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TheImpactofStateUnemployment
BenefitsonUnemploymentinAmerica
JimmyChang
NorthwesternUniversity
MathematicalMethodsintheSocialSciences,SeniorThesis2017
Advisor:JeffreyThomasLewis
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Acknowledgments
First,Iwouldliketothankmyparents,AnnieandYanChang,forgivingmethe
opportunitytoreceiveagreateducationandforbeingsupportiveofmydecisions
throughoutmyentirelife-especiallyduringmyNorthwesterncareer.Inaddition,Iamso
thankfulforthehelpofmythesisadvisorProfessorJeffreyLewis,whoprovideda
seeminglyendlessstreamofresourcestoenablemetocompletethisresearch.Iwouldalso
liketothankProfessorFerrieandtherestoftheMMSSfacultyforinspiringmeandgiving
metheanalyticaltoolsforsuccess.TomyfriendsNourAlharithiandRaymondDai,thank
youforbeinganamazingemotionalsupportthroughthisthesisprocessandthroughout
mysenioryear.TomyfriendandcolleagueJohnMicevych,thankyouforbeingthe
inspirationandasoundingboardformythesistopic.Finally,Icouldnothavecompleted
thisprojectwithoutthehelpofAlecBlumenthal,EmilieGreenberg,SpencerOh,andthe
restofmyMMSSclassmateswhohavegivenmeafun,challengingenvironmenttolearn
andlaughoverthesepastfouryears.
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TableofContents
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Abstract
UnemploymentisanissuethathaspersistedintheUnitedStates,especiallyinthe
aftermathofthefinancialcrisisof2008thatledtotheGreatRecession.However,inorder
tocombatunemployment,stateshaveemployedvaryingpolicieswithvaryingresults.In
thispaper,Iaimtoquantifytheeffectsofthesedifferentstatepoliciesonunemployment
reduction–focusingontwocomponentsofunemploymentbenefits:unemployment
insurance(UI)andemploymentcasemanagement.BycompilingUnitedStatescensusand
employmentdataonastatelevelandperformingOLSregressionanalyses,Idiscoverthat
thegenerosityofstateUIpackageshasnosignificanteffectonreducingunemployment,
andtheimplementationofemploymentcasemanagementhasasignificanteffecton
unemploymentreductioncomparedtotheuseoftraditionalunemploymentalleviation
methods.
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Introduction
In1932,Wisconsinbecamethefirststatetoofferweeklycashpaymentsto
unemployedindividualssothattheycouldaffordbasicnecessitieswhilelookingforstable
work.ThesepaymentswereusedasareliefmeasureforworkersaffectedbytheGreat
Depression.FollowingwithWisconsin’sreliefprogram,FranklinDelanoRooseveltsigned
intolawtheSocialSecurityActof1935withaprovisionthatincludedmonetaryassistance
totheindividualsseekingemployment–thisbecamethefirstformalUnemployment
Insurance(UI)programandestablishedtheprecedentthatunemploymentinsurancewas
basedonfederalmandatebutadministeredindependentlybythestate(U.S.Departmentof
Labor2007).
Sincethen,stateshavecarriedouttheirindividualUIpoliciestoaddresstheirown
unemploymentissues–withlittleempiricalknowledgeofitseffects.Afteraflurryof
researchintounemploymentinsuranceinthelate1980sand1990s,researchhasslowed
andhadneverbeenperformedatastatelevel.TheGreatRecessionhasonceagainshineda
spotlightontheimportanceofstateUIprograms.DuringtheGreatRecession,federalUI
extensionswerecreatedandgiventojobseekerswhohaveexhaustedtheirstateUI
benefits,providingupto73weeksofextendedUIatitspeak(U.S.DepartmentofLabor
2007).Asof2017,federalextensionscontinuetobemadeavailabletoindividualsduring
periodsofhighunemploymentforupto13additionalweeks(U.S.DepartmentofLabor
Employment&TrainingAdministration).However,statesarestillseenasthemain
administratorsofUI,havingcontrolovertheminimumweeklyUIamount,maximum
amount,whetheradditionalaidisprovidedtounemployedindividualswithdependents,
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andtheduration.WhilestatesbelievethattheyhaveenactedUIpoliciesthatbestservethe
unemployedindividualsintheirjurisdiction,theeffectivenessofthisvariationinpolicy
needstobedetermined.
Casemanagementisaserviceprovidedtoindividualsinwhichanindividualisgiven
acuratedsetofresourcesbasedonspecificneedsinordertoachieveadesiredgoal.Inthe
UnitedStates,casemanagementismostpopularlyusedinthehealthcaresystem.Patients
aretreatedas“cases”andareassignedcasemanagerstopersonalizepatients’care.These
casemanagersarefull-timeresourcesforpatients,offeringthemtheappropriatetreatment
fortheirillnessesattheappropriatefacilitybasedontimeandmoneyrestraints.Asa
result,patientsarehealthymorequickly,andthustheyarelessstrainonthehealthcare
systemsandaremoreproductivemembersofsociety.
Thesameprinciplesofcasemanagementcanbeappliedtounemployment.While
unemploymentisanaturalresultofthebusinesscycleandchangingeconomictrends,long
termunemployment–whethercyclicalorstructural–isapervasiveissuethatdrains
publicresourcesandpreventseconomiesfromfunctioningatitsoptimalcapacity.Case
managementseekstobeanadditionalcomponenttothesolutionofunemployment–
complementarytounemploymentinsurance.
Employmentcasemanagement–whichwillbesimplycalled“casemanagement”for
therestofthepaper–isaworkforceinvestmentprogramthatprovidesguidanceand
supporttoindividualstoregainemployment(Laird2011).Casemanagersoffera
personalized,high-touchservicetonotonlyplaceindividualsintooccupationsquicklybut
alsoplacethemintojobsthatmatchtheirskillsanddesiredcareergoals.Theserecipients
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aretypicallyclaimantsofunemploymentinsurance,andcasemanagerscarryoutfour
categoriesofactivitiesforjobseekers:skillsassessment,careerplanning,coordinationof
supportservices,andjobmatching/placement/followup(Laird2011).
Sincethe1990s,developednationssuchastheUnitedKingdom,Canada,andNew
Zealandhaveinstitutedmorepersonalizedservicefortheunemployed,andAustralia
createdanationwidepolicyofutilizingcasemanagementtowardre-employment(OECD
1998,Davidson2002,Gursansky2003).However,littlehasbeenexploredonthe
effectivenessofcasemanagementacrosstheentireUnitedStateswherethetopicof
welfare–especiallyforunemployment–canbepoliticallysensitive.Givenrecent
discussionofconservativefiscalspending,itisincreasinglyimportanttofindeffective
solutionstolongtermunemploymentinordertoprovideresourcestoindividualsinneed
whilesimultaneouslyreducingwelfaredependencyandpromotingself-sufficiency.
AccordingtotheOrganisationforEconomicCooperationandDevelopment(OECD),
theUnitedStatesroughlyspends0.4%ofitsannualGDPonpublicunemployment
spending–severelylaggingbehindmostdevelopedOECDnationsinprovidingresources
tounemployedindividualsinneed(FigureAofAppendix).Thequestionisraised:canthe
UnitedStatesprovidemoreresourcestowardcombattingunemploymentintheformof
unemploymentbenefits?Wouldthistranslatetoalargerdecreaseinunemployment?What
componentsofunemploymentbenefitsshouldbeinvestedintoinordertohavethelargest
impactonunemployment?Theanswerstothesedrivingquestionsmayserveasthe
foundationofunemploymentreforminthiscountry.
