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Research Group on Human Capital Working Paper Series

Social Mobility Trends in Canada: Going up the Great Gatsby Curve

Working Paper No. 19-03

Marie Connolly, Catherine Haeck, and David Lapierre

May 2019 (revised version)

https://grch.esg.uqam.ca/en/working-papers-series/

SocialMobilityTrendsinCanada:GoinguptheGreatGatsbyCurve

MarieConnolly*,CatherineHaeckandDavidLapierre

GroupederecherchesurlecapitalhumainUniversityofQuebecinMontreal

Thisversion:May27,2019

AbstractWhile cross-sectional increases in inequality are a cause for concern, the study of theintergenerational transmissionof socioeconomic status isperhapsmore relevant.How issocialstatusreproducedfromonegenerationtothenext?Recentworkhashighlightedtherelationship, if not causal then correlational, between inequality andmeasures of socialmobilityinacross-countrysetting.ThisrelationshipisdubbedtheGreatGatsbyCurve(Corak2013): places with higher inequality during one’s childhood are correlated with lowerintergenerationalincomemobilitybetweenthechildandhisorherparents.Inthispaper,newlydevelopedadministrativeCanadiantaxdataareexploitedtocomputemeasuresof intergenerational incomemobility at the national and provincial levels. Thisworkprovidesdetaileddescriptiveevidenceonthetrendsinsocialmobility.Resultsshowthatmobility has steadily declinedover time, and that there has been an increase in theinequalityof theparental incomedistribution, asmeasuredby theGini coefficient.HenceCanada, and all its provinces, have been “going up” the Great Gatsby Curve. The crosssectional,crosscountryrelationshipthusalsoholdswithinasamecountryovertime,leadingcredencetothemorecausalthancorrelationalnatureoftherelationship,thoughcausalityisnot formally tested here. The decrease in mobility, particularly for children born in thebottomquintileof the incomedistribution,shouldbeofconcernto federalandprovincialpolicymakersalikeandhighlightstheneedforadditionalresearchinordertoprovideequalopportunitiestoallchildren.JEL:J62,D63Keywords:socialmobility,intergenerationaltransmissions,incomeinequality,GreatGatsbycurve,Canada*Correspondingauthor,connolly.marie@uqam.caTheauthorswouldliketothanktheFondsderechercheduQuébec-Sociétéetculturefortheirfunding(grant2016-PU-195586) and the Social Analysis and Modelling Division at Statistics Canada, in particular YuriOstrovskyandGrantSchellenberg,formakingthisworkpossible.CristianStraticaprovidedsuperbresearchassistance.Theauthorsalso thankparticipantsat theCRDCNandSCSEconferencesandat seminarsat theMontreal Applied Micro Group, McGill University, Dalhousie University and the University of Ottawa forcomments.Allerrorsremaintheirown.TheanalysispresentedinthispaperwasinpartconductedatStatisticsCanada’sFederalResearchDataCentreandattheQuebecInteruniversityCentreforSocialStatistics,whichispartoftheCanadianResearchDataCentreNetwork(CRDCN).TheservicesandactivitiesprovidedbytheQICSSaremadepossiblebythefinancialorin-kindsupportoftheSocialSciencesandHumanitiesResearchCouncil(SSHRC), the Canadian Institutes of Health Research (CIHR), the Canada Foundation for Innovation (CFI),StatisticsCanada,theFondsderechercheduQuébec-Sociétéetculture(FRQSC),theFondsderechercheduQuébec-Santé(FRQS)andtheQuebecuniversities.Theviewsexpressedinthispaperarethoseoftheauthors,andnotnecessarilythoseoftheCRDCNoritspartners.

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1. Introduction

InCanadaasinmostotherpartsoftheworld,incomeinequalityisontherise.Whilecross-

sectionalincreasesininequalityareacauseforconcern,thestudyoftheintergenerational

transmission of socioeconomic status is perhaps more relevant. How is social status

reproducedfromonegenerationtothenext?Recentworkhashighlightedtherelationship,

ifnotcausalthencorrelational,betweeninequalityandmeasuresofsocialmobilitysuchas

the intergenerational elasticity of income in a cross-country setting. This relationship is

dubbed theGreat Gatsby Curve (Corak 2013): placeswith higher inequality duringone’s

childhoodare correlatedwith lower intergenerational incomemobilitybetween the child

andhisorherparents.Thisisparticularlyworrisomeinthecontextofincreasinginequality:

are children from low-income backgrounds ever more likely to remain in a low-income

situationasadultsthaneverbefore?

ResearchintheUnitedStatesreachesdivergentconclusionsdependingonthedatasource

andmethods:Chettyetal.(2014a)usetaxdataandfindthattherank-rankrelationshiphas

notchangedbetweenthe1971and1982birthcohorts,whileDavisandMazumder(2017)

usetheNationalLongitudinalSurveysanddocumentdeclinesinintergenerationalmobility

between cohorts born 1942-53 and 1957-64 in both the rank-rank relationship and the

intergenerationalelasticityofincome.Upuntilrecently,thistypeofanalysiswasimpossible

inCanadaduetothelackofsuitabledata.Thishaschangedwiththerecentadditionofnew

birth cohorts to Statistics Canada’s Intergenerational Income Database (IID). The earlier

birthcohorts,bornfrom1963to1970,featuredinCorakandHeisz(1999)’sgroundbreaking

workonintergenerationaltransmissionofincome.Thelaterbirthcohortsnowstretchupto

1985.

In this paper, all available birth cohorts in the IID are exploited to computemeasuresof

intergenerationalincomemobilityandlookattrendsatthenationalandprovinciallevels.

Thesampleissplitintofivesuccessivebirthcohorts,spanningfrom1963to1985.Whilethe

focus is on rank mobility, shown to be more stable over the lifecycle than the

intergenerational elasticity, and on quintile transitions matrices, intergenerational

elasticities are also presented. Child income is measured over five years for three non-

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overlappingagegroups:whenthechildis25to29,30to34,and35to39yearsold.Late

thirtieshavebeenfoundtobemorerepresentativeoflifetimeincome,buttheyoungerbirth

cohort, born from1982 to 1985,has not reached those ages yet. Parental income is also

measuredoverfiveyears,whenthechildisaged15to19yearsold.

Findings show thatmobility has steadily declined over time, nationally and provincially.

Relativemobility,asmeasuredbytherank-rankcorrelation,wentfrom0.189forchildren

born1963-66to0.234forthoseborn1982-85.Lookingattransitionmatrices,theprobability

thatachildfromthebottomquintileoftheparentalincomedistributionstaysinthebottom

quintileofhisorherincomedistributionwentfrom27.1%upto32.6%,withacorresponding

declineoftheprobabilityforthosekidstoreachmiddleclass.Theresultsarethusmorein

linewithDavisandMazumder’sfindingsofdecliningmobilityintheUnitedStatesthanwith

Chettyetal.’sfindingsofstablecopulabetweenparentalandchildincomedistributions.

