Integrering av innvandrere i arbeidslivet

Integrering av innvandrere i arbeidslivet

Bernt Bratsberg, Frischsenteret

Bygger på samarbeid med Oddbjørn Raaum og Knut Røed

Norsk Trygdemedisinsk Forening, 8. mars 2018

Innvandrere og arbeidsliv

•  Introduksjon

•  BoGdseffekter: Integrering eJer innvandringsgrunn

•  Tap av jobb og fortsaJ deltakelse

•  Betydning av trygdesatser

•  Introduksjonsprogrammet

Forskningsprosjekter om innvandrere på arbeidsmarkedet

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed (2016), “Flyktninger på det norske arbeidsmarkedet,” Søkelys på arbeidslivet 33(3): 185-207.

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed (2016), “Labor market integraGon of refugees in Norway,” in F. Fasani (ed), Refugees and Economic Migrants: Facts, policies and challenges, VoxEU.org Book, CEPR Press: 37-52.

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed (2017), “Immigrant Labor Market IntegraGon across Admission Classes,” Nordic Economic Policy Review 2017, 17-54. (Her med oppdaterte data)

•  Bernt Bratsberg, Oddbjørn Raaum, and Knut Røed (2017), “Immigrant Responses to Social Insurance Generosity,” Frisch Centre, December 2017

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed (2018), “Job Loss and

Immigrant Labor Market Performance,” Economica, 85: 124–151. doi:10.1111/

ecca.12244

•  Bernt Bratsberg, Oddbjørn Raaum, and Knut Røed (2018), “Economic IntegraGon of Refugees: Effects of the Norwegian IntroducGon Program,” Frisch Centre (in progress)

Migrasjon fremmer velferden!

•  Store økonomiske gevinster ved fri bevegelse av arbeidskrah (Clemens, 2011; Kennan, 2012;

Rodrik, 2016)

•  Men: Flyktninger, familieinnvandrere, og (i noen grad) arbeidsinnvandrere fra

lavinntektsland har lave sysselsejngsrater og

stort stønadsbehov.

Flyktninger i USA vs. Europa

•  I USA integreres flyktninger raskere inn i arbeidsmarkedet enn andre

innvandrergrupper (Borjas, 1982; Cortes, 2004; Chin and Cortes, 2015)

–  Høy humankapital (utdanning, språkkunnskaper), lang Gdshorisont.

•  Europeiske erfaringer mer blandet?

Flyktninger har lavere sysselsejng enn andre migranter i de fleste land

Kilde: Dumont et al. (2016)

Men de henter seg Glsynelatende raskt inn

Source: Dustmann et al. (2016)

Vanskelig å studere integrasjon over ;d

•  Hvordan påvirkes integrasjon av boGd?

•  Metodiske unordringer

–  TverrsniJsdata kan «lure oss»

–  Ulike innvandringskohorter har forskjellige

opprinnelsesland og ankommer ved ulike aldre –  Ulike innvandringskohorter utseJes for ulike

konjunktursituasjoner

–  Retur- og videremigrasjon er selekGv

BRR, NEPR 2017

Følger de samme innvandrerne over mange år, fordelt eJer innvandringsgrunn.

•  Alle innvandrere fra bosejngsår, 18-47 år ved ankomst, fra 1990

•  Innvandringsårsak/landbakgrunn:

–  Flukt (flyktninger og asylsøkere)

–  Gjenforening eller etablering av familie –  Arbeid eller utdanning fra lavinntektsland –  Nye EU

–  Gamle EU

•  Hovedinntektskilde: Arbeid eller trygd/stønad?

–  Sammenligner inntekter fra arbeid og overføringer

BruJo innvandring Gl Norge 1990-2016

0102030405060

Immigration (1000s)

1990 1995 2000 2005 2010 2015

New EU

Old EU/OECD Work (LDC) Education Family Refugee

Ikke alle blir…

020406080100020406080100

0 5 10 15 20 0 5 10 15 20 0 5 10 15 20

A. Refugee B. Family C. Education

D. Work (LDC) E. Old EU/OECD F. New EU

1990-94 1995-99 2000-04 2005-09 2010-15

In Norway (%)

Years since entry

Ikke alle blir…

•  FortsaJ i Norge eJer 10 år:

–  Flyktninger 85%

–  Familiemigranter 85%

–  Nye EU 70%

–  Arbeid (lavinntektsland) 45%

–  Gamle EU 40%

–  Utdanning (lavinntektsland) 30%

Innvandrerandeler

Note: PopulaGon consists of those aged 25-65 and in Norway at end of each calendar year.