Inthisstudy,Ianalyzetheeffectoftwounemploymentbenefits,unemployment
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insurancegenerosityandcasemanagement,offeredinAmericaonastatelevel.My
researchcomparesunemploymentdatawithUIgenerosity(i.e.theamountofweeklyUI
compensation)andthepresenceofcasemanagementacrossstatesandyearsfrom2007to
2016.First,IwilloutlinethecontributionsofexistingliteratureontheeffectsofUI
generosityandcasemanagementonunemployment.Afterwards,Iwillexplainmydata
collectionmethodsandmyrationaleandapproachtowarddeterminingtheeffectsofmy
twovariablesofinterest.Next,Iwilldiscussmyfindingsandtheimplicationsofmyresults
onstatere-employmentbenefitpoliciesmovingforward.Finally,Iwillconcludewith
limitationsandfutureextensionstomyresearch.
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LiteratureReview
Unemploymentinsuranceisawidelyscrutinizedtopicduetoitspoliticallysensitive
nature–conjuringupimagesoffreeriderswhomanipulatethewelfaresystemtoreceive
compensationwhiledoingnowork.Existingliteratureoftenreferencesthe“common
belief”thatunemploymentinsurancelengthensthedurationofunemploymentbecauseit
lowerstheeffortaclaimantputsforthinsecuringemployment(Shavell&Weiss1979,
Fallick1991,Hopenhayn&Nicolini1997).Infact,previousstudieshaveverifiedthisbelief.
Intheirpaper“TheImpactofthePotentialDurationofUnemploymentBenefitsonthe
DurationofUnemployment”,LawrenceKatzandBruceMeyer(1988)foundthatincreases
inunemploymentinsurancedurationledtoincreasesintheaveragedurationof
unemploymentforUIclaimants.TheeffectisevenprevalentoutsideofAmerica,where
RafaelLalive(2007)showedthatlargeextensionsinUIdurationintheAustrianUIsystem
ofupto170weeksledtoanincreaseinthedurationofunemployment.
However,thesestudiesfocusedonthedurationofUI,whilemyresearchtriesto
determinetheeffectonunemploymentoftheweeklymonetaryamountofUIgivento
claimants.KatzandMeyer(1998)revealthatincreasingtheweeklyamountofUIisbetter
atnothavinganegativeeffectonunemploymentdurationthanincreasingthedurationof
UI;however,thatisallthefindingstheygiveontheeffectofUIamount,astheirfocuswas
mainlyUIduration.Withthatsaid,inthepaper“UnemploymentInsuranceand
UnemploymentSpells”,Meyer(1990)createsadditionalresearcharoundtheeffectofthe
amountofunemploymentinsuranceonunemploymentduration.Thisstudyshowedthat
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higherlevelsofUIweeklyamountshad“astrongnegativeeffectontheprobabilityof
leavingunemployment”foranindividual.
A1991studyondisplacedworkersshowedthattheamountofweeklyUIhadno
effectontherateoftransitionfromemploymenttore-employment(Fallick1991).
IrrespectiveoftheamountofweeklyUI,unemploymentinsurancewasshowntobe
effectiveatincreasingre-employmentinthebeginningofanindividual’sunemployment
spell,butitbecamelesseffectiveastheindividualapproachedUIexpiration.Moreover,UI
levelsdidn’thelpdisplacedworkersgetre-employedfasterintheirinitialindustry,andUI
levelsactuallyslowedtherateofemploymentinanewindustry(Fallick1991).
Thus,existingliteratureshowsthatunemploymentinsuranceisnoteffectiveatthe
reductionofunemployment.However,unemploymentinsuranceisstillseenasimportant,
asthereservationwagesallowjobseekerstobelessrisk-averseandtrytoattainjobsthat
betterfittheirskillsandinterestswhichmaximizesoutputforsociety(Hopenhayn&
Nicolini1997).AllthepreviousstudiesmentionedlookedatUIbenefitsatanindividual
level–employingindividualrationalchoicemodelssuchasthejobsearchmodeltofindthe
effectofUIonunemployment.Asaresultofthisindividualapproach,thesestudiesallhave
smallsamplesizesof1115interviewedhouseholdsoveroneyear(Katz&Meyer1988),
3365maleUIclaimantsin12statesacross6years(Meyer1990),and1190displaced
workersoveroneyear(Fallick1991).Myresearchusesanaggregatemodel,lookingat
unemploymentatastatelevelacrossallstatesandWashingtonD.C.over10yearswhile
utilizingadatasourceofover3millionobservations.Thisdifferenceinmethodology,along
theuseofrecentdatathatincludespolicyandsentimentchangesfromtheGreatRecession,
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leadsmetodeviatefromexistingliteratureandhypothesizethatstateUIgenerosityhasa
significanteffectonthereductionofunemploymentrate.
Existingliteratureontheeffectivenessofcasemanagementcanbeseparatedinto
twobuckets:literatureincountriescomparabletotheUnitedStatesandliteratureona
specificsubpopulationwithintheUnitedStates.Withtheformer,Australiahasbeenwidely
seenasacasestudyonnationwideimplementationofcasemanagementintheir
employmentwelfaresystem.In1994,thegovernmentcreatedtheJobCompact,asocial
contractinwhichthegovernmentguaranteedajobtoanylong-termunemployed
individual,andinreturntheindividualwasobligatedtoacceptanyjobpositionthatwas
deemedreasonable(Gursansky2003).TheJobCompactwaseligibletoanyAustralian
citizenwhohadbeenunemployedfor18months(OECD1998),andcasemanagementwas
thepreferredmethodofservicetoassisttheseindividualsinsecuringemployment.
A1996studyonwomen’sexperienceswiththeJobCompactrevealedthattherewas
nopositivecorrelationbetweenhavingreceivedcasemanagementandtheirreported
employmentoutcomes(Gursansky2003);withthatsaid,itwasarguedthattherelative
newnessofcasemanagementasaserviceandthechangingpoliciesofitsadministrationto
individualsmadeitdifficulttoevaluatecasemanagement’seffectonunemployment
(Eardley&Thompson1997).
However,theJobCompactwaseventuallyretired,astheprogramfacedpolitical
pressureduetoitshighcostsandlowreturnoninvestmentforsociety.Theprogram
focusedonhelpingindividualswhostruggledwithlong-termunemployment–individuals
whohaddevelopedpersonalissuesandthuswerehardtohire.Anestimated$8860AUD
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wasputintoeachindividualintheprogram:$660fromcasemanagementand$8200for
theballooningprogramcosts(Davidson2002).Casemanagementwasultimatelynot
effectiveinreducingunemploymentinAustralia.
TheotherbucketofliteraturefocusedoncasemanagementinAmericafor
individualswithhistoryofsubstanceabuse.A2001studyprovidedacasestudyof10
chronicallyunemployedindividualswhowereonamethadonetreatmentprogramfor
opioidaddiction.Aftertwomonthsincasemanagement,9ofthe10individualswere
employed;6ofthe10kepttheirjobsafter8months(Zanis2001).Alargerstudyin1996
examinedtheuseofcasemanagementon632veteransundergoingsubstanceabuse
treatment.Theveteranswhooptedforcasemanagementexhibitedmoreimprovementin
employmentfunctioning–especiallydurationofemployment–thantheveteranswho
werenotincasemanagement(Siegal1996).
