Bus stop, property price and land value tax: A multilevel hedonic analysis with quantile calibration

LandUsePolicy42(2015)381–391

ContentslistsavailableatScienceDirect

Land

Use

Policy

jou rn al h om ep a g e :w w w . e l s e v i e r . c o m / l o c a t e / l a n d u s e p o l

Bus

stop,

property

price

and

land

value

tax:

A

multilevel

hedonic

analysis

with

quantile

calibration

Yiming

Wang

a,∗

,

Dimitris

Potoglou

b,c

,

Scott

Orford

b

,

Yi

Gong

d

a_{TheBartlettSchoolofConstructionandProjectManagement,TheBartlettFacultyofBuiltEnvironment,UniversityCollegeLondon,LondonWC1E7HB,UK} b_{SchoolofPlanningandGeography,CardiffUniversity,KingEdwardVIIAvenue,CardiffCF103WA,UK}

c_{RANDEurope,WestbrookCentre,MiltonRoad,CambridgeCB41YG,UK}

d_{SustainablePlacesResearchInstitute,CardiffUniversity,33ParkPlace,CardiffCF103BA,UK}

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received20October2013

Receivedinrevisedform30May2014

Accepted26July2014

Keywords:

Landvaluetax Transportinfrastructure Busstop

Propertyprice

a

b

s

t

r

a

c

t

Basedonamultilevelandquantilehedonicanalysisregardingthelocalpublicbussystemandtheprices ofresidentialpropertiesinCardiff,Wales,wefindstrongevidencetosupporttworesearchhypotheses: (a)thenumberofbusstopswithinwalkingdistance(300–1500m)toapropertyispositivelyassociated withtheproperty’sobservedsaleprice,and(b)propertiesofhighermarketprices,comparedwiththeir cheapercounterparts,tendtobenefitmorefromspatialproximitytothebusstoplocations.Giventhese statisticalfindings,wearguethat,landvaluetax(LVT),albeitaclassicpoliticalideadatingbacktotheearly 20thcentury,doeshavecontemporaryrelevanceand,withmoderngeographicinformationtechnologies, canberigorouslyanalysedandempiricallyjustifiedwithaviewtoactualimplementation.LevyingLVT willnotonlygenerateadditionalfiscalrevenuestohelpfinancethedevelopmentandmaintenanceof localpublicinfrastructures,butwillalsoensureamorejustdistributionoftheeconomicwelfareyielded bypublicinvestment.

©2014TheAuthors.PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/3.0/).

Introduction

Inrecentyears,theUnitedKingdom(UK)haswitnessedarevival ofpublicinterestsinlandvaluetax(LVT).1 _{Theoriginalideaof}

LVTdatesbacktoGeorge(1879),anAmericanpoliticaleconomist, who,partlyinspiredbySmith(1863),positsthatthevalueofland, ultimately,comesfromtheadjacentinfrastructuresandamenities investedbythewholecommunity.Incrementsinlandvaluedue topublicinvestment,thus,oughttobere-capturedthroughLVT. TheearliestpoliticalattemptstolegislateLVTtookplaceinthelate EdwardianBritain(Short,1997,Chapter2).LVTwasofficially pro-posedinthe1909financebill(alsoknownas“People’sBudget”), whenDavidLloydGeorgeservedasChancelloroftheExchequer asamember ofthegoverningLiberalparty.However,thethen Conservatives-dominatedHouseofLords,thoughpassingthe gen-eralbudgetin1910,managedtovetotheLVTproposal.Asimilar storyhappenedlaterwiththe1931FinanceAct,whichcontained

∗_{Correspondingauthor.+4402076791890.}

E-mailaddress:[email protected](Y.Wang).

1_{FortheexamplesofLabour’sLandValueCampaign(http://www.labourland.}

org/)andtheLiberalDemocraticParty’sActionforLandTaxationandEconomic

Reform(http://libdemsalter.org.uk/).

aLVTinitiativepassedbytherulingLabourpartybutwasrejected againbytheTorygovernmentin1934(Wenzer,2000).Oneofthe latesteffortstoseeklegislationofLVTwasin2012byCarolynLucas, aGreenpartymemberoftheUKparliament(TheUKParliament,

2012).

AlthoughLVTwasneverimplementedinBritain,itstracescan beobservedinmanyotherplacesaroundtheworld,suchasinthe citiesofPittsburghandHarrisburgintheAmericanStateof Penn-sylvaniaandanumber ofcountriessuchasAustralia, Denmark, Estonia,Russia,andNewZealand(Andelson,2000;Bourassa,1990;

Dye and England, 2010; Wyatt, 1994). While the actual policy

practice varies among these international cases, LVT has been increasingly justified as a way to financethe construction and maintenanceofpublictransportinfrastructures.Thebasicrationale remainsquitethesameasperGeorgeoriginal(1879),thatpublicly investedtransportnetworkcanpromotethevaluesofnearby pri-vatelyownedlandplots,giventheirimprovedaccessibility.From apoliticaleconomyperspective,thispartofaddedlandvalue,if substantiated,becomesakindofpositiveexternalitieswhichcan beoffsetorcapturedthroughLVT.Otherwise,generaltaxpayers (whogenerategovernmentrevenues)areessentiallysubsidising landownerswho“quietly”extractthevalues ofpublictransport infrastructures.Makingthis free-rideproblemevenmore press-ingistheundersupplyandunderfundingofpublictransportinthe

http://dx.doi.org/10.1016/j.landusepol.2014.07.017

present-dayUK,whichhasresultedinaseriesofsocialexclusion issues,facedtypicallybythelowerincomepopulationwhohave difficultiesaffordingprivatetransport(Lucas,2006).

In this paper,we explore theviabilityof levyingland value taxtofinancethemaintenanceanddevelopmentoflocalpublic transportinfrastructureswithinacontemporaryUKcontext.Our empiricalstudyfocusesonthepublicbussystemownedbyCardiff citycouncilinsouthWales,whichsawa

£

0.6millionfundingcut inthefinancialyearof2012,leadingtoasecondincreaseinbus faressinceOctober2011(WalesOnline,2012).Employinga con-ventionalordinaryleastsquare(OLS)hedonicregressionapproach, wefirstlyexaminetherelationsbetweenthesalepricesofcirca 10,000residentialpropertiesacross12electoralwardsincentral Cardiff from2000to 2009(see Fig.2), and thenumber of bus stopswithintheradiiof300m,400m,500m,750m,1000mand 1500mofeachproperty,basedonthe2007NationalPublic Trans-portAccessNodes(NaPTAN)dataset(DepartmentforTransport, 2007).WethenfurtherrefinetheOLSresults,respectively,withina multilevelmodelling(JonesandBullen,1994)andquantile regres-sionframework(Koenker,2005).Ourmultilevelanalysissuggests theOLSestimatestobeunbiasedwithrespecttotheinfluenceof busstoplocationsontheimplicitlandvaluesofnearbyproperties. Likewise,ourquantilebivariateposthoctestsconfirmthe over-allrobustnessoftheOLSoutcomes.Apolicyimplicationofthese statisticalfindingsistoexerciseatwo-tierprogressivelocalland valuetaxationschemeinhelpingCardiffcouncilfinancethelocal bussystem.Our estimation, basedonthe numberof bus stops withina 1500mradiusofeveryindividualpropertyincludedin oursampledata,suggeststhat,forapropertypricedbelowcirca

£

195,000,everyadditionalbusstopcontributestoacirca0.11% marginalincreaseinpropertypricethroughlandvaluebetterment. Thecorrespondingfigureis0.22%forapropertyinthesecondtier withamarketpriceabove

£

195,000.

