On the nexus of air pollution and health expenditures: new empirical evidence

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Opinion

article

On

the

nexus

of

air

pollution

and

health

expenditures:

new

empirical

evidence

Carla

Blázquez-Fernández

∗

_,

_David

_{Cantarero-Prieto,}

_Marta

_{Pascual-Sáez}

DepartmentofEconomics,UniversidaddeCantabria,Santander,Spain;GENGovernanceandEconomicsNetwork,Spain

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received20November2017 Accepted29January2018 Availableonline22May2018

Keywords: Airpollution Healthexpenditure Paneldata OECD

a

b

s

t

r

a

c

t

Objective:Toanalysetheimpactofpercapitaincomeandenvironmentalairqualityvariablesonhealth expendituredeterminants.

Method: Inthisstudy,weanalysetherelationshipbetweenairpollutionandhealthexpenditurein29 OECDcountriesovertheperiod1995-2014.Inaddition,wetestwhetherourfindingsdifferbetween countrieswithhigherorlowerincomes.

Results:Theeconometricresultsshowthatpercapitaincomehasapositiveeffectonhealthexpenditure, butisnotasstatisticallysignificantasexpectedwhenlag-timeisincorporated.Inaddition,ananchorage effectisobserved,whichimpliesthatabout80%-90%ofpreviousexpenditureexplaincurrent expendi-ture.Ourempiricalresultsarequiteconsistentbetweengroupsandwhencomparedwiththefullsample. Nevertheless,thereappeartobesomedifferenceswhenbrokendownbyfinancingscheme(total,public, andprivate).

Conclusions:Overall,ourfindingscouldbeusedtoclarifytheappropriatehealthexpenditurelevelorto obtainbetterenvironmentalqualityandsocialwell-being.Thatis,empiricalsupportisprovidedonhow healthmanagementandpolicymakersshouldincludemoreconsiderationsfortheuseofcleanerfuels indevelopedcountries.

Relación

entre

la

contaminación

atmosférica

y

los

gastos

sanitarios:

nueva

evidencia

empírica

Palabrasclave:

Contaminaciónatmosférica Gastosanitario

Paneldedatos OCDE

r

e

s

u

m

e

n

Objetivo:Estudiarelimpactoquetienenlarentapercápitaylasvariablesdecalidadambientalsobrelos gastossanitarios.

Método:Analizamoslarelaciónentrelacontaminaciónatmosféricayelgastosanitarioen29paísesdela OCDEduranteelperiodo1995-2014.Además,estudiamossinuestroshallazgosdifierensegúnlospaíses (coningresosmásaltosomásbajos).

Resultados: Losresultadoseconométricosmuestranquelarentapercápitatieneunefectopositivoen losgastossanitarios,peronotanestadísticamentesignificativocomoseesperabaalincorporardemoras. Además,seapreciaunefectodeanclaje,elcualimplicaquealrededordel80-90%delosgastosanteriores explicanlosactuales.Nuestrosresultadosempíricossonbastanteconcordantesentrelosgrupos consid-erados,alcompararseestosconlamuestracompleta.Sinembargo,parecenexistiralgunasdiferenciasal desglosarportipodefinanciación(total,públicayprivada).

Conclusión:Engeneral,nuestroshallazgospodríanutilizarseparaesclarecerelniveladecuadodegasto sanitario,obienparaobtenerunamejorcalidadambientalybienestarsocial.Esdecir,sebrindaapoyo empíricosobrecómolaAdministración(sanitaria)ylosresponsablesdelasdistintaspolíticaspúblicas deberíanincluirmásconsideracionesparaelusodecombustiblesmáslimpiosenlospaísesdesarrollados. ©2018SESPAS.PublicadoporElsevierEspa ˜na,S.L.U.Esteesunart´ıculoOpenAccessbajolalicencia CCBY-NC-ND(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Introduction

Nowadays, there is an extensive literature focused on the determinants of health expenditures, being income the main one.1 _However,_non-income_factors _like_the_health _care _model,

∗ _{Corresponding}_author.