Whilepreviousstudieshavefocusedonspecificgroupsofindividualswhohave
receivedcasemanagementordifferentcountriesthathaveimplementedcase
management,myresearchaimstocontributetoinstitutionalknowledgebydetermining
theeffectofcasemanagementonalargegroupofindividualsusingalargesamplesize
acrossalloftheUnitedStates.Asexistingresearchisdividedovertheeffectsofcase
managementonunemploymentlevels,Ifollowintuitionandoperatewiththehypothesis
thatcasemanagementdoes,infact,haveasignificanteffectonreducingemployment.After
all,itseemslogicalthathavingadditionalhelpinthejobsearchprocesswouldleadtoless
unemployment.Iwilldeterminethisthroughanapproachthatdiffersfromthe
methodologiesoftheexistingliterature.
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Data
TheUnitedStatesCensusBureauandtheUnitedStatesBureauofLaborStatistics
administertheCurrentPopulationSurvey(CPS)inordertoprovidedataonthecurrent
stateofthecountry’semploymentandlaborforceparticipation.TheCPScontainstwo
supplementarydatasets:theMergedOutgoingRotationGroup(MORG)andtheAnnual
SocialandEconomicSupplement-whichwillbereferredtoastheMarchCPSdataset,as
theannualsupplementisreleasedeveryMarch.
TheNationalBureauofEconomicResearch,aCambridge,MA-basedeconomic
researchorganization,extractsandcompilestheCPSMORGintooneannualdataset,while
theCenterofEconomicandPolicyResearch,aWashingtonD.C.-basedeconomicpolicy
think-tank,doesthesamefortheCPSMarch.Bothsupplementarydatasetscontain
observationsonanindividuallevelwithemploymentstatusaswellaseducationleveland
demographicinformation.Foreachgivenyear,theMarchCPSdatasethas185,487
observations,whiletheCPSORGdatasethas314,873observations–allowingforan
analysisofalargergroupthanthosethatpreviousstudieshavelookedinto.
Formydataset,IultimatelydecidedtousetheCPSMORG,asitprovidedthe
advantageofhavingnearlytwicethenumberofobservationsasCPSMarch.Thislarge
sampleallowedformorenuancedanalysisthanpreviousstudies,whichIwillcoverin
Methodology.Thus,ImanipulatedtheannualMORGdatasetstolookatpooledcross-
sectionaldatafrom2007-2016–essentiallyconsolidatingtheindividual-leveldataintoa
state-yearlevel–inordertostudytheeffectsofeconomicconditionsandUIprogram
characteristicsonunemployment.Mydatasetonlyincludedallindividualsaged19-64who
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arelabeledatactiveinthelaborforceorwhoselaborforcestatuswasnotmissing.Theage
limitationwascreatedinordertoaccountforeligibilityofunemploymentinsurance.I
chosetofocusonage,race/ethnicity,andgenderasthemaindemographiclabelsformy
analysis.
DependentVariable:
o Unemploymentrate:Thisprimarydependentvariablecalculatestheamountof
peoplewhoareunemployedasapercentageoftheactivelaborforceaged19-64in
eachstate.
IndependentVariables:
o UImaximumweeklybenefitamountwithdependent(s):Thismetricisconsideredone
oftwoproxiesforstategenerositytowardunemploymentItisthemaximumweekly
amountofunemploymentinsuranceanindividualcanreceivewhenhe/shehas
dependents(e.g.children).Thismetricrepresentsthe“absolutevalue”ofUI
generosity,andisgivenbystateandbyyearfrom2007-2016.Thevariablewas
collectedthroughthe“UnemploymentInsurance”chapteroftheU.S.Houseof
RepresentativesWaysandMeansCommitteeGreenBook,whichoutlinesfederal
benefitsandwelfaretothestates.GreenBooksfortheyears2016,2014,2012,and
2011wereused;otheryearswerecollectedthroughreportsfromtheCongressional
ResearchService,thepublicpolicythink-tankoftheU.S.Congress.Thesereportsare
usedbytheWaysandMeansGreenBooksintheUIchapter.Thisvariableis
calculatedastherealmaximumweeklyUIbenefit,meaningthemetricisadjusted
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forinflation.Year-by-yearinflationwascollectedfromtheBureauofEconomic
Analysis–withthebaseyearof2009–inordertocreatetheadjusted
measurement.Intheregressions,UImaximumweeklybenefitamountwith
dependent(s)isdividedby100toshowtheeffectofincreasingthemaximum
amountby$100asopposedtoamere$1increase.
o AlthoughmanyUImetricsarenotinthefinalregressionspecification,Table
CinAppendixlooksatregressionswithvariousotherindependentvariables
foundintheWaysandMeansCommitteeGreenBook:UImaximumweekly
benefitamountwithoutdependent(s),UIminimumweeklybenefitamount,and
maximumweekseligibleforUIcompensation.TherationalebehindusingUI
maximumweeklyamountofbenefitswithdependent(s)willbeexplainedlater
inMethodology.
o UIreplacementratio:ThismetricisthesecondmeasurementasaproxyforstateUI
generositytowarditsjob-seekingindividuals,representingthe“relativevalue”ofUI
generosity.ReplacementratioistheratioofaUIclaimant’sweeklybenefit
comparedtoanaverageweeklywageofa“usualjob”foraclaimant.Averageweekly
wageiscalculatedashourlywagenormalizedto40-hourworkweek.TheUI
replacementratiosbystateandbyyearwerecollectedfromtheEmployment&
TrainingAdministrationoftheUnitedStatesDepartmentofLabor(DOLETA).
Unfortunately,datawasnotfoundforFlorida2014;therefore,regressionsusing
replacementratiowillhaveasamplesizeofonefewer.
o TworeplacementratioswereofferedbytheDOLETA.Idecidedtouseonly
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oneofthemformyfinalregressionspecification,asthesecondratio
equationwasslightlymorecomplicated.However,inTableCinAppendix,I
usethesecondUIreplacementratio.Thesecondreplacementratiois
calculatedasaweightedaverageoftheweeklybenefitdividedbyaweighted
averageofthenormalizedweeklyworkwage.
o Casemanagement:Adummyvariablethatidentifiestheimplementationofcase
managementasanunemploymentserviceforjobseekers.Casemanagementis
definedasthepresenceofacustomer-relationshipmanagementsysteminwhich
jobseekersaregivenonecasemanagertointeractwiththroughtheentirejob
searchprocess,asopposedtocareercentersprovidingone-offservicestoconnect
jobseekerstovariousresources(e.g.UI,training,resumereview,workshops).Data
onthisvariablewascollectedthroughonlineresearchofeverystatedepartment
thatofferedassistancetojobseekers.
o Highintensityofcasemanagement:Adummyvariablethatidentifiesthepresenceof
ahighlevelofintensityinastate’scasemanagementpractices.Ahighlevelof
intensityisdefinedastheuseofemploymentenforcementasacomponentofcase
management,meaningcasemanagersactivelyreachedouttojobseekerstoverify
thattheyhavefollowedthestepstowardsecuringemployment.Casemanagement
ofthislevelwillalsohavecasemanagersfollowupwithindividualsoncetheyhave
securedemploymentinordertoensuretheymaintainthepositions.
o Lowintensityofcasemanagement:Adummyvariablethatidentifiesthepresenceof
alowlevelofintensityinastate’scasemanagementpractices.Alowlevelof
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intensityisdefinedasthepresenceofrelationshipmanagementbetweencase
managersandemploymentseekers.Casemanagersareusedasresourcestosecure
employment,buttheydonotactivelyenforcethatjobsearchstepsarebeingcarried
outnordocasemanagersfollowuponindividualsintheircaseloadoncetheyhave
secureemployment.