Theremainderofthispaperisorganisedasfollows.Thenext section“Landvaluetax:fromEdwardiantocontemporaryBritain” reviewstheliteratureonlandvaluetaxandtherelatedplanning practices,mainlywithinaUKcontext.Thisisfollowedbythedesign ofthisresearchin“Researchdesign”section,whichstudiesthecase ofCardiffBus,byfollowinganOLSandmultilevelhedonic regres-sionapproachsupplementedbyaquantilecalibration.Thedataand modelresultsarereportedinsections“ThecaseofCardiffbus”and “Modelresults”,respectively,beforethestudy’spolicyimplications arediscussedin“Policyimplications”section.Theconclusionsare summarisedin“Conclusionandfutureresearch”section,alongside thedirectionsoffutureresearch.

Landvaluetax:fromEdwardiantocontemporaryBritain

TheEdwardians

Thelatestglobaleconomicrecessionhasforcedmanycountries tocutpublicspending.ThisisparticularlythecaseintheUK,with thecoalitiongovernmentaimingtoreducepublicexpenditureby asmuchas

£

6.2 billionbetween2010and 2011(HerMajesty’s Treasury,2010).Sincebudgetarystringencycontinuedinto2012 and2013,publicfinancehasbecomeatopchallengeconfronting theWestminsterparliament,whichisseekingnewsourcesoftax income,forexample,byproposingafurtherriseinvalue-added consumptiontax(VAT)from20%to25%(TheTelegraph,2012).

Acenturyago,theEdwardianpoliticiansweresimilarlyfaced withapublicfinancechallengetofundtheemergingwelfarestate programmes,includinganembryonicpensionscheme(Hattersley, 2004).DavidLloydGeorge,duringhisChancellorshipofthe Exche-quer as a member of thegoverning Liberal party, proposedto tax on tobaccos, luxurious goods, and most important of all,

land,inthe1909financebill.Thesetaxationmeasureswerenot

only intended to balance the government budget, but also to

tackle widespread political and economic inequalities faced by theBritish society. Given its populist flavour, the 1909budget wasoftencalledPeople’sBudget(Short,1997).However,thethen Conservatives-dominatedHouseofLords,thoughreluctantly pass-ingmanyinitiativesincludedinPeople’sBudgetoneyearlaterin 1910,managedtovetothelandvaluetax(LVT)proposal.

TheoriginalideaofLVTactuallycamefromtheothersideofthe Atlantic.George(1879),anAmericanpoliticaleconomistbornin Philadelphia,Pennsylvania,oncewrote:

“Thetaxuponlandvaluesis,therefore,themostjustandequal ofalltaxes.Itfallsonlyuponthosewhoreceivefromsocietya peculiarandvaluablebenefit,andupontheminproportionto thebenefittheyreceive.Itisthetakingbythecommunity,for theuseofthecommunity,ofthatvaluewhichisthecreationof thecommunity.”(George,1879,Chapter33)

George’scentraltenetisthatthevalueofland,ultimately,comes fromtheadjacentinfrastructuresandamenitiesinvestedbythe localcommunity.Incrementsinlandvalueduetopublic invest-mentthereforeoughttobere-capturedthroughLVT.Thisargument resonateswiththegroundrenttheoriesbySmith(1863),Ricardo

(1891),andevenMarx(1867).Thetaxonlandvaluecanalsobe

consideredakindofPigovian(1920)tax,ifoneseestheaddedland valueaccruingfromthepositiveexternalitiesyieldedby commu-nityinvestment(Petrella,1988).

TheContemporaries

ThePigovianaspectofLVTisperhapsbestfeaturedinits

con-temporarypractice, asLVT has beenmore and more exercised

as a way to support the financing of public transport infras-tructures (Ryan, 1999; Rybeck, 2004;Smith and Gihring,2006;

Al-Mosaindetal.,1993;BollingerandIhlanfeldt,1997;Bowesand

Ihlanfeldt,2001;Debrezionetal.,2007,2011;HessandAlmeida,

2007).Underpinningthispolicypracticeisatheoretical conjec-ture that publicly invested transport facilities adds significant values to the nearbyprivately owned land plots by improving theirspatialaccessibilitiestothetransportnetwork.Thiskindof public-investment-triggeredprivatelandvaluebettermentisa typ-icalinstanceofpositiveexternalitiesthatcouldbeoffsetthrough propergovernmentintervention(Pigou,1920).

Nonetheless, land value taxation remains unimplemented

withintheUK,eventhoughsomecloselyassociatedfiscal interven-tionsdoexistintheBritishtownplanningpractice.Forexample, section(106)ofthe1990TownandCountryPlanningActallows local planning authorities to charge developers, on a case-by-case basis and often by negotiation, a so-called section (106) paymenttocompensate for thepotentialnegative externalities (e.g.,congestionand crowdedness)of newdevelopmentonthe local community (The UK Parliament, 1990). Later, the Barker

ReviewofLandUsePlanning (2006)waslargelycritical of

sec-tion (106) for its vagueness in concept and inconsistencies in practice.ThecommunityInfrastructurelevy(CIL)wasintroduced inthe2008PlanningActtopartiallyreplacesection(106)(TheUK

Parliament,2008).

Likelandvaluetax,section(106)andCILarebothpublic finan-cialmeasuresintendedforexternalities,hencePigovianbynature. However,LVTdiffersfromsection(106)andCILinbeinga bet-termenttax,whichtriestocapturethepositiveexternalitiesof communityinvestmentinlocalpublicinfrastructures(Leeetal., 2013). By comparison, the two types of planning charges are employedtocompensateforthepotentialnegativeexternalities ofnewpropertydevelopmentswithrespecttothelocalhousing andinfrastructurecapacities.Theyarethusessentiallythesame

Y.Wangetal./LandUsePolicy42(2015)381–391 383 thingaswhatiscalled“impactfee”intheUS(see,e.g.,Ihlanfeldt

andShaughnessy,2004).

GiventhesubtleandyetimportantdifferencebetweenLVTand planningcharges,itperhapsmakesmoresensetolookatLVTin ref-erencetotheexistingUKtaxationsystem.2_{Forexample,Maxwell}

andVigor(2005)suggestsubstitutingLVTforcounciltaxandthe

stampduty. Theyargue that LVT is a levyonland, while both thestampdutyandcounciltaxareestimatedbypropertyvalue andareapropertytax.Taxingonpropertyinsteadoflandvalue involvesdisincentivesforhomeownerstomaintainandimprove theirhousingconditions–themoretheyinvestinmaintenanceand renovation,themorepropertytaxliable.Thisperspectiveresonates closelywithBourassa’s(1990,1992)earlierempiricalstudiesabout asimilartopicwithintheUScontext,whichidentifiedasignificant incentiveeffectofLVTvis-à-vispropertytaxation.

Researchdesign

Researchquestion

Levyingland-valuetaxinvolvesbothsubstantialpoliticalaswell astechnicalcomplexitiesandconstitutesaradicalreformtothe existingUKpublicfinanceregime.Ourresearchfocusesmoreonthe empiricalandtechnicalaspectsoftheissue,aimingtoexplorethe waystoassesslocalpublicinfrastructures’potentialcontribution totheadjacentlandvalues andtoaddresstheaccordingpolicy implications.