0510152005101520

1990 1995 2000 2005 2010 2015 1990 1995 2000 2005 2010 2015 Population

Employment Social Insurance

New EU

Old EU/OECD Work (LDC) Education Family Refugee

Percent

Innvandrerandeler

Note: PopulaGon consists of those aged 25-65 and in Norway at end of each calendar year.

Integrasjonsprosessen

•  For flyktninger forventer vi lave sysselsejngsrater de første årene

•  Over Gd forventer vi økende arbeidsmarkedsdeltakelse

–  Språk

–  Utdanning –  Erfaring –  NeJverk

•  Men yrkeserfaring gir også rejgheter Gl inntektssikring

•  Tidligere forskning har vist at innvandrere er sårbare for konjunktursvingninger og rammes hardere av jobbtap

•  Ikke opplagt at integrasjonsprosessen vedvarer i det lange

løp

VikGgste inntektskilde: Data

Flukt Familie +l

immigrant Familie +l

norskfødt Nye EU Gamle EU Norskfødt

(1) (2) (3) (4) (5) (6)

A. Menn

Jobb 0,581 0,768 0,799 0,883 0,890 0,871

Overføringer 0,379 0,164 0,149 0,050 0,046 0,120

Observasjoner 366.136 109.390 75.442 322.823 402.884 2.093.261 B. Kvinner

Jobb 0,463 0,508 0,733 0,803 0,846 0,803

Overføringer 0,416 0,213 0,102 0,064 0,050 0,168

Observasjoner 231.710 301.878 214.786 191.564 291.723 1.963.026

Note: Samples are restricted to those 25-62 years of age, not in educaGon, and in the country at the end of the observaGon year. Immigrant samples are further restricted to those 18-47 years of age at entry and who entered between 1990 and 2013.

ObservaGon period is 1993-2014. NaGve samples are 10 percent random populaGon extracts.

SysselseDng: Andel av innvandrere som har arbeid som vikGgste inntektskilde. EJer boGd.

PopulaGon consists of those aged 25-62 and in Norway at end of each calendar year.

020406080100

0 5 10 15 20 0 5 10 15 20

A. Men B. Women

Refugee Fam imm Fam Nor New EU Old EU

Employment (%)

Years since entry

Stønad: Andel av innvandrere som har trygd/stønad som vikGgste inntektskilde. EJer boGd.

PopulaGon consists of those aged 25-66 and in Norway at end of each calendar year.

0204060

0 5 10 15 20 0 5 10 15 20

A. Men B. Women

Refugee Fam imm Fam Nor New EU Old EU

Social insurance (%)

Years since entry

StaGsGsk analyse:

Isolering av årsakssammenhenger

Vi ønsker å idenGfisere effekter av bo;d, kontrollert for

•  alder,

•  ankomstår,

•  opprinnelsesland,

•  konjunkturer

•  Individuelle kjennetegn - utdanning.

Regresjonsanalyse: Predikert sysselsejngsdifferanse mellom innvandrere og norskfødte

Note: DifferenGals are based on a regression model that controls for educaGonal aJainment, whether schooling is acquired in Norway, whether the highest aJainment is from Norway, whether educaGon informaGon is missing, local unemployment, and age at entry—all interacted with the five admission categories. The regression further controls for age, county of residence, year of observaGon, and country of birth, as well as educaGonal aJainment and local unemployment interacted with naGve status.

DifferenGals are evaluated at the weighted average educaGonal aJainment in each immigrant sample.