ControlVariables:
o Employmentgrowthrate:Employmentgrowthrateiscalculatedasthegrowthin
totalnon-farmandnon-seasonallyadjustedemploymentineachstatefrom
DecemberofthepreviousyeartoDecemberofthespecifiedyear.Thismetricwas
collectedfromtheBureauofLaborStatistics.
o Highschoolgraduates:Thepercentageofindividualswhograduatedfromhigh
schoolcomparedtothetotallaborforce.Asthisdatacamefromasurvey,havinga
levelofeducationof“highschoolgraduate”meansthatanindividualcompleted
highschoolbutdidnotattendcollege.Alltheeducationlevelcontrolvariablesare
mutuallyexclusiveandcollectivelyexhaustive.Therationaleforhavingeducation
levelcontrolvariableswillbegiveninMethodology.
o Somecollegeeducation:Thepercentageofindividualswhoreceivedsomecollege
educationcomparedtothetotallaborforce.
o Collegegraduates:Thepercentageofindividualswhograduatedfromcollege
comparedtothetotallaborforce.
o Advanceddegreerecipients:Thepercentageofindividualswhoreceivedan
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advanceddegreecomparedtothetotallaborforce.Advanceddegreesaredefinedas
MastersofArts/Sciences,PhDs,etc.
o Male:Thepercentageofindividualswhoidentifyasmaleastheirgendercompared
tothetotallaborforce.
o Black:Thepercentageofindividualswhoidentifyasblack/African-Americanas
theirracecomparedtothetotallaborforce.
o Hispanic:ThepercentageofindividualswhoidentifyasHispanic/Latinxastheir
ethnicitycomparedtothetotallaborforce.
o Ages19–29:Thepercentageofindividualswhoare19-years-oldto29-years-old
comparedtothetotallaborforce.Anexplanationforhavingagecontrolswillbe
giveninMethodology.
o Ages30–39:Thepercentageofindividualswhoare30-years-oldto39-years-old
comparedtothetotallaborforce.
o Ages40–49:Thepercentageofindividualswhoare40-years-oldto49-years-old
comparedtothetotallaborforce.
o Ages50–65:Thepercentageofindividualswhoare50-years-oldto65-years-old
comparedtothetotallaborforce.
Fromthevarioussourceslistedabove,Icompiledadatasetof510observations–
across50statesandWashingtonD.C.and10years.Unfortunately,limitationsexistinthe
datacollectionprocess.Firstly,asmentionedabove,theUIreplacementratiometricwas
missingavalueofFlorida2014;thus,Iwasunabletoincludethatstate-yearinmyfinal
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dataset.Regardingdatacollectionofthecasemanagementvariable,Ihaddifficulty
collectinginformationontheyearthatcasemanagementwasfullyimplemented.Case
managementis,inpractice,anoisyvariabletotrack,asthereislittleinformationonthe
dateofimplementation.Eithercasemanagementhadinformallybeenimplemented
withouthavingitsofficialcasemanagementidentificationoritwasrolledoutslowlywith
nodefinitestartdate.Thus,Iwasforcedtoassumethatallstates–iftheypracticedcase
management–hadalreadyhadtheserviceintactby2007andonwardscompletelyto
2016.ThislimitationwillbefurtherdiscussedasanextensionofmyanalysisinConclusion.
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Methodology
Inordertodeterminetheeffectofunemploymentinsurancelevelandcase
managementonunemployment,Icreatedaseriesofregressionsinordertoisolatethe
effectsofthetwounemploymentbenefits.IultimatelydecidedtouseOLSregressionswith
stateandyearfixedeffects.Statefixedeffectscontrolforunobservablefactorsthataffect
unemploymentthatvaryacrossstates,butnotovertime.Yearfixedeffectscontrolfor
unobservablefactorsthataffectunemploymentthatvaryovertime,butnotacrossstates.
Lastly,robuststandarderrorsthatareclusteredonstateareusedtoaccountfor
heteroscedasticityandautocorrelation.Heteroscedasticitywasdiscoveredbygraphinga
residualvs.fittedvaluesplotafterperformingthefirstseriesofregressionsandobserving
aU-shapedpatternamongtheresidualvalues(FigureBofAppendix).ABreusch-Pagantest
wasalsoconductedtocorroboratethatrobuststandarderrorsareneeded,andtheBPtest
statisticwassignificantata5%level.
TheWaysandMeansCommitteeGreenBookprovidesanumberofmetricsto
measuretheUIgenerositytowardclaimants.Ultimately,onlytheindependentvariableof
maximumweeklybenefitlevelwithdependent(s)isused–therationalebeingthatthe
variablerevealsthelargestamountthatastateiswillingtogivetoaclaimantwhilealso
showingastate’swillingnesstohelpclaimantswhohaveotherindividualsdependingon
them.Moreover,minimumweeklybenefitamounthaslessvarianceovertheobservations
comparedtomaximumamount.ThemaximumweeksofUIeligibilityalsohadverylittle
variationacrossyearsandstates,andIwashesitanttouseavariablewithsmallmovement
fromobservationtoobservation.
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EducationlevelcontrolswereaddedinordertoaccountforthevariabilityinUI
participationratesacrosssubgroupswithdifferentlevelsofeducation.Thesamelogicwas
employedforcontrolsingender,race/ethnicity,andagesubgroups.Tables1,2,and3show
thevariabilityofUIparticipationacrossthefourgroupsofcontrolvariables.
Table1:UIParticipationRatesbyGenderandAgeGroup,2015
Males FemalesAges19-29
1.68% 1.18%
Ages30-39
2.42% 1.77%
Ages40-49
2.69% 1.92%
Ages50-65
2.77% 1.93%
Calculationsaremadeusing2016MarchCPSdata,whichrefertocalendaryear2015.AnindividualwhoreportsreceivinganypersonalincomefromUIin2015iscodedasparticipatinginUI.Thesamplesincludeindividualsaged19-64whoselaborforcestatusisnotmissing.ParticipationratesareweightedbytheMarchCPSpersonweight.
ThefirstsetofregressionsIrunisfortheunrestrictedsample,whichincludesall
individualsaged19-64whoareinthelaborforceandwhoselaborforcestatusisnot
missing.ThemodelspecificationIusefortheunrestrictedsampleisshownbelow:
(1) unemployment_ratest=β0+β1employment_growth_ratest+
β2UI_replacement_ratiost+β3UI_max_benst+β4HS_gradst+β5some_collegest+
β6college_gradst+β7advanced_degreest+β8malest+β9blackst+β10hispanicst+
β11age1929st+β12age3039st+β13age4049st+γs+νt+εst
Thevariablesfromequation(1)havebeendefinedintheDatasection.The
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subscriptssandtareforstateandyearrespectively,andγsandνtareyearandstatefixed
effectsrespectively.TheresultsarereportedinTable4inResults.Regressions(1)and(2)
–indicatedbythecolumns–includetheemploymentgrowthrateandexcludethetwoUI
variables,regressions(3)and(4)excludetheemploymentgrowthrateandincludethetwo
UIvariables,andregressions(5)and(6)includeallthreevariables.Regressions(2),(4),
and(6)includestateandyearfixedeffects,whiletheotherregressionsdonot.Regression
(6),inwhichIincludemeasuresofbotheconomicconditionsandUIprogram
characteristicsontheright-hand-sideandemploystateandyearfixedeffects,ismy
preferredspecification,andIwillfocusmydiscussiononthoseresultsinResults.Variables
weregraduallyincludedintotheequationinordertodeterminetheirimportancein
isolatingtheeffectsofcasemanagementandUIgenerosity.
