidy,whichimpliesanexcessivecostof$35,601associatedwithonlyoneadditionalPEVpurchase.Incontrast,theEnhancedFleetModernizationPilotProgram(commonlyknownas“ReplaceYourRide”(RYR))isfoundtobemorecost-effectivethanthefederaltaxincentives,asitgrantssubsidiesexclusivelyforlower-incomeindividualsindisadvan-tagedcommunities.

SheldonandDua

(2019b)substantiatethattheadditionalityofthe

RYRprogramismorethan44percentforPEVadoptionand78percentforhybridelectricvehicles.

Despitetherichevidenceontheeffectsofeitherpurchasesubsidiesorchargingnetworkdevelopment,remarkablylittleattentionhasbeendrawntotheinteractionbetweenthetwo.Althoughsomestudieshavecomparedtherelativeeffectivenessofthesetwopolicyinterven-tionsassubstitutes(

Sikesetal.,

2010;

Lietal.,

2017

),simulationanalyseshavesuggestedthathybridapproachescombiningpublicchargingandcleanvehiclerebatesengendermoresubstantialEVadoptionthanisolatedindividualincentives(

SilviaandKrause,

2016;

Miele

etal.

,

2020;

Lednaetal.,

2022

).However,thesesimulation-basedstudiesrelyonvarioussimplifyingassumptionstocharacterizetheinterdependenteffectsofchargingaccessibilityandpurchasesubsidies,whichmayormaynotaccordwithempiricalevidence.Forinstance,

Lednaetal.

(2022)assumethatfullovernightchargingisavailableforallEVdrivers,which

failstodemonstratetheimportanceofpublicinfrastructure,particularlyforthelargenum-berofhouseholdsthatdonothaveaccesstoanexclusivechargingoutlet(

Trautetal.,

2013

).Therefore,theinteractionbetweenthesetwoformsofpolicyinterventionsistheoreticallyambiguousandcallsforadditionalempiricalinvestigation.

Thispaperempiricallyexaminestherelationshipbetweencharginginfrastructurepreva-lenceandtheadditionalityofEVsubsidies,leveragingsurveydatafromCVRPandgeospa-tialdataonpublicchargingstationsclosetothesurveyrespondents.TheCVRPsurveyprovidesdirectmeasurementsofparticipants’perceptionsabouttheimportanceofCVRPrebatesandotherfinancialincentivesintheirPEVpurchasedecision,allowingustopreciselyidentifyhowCVRPadditionalityrespondstoevolvingcharginginfrastructureaccessibility.

5

Aftercontrollingforcomprehensivedemographicandvehicle-relatedcharacteristics,wefindasignificantpositiveassociationbetweentheadditionalityofrebateprogramsanddensityofchargingfacilitiesinbothlocal(within5miles)anddistant(upto100milesareas).

Theeffectsexhibitconsiderableheterogeneitybetweenlower-andhigher-incomeindi-viduals.Inparticular,theformerwholiveclosetochargingstationsaremorelikelytoreportthattheCVRPsubsidywascriticalintheirPEVpurchasedecisionthanotherswithsimilarincomebutloweraccesstopubliccharging,whereashigher-incomeEVcustomersdonotresponddifferently.Morechargingfacilitiesnearby,therefore,enhancetheaverageincentiveeffectsofcleanvehiclerebatesbyattractingmore“additional”adoptersfromthelower-incomepopulation.Precisely,aunitincreaseinthenumberofchargingstationsper10,000peoplewithin5milescausesa0.76percentincreaseintheprobabilityofalower-incomeindividualstating“wouldnotpurchaseorleasethePEVwithouttheCVRPrebate”and,analogously,a0.71percentincreaseintheprobabilityoftheirreportingthehighestlevelofimportancetothesurveyquestion“howimportantwastheCVRPrebateinmakingitpossibletoacquireaPEV,”holdingallotherfactorsequal.Incontrast,chargingsta-tiondensitywithin5mileshasnostatisticallysignificanteffectontheimportanceoftheCVRPrebateamongthehigher-incomepublic,perhapsbecausetheyaremorelikelytohaveat-homecharging.