-.6-.5-.4-.3-.2-.10

0 5 10 15 20 0 5 10 15 20

A. Men B. Women

Refugee Fam imm Fam Nor New EU Old EU 95% CI

Employment difference vs. natives

Years since entry

Regresjonsanalyse: Predikert differanse i stønadsavhengighet mellom innvandrere og norskfødte

-.10.1.2.3.4.5

0 5 10 15 20 0 5 10 15 20

A. Men B. Women

Refugee Fam imm Fam Nor New EU Old EU 95% CI

Social insurance difference vs. natives

Years since entry

Faktorer som skiher

sysselsejngsprofilene opp eller ned

•  Utdanning fra opprinnelsesland

•  Utdanning fra Norge

•  Konjunktursituasjonen

•  Alder ved ankomst

•  Opprinnelsesland

(1) Utdanning fra hjemlandet:

Note: Men

-.1-.05 0.05.1

Predicted employment differential (ref= secondary)

Refugee FamImm FamNor NewEU OldEU Native

Compulsory Tertiary 95% CI

(2) Utdanning fra Norge:

-.05 0.05.1.15.2.25

Predicted empl diff (ref= foreign schooling)

Refugee FamImm FamNor

Compulsory Secondary Tertiary 95% CI

Note: Men

(3) Utdanning fra Norge som er lavere enn høyeste fullførte:

-.05 0.05.1

Pred empl diff (ref= foreign educ above Norwegian)

Refugee FamImm FamNor

Men Women 95% CI

(4) Lokal arbeidsledighet:

-6-4-20

Predicted effect on employment

Refugee FamImm FamNor NewEU OldEU Native

Men Women 95% CI

(5) Alder ved ankomst (menn):

-.15-.1-.05 0.05

Pred empl diff (ref= age 25-29)

Refugee FamImm FamNor NewEU OldEU

Age 18-24 Age 30-34 Age 35-39 Age 40-47 95% CI

Opprinnelsesland av stor betydning.

Fordeling av flyktninger eJer opprinnelsesland:

Note

Men Women

Afghanistan Bosnia Eritrea Iran

Iraq Kosovo Other Somalia

«Effekter» av opprinnelsesland:

Note -.2-.10.1.2

Pred empl diff (ref= refugee average)

Afghanistan Bosnia Eritrea Iran Iraq Kosovo Somalia

Men Women 95% CI

Integrering eJer innvandringsgrunn

–  For mange innvandrere ser integrasjonsprosessen ut Gl å miste trykket eJer 5-10 år, og dereJer gå i revers.

–  DeJe tyder på at vi ikke greier å utnyJe det

potensialet som fakGsk er der.

Hvorfor?

1. Konjunkturer

•  Innvandrere mer sensiGve for konjunktursvingninger

•  Mer Glbøyelig Gl å jobbe i bedriher som nedbemanner eller stenger

•  Mer Glbøyelig Gl å bli plukket ut for oppsigelse ved nedbemanning

–  Sist inn – først ut

–  Mer “marginale” jobber

•  Større negaGv effekt av jobbtap

–  Mindre fleksibel kompetanse

2. Kompetanse

•  Utdanning fra hjemlandet av begrenset verdi i Norge

•  Kan bety dårlige jobbmuligheter relaGvt Gl reell kompetanse og ambisjoner

Hvorfor?

3. Inntektssikring

•  Høye kompensasjonsgrader i inntektssikringsordninger

–  Progressivitet og forsørgerGllegg –  Dårlige jobbmuligheter

•  Liten nyJeforskjell på jobb og ikke-jobb

4. IntegreringspoliGkk

•  Fokus på «første jobb» gir også billeJ Gl inntekssikring, men uten nødvendigvis å danne grunnlag for en

levedykGg yrkeskarriere

To forskningsprosjekter om

innvandrere på arbeidsmarkedet

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed, “Job Loss and Immigrant Labor Market Performance,” Economica, 2018

•  Bernt Bratsberg, Oddbjørn Raaum, and Knut Røed,

“Immigrant Responses to Social Insurance Generosity,” Frisch

Centre, November 2017

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed, “Job Loss and Immigrant Labor Market Performance,” Economica,

forthcoming

•  Bernt Bratsberg, Oddbjørn Raaum, and Knut Røed,

“Immigrant Responses to Social Insurance Generosity,” Frisch Centre, November 2017

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed (2017),

“Immigrant Labor Market IntegraGon across Admission Classes,” Nordic Economic Policy Review 2017, 17-54.