E-mailaddress:[email protected](C.Blázquez-Fernández).

population and ageing dynamics, population lifestyles, the technologicalprogressor theenvironmentaldeterminantshave beenalsoidentified.2 _Indeed,_there_are_both_demand_and_supply

factorsthatexplainhealthexpendituresdynamics.Inthisstudy, wefocus onenvironmentalissues thatarevery muchin vogue thesedays.3–5_Precisely,_we_look_forward_to_answering_the

follow-ingquestion:doesairpollutionaffecthealthcareexpenditures? Nowadays,manyofthemostimportantresearchersaregrappling withhow bestto characterize theeffects of environmentalair

https://doi.org/10.1016/j.gaceta.2018.01.006

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quality,inordertohelpregulatorsanddecisionmakerscraft more-effectivepolicies,toaddressbothhealthandenvironmentalissues inacontextofscarceresources.

Whatisitwellknownisthatairpollutionisresponsibleformany adverseeffects onhealth and well-being.6 _Hence,_air _pollution,

bothreferringhouseholdairpollutionandambientairpollution, isconsideredoneofthegreatsilentenvironmentalkillersthese days.7_Actually,_air_pollution_is_a_major_cause_of_{non-communicable}

diseasesthatshouldbetakenintoaccounttoagreaterextent.8

Moreover,ambientairpollution,inwhichwefocusinthispaper, isresponsibleforcountlesseconomiclosses.9_Mainly,_associated

withhealthcareutilizationandso,healthexpenditures.Butalso, lostordelayedproductionduetoabsencefromwork.

Then,aspointedbyEckelmanandSherman10 _new_efforts_to

improveenvironmentalperformanceofhealthcarecouldreduce expendituresdirectlyandindirectly.Thatis,bywastereduction andenergysavings,andthroughreducingpollutionburdenon pub-lichealth,thesefactorsoughttobeincludedineffortstoimprove healthcarequalityandsafety.Indeed,aspointedbyPascaletal.11

Europeancitizensarestill exposed toconcentrationsexceeding theWorldHealthOrganizationrecommendations.Theseauthors bytheAphekomProjectproviderobustestimatesconfirmingthat reducingurbanairpollutionwouldresultinsignificanthealthand monetarygains.Moreover,bystudyingthepublichealthimpacts ofurbanairpollutionin25Europeancities,theyestimateda mon-etarygainaroundD31billionannually,includingsavingsonhealth expenditures,absenteeismandintangiblecostssuchaswell-being, lifeexpectancyandqualityoflife.

Basedonthesepreviousassumptions,thegeneralaimofour studyistoexpandtheanalysisofthedeterminantsofhealth expen-ditures.Weanalysetherelationshipbetweenhealthexpenditures andincomeattheaggregatelevel,byprovidingsomeupdateson previousrelatedstudiesfordevelopedcountriesand incorporat-ingenvironmentalfactors.Besides,mostofthestudiesmakeuseas healthexpenditurevariablethetotalhealthexpendituremadeby eachcountry,wealsodistinguishbetweenpublicandprivateones. Precisely,this studyexploitsa balanced datasetof 29 OECD selectedcountriesduringtheperiod1995-2014.Moreover,a clus-teranalysisbasedontheheterogeneityofoursampleselectedis alsoperformed.Then, froma firstspecificationin linewiththe mainarticlesonthesubject,weintroducethedescribednovelties, wherethedependentvariableisalwaysthelogarithmofpercapita totalhealthcareexpenditures,butconsideringseveralhealthcare financingschemes.Indoingso,wefirstassumealinearand homo-geneousrelationshipbetweenincome,environmentalfactorsand healthexpenditures.Nevertheless,attheend,wealsoconsidera dynamicmodelfollowingthelineproposedbyLago-Pe ˜nasetal.12

Therefore, themain contributionof this paper is theuse of recentlydataandtheintroductionofnewvariablesintheestimates thatmakeanewimageofthetraditionalstudiesinordertoprovide supportabouthowhealthmanagementandpolicymakersshould includenewinsightsfortheuseofcleanerfuelsindeveloped coun-tries.Indeed,thisresearchlineofinternationalstudiesbyanalysing complexrelationshipsamongairpollutantsandhealth(andhow itvariesacrossterritories)couldimprovepublichealthandreduce inequalitiesindevelopedcountries.Thatis,ourresultshighlight thatitismorecrucialthanevertocarryoutanappropriatepolicy analysisatthemacroeconomiclevel,whichwillallowpolicymakers tobetterallocatescarceresources.