However,afterthefirstseriesofregressions,Ihadthesuspicionthatlookingata
largersamplemightmasktheeffectofUIforasmallersubgroupthatismoreatrisktotake
upunemploymentbenefits.IlookedintoUIparticipationratesbygender,education,and
race(mythreemaindemographicgroups)inCPSMarchanddiscoveredthatlower-
educatedmales–especiallywhitemalehighschoolgraduates–hadhigherUIparticipation
rates.Forexample,malesthathaddroppedoutofhighschoolhad1.1%moreparticipation
inunemploymentinsurancethanfemalesthathaddroppedoutofhighschool.Acrossthe
board,malesaremorelikelytoparticipateinUI,butthedisparityismostapparentinhigh
schooldropouts,highschoolgraduates,andindividualswithsomecollegeeducation.The
resultsareshowninTables2and3.
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Table2:UIParticipationRatesbyGenderandEducation,2015 Males FemalesHSDropouts
2.56% 1.46%
HSGraduates
3.14% 1.95%
SomeCollege
2.64% 2.12%
CollegeGraduates
1.44% 1.34%
AdvancedDegree
1.12% 0.98%
Calculationsaremadeusing2016MarchCPSdata,whichrefertocalendaryear2015.AnindividualwhoreportsreceivinganypersonalincomefromUIin2015iscodedasparticipatinginUI.Thesamplesincludeindividualsaged19-64whoselaborforcestatusisnotmissing.ParticipationratesareweightedbytheMarchCPSpersonweight.
Table3:UIParticipationRatesbyGender,Education,andRace,2015
WhiteMales Non-whiteMales WhiteFemales Non-white
FemalesHSDropouts
3.24% 2.23% 1.50% 1.44%
HSGraduates
3.76% 2.25% 2.24% 1.58%
SomeCollege
2.91% 2.15% 1.91% 2.46%
CollegeGraduates
1.40% 1.53% 1.32% 1.38%
AdvancedDegree
0.94% 1.54% 0.90% 1.14%
Calculationsaremadeusing2016MarchCPSdata,whichrefertocalendaryear2015.AnindividualwhoreportsreceivinganypersonalincomefromUIin2015iscodedasparticipatinginUI.Thesamplesincludeindividualsaged19-64whoselaborforcestatusisnotmissing.ParticipationratesareweightedbytheMarchCPSpersonweight.
TheadvantageofusingCPSMORGdatasetsistheabilitytonarrowthedemographic
groupinfocuswithoutcompromisingthepowerofthemodel.Thus,afterexaminingthe
unrestrictedsample,Inextrestrictthesampletoincludeonlymalesaged19-64whoarein
thelaborforceandhavelessthanacollegedegree.Intheseregressions,thecollege
24
graduate,advanceddegree,andmalevariablesareexcludedfromtheright-hand-side.The
modelusedforthisrestrictedsampleisshownbelow:
(2) unemployment_ratest=β0+β1employment_growth_ratest+
β2UI_replacement_ratiost+β3UI_max_benst+β4HS_gradst+β5some_collegest+
β9blackst+β10hispanicst+β11age1929st+β12age3039st+β13age4049st+γs+νt+
εst
Finally,Irestrictthesampleevenfurthertoincludeonlywhitemalehighschool
graduatesaged19-64whoareinthelaborforce–thesubgroupwiththehighestUI
participationrates.Whenthoseregressionsareruntheblack,Hispanic,andmalevariables,
andalloftheeducationvariablesareexcludedfromtheright-handside.Duetothesmaller
sizeofthesubgroup,HawaiiandWashingtonD.C.couldnotbeincludedintothedataset–
bothareashadlessthananaverageof30individualswhofitthiscriterionoverthe10
yearsobserved.Themodelusedforthefurtherrestrictedsampleisshownbelow:
(3) unemployment_ratest=β0+β1employment_growth_ratest+
β2UI_replacement_ratiost+β3UI_max_benst+β11age1929st+β12age3039st+
β13age4049st+γs+νt+εst
Forequations(2)and(3),thesamemethodologyisinplacewherevariablesof
interestandfixedeffectsareaddedoveraseriesofregressionsinordertoaccurately
isolatetheeffectofUIbenefitsonunemployment.Forthesesmaller,more-focused
25
samples,myhypothesisisthattheeffectsofUIreplacementratioandUImaximumweekly
benefitwithdependentswillhaveanevengreatermagnitudeeffectonthereductionof
unemploymentrate.TheresultsofthesmallersampleswithhigherUIparticipationare
listedinTablesAandBintheAppendix.
Tostudytheeffectsofcasemanagementonunemploymentrate,Iemployedthe
samemethodologyofaseriesofOLSregressions–usingtwodifferentspecifications:one
withthesimplepresenceofcasemanagement,andanotherwiththepresenceofahigh
levelofintensityforcasemanagementversusalowlevelofintensity.Forthese
specifications,Ifocusedontherestrictedsampleofonlymalesaged19-64whoareinthe
laborforceandhavelessthanacollegedegree–theoreticallythemainrecipientsofcase
managementserviceduetothesubgroup’shighUIparticipationrate.Idecidedagainst
usingtherestrictedsampleofwhitemalehighschoolgraduatesaged19-64inthelabor
force–thesubgroupwiththehighestUIparticipationrate–becausethesamplewastoo
small.Themodelsusedareshownbelow:
(4) unemployment_ratest=β0+β14case_managements+β1employment_growth_ratest
+β2UI_replacement_ratiost+β3UI_max_benst+β4HS_gradst+β5some_collegest+
β9blackst+β10hispanicst+β11age1929st+β12age3039st+β13age4049st+γs+νt+
εst
26
(5) unemployment_ratest=β0+β14case_management_highs+
β15case_management_lows+β1employment_growth_ratest+
β2UI_replacement_ratiost+β3UI_max_benst+β4HS_gradst+β5some_collegest+
β9blackst+β10hispanicst+β11age1929st+β12age3039st+β13age4049st+γs+νt+
εst
Again,thesamemethodologyisinplacewherevariablesofinterestandfixedeffects
areaddedoveraseriesofregressionsinordertoaccuratelyisolatetheeffectofcase
managementonunemployment.TheUIvariablesofgenerosityarealreadyincludedinto
theregressions.TheresultsoftheeffectarelistedinTable5inResults.
27
Results
Afterrunningtheseriesofregressionsforequation(1),Iobservedthatmy
hypothesisthathighlevelsofUIgenerosityleadtoareductioninunemploymentratewas
false.ThecoefficientsandstandarderrorsofthevariablesarelistedinTable4below.