Paralleltothisdeclineinmobility,findingsalsodocumentanincreaseintheinequalityofthe

parentalincomedistribution,asmeasuredbytheGinicoefficient.HenceCanada,andallits

provinces,havebeen“goingup”theGreatGatsbyCurve.Thecrosssectional,crosscountry

relationshipthusalsoholdswithinacountryovertime,leadingcredencetothemorecausal

thancorrelationalnatureof the relationship, thoughcausality isnot formally testedhere.

ThisstudyprovidesdetaileddescriptiveevidenceonthetrendsinsocialmobilityinCanada,

exploitingnewlyavailableadministrativetaxdata.Thedecreaseinmobility,particularlyfor

children born in the bottom quintile of the income distribution, should be of concern to

federalandprovincialpolicymakersalike,andhighlightstheneedforadditionalresearchon

the mechanisms behind the decline in mobility in order to understand which policy or

programwouldstandthebestchanceatimprovingequalityofopportunitiesforallchildren.

Theremainderofthepaperisstructuredasfollows.Sections2and3containinformationon

themethodologyand thedata.The findingsarepresented inSection4. Section5offersa

discussionandconcludes.

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2. Methodology

Thegoalistomeasuretheintergenerationaltransmissionofincome,orthedegreetowhich

an individual’s incomedependsonthatofhisorherparents.The focusofthestudy ison

incomebecausethedatacontaindetailed,reliable,andlongitudinalinformationonincome

forsuccessivecohortsofyouthandtheirparents,whichallowsthecomputationofstatistics

bothovertimeandacrossspace.Whileotherdimensionsofsocialmobilitymaybeimportant

or interesting, such as occupation, education, or cultural capital, no administrative data

source in Canada contains the necessary information to study those dimensions. The

intergenerational elasticity (IGE) of income has been widely used in the literature as a

measureofmobility(orlackthereof),includingstudiesbasedonearlyIIDcohortsinCanada

such as Corak and Heisz (1999) and Chen et al. (2017). The IGE of income is typically

computed by estimating a linear model where the natural logarithm of child income is

explainedbythenaturallogarithmofparentalincome.However,duetothepresenceoflogs,

asDahlandDeLeire(2008),Chettyetal.(2014b)andConnolly,CorakandHaeck(2019)have

noted,IGEestimatesaresensitivetothetreatmentofverysmallvaluesofincomeinaway

thatmeasuresofrankmobilityarenot.Rankmobilityisdefinedinmuchthesamefashionas

the IGE, except that child and parental income aremeasured as percentile ranks in their

respectiveincomedistribution.Sincerankmobilityprovestobemuchmorerobusttothe

treatmentoflowincomesandacrossmodelspecifications,thisanalysisoftrendsinsocial

mobilityisbasedonrankmobility,whichiscomputedbyestimatingthefollowingmodel:

𝑅",$% = 𝛼% + 𝛽%𝑅"*+,$% + 𝜀$%, (1)

where𝑅",$% is the income rank of child i—the t generation—in province p,𝑅"*+,$% is the

incomerankofhisorherparent(s)—thet−1generation—,and𝜀$%isarandomterm.The

slopefromEquation(1),𝛽%,canbeinterpretedasameasureofintergenerationalmobility:

thehigherthe𝛽%,themoreparentalincomerankexplainschildincomerank,andtheless

mobilitythereis.Equation(1)isestimatedbothatthenationalandprovinciallevel,where

geographical location is fixedduring teenageyears.The ranks canbe computed from the

nationaldistributionortheprovincialdistribution,andestimatesusingbothtypesofranks

willbepresented.MoredetailsonthedatafollowinSection3.

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ModelsbasedonEquation(2)belowarealsoestimated:

𝑙𝑛/𝑌",$%1 = 𝑎% + 𝑏%𝑙𝑛/𝑌"*+,$%1 + 𝑒$%, (2)

where𝑌",$%ischildi’sfromprovinceptotalincome,𝑌"*+,$%ishisorherparents’income,and

𝑒$%isarandomterm.Theslopeofthismodel,b,istheintergenerationalelasticityofincome.

Another typeofmobilitymeasure that canbe computed is the transitionmatrix.Quintile

transitionmatricesareused,whereeachcolumnreferstoaquintileoftheparentalincome

distribution, each row to a quintile of the child income distribution, and each cell is a

conditionalprobability.Conditionalprobabilitiesaredenoted𝑃6,7:theprobabilityofmoving

fromorigino(parentalincomequintile)todestinationd(childincomequintile),orPr(child

income𝜖quintiled|parentalincome𝜖quintileo).AsinCorak(2017)andConnolly,Corak

andHaeck (2019), the focus isona fewkeypointsof thetransitionmatrix:𝑃+,+,𝑃+,9, and

𝑃+,:*;.Theintergenerationalcycleofpoverty,𝑃+,+,capturestheprobabilityforachildraised

inabottomquintileofthefamilyincomedistributiontoremaininthebottomquintilehimor

herselfasanadult.Therags-to-richesmovement,𝑃+,9,istheprobabilitytoescapethebottom

quintileandattainthetopincomequintile.Finally,𝑃+,:*;,measurestheprobabilitytoleave

the bottom incomequintile and reach themiddle three quintiles,which could be loosely

definedasthemiddleclass.

3. The Intergenerational Income Database

This study isbasedonall current cohortsof StatisticsCanada’s Intergenerational Income

Database. This database, first developed in the mid 1990s (see Corak and Heisz, 1999),

containslongitudinaladministrativetaxfilesofsuccessivecohortsofchildreninCanadaand

theirparents.TheoriginalIIDcohorts,1982,1984and1986,coveredchildrenbornbetween

1963and1970,inclusively.MorerecentcohortsarenowavailableintheIID,11991,1996

and 2001, coveringmost birth years between 1972 and 1985. In the IID, each cohort is

identifiedusingthefirstfiscalyearinwhichthelinkbetweentheparentsandthechildis

1TheauthorsthanktheFondsderechercheduQuébec-SociétéetcultureforfundingthatallowedthenewcohortstobeaddedtotheIID(grant2016-PU-195586).

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attempted.Forexample, the1982cohort includeschildrenbornbetween1963and1966,

whowerematchedtotheirparentsasof1982,whentheywere16to19yearsold. If the

matchcouldnotbeestablishedin1982,thematchwasattemptedagainoverthenextthree

years. In the current study, toavoidoverlappingbirthyearsacrossdifferent cohorts, the

1984IIDcohortisdividedintwo,poolinghalfwiththe1982IIDcohortandtherestwiththe

1986IIDcohort,dependingonbirthyear,andthenremovingduplicates.Table1givesthe

birthyearsandnumberofobservationspercohortasdefinedforthispaper.Thereareover

onemillionchildrenperbirthcohort,foratotalofclosetosixmillionchild-parentspairs.