Methods

Data

Existing studies have examined different aspects of health expendituredeterminants.Herewefocusonenvironmentalones.3

Concentration of air pollutants Climate chan

ge

Illnesses _{Demand for h} ealth

care ser_vices _Health expenditure

s

∗Increased respir

atory symptoms and illness

∗Allergic diseases

∗Asthma

∗Exarcerbated chronic hear

th and lung aging

∗_{Increased lung cancer r}

isk

∗Increased r

isk of premature death

∗Etc.

Figure1.Pathwayeffectsofclimatechangeonhealthendpoint.(Authors’ elabora-tionadaptedfromBernardetal.15_).

Inordertoworkwithacompletebalancedpaneldata,inthisstudy ourtemporalanalysisperiod is1995-2014for aselectedgroup of29OECDcountriesnamely:Australia,Austria,Belgium,Canada, CzechRepublic,Denmark,Finland,France,Germany,Greece, Hun-gary,Iceland,Ireland,Italy,Japan,Latvia,Luxembourg,Netherlands, NewZealand,Norway,Poland,Portugal,Slovenia,Spain,Sweden, Switzerland,Turkey,UnitedKingdom,andtheUnitedStates.The benefitsofusingabalancedpaneldatasetconsistinthatitallows doingtheanalysisofstationarityofthevariables.Besides,mostof thetestsrequirethatthepanelsbestronglybalanced.13

Theeconometricanalysisreliesonannualdataobtainedfrom two different data sources:the latestversions of OECD Health StatisticsandOECDEnvironmentStatistics.Informationaboutper capitahealthcareexpenditures(total,publicandprivateones)and percapitaGDParemeasuredatPurchasingPower Parity(PPPs) terms.Sulphuroxideemissions,nitrogenoxideemissions,and car-bonmonoxideemissionsareinkilospercapita.Allvariablesare convertedintonaturallogarithmicformbeforetheempirical anal-ysis.Thedefinitionofthevariablesandsummarystatisticsfinally consideredaredescribedinTableIintheonlineAppendix.

Thisresearchprovidesrigorousscientificexaminationstostudy the following issue: how air quality indicators affect health expenditures.Takingintoaccountpreviousanalysis,apositive rela-tionship betweenincome and health expenditures is expected. Additionally, we hypothesized that su, ni, and ca would also increasehealthexpenditures.

Figure1representsthepathwayeffectsofclimatechangeon

healthendpoint,becauseitmayaffecttheexposurestoair pol-lutants.Inanycase, pollutioncouldappear byboth naturaland humansources.Hereitismodelledhowair,thatcouldbe contam-inatedwithpollutants,maynegativelyaffecthealthingeneraland healthexpendituresinparticular.Thus,thehealtheffectsofair pol-lutionarediverse,andincludedirectandindirectones.Allinall, themostsensitivegroupsincludechildren,olderadultsandpeople withchronicheartorlungdisease).Theexplanationisbasedon theideathatthesethreeairpollutantsmeasureshereconsidered deteriorateairqualityandso,theywouldaffectnegativelyhealth outcomes.14

Moreover,aspointedbyBernardetal.,15_health_effects_of

expo-surestosulphurandnitrogenoxides,andcarbonmonoxides,can causereducedworkcapacity,aggravationofexisting cardiovascu-lardiseases,effectsonpulmonaryfunction,respiratoryillnesses,

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Table1

Healthexpenditureregressions:linearmodelone-way.

Variable/specification hetotal hepublic heprivate

(i) (ii) (i) (ii) (i) (ii)

su − 0.271 b − 0.055 a − −0.032

(0.012) (0.013) (0.023)

ca − −0.034 − −0.024 − −0.179 a

(0.021) (0.233) (0.040)

ni − −0.021 − −0.070 b − 0.199 a

(0.028) (0.030) (0.053)

gdp 0.780 a _0.786 a _0.817 a _0.852 a _0.742 a _0.634 a

(0.013) (0.022) (0.015) (0.025) (0.026) (0.041)

constant −0.120 −0.028 −0.810 a −0.959 a −1.135 a 0.159

(0.137) (0.285) (0.154) (0.139) (0.277) (0.541)

Hausmantest FE FE FE FE RE FE

R-squared:within 0.862 0.863 0.843 0.848 0.594 0.618

R-squared:between 0.907 0.899 0.930 0.922 0.467 0.354

R-squared:overall 0.860 0.844 0.874 0.855 0.476 0.391

FE:fixedeffects;RE:randomeffects. a_Significant_at_1%.

b_Significant_at_5%.

