The Impact of State Unemployment Benefits on Unemployment...

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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.







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%


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%


TheadvantageofusingCPSMORGdatasetsistheabilitytonarrowthedemographic

groupinfocuswithoutcompromisingthepowerofthemodel.Thus,afterexaminingthe

unrestrictedsample,Inextrestrictthesampletoincludeonlymalesaged19-64whoarein

thelaborforceandhavelessthanacollegedegree.Intheseregressions,thecollege

24

graduate,advanceddegree,andmalevariablesareexcludedfromtheright-hand-side.The

modelusedforthisrestrictedsampleisshownbelow:



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:


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+


εst

26

(5) unemployment_ratest=β0+β14case_management_highs+

β15case_management_lows+β1employment_growth_ratest+



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)


-7.696*(4.138)

5.412(4.482)

-7.754*(4.172)

5.412(4.482)


-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


0.498(0.164)

0.207(0.263)

0.478***(0.155)

-0.107(0.232)


-6.548(4.318)

6.569(4.984)

-7.594*(4.215)

5.412(4.482)


-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




^UImaxdependentbenefitisdividedby100inordertoshowitseffectonunemploymentthrough$100shifts

38

TableB:TheEffectsEconomicConditionsandUIProgramCharacteristicsontheUnemploymentRateofWhiteMaleHighSchoolGraduatesAged19-64,2007-2016

Y=Unemploymentrate


0.628***(0.173)

0.260(0.241)

0.623***(0.002)

0.112(0.231)


-6.430(4.276)

0.929(5.643)

-7.586*(4.158)

-0.303(5.078)


-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



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)


-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


yes yes yes yes yes yes


^UIminbenefitisdividedby100inordertoshowitseffectonunemploymentthrough$100shifts^^-UImaxbenefitisdividedby1000inordertoshowitseffectonunemploymentthrough$1000shifts

40

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42

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43



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