Whenabroaderareaisconsidered,chargingavailabilityatgreaterdistancesappearstostimulatemorewidespreadPEVadoptioninbothlower-andhigher-incomegroups.Theestimationresultsshowthatincreasingchargingstationdensitywithin100milesresultsina13percentand7.3percentincrease,respectively,intheoddsofalower-incomeandhigher-incomeindividualconsideringtheCVRPrebatehighlyessential.Theseeffectssuggestthat,unlikehomecharging,rangeanxietyfactorsintoEVadoptiondecisionforbothgroups.Nevertheless,theimpactsaremoresubstantialforlower-incomedrivers,againhighlightingtheirgreaterdependenceonpubliccharging.Furthermore,wefindthattheseimpactsaremoresignificantforlower-incomecarbuyerswholiveinlow-densityareasandreplaceavehiclewiththenewEV,demonstratingevenfurthertheimportanceofrefininghowchargingstationinvestmentsandsubsidiesaretargetedsuchastomaximizetheadditionalityoftheseprograms.

Tothebestofourknowledge,thisanalysispresentsthefirstattempttoempiricallyestimatethecausalrelationshipbetweencharginginfrastructureprevalenceandtheaddi-tionalityofcleanvehiclesubsidies.TheCVRPsurveydataprovideuniqueadvantagestomeasuringtheadditionalityofvariousincentivesinpurchasedecisionsfromtheperspectiveofPEVadopters,allowingustolinkchangesintheirdecisionmakingwiththeexpansionofchargingnetworks.

6

Theremainderofthepaperisorganizedasfollows.Section

2

introducesthepolicybackgroundoftheCVRPandthedata.Section

3

providesatheoreticalinterpretationofpotentialimpactsbasedonamotivatingexample.WepresenttheempiricalframeworkinSection

4

andestimationresultsinSection

5.

TheconcludingremarksandpolicyimplicationsareprovidedinSection

6.

2PolicyBackgroundandData

2.1CVRP

Californiahasalwaysbeenapioneerincombatingclimatechangethroughdecarboniza-tionandelectrificationofthetransportationsector.Toachievetheambitioustargetof5millionon-roadZEVsby2030,CaliforniaAirResourcesBoard(CARB)launchedCVRPin2012toreducefinancialbarrierstocleanvehicleadoption.Inparticular,CVRPoffersgener-ouscashrebatesforthepurchaseorleaseofnewlight-dutyPEVs,FCEVs,andzero-emissionmotorcycles(ZEMs).

CVRPwasinitiallyimplementedonafirst-come-first-servebasiscontingentuponfundsavailability,withnoeligibilitycriteriabasedonfinancialstatusatitsinception,raisingcon-cernsaboutinequitablerebatedistributionandlowcost-effectiveness.Tomaketherebatemoreaccessibleandbeneficialforlower-incomeindividuals,CARBestablishedincomeeligi-bilityandincreasedrebateamountsforthosewithannualgrossincomesbelow300percentofthefederalpovertylevel(FPL)inMarch2016.Theincomecapsandmaximumper-vehiclestandardandincreasedrebatesduringourstudyperiod(fromSeptember1,2012toDecem-ber29,2019)arepresentedinTable

1

.3

BeforeMarch2016,CVRPgrantedthepurchaseorleaseofeligiblevehiclesupto$5,000forFCEVs,$2,500forBEVs,$1,500forPHEVs,and$900forZEMs.Forparticipantswithincomesbelow300percentoftheFPLwhopurchasedorleasedtheirvehiclesbetweenMarch29,2016,andOctober31,2016,therebateamountswereraisedby$1,500foreachvehicle.IftheirpurchaseswereonorafterNovember1,2016,therebateamountswereincreasedby$2,000.Inaddition,incomecapsweresetat$250kforsingletaxfilers(includingmarriedfilingseparately),$340kforhead-of-householdfilers,and$500kforjointfilersonMarch29,2016.Thesethresholdswereadjustedto$150k,$204k,and$300konNovember1,2016,respectively.Consumerswithincomeabovetheincome

capswerenoteligibleforCVRPrebatesunlesstheyacquiredFCEVs.