Table4:TheEffectsofEconomicConditionsandUIProgramCharacteristicsontheUnemploymentRateofAllIndividualsAged19-64,2007-2016
Y=Unemploymentrate
(1) (2) (3) (4) (5) (6)UImaxdependentbenefit^
0.372**(0.154)
0.342(0.149)
0.361**(0.149)
-0.260(0.136)
ReplacementratioforUI
-4.265(2.932)
2.779(3.284)
-4.718*(2.896)
2.190(2.981)
Employmentgrowthrate
-0.160***(0.026)
-0.227***(0.038)
-0.159***(0.026)
-0.224***(0.038)
%HSgraduate
-0.134(0.107)
-0.016(0.075)
-0.130(0.105)
-0.031(0.079)
-0.128(0.104)
-0.015(0.076)
%Somecollege
-0.111(0.122)
-0.027(0.064)
-0.105(0.122)
-0.055(0.068)
-0.090(0.124)
-0.024(0.066)
%Collegegraduates
-0.283***(0.089)
-0.181**(0.084)
-0.316***(0.090)
-0.165*(0.093)
-0.301***(0.089)
-0.172*(0.088)
%Advanceddegree
-0.024(0.135)
-0.118(0.077)
-0.068(0.140)
-0.136*(0.081)
-0.059(0.142)
-0.112(0.080)
%Male
-0.219(0.166)
-0.094(0.078)
-0.261*(0.150)
-0.011(0.075)
-0.247(0.155)
-0.096(0.079)
%Black
0.030(0.021)
-0.099(0.067)
0.041**(0.021)
-0.112*(0.066)
0.046**(0.022)
-0.097(0.066)
%Hispanic
0.029(0.033)
-0.032(0.046)
0.030(0.032)
-0.039(0.047)
0.035(0.034)
-0.030(0.047)
R2 0.206 0.872 0.210 0.861 0.230 0.872n 510 510 509 509 509 509
Agecontrols yes yes yes yes yes yesState&yearfixeffects
no yes no yes no yes
Thesampleincludesindividualsaged19-64whoareinthelaborforceandwhoselaborforcestatusisnotmissing.Seethetextforadescriptionofhowtheindependentvariablesaredefined.Robuststandarderrorsthatareclusteredonstateappearinparentheses.***,**,and*indicatestatisticalsignificanceatthe1%,5%,and10%levels,respectively.
^UImaxdependentbenefitisdividedby100toshowitseffectonunemploymentthrough$100shifts
28
ThemostimportanttakeawayfromTable4isthatwhenexaminingtheeffectsofUI
generosityonunemployment,controllingforeconomicconditionsisanecessity.In
regressions(3)and(4),theUImaximumbenefitlevelandtheUIreplacementratioare
includedontheright-handsideandtheemploymentgrowthrateisexcluded.Stateand
yearfixedeffectsareexcludedinregression(3)andthenincludedinregression(4).
Movingfromregression(3)toregression(4),theR2jumpsfrom0.210to0.861,which
demonstratesthatusingyearfixedeffectstocontrolforvariablesthatvaryovertimebut
notacrossstates,suchasnationaleconomicconditions,isessentialtoexplainingvariation
intheunemploymentrate.Addingcontrolsforstate-specificeconomicconditionsfurther
improvesthefitoftheregressionline.Movingfromtheregression(4)specificationtothe
regression(6)specification,inwhichtheemploymentgrowthrateisaddedasaregressor,
increasestheR2from0.861to0.872.Whentheemploymentgrowthraterisesby1
percentagepoint,theunemploymentrateispredictedtodeclinebyabout0.22percentage
points.Inadditiontoemploymentgrowthrate,thepresenceofgraduatingcollegehasa
significanteffectonreducingunemployment–whichfollowsestablishedthinkingthata
collegedegreeleadstomorejobsecurity.Withapercentagepointincreaseofindividuals
withacollegedegreeinapopulation,wepredicttheunemploymentratetodecreaseby
0.17percentagepoints.
TheTable4resultsalsoindicatethattheUIprogramcharacteristicshavelittle
explanatorypower.NeitherthecoefficientestimateontheUImaximumweeklybenefit
amountwithdependent(s)northecoefficientestimateontheUIreplacementratiois
statisticallysignificant.Inregression(2),theemploymentgrowthrateisincludedonthe
29
right-handside,thetwoUIvariablesareexcluded,andstateandyearfixedeffectsare
employed.Movingfromtheregression(2)specificationtotheregression(6)specification,
inwhichthetwoUIvariablesareaddedasregressors,doesnotincreasetheR2.TheR2is
equalto0.872inbothregression(2)andregression(6).
AfinalpointworthemphasizingisthattheTable4resultsindicatethatusingstate
andyearfixedeffectsiscruciallyimportant.Intheregression(5)specification,which
excludesbothstateandyearfixedeffects,thecoefficientestimateontheUIreplacement
ratioisnegativeandstatisticallysignificantatthe10%level.Oncestateandyearfixed
effectsareadded,however,thecoefficientestimatebecomespositiveandstatistically
insignificant.Itcouldbethatwealthierstates,whichtendtohavelowerratesof
unemployment,alsotendtohavehighUIreplacementratiosbecausecitizensand
policymakersfeelthatthegovernmentcanaffordtoreplaceahighpercentageoflost
incomewhenworkersarelaidoffduringadownturnbecauseofthestate’sabundant
resources.Failingtocontrolforthesepotentialsourcesofomittedvariablebiaswiththe
useofstateandyearfixedeffects–suchasinregression(5)–resultsinthemisleading
coefficientestimatesinwhichthetwoUIvariableshaveastatisticallysignificantimpacton
reducingunemployment.
Afterrunningequations(2)and(3),thecoefficientsandstandarderrorsofthe
variablesarelistedinAppendixTableAandB.Thesameresultsasthoseforequation(1)
wereobserved–whenexaminingtheeffectsofUIgenerosityonunemployment,
controllingforeconomicconditionsandunobservedeffectsacrossstatesandacrosstimeis
anecessity.However,evenwiththecontrolsinplace,bothmeasurementsofUIgenerosity
30
donothaveasignificanteffectonreducingunemployment.Forallthreeequations,ajoint
significancetestshowedthatUImaximumweeklybenefitamountwithdependent(s)and
UIreplacementratioarenotjointlysignificant.Acrossallsamples,onlyemployment
growthratehasasignificanteffectonunemployment–whichmakesintuitivesensebased
onfundamentaleconomics.
TableCintheAppendixshowsvariousspecificationsthatusethedifferentUI
generosityvariablestoshowtheirsignificancefortherestrictedsampleofwhitemalehigh
schoolgraduatesaged19-64whoareinthelaborforce.Theresultsshowthatnoneofthe
otherUIgenerosityvariablesaresignificant–exceptforthemaximumweeksofUI
eligibilitywhichissignificantata1%level;however,thecoefficientisincorrectlypositive.
Thiserroneousdirectionmaybeexplainedbythelackofvariationacrossstatesandacross
timeforthemaximumweeksofeligibility–hencethereasonastowhythevariablewasn’t
includedintheoriginalseriesofregressions.
Forthecasemanagementanalysis,equations(4)and(5)wererun,andmy
hypothesisthatthepresenceofcasemanagementleadstoasignificantreductionin
unemploymentwascorrect,buttheresultsdidnotplayoutexactlytomyexpectations.The
coefficientsandstandarderrorsofthisanalysisarelistedbelowinTable5.Again,the
importanceoftheuseofstateandyearfixedeffectsisevident.Whenusingtheregression
(1)and(3)specificationswithoutbothstateandyearfixedeffects,thecoefficientestimate
oncasemanagementisnotsignificant;however,thecoefficientestimateofUImaximum
weeklybenefitamountwithdependent(s)isincorrectlypositiveandstatisticallysignificant
atthe1%level,whilecoefficientestimateofUIreplacementratioisstatisticallysignificant
31
atthe10%level.