While theword “infrastructure”connotesa variety of facili-ties(usuallyofphysicalpresence),thispaperconcentratesonthe relationshipbetweenlandvaluesandpublictransport infrastruc-tureintheUK.Thisisbecauseofthegeneralconsensusnowadays regardingtheubiquitousandintimateinteractionsbetween trans-portandlanduseactivities(GeursandvanWee,2004).Another reason is that landvalue taxation, in recent decades,hasbeen increasinglyrationalisedasavaluecapturemechanismtofinance thedevelopmentand maintenance ofpublictransport facilities. Last,giventhecurrenteconomicclimate,publictransport infras-tructuresintheUKaretypicallyshortoffundingandthusinneed ofstrengthenedfiscalsupport(Lucas,2006).

Ourspecificresearchquestioncentresonhowtoassessthe spa-tialrelationshipsbetweenthelocalpublictransportinfrastructures and thelandvalues ofnearbyresidential properties.A concep-tual issue is that housing sub-markets are a salient feature of theBritishlocalrealestate sector(Orford,2000).A correspond-ingmethodologicalframeworkneedstobeinplacetocapturethe latentheterogeneitieswithregardtothecharacteristicsof differ-entneighbourhoodenvironments,divergentpropertypricelevels, andthevaryingrelationsbetweentheirimplicitlandvaluesand thenearnesstopublictransportlocations.

Ahedonicapproach

Given our research question, we employ a hedonic regres-sionapproachasthebasicmodellingmethodinthisstudy.While

Rosen’s(1974) seminal theoreticalpaper recommended a

two-stageregressionprocedure,forthispolicy-orientedpaper,weadopt areduced-formversionoftheRosenoriginaland,asshowninEq.

(1),assumea linearsemi-logfunctionforminthefirststageof hedonicregression,whichallowsustosimplifythesecondstageby directlyvaluingthebusstoplocationsbasedonthecorresponding

2_{Actually,landvaluetax(LVT)isalsooftencalledsingletax,becauseaccording}

toHenryGeorge,thecollectionofLVTshouldreplaceanyothertaxationschemes,

suchasthoseonincomesandconsumptions.

coefficientestimates (see a similarapplication,for example,by

Heikkilaetal.(1989),p.223):

log(p)=F(H,Y,W,L,ε) (1)

wherepdenotestheproperty’ssaleprice,ofwhichthenaturallog isafunctionofH,Y,WandL,plusanerrorterm,ε.Hstandsfora setofhedoniccontrolvariables,eachofwhichcorrespondstoan attributeoftheobservedproperty,intermsofwhetheritisfreehold (r),newlybuilt(n),detached(d),semi-detached(s),orterraced(t), floorarea(f),andhowfarthepropertyislocatedfromthecentral businessdistrict(z).HmaybespecifiedasEq.(2):

H={r,n,d,s,t,f,z} (2)

Yrepresentsanothersetofdummy-codedvariablescapturing theyearinwhichanobservedsaletransactiontookplace.Thisis intendedtoadjustfortemporaleffects,suchasshortterm property-priceinflationinthelocalmarket,withXdenotingthetotalnumber ofyearsunderobservation.Ifthefirstyearisnotedasyear0,we haveEq.(3):

Y={Yu|u=0,1,2,...,X−1} (3) Wconsistsofaseriesofdummy-codedvariables,each indicat-ingalocaljurisdictionwithinwhichapropertyislocated.These variables captureaveragelocal environmentaleffects related to educationalandrecreationalamenitiesaswellastheoverall rep-utationofthearea.AssumingatotalofMjurisdictionswithinthe studyarea,oneofwhichisdenotedasareferencejurisdiction,W0,

wemaydefineWasfollows:

W={Wv|

v

=0,1,2,...,M−1} (4) ItshouldbenotedthatthemodelspecificationasperEqs.(4)and (5)maybeconsideredfollowinga‘discrete-spaceexpansion’

pro-cess(JonesandBullen,1994,p.254),wherebytheconstanttermof

aregressionequationisexpandedintothe(X−1)+(M−1)dummy variables.

L={ı} (5)

LinEq.(5)representsasetoftargetvariables,whichrelatedirectly tothe locationof land beneath a property. Thesevariables are supposedtomeasurespatialaccessibilityandproximityto pub-lictransportinfrastructure.WeassumeinthispaperthatLconsists ofonlyoneelementı.ıinEq.(5)measurestheaggregatenumber ofpublictransportnodes(e.g.,trainstations,busstops,airport ter-minals)withinabufferorcatchmentareaofanobservedproperty location.3

Finally,acoupleofstandardeconometricassumptionsare asso-ciatedwiththeerrorterm,ε.First,weassumeindependenceor zeroautocorrelationintheobservedvaluesofε.Nevertheless,data collectedintherealworldarelikelytosufferfromspatialaswell astemporalautocorrelation,dependingonhowthecollectionis conducted.Second,weassumeasingleconstantvarianceinthe errortermornon-heteroskedasticity.However,thisassumptionis alsosubjecttoposthoctest,giventhathousingsub-marketsarean inherentfeatureoftheUKlocalrealestateindustryandtherefore thepossibilityofspatialheterogeneityinimplicitpricesbetween sub-markets.

3_{Itneedstobeacknowledgedthatrecentyearshaveseensomehighly}

sophis-ticatedaccessibilitymeasures(e.g.,Ferrarietal.,2012).Whiletheseinnovative measuresarenotthecentraltopicofthispaper,theycanbeveryusefulforfuture research.

Multi-levelmodelling

Multilevelmodellingmaybeseenasageneralisedversionof lin-earregression(Duncanetal.,1998).Amultilevelmodellinganalysis combinesbothindividualandcontextualparameters,suchasthe geographicaljurisdiction(e.g.,electoralwards)inwhichaproperty islocatedandtheyearswhenapropertyistransacted.Multilevel modelsareintendedtoassessthecorrelationbetween observa-tionswithinthesame level ofanalysis and attempttocapture thesevariationsbyallowingtheregressionintercepttovaryacross, forexample,thejurisdictionsandtheyearsofsale.Thisapproach isknownasa“randomintercept”multi-levelmodellingmethod

(JonesandBullen,1994).

ˇ0,v,u=ˇ0+ v+˚v,u (6)

ˇ0inEq.(6)istheaverageinterceptforalloftheobserved prop-ertiesacrossdifferentjurisdictionsandsoldindifferentyears.v and˚v,uaretwoindependenterrorcomponents:vmeasuresthe extenttowhichtheregressioninterceptforobservationswithin agivenjurisdiction,Wv (

v

=0,1,2,...,M−1),deviatesfromthe overallaveragedconstantterm,ˇ0.Likewise,˚v,u measuresthe differencebetweenˇ0andtheinterceptforobservations,notonly withinWv,butalsosoldinagivenyear,Yu(u=0,1,2,...,X−1).

