Do temporary help jobs improve labor market outcomes for low skilled workers? : evidence from random assignments

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Paper

Series

Do

Temporary

Help

Jobs

Improve

Labor

Market

Outcomes

for

Low

Skilled

Workers?

Evidence

from

Random

Assignments

David Autor

Susan

N.

Houseman

Working

Paper

05-26

October

27,

2005

Room

E52-251

50

Memorial

Drive

Cambridge,

MA

02142

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MASSACHUSETTS

INSTITUTE

OF

TECHNOLOGY

I

Do

Temporary Help

Jobs

Improve Labor Market

Outcomes

for

Low-Skilled

Workers?

Evidence

from

Random

Assignments

October

2005

Revised

from

January

2005

Abstract

A

disproportionate share oflow-skilled U.S.workersis

employed

by temporary helpfirms.These firms offer rapid entry intopaid

employment,

buttemporaryhelpjobs aretypically briefanditis

unknown

whethertheyfosterlonger-term

employment.

We

draw

upon

an unusual,large-scalepolicyexperimentin

thestate of

Michigan

toevaluatewhetherholdingtemporaryhelpjobsfacilitateslabormarket

advancement

for low-skilled workers.

To

identifytheseeffects,

we

exploitthe

random

assignment of

welfare-to-

work

clients across

numerous

welfare service providers inamajormetropolitanarea.

These

providersfeaturesubstantiallydifferentplacementratesattemporaiyhelpjobs but offerotherwise similar services.

We

find that

moving

welfareparticipants intotemporary helpjobsboosts theirshort-term earnings.Butthesegainsare offsetby lowerearnings, lessfrequent

employment,

andpotentially higher welfare recidivismoverthenextoneto

two

years. In contrast,placementsin direct-hirejobsraise participants' earningssubstantially and reducerecidivismbothoneand

two

years following placement.

We

concludethatencouraginglow-skilled workerstotaketemporaryhelpagency jobs isno

more

effective

-

andpossibly less effective

-

than providingno job placementsatall.

David

H.

Autor

MIT

Department

of

Economics

and

NBER

50

Memorial

Drive,

E52-371

Cambridge,

MA

02142-1347

dautor(g)mit.edu

617.258.7698

Susan N.

Houseman

W.E. Upjohn

Institute for

Employment

Research

300

S.

Westnedge Ave.

Kalamazoo,

MI

49007-4686

houseman(g),upiohninstitute.org

269.385.0434

'

Thisresearchwassupported bythe RussellSage Foundation andtheRockefellerFoundation.

We

are particularly gratefiilto

JoshuaAngrist,OrleyAshenfelter,TimBartik,MaryCorcoran,JohnEarle,RandyEberts,JonGruber, Brian Jacob,Lawrence Katz,AlanKrueger,AndreaIchino,PedroMartins,JustinMcCrar)',Albert Saizand seminarparticipantsatMIT,the

NBER

SummerInstitute,theUpjohnInstitute,theUniversityofMichigan,theCenterforEconomicPolicy Research,theBankof

PortugalandtheSchumpeterInstituteofHumboldtUniversityforvaluable suggestions.

We

are indebtedtoLillian Vesic-Petrovicforsuperb research assistanceandtoLaurenFahey, EricaPavao,andAnneSchwartzforexpert assistancewithdata.

Autor acknowledges generoussupportfromtheSloanFoundationandtheNationalScience Foundation

(CAREER

award SES-0239538).

A

disproportionate shareofminorityand iovv-si<i!!edU.S.wori<;ers is

employed

by temporaryhelp

firms.In 1999,African

American

workers were overrepresented intemporaryhelp agencyjobs by 86

percent, Hispanics by31 percent,and highschooldropouts by 59percent; by contrast,college graduates

were

underrepresented by 47percent(DiNatale 2002). Recent analysesofstateadministrativewelfare

data reveal that 15 to40 percentof formerwelfare recipients

who

obtained

employment

intheyears

followingthe 1996 U.S. welfarereform tookjobs inthetemporaryhelpsector.' These

numbers

are

especiallystriking in light ofthe fact that thetemporary help industry accounts forlessthan 3 percentof

averageU.S.daily

employment.

The

concentrationoflow-skilledworkers inthetemporaryhelp sector has catalyzed a researchand

policy debate aboutwhether temporary helpjobsfosterlabormarket advancement.

One

hypothesis isthat

becausetemporaiyhelp firms face lowerscreening andtermination costs thandoconventional,direct-hire

employers,they

may

choosetohire individuals

who

otherwise

would have

difficultyfindingany

employment

(Katzand

Krueger

1999; Autor and

Houseman

2002b;

Autor2003; Houseman,

Kalleberg,

and Erickcek2003). If so,temporaryhelpjobs

may

reducethetimeworkers spend in unproductive,

potentially discouragingjobsearchandfacilitate rapid entryinto

employment.

Moreover, temporary

assignments

may

permitworkerstodevelop

human

capitaland labormarketcontactsthatlead, directlyor

indirectly, tolonger-term jobs. Indeed,alarge and growing

number

ofemployersusetemporary help

assignments as a

means

toscreenworkers fordirect-hirejobs

(Abraham

1988;Autor 2001;

Houseman

2001; Kalleberg,Reynolds, and

Marsden

2003).

Incontrastto thisview,

numerous

scholarsandpractitionershave arguedthattemporary help

agencies provide little opportunity orincentiveforworkers to investin

human

capital ordevelop

productivejobsearchnetworks andinstead offerworkers a seriesofunstableand primarily low-skilled

jobs (Parker 1994;Pawasarat 1997;Jorgensonand

Riemer

2000). Insupportofthis hypothesis,Segal and

Sullivan (1997)

fmd

thatwhilemobility outofthetemporary help sectorishigh, adisproportionateshare

' _{SeeAutor and}Houseman_(2002b)

on Georgia andWashingtonstate;Cancianetal.(1999) on Wisconsin;Heinrich,Mueser, and Troske (2005) on NorthCarolinaandMissouri;and Pawasarat(1997)on Wisconsin.

ofleaversenters

unemployment

or exits the laborforce. Iftemporaryhelpjobs exclusivelysubstitute for

spellsof

unemployment,

these facts

would

beoflittleconcern.

But

tothedegreethatspells intemporary

help

employment crowd

outproductive direct-hirejobsearch,they

may

inhibit longer-term labor

advancement.

Hence,

the shorttermgainsaccruing fromnearer-term

employment

intemporaryhelpjobs

may

be offset

by

employment

instabilityand poorearningsgrowth.

Distinguishing

among

these

competing

hypotheses isanempirical challenge.

The

fundamental

problem

is thatthereareeconomically large, buttypicallyunmeasured, differencesin skillsand

motivationof workerstaking temporary helpanddirect-hirejobs,as

we show

below. Cognizant ofthese

sample-selectionproblems,several recentstudies,

summarized

below,attemptto identify the effects

of

temporaryhelp

employment

on

subsequentlabormarket

outcomes

among

low-skilland

low-income

populations intheUnited States. Inaddition, aparallel

European

literatureevaluateswhether temporary

help

employment,

aswellasfixed-termcontracts,providea"steppingstone" intostable

employment.

Notably, theserecentU.S. and

European

studies,withoutexception,find thattemporaryhelpjobsprovide

a viableportofentry intothe labormarket andleadtolonger-termlabormarket advancement.'

Inadditionto theirfindings, somethingthese studieshave in

common

isthatthey

draw

exclusively

on

observational datatoascertain causal relationships. Thatis,the research designsdepend

upon

regression

control, matching,selection-adjustment, andstructuralestimationtechniquestoaccountforthe likely

non-random

selectionofworkers withdifferentearnings capacitiesintodifferentjobtypes.