Afterthefixedeffectsareaddedinregressions(2)and(4),theUIgenerosity
variablesarenolongersignificant.Forregression(2),casemanagementisnownegative
andsignificantatthe1%level.Thepresenceofcasemanagementispredictedtodecrease
unemploymentrateby3.71percentagepoints.Theresultsofregression(4)hasa
surprisingfinding.Iexpectedbothlevelsofintensityofcasemanagementtohavea
significanteffectonreducingunemploymentandthatahighintensitylevelofcase
managementtohavealargereffectonunemploymentthanasimplepresenceofcase
managementwhilealowintensitylevelofcasemanagementwouldhaveasmallereffect
comparedtothepresenceofcasemanagement.However,onlythecoefficientestimateof
highintensitycasemanagementisstatisticallysignificantata1%level,whilethe
coefficientestimateoflowintensitycasemanagementisnotsignificantatall.Moreover,the
coefficientestimateofhighintensitycasemanagementhasasmallereffecton
unemploymentthanjustthepresenceofcasemanagement.Thus,Iobservethatonlyahigh
levelofcasemanagementintensitycontributestoastatisticallysignificantreductionin
unemploymentrate,whiletheeffectoflowlevelintensityisnegligible.Thepresenceofa
highlevelofintensityofcasemanagementispredictedtodecreaseunemploymentrateby
2.5percentagepoints.Aswiththeotherseriesofregressions,employmentgrowthratehas
aconsistentlysignificanteffectonunemployment–allatthe1%level.
32
Table5:TheEffectsofCaseManagementontheUnemploymentRateofMalesAged19-64withLessThanaCollegeDegree,2007-2016
(1) (2) (3) (4)
Casemanagement
-0.090(0.378)
-3.714***(1.046)
Hightouchcasemanagement
-0.151(0.396)
-2.543***(0.725)
Lowtouchcasemanagement
-0.030(0.481)
0.039(2.426)
UImaxdependentbenefit^
0.484***(0.148)
-0.107(0.232)
0.490***(0.149)
-0.107(0.232)
ReplacementratioforUI
-7.696*(4.138)
5.412(4.482)
-7.754*(4.172)
5.412(4.482)
Employmentgrowthrate
-0.348***(0.040)
-0.405***(0.055)
-0.348***(0.040)
-0.405***(0.055)
%HSgraduate
-0.043(0.076)
-0.054(0.071)
-0.042(0.076)
-0.054(0.071)
%Somecollege
-0.026(0.088)
-0.043(0.074)
-0.025(0.088)
-0.043(0.074)
%Black
0.083***(0.024)
-0.130(0.123)
0.084***(0.024)
-0.130(0.123)
%Hispanic
0.030(0.022)
-0.025(0.063)
0.030(0.022)
-0.025(0.063)
R2 0.228 0.853 0.228 0.853n 509 509 509 509
Agecontrols yes yes yes yesState&yearfixeffects
no yes no yes
Thesampleincludesmalesaged19-64withlessthanacollegedegreewhoareinthelaborforceandwhoselaborforcestatusisnotmissing.Seethetextforadescriptionofhowtheindependentvariablesaredefined.Robuststandarderrorsthatareclusteredonstateappearinparentheses.***,**,and*indicatestatisticalsignificanceatthe1%,5%,and10%levels,respectively.
^UImaxdependentbenefitisdividedby100toshowitseffectonunemploymentthrough$100shifts
33
Conclusion
Ultimately,myUIgenerosityhypothesiswasnotprovencorrectwithempirical
evidence–UIgenerositylevelshavenostatisticallysignificanteffectonreducing
unemployment.TheseresultsalignwithpreviousresearchthatlargerUIbenefitshada
negativeeffectonindividualsleavingunemployment(Meyer1990)andwithconventional
thoughtamongthelaboreconomiststhatmoregenerousUIpoliciesprolong
unemployment.Theimplicationofmyfindingsisthatstatesareunnecessarilyspending
moneyonhighlevelsunemploymentinsurance,aslargeramountsofUIdonottranslate
intoastatisticallysignificantdecreaseinunemploymentrate.Onanindividuallevel,more
generousUIpackagesdonotleadtoindividualsfindingemploymentmoreeasily.
However,asmentionedpreviously,therewerelimitationstomyanalysesthatmay
accountfortheinsignificanteffectsofUIreplacementratioandUImaximumweekly
benefitwithdependent(s)onunemployment.Mydatasetonlyincluded510observations–
withseveralobservationsbeingomittedduetopreviouslymentionedcomplications.As
such,Iwasonlyobserving10yearsofdataacrossthe50statesandWashingtonD.C.When
statefixedeffectswereincludedintotheregression,thestatefixedeffectsmayhave
absorbedallthemovementinthesample–thuseliminatingtheeffectsofmyUI
independentvariablesofinterest.Afutureextensionofmystudycanlookintoincluding
timeperiodsbefore2007intothedataset–thusincreasingtheobservationssuchthat
strongerconclusionscanbedrawn.
Itwouldbeinterestingtolookintoanarrowergroupofindividualswhoaremore
likelytotakeupunemploymentinsurance–perhapsevendividetheCPSdatabymore
34
subgroupsthanmerelygender,race/ethnicity,andeducationlevel.Forexample,future
studiescanlookintoworkersinmanufacturing–individualswhoaremoreatrisktolose
theirjobsandbecomeclaimantsofunemploymentinsuranceinagivenyear–andseeifUI
generosityhasasignificanteffectonthem.Additionally,thefocuscanbenarrowedtoafew
groupsofstatesthathavehadahistoricallylargepercentageoftheworkforcein
manufacturing.TheadvantageofusingCPSdataisthelargesamplesizeitprovidessothat
incrediblynarrowsubgroupscanbeobserved.
Formystudyoncasemanagement,myhypothesisthatcasemanagementleadstoa
reductioninunemploymentisconfirmed.Thepresenceofcasemanagementhasa
significanteffectondecreasingtheunemploymentrate,andadeeperdiverevealsthata
highlevelofcasemanagementintensityhasasignificanteffectonunemploymentwhilea
lowlevelofintensityhasaninsignificanteffect–whichcontradictedmyhypothesisthat
bothlevelsofintensityhaveasignificanteffectonunemployment.Thesefindings
contradictexistingliteraturethatcasemanagementdidnotimprovere-employment
(Gursansky2003)andthatmoreresourcesincasemanagementleadstonosignificant
improvementinshort-termemploymentoutcomes(Peck&Scott2005).However,these
findingssupportedtheanecdotalevidencefoundinstudiesofsmallersubgroupsand
samplesizes(Zanis2001,Siegal1996).
Theimplicationofmyfindingsoncasemanagementisthat,ingeneral,case
managementworks–thepracticeiseffectiveinreducingunemploymentandshouldbe
investedinasacomplementtoexistingre-employmentservices.However,specificityon
theservicesofferedbycasemanagementareimperativeforsuccessfulimplementation.
35
Casemanagersmustbetrainedtoenforcejobsearchstepsforindividualsintheir
caseloads.Thislevelofengagementensuresthatjobseekersareactivelypursuingand
completingstepstowardre-employment.Inaddition,casemanagersmustofferafollow-up
serviceforindividualsintheircaseloadswhohaverecentlysecuredjobs,ensuringthat
individualsnotonlyobtainajobbutalsohaveastablegraspontheresponsibilitiesofthe
job.Statesthatarenotfollowingtheseguidelinesandthatarenotofferingtheseservices
areinvestingtimeandmoneyintocasemanagementprogramsthatwillhavenosignificant
effectoncombattingunemploymentintheirarea.