Wedeploythismultilevelspecificationtocapturebothspatial andtemporallandvaluevariations,asperFig.1.InFig.1(a),thedata aregroupedgeographicallyintheupmostlevelbyelectoralward (ourproxyforhousingsub-markets),hopedtoaddresspotential issuesofspatialautocorrelationandheterogeneity.Thedifferent yearsofhousesalesarethendefinedasthesecondlevelofanalysis, inviewofdealingwithpotentialtemporalautocorrelation.Fig.1(b) presentsanalternativepanelstructure,wherewardremainsthe firstlevelofanalysisandeachindividualpropertyisnowsituated atthenextstage.However,theyearofsaleforeverypropertyis furtherdefinedasatertiarylevel.Thisalternativehierarchyis rele-vantwhenadatasetcontainsmanypropertiesthathavebeensold multipletimesduringtheperiodofobservation.

Quantilecalibration

The method of quantile regression is firstly introduced by

KoenkerandBassett(1978).Quantileregressionessentially

esti-matesmultiplequantiles(e.g.10%,50%or75%)inthedependent variable’sconditionaldistribution.Asaresult,theapproachtends togeneratemorerobustcoefficientestimatesandprovidemore comprehensiveinformationaboutthedistributionoftheresponse variablethanconventionalregressiontowardsthemean(Koenker,

2005).

Inthecaseofthispaper,weareconcernedwiththe substan-tialpricedifferentiationfeaturingmanyUKlocalpropertymarkets

(Orford,2000).We hypothesisethat propertiesatthe highend

ofalocalrealestatemarketmayexhibitsystematicallydifferent transport-landrelationsthan thoseat thelowerend. In econo-metricterms,this leadstonon-constantconditionalvariance in log(p)(i.e.,thenaturallogofpropertyprice),henceaviolationof thehomoscedasticityassumption.Toadjustfortheheterogeneous relationsbetweenpropertypriceandthenumberofnearbypublic transportfacilities,weapplyabivariatequantileregressionmethod inourposthocrobustnesstest:

log(p)i_q=G(ı,ε) (7)

wherei(i=1,2,...,q)standsfortheithquantileintheconditional distributionoflog(p),ifthedistributionisdividedintoatotalofq equalintervals.

Fordemonstrationpurposes,assumeK(log(p))asthekernel densityfunctionoflog(p).Oneshallseethatthequantileestimation

isdifferentfromtheconventionalmeanestimation.Specially,to estimatethemeanorexpectedvalueoflog(p),wehave

E(log(p))=

log (p)max log(p)min

log(p)×K(log(p))dlog(p) (8)

The quantile estimation is however different by solvingthe belowequationinreferencetolog(p)i_q:

log (p)i_q log(p)min

K(log(p))d log(p)= i

q (9)

A quantile coefficient, given a linear function form, can be workedoutthrough linearprogramming(KoenkerandHallock, 2001).Acquiring alargenumber of quantilecoefficients in this wayenablesustoconductbootstrappingre-samplingandgenerate anasymptotickerneldensitydistributionsuchasK(log(p)), allow-inganassessmentoftheasymptoticstandarderrorandconfidence intervalforeveryquantilecoefficient(MachadoandMata,2005).

ThecaseofCardiffbus

Thelocalbackground

TheWelshCapitalcityofCardiffisourstudysite,becausethecity exemplifiesanarrayofUK-wideissueswithregardtothefinancing oflocalpublictransport.PublicservicesintheUKhaveexperienced widespreadfundingcutsandausteritymeasuressince2008.Local publictransportisoneoftheseverelyaffectedsectors.Forexample, inCardiff,thelocalcouncil-ownedCardiffbussystemwitnesseda

£

0.6millionfundingcutbytheWelshGovernmentin2012,leading toasecondincreaseinbusfaresinceOctober2011(WalesOnline,

2012).

Aselsewhere,lackoffundingforpublictransportimplicatesa numberofpotentialissuesinCardiff.Inflatedbusfare,for exam-ple,islikelytodiscourageenvironment-friendlytravelbehaviour andpushpeoplebackintotheircars(NewmanandKenworthy, 1999).Internationalexperiencealsoshowsthatrestrictedpublic transporttendstomakecommutingcostparticularlyunaffordable forthelowerincomepopulation, exacerbatingthe“spatial

mis-match” betweenwhere theylive andwhere theycanfind jobs

(Kain,1992).Business opportunitiescanalsobeaffectedifthey

becomelessaccessibleduetoashrinkingsupplyofpublic trans-port facilities. Allof theseissues, among many others, alert us tothechallengeoffinancingpublictransportinadireeconomic climate.

Levyinglandvaluecapturepropertytaxappearstobea prom-isingsolution.InthecaseofCardiffBus,asinglefareof

£

1.70only accountsforthevalueofbusservicetoapassenger,whileaproperty ownerwholivesadjacenttotheCardiffbusnetworkdoesnot nec-essarilypaythebusfareinsofarasnotusingtheservice.However,

fromaGeorge(1879)perspective,theCardiff Busnetworkmay

havepromotedtheaccessibilityofitsnearbyrealestateproperties, hencecontributingtoanappreciationofeachproperty’svalueby ameasurablepercentage.Ifthisresearchhypothesiscanbe sub-stantiatedand evidenced,a landvaluecapturetaxation scheme becomesjustifiable.

Thedata

Thedatasetusedinthisstudycontainsobservedpropertyprices andbusstoplocationsmainlywithincentralCardiffbetween2000 and2009(seeFig.2).Ourstudyareacovers12localelectoralwards. TheareacontainstypicalVictorianandEdwardianterracedhouses, flatsinconvertedbuildingsandsuburbanstylesemi-detachedand

Y.Wangetal./LandUsePolicy42(2015)381–391 385

Fig.1.Cross-sectional(a)vsmultilevelpanel;(b)structuresforpropertydataanalysis.

Notes:adaptedfromDuncanetal.(1998).

Table1

Definitionofvariablesanddescriptivestatistics.

Continuousvariables Definition Mean St.dev.