3TheCVRPincomecapsandmaximumper-vehiclestandardandincreasedrebatesafter2019aredis-playedinAppendixTable

A1.

7

Table1:CVRPMaximumRebateAmountsforVehiclesPurchased/Leased2012–2019

Filingstatus

Grossannualincomelevel

Vehicletype

FCEV

BEV

PHEV

ZEM

I.BeforeMarch29,2016

Standardrebate

N/A

N/A

$5,000

$2,500

$1,500

$900

II.FromMarch29,2016toOct31,2016

Increasedrebate

forlow/moderate

income

Grossannual

householdincome

≤300%ofFPL

$6,500

$4,000

$3,000

Not

eligible

Standardrebate

Individual

300%ofFPLto$250k

$5,000

$2,500

$1,500

$900

Headofhousehold

300%ofFPLto$340k

Joint

300%ofFPLto$500k

Incomecap

Individual

>$250k

$5,000

Noteligible

Headofhousehold

>$340k

Joint

>$500k

III.OnorAfterNovember1,2016

Increasedrebate

forlow/moderate

income

Grossannual

householdincome

≤300%ofFPL

$7,000

$4,500

$3,500

Not

eligible

Standardrebate

Individual

300%ofFPLto$150k

$5,000

$2,500

$1,500

$900

Headofhousehold

300%ofFPLto$204k

Joint

300%ofFPLto$300k

Incomecap

Individual

>$150k

$5,000

Noteligible

Headofhousehold

>$204k

Joint

>$300k

8

Figure1:NumberofCVRPSurveyRespondents

2.2Data

CVRPSurveyResponses

TheprimarydatausedinthisanalysisareobtainedfromavoluntaryconsumersurveyadministeredtoallCVRPparticipantswhopurchasedorleasedPEVs(excludingFCEVsandZEMs)since2012.Ourdatainclude65,643responseswithvehiclepurchaseorleasedatesfromSeptember1,2012,toDecember29,2019.Figure

1

showsthegeographicdistributionoftherespondents.Asexpected,theyareclusteredatthemorepopulatedZCTAsnearmajorcities.

Thissurveycontainsinformationabouthouseholddemographics,housingcharacteristics,factorsinpurchaseorleasedecisions,initialinterestinPEVs,anddealershipexperience.OfparticularinteresttoouranalysisareaseriesofquestionsregardingtheimportanceofcleanvehiclesubsidiesinthePEVacquisitiondecision,including“WouldyouhavepurchasedorleasedyourPEVwithouttheCVRPrebate?”and“Howimportantwasthestaterebate(CVRP)inmakingitpossibletoacquireaPEV?”ThedistributionofresponsesforeachquestionrelatedtotheimpactsofpurchaseincentivesareexhibitedinTable

2.

Descriptivestatisticsofselecteddemographics,housingconditions,andvehicle-relatedcharacteristics

9

aredisplayedinTable

3.

Consideringthepotentialdifferencesbetweenlower-andhigher-incomeindividualsinEV

adoption(BeresteanuandLi,

2011;

MuehleggerandRapson,

2022),wereportdescriptive

statisticsforlower-andhigher-incomeparticipantsseparatelyinthelastfourcolumnsofTable

2

andTable

3

forcomparison.Specifically,thelower-andhigher-incomegroupshaveanannualgrossincomelessthanandmorethan$100,000,respectively.