However,thisanalysisoncasemanagementalsohadlimitationsthatmay
incorrectlygivesignificancetothepresenceofcasemanagementanditsvaryinglevelsof
intensity.Apartfromthesamplesizeissue,IpreviouslymentionedinDatathatIwas
forcedtoassumethatstateswithcasemanagementhadalreadyimplementedtheservice
before2007andcarriedonwiththeservicewithnochangeinintensityuntil2016.Inorder
torelaxthisassumption,afuturestudycangatherthisdatathroughamoredetailed–for
example,bycontactingeachstate’sdepartmentthatfocusesonunemployment,identifying
theexactdatethatcasemanagementwasimplemented,anddiscussingthechangesinstate
casemanagementpracticessinceitsinitialimplementation.
Toconclude,mystudysoughttoshinemorelightonthefulleffectsof
unemploymentbenefitslikeUIgenerosityandcasemanagementthroughaholisticlook
acrossAmericainthemostrecentyearswhilenarrowingfocusintospecificsubgroups.
Thereisstillmoreresearchtobedonetoidentifypracticesthateffectivelycombat
unemployment,andmystudyisacontributiontowardthisgoal.
36
Appendix
FigureA:PublicUnemploymentSpendingofOECDCountries
Source:OECD
FigureB:Residualvs.fittedvaluesplotofmyregressionofequation(1)
0
0.5
1
1.5
2
2.5
3
3.5
BEL
ESP
IRL
FIN
ITA
FRA
NLD PRT
LUX
DEU
AUT ISL
OEC
DCH
ESV
NCZE
AUS
CAN
LVA
HUN
SWE
NZL
USA
SVK
NOR
ISR
EST
GBR
KOR
JPN
TUR
CHL
DNK
PublicunemploymentspendingTotal, %ofGDP, 2013
-20
24
Res
idua
ls
0 5 10Fitted values
37
TableA:TheEffectsofEconomicConditionsandUIProgramCharacteristicsontheUnemploymentRateofMalesAged19-64withLessThanaCollegeDegree,2007-2016
Y=Unemploymentrate
(1) (2) (3) (4) (5) (6)UImaxdependentbenefit^
0.498(0.164)
0.207(0.263)
0.478***(0.155)
-0.107(0.232)
ReplacementratioforUI
-6.548(4.318)
6.569(4.984)
-7.594*(4.215)
5.412(4.482)
Employmentgrowthrate
-0.351***(0.040)
-0.410***(0.056)
-0.348***(0.040)
-0.405***(0.055)
%HSgraduate
0.008(0.087)
-0.055(0.069)
-0.052(0.079)
-0.086(0.074)
-0.046(0.076)
-0.054(0.071)
%Somecollege
0.011(0.091)
-0.046(0.074)
-0.050(0.091)
-0.085(0.079)
-0.030(0.088)
-0.043(0.074)
%Black
0.086***(0.027)
-0.122(0.124)
0.075***(0.024)
-0.131(0.132)
0.083***(0.024)
-0.130(0.123)
%Hispanic
0.045*(0.045)
-0.028(0.064)
0.018(0.020)
-0.029(0.066)
0.029(0.021)
-0.025(0.063)
R2 0.200 0.852 0.185 0.836 0.228 0.853n 510 510 509 509 509 509
Agecontrols yes yes yes yes yes yesState&yearfixeffects
no yes no yes no yes
Thesampleincludesmalesaged19-64withlessthanacollegedegreewhoareinthelaborforceandwhoselaborforcestatusisnotmissing.Seethetextforadescriptionofhowtheindependentvariablesaredefined.Robuststandarderrorsthatareclusteredonstateappearinparentheses.***,**,and*indicatestatisticalsignificanceatthe1%,5%,and10%levels,respectively.
^UImaxdependentbenefitisdividedby100inordertoshowitseffectonunemploymentthrough$100shifts
38
TableB:TheEffectsEconomicConditionsandUIProgramCharacteristicsontheUnemploymentRateofWhiteMaleHighSchoolGraduatesAged19-64,2007-2016
Y=Unemploymentrate
(1) (2) (3) (4) (5) (6)UImaxdependentbenefit^
0.628***(0.173)
0.260(0.241)
0.623***(0.002)
0.112(0.231)
ReplacementratioforUI
-6.430(4.276)
0.929(5.643)
-7.586*(4.158)
-0.303(5.078)
Employmentgrowthrate
-0.331***(0.044)
-0.409***(0.077)
-0.330***(0.042)
-0.400***(0.078)
R2 0.095 0.777 0.104 0.762 0.142 0.777n 490 490 490 489 489 489
Agecontrols yes yes yes yes yes yesState&yearfixeffects
no yes no yes no yes
Thesampleincludeswhitemalehighschoolgraduatesaged19-64whoareinthelaborforceandwhoselaborforcestatusisnotmissing.Seethetextforadescriptionofhowtheindependentvariablesaredefined.Robuststandarderrorsthatareclusteredonstateappearinparentheses.DistrictofColumbiaandHawaiiwereomittedfromthedatasetduetoasmallsamplesizeforeachstate-year.***,**,and*indicatestatisticalsignificanceatthe1%,5%,and10%levels,respectively.
^UImaxdependentbenefitisdividedby100inordertoshowitseffectonunemploymentthrough$100shifts
39
TableC:RobustnessChecksoftheEffectsofEconomicConditionsandUIProgramCharacteristicsontheUnemploymentRateofMalesAged19-64withLessThanaCollege
Degree,2007-2016
Y=Unemploymentrate (1) (2) (3) (4) (5) (6)
UImindependentbenefit^
0.699(1.075)
0.723(1.032)
0.195(0.899)
0.219(0.863)
UImaxbenefit^^
0.045(3.316)
-0.063(3.246)
-0.010(3.226)
-0.135(3.161)
Replacementratio1forUI
3.597(4.763)
4.238(4.674)
3.444(4.978)
Replacementratio2forUI
3.718(3.647)
4.317(3.587)
3.611(3.716)
MaxUIdurationlength
0.247***(0.078)
0.246***(0.078)
0.244***(0.078)
0.243***(0.078)
Employmentgrowthrate
-0.372***(0.057)
-0.371***(0.057)
-0.403***(0.057)
-0.401***(0.056)
0.373***(0.059)
-0.372***(0.059)
%HSgraduate
-0.059(0.069)
-0.057(0.069)
-0.053(0.070)
-0.050(0.070)
-0.059(0.069)
-0.056(0.069)
%Somecollege
-0.036(0.073)
-0.032(0.074)
-0.040(0.074)
-0.036(0.074)
-0.035(0.073)
-0.032(0.074)
%Black
-0.085(0.128)
-0.085(0.128)
-0.137(0.126)
-0.138(0.126)
-0.088(0.131)
-0.088(0.131)
%Hispanic
-0.024(0.063)
-0.023(0.064)
-0.027(0.063)
-0.027(0.064)
-0.024(0.063)
-0.023(0.064)
R2 0.858 0.858 0.853 0.853 0.858 0.858n 509 509 509 509 509 509
Agecontrols yes yes yes yes yes yesState&yearfixeffects
yes yes yes yes yes yes
Thesampleincludesmalesaged19-64withlessthanacollegedegreewhoareinthelaborforceandwhoselaborforcestatusisnotmissing.Seethetextforadescriptionofhowtheindependentvariablesaredefined.Robuststandarderrorsthatareclusteredonstateappearinparentheses.***,**,and*indicatestatisticalsignificanceatthe1%,5%,and10%levels,respectively.
^UIminbenefitisdividedby100inordertoshowitseffectonunemploymentthrough$100shifts^^-UImaxbenefitisdividedby1000inordertoshowitseffectonunemploymentthrough$1000shifts
40
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