p PropertysalepriceinBritishpoundsterling(£) 143922 87264

log(p) Naturallogarithmofpriceofthepropertywhensold 11.725 0.5

ı300m Numberofbus-stopswithin300metres(m)offtheproperty 7.4 3.7

ı400m Numberofbus-stopswithin400metres(m)offtheproperty 13.3 5.3

ı500m Numberofbus-stopswithin500metres(m)offtheproperty 20.7 7.4

ı750m Numberofbus-stopswithin750metres(m)offtheproperty 45.2 14.8

ı1000m Numberofbus-stopswithin1000metres(m)offtheproperty 77.7 24.4

ı1500m Numberofbus-stopswithin1500metres(m)offtheproperty 167.7 57.5

F Floorareaofapropertyinsquaremetres(m2_{) 105.2 48.9}

Z Distancetothecentralbusinessdistrictinmetres(m) 3225.3 1408.7

Categoricalvariables Definition Proportion

r 1ifpropertyisonfreeholdtenure,0otherwise 89.7%

n 1,ifpropertyisnewlybuiltwhensold,0otherwise 3.8%

Propertytype

Flatasathereferencecategory 4.1%

d 1,ifpropertyisadetachedhouse,0otherwise 12.0%

s 1,ifpropertyisasemi-detachedhouse,0otherwise 25.6%

t 1,ifpropertyisaterracedhouse,0otherwise 58.3%

Year

Y0 1,ifpropertywassoldin2000,0otherwise(referencecategory) 11.2%

Y1 1,ifpropertywassoldin2001,0otherwise 13.4%

Y2 1,ifpropertywassoldin2002,0otherwise 14.5%

Y3 1,ifpropertywassoldin2003,0otherwise 12.6%

Y4 1,ifpropertywassoldin2004,0otherwise 12.3%

Y5 1,ifpropertywassoldin2005,0otherwise 9.6%

Y6 1,ifpropertywassoldin2006,0otherwise 12.9%

Y7 1,ifpropertywassoldin2007,0otherwise 12.4%

Y8 1,ifpropertywassoldin2008,0otherwise 1.1%

Ward

W0 1,ifapropertyislocatedinCyncoed(referencecategory) 11.5%

W1 1,ifpropertyislocatedinAdamsdownorButetown,0otherwise 12.1%

W2 1,ifpropertyislocatedinCathays,0otherwise 2.4%

W3 1,ifpropertyislocatedinHeath,0otherwise 1.6%

W4 1,ifpropertyislocatedinLlanishen,0otherwise 1.3%

W5 1,ifpropertyislocatedinSplottorRumney,0otherwise 23.1%

W6 1,ifpropertyislocatedinPenylan,0otherwise 15.0%

W7 1,ifpropertyislocatedinPentwyn,0otherwise 17.6%

W8 1,ifpropertyislocatedinPlasnewydd,0otherwise 13.9%

Fig.2.PropertiesandbusstopsincentralCardiff.

purpose-buildflats.Over 9700residentialpropertieswithinthe areahavebeensoldatleastoncebetween2000and2009, pro-viding12,887salerecords,accordingtotheLandRegistry.Apart fromthesale records,LandRegistry alsocarries detailed infor-mationregardingtheseproperties,includingtheirdwellingtypes

(detached,semi-detached,terraceorflat),tenures(freeholdand leasehold),andwhethera propertywasa newbuild. Floorarea wascalculated forevery propertyin thesample usinga meth-odologydescribed in Orford (2010). The bus stoplocationsare retrievedfrom the2007NationalPublicTransportAccessNode

Table2

Numberoftimesapropertyissoldwithinthe9-yearperiodofthedata.

Numberoftimesapropertyissoldwithinthe9-yearperiodofobservation

1 2 3 4 5 6 7

Y. Wang et al. / Land Use Policy 42 (2015) 381–391 387 Table3

Resultsofordinaryleastsquares,log(p)asdependentvariable.

Model1 Model2 Model3 Model4 Model5 Model6

Within300m Within400m Within500m Within750m Within1000m Within1500m

ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e.

Constant 10.506*** _{0.025 10.479}*** _{0.027 10.438}*** _{0.028 10.417}*** _{0.034 10.343}*** _{0.039 10.269}*** _0.048 Freehold(r) 0.120*** _{0.009 0.121}*** _{0.009 0.123}*** _{0.009 0.126}*** _{0.009 0.127}*** _{0.009 0.125}*** _0.009 New-built(n) 0.228*** _{0.013 0.230}*** _{0.013 0.232}*** _{0.013 0.230}*** _{0.013 0.237}*** _{0.013 0.217}*** _0.013 Detached(d) 0.651*** _{0.016 0.654}*** _{0.016 0.654}*** _{0.016 0.647}*** _{0.016 0.644}*** _{0.016 0.645}*** _0.016 Semi-detached(s) 0.468*** _{0.014 0.471}*** _{0.014 0.469}*** _{0.014 0.465}*** _{0.014 0.464}*** _{0.014 0.465}*** _0.015 Terraced(t) 0.360*** _{0.014 0.361}*** _{0.014 0.359}*** _{0.014 0.356}*** _{0.014 0.354}*** _{0.014 0.357}*** _0.014 Floorarea(f) 0.004*** _{0.000 0.004}*** _{0.000 0.004}*** _{0.000 0.004}*** _{0.000 0.004}*** _{0.000 0.004}*** _0.000 DistancetoCBD(z) 0.035*** _{0.004 0.038}*** _{0.004 0.042}*** _{0.004 0.046}*** _{0.005 0.055}*** _{0.005 0.066}*** _0.007 Salein2001(Y1) 0.112*** 0.009 0.110*** 0.009 0.111*** 0.009 0.112*** 0.009 0.113*** 0.009 0.110*** 0.009 Salein2002(Y2) 0.301*** 0.009 0.297*** 0.009 0.297*** 0.009 0.297*** 0.009 0.299*** 0.009 0.295*** 0.009 Salein2003(Y3) 0.526*** 0.009 0.522*** 0.009 0.524*** 0.009 0.525*** 0.009 0.522*** 0.009 0.520*** 0.009 Salein2004(Y4) 0.694*** 0.009 0.693*** 0.009 0.693*** 0.009 0.694*** 0.009 0.693*** 0.009 0.691*** 0.009 Salein2005(Y5) 0.781*** 0.010 0.778*** 0.010 0.776*** 0.009 0.778*** 0.009 0.777*** 0.009 0.776*** 0.010 Salein2006(Y6) 0.791*** 0.009 0.789*** 0.009 0.789*** 0.009 0.791*** 0.009 0.791*** 0.009 0.789*** 0.009 Salein2007(Y7) 0.842*** 0.009 0.840*** 0.009 0.840*** 0.009 0.841*** 0.009 0.840*** 0.009 0.839*** 0.009 Salein2008(Y8) 0.858*** 0.023 0.857*** 0.023 0.861*** 0.022 0.860*** 0.022 0.861*** 0.022 0.861*** 0.022 Adamstown(W1) −0.512*** 0.014 −0.508*** 0.014 −0.502*** 0.014 −0.499*** 0.014 −0.488*** 0.014 −0.465*** 0.015 Splott(W2) −0.513*** 0.012 −0.507*** 0.012 −0.493*** 0.012 −0.486*** 0.013 −0.464*** 0.014 −0.430*** 0.017 Cathays(W3) −0.196*** 0.020 −0.194*** 0.020 −0.186*** 0.020 −0.182*** 0.020 −0.164*** 0.020 −0.152*** 0.021 Heath(W4) −0.142*** 0.019 −0.137*** 0.019 −0.139*** 0.019 −0.143*** 0.019 −0.146*** 0.019 −0.144*** 0.019 Llanishen(W5) −0.240*** 0.024 −0.250*** 0.024 −0.257*** 0.024 −0.262*** 0.025 −0.269*** 0.025 −0.276*** 0.025 Penylan(W6) −0.064*** 0.011 −0.064*** 0.011 −0.062*** 0.011 −0.051*** 0.011 −0.039*** 0.011 −0.018 0.013 Pentwyn(W7) −0.648*** 0.010 −0.647*** 0.010 −0.643*** 0.010 −0.644*** 0.010 −0.638*** 0.010 −0.638*** 0.010 Plasnewydd(W8) −0.235*** 0.014 −0.230*** 0.014 −0.225*** 0.014 −0.229*** 0.014 −0.229*** 0.014 −0.218*** 0.014 Pontprennau(W9) −0.500*** 0.020 −0.502*** 0.020 −0.502*** 0.020 −0.506*** 0.020 −0.508*** 0.020 −0.505*** 0.020

Numberofbusstops(ı) 0.003*** _{0.001 0.003}*** _{0.001 0.003}*** _{0.000 0.001}*** _{0.000 0.001}*** _{0.000 0.001}*** _0.000

Samplesize 9655 9650 9656 9653 9659 9669 R2 _{0.850 0.850 0.850 0.851 0.850 0.849} F-test(df) 2176(25) 2179(25) 2185(25) 2195(25) 2186(25) 2167(25) p-Value 0.000 0.000 0.000 0.000 0.000 0.000 *p<0.1;**p<0.05. ***_p<0.001.