The

veracity

ofthe findingstherefore

depends

criticallyontheefficacy ofthesemethods fordrawingcausal inferences

from non-experimentaldata.

In thisstudy,

we

take analternativeapproachtoevaluating whether temporaryhelpjobs improve

labormarket

outcomes

for low-skilledworkers.

We

exploitaunique, multi-year policy experimentin a

large

Michigan

metropolitan areain

which

welfare recipientsparticipatingina return-to-work

program

As

we

demonstrate below.

Work

Firstparticipants

randomly

assignedtodifferentcontractors had

significantly differentplacementrates intodirect-hireortemporary help jobs butotherwise received

similarservices.

We

analyzethisrandomizationusing an"intentionto treat"

framework

whereby

randomizationalters theprobabilities thatindividualsareplacedindifferenttypes ofjobs(direct-hire,

temporary-help,

non-employment)

duringtheir

Work

Firstspells.

To

assessthelabormarket consequences oftheseplacements,

we

use administrative data

from

the

Work

First

program

linked with

Unemployment

Insurance (UI)

wage

recordsfortheentireStateof

Michigan

forapproximately 39,000

Work

Firstspells initiated

from

1999 to2003.

The

Work

Firstdata

include

demographic

informationon

Work

First participantsand detailedinformation

on

jobsfound

during the program.

The

UI

wage

recordsenable ustotrackearnings ofall participantsovertime,aswell

asprovide labormarkethistories on participants before

program

entry.

Among

Work

First participants

who

found

employment,

about20percentheldtemporary helpjobs.

Our

primary findingisthat"marginal"direct-hire

Work

Firstplacements

-

thoseinduced

by

the

random

assignmentofparticipantsto

Work

Firstcontractors

-

increase payroll earningsby several

thousanddollars,increase time

employed

byoneto

two

quarters,and lowerthe probabilityofrecidivism

intothe

Work

First

program

by 20 percentage points overthesubsequent

two

years.

These

relationships

are significant,consistentacross randomization districts,and economically large.

By

contrast,

we

find

thattemporary-helpplacements improve

employment

andearnings

outcomes

only intheveryshort-term.

Over

timehorizonsofoneto

two

years,temporaryhelpplacements

do

not improve

-

andquitepossibly

worsen

-

these labormarket outcomes. Ratherthanpromotingtransitionsto direct-hirejobs, temporary

helpplacementsprimarily displace

employment

andearnings fromother(direct-hire)jobs.

We

alsoconsiderand present strongevidence against

two

potential threats to validity.

One

isthatthe

adverse findings

we

document

fortemporary helpjob placements could bedriven byageneral association

between "bad contractor" practicesanduseoftemporary helpplacements.

To

addressthisconcern,

we

'_{GiventhediversityoflabormarketinstitutionsinEuropean economies,}

thereisno presumptionthatthecross-country findings

firstestablish thattheestimated negativeconsequences of temporaryhelpplacements areevidentin

almostall oftherandomizationdistricts inour sample, and hencethat our findingsarenot driven bythe

poorpractices of oneor

more

aberrant contractors. Second,toexplorethe concernthatthere

may

beother

important

unmeasured

contractor practices(e.g.,additional supportsandservices) thatexplain thelink

between

contractor

random

assignments andparticipants' outcomes,

we

testandconfirmthat thereis no

remaining, significant variation inthe effectsof

Work

Firstcontractorson participant

outcomes

thatisnot

capturedby contractorplacementrates. Third,

we

find thatdirect-hireand temporaiy agency job

placementrates arepositivelyandsignificantly correlatedacross contractors, a fact thatreducesthe

plausibilityofa scenario in

which "bad"

contractorsprimarily placeparticipants in

temp

agencyjobs and

"good"

contractorsprimarily place participantsindirect-hirejobs. These findingssuggestthatitisjob

placementrates themselves

-

nototherconfoundingfactors

-

thataccountforour

main

findings.

A

second concern

we

tackleisthepossibilityof parameterinstability. Becausecontractorshave

internal discretionabout

which

clients toencourage toward

which

jobtypes, our estimatesmightnot

necessarilyidentify astable"intentionto treat"relationship, as

would

occurif

random

assignments

uniformly raised orloweredthe probabilitythateachparticipantobtained agivenjobplacement

(temporary help, direct-hire,non-employment).

To

addressthis issue,

we

exploit thepanelstructureofthe

datatoanalyzethe labormarket

outcomes

ofparticipants

who

experiencemultiple

Work

Firstspells

during the

sample

window

and

who

are assignedtomultiple contractors(becauseof therepeated

randomization). Fixed-effects instrumental variables

models

estimated

on

thissubsample affirm the

main

findings:using only within-person,over-time variationin

outcomes

forparticipants

randomly

assignedto

contractorswithdiffering placementpractices,

we

estimatethatdirect-hirejobs induced by

random

assignmentsraise post-assignmentearningsand

employment,

whiletemporary helpplacements retard

them. CoiToboratingthis-evidence,

we

demonstratethat"marginal"workers placed intemporary help

positionshave

comparable

pre-placementearningshistories to marginal workersplaced indirect-hire

positions, again indicatingtliatthecontrastbetweentiiepositive labormarket

outcomes

ofdirect-hire

placements andthegenerally negative

outcomes

oftemporary helpplacements resultfromdifferences in

the quality ofjobs,notfrom differences inthe quality of workers placedinthesejobs.

Inadditiontopresenting findings

from models

based onthequasi-experiment,

we

use our detailed

administrative datatoestimate conventional

OLS

andfixed-effects

models

forthe relationship

between

temporally help job-taking and subsequentlabormarket outcomes.Consistent withthe U.S. and

European

literatureabove

-

butoppositetoourmain, quasi-experimental estimates

-

OLS

andfixed-effects

estimates indicate thatworkers

who

taketemporaryhelpjobsfare almostas wellasthose taking

direct-hire positions.

The

contrastwithour core findings suggestseither thatnon-experimentalestimates are

biasedby the

endemic

self-selectionof workers intojobtypes accordingto

unmeasured

skills and

motivation, orthatthere aresubstantialdifferences betweenthe"marginal"treatmenteffectsrecovered by

ourquasi-experimentanalysis and "average"treatmenteffects oftemporary helpplacements observedin

non-experimentaldata.

We

suggestthatthe emerging consensus ofthe U.S.and

European

literaturesthat

temporaryhelpjobsfosterlabormarket

advancement

-

based wholly on non-experimentalevaluation

-should becarefully consideredin lightoftheevidence from

random

assignments."

1.

Prior

evidence

and

the

Michigan

Work

First

quasi-experiment

a.

Prior

non-experimental

estimates

The

characteristics of workers

who

takedirect-hire andtemporaryhelpjobsdiffersignificantly.

Even

in ourrelatively

homogenous

sample,

we

findthat

Work

Firstparticipants

who

taketemporaryhelpjobs

are older,

more

likelytobeblack, and havehigher priorearningsinthetemporary helpsectorthando

participants

who

takedirect-hirejobs(see Table 1).

Not

surprisingly,the contrastwith those

who

takeno

employment

duringtheir

Work

Firstspell is

much

more

pronounced.

These

contrastsunderscorethe

OurmicroeconoiTiicevidenceanswersthequestionof whethertemporar)' helpjobsbenefit theindividualswhotakethem, butit

doesnotinformthequestionofwhetherthe activitiesoftemporaryhelp finnsandotlierflexiblelabormarketinstitutions(suchas

fixed-term contracts)improveor retard aggregate labormarket performance by reducingsearchfrictionsorimprovingtliequality

of worker-firmmatches.SeeKatzand Krueger(1999).Blanchardand Landier(2002),Garcia-PerezandMunoz-Builon(2002),

difficultyofdisentanglingthe effects ofjob-takingon subsequent labormarket

outcomes from

thecauses

thatdetermine

what

jobs aretakeninitially.