–  Her med oppdaterte data

OmsGllinger og jobbtap

BenyJer oss av

•  Bedrihsnedleggelser/konkurser

•  Store nedbemanninger

Eksponering vs. effekt av eksponering

Data

•  Skiller mellom konkurs og minst 60%

nedbemanning

•  Konkurser/nedbemanninger årene 1994-2010

–  Fra VOF (BOF) samt Arbeidstakerregisteret

•  AnsaJe alder 25-55 år

•  Innvandrere

–  «Ikke-vestlige» (LDC), «vestlige» (EEA)

•  Norskfødte i samme aldersspenn

Eksponering for konkurs/nedbemanning de nærmeste tre årene (prosent)

LDC imm EEA imm NaGve

Firm bankrupt yrs 1-3 (%) 2.8 2.6 1.8

Firm downsizes yrs 1-3 (%) 11.0 9.0 8.1

Observa+ons 168 872 201 543 7 923 400

Økt eksponering for konkurs eller nedbemanninger.

(Prosentpoeng/100)

Data for effektanalyse

•   Grunnet mulig seleksjon ser vi på arbeidsstokken

–  2 år før konkursen (nedbemanning) er registrert som basisår (år null)

–  Bedriher med minst 10 ansaJe

–  SysselsaJ 2 år før «år null», minst eJ års ansiennitet, ikke moJaJ dagpenger ved arbeidsløshet eller

uføretrygd

–  Solid foNeste i arbeidsmarkedet

•  Konkurs i VOF, eller reduksjon i arbeidsstokken

med minst 60% fra 31.12 Gl samme dato neste år

Ledighetsinsidens rundt konkurs/nedbemanning

0204060

-3 0 3 6 -3 0 3 6 -3 0 3 6

LDC immigrant EEA immigrant Native

Bankrupt Downsize Stable

Reg unemployed during year (%)

Years since base year

Sysselsejng, før og eJer

708090100

-3 0 3 6 -3 0 3 6 -3 0 3 6

LDC immigrant EEA immigrant Native

Bankrupt Downsize Stable

Employed (%)

Years since base year

Realinntektsutvikling (relaGv)

8090100110120

-3 0 3 6 -3 0 3 6 -3 0 3 6

LDC immigrant EEA immigrant Native

Bankrupt Downsize Stable

Real earnings relative to base year

Years since base year

Sysselsejngseffekter konkurs

Men Women

First

post year

5 year

period 9 year period

First post year

5 year

period 9 year period

(1) (2) (3) (4) (5) (6)

Bankrupt -0.050 -0.166 -0.291 -0.089 -0.308 -0.346 (0.004) (0.015) (0.042) (0.009) (0.032) (0.084) LDC* -0.083 -0.204 -0.290 -0.042 -0.138 -0.289 bankrupt (0.010) (0.032) (0.094) (0.021) (0.080) (0.229)

Obs 571

537 471

883 311 862 258

720 214 944 145 097

Oppsummering effekter

•  Konkurs => langsikGg fall i sysselsejng og arbeidsinntekt

•  Konsekvensene langt mer alvorlig for LDC innvandrere

•  Store nedbemanninger rammer også

sysselsejng på langt sikt, svakere enn for

konkurser eJersom ikke alle mister jobben

Seleksjonsskjevhet?

•  Jobber innvandrere og nordmenn på

forskjellige arbeidsplasser? Sortering eJer arbeidsplass?

–  Hva om vi følger medarbeidere fra samme

virksomhet?

Robustness analyses, firm fixed effects

effects As Table 3, firm

fe sample With firm fixed

effects As Table 3, firm fe sample

(1) (2) (3) (4)

Bankrupt -0.042*** -0.185***

(0.005) (0.018)

LDC*bankrupt -0.046** -0.048*** -0.135* -0.114**

(0.023) (0.015) (0.073) (0.053)

EEA*bankrupt 0.024 0.010 0.001 0.037

(0.020) (0.011) (0.057) (0.038)

Downsize -0.007*** -0.038***

(0.002) (0.007)

LDC*downsize -0.029*** -0.038*** -0.071** -0.087***

(0.010) (0.007) (0.033) (0.026)

EEA*downsize -0.009 -0.008* -0.011 0.009

(0.006) (0.005) (0.020) (0.016)

Observa+ons 850 151 850 151 844 859 844 859

Fixed effects 36 403 36 165

Jobbtap

VikGg forklaring på forskjeller mellom grupper i

sysselsejngsutvikling og inntekstvekst?