Table4

TestingautocorrelationandhomoscedasticityinOLSresults.

Model1 Model2 Model3 Model4 Model5 Model6

Within300m Within400m Within500m Within750m Within1000m Within1500m Independenceofε Durbin–Watson 1.773 1.777 1.779 1.779 1.779 1.776 p-Value 0.000 0.000 0.000 0.000 0.000 0.000 Spatialautocorrelation Moran’sI 0.150 0.150 0.149 0.149 0.150 0.149 Expected −0.0001 −0.0001 −0.0001 −0.0001 −0.0001 −0.0001 Standarddeviation 0.0004 0.0004 −0.0004 0.0004 0.0004 0.0004 p-Value 0.000 0.000 0.000 0.000 0.000 0.000

Homoscedasticity BreuschandPagan(1979)test

2_{(df) 0.233(1) 0.101(1) 0.533(1) 0.887(1) 1.503(1) 0.612(1)}

p-Value 0.6293 0.7512 0.4651 0.3461 0.2202 0.4341

(NaPTAN-v2.2)dataset(Department forTransport,2007).These arealsoshowninFig.2.Thenumberofbusstopswithinspecified radiiofeachproperty(i.e.,300m,400m,500m,750m,1000m,and 1500m)wascalculatedusingArcGIS.Table1presentsasummary ofthevariablesincludedinthesampleofpropertiesinthedataset.

Table2alsoshowsthatthisisbroadlyacross-sectionalratherthan

paneldataset,asmorethan75%ofthepropertieshaveonlybeen soldonceduringthe9-yearperiod.

Modelresults4

OLSresults

Table3presentstheresultsofsixordinaryleastsquare(OLS)

regressions based on the conventional hedonic approach

pre-scribedin“AHedonicApproach”section.Thedependentvariable ineveryregressionisthenaturallogarithmofprice(log(p))andall ofthesixmodelsattempttocapturetheeffectofCardiffBuson landvalueviaı,whichmeasuresthenumberofbusstopswithin differentwalkableradii(i.e.,300m,400m,500m,750m,1000m, and1500m)aroundeachpropertycontainedinthedataset. Fol-lowingBelsleyetal.(1980)avarietyofregressiondiagnostictests wereperformedontheOLSmodelsinordertocheckwhetherany oftheregressionassumptionshadbeenviolated.Theseincluded identifyingoutliersthatmayhaveadisproportionateinfluenceon themodels,andremovingthecorrespondingobservationsif neces-sary;checkingforseriousmulti-collinearityinthemodels;testing thenormalityoftheerrorterm;andcheckingforheteroscedasticity andautocorrelationintheerrorterm.Thelattertestsarediscussed inmoredetailinalatersection.

Model1,forexample,includestheexplanatoryvariablewith regardtothenumberofbusstopswithin300maroundeach prop-erty.Theestimatedparametercorrespondingtothisvariableshows that theeffect of Cardiff Buson property priceor, more accu-rately, onland value as reflected in property price,is positive andstatisticallysignificantatthe1%significancelevel. Inother words,themorebusstopstherearearoundaproperty,thehigher thevalueoflandbeneaththatproperty.Similarfindingsarealso discerniblefromtheotherregressionsestimatingtheeffectof num-berof busstopswithin400m, 500,750m,1000mand 1500m, respectively.

Bybacktransformingthemagnitudeoftheestimated coeffi-cientwithregardtothenumberof busstopswithin300m, we cancalculatethemarginalincreaseinlandvalueasaresultof pla-cingeveryextrabusstoparoundaproperty.Inpercentage, this

4 _{OLSresultsareestimatedinIBMSPSSStatistics20,whilethemulti-levelanalysis}

isconductedwithMLWinv.3.20(Rasbashetal.,2012).Thequantileregressionis

exercisedusinganR/SPSSinterfacebasedontheoriginal“quantreg”Rcodesby

Koenker(2007).

addedlandvalueequalsto(e0.003_{−1)×100≈0.3%.Examinationof}

thecoefficientsofthenumberofbus-stopswithindifferentbuffer zonesaroundpropertyinTable3suggeststhattheeffectofbus stopswithindistanceisrelativelystableandstatistically signifi-cant.Thelandvaluebenefitofeveryadditionalbusstopwithina circularcatchmentarealargerthan500mbyradiusisabout0.1% ofthecorrespondingpropertyprice.Thefigurerisesto0.3%ifthe sizeofcatchmentshrinksto500morlessbyradius.Overall,all modelsshowthattheavailabilityofpublictransportinfrastructure cansignificantlypromotelandvalueand therebyraiseproperty price.

Thecoefficientofz,thedistancetoCardiff’scentralbusiness district(CBD),isalsopositiveandstatisticallysignificant. Accord-ingtosomestudies,thisfindingiscounter-intuitiveandagainst theconventionalwisdomabouturbanspatialstructure.Per clas-sicurbaneconomictheory(e.g.,Anasetal.,1998),propertyprices shoulddeclinealongsideincreaseintheproperties’distancetocity centre.However,previousstudieshavealsoprovidedseveral expla-nationsforthepositiveinfluenceofdistancetoCBDonproperty price.Forexample,theassumptionofa declininglandvalueas distanceincreasesfromCBDisbasedontheadoptionofa mono-centriclocationchoicemodel(DubinandSung,1987),whileCardiff appearstobearatherpolycentriccity.

Floorareaisalsoapositiveandstatisticallysignificantfactorin termsofitsimpactonpropertyprice.Theeffectoffloorspaceis consistentacrossallsixmodelspresentedinTable3.Followinga backtransformationoftheparameterwithrespecttofloorspace, wefindthateveryadditionalsquaremetreinapropertyincreases itsvalueby(e0.004_{−1)×100≈0.4%.}

Wecapturemeanspatialvariationinpropertypricebyusinga seriesofdummy-codedvariablesrepresentingthewardsinwhich eachpropertyislocated.ThewardnamedCyncoedisusedasthe referencecategoryasitistheareawiththehighestaverage prop-ertypriceinthedataset.Allmodelsshowasignificantdifferencein propertypricefromCyncoed,althoughthelastregression(model

6inTable3)indicatesnosignificantdifferenceinpropertyprice

betweenCyncoedandPenylan.

Allothercoefficientshavetheexpectedsignsandagreewith conventionalfindingsinthehedonicliterature(Edmonds,1984). Forexample,apropertyunderafreeholdtenureislikelytoshowa higherpricecomparedwithaleaseholdproperty.Similarly,anewly builtpropertytendstohavemoremarketvaluethananaged prop-erty.Detachedpropertiesexhibitthehighestprices,followedby semi-detachedpropertiesandflats,ofwhichthelatterisdefined asthereferencepropertytypeinthisanalysis.Finally,thedummy variableswithregardtopricedifferencesduetothecalendaryear whenapropertywassoldareallsignificantlydifferentfromzero. Theyearof2000isusedasthereferenceyear,whiletheremaining coefficientsindicateaconstantincreaseinpropertypriceovertime, partlyduetoinflationinpoundsterlingandpartlyduetodynamics inthelocalhousingmarket.