Table1:TheIntergenerationalIncomeDatabasecohortsIIDcohort Birthyears IIDcount IIDweightedcount

1982-84 1963to1966 1,219,470 1,566,2401984-86 1967to1970 1,158,900 1,555,2801991 1972to1975 1,095,160 1,474,1401996 1977to1980 1,166,440 1,557,8002001 1982to1985 1,349,190 1,633,270

Source:Authors’calculationsbasedontheIID

IntheIID,taxfilesareavailableannuallystartingin1978forthe1982,1984and1986IID

cohortsandstartingin1981forthemorerecentcohorts.Thelastavailableyearoftaxdata

for all cohorts is currently 2014. From those tax files, a variety of incomemeasures are

availableforeachindividualofthefamily:boththemotherandthefather,thechild,aswell

asthespouseofthechildwhenreportedonthechild’staxreturn.Theanalysisisbasedon

total income from all sources, as defined by the Canada Revenue Agency. This includes

earnings, interest and investment income, self-employment net income, taxable capital

gains/lossesanddividends,andbenefits.Inthemainanalysispre-taxtotalincomeisused;

after-taxincomeisalsoconsideredinonepartoftheanalysis.

Parentalincomeisdefinedastheaverageannualparentalincomewhenthechildisaged15

to 19 years old, including bothmother and father if present. Taking a five-year average

reducesbiasesresulting fromtransitoryshocksto income.A five-yearwindowduringthe

lateteenageyearsisusedtoreflectresourcesavailabletothechildduringthosecrucialyears

ofhumancapitalaccumulationandtransitionsbetweensecondaryandpostsecondaryschool

orbetweenschoolingandthelabormarket.Theseagesarealsotargetedbecausetheyare

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the closest to the year of the family link in the tax files, thus ensuring that the family

circumstancesthatapplytothechild’slifeareeffectivelycaptured.Becausebiologicallinks

arenotidentifiedintheIIDandbecauseonlytheadultsidentifiedasthechild’sparentsat

themomentofthelinkcanbetracked,theearliertheperiodconsideredinthechild’slife(e.g.

earlychildhood),thelowerthecertaintythattheactualfamilyofthechildatthatmomentof

hisorherlifeiscapturedaccurately.Anotherreasontouseparentalincomewhenthechild

is15to19yearsoldisthatsincethetaxfilesstartin1978,dataonparentalincomeduring

earlychildhoodforthefirstbirthcohortsarenotavailablesuchthatcomparabilityacross

cohortswouldbeachallenge.Futurestudiescouldtrytoinvestigatetheeffectofparentalage

atchildbirthonmeasuresoftotalincomerank.

Comparabilityacrosscohortsbecomesanimportantissuewhendecidinghowtocompute

the child incomemeasure. If five-year averages are used for child income, as isdone for

parents,thenthelatestthatcanbestudiedinthechild’slifeforthelastcohort,thoseborn

between1982and1985,isfromtheagesof25to29yearsold.Achildbornin1985willturn

29yearsoldin2014,thelastyearofdataavailableatthetimeofwriting.Theseages,25to

29,arecomparabletowhatChettyetal.(2014b)useintheirmainanalysis(ages29to32)

andinsensitivitychecks(ages26to29).Tostudytrendsoverthelongestperiodpossible

usingtheIID,five-yearaveragesfromage25to29areusedinthemainanalysis.Childincome

averagesarealsocomputedfortheagesof30to34and35to39yearsold.Thefirstfourof

thefivecohortsareusedwhenchildincomeiscapturedbetweentheagesof30and34years

old,andonlythefirstthreeofthefivecohortsareusedifagesisconstrainedto35to39years

old.Notethatwheneveraparentorachildisnotfoundinthetaxfilesforagivenyear,an

income of $0 is imputed for that year. The sample is then restricted to children that are

observedatleastonceoverthefive-yearperiod,andtoparentsandchildrenthathavean

averageincomeofatleast$500.Thistreatmentiscoherentwiththesampleselectiondone

byCorak(2017).

Alldollarfiguresareconvertedto2016CanadiandollarsusingtheAll-itemsConsumerPrice

Index(CANSIMTable326-0021).Oncethefive-yearaveragesarecomputedforbothchild

andparentalincome,percentileranksarecomputedusingthenationaldistributionformost

of the analysis, and the provincial distribution for some complementary analysis. The

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provinceofresidenceisfixedatthetimeofthelinkbetweenthechildandtheparents,i.e.

whenthechildisaged16to19.Thismeansthatifachildmovesoutaprovincebythetime

hisorherincomeismeasured,thatchildisstillassignedtotheplacewhereheorshegrew

up,aswasdoneinChettyetal.(2014b),Corak(2017)andConnolly,CorakandHaeck(2019).

Studyingtheeffectofgeographicalmobilityonincomemobilityisleftforfurtherstudies.

Table2presentssomedescriptivestatisticsforeachbirthcohortinthesamplesstudied.The

toppanelsshowsstatisticsontheparents.Averageparentalincomeincreasedovertime,as

diditsstandarddeviationaswelltheGinicoefficientscomputedusingbothbefore-taxand

after-taxincome,areflectionofincreasingincomeinequality.Thenumberofparentslinked

toachilddependsonwhofiledataxreturnontheyearoftheparent-childmatch(i.e.when

thechildis16to19):ifonlyoneparentfiledataxreturn,thenonlythatparentisobserved

intheIID.Forthe1963birthcohort,thefractionofchildrenforwhomonlyoneparentfiled

taxeswas30.8%.Thisfractiondoesnotreallyreflectthemaritalarrangementofthechild’s

parents:single-earnerhouseholdsmaybeamarriedcouple,but ifonlyonespouse filesa

return,thentheyarereportedhereasa“one-parenttaxfiler,”despitebeingmarried.This

situationismorelikelytohappenformarriedcouplesinwhichoneofthetwoparentsdoes

not work, typically the mother. The rise in women’s labour force participation and the

increase indual-earner families (StatisticsCanada,2016)explains the substantialdrop in

one-parenttaxfilerfractionovertime,to21.8%,despitetheincreaseinlone-parentfamilies

documented elsewhere (Statistics Canada, 2015). That said, theway the parental income

variableisconstructedinthisanalysisisnotproblematic:parentalincomesimplyrepresents

householdincomearoundthetimeoftheparent-childmatch,thusreflectingtheresources

availabletothehouseholdthatthechildlivedin.Ifahouseholdhasoneparentearnerand

tax filer, then only that parent’s income counts towards household income,whether it is

becausetheparentisaloneparent,oramarriedparentinasingle-earnerhousehold.