Sysselsejng og inntektsvekst over Gd

8090100110120

0 2 4 6 8 10 0 2 4 6 8 10

Employment Real earnings

LDC immigrant EEA immigrant Native

Index relative to base year

Years since base year

Jobbtap

VikGg forklaring på forskjeller mellom grupper i sysselsejngsutvikling og inntekstvekst?

•  A. Eksponering

- En andel av de som mister jobben blir ikke ledige

-  De som opplevde konkurs vet vi mistet jobben, ca halvparten ble arbeidsledige => for hver vi observerer fra jobb Gl ledighet vet vi at to mistet jobben.

⇒   Eksponering = innstrømming * 2

⇒   NaGves: 10,5%; LDC immigrants: 24% over 2 år

•   B. Effekt

Kausal effekt av å miste jobben = effekt av konkurs, justert for andel ble arbeidstakere uten konkurs som mistet jobben («contaminaGon bias»)

•  A. og B. =>

Jobbtap forklarer 50% av forskjell i sysselsejng

(8,4pp) og 60% av forskjell i inntektsvekst (15 log pnts) mellom LDC innvandrere og etnisk norske over 3-

årsperiode, likt fordelt på eksponering og effekter

To forskningsprosjekter om

innvandrere på arbeidsmarkedet

•  Bratsberg, Bernt, Oddbjørn Raaum, and Knut Røed, “Job Loss and Immigrant Labor Market Performance,” Economica

•  Bernt Bratsberg, Oddbjørn Raaum, and Knut Røed,

“Immigrant Responses to Social Insurance Generosity,” Frisch

Centre, November 2017 (in progress)

Research ques+ons

Labor market success of immigrants from low income countries; What is the role of generous social insurance replacement rates?

A.  Do program parGcipants postpone transiGon to jobs when program benefits become more generous ?

B.  Are immigrants more responsive to change in benefits than naGves?

C.  Do higher benefits affect future earnings (from work) and incomes? Different for immigrants?

D.  InterpreGng differenGal effects: Immigrant background or other characterisGcs with differenGal benefit effects (e.g., earnings potenGal)?

Iden+fica+on of effects

Challenge: Benefit formula contains a rich number of characterisGcs =>

benefits typically correlate with unobserved factors that affect post-program outcomes => in need of rules generaGng (exogenous) random variaGon in benefits

•  Large temporary disability program (TDI) in Norway. Individual

administraGve records combined with tax and demographic registers (full populaGon)

•  Benefit generosity effect: Labor market and income responses to higher program benefits

SoluGon: Benefit reform in 2002, new principles, possible to calculate benefits under old and new rules => random-assignment like variaGon across eligible applicants

•  Related studies: Nielsen et al (2010), Fevang et al (2016), Mullen and Stabile (2016), Borghans et al (2014)

Empirical research quesGon

•  Do immigrants and other persons with poor earnings/job prospects respond more strongly to changes in social insurance

(dis)incenGves?

•  IdenGficaGon by means of a reform in the temporary disability insurance (TDI) program in Norway in January 2002

•  A new principle for calculaGon of benefits

–  From a “pension model” to an “earnings replacement model”

–  Only earnings the last three years maJer

–  Higher minimum levels and benefits for immigrants with few years of residence in Norway

–  Lower child allowances

•  Average absolute change (up or down) in benefit levels: 23 %

Data

•  TDI program parGcipants, program entry 1999-2004

–  (3 yrs each side of reform)

•  Age 27 to 59 at program entry

•  Follow parGcipants through 2014

DescripGve staGsGcs, TDI program parGcipants

Men Women

Immigrants NaGves Immigrants NaGves

(1) (2) (3) (4)

Age 40.0 40.4 39.9 40.4

Educa+onal aaainment (%)