Y.Wangetal./LandUsePolicy42(2015)381–391 389 Multilevelresults

Asmentioned earlier, ordinaryleast square(OLS) regression mayinvolvepotentialissuesrelatedtospatialandtemporal auto-correlations. In terms of spatial autocorrelation, the prices of propertieswithinasamejurisdiction(i.e.,electoralwardsinour data)arelikelytobemoresimilarthanthoseoutside.Intermsof temporalautocorrelation,propertiessoldwithinthesameyearmay showaconvergenceinsalepricevis-à-visthosetransactedwithin adifferentyear.Toaccountforboththegeographicaswellas tem-poralautocorrelations,ourOLSmodelswouldhavetobeexpanded extensivelytoaccommodate(M−1)×(X−1)interactionfactors.In contrast,multilevelmodellinganalysisappearstobeamore effi-cientalternativetoaddresstheissueofautocorrelation(Jonesand

Bullen,1994).

Table4identifiesaproblemofautocorrelationunderlyingall

thesixOLSmodels.TheDurbin–Watsontestsuggestsanoverall significantserialinterdependenceoftheerrorterms(ε)inevery OLSmodel.BecausetheDurbin–Watsonresultismoresensitive totemporalautocorrelation,wefurtherexerciseaMoran’sItest

(Anselin,1988),ofwhichtheestimatesalsoconfirmapresenceof

asignificantalbeitweakspatialautocorrelation(Moran’sI_≈0.15). However,theBreuschandPagan(1979)testforthewholemodel suggeststhatheteroscedasticityisnotaproblemintheerrorterms andtheyhaveconstantvariance.Toaddresstheautocorrelation problem,sixmultilevelregressions(models7–12)arefurther con-ducted.Sinceover75%ofthesampledpropertiesaresoldonlyonce between2000and2009,weestimatethemultilevelmodelsin ref-erencetothecross-sectionalhierarchyshowninFig.1(a)instead ofthepanelstructureasperFig.1(b).

Table5illustratestheresultsofourmultilevelmodelling

anal-ysis. Both theward-by-ward (2

ward) and year-to-year variance

(2

year)arestatisticallysignificant,confirmingtheOLSfindingthat

therearegeneralisabledifferencesacrosswardsandyearsinterms ofpropertyprice.Around19%oftheaggregatevarianceinproperty price(2

property)canbeattributedto2ward,comparedwitharound

56%to2

year.Nevertheless,ı,which measurestheimpactofbus

stopsonnearbylandvalue,remainsstableandisthusunbiased. ThisessentiallyconfirmstherobustnessoftheOLSestimates,even infaceoftheidentifiedspatialandtemporalautocorrelations.

Quantileresults

Table6reportstheresultsofourquantilebivariateregressions.

Asnotedabove,weconductthisquantileanalysismainlyasapost hoccalibrationoftheOLSestimates,incaseprice-based hetero-geneitiesleadtoabiasedcoefficientmeasureofı.We thususe log(p)asthedependentvariableand ıastheonlyindependent variabletogaugethenumberofbusstopswithindifferentwalkable distances,from300mto1500m,aroundeveryobservedproperty location.

Generallyspeaking, Table6 indicatesrelativelyweakand/or insignificantassociationsbetweenthenumberofbus stopsand propertypricesatthe10%and20%quantiles,wheretheobserved propertypricesarebelow

£

74,000inthedataset.Incontrast,the strongestandmostsignificantcorrelationscanbefoundfor proper-tiesatthe80%quantile,pricedaround

£

195,000.Thoseevenmore expensivepropertiesatthe90%quantile(i.e.,

£

250.000),however, seemtobenefitnomorefromthenumberofnearbybusstopsthan thoseatthe80%quantile,eventhoughtheytendtobebetteroff comparedwithallpropertiesbelowthe80%quantile,especially whenweincreasethesearchradiustomorethan750m.

WhileconfirmingtheoverallrobustnessofOLSestimateswith regardtothemeanofı,theresultsofourquantileanalysisdo

sug-gestıtobesystematicallyvolatileacrossdifferentpricesegments. Table

5 Results of multi-level modelling, log( p ) as dependent variable. Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Within 300 m Within 400 m Within 500 m Within 750 m Within 1000 m Within 1500 m ˇ0 s.e. ˇ0 s.e. ˇ0 s.e. ˇ0 s.e. ˇ0 s.e. ˇ0 s.e. Constant 10.735 *** 0.070 10.710 *** 0.071 10.671 *** 0.071 10.660 *** 0.073 10.590 *** 0.075 10.520 *** 0.079 Freehold ( r ) 0.116 *** 0.009 0.117 *** 0.009 0.119 *** 0.009 0.122 *** 0.009 0.123 *** 0.009 0.121 *** 0.009 New-built ( n ) 0.221 *** 0.013 0.223 *** 0.013 0.224 *** 0.013 0.221 *** 0.013 0.226 *** 0.013 0.208 *** 0.013 Detached ( d ) 0.659 *** 0.016 0.662 *** 0.016 0.663 *** 0.016 0.655 *** 0.016 0.653 *** 0.016 0.654 *** 0.016 Semi-detached ( s ) 0.476 *** 0.014 0.480 *** 0.014 0.478 *** 0.014 0.473 *** 0.014 0.472 *** 0.014 0.474 *** 0.014 Terraced ( t ) 0.369 *** 0.014 0.371 *** 0.014 0.370 *** 0.014 0.366 *** 0.014 0.364 *** 0.014 0.367 *** 0.014 Floor area ( f ) 0.004 *** 0.000 0.004 *** 0.000 0.004 *** 0.000 0.004 *** 0.000 0.004 *** 0.000 0.004 *** 0.000 Distance to CBD ( z ) 0.035 *** 0.004 0.038 *** 0.004 0.042 *** 0.004 0.045 *** 0.005 0.054 *** 0.005 0.065 *** 0.007 Number of bus stops ( ı ) 0.003 *** 0.001 0.003 *** 0.001 0.003 *** 0.000 0.001 *** 0.000 0.001 *** 0.000 0.001 *** 0.000 2 ward 0.034 ** 0.020 0.033 ** 0.020 0.033 ** 0.020 0.033 ** 0.020 0.033 ** 0.020 0.033 ** 0.020 2 year 0.099 *** 0.016 0.099 *** 0.016 0.098 *** 0.016 0.099 *** 0.016 0.098 *** 0.016 0.099 *** 0.016 2 property 0.044 *** 0.001 0.044 *** 0.001 0.043 *** 0.001 0.043 *** 0.001 0.044 *** 0.001 0.044 *** 0.001 Contribution of 2 ward to 2 property 0.192 0.188 0.190 0.189 0.189 0.188 Contribution of 2 year to 2 property 0.559 0.563 0.563 0.566 0.560 0.563 Sample size 9655 9650 9656 9653 9659 9669 * p < 0.1. ** p < 0.05. *** p < 0.001.

Table6

Resultsofquantilebivariateregressions,log(p)asdependentvariableandıasindependentvariable.

Quantile ı300m ı400m ı500m ı750m ı1000m ı750m

ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e. ˇ s.e.