Several recent studiesattemptto

overcome

problems

of

sample selection.

Lane

etal. (2003)use

matched

propensity scoretechniquestostudytheeffects of temporaryagency

employment on

the labor

market

outcomes

of

low-income

workers

and

thoseat riskof beingon welfare.

They

cautiouslyconclude

thattemporary

employment

improves labormarket

outcomes

among

those

who

mightotherwise have

been unemployed,

andthey suggestthe useof temporaiy helpjobs by welfare agenciesasa

means

to

improve

labormarket outcomes.

However,

they

acknowledge

thatintheir

Survey

of

Income

and

Program

Participationdata it

was

infeasible toconstructcomparison groupsthatwerewell-

matched

on earnings

histories but differed on jobtypes,

which

led toapotential bias intheestimates.

Using

aresearchpopulation

and

databasecloselycomparable totheone usedinthis study,Heinrich,

Mueser. andTroske (2005) study'theeffectsof temporary agency

employment

on subsequentearnings

among

welfare recipientsin

two

states.

To

controlforpossible selectionbias inthedecisiontotakea

temporaiy agencyjob, they estimate a selection

model

that is identifiedthroughthe exclusionofvarious

county-specificmeasures

from

the

models

forearnings but not

from

thosefor

employment.

Interestingly,

thecorrectionfor selection biashas littleeffect

on

theirregression estimates, suggesting either thatthe

selection

problem

is unimportantorthat theirinstrumentsdo notadequatelycontrol forselectionon

4

unobservable variables. Like

Lane

etal. (2003), they findthattheinitial earningsofthose taking

temporaryhelpjobsare lower than ofthose taking direct-hirejobsbutthatthey aresignificantly better

thanofthose

who

arenot

employed

andtendtoconverge over

two

years towardtheearnings ofthose

initiallytakingdirect-hirejobs.

An

alternativeapproach, pursued by Ferber and Waldfogel (1998) and Corcoran and

Chen

(2004),is

toestimatefixed-effects regressionstoassess whetherindividuals

who

move

intotemporary-helpand

other non-traditionaljobsgenerallyexperience

improvements

in labor-marketoutcomes.

A

virtueofthe

"*

Theirempirical strategyassumesthatthe county-level variablesusedtoidentifythe selectionmodelinfluence earningsonly

fixed-effect

model

isthatitwill purgetime-invariant unobservedheterogeneity in individualearnings

levels thatmightotherwise be a source ofbias.

However,

ifthere isheterogeneityin earningstrajectories

(ratherthan inearnings levels) thatiscorrelatedwith job-taking behavior,the fixed-effects

model

will not

resolve this bias.''

As

isconsistentwithotherwork, thestudies byFerberand Waldfogel (1998) and

Corcoran and

Chen

(2005) find thattemporary helpandothernon-standard

work

aiTangementsare

associated with

improvements

inindividuals' earningsand

employment.

Numerous

recent studies have addressedthe roleof temporary

employment

in facilitatinglabor

markettransitions inEurope. Usingpropensity scorematching methods,Ichino etal.(2004, 2005)

concludethat,relative to startingoffunemployed, beinginatemporary help jobsignificantlyincreases

the probabilityoffinding permanent

employment

within 18months. Ina similarvein, Gerfinetal.

(forthcoming)use matching techniquestoestimatethe effectofsubsidizedtemporaryhelpplacements

on

the labormarketprospectsof

unemployed

workersinSwitzerlandandfind significantbenefits tothese

placements.Booth,Francesconi, and Frank(2002)and Garcia-Perez and

Munoz-Bullon

(2002) studythe

effects

on

subsequent

employment outcomes

of temporary (agencyand fixed-term)

employment

in

Britainand temporary

agency

employment

inSpain, respectively.Theirempirical strategies aresimilarto

thoseused in Heinrich, Mueser, and Troske (2005), andtheyfindgenerally positive effects oftemporary

employment,

as well.

Using

matching andregression controltechniques, studiesby

Andersson

and

Wadensjo

(2004),

Amuedo-Dorantes,

Malo,and

Munoz-Bullon

(2005), and Kvasnicka (2005)also find

positiveeffectsof temporary help

employment on

labormarket

advancement

forworkers in

Sweden,

Spain,and

Germany,

respectively.Zijl etal.(2004) apply astructuralduration

model

to estimate the

effectoftemporary helpjob-takingondurations todirect-hire("regular")

work

intheNetherlands

and

concludethattemporary helpjobs substantially reduce

unemployment

durationsand increasesubsequent

jobstability.

Thefixed-effectsestimatorisideallysuitedtoaproblemwheresuccessiveoutcomeobservationsforeachindividualreflect

simpledeviationsfroma stablemean,i.e.,afi,\ed,additive errorcomponent. Butmanylow-skilledworkers,andespeciallythose receiving welfare,are likely tobeundergoingsignificant shiftsinlabor forcetrajectory astheytransitionfromnon-employment

toemployment. Thisheterogeneity inslopes ratlierthanintercepts will notbe resolvedbythe fixed-effectsmodel.InSection3,

While

all ofthesenon-experimental studies concludethattemporaryhelpjobs improve subsequent

labormarket outcomes,

we

believethat the importance oftheresearch questionalso warrants an

experimental(orquasi-experimental) evaluationtoexploretherobustnessoftheseconclusions.

We

pursuesuchanapproachhere.'

b.

Our

Approach:

The

Michigan

Work

First

quasi-experiment

Most

recipients of

TANF

('Temporary Assistancefor

Needy

Families')benefits

must

fulfill

mandatory

minimum

work

requirements. In Michigan,thoseapplyingfor

TANF

benefits

who

do not

meet

these

work

requirements

must

beginparticipating ina

Work

First

program

designedto helpplace

them

in

employment.

Foradministrativepurposes, welfareand

Work

Firstservicesinthe metropolitan

area

we

studyaredivided intogeographicdistricts,

which

we

referto asrandomizationdistricts.

The

Work

First

program

isadministeredbyacity agency,but the actual provisionofservicesis contracted out

tonon-profit orpublic organizations. Within each geographic district,onetothree

Work

Firstcontractors

provide servicesfor

TANF

recipientsresiding inthedistrictineach

program

year.

When

multiple

contractors provide

Work

Firstservices within adistrict,theyalternatetaking in

new

participants.Thus,

thecontractorto

which

aparticipantisassigneddepends onthe datethat heor she appliedfor benefits.

As

we

demonstrate formally below,thisintakeprocedure is functionally equivalentto

random

assignment.

As

the

name

implies,the

Work

First

program

focusesonplacingparticipants intojobs quickly. All

contractors operating inourmetropolitanareaoffera fairlystandardized

one-week

orientationthat

teachesparticipants basicjob-search andlifeskills. Services suchaschildcareandtransportation are

provided

by

outsideagencies andareavailableon anequal basis to participants atallcontractors.

By

thesecond

week

oftheprogram, participantsare expectedtosearch intensively for

employment

and areformally requiredtotakeany jobofferedto

them

provided it paysthe federal

minimum

wage

and

'_{Theapproachtaken}

inthispaperfollowsourearlier pilotstudy(AlitorandHouseman2002a),whichexploits asmaller

quasi-experimentalrandomization of

Work

Firstparticipantsinanothermetropolitan areaofMichigan and analyzesonlyshort-temi labormarketoutcomemeasures. (UnemploymentInsurancewagerecordswerenot availablefor thatstudy.)Theearlierstudyand

thecurrentworkboth findpositiveshort-temieffectsof temporaryhelpplacements onearnings.ByutilizingUIrecordsto

satisfies

work

hoursrequirements. Althougli Wori< First participants

may

findjobs ontlieirown, job

developersat eachicontractor play anintegral roleintheprocess. Thisrole includesencouragingand

discouraging participants fi-omapplyingforspecificjobsandto specificemployers, referringparticipants

directly tojob sitesforspecific openings, andarrangingon-sitevisitsby employers

-

including temporary

help agencies

-

thatscreenand recruitparticipants atthe

Work

Firstoffice.For example,Autor and

Houseman

(2005,Table 1)report that24percentofcontractorssurveyed inthismetropolitan arearefer

participants totemporaryhelpjobson a

weekly

basis,while 38 percent

make

suchreferralsonly

sporadically or never. Similarly, 14 percentofcontractors directly invitetemporaryhelpagencieson-site

weekly

or

monthly

to recruit participants, while29 percentofcontractorsneverdoso.