Compulsory 40.5 42.0 46.7 40.5

Unknown 8.2 0.8 8.3 0.4

Employed year before (%) 74.2 86.2 72.0 83.4

Avg. earnings 3 prior years 264 695 380 300 204 891 267 696

TDI benefits (NOK):

Pre-reform rules 158 881 227 417 125 113 172 352

Post-reform rules 210 578 250 443 179 469 199 768

Implied replacement (pre-tax):

Pre-reform rules 0.620 0.593 0.606 0.642

Post-reform rules 0.798 0.654 0.878 0.744

Spell dura+on (months) 24.8 25.0 27.7 29.3

Spell outcome:

Employment 32.9 49.9 26.8 42.7

Number of spells 7 128 64 346 5 267 67 909

Frac+on post reform 59.0 54.4 63.2 54.8

DistribuGon of benefit change due to the reform

The distribu+on of hypothe+cal change in benefits from the 2002 TDI reform, by gender and immigrant status. Poten+al claimants with long term sick leave

0.005.01.015 0.005.01.015

-100 -50 0 50 100 150 200 -100 -50 0 50 100 150 200

A. Immigrant men B. Immigrant women

C. Native men D. Native women

Potential entrants pre-reform Potential entrants post-reform

Density

Reform benefit gain (1000 NOK)

EsGmated hazard rate elasGciGes wrt TDI benefits

Men Women

Immigrants NaGves Immigrants NaGves

(1) (2) (3) (4)

Log actual TDI benefit Effect on transi+on to:

Employment -0.647***

(0.143) -0.311***

(0.068) -0.424***

(0.127) -0.084

(0.052)

PDI -0.086

(0.180) -0.136

(0.102) 0.028

(0.160) -0.111

(0.086)

Unemployment -0.538

(0.398) -0.103

(0.250) -0.466

(0.675) 0.156

(0.383)

Non-par+cipa+on -0.069

(0.127) -0.137

(0.091) 0.128

(0.111) -0.171**

(0.084)

Number of spells 7 128 63 346 5 267 67 909

Number of support points in

heterogeneity distribu+on 5 6 1 6

EsGmated effects on annual labor earnings of a Euro increase in the TDI benefit

-.6-.4-.20.2-.6-.4-.20.2

0 2 4 6 8 10 0 2 4 6 8 10

A. Immigrant men B. Native men

C. Immigrant women D. Native women

Effect estimate, earnings

Years since program entry

EsGmated effects on aher-tax income of a Euro increase in the TDI benefit

-.20.2.4-.20.2.4

0 2 4 6 8 10 0 2 4 6 8 10

A. Immigrant men B. Native men

C. Immigrant women D. Native women

Effect estimate, after-tax income

Years since program entry

Cross effects on spousal labor supply?

EsGmated effects on spouse earnings of a Euro increase in TDI benefits

-1-.50.5-1-.50.5

0 2 4 6 8 10 0 2 4 6 8 10

A. Immigrant men B. Native men

C. Immigrant women D. Native women

Effect on spouse's earnings

Years since program entry

EsGmated effects on household aher-tax income of a Euro increase in TDI benefits

-.50.5-.50.5

0 2 4 6 8 10 0 2 4 6 8 10

A. Immigrant men B. Native men

C. Immigrant women D. Native women

Effect on after-tax family income

Years since program entry

Immigrants or characterisGcs of immigrants?

Immigrants and naGves differ wrt potenGal earnings and household characterisGcs

Men Women

Immigrants NaGves Immigrants NaGves

(1) (2) (3) (4)

A. Valua+on of employment: Average of 3 best earnings years, 12-3 yrs before (%)

Low (p1-p25 of immigrant distribu+on) 25.0 3.7 25.0 5.1

Medium (p26-p75 of immigrant

distribu+on) 50.0 39.4 50.0 45.5

High (p76-p100 of immigrant distribu+on) 25.0 56.9 25.0 49.4

B. Valua+on of non-employment: Family status (%)

Low (single) 33.1 65.4 30.1 53.3

Medium (employed spouse) 30.2 26.0 47.4 41.4

High (spouse homemaker) 36.7 8.6 22.4 5.3

EsGmated impact of increase in TDI benefits on average earnings over five- year period aher TDI entry, with and without interacGons with the value of

employment and non-employment

Men Women

NaGves Immigrant

interacGon NaGves Immigrant interacGon

(1) (2) (3) (4)