Table2:Descriptivestatistics

BirthcohortVariable 1963 1967 1972 1977 1982Averageparentalincome(beforetax) $78,800 $77,700 $82,100 $81,200 $89,200 (84,300) (82,800) (91,800) (104,200) (167,300)

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Ginicoefficient,parentalbefore-taxincome 36.360 37.773 39.267 41.177 44.374Ginicoefficient,parentalafter-taxincome 34.081 34.699 36.039 37.461 40.526Fractioninone-parenttaxfilerhousehold 0.308 0.296 0.248 0.231 0.218Averagechildincome Ages25-29 $34,100 $32,000 $34,100 $35,300 $36,700

(23,100) (24,200) (27,800) (27,000) (30,100)Ages30-34 $42,100 $43,600 $46,100 $47,700 —

(44,300) (130,600) (44,800) (41,600) Ages35-39 $51,500 $53,600 $56,500 — —

(73,400) (77,600) (63,500) (73,400) Ginicoefficient, Ages25-29 38.774 41.337 41.497 41.333 43.323childbefore-taxincome Ages30-34 45.150 46.844 46.085 45.723 —

Ages35-39 48.860 50.459 49.273 — —Ginicoefficient, Ages25-29 31.179 32.733 33.113 33.503 35.244childafter-taxincome Ages30-34 35.310 36.779 36.237 36.143 —

Ages35-39 38.886 39.796 38.686 — —Fractionfemale(ages25-29) 0.490 0.487 0.489 0.489 0.491Fractionsingle,children Ages25-29 0.511 0.491 0.525 0.558 0.579

Ages30-34 0.308 0.311 0.320 0.350 —Ages35-39 0.246 0.252 0.264 — —

N(excludingparentsandchildren Ages25-29 1,469,010 1,437,190 1,357,900 1,442,150 1,501,800withincomeunder$500and Ages30-34 1,421,820 1,386,020 1,321,720 1,408,010 —childrenmissingallyears) Ages35-39 1,393,430 1,364,920 1,301,780 — —Sampleselection-parents Fractionmissingatleastonce 0.075 0.081 0.109 0.093 0.110Fractionwithincomeunder$500 0.018 0.022 0.018 0.017 0.022Sampleselection-children Fractionmissingallyears Ages25-29 0.029 0.038 0.045 0.043 0.044

Ages30-34 0.050 0.064 0.069 0.065 —Ages35-39 0.068 0.080 0.083 — —

Fractionmissingatleastonce Ages25-29 0.199 0.240 0.245 0.245 0.247Ages30-34 0.225 0.248 0.249 0.241 —Ages35-39 0.230 0.252 0.247 — —

Fractionwithincomeunder Ages25-29 0.015 0.018 0.019 0.017 0.018$500 Ages30-34 0.026 0.027 0.021 0.018 —

Ages35-39 0.027 0.025 0.021 — —Note:Standarddeviationsinparentheses.AllfiguresareweightedusingIIDweights.Source:Authors’calculationsbasedontheIID

ThesecondpanelofTable2presentsstatisticsthatrelatetothechild.Similarlytothetrends

observedfortheparents,incomeinequalityisontherise,asseenthroughtheincreaseinthe

Ginicoefficients.Thebottomtwopanelsinvestigatethesampleselection.Atmost2.2%of

parentsand2.7%of childrenareexcludedbecause their total income isunder$500.The

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fractionofchildrenthatarecompletelymissingfromthetaxdataovertherelevantfive-year

intervalincreaseswiththeageofthechild,goingfrom3-4%atages25to29,to5-7%atages

30to34,to7-8.3%when35to39yearsold.Thedeathrateisstillverylowatthoseages,so

the attrition most likely reflects outmigration. A nontrivial fraction of both parents and

childrenhaveatleastoneyearoftaxfilesmissing:upto11%fortheparents,andupto25.2%

for the children. In robustness analyses, the sample is further restricted to parents and

children that are observed all years over the five-yearwindow, and similar findings are

obtained.

4. Findings

Thissectionpresentsthefindingsfromthisstudy.Foreaseofpresentation,birthcohortsare

referred to by the first birth year of the cohort (e.g. 1963 birth cohort designates the

1963−1966 birth cohort). The first subsection presents the main findings regarding

intergenerational mobility at the national level, including results on rank mobility,

intergenerational elasticities, anddifferencesby gender of the child.Nonlinearity in rank

mobilityisexplorednext.Then,rankmobilityattheprovinciallevelisinvestigated,followed

by trends in the transitionmatrices. The next subsection presents a version of theGreat

GatsbyCurve,linkinginequality(theGinicoefficient)torankmobility.Robustnessanalyses

areshownlast.

4.1. Mobility at the national level

Mobility estimates at the national level are presented first. Table 3 shows the estimated

slopesfromtherankmobilityEquation(1),bybirthcohortandageatwhichchildincomeis

measured,forsonsanddaughterscombinedandseparately,aswellastheintergenerational

elasticityestimatesfromEquation(2).Ahigherrank-rankslopeorahigherIGEmeansthat

parentalincomehasahigherexplanatorypoweronchildincome,andthusmobilityislower.

Table3:Mobilityestimates

Birthcohort 1963 1967 1972 1977 1982

Rank-rank

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All ages25-29 0.189 0.188 0.216 0.215 0.234ages30-34 0.201 0.214 0.232 0.235 —ages35-39 0.201 0.214 0.230 — —

Sons ages25-29 0.188 0.187 0.214 0.219 0.233ages30-34 0.227 0.237 0.252 0.253 —ages35-39 0.238 0.247 0.257 — —

Daughters ages25-29 0.204 0.200 0.228 0.216 0.238ages30-34 0.193 0.205 0.223 0.224 —ages35-39 0.182 0.194 0.214 — —

Intergenerationalelasticity(IGE) All ages25-29 0.153 0.154 0.199 0.210 0.224

ages30-34 0.171 0.184 0.223 0.239 —ages35-39 0.180 0.192 0.232 — —

Sons ages25-29 0.154 0.157 0.200 0.215 0.223ages30-34 0.192 0.202 0.238 0.251 —ages35-39 0.214 0.221 0.255 — —

Daughters ages25-29 0.165 0.160 0.206 0.210 0.227ages30-34 0.166 0.178 0.219 0.234 —ages35-39 0.161 0.174 0.219 — —

Note:Standarderrorsareall0.001orlowerfortherankmobilityestimatesandfortheIGEforsonsanddaughterscombined.FortheIGEforsonsanddaughtersseparately,standardserrorsareallbelow0.002.Source:Authors’calculationsbasedontheIID

Aclearpatterntowardsdecreasingintergenerationalmobilitycanbeobservedwhenmoving

fromtheearlierbirthcohortstothelaterbirthcohorts:therank-rankslopehasbeensteadily

goingup,birthcohortafterbirthcohort.Whenmeasuredatages25to29,therank-rankslope

wentfrom0.189to0.234betweenthe1963cohortandthe1982cohort,a24%increase.This

trendispresentforbothsons(0.188to0.233)anddaughters(0.204to0.238),albeitfora

somewhatsmallerextentforthelatter.Intergenerationalelasticitiesalsoexhibitanupward

patternacrossbirthcohorts,hencetowardslowermobility:theIGEwentfrom0.153to0.224

forsonsanddaughterscombined,withsimilartrendswhengendersaretakenseparatelyand

againlowermobilityforsonsrelativetodaughters.Thesameupwardtrendcanbeseenwhen

childincomeismeasuredatolderages,evenifthepointestimatestendtobeslightlylarger

theolderthechildis.

AlthoughCanada ismovingtowards lessequalopportunities, therank-rankcorrelationof

the1982birthcohortinCanadaat0.234isstilllowerthanthe0.344estimatereportedby

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Chettyetal.(2014b)fortheUnitedStates.