10% −0.004 0.003 0.001 0.002 0.007*** _{0.002 0.004}*** _{0.001 0.002}*** _{0.000 0.001}*** _0.000 20% 0.004 0.003 0.003* _{0.002 0.005}*** _{0.001 0.003}*** _{0.000 0.002}*** _{0.000 0.001}*** _0.000 30% 0.011*** _{0.002 0.007}*** _{0.002 0.007}*** _{0.001 0.003}*** _{0.001 0.002}*** _{0.000 0.001}*** _0.000 40% 0.013*** _{0.002 0.009}*** _{0.001 0.009}*** _{0.001 0.004}*** _{0.001 0.002}*** _{0.000 0.001}*** _0.000 50% 0.013*** _{0.001 0.013}*** _{0.001 0.009}*** _{0.001 0.004}*** _{0.000 0.003}*** _{0.000 0.001}*** _0.000 60% 0.010*** _{0.002 0.010}*** _{0.002 0.009}*** _{0.001 0.004}*** _{0.000 0.002}*** _{0.000 0.001}*** _0.000 70% 0.013*** _{0.002 0.013}*** _{0.002 0.008}*** _{0.001 0.003}*** _{0.000 0.002}*** _{0.000 0.001}*** _0.000 80% 0.020*** _{0.002 0.020}*** _{0.002 0.010}*** _{0.001 0.005}*** _{0.001 0.003}*** _{0.000 0.002}*** _0.000 90% 0.011*** _{0.002 0.011}*** _{0.002 0.008}*** _{0.001 0.005}*** _{0.001 0.003}*** _{0.000 0.002}*** _0.000 * _p<0.1. **p<0.05. ***_p<0.001.

Specifically,spatialproximitytoCardiffBusstopstendsto ben-efitpropertiesatthehighendofthelocalrealestatemarket.The strongestpositiveexternalitiescanbeobservedinpropertiesabove the80%pricequantile,witheveryadditionalbus stopwithin a 1500mbufferzone,forexample,contributingtoanincreaseby about0.22%inpropertysalepricethroughlandvaluebetterment. Thecorrespondingfigureforthecheaperpropertiesishalvedto around0.11%.

Policyimplications

Theresultsofourregressionanalysisbasedonempiricaldata fromCardiff havesomeimportantpolicyimplications.First and foremost,theoutcomesofourordinaryleastsquareregressionand multilevelmodellinganalysisprovideconvincingevidenceto sup-portaclassicGeorgisthypothesisinthecaseofCardiffBus,thata significantpartoftheaddedlocalpropertyvaluesdoescomefrom thelandbeneaththem,ormorespecifically,fromthelandplots’ geographicadjacencytothebusstoplocations.Thisfinding jus-tifiesapotentialpolicyinterventionintermsoffinancingCardiff Busthroughalandvaluetaxmechanism,giventhesubstantiated positiveexternalitiesyieldedbyCardiffBus.

Second,theresultsofourquantilecalibrationentailsomeeven moreintriguingpracticalinsights.Wefindthatthepositive exter-nalitiesofCardiffBusaredistributedunevenlyamongproperties atdifferentpricelevelsinthelocalrealestatemarket.Generally speaking,accordingtoTable6,propertiesatthehighend(atthe80% and90%quantiles)ofthemarkettendtobenefitmorethanthoseat thelowend(atthe10%and20%quantiles).Thisimplicatesa neces-sitytoexerciseprogressivelandvaluetaxation,wherebyproperties atdifferentpricelevelsneedtobetaxedatdifferentrates,sothat theunevendistributionofpositiveexternalitiescanbeaccordingly captured.Ourestimation,basedonthenumberofbusstopswithin a1500mradiusofeveryindividualpropertyincludedinoursample data,suggestsatentativelandvaluebettermenttaxrateof0.11% pernewbusstopforthefirsttierofpropertieswhicharepriced below

£

195,000and0.22%forthesecondtierofpropertieswhich areofhighermarketvalues.

Wenoticeasomewhatsimilarprogressivetaxationmechanism alreadyincorporatedinCardiff’sexistingcounciltaxsystem,which divideslocalresidential propertiesinto ninedifferentbands by theirestimatedvaluesandappliesincrementaltaxrates.Thereis thusapossibilityofintroducinganembryoniclandvaluetax ele-mentintothecurrentcounciltaxscheme,dependingonhowwe translatethequantilehedonicapproachfeaturedinthisstudyinto thecounciltaxationsystemusedinpracticeandalsoonwhethera largeenoughdatasetcoveringtheentireCardiffCounciljurisdiction willbecomeavailableinthenearfuture.

Third, our overall empirical analysis defies a conventional wisdomthatpublicinfrastructure alwaysservespublicinterest.

Arguably,thecase ofCardiffBusillustratesafree-ridescenario,

wherein the most wealthy property owners, intentionally or

unintentionally,endupextractingthevaluesofpubliclyfunded transport infrastructures. Asimilar findinghasalso beenmade recentlybyBanisterandThurstain-Goodwin(2011,pp.216–221), whosuggestlandvaluebettermentcreatedbytherailnetworks tobeevenmoreextensive.Inthissense,levyinglandvaluetax isnotonlytocaptureeconomicexternalities,butalsotoensure socioeconomicjusticeandfairness,aspertheEdwardiantradition.

Conclusionandfutureresearch

Inthispaper,weexplorethepotentialviabilityoflevyingland valuetaxwithinalocalUKcontext.Wefocusontheempiricaland technicalaspectsbyaskinghowtoassessthespatialisedrelations betweenthelocalpublictransportinfrastructuresandtheland val-uesofnearbyresidentialproperties.Weanswerthisquestionby studyingthecaseofCardiffBus.Basedonourmultileveland quan-tilehedonicanalysis,wefindstrongevidencewithregardtothe positiveexternalitiesofCardiffBusnetworktowardsthemarket valuesofnearbyresidentialproperties.Giventheuneven external-itydistributionbetweenpropertiesatdifferentpricelevels,wecall foraprogressivelandvaluetaxscheme.

Becauseofthepoliticalcontextofourstudy,weconsideraction researcha key directionof ourfuture research.We would like totakemore opportunitiesto useourresearchtoeducate and informthegeneralpublicaboutwhylandvaluetax(LVT)isan economicallyaswellassociallydesirableidea.Potential opposi-tionstoLVTareless likelyfromanefficiencyperspective,since mostclassicresearchhasalreadyconfirmedthatpurelytaxingon incomesfromlandwould notdistortresource allocation(Mills,

1981;Tideman,1982;Wildasin,1982).Morerecentresearchalso

showsthatitisactuallyeasierthanthoughttoimplementneutral ornon-distortionallandtaxation(Arnott,2005).Evenwitherrors inlandvaluation,thecollectionofLVThasbeenfoundtoresult innomore distortionsthan theconventionalproperty taxation scheme(Chapmanetal.,2009).ResistancestoLVTarethusmore likelyaboutthedistributionaleffectsoflandtaxation,orputsimply, regardinghowtosplitthebillsthatfundpublicinvestments. Con-troversialasthisquestionis,wehopeourcurrentstudyandfuture researchonlandvaluetaxwillhelpthevotersmakeaninformed decision.

Acknowledgements

The research reported in this paper is funded by the

BritishAcademy/LeverlulmeSmallResearchGrantinitiative(ref: SG122122).Allerrorslurkinginthepaperaretheauthors’.

Y.Wangetal./LandUsePolicy42(2015)381–391 391

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