A. Without interac+ons between benefits and value of employment and non- employment

-0.097***

(0.030) -0.219***

(0.080) -0.056**

(0.024) -0.164**

(0.081) B. With interac+ons between benefits and

value of employment and non- employment

Baseline (low value of employment/high

value of non-employment) -0.404***

(0.132) -0.144*

(0.086) -0.317***

(0.112) -0.103 (0.083) + medium value of employment 0.187*

(0.107) 0.004

(0.085) + high value of employment 0.310***

(0.110) 0.165*

(0.085) + medium value of non-employment 0.057

(0.088) 0.202**

(0.084) + low value of non-employment 0.065

(0.086) 0.142*

(0.086)

Contribu+ons and results

A.  Higher benefits postpone the transiGon from TDI to employment and reduce future labor earnings

B.  Immigrant responses are significantly stronger than those of naGves C.  The stronger response among immigrants is partly due to their larger

share with low earnings potenGal (for whom responses are larger even for naGves)

D.  Total aher-tax income increases among naGves in response to higher benefits, but much less so for immigrants

E.  Find cross effects on spouses’ labor supply, parGcularly from immigrant women to immigrant men

Innvandreres integrering på arbeidsmarkedet

•  Tiltak som virker?

–  Utdanning –  Tidlig arbeid –  Underholdkrav

–  Vilkår for sosialhjelp

–  Introduksjonsprogrammet

•  Kausale effekter?

IntroducGon program

The major program for refugee integraGon since 2004

•  “Refugees and their families who have been granted a residence permit in Norway have the right to/are obliged to complete an introductory program. All municipaliGes that seJle refugees are obliged to offer the program”

•  “The purpose is to increase the possibility of newly arrived

immigrants parGcipaGng in working and social life and to increase their financial independence”

•  Two (three) years, individual sGpend/grant of 2G (NOK 187 268) per year

Source: IMDI web page

IntroducGon program

Who

• Age 18-55

• Recent refugees and family

• With needs for basic qualificaGons

• 2017: 27 000 parGcipants

What

• FullGme training

• 2 – 3 yrs

• Individualized plans

• ‘QualificaGons’ – not educaGon

• Mandatory program – sGpend Ged to acGve parGcipaGon

• Test requirements since 2013

• Pass requirements since 2017

How

• Transfers from central admin to

municipaliGes

• 2016 budget: NOK 11.5 bill

• Municipality autonomy in organisaGon

• Legislated

requirement, but few guidelines

Adapted from Djuve and Kavli (2017) and IMDi (2017)

Evaluate effects of introducGon program?

Difference-in-differences design:

•  Treatment grp: Refugees and their family

•  Control group: Family to non-refugee immigrants

–  Immigrants from the same source countries

•  Pre-reform cohorts: 1999-2001

•  Post-reform cohorts: 2003-2005

–  Follow for 14 and 10 yrs aher admission

Program take-up rates

Treatment grp: Iraq (28%), Somalia (16%), Afghanistan (8%), Kosovo (7%), Iran (6%) Control group: Pakistan (11%), Vietnam (10%), Sri Lanka (8%), Turkey (7%), Iran (5%) ..

Iraq (4%), Kosovo (4%) .. Somalia (2%) .. Afghanistan (1%)

020406080 1999 2000 2001 2002 2003 2004 2005 1999 2000 2001 2002 2003 2004 2005 1999 2000 2001 2002 2003 2004 2005 1999 2000 2001 2002 2003 2004 2005

A. Treatment men B. Treatment women C. Control men D. Control women

Program take-up rate

Employment

Higher minimum levels

N= 266 519

050100050100

0 5 10 15 0 5 10 15

A. Treatment grp men B. Treatment grp women

C. Control grp men D. Control grp women

Pre-reform Post-reform

Employment (%)

Years since entry

Social insurance

020406080020406080

0 5 10 15 0 5 10 15

A. Treatment grp men B. Treatment grp women

C. Control grp men D. Control grp women

Pre-reform Post-reform

Social insurance (%)