4

AsshowninTable

2

,lower-incomerespondentsaremorelikelytoconsidertheCVRPrebateessentialintheirpurchaseorleasedecisions.Inparticular,theyaremorelikelytoreportthattheywouldnothavepurchasedorleasedaPEVwithouttheCVRPrebateandtovalueitas“veryimportant”or“extremelyimportant”inmakingitpossibletoacquireaPEV

.5

Similarly,lower-incomeindividualsalsotendtovalueotherincentiveprogramsmoreandhavealowerinitialinterestinPEVsonaverage

.6

Inaddition,lower-incomerespondentsalsoattachgreaterimportancetoworkplacechargingorfreechargingawayfromhome,whichisinlinewithourexpectationthattheytendtodependmoreonpublicinfrastructureduetolimitedaccesstohomecharging.Table

3

alsoshowsthatasubstantiallylowerpercentageoflower-incomerespondentsliveinadetachedsingle-familyhouseorownaresidencecomparedtothehigher-incomeones.

Onecaveatinusingthisdatasetistheno-responsebias,whicharisesinvoluntarysurveyswherealowrateofresponsescanskewtheresults.Althoughapproximately75percentofeligiblePEVshaveobtainedCVRPrebates,thetakeuprateoftheCVRPconsumersurveyisaround23percent.Toimprovetherepresentativenessofthesurveysamples,CARBappliedaconventionalrankingmethod,theiterativeproportionalfitting(IPF)procedure,

7

togenerateresponseweightsbasedontheapplicationinformationofallparticipants.Weleveragetheweighteddatatoconductrobustnesschecksforourbaselineunweightedregressionsandobtainhighlyconsistentresults.Weprefertheunweightedestimatesduetotheobservedweakcorrelationbetweentheweightsandouroutcomevariables.Alldescriptivestatisticsaredisplayedbasedonoriginalunweighteddatainaccordancewithourbaselineestimation.

4Thelackofgranularityinincomecategoriesintheoriginaldataandtheabsenceoftaxfilinginformationhinderourabilitytogroupindividualsintoloworhighfinancialstatusmoreprecisely.Althoughthecutoffforourlower-incomegroupissignificantlyhigherthanconventionaldefinitions,itisameaningfuldistinctioninthecontextofEVadoption.

577.82percentlower-incomeand72.84percenthigher-incomerespondentsanswered“veryimportant”or“extremelyimportant”tothisquestion,respectively.

6Thedistributionsofthestatedimportanceoffederaltaxincentivesarehighlyanalogousbetweenthetwogroups.Thedifferencemightbebecausefederaltaxsubsidiesaretaxcreditsandcannotrollovertothenextyear.Therefore,PEVpurchaserswithlowerincomemaynotqualifyforthefullamountoffederaltaxsubsidyduetotheirinadequatetaxableincome.

7IPF,alsocommonlyknownas“biproportionalfitting”ineconomicsandstatistics,isaprevailingap-proachtoadjustsampleweightstomoreaccuratelyreflectthedistributionofthetruepopulation.

10

Table2:DescriptiveStatisticsforCategoricalImpactsofIncentives

Characteristic

Fullsample

FrequencyPercentage

Lower-income

FrequencyPercentage

Higher-income

FrequencyPercentage

WouldyouhavepurchasedorleasedyourPEVwithouttheCVRPrebate?

YesNo

31,642

33,317

48.7151.29

6,952

8,813

44.1055.90

24,690

24,504

50.1949.81

Howimportantwasthestaterebate(CVRP)inmakingitpossibletoacquireaPEV?

NotatallimportantSlightlyimportant

ModeratelyimportantVeryimportant

Extremelyimportant

1,881

4,768

10,089

17,729

30,017

2.927.3915.6527.4946.55

444

953

2,061

4,024

8,108

2.856.1113.2225.8152.01

1,437

3,815

8,028

13,705

21,909

2.947.8016.4228.0344.81

HowimportantwerefederaltaxincentivesinmakingitpossibletoacquireaPEV?

NotatallimportantSlightlyimportant

ModeratelyimportantVeryimportant

Extremelyimportant

2,636

4,074

8,693

16,085

31,113

4.216.5113.8925.6949.70

665

969

2,021

3,737

7,676

4.416.4313.4124.8050.94

1,971

3,105

6,672

12,348

23,437

4.156.5314.0425