Foreaseofexposition,Figures1through3presenttheestimatesfromTable3ingraphical

form.Figure1presentstheresultingestimatesoftherank-rankslope,ameasureofrelative

mobility, while Figure 2 shows the estimates of the IGE, and Figure 3 looks at sons and

daughters,separately.

[InsertFigure1abouthere.]



4.2. Nonlinearity in rank mobility

Figure4presentsfivebinnedscatterplotsofrankmobility:oneforeachbirthcohort.TheX-

axisrepresentsthepercentileranksoftheparentalincomedistributionandtheY-axisshows

themeanchildpercentilerankusingincomemeasuredwhenthechildisaged25to29to

allowforacomparisonacrossallcohorts.Eachpointthereforecapturestheaveragerankof

childrenforeachoftheparent’spercentilerank.Theequationshownatthebottomrightof

each subfigure shows the corresponding estimates of Equation (1). These binned scatter

plots are a way to visualize the estimation of Equation (1). Note that the rank-rank

relationshipdoesnotappearaslinearaswhatChettyetal.(2014b)hadfoundfortheUnited

States, especially at the bottom of the parental income distribution (below the 20th

percentilesforparents).


To further investigate the nonlinearity, locally-weightednonparametric smoothedscatter

plotsarepresented inFigure5, separately foreachbirth cohort.Darker linesare for the

earlierbirthcohortsandlighteronesforthemorerecent.Thecurvesappearnottobelinear:

theslopeismorepronouncedatthebottomoftheparentalincomedistribution.Moreover,

the curves for thevariousbirth cohortsare roughly stackedaccording tobirthyears: the

earlierbirth cohortshavehighermeanchild ranks than the laterones for lowerparental

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ranks, and lower mean child rank for higher parental ranks. This is coherent with the

decliningrankmobilitythatwasalreadynotedusingalinearmodelintheprevioussection,

but indicates that the changes inmobility observed over time come from changes in the

bottomandtopquintileoftheparentalincomedistribution.Aninterestingresulttolookat

itiswherethecurvesmeeteachotherastheparentalincomerankincreases.Thecurvefor

the1967cohortmeetsthe1963curveatparentalincomepercentilerankof16,whereasthe

1982curveonly reaches the1963cohort atpercentile36, a full20 ranks furtherup the

incomedistribution.Thismeansthatthechildrenfromthebottom36%ofthe1982parental

incomedistributionhaveonaveragelowerincomeranksthansimilarlypositionedchildren

fromtheearliestbirthcohort. Inasense, ithasgrownmoredifficult toreachtherelative

positionofthechildrenofthe1963cohortforchildrenfromlow-incomebackgroundsinlater

birthcohorts.Thereverseistrueatthetopendoftheparentalincomedistribution.


LookingatFigures4and5,itseemsreasonablethatamodelallowingtwoslopes,onebelow

andoneabovethe20thpercentileoftheparentalincomedistribution,wouldprovideagood

fit for the data. Consequently, a version of Equation (1), the rank mobility equation, is

estimatedusingasplinemodelallowing for twoslopes.Theresultingslopeestimatesare

plottedinFigure6,wherethepanelontheleftisfortheslopeforparentalranks1to20,and

theoneontherightisforranksfrom21to100.NoteherethatthescalesoftheY-axesare

notthesameforthetwopanels.Lookingateitherofthetwoslopes,asimilarpatterncanbe

seen,withestimatedslopesshowinganincreasingtrendfromthe1963cohorttothe1982

cohort(rightpanel),albeitwithaslightlydifferentintermediatetrajectoryfortheslopesfor

lowerparentalranks(leftpanel).ThepanelontheleftofFigure6showsthattheslopefor

thebottomquintileofparentspeakedforthe1972birthcohortatover0.7beforegoingback

downtoreachcloseto0.55forthe1982cohort.Acrossallyears,theslopesaremuchhigher,

somobilitymuchlower,forthebottomquintileoftheparentalincomedistributionthanthey

are for the top fourquintiles, and the rateof increasehasbeen stronger for thatbottom

quintile, too. Incontrast, for therestof theparental incomedistribution,mobility, though

decreasing,isrelativelyhigh.Althoughtheslopesinthebottomquintilearehigherin1963

and1972comparedto1977and1982,theaveragerankofachildgivenhisorherparents’

13

rankisalmostalwayslowerin1977and1982thanthatoftheearliercohort(seeFigure5).

Astimepasses,itisgettingmuchharderforachildfromthebottomincomequintiletoreach

higherincomeranks.Whatmattersformobilitymaynotsimplybetheslopeoftherank-rank

relationship,butalsoitsaveragelevel,orinthepresentcasewherethecurvesmeet.


4.3. Rank mobility at the provincial and territorial level

Uptonow,theanalysisfocusedonthenationallevel.Thissectionnowturnstorankmobility

attheprovinciallevel.Threesetsofresultsarepresentedfrommodelsestimatedseparately

for each province or territory: onewhere parental and child ranks are computed at the

nationallevel;onewhereranksarecomputedwithineachprovinceorterritory;andfinally

onewhereranksarecomputednationallybuttheincomemeasuredusedisnetoftaxes.Using

localranksisonewaytotakeintoaccountthedifferentrealitiesofthedifferentprovinces

andterritories,andinasensetocontrolforcostoflivingdifferences.Ifasalaryof$60,000

doesnotmeanthesamethinginAlbertaandinNovaScotia,thenusingwithin-provinceranks

should help compare the relative positions of each. The next three figures present the

resultingslopeestimates,usingnationalranks(Figure7)thenprovincialorterritorialranks

(Figure8),andafter-taxincome(Figure9).StartingwithFigure7,onecanseethatthetrend

ofdecreasingmobilityobservedatthenationallevelisalsopresentinallprovinces,albeitto

differentdegrees.OnlytheYukonshowsanoveralldecreaseintherank-rankslope,butit

shouldbenotedthatthepopulationsizefortheYukonisquitesmallcomparedtotheother

regions.Therearesubstantialdifferencesacrossprovinces,withsomeprovincesshowing

lowslopes/highmobility,suchasPrinceEdwardIslandorNewfoundlandandLabrador,with

slopes around 0.15-0.23, and other provinces with high slopes/low mobility, like

Saskatchewan and Manitoba, both with slopes above 0.3 for the latest birth cohort.

Saskatchewan is also theprovince that saw the greatest increase in the slope coefficient,

goingfrom0.17forthe1963birthcohorttoalmostdoublethatforthe1982birthcohort.By

and large, using ranks computed at the provincial or territorial does not change the

conclusionsdrawnfromlookingatFigure6;theestimatedslopesarepracticallyidentical.

The samecanbe saidaboutusingafter-tax incomerather thangross income to compute

14

incomeranks:Figure9displayspatternsthatareverysimilartothoseofFigures7and8.