The

correlations

betweenthese frequenciesandcontractors' (self-reported)temporaryagency placementrates are0.29for

on-site visitsand 0.53 fortemporaryagencyreferrals,thelatterof

which

is highlysignificant. This

indicates thatthejobs that participantstake

depend

in partoncontractors'

employer

contactsand,

more

generally, onpolicies that foster ordiscouragetemporary agency

employment

among

participants.

It is logical toask

why

contractors' placementpractices significantly vary.

The most

plausible

answer

isthatcontractors areuncertainabout

which

types of job placementsare

most

effectiveand hence pursue

different policies.Contractors do nothaveaccessto

UI

wage

recordsdata(used in thisstudy toassess

participants' labormarket outcomes), andthey collectfollow-updataonlyforashorttime periodand

onlyforindividuals placedinjobs. Hence,theycannotrigorously assesswhether job placements improve

participant

outcomes

orwhetherspecificjob placementtypes matter.During in-personand

phone

interviewsconducted forthisstudy, contractors expressedconsiderable uncertainty,and differing

opinions, aboutthe long-termconsequences of temporary job placements (Autor and

Houseman

2005).

We

exploit these differences,which impacttheprobabilityoftemporary agency,direct-hire,or

non-employment

among

statistically identical populations,to identifythe effects of

Work

First

employment

Participants reenteringthesystemforadditionalWorkFirstspellsfollow thesameassignment procedureandthusmaybe

and jobtypeon long-termearningsand

program

recidivism. Inoureconometricspecification,

we

use

contractorassignmentasan instrumental variable affectingtheprobabilitythata participant obtains a

temporary help job, adirect-hirejob, or

no

job duringtheprogram.

Our methodology

doesnot

assume

thatcontractorshave noeffecton participant

outcomes

otherthan

throughtheireffects

on

job placements

-

onlythatanyother practices affectingparticipant

outcomes

are

uncorrelatedwithcontractorplacementrates.

However,

fewresourcesarespenton anything butjob

development

(Autorand

Houseman

2005).General orlifeskillstraining providedinthe first

week

ofthe

Work

First

program

isvery similar acrosscontractors.

And

supportservices intendedto aidjobretention,

suchaschildcare andtransportation,are equally availabletoparticipants inallcontractorsandare

providedoutsidetheprogram.

Survey

evidencecollected forthe majorityofcontractors in oursample

confirmsthat

Work

Firstservices otherthanjob placementsarealmostentirelystandardized across

contractorsoperating in thismetropolitanarea(Autorand

Houseman

2005). InSection4,

we

provide

econometric evidence supportingthevalidityoftheidentificationassumption.

2.

Testing the research design

a.

Data

and

sample

Our

research dataarecomprised of

Work

Firstadministrative records data linkedto quarterly

earnings

from

the Stateof Michigan's

unemployment

insurance

wage

records data base.

We

use

administrativedataonall

Work

First spells initiatedfromthe fourthquarterof1999 throughthe first

quarterof

2003

inthemetropolitanarea.

The

administrative datacontain detailed information

on

jobs

obtainedby participantswhilein the

Work

Firstprogram.

To

classifyjobs intodirect-hireand temporary

help,

we

use the

names

ofemployersat

which

participantsobtainedjobsinconjunctionwithcarefully

q

compiled lists of temporary helpagencies in themetropolitanarea. Inasmall

number

ofcases

where

the

*_{Inasurveyofcontractorsoperating}inthis city,half indicated theyweredirectlyinvolvedin75percent ormoreofWorkFirst

participantjob placements, and85 percentofcontractorstookcredit formoretlian50percentofthejobs obtainedintheir

program(AutorandHouseman2005).

'Particularlyhelpftilwasacomprehensivelistof temporaryagencies operatinginourmetropolitan areaasof 2000, developed by DavidFasenfestandHeidi Gottfried.

appropriate coding ofan

employer

was

unclear,

we

collected additional informationonthe natureofthe

businessthroughaninternetsearch ortelephonecontact.

We

alsousetheadministrative datatocalculate

theimplied

weekly

earnings foreach

Work

Firstjobbymultiplyingthehourly

wage

rateby

weekly

hours.

The

Ul data include totalearningsin thequarterandthe industry in

which

theindividual hadthe

most

earningsinthe quarter.

We

use

them

toconstruct pre- andpost-

Work

FirstUI earnings foreach

participant forthe fourtoeight quarters prior toand subsequenttothe

Work

First placement.

In 14 ofthedistricts inthe metropolitanarea,

two

or

more

Work

Firstcontractors servedthedistrict

overthetime period studied. In

two

districts,however, one contractorineachdistrict

was

designatedto

serve primarily ethnic populations,andparticipantswere allowedtochoosecontractorsbasedon language

needs.

We

dropthese

two

districts

from

oursample.

We

further limitthesampleto spellsinitiated

when

participantswere

between

the ages of16and 64 and dropspells

where

reportedpre-orpost-assignment

quarterly

UI

earnings valuesexceed $15,000 in asinglecalendarquarter. These restrictionsreduce the

sample by lessthan 1 percent. Finally,

we

dropall spells initiated inacalendar quarter inanydistrict

where

oneor

more

participating contractorsreceivednoclients duringthe quarter, asoccasionally

occurred

when

contractorswere terminated andreplaced.

Table 1 summarizes the

means

ofvariableson demographics,

work

history,andearnings following

program

entry forall

Work

Firstparticipants inourprimarysampleaswellas by

program

outcome:

direct-hirejob, temporaiyhelp job, ornojob.

The

sample ispredominantly female(94 percent)and black

(97percent). Slightlyunderhalf (47 percent)of

Work

Firstspells resultedinjob placements.

Among

spellsresulting injobs, 20 percenthave at leastone jobwith atemporaryagency.

The

average earnings

andtotal quartersof

employment

overthe fourquarters following

program

entry arecomparable forthose

TheUIwagerecordsexcludeearningsoffederalandstateemployees and oftheself-employed.

'

'Thisfurtherreducedthe finalsample by3,091spells,or7.4percent.

We

haveestimatedthemainmodelsincluding these

observations with near-identicalresults.

obtainingtemporaryagency and direct-hire jobs, while earnings andquartersof

employment

forthose

who

do not obtain

employment

duringthe

Work

First spell are

40

to50percent lower.

The

averagecharacteristics ofparticipants varyconsiderablyaccordingtojob outcome.

Those

who

do

not findjobs whilein

Work

Firstare

more

likely tohave droppedoutof highschool,tohave

worked

fewerquarters before entering the program, andtohave lowerprior earnings than those

who

find jobs.

Among

thoseplaced injobs,those takingtemporai7

agency

jobs actuallyhave

somewhat

higheraverage

priorearningsandquarters

worked

than those takingdirect-hirejobs.

Not

surprisingly, those

who

take

temporally jobswhile inthe

Work

First

program

havehigherpriorearnings and

more

quarters

worked

in

thetemporary help sectorthanthose

who

takedirect-hire jobs. Data used inpreviousstudies

show

that

blacksare

much

more

likelythan whites to

work

intemporary agency jobs (Autor and

Houseman

2002b;

Heinrich, Mueser, and Troske2005).