Robuststandarderrorsarereportedinbrackets.

lungirritation,andalterationsinthelung’sdefencesystems.That is,anincreaseinutilization(demand)ofhealthcareservicesdue tobadhealthcareoutcomesisprojected.

Theseinterestingfindingscouldbeusedtoderivethe appro-priatehealth expenditure level, toobtainbetter environmental quality,andsocialwell-being.Researchneedsconsideringair pol-lution models(and theirpotentiallinkagewithclimatechange scenarios)inordertoclosegapsintheunderstandingofthe rela-tionshipbetweenairpollutionexposureandhealtheffects.Inany case,healthmanagementandpolicymakersshouldconsiderthese relationships.

Statisticalapproach

Overall, we follow recent contributions, which considerthe modellingadvanceoftherelationshipbetweenhealthand envi-ronmentalissuesasNarayanandNarayan3_or_Qureshi_et_al.16_Our

empiricalresultsarebasedonthefollowingspecificationswithall thevariablesofinterestareconvertedinnaturallogarithmsform toallowustounderstandthemaselasticities.

Firstly,alinearone-waypaneldatamodelforhealth expendi-ture(he),asdependentvariabletobeanalysed(whileconsidering different measures of it depending on its source of financing: total,public, andprivate)basedontheacknowledgedliterature isspecified.17,18_Therefore,_when_income_changes_the_variation_in

healthcareexpenditureitislikelytobeacombinationof multi-pleforces.Itisveryusefultoisolatetheseeffectstogainenhanced insightsintoseveralcomponents.Inamoreformalway,ourmodel hasthefollowinggeneralform:

heit=f(x_it,ˇ)+ε_it (1)

whereheitisthelogarithmofpercapitahealthcareexpenditures atthetthobservationfortheithcountry;f(•)denoteshealthcare expenditurestructure;xitisthecorrespondingmatrixof explana-toryvariables;ˇisavectorofparameterstobeestimated(su,ni,ca

andgdp).Thetermεistheerrorboundedwiththegeneralstatistical properties.Besides,feasiblegeneralizedleastsquaresare consid-ered.Thisprocedureallowsestimationinpresenceoffirst-order autocorrelationwithinpanelsandcross-sectionalcorrelation,and heteroscedasticityacrosspanels.

Secondly,adynamicpaneldataapproachisapplied.Thatis,we includeontheright-handsideofequation(1)thelaggeddependent variable,inordertocapturetheinertiaofhealthcareexpenditures. Inotherwords,wetrytodisentangleifthelogarithmofpercapita

healthcareexpendituresonayearisconditionedbytheprevious one:

heit=x′itˇ+heit−1+εit (2)

Results

Preliminarytest

Beforepresentingtheresultsfromtheestimationofthe above-mentionedspecifications,wefirstanalyseallvariablestoensure accurate estimates. That is, to obtain empirical findings that are not spurious and have economic sense.Precisely, first and second generation of panel unit root tests are employed here.

TablesIIand IIIin theonlineAppendix showthis typeof tests.

Firstly,weappliedpanelunitroottestsassumingcross-sectional independence.RegardingLevinetal.19_and_Im_et_al.20_,_mixed_results

concerningvariablesbeingstationaryareshowed.Statisticforthe logarithmofourvariableswhentheADFregressionhasan inter-ceptonlyandaninterceptandalineartimetrend,arepresented. Nevertheless,acommonfeatureoftheseeconometrictestsisthat theylosepowerasindividualspecifictrendsareincluded.13_In_all

cases,thelagorderp,wasselectedusingtheAkaikeinformation criterion.Then,wealsoapplytheBreitung21_test_that_indicates_the

hypothesisthatvariablescontainsunitrootisneverrejected. Con-sideringallofthis,weturnedtoPesaran22_second_generation_test

thatattemptstoremovecross-sectionaldependence.Wepresent resultsforlagordersp=0,1,2and3,findingthatinmostofthe casesourvariablesofinterestareintegratedoforder1,I(1).

Empiricalresults

Theestimationofthespecificationdescribedyieldstheresults reportedinTables1-4.Thefirsttwotablesconsidering(1)whereas thelatest(2).Coefficientsarehighlysignificant,andthegoodness offitisveryhighinallcases.Ourmainfindingscanbesummarized asfollows.FigureIintheonlineAppendix,plotstheresidualsfrom

Table1specification(ii)toassessthegoodnessoffitofthemodel andthusexaminetheexistenceofnon-linearityand,ifthatcase, toimproveourspecificationandestimates.