4.5. Trends in transition matrices

Inthissubsection,pointsfrom5x5transitionmatricesarepresented,showingconditional

probabilitiesforthevariousincomequintiles.Again,findingsarepresentedgraphicallyfor

easeofexposition.Figure10shows,conditionalonparentalincomequintile,theprobability

thatachildhasanincomeinthebottomquintileofhisorherincomedistribution.Formost

parentalincomequintiles,thisprobabilityisrelativelystableacrossthefivebirthcohorts,

andperhapsslightlydecreasingfortheverytopincomequintile.Thelargestmovementis

seenforchildrenwhogrewupinfamiliesatthebottomoftheincomedistribution.𝑃+,+,the

probabilitytoremaininthebottomquintile,hasgrownfrom0.27to0.33,a22%increase

betweentheoldestcohortandtheyoungestone.Ithasthusbecomemoredifficultforachild

fromadisadvantageousbackgroundtogetoutofalowincomesituation.


Figure11isconstructedthesamewayasFigure10,butthistimeshowingtheprobabilityfor

achildtohaveanincomeinthetopincomequintileofhisorherdistribution.Figure11shows

thatall theprobabilitiesremain constantacross the fivebirth cohorts.The flipsideof the

increasein𝑃+,+observedinFigure10isthusnotthatchildrenfromlow-incomefamilieshave

a lower probability to reach to top income quintile, but rather that they have a lower

probabilitytobeinoneofthethreemiddleincomequintiles(quintiles2,3or4).Thiscanbe

seen in Figure 12,which presents the probability for a child to be in thosemiddle three

quintiles,conditionalonparental incomequintile.Thedrop inthesetransitionstomiddle

class,sotospeak,canclearlybeseenforchildrenwhogrewupinbottom-quintilefamilies.

Forthosechildren,theprobabilitytoreachoneofthethreemiddlequintileswentfrom0.60

forthe1963birthcohortto0.56forthe1982cohort,anearly8%decrease.

15



4.6. The Canadian Great Gatsby Curve

NowthatmeasuresofrankmobilityforfivesuccessivebirthcohortsofCanadianshavebeen

computed,theycanbeputinrelationwithameasureofincomeinequalityfortheparental

incomedistribution,totraceoutawithin-countryversionoftheGreatGatsbyCurve.Figure

13doesjustthisfortheslopecoefficient,ameasureofrelativemobility,atthenationallevel.

Eachdotrepresentsabirthcohort,anditisclearthatCanadahasbeen“goingup”thecurve,

bymoving towards the top right. In doing so, the successive cohorts are tracing out the

upward sloping curve, too, showing that the classic inequality-mobility relationship

describedintheliteratureacrosscountriesforagiventimeperiod(Corak2013)alsoholds

withinacountryacrossbirthcohorts.Figure14issimilartoFigure13,thistimeusingafter-

taxincome.TheGinicoefficientsfortheparentalincomedistributionarelowerwhenusing

after-taxincome,aresultoftheincomeredistributionthroughthetaxsystem,buttheslope

coefficientsremainverysimilar.TheresultingGreatGatsbycurveisthussimplyshiftedto

theleft.



Anotherwaytovisualizetherelationshipbetweeninequalityandmobilityistolookwithin

Canada by plotting a provincial version of Figure 13, that is one where each point

correspondstoaprovinceandbirthcohort.Again,theinequality-mobilityrelationshipholds

within a given country for a given point in time (looking at a given birth cohort across

provinces),andwithinagivencountrywhenallcohortsarepooledtogether(seethebest

linearfitlineonFigure15).Figure16presentsthesamepoints,connectedbyprovincethis

time.Giventhateveryprovincehasseenanincreaseininequalityovertheperiodstudied,so

increasing Gini coefficients, each provincial series is labeled by adding the province

abbreviationtotherightoftheseries,i.e.nexttothepointcorrespondingtothe1982birth

cohort.Themovementof“goingup”theGreatGatsbyCurveisnotjusttrueforCanadaoverall

16

(asseeninFigure13);itistrueforeverysingleprovinceofCanada.Someprovinceshavea

relatively steep mobility-inequality profile, meaning that their decrease in mobility is

relatively more important than their increase in inequality (for example Saskatchewan),

while others have a flatter profile, with relatively large increases in inequality but not

necessarilylargeincreasesintherank-rankslopecoefficient(forexampleOntario).



4.7. Robustness analyses

Inthissectionrobustnessanalysesarepresented.Onepossiblesourceofbiascouldcome

fromthefactthatsomeindividualscannotbefoundinthetaxfilesinsomeyears.Table2

showedthatwhenlookingatages25to29,3to4%ofchildrencannotbelinkedtoanytax

file.Thosepercentagesare5to7%whenconsideringages30to34and7to9%forages35

to39.Moreover,somechildrencanonlybefoundinsomeyears.Thequestionofwhattodo

whenchildrenaremissing fromthetax filescouldbe important. In themainanalysis, the

sampleexcludesparentsandchildrenwithaverage incomeunder$500andchildrenthat

cannotbefoundinanytaxfile.Inarobustnessanalysis,thesampleisfurtherrestrictedto

includeonlyparentsandchildrenthatareobservedforthefull5-yearwindowduringwhich

incomeismeasured.TheresultingslopeestimatesfromEquation(1)areinTable4.

17

Table4:Mobilityestimatesfromalternativespecifications

Birthcohort 1963 1967 1972 1977 1982

Rank-rankallquintilesoftheparentalincomedistributionAll ages25-29 0.189 0.188 0.216 0.215 0.234

ages30-34 0.201 0.214 0.232 0.235 —ages35-39 0.201 0.214 0.230 — —

Restrictedset ages25-29 0.186 0.182 0.209 0.206 0.226ages30-34 0.201 0.214 0.231 0.233 —ages35-39 0.202 0.215 0.229 — —

Rank-rankbottomquintileoftheparentalincomedistributionAll ages25-29 0.483 0.616 0.722 0.460 0.544

ages30-34 0.432 0.585 0.657 0.392 —ages35-39 0.439 0.563 0.635 — —


Rank-ranktopfourquintilesoftheparentalincomedistributionAll ages25-29 0.172 0.160 0.181 0.178 0.193

ages30-34 0.197 0.203 0.214 0.217 —ages35-39 0.201 0.208 0.218 — —


Note:Standarderrorsareall0.001fortherankmobilityestimatesforallquintilesandforthetopfourquintiles.Forbottomquintile,standardserrorsareallaround0.01.Source:Authors’calculationsbasedontheIID

Tables4presentstherank-rankslopeestimatesforthewholedistribution(toppanel)aswell

asseparatelyforthebottomquintileoftheparentalincomedistribution(middlepanel)and

for the other four quintilesof the parental incomedistribution (bottompanel). Although

therearesomedifferenceswhencomparingtheresultsfromthemainsampletothoseofthe

restrictedset,thepatternsmostlyhold.Forexample,thetoppanelshowsthattheestimated

slopewentfrom0.189to0.234acrossthebirthcohortsinthemainanalysis,andfrom0.186

to 0.226 in the restricted set. Looking at the bottom quintile of the parental income

distribution in the middle panel, the increase in the slope coefficient for the later birth

cohortsissomewhatlargerintherestrictedsetthanitisinthemainsample:0.566and0.700

forthe1977and1982birthcohorts,respectively,fortherestrictedset,comparedto0.460

18

and0.544fortheanalysissample.Overall,thepotentialbiascomingfromtheunavailability

oftaxfilesforsomeindividualsdoesnotappeartobemuchofaconcern.