Even

in ourpredominantly African-American sample,

we

also find

thisrelationship.

The

tablereveals onefurthernoteworthypattern:hourly wages,

weekly

hours, and

weekly

earnings

areuniformlyhigherforparticipantsintemporary helpjobsthan forthose in direct-hirejobs. This pattern

stands in contrasttothewidelyreported finding oflower

wages

intemporary help positions (Segal and

Sullivan 1998; General

Accounfing

Office2000; DiNatale2001).

Although

it is possiblethatthispattern

isspecific totheregional labormarket

we

study,

many

studiesthatreportlowerearnings fortemporary

help

agency

jobs, includingSegal and Sullivan (1998),relyon quarterly

unemployment

insurancerecords

which

reporttotal earnings but nothoursof work.

Because

temporary help jobs aregenerallytransitory,

theabsence of hours information in UI data

may

lead tothe inferencethattemporary helpjobspay lower

hourly

wages

when

in facttheysimply provide fewertotal hours.

b.

Testing

the efficacy of the

random

assignment

If

Work

Firstassignments arefunctionally equivalentto

random

assignment, observedcharacteristics

ofclients assignedto contractors within arandomization districtshouldbe statisticallyindistinguishable.

'^_Note

thatbecauseparticipantswhodonotfindjobs duringtheirWorkFirstassignmentsface possible sanctions, unsuccessful participantscontinuetofacestrongworkincentivesafterleavingWorkFirst.

We

testthe

random

assignment across contractors withinrandomization districtforeach

program

year by

comparing

the following tenparticipant characteristics; gender,white race, other(non-white)race, age,

elementary-school-onlyeducation,post-elementary high-schooldrop-outeducation,

number

ofquarters

worked

intheeight quarters before

program

entry,

number

ofquarters primarily

employed

with a

temporary agency inthese prioreightquarters,total earnings inthese prioreight quarters,andtotal

earningsinthe prioreight quarters

from

quarterswhereatemporaryagency

was

the primary employer.

With

ten participantcharacteristics,

we

are likelytoobtain

many

falserejectionsofthe null(i.e..

Type

Ierrors), andthisisexacerbatedby the fact thatnotall participant characteristics areindependent(e.g.,

lesseducated participants are

more

likely to beminorities).

To

resolve these confoundingfactors,

we

use

a

Seemingly

Unrelated Regression

(SUR)

systemtoestimatetheprobabilitythattheobserveddistribution

ofparticipantcovariates across contractors withineach randomizationdistrictandyearisconsistentwith

chance. ^

_The

_SUR

_{accountsforboththe multiplecomparisons(ten)simultaneously ineach district}

_and

thecorrelations

among

demographic

characteristicsacrossparticipantsateachcontractor.

Formally,let X*„ be a

^xl

vectorofcovariatescontaining individual characteristics forparticipant

/ assignedtoonecontractorin district

d

during year t. Let Z^, be avectorofindicatorvariables

designating thecontractorassignment forparticipant /,

where

the

number

ofcolumns in

Z

isequalto the

number

ofcontractors in district

d

. Let /,. bea ^ by k identitymatrix.

We

estimatethefollowing

SUR

model:

(1)

x,=(/,®(z„

1))^+^

x„={xi,:,...,x:;)'.

Here, Xj^ isastackedsetoftheparticipant covariates, theset ofcontrol variables include contractor

assignment

dummies

anda constant, and

^

isa matrixoferrortermsthatallows forcross-equation

correlations

among

participant characteristicswithin district-contractorcells.'""

The

p-value forthe joint

'^_This

methodfor testingrandomizationacrossmultipieoutcomesisproposedbyKlingetal.(2004)and Kiing andLiebman (2004).

Since the contractorassignmentdummiesin Z aremutuallyexclusive,oneisdropped.

significanceofthe elements of

Z

in thisregressionsystem providesan

omnibus

testforthenull

hypothesisthatparticipant covariatesdonot differ

among

participantsassignedtodifferentcontractors

within adistrict

and

year;ahighp-value correspondstoan acceptance ofthis null.

Table 2 providesthe chi-squarestatistics andp-valuesforthesignificance of

Z

inestimatesof

Equation(1) foreach ofthe 41 district-by-yearcells inoursample. Consistent withthe hypothesisthat

assignment ofparticipantsacross contractors operatingwithineach district is functionally equivalentto

random

assignment,

we

find that46 of

48

comparisonsacceptthe nullhypothesis atthe 10percent level

and

47

of48 at the 5 percent level.

We

nextperform groupedstatisticalteststoevaluate thevalidityofthe

randomizationforthe entireexperiment. Sinceparticipantassignmentsare independentacrossdistricts

and overtime, thechi-squareteststatistics ineachcellcan be

combined

toform anoverall chi-squared

test statistic

(DeGroot

and Schervish 2002,

Theorem

7.2.1).

As

is

shown

inthefinal

row and column of

Table2,the overall p-valueoftherandomizationacrossall41 cells inoursamples is0.33,with

587

degreesof freedom. Moreover,the nullofparticipantbalance across contractorswithin districtsis

acceptedatthe 5percentlevelorbetter ineach ofthe 12districts and inall fouryearsofthesample.In

sum,thedataappeartoaffirmthe efficacyofthe

random

assignment.

c.

The

effect

of

contractor

assignments

on

job

placements

Our

research designalso requiresthatcontractor

random

assignmentssignificantly affectparticipant

job placement outcomes.

To

testwhetherthisoccurs,

we

estimatedasetof

SUR

models akinto equation

(1)

where

the dependentvariables areparticipant

Work

Firstjob

outcomes

(direct-hire,temporary help,

non-employment).

These

tests providestrong supportforthe efficacyofthe research design:alltestsof

contractor-assignmenteffectson participantjob placements

-

eitheracross contractorswithin a year or

'^

Sevenof 48district-by-yearcellsaredropped becausethereisonlyone(orinsomecasesno) participating contractorinthe

districtformostorallofthe year. Intwodistrict-by-yearcells,one matchingcharacteristics(raceor education)wasidentical for

allrandomly-assignedparticipants;wetherefore didnottestforequalityofthis characteristicwithin thecell,andthedegreesof freedomforthechi-squarestatisticarereducedaccordingly.

within contractors across years

-

rejecttinenull atthe 1 percentlevel orbetter.

The omnibus

testforall 41

comparisonsalso rejectsthe nullat well

below

the 1 percentlevel.'*

Are

the effects of randomization on participantjobplacement

outcomes

economically large in

additionto beingstatistically significant?

To

answerthisquestion,

we

calculatepartialR-squared values

fromaset ofregressions ofeachjob placement

outcome on

the

random

assignment

dummy

variables.

Thesepartial-R-squared values are0.019 forany

employment.

0.013 fortemporary help

employment,

and

0.011 fordirect-hireemployment.

We

benchmark

thesevalues againstthe partialR-squaredvalues from a

setofregressions ofthethreejob placement

outcomes

on

allotherpre-determined covariatesin our

estimates including theten

demographic

andearnings history variablesdiscussedabove andacomplete

setofdistrict-by-year andcalendar-year-by-quarterofassignment

dummies.

The

partial-R-squared values

forthesepre-determined covariatesare0.036 forany

employment,

0.024 fortemporaryhelp

employment,

and 0.026 fordirect-hire

employment.

A

comparison ofthe

two

sets ofpartialR-squared values

shows

thatthe

random

assigmnentsexplain40to 55 percentas

much

ofthe variation injob placement

outcomes

among

participants asdothe

combined

effects of demographics,earnings history,anddistrictand time

effects.

We

concludethatthe

economic

magnitude ofthe randomization

on

job-taking

outcomes

is

substantial.