Years since entry

Program effects on employment

Higher minimum levels

Note: Regressions control for age (indicators 25-57), local unemployment rate, county of recidence, and year (2000-2015)

-.4-.20.2

0 2 4 6 8 10 0 2 4 6 8 10

A. Men B. Women

Estimate 95% CI

Reform effect on employment

Years since entry

Program effects on social insurance

Higher minimum levels

Note: Regressions control for age (indicators 25-57), local unemployment rate, county of recidence, and year (2000-2015)

-.20.2.4

0 2 4 6 8 10 0 2 4 6 8 10

A. Men B. Women

Estimate 95% CI

Reform effect on social insurance

Years since entry

Robustness

•   ComposiGon: country of origin

•   Age, period and local labor market effects from low- educated naGves

•  Wage subsidies during iniGal years in pre-reform period

•   Earnings

Program effects on employment II

Higher minimum levels

Note: Regressions control for age (indicators 25-57), local unemployment rate, county of recidence, and year (2000-2015)

-.4-.20.2-.4-.20.2

0 2 4 6 8 10 0 2 4 6 8 10 0 2 4 6 8 10

A. Men DiD B. Men within-country C. Men low-educ native ref

D. Women DiD E. Women within-country F. Women low-educ native ref

Estimate 95% CI

Reform effect on employment

Years since entry

Program effects on social insurance II

Higher minimum levels

-.20.2.4-.20.2.4

0 2 4 6 8 10 0 2 4 6 8 10 0 2 4 6 8 10

A. Men DiD B. Men within-country C. Men low-educ native ref

D. Women DiD E. Women within-country F. Women low-educ native ref

Estimate 95% CI

Reform effect on social insurance

Years since entry

Wage subsidies

Higher minimum levels

N= 266 519

051015051015

0 5 10 15 0 5 10 15

A. Treatment grp men B. Treatment grp women

C. Control grp men D. Control grp women

Pre-reform Post-reform

Wage subsidy (%)

Years since entry

Program effects on employment aher nejng out wage subsidies

Higher minimum levels

N= 266 519

-.3-.2-.10.1

0 2 4 6 8 10 0 2 4 6 8 10

A. Men B. Women

Estimate 95% CI

Reform effect on employment

Years since entry

Effects of the introducGon program

•  Large, negaGve effect on employment yrs 1-3

–  Program lock-in

•  PosiGve effects on employment, male refugees yrs 4-5

•  Small effect on social insurance receipt of female refugees 9-10 yrs aher entry(?)

•  Otherwise, no long-term effects on employment or social insurance up-take

But, does program lead to

•  Human capital, beJer jobs, higher pay?

•  Improved overall economic posiGon of refugees?

Examine earnings

Log earnings

Higher minimum levels

N= 149 575

10.51111.51212.510.51111.51212.5

0 5 10 15 0 5 10 15

A. Treatment grp men B. Treatment grp women

C. Control grp men D. Control grp women

Pre-reform Post-reform

log earnings

Years since entry

Program effects on log earnings

Higher minimum levels

Note: Regressions control for age (indicators 25-57), educaGonal aJainment at admission, local unemployment rate, county of recidence (current and at admission; 38 indicators), year (2000-2015) and country of birth (136 indicators)

-1-.50.5

0 2 4 6 8 10 0 2 4 6 8 10

A. Men B. Women

Estimate 95% CI

Reform effect on log earnings

Years since entry

Immigrant labor market integraGon:

Lessons from Norway

The labor market integraGon process loses steam and goes into reverse aher just a few years, with rising welfare dependency rates with years in Norway

IntroducGon program:

•  Large lock-in effects

•  PosiGve short-term effects for refugee men

•  Small, posiGve long-term term effects on economic status of refugee women?

•  Otherwise, no discernable long-term effects on economic self- sufficiency

Konsekvenser for poliGkken

1.   En integreringspoliGkk med sterkere fokus på langsikGge karrieremuligheter

2.   Mer utdanning i Norge og/eller bedre utnyJelse av utdanning fra utlandet

3.   En mer akGvitetsorientert inntektssikring

- StøJe Gl å forbli i arbeid bedre enn støJe Gl å holde seg utenfor

- Mer bruk av gradert inntektssikringsordninger