Firstly,percapitaGDPhasa positive effectonhealth. How-ever,weshowsomedifferenceswhendesegregatingbyhealthcare financingschemes.Itshouldalsobenotedthatthe‘unit’rulehas limitations,especially,whenelasticitiesof0.01and0.99areboth

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Table2

Healthexpenditureregressions:linearmodeltwo-way.

Variable hetotal hepublic heprivate

su −0.032 a −0.033 a −0.043 b

(0.012) (0.013) c _(0.019)

ca 0.032 0.036 0.043

(0.020) (0.022) (0.033)

ni −0.001 0.009 0.140 a

(0.031) (0.033) (0.053)

gdp 1.027 a _1.027 a _0.617 a

(0.043) (0.045) (0.074)

constant −2.561 a −2.937 a 0.048 b

(0.399) (0.412) (0.698)

Waldchi2 _1540.75 _1496.59 _394.11 Prob>chi2 _0.000 _0.000 _0.000

a_Significant_at_1%. b _Significant_at_5%. c _Significant_at_10%.

Standarderrorsarereportedinbrackets.

Table3

Healthexpenditureregressions:dynamicmodel.

het-1 0.940 a _0.890 a _0.815 a

(0.026) (0.033) (0.047)

su 0.009 0.018 −0.014

(0.012) (0.017) (0.014)

ca −0.044 a −0.056 c −0.085 b

(0.07) (0.031) (0.036)

ni 0.044 0.057 c _0.095 a

(0.021) (0.031) (0.037)

gdp 0.003 0.075 b _0.024

(0.034) (0.035) (0.026)

Waldchi2 _11707.22 _6356.67 _1727.51 Prob>chi2 _0.000 _0.000 _0.000

a_Significant_at_1%. b _Significant_at_5%. c _Significant_at_10%.

classifiedas‘necessities’.Thesenumbersareeconomicallyand sta-tisticallyquitedifferent.

Atthisregard,higherelasticitiesareobtainedforpublichealth expenditures.Therefore,thesmallestareforprivateones.Overall, incomeelasticityisnotasstatisticallysignificantwhen incorpo-ratinglags.Thatis,ananchorageeffectisappreciated(0.80-0.90). In other words, about 80% of a year’s health expenditure is

conditionedby theprevious one despitethe presenceof other explanatoryvariables.

Secondly,littleeffectsarefoundforairqualityvariablesasthe mostimportantfactoragain,andinaccordancewithprevious evi-dence,appeartobeincome.23

Asforairpollutantsvariables,themostimportantfactoristhe oneregardingsuinthelinearestimations,whereascaisforthe dynamicone.Thesevariablesexplainmoreprivateexpenditures.A surprisinglyfacthereisthereverseeffectofenvironmentalfactors hereconsidered.Forexample,whereassuaffectexpendituresina positivewayinthelinearone-wayestimates,thereverseeffectis obtainedforthetwo-way.Neitherstablesresultsareobtainedfor

ni.Butregardingcaones,stablenegativeeffectsareshown.

Robustnessofresults

Hereandnow,webrieflytesttherobustnessoftheresults.We noticedthat theempiricalmodel previouslyestimated imposes commoneffects forallthecountriesin thesample.Tobemore specific,Table4containstheresults,whileFigure2plotsthem.

Definitely,wecheckthesensitivityoftheestimatestoincome heterogeneityinthesampleof29OECDselectedcountries con-sidered. Indoing so,we split thesample ofcountriesinto two groupsbasedonakmeansandkmedianspartitioncluster analy-sisforincome(considering2005baseyear,halfoftheperiod).Both methodsarewidelyusedforexploratorydataanalysis.Precisely, thesepartitionmethodsbreaktheobservationsintoadistinct num-berofnon-overlappinggroups.

Thefirst,groupI,consistof19OECDcountries:Australia, Aus-tria,Belgium,Canada,Denmark,Finland,France,Germany,Iceland, Ireland,Italy,Japan,Luxembourg,Netherlands,Norway,Sweden, Switzerland,UnitedKingdom,andUnitedStates.While,10OECD countries constitute the second one, group II: Czech Republic, Greece,Hungary,Latvia,NewZealand,Poland,Portugal,Slovenia, Spain,andTurkey.