3.

Main

results:

The

effects

of

job

placements

on

earnings

and

employment

We

now

use thelinked quarterly earnings records fromthe stateof Michigan's

unemployment

insurancesystem toassess

how Work

Firstjob placementsaffect participants' earningsand

employment

overthesubsequenteightcalendar quarters following

random

assignment.

Our

primaryempirical

model

is:

(2) };„„

=a

+

/ij,+P,D,

+

X;p, +

y,

+0,+

{y,x0,)

+

f,^.,,

,

^_{Tablesdisplaying these}

resultsareavailablefromtheauthors.Atthe district-by-yearlevel,werejectthe nullhypothesisof no

contractoreffectson job placement outcomesin36 of41district-year cellsatthe1percentlevel,andwerejectatthe 5percent

level in39of41 cells.

where

thedependentvariable is real

UI

earnings or quarters of UI

employment

followingthequarterof

Work

Firstassignment. Subscript ; refers toparticipants,

d

to randomizationdistricts, c tocontractors

withinrandomizationdistricts, and t toassignmentyears.

The

variables Z), and 7^ are indicatorsequalto

one

ifparticipant i obtained a direct-hire ortemporary-agency jobduring the

Work

Firstspell.

The

vector

ofcovariates,

X

, includesgender, race (white, black, or other), age,education (primary school only,high

school dropout, highschool graduate, greaterthan highschool), and

UI

earnings(in real dollars) forthe4

quartersprior to

random

assignment.

The

vectors

y

and contain

dummies

forrandomizationdistricts

and

year

by

quarterof

random

assignment.

The

coefficients ofinterest inthis

model

are /]^ and /?,,

which

providetheconditional

mean

difference inhoursandearningsfor participants

who

obtaineddirect-hire ortemporary-agencyjobs

duringtheir

Work

Firstspells relative toparticipants

who

did notobtainany

employment.

The

estimation

sample

includes38,689 participantspells initiated

between

1999 and

2003

inthe 12randomization

districts inour sample.

To

accountforthegrouping ofparticipants withincontractors,

we

use

Huber-1

R

White

robust standard errorsclusteredatthecontractor x yearofassignment level.

Insubsequent two-stage leastsquares

models

(2SLS),

we

instrument

T

and

D

with

contractor-assignment-by-year

dummy

variables.For purposes ofthe

2SLS

models, useofthese contractor-by-year

dummy

variables is almost identical tousing contractor-yearplacement jobrates(byjobtype)as

instrumental variables. Accordingly,this

model

can be convenientlyapproximatedas

"_{It isnot yet feasibletotrackpost-assignmentearningsformorethan eight quartersbecausemanyof}theWorkFirst

assignmentsinourdataoccurredasrecently as2002and 2003.

'^_{Thesestandarderrorsdonot,however, accountforthefact thatthereare25,802 uniqueindividuals represented}inourdataand

sosomeparticipantshaverepeatspells,whichmayinduceserialcorrelationinemploymentoutcomesacrossspells forthesame individual.

We

demonstratebelowthatourresultsarequalitativelyidenticalwhenthesampleislimitedtothe firstspellforeach

participant(see alsoAppendixTable 1).

"

_{It isalmostidentical becausemeansand}

_dummy

_variableswilldiffer slightlyifthereisany samplecorrelationbetween

contractordummiesandparticipantcharacteristics.However,wehavealready establishedtliat,becauseoftherandom assignment,thiscorrelationisnot significantly differentfromzero.

where

Pa

and

Pa

are contractoi"x yeartemporary helpanddirect-hire placementrates, and

where

the

error term is partitioned into

two

additivecomponents, e.^j,

=

r^,

+

co^^^^.

The

firstis acontractor-by-year

random

effect, reflecting unobservedcontractor heterogeneity.

The

secondisaparticipant-spell specific

iid

random

errorcomponent. Equation(3) underscores thetwo key conditionsthatour identification

strategy requiresfor valid inference. First, it mustbethecasethat co isuncorrelated with

Pa

and

Pa

, a

conditionthatis (almost)guaranteedtobe satisfied bytherandomization.

The

second condition isthat

contractor-by-year

random

effectsare

mean

independentofcontractorplacementrates, i.e.,

E{v^^Pj)

=

£(v'„P^°) .It istherefore not problematicforourestimation strategy ifcontractors have

significant effectsonparticipant

outcomes

through

mechanisms

otherthanjob placements(e.g.,other

activitiesand supports)providedthattheseeffects arenotsystematicallyrelated tocontractorjob

placementrates.

We

proceed for

now

undertheassumptionthatthis condition issatisfied and

examine

corroborating evidencein Section4.

a.

Ordinary

least

squares estimates

To

facilitatecomparisons withearlier empirical work,

we

begin ouranalysiswith ordinary least

squares

(OLS)

estimatesof Equation (2).

The

firsttwo

columns

of Table 3 presents

OLS

estimates of

Equation (2) forrealearnings andquarters of

employment

for thefirst four calendar quartersfollowing

Work

Firstassignment forall38,689 spellsinourdata.

As

shown

in

column

(1),participants

who

obtainedany

employment

duringtheir

Work

First spellearned

$789

more

inthecalendar quarter

following UI placementthan didclients

who

did not obtain

employment.

Interestingly, there is little

difference

between

thepost-assignmentearningsofparticipants takingdirect-hireand temporary help

jobs. Firstquarter earningsare estimatedat$803 and $731, respectively.

These

contrasts are significantly

differentfromzero butnotsignificantly differentfrom oneanotheratthe 5 percent level {

p

=

.09).

Additional rows of Table 3 repeat the

OLS

estimatesfortotal

Ul

earningsinthefourquarters

following

program

entry.Participants

who

obtained any

employment

duringtheir

Work

Firstassignment

earned approximately $2,500

more

overthe subsequentcalendaryear than those

who

did not. Inall

assignmentquarters, those

who

obtaineddirect hireplacements earned about 15 percent

more

than those

who

obtainedtemporaryhelpplacements. PanelB,

which

presents comparable

OLS

models

forquarters

of

employment

following

Work

First assignment,

shows

thatparticipants

who

obtaineddirect-hireor

temporary helpjobs

worked

about0.9calendar quarters

more

overthesubsequentyearthandid

participants

who

did notfind work.

Table 4 extendsthe UI earnings and

employment

estimatesto

two

fullcalendar years following

Work

20

Firstassignment.

Over

thisperiod, participants

who

obtainedtemporary helpanddirect-hire placements

earned $3,385 and $4,212

more

thanthose

who

did not findajob and

worked

anadditional 1.2and 1.3

quarters respectively(bothsignificantat

p

=

0.01).

b.

Instrumental

variables

estimates

The

preceding

OLS

estimates areconsistentwithexisting research,

most

notablywith Heinrichet al.

(2005),

who

findthatMissouri andNorth Carolinav/elfarerecipients takingtemporaryhelpjobs earn

almostas

much

overthesubsequent

two

yearsasthoseobtaining direct-hire

employment -

and

much

more

than non-job-takers. Like Heinrichetal., ourprimary empirical

models

forearnings and

employment

containrelatively rich controls, includingprior(pre-assignment) earningsandstandard

demographic

variables. Instrumental variables estimatesforthe labormarket consequences of

Work

Firstplacements appear initiallytobe consistentwiththe

OLS

models.

The

2SLS

models

in

columns

(3)

and (4)of Table 3 confirm aneconomically largeandstatisticallysignificantearnings gainaccruing

from

Work

Firstjob placements during thefirstpost-assignmentquarter.

The

estimated gaintoa

Work

First

job placement,

$559

(/

=

5.8),isabout 25 percentlessthanthe analogous

OLS

estimate.

When

job placements aredisaggregated by

employment

types, however, discrepanciesemerge.