5. Discussion and conclusion

Inthisstudy,decreasesinsocialmobilityacrossfiveconsecutivebirthcohortsinCanadaare

documentedusing a previously unavailable very large setof administrative tax files. The

focusisonrankmobility,andfindingsshowthattheslopebetweenachild’sincomerank,as

anadult,andhisorherparents’incomerankhasbeenonanincreasingtrend,goingfrom

0.189to0.234betweenthe1963-66birthcohortandthe1982-85cohort.Therealsoappears

tobesubstantialnonlinearityintherankmobilityequation,motivatingasplitoftherank-

rankslopeintwosegments:oneforparentalincomerankuptothe20thpercentile,theother

forranks21to100.Thebottomsegmenthasmuchhigherslopes,thuslowermobility,than

thetopsegment.Moreover,theaveragechildranksforthemorerecentcohortsarelower

than thoseof the first cohort for a substantial partof the bottomof theparental income

distribution: even childrenwhose parents are at the 30th to 35th percentiles have lower

average ranks for the1982-85cohort than for the1963-66cohort.Rankmobility is also

described at the provincial and territorial levels.While therehas been a deterioration of

mobilityineverysingleprovince,therearestilllargevariationsinrank-rankslopesacross

regions in most recent cohort, and the within-province variations over time have had

differentmagnitudes.Someplaces,notablytheMaritimes,haveamongthelowestrank-rank

slopes,meaningthemostequalopportunitiesforchildren,alongwiththesmallestincreases

inslopes.Ontheotherhand,Manitobagenerallydisplaystheleastintergenerationalmobility

amongst the10provinces, and it is inSaskatchewan that thedeteriorationof equalityof

opportunitieshasbeen theworst.A lookatquintile transitionmatrices revealsmuch the

samestoryofdecliningmobility:childrenborn inthebottom20%of families in termsof

incomehave become less likely to exit the bottomquintile themselves, and less likely to

transitionintothemiddleclass.

These results can seem to contradict Ostrovsky’s (2017) finding of stable rates of

intergenerational incomemobility between 1970 and 1984, using the same data source.

19

Ostrovsky’smeasurehoweverwasquitedifferent:heusedasanabsolutemobilitymeasure

thefractionofchildrenearningmorethantheirparentsatage30.Thischoicewasmotivated

bythedesiretocomparetheCanadiancasewithChettyetal.’s(2017)similarestimatesfor

theUnitedStates.Therestrictiontouse incomemeasuredatage30 forbothparentsand

childrenconstrainedthecohorts thatcouldbeusedfromtheIID.Duetodataconstraints,

Ostrovsky’s analysis starts with birth year 1970, but the present analysis documents

decreases in rankmobilitystartingwith the1963birth cohort. It is thuspossible thatby

havingtostartwiththe1970birthcohort,asubstantialpartofthedeclineobservedherein

was missed. Moreover, the absolute mobility measure used in Ostrovsky states which

fractionofchildrentipspastacertainincomethresholdandinsodoingdoesnotdescribethe

rank-rankrelationshipinthesamelevelofdetailsasdonehere.

Togetherwiththeincreasesinincomeinequalityobservedoverthesametimeperiod,the

increasinglystrongassociationuncoveredbetweenparentalincomerankandchildincome

rankmeansthatCanada,andeverysingleoneofitsprovinces,havebeen“goingup”theGreat

GatsbyCurve.Moreinequalityhasgonehandinhandwithlowermobility.Thisassociationis

purelycorrelationalatthisstage,andthecurrentdescriptiveanalysismakesnoattemptto

uncovercausalrelationships.Butthefactthattherelationshipholdsacrosscountriesfora

giventimeperiod,aswellasforagivencountryovertime,andwithinagivencountry(across

itsregions)bothatagivenpoint in timeandacrosstime,points tosomethingmorethan

simplyaspuriouscorrelation.Whentherungsofthesocioeconomicladderarefurtherapart,

itbecomesmoredifficulttoclimbit.Theoreticalmodelsexplainingthisrelationshipwould

beanimportantstepforwardinourunderstandingofsocialmobility.

Armedwithabatteryofdescriptivestatistics,amuchclearerportraitofthesituationofsocial

mobilityinCanadaanditsrecenttrendsemerges.Alotofquestionsremain.Whatmakesa

regionmoremobilethananother,andwhydosomeexperiencemuchstrongerdeclines?The

literaturesuggestssomefactorsthatcorrelatewithmoreorlessintergenerationalincome

transmission (see Chetty et al., 2014b, or Connolly, Corak and Haeck, 2019). But more

researchisneededtouncovercausalmechanismsandidentifypublicpoliciesthatmayplay

infavourofmoreequalopportunitiesforCanadianchildren.

20

References Becker,G.S.,&Tomes,N.(1979).AnEquilibriumTheoryoftheDistributionofIncomeand

IntergenerationalMobility.JournalofPoliticalEconomy,87(6),1153-1189.Becker,G.S.,&Tomes,N.(1986).HumanCapitalandtheRiseandFallofFamilies.Journalof

LaborEconomics,4(3,Part2),S1-S39.

Black,S.E.,&Devereux,P.J.(2011).RecentDevelopmentsinIntergenerationalMobility.InO.C.Ashenfelter,&D.E.Card(Eds.),HandbookofLaborEconomics,4B(16), (p.1487-1541).Amsterdam:North-Holland.

Chen,W.H.,Ostrovsky,Y.,&Piraino,P.(2017).LifecycleVariation,Errors-in-VariablesBiasand Nonlinearities in Intergenerational Income Transmission: New Evidence fromCanada.LabourEconomics,44(January),1-12.

Chetty,R.,Hendren,N.,Kline,P.,Saez,E.,&Turner,N.(2014a).IstheUnitedStatesStillaLandofOpportunity?Recent Trends in IntergenerationalMobility.TheAmerican EconomicReview,104(5),141-147.

Chetty,R.,Hendren,N.,Kline,P.,&Saez,E.(2014b).WhereistheLandofOpportunity?TheGeographyof IntergenerationalMobility in theUnitedStates.TheQuarterly JournalofEconomics,129(4),1553-1623.

Chetty, R., Grusky,D., Hell,M.,Hendren,N.,Manduca, R., &Narang, J. (2017). The FadingAmericanDream:TrendsinAbsoluteIncomeMobilitySince1940.Science,356(6336),398-406.

Connolly,M.,Corak,M.,&Haeck,C.(2019).IntergenerationalMobilitywithinandbetweenCanadaandtheUnitedStates.Forthcoming,JournalofLaborEconomics.

Corak,M.(2013).IncomeInequality,EqualityofOpportunity,andIntergenerationalMobility.TheJournalofEconomicPerspectives,27(3),79-102.