Specially,resultshighlightedtheabove-mentionedregarding therelevanceofhealthexpenditureinthepreviousperiod.Again, littledifferencesarefoundbyhealthcarefinancingscheme.

Whendistinguishingbyclusters,morestatisticallysignificant resultsareshownforgroupI.However,ourfindingsareconsisted betweengroupsandwhencomparingwiththefullsample anal-ysis.nishouldbeatmainaction agendaoutlines,especially for groupII,wherehigherelasticitiesarefounded(i.e.,0.034versus 0.136).

Table4

Sensitivitytoalternativesamples.

GroupI GroupII GroupI GroupII GroupI GroupII

het-1 0.853 a _0.842 a _0.831 a _0.783 a _0.720 a _0.848 a

(0.038) (0.050) (0.029) (0.036) (0.092) (0.030)

su 0.004 0.006 0.015 0.007 −0.025 0.005

(0.017) (0.007) (0.018) (0.011) (0.035) (0.022)

ca −0.058 a −0.016 −0.075 a 0.003 −0.081 −0.050

(0.023) (0.038) (0.025) (0.062) (0.089) (0.061)

ni 0.048 a _0.094 b _0.034 a _0.136 a _0.105 b _0.084

(0.011) (0.040) (0.038) (0.051) (0.048) (0.134)

gdp 0.060 b _0.087 _0.080 b _0.175 a _0.087 _0.037

(0.027) (0.059) (0.038) (0.055) (0.056) (0.028)

Waldchi2 _3132.62 _14337.65 _10142.75 _37707.36 _1022.70 _5338.90

Prob>chi2 _0.000 _0.000 _0.000 _0.000 _0.000 _0.000

a_Significant_at_1%. b _Significant_at_5%.

Numberofobservations:361and190,forgroupsIandII,respectively.GroupI:Australia,Austria,Belgium,Canada,Denmark,Finland,France,Germany,Iceland,Ireland, Italy,Japan,Luxembourg,Netherlands,Norway,Sweden,Switzerland,UnitedKingdom,andUnitedStates.GroupII:CzechRepublic,Greece,Hungary,Latvia,NewZealand, Poland,Portugal,Slovenia,Spain,andTurkey.

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0.200 0.900

0.850

0.800

0.750

0.700

0.650 0.150

0.100

0.050

0.000

-0.050

-0.100

su Group I

he_total he_public he_private

Group I Group I

Group II Group II Group II

ca ni gdp he(t-1)

Figure2. Elasticitiesbyincomegroupandfinancingscheme.Lefty-axisrepresentsairqualityelasticities.Righty-axisrepresentsanchorageeffect.

One of the implications of these interesting findings is that future health expenditure would increase as eco-nomic growth does, and the air quality indicators would do.

TableIVintheonlineAppendixalsotestedhowparametersforsu,

ni,andcaaredifferentforcountrieswithalowerorhigherincome by introducing interaction effects. DGDPi would be a dummy variable coded 1 for observations corresponding to countries in groupIand 0 otherwise.Hence, generalpublicpolicies,and especiallythoseonesthatcontainshealthexpenditureestimates, shouldcontainreliablehealthcareexpenditureprojections.That is,forecastsshouldtakeintoaccountbothtraditionaldeterminants (asincome),includingrecentfactorsaspopulationdynamics, pop-ulationlifestylesorthetechnologicalprogress;andotherdrivers, liketheoneshereanalysed(airqualityvariables).24

Discussion

In viewofouroutcomes,it maybeconcludedthat we con-tribute tostudy the ecologicaland health economicsliterature regardingtheimpactofpercapitaincomeandenvironmentalair qualityvariablesonhealthexpendituredeterminants.Precisely,we trytosolvethequestionregardinghowairpollutioncouldaffect healthcareexpenditures.Followingrecentliterature,westudied therelationship between health expenditures and income (per capita),nitrogen,sulphuroxide,andcarbonmonoxideemissions. Indoingso,weconsidereda balancedpaneldataof29selected OECDcountriesfortheperiod1995-2014.Besides,ourmain find-ingsarealsopresentedtakingintoaccountheterogeneitybetween countries.