Temporary

help anddirect-hirejob placements are estimatedto raise quarterone earningsby

$460

and

^°_To

includeU!outcomesforeightcalendar quartersfollowingassignment,wemustdropallWorkFirstspells initiated after

2002.This reducesthesampleto27,029spells. ^'

Allof ourmainmodelscontrol fordemographic andearnings history covariates as wellas fortimeanddistrictduinmies and

theirinteraction.

OLS

(butnotIV)estimatesofwageandemploymenteffectsofdirect-hireand temporary-help placementsare

about 20percentlargerwhenthesedemographic and earnings history controlsareexcluded(estimates availablefromthe authors).

$622

respectively.Both arestatisticallysignificant. Whileavailableprecisiondoesnotallow usto reject

the nullhypothesis thatthese point estimates are

drawn

from

the

same

distribution

_{p

=

0.49), itis

noteworthythatthe

IV

estimatefortheearningsgainfrom temporaryhelp placementsisapproximately

25 percentsmaller thanthe

wage

gainfor direct-hirejobs.

Comparable

2SLS

models

forquartersof

employment

(ratherthan earnings)confirm important differences inthe

employment

consequences of

temporary helpanddirect-hirejob placements.Placements in direct-hirejobsraisethe probabilityofany

employment

inthefirst post-assignmentquarterby 36 percentage points (?

=

6.1).

By

contrast,

placements intemporaiy helpjobsraisetheprobability offirstquarter

employment

by only 12 percentage

points. Thispoint estimateis notdistinguishable from zero(/

=

1.7), but itis significantly different

from

the pointestimatefordirect-hireplacements.

When

the

wage

and

employment

analysis isextended

beyond

thefirst post-assignmentquarter,a far

more

substantial disparity isevident. In thefirstfourcalendarquarters followingassignment.

Work

First

clientsplaced intemporary helpjobsearn$2,470 lessthan those receiving adirect-hire placement and

$306

lessthan those receivingno placementatall(thoughthis lattercontrastis insignificant). Estimates

forquarters of

employment

tellacomparablestory. Direct-hire placementsraise totalquarters

employed

by0.90 overthesubsequent fourcalendar quarters{t

=

6.5), whiletemporaryhelpplacementshave an

economically small andstatistically insignificanteffectontotal quarters

worked

inthefirstyear.

Examining outcomes

overatwo-yearperiod following

Work

Firstassignment(Table4)addstothe

strengthoftheseconclusions. Estimated lossesassociatedwithtemporary helpjob placements are sizable,

$2,176 in earningsand0.16 calendar quartersof

employment,

thoughnotstatisticallysignificant.

By

contrast, direct-hireplacementsraise earningsby $6,407 andtotalquarters of

employment

by 1.56over

two

years. Forboth estimates,

we

caneasily reject the null hypothesisthatthe effects ofdirect-hire and

temporary-help job placements areequal.

The

clearpicture thatemerges fromthese

2SLS

models

isthat

temporaryhelpplacements

do

not

improve

-

andpotentially

harm

-

labor market

outcomes

forthe

Work

Firstpopulation.-"

c.

The dynamics

of earnings,

employment,

and

Work

First

recidivism

To

betterunderstandthe disparate impacts oftemporary helpand direct-hirejobplacements,

we

explore the

dynamics

underlyingtheseoutcomes.

We

firstestimate asetof

2SLS

models thatdistinguish

between

employment

and earnings intemporary help versusdirect-hire jobs. Specifically,

we

estimate a

variantofEquation(2)

where

thedependentvariable isearnings or

employment

intemporary help

employment

ordirect-hire

employment.

Participantsnot receiving earnings or

employment

inthe relevant

23 sectorare

coded

aszero torthese

outcome

measures.

Table5

shows

thatmarginal

temp

workersearnan additional

$999

and

work

an additional0.48

quarters intemporary help jobs inthe firstcalendaryearfollowing

random

assignment.(Bothare

significant.)

However,

these gains intemporaryhelp earningsand

employment

appearto

come

atthe

expense ofearnings and

employment

indirect-hirejobs.

We

estimatethattemporary help placements

displace $1,486 indirect-hireearningsand 0.48 quarters indirect-hire

employment

inthefirstyear.

On

net,the first-quarterbenefits totemporary helpplacements, clearlyapparentinTable4,

wash

outentirely

overthe firstyear.

As shown

in thebottom panelof Table 5,direct-hireplacementscontinuetohavelarge

positiveandsignificantimpacts ondirect-hire earningsand

employment

inthesecond post-assignment

year, whereas temporary helpplacements have nostatisticallysignificant effect

on

employment

and

earningsineitherdirect-hire ortemporaryagency jobs overthishorizon.Thus,thepositive short-term

benefitsof temporaryhelp placements displayed inTable 3 derive entirely fromincreased

employment

in

' _{Thestandard errorsthatweestimateabove cannot simultaneously account}forthe clusteringoferrorsamongparticipants assignedtoacontractorandtheclusteringoferrorsacrosstime withinthesameindividual.

We

evaluatetlieimportanceofserial

correlationbyestimatingkeymodelsusing only thefirstWorkFirstspellperparticipant.Thesefirst-spellestimates,shownin

Appendi.xTable 1,arecloselycomparabletoourmainmodelsforearningsandemployment

m

Table3.Notably,giventhe

one-thirdreductioninsamplesize,theslightreductionintheprecisionoftlieestimates indicatesthatdieprecisionof our primary

estimatesisnot substantially affectedbyserialcoirelation.

^"'

Forasmallsetofcases,theindustrycodeismissing fromthe UIdata(thoughwedo measuretotalearningsand employment). Theseobservations are includedintheTable5analysis but theoutcomemeasuresarecodedaszeroforboUidirect-hireand temporary-helpearningsandemployment. Consequently,theTable5point estimatesdonotsumpreciselytothetotalsinTables

3and4. In theWorkFirstadministrative case datausedtocode jobtypesobtained duringthe WorkFirst spell,jobtypes

(temporaryhelp ordirect-hire) are identifiedbyemployernamesin allcases.

thetemporary helpsector;

we

find no evidencethattemporaryagency placements help workers transition

todirect-hire jobs.

To

furtherexplorethe

dynamics

of job placementand jobholding,

we

also

examine

how

job

placement typeaffects

Work

First

program

recidivism.

Using

Work

Firstadministrative data,

we

implement

a variant of Equation(2) wherethedependentvariable isan indicator variable equaltooneifa

participantreturnsto

Work

Firstwithin

360

or 720 days ofthe

commencement

oftheprior spell.

As

shown

inTable 1,36 percentofthe

Work

Firstspells resultin welfare

program

recidivismin

Michigan

within oneyearand 51 percent leadtoreentry within

two

years. Table6

shows

thatparticipants

who

obtainjobsduring their

Work

First spells aresubstantially less likelyto recidivatewithin ayearortwo.

Those

takingdirect-hirejobs are 12and 11 percentagepoints less likely torecidivate overone and

two

years,respectively (33 and 22percentlessthan average).

Those

takingtemporaryhelpjobsare7 and5

percentage points (19and 10 percent)less likelyto recidivateoverone and

two

years.

These

OLS

models

areunlikelytorevealcausalrelationships.

When we

estimatetherecidivism models using

Work

First

random

assignmentsas instruments forjob

attainment,

we

find thatonlydirect-hirejobsreducethe probability ofrecidivism. Point estimatesfor

temporary helpjobs are positive, indicating a higher probabilityofrecidivism, but neitheris significant.

However,

we

canreadily reject the nullhypothesis thatthe effectsofdirect-hireand temporaryhelpjob

placements

on

two-year recidivismareequivalent. Thus,consistentwiththefindings pertainingto

employment

andearnings, only direct-hireplacements appeartohelpparticipantsreduce

program

recidivism,presumably because theymost likelyto leadtostableemployment."

