Inclusion of Immigrants into Welfare: The Myths and the Veracity in the EU

Martin KahanecCentral European University

Institute for the Study of Labor (IZA)

Central European Labour Studies Institute (CELSI)

Credits to: Alan Barrett, Corrado Giulietti,

Martin Guzi, Bertrand Maitre, Klaus Zimmermann, et al.

June 2012, Bratislava

What are we interested in, and why?

• Immigrant welfare receipt is a controversial issue

– Immigrants more likely to have worse socio-economic outcomes (…)

– Concerns that immigrants disproportionally participate in (abuse) welfare (Cohen, Razin and Sadka, 2009 and Nannestad, 2006)

– Concerns that immigrants constitute a fiscal burden for host countries (De Giorgi and Pellizzari, 2009)

Immigrants across the EU

Highest shares CY, IE, BE, AT, SE, UK; lowest RO, BG, PL, SK, HU, CZ.

0

5

10

15

20

25

RO

BG PL

SK

HU

CZ FI

LT

PT

DK

ES SI

NL

GR IT

EE

LV

FR

UK

SE

AT

BE IE CY

Other

EUN

EU12

EU15+EFTA

Source: Kahanec, 2012. EU LFS 2010

Poverty among immigrants

Figure 4.9: Estimated marginal impact of migrant status on support receipt: At risk of poverty

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

LU BE CY FI GR SE FR AT UK NO CZ ES IT IE DK NL PT DE* IS PL

Non-EU EU

Source: EU-SILC (2008). Notes: *All migrants for Germany.

Unskilled immigrants?

Non-EU immigrants well-educated, especially in NMSs. Less skilled than natives are EUNs in the EU15, other immigrants in eg ES and FI.

c) Percent high-educated EUN immigrants and natives

d) Percent high-educated other immigrants and natives

DEIT

SK

PT

NL

UKLV

PL LT

SIFR

CY

BE

DK

HU

CZ

EE

AT

FI

IE

GR

ES

RO

SE

0

10

20

30

40

50

60

0 10 20 30 40 50 60

Percent high skilled, natives

Per

cen

t h

igh

ski

lled

, EU

N

DE

IT

SK

PT

NL

UK

LV

PL

LTSI

FR

CY

BE

DKHU

BG

CZ

EE

AT

FI

IE

GRES

RO

SE

0

10

20

30

40

50

60

0 10 20 30 40 50 60

Percent high skilled, natives

Per

cen

t h

igh

ski

lled

, oth

er o

rig

in

Tertiary education. Source: Kahanec, 2012. EU LFS 2010

Brain waste?

Non-EU immigrants more often work in less-skilled occupations (especially ES, IT, AT, DE< SE, NL), except for some NMSs.

c) Percent high-skilled EUN immigrants and natives

d) Percent high-skilled other immigrants and natives

SE

RO

ES

GR

IE

FI

AT

EECZ

BGHU

DK

BE

CYFR

SI

LT

PLLV

UKNL

PT

SK

ITDE

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

10 15 20 25 30 35 40

High-skilled share, natives

Hig

h-s

kile

d s

har

e, E

UN

SE

RO

ES

GR

IE

FI

AT

EE

CZ

BG

HU

DKBE

CY

FR

SI

LTPL

LV

UKNL

PT

SK

IT

DE

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

10 15 20 25 30 35 40

High-skilled share, natives

Hig

h-s

kile

d s

har

e, o

ther

ori

gin

ISCO 1-3. Source: Kahanec, 2012. EU LFS 2010

Ratio of proportions of immigrants and natives: Unemployment support

0

1

2

3

4

5

NO FI IS PL AT UK IT GR LU FR DK SE DE* BE PT NL ES CY IE CZ

Non-EU EU

Estimated marginal impact of immigrant status on support receipt: unemployment, sickness and disability

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

FI DK AT FR NO LU DE* IT GR NL BE IS UK SE PT ES PL IE CY CZ

Non-EU EU

Ratio of proportions of immigrants and natives: Unemployment support for those who are unemployed

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

LU DK GR UK IT CZ IS DE* PL AT FI FR PT ES BE NO CY SE IE NL

Non-EU EU

So…

• Immigrants more likely to be poor

• Not necessarily less educated than natives

• But downskilling

• Take up welfare more frequently

• But have inadequate access to welfare

• Do they shop for welfare?