Corak,M.(2017).DividedLandscapesofEconomicOpportunity:TheCanadianGeographyofIntergenerationalIncomeMobility.UniversityofChicago,HumanCapitalandEconomicOpportunityWorkingPaperNumber2017-043.

Corak, M., & Heisz, A. (1999). The Intergenerational Earnings and Income Mobility ofCanadian Men: Evidence from Longitudinal Income Tax Data. Journal of HumanResources,34(3),504-533.

Dahl,M.W.,&DeLeire,T.(2008).TheAssociationbetweenChildren'sEarningsandFathers'LifetimeEarnings:EstimatesUsingAdministrativeData.DiscussionPaperNo.1342-08,UniversityofWisconsin-Madison,InstituteforResearchonPoverty.

Davis, J., & Mazumder, B. (2017). The Decline in Intergenerational Mobility After 1980.FederalReserveBankofChicago,WP2017-05,March2017.

Ostrovsky,Y.(2017).DoingasWellasOne'sParents?:TrackingRecentChangesinAbsoluteIncome Mobility in Canada. Economic Insights, Catalogue no. 11-626-X — No. 073,StatisticsCanada.

21

Statistics Canada (2015). Lone-parent families: The new face of an old phenomenon.CanadianMegatrends,Catalogueno.11-630-X,2015002,ISBN978-0-660-25887-4.

Statistics Canada (2016). The rise of the dual-earner family with children. CanadianMegatrends,Catalogueno.11-630-X,2016005,ISBN978-0-660-25887-4.

22

Figures

Figure1:Rankmobilitybyagegroupandbirthcohort

Note:This figureshowstheestimatedslopecoefficientofEquation(1),byagegroupandbirthcohort.Source:Authors’calculationsbasedontheIID

23

Figure2:Intergenerationalelasticity,byagegroupandbirthcohort

Note:This figureshowstheestimatedslopecoefficientofEquation(2),byagegroupandbirthcohort.Source:Authors’calculationsbasedontheIID

24

Figure3:Rankmobilitybyagegroupandbirthcohort,sonsanddaughtersseparately

Note:This figureshowstheestimatedslopecoefficientofEquation(1),byagegroupandbirthcohort,forsonsanddaughtersseparately.Source:Authors’calculationsbasedontheIID

25

Figure4:Rankmobilitybybirthcohort

Note: This figure shows binned scatter plots of rank mobility by birth cohort. Each dotcorrespondstoonepercentilerankoftheparentalincomedistribution.TheY-axisgivesthemeanvalueofchildrankbyparentalincomerank.Childindividualincomeismeasuredatages25to29.TheestimateofEquation(1)isshownatthebottomrightofeachsubfigure.Source:Authors’calculationsbasedontheIID

26

Figure5:Nonlinearityinrankmobilitybybirthcohort

Note:ThisfigureshowsthelowessestimationsofEquation(1),bybirthcohort.Source:Authors’calculationsbasedontheIID

27

Figure6:Rankmobilitybelowandabovethe20thpercentileofparentalincome

Note:Thisfigureshowstheestimatedslopecoefficientofrankmobility,byagegroupandbirthcohort,whereEquation(1)ismodifiedtoallowtwoslopes:oneforparentalranks1to20,andtheotherforparentalranks21to100.Source:Authors’calculationsbasedontheIID

28

Figure7:Rankmobilitybyprovinceorterritoryandbirthcohortusingnationalranks

Note: This figure shows the estimated slope coefficient of Equation (1), by province orterritoryandbirthcohort,withrankscomputedatthenationallevel.Source:Authors’calculationsbasedontheIID

29

Figure8:Rankmobilitybyprovinceorterritoryandbirthcohortusingprovincialor

territorialranks

Note: This figure shows the estimated slope coefficient of Equation (1), by province orterritoryandbirthcohort,withrankscomputedattheprovincialorterritoriallevel.Source:Authors’calculationsbasedontheIID

30

Figure9:Relativerankmobilitybyprovinceorterritoryandbirthcohortusingafter-

taxincomeandranksatthenationallevel

Note:ThisfigureshowstheestimatedinterceptcoefficientofEquation(1),byprovinceorterritoryandbirthcohort,withrankscomputedatthenationallevel.Source:Authors’calculationsbasedontheIID

31

Figure10:Probabilityforachildtobeinbottomincomequintilebyparentalincome

quintileandbirthcohort

Note:Thisfigureshowstheprobabilityforachildtobeinthebottomincomequintileofhisorherincomedistribution,byparentalincomequintileandbirthcohort.Source:Authors’calculationsbasedontheIID

32

Figure 11: Probability for a child to be in top income quintile by parental income

quintileandbirthcohort

Note:Thisfigureshowstheprobabilityforachildtobeinthetopincomequintileofhisorherincomedistribution,byparentalincomequintileandbirthcohort.Source:Authors’calculationsbasedontheIID

33

Figure12:Probabilityforachildtobeinmiddlethreeincomequintilesbyparental

incomequintileandbirthcohort

Note:Thisfigureshowstheprobabilityforachildtobeinthemiddlethreeincomequintilesofhisorherincomedistribution,byparentalincomequintileandbirthcohort.Source:Authors’calculationsbasedontheIID

34

Figure13:GreatGatsbyCurveforrelativerankmobility

Note:ThisfigureshowstherelationshipbetweentheGinicoefficientoftheparentalincomedistribution(ontheX-axis)andtheestimatedslopeofEquation(1)(ontheY-axis).Thelineisthebestlinearfit.Eachpointcorrespondstoabirthcohort.Source:Authors’calculationsbasedontheIID

35

Figure14:GreatGatsbyCurveforrelativerankmobility,usingafter-taxincome

Note:ThisfigureshowstherelationshipbetweentheGinicoefficientoftheparentalafter-taxincomedistribution(ontheX-axis)andtheestimatedslopeofEquation(1)(ontheY-axis).Thelineisthebestlinearfit.Eachpointcorrespondstoabirthcohort.Source:Authors’calculationsbasedontheIID

36

Figure15:GreatGatsbyCurveforrelativerankmobilityattheprovinciallevel

Note:ThisfigureshowstherelationshipbetweentheGinicoefficientoftheparentalincomedistribution(ontheX-axis)andtheestimatedslopeofEquation(1)(ontheY-axis,wheretheranks are computed at the national level). The line is the best linear fit. Each pointcorrespondstoaprovinceorterritoryandbirthcohort.Source:Authors’calculationsbasedontheIID

37

Figure16:GreatGatsbyCurveforrelativerankmobilitybyprovince

Note:ThisfigureshowstherelationshipbetweentheGinicoefficientoftheparentalincomedistribution(ontheX-axis)andtheestimatedslopeofEquation(1)(ontheY-axis,wheretheranksarecomputedatthenationallevel).Eachpointcorrespondstoaprovinceandbirthcohort.Thepointsforagivenprovinceareconnectedfromtheoldestbirthcohorttothemorerecent,withtheprovinceabbreviationnexttothepointforthemorerecentbirthcohort.Source:Authors’calculationsbasedontheIID

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