4.

Bad

jobs

or

bad

contractors?

A

potentialobjectiontothe interpretationofour core resultsisthatthey

may

conflatethe effectof

contractor qualitywiththe effect ofjobtype.Imagine, forexample, that

low

quality

Work

First

contractors

-

thatis,contractors

who

generally providepoorservices

-

placeadisproportionateshareof

their

randomly

assignedparticipants intemporary helpjobs, perhaps becausethesejobsare easiest to

locate.Also

assume

forthe sakeof

argument

thattemporaryhelp jobshavethe

same

causal effecton

employment

andearningsasdirect-hirejobs.

Under

theseassumptions, our

2SLS

estimateswill

misattribute theeffectofreceiving abadcontractorassignmenttothe effectofobtaining atemporaryhelp

job.

Our

causal

model assumes

that contractorssystematicallyaffect participant

outcomes

onlythrough

job placements, notthrough other qualitydifferentials.

The above

scenario violatesthis assumptionsince

itimpliesthat

ECv.PJ)

< or £(i'„Pf)

>

(orboth).

We

view

the"bad contractor" scenarioasimprobable.

Based on

asurvey of

Work

Firstcontractors

servingthismetropolitan area(Autorand

Houseman

2005),

we

document

that

program

fundingistight

and

few

resources arespenton anythingbutjob development.

A

standardized

program

ofgeneral or life

skills trainingis providedinthefirst

week

ofthe

program

atall contractors.After the firstweek,all

contractors focus

on

job placement. Supportservices intendedto aidjobretention, such as childcareand

transportation,areequally availableto participants from allcontractorsandareprovidedoutside the

program. Italso bears

emphasis

that direct-hire and temporaryagency job placementrates arepositively

and significantlycorrelatedacross contractors, implyingthatcontractors withhigh job placementrates

tendtobe strong

on

both placement margins;this factreducesthe plausibilityofa scenarioin

which

"bad"

contractorsprimarily place participantsin

temp

agency jobs and

"good"

contractorsprimarily place

participants indirect-hirejobs. Nevertheless,

we

believe thebadcontractorconcern deservesclose

scrutinyandso provide

two

formal checks on itbelow.

a.

Exploiting

the

12

experiments

to

gauge

the

consistency

of

the

estimates

A

firsttest isto reestimate our

main models

separately foreach ofthe 12randomizationdistrictsin

our sample.Iftheaggregateresults aredrivenby outlying contractorsoraberrantrandomization districts,

"''

A

keyquestionthatourdatadonot yetallowustoansweriswhetherWorkFirstjobplacementsfosteredbyrandom assignmentsreducestatewelfarepayments.Infuturework,wewillobtain linked welfarepaymentdatafrom the stateof MichigantoanalyzethefiscalimpactsofWorkFirstjob placements.

these

models

will revealthis fact.

Appendix

Table2apresents

OLS

and

2SLS

models

bydistrictforthe

two-way

contrastbetween

employment

andnon-employment.

As

is consistentwiththepooled, district

estimatesin Table 3,eightof12

2SLS

pointestimates forthe effectof job placementson earningsare

positiveandfive arestatistically significant.

Of

thethree negative point estimates, none isstatistically

significant(though oneismarginally so). Similarly, 11 of12

2SLS

estimates forthe effects ofjob

placement

on

quarters of

employment

arepositiveandeightare statisticallysignificant.

In

Appendix

Table2b,

we

provideestimates forthecontrast

between

direct-hire

employment,

temporaryhelp

employment and

non-employment. Theseestimates use thesub-sample ofdistricts (7of

12)

where

participantswere

randomly

assigned

among

threecontractors during atleast

some

part ofthe

three-yearsample

window.

The

results,

summarized

inFigure 1,provideconsistentsupport forthe

main

inferences.In five of seven randomizationdistricts, thepointestimate forthe effectof temporary-help

placements onfour-quarterearningsissubstantially lesspositive (or

more

negative)thanfor direct-hire

placements (byat least$2,000), andthreeofthese fivecontrasts are significant." Similarly, the estimated

effectofdirect-hireplacements

on

four-quarter

employment

exceeds thatof temporary-help placements in

six of sevendistricts, andthreeofthese contrasts are statistically significant. Thesedisaggregated

estimates confirm thatour core findings reflect arobustandpervasive feature ofthe data.

b.

A

test

of

contractor heterogeneity

As

noted above,asurveyofcontractors failed touncoversystematic differences incontractor

practicesasidefromdifferences intheirjob placementrates. Here,

we

providea formal testofthe

existence ofother differences incontractor practices that affectparticipantoutcomes. Referring to

equation(3),thereduced form versionofour

main

estimating equation,thepresence ofsizablecontractor

heterogeneity inearnings or

employment outcomes

(large a^) indicates thatcontractors havesubstantial

"'_The

correlationbetweencontractor-by-yeartemporaryhelpanddirect-hireplacementratesis0.241 (p=.02).

A

regressionof

direct-hireplacementrateson temporaryhelpplacementrates,yeardummies,anda constant yields a coefficientonthe

temporaryhelpplacementratevariableof 0.389(p=.01).

'One_{countervailing contrast}

isalsosignificantat _p=.05.

impactson

Work

First participants that are independentoftheirplacement practices.

While

not

intrinsically a

problem

forour identification strategy, thisfinding

would

suggestthatourstatistical

model

focused

on

job placements, providesalimited empirical characterizationof

how

contractors affect

participantoutcomes.

Moreover,

ifthese other contractoreffects

were

correlatedwithplacement

practices, this

would

causeusto (atleast partly)misattributethe consequences ofother contractor

practicestojob placementpractices.

By

contrast, asmall(or insignificant)value of a^ indicates that

placementrates foratemporary help, direct-hire,orno jobcapture theentire effect thatcontractors have

on

participantoutcomes.

We

testthe

magnitude

of al byfirstestimatingequation(3)

by

OLS

and retainingtheresiduals.

We

next re-estimate Equation(3), replacing

Pa

and Piywithacompletesetofcontractor-by-year

dummies,

alsoretaining the residuals.

We

thentestforthesignificance of o",'

by

usingaconventional F-test to

evaluate whetherthe unrestrictedmodel, containingthe 59contractor-by-year

dummy

variables,has

significantly

more

explanatory

power

forparticipant

outcomes

than the restricted

model

in

which

these

dummies

areparameterized using only

two

measures.

Pa

and

Pa

.'

TheseF-testsyielda surprisingly strong result.For bothparticipant

outcomes

(four-quarterearnings

and four-quarter

employment),

we

acceptatthe 16 percent levelorbetterthenull hypothesisthat the59

contractor-by-year

dummy

variables have noadditionalexplanatory

power

forparticipant

outcomes

^T

^ D

beyond

simple

mean

contractor-by-yearjobplacementrates,

Pa

and

Pa

.

We

therefore canrejectthe

possibility thatthere isanysignificant, non-placement-relatedeffect ofcontractors

on

participant

outcomes. This findingdemonstratesthat

we

arenot misattributing the effects ofother contractor

"Thereare100contractor-by-yearcellsand 40district-by-year

dummy

variablesplus anintercept.Thisleaves59

contractor-by-yeardummiesasinstruments.TheF-testoftheserestrictionsisdistributedF(J-M,N-.I),where

N

isthetotalcountof

observations,Jisthenumberof parametersintheunrestrictedmodel,andJ-Misthenumberof parametersintherestricted

model.

"*_By

contrast,whenplacementratesareparameterizedusingasingleplacementmeasurethatdoesnot distinguishbetween

temporaryhelpanddirect-hirejobs(

£

, =

7^,+ A,)'''""^F-test rejects thenullatthe7 percentlevel forbothoutcomemeasures.