Inthisspirit,ourpaperalsoprovidesagreaterunderstandingof theunderlyingeconomicframeworknestedwithintheliteratureof healthexpendituremodels.1,2_Our_results_are_in_accordance_with

previouscontributions.Severalmeasureshereconsidered deterio-rateairqualityandso,negativelywouldaffecthealthoutcomes.3,5

However,ithasbeenhighlightedtheimportanceoftheeconomic conditions. Moreover,in ouranalysis nitrogen oxideemissions wouldhave moresignificance than sulphuroxideemissions,or carbonmonoxideonesthatwereconsideredinearlierstudies.24,25

Thecostsavingsofthehealthco-benefitsachieved(health sta-tus,healthcareutilizationandhealthexpenditures)26,27_by_policies

tocutpollutantsemissionsareactuallylarge.28,29_This_is

particu-larlyimportantinthecontexthereconsideredwherehealthcare expendituresarestillgrowing.Inanyeconomicassessmentofthe costsof mitigationand adaptation,it shouldbeconsideredthe

healthbonusonsavings.Inspiteofthevastevidenceonhealth careexpendituredeterminants,thereisstillaneedoffurther infor-mation.Scienceandpublicpolicywouldbenefitfromadditional researchthatintegratestheoryandpracticefrombothairpollution effectstogainabetterunderstandingofthisissue.

Hence,inthisstudymoreempiricalsupportisprovidedabout howhealthmanagementpoliciesshouldincludeconsiderationsfor theuseofcleanerfuelsintheOECDcountries.Overall,ourresults highlightthatitismorecrucialthanevertocarryoutanappropriate policyanalysisatthemacroeconomiclevel,whichwillallow poli-cymakerstobetterallocatescarceresources.Inanenvironmentof financialconstraints,everyeffortisshort.Nonetheless,samehealth policiescanhavedifferenteffects,dependingonthefiscalpolicy frameworksinwhichtheyareimplemented.

Allinall,itisimportanttohighlighttheresearchlimitations andextensionsofthisstudy.Butinsteadofdampeningresearchers’ spirits,limitationsshouldserve tospurfurtherresearchintoan issueof vital importance.Limitations aremainly relatedto the OECD sample used (regions/countries,period and variables). In general,futureresearchcouldincludemoreenvironmental qual-ityvariables(moreaspectsthanthoseassociatedtoairpollution) relatedwithhealthcareexpenditures(besides,morehealth out-putsshouldbetakeninmind)whenconsideringallOECDcountries orbearinginminddifferencesbetweendevelopedanddeveloping countries.Whenmoredatawouldbeavailable,distinguishingby subperiodsoftimecouldbeinteresting,asforexample,to con-siderotherfactorsthatleadtoexhibitasignificantassociationover thelatesteconomiccrisis.Theseandotherissues couldbe con-sideredasconcernsofthisinterestingrelationshipthatremains unexplained.

Editorincharge

CristinaLinaresGil.

Transparencydeclaration

Thecorrespondingauthoronbehalfoftheotherauthors guar-antee the accuracy, transparency and honesty of the data and informationcontainedinthestudy,thatnorelevantinformation hasbeenomittedandthatalldiscrepanciesbetweenauthorshave beenadequatelyresolvedanddescribed.

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Whatisknownaboutthetopic?

Researchersaregrapplingwithhowbesttocharacterizethe effectsofenvironmentalairqualitytoaddressbothhealthand environmentalissuesinacontextofscarceresources.What isitwellknownisthatairpollutionisresponsibleformany adverseeffectsonhealthandwell-being.

Whatdoesthisstudyaddtotheliterature?

Weuserecentlydataandintroducenewvariablesin esti-matesthatmakeanewimageofthetraditionalonesinorder toprovidesupportabouthowhealthmanagementandpolicy makersshouldincludenewinsightsfortheuseofcleanerfuels.

Authorshipcontributions

Allauthorsdevelopedtheideaandcontributedtotheconcept anddesign.Allauthorscontributedtothewritingofthemanuscript andreadandapprovedthefinalmanuscript.

Conflictsofinterests

ApreviousversionofthepaperwaspresentedattheXXXVII JornadasdeEconomíadelaSaludorganizedbytheSpanishHealth EconomicsAssociationandtheSpanishEpidemiologicalSocietyin Barcelona,6to8September2017.Wearegratefulforthecomments receivedfortheparticipants.

Carla Blázquez-Fernández thanks Spanish Health Economics Association(AES)-TravelExpensesforattendingXXXVIIJornadas AES(Barcelona).

None. None.

AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound,in theonlineversion,atdoi:10.1016/j.gaceta.2018.01.006.

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