What do we do? • We take unemployment benefits spending (UBS) in GDP

a measure of welfare (for now)– Aggregate measure, “generosity index”

• We explicitly account for the possible endogeneity of welfare spending

• We concentrate on Europe as a cluster of welfare-heterogeneous countries among which migration is relatively easy

• We have panel data with a good number of observations

Data

• Gross inflows of foreigners/population, 16-64: OECD-SOPEMI• UBS and other welfare measures/GDP: OECD Social Expenditure

Database (SOCX)• Contextual variables: (unemployment rate, per-capita GDP, etc):

World Development Indicators (WDI) online database. • Unbalanced panel with 248 observations, 19 EU countries 1993-

2008

Econometric model

where:

mit - immigrant inflows as percentage in total population in country i at time t

Xit-1 - UBS as a percentage of GDP

Zit-1 is the matrix that includes the immigration rate (networks), per-capita GDP, unemployment rate.

All explanatory variables are lagged, as we assume lagged response of potential immigrants. This may also alleviate the endogeneity problem but only partially if at all (see below).

Fixed country and year dummies, so variation only within countries and beyond systemic shocks. Population weights.

'1 1it it it i t itm x z γ

Results (OLS, non-EU)

(a) (b) (c) (d) Non-EU immigrants

UBS 0.058 * 0.061 * 0.066 *** (0.028) (0.031) (0.021) Stock of non-EU immigrants 0.141 *** 0.129 *** 0.123 *** 0.079 * (0.028) (0.026) (0.028) (0.039) Per-capita GDP 0.017 *** 0.019 *** 0.018 *** 0.007 (0.007) (0.007) (0.007) (0.004) Unemployment rate -0.007 -0.015 -0.005 -0.026 (0.018) (0.017) (0.016) (0.015) Constant -0.056 *** -0.063 *** -0.053 *** -0.02 (0.023) (0.024) (0.021) (0.014)

2R 0.64 0.65 0.68 0.52

a - wihout UBS; b - with UBS; c - with other welfare components (health, family, pension); d – no weights

Endogeneity of UBS

• OLS results point at a welfare magnet for non-EU immigrants• But we have an endogeneity problem: UBS may be a function of

immigrationA) Immigrants themselves directly increase UBS take up or decrease

average GDP

B) Policy reaction to immigration may cut/expand UBS

So we need to take care of reverse causality – 2SLS

• We need an instrument that is correlated with UBS, but not with immigration

• We propose “the number of parties in the ruling coalition”

• Argument: with a relatively large number of parties in coalition, it is difficult to impose austerity on spending. Or, there are more parties with interest to spend (and win voters)

• Simultaneously, this instrument is unlikely to be directly correlated with immigration.

• Is this instrument relevant?

First stage: UBS on # of coalition parties

0.0

2.0

4.0

6

0 2 4 6 8

EU immigrants Non-EU immigrants

IV GMM IV GMM

UBS 0.040 -0.013 -0.003 -0.004 (0.065) (0.029) (0.007) (0.022) Stock of immigrants 0.133 *** 0.115 *** 0.075 *** 0.073 *** (0.018) (0.011) (0.009) (0.014) Per-capita GDP 0.019 *** 0.015 *** 0.000 0.000 (0.003) (0.002) (0.001) (0.001) Unemployment rate -0.012 -0.013 *** 0.000 0.002 (0.011) (0.006) (0.001) (0.003) Constant -0.068 *** -0.054 *** 0.001 0.002 (0.012) (0.007) (0.002) (0.005) N 248 248 248 248

Notes: robust standard errors in parentheses. */**/*** indicate significance at the 10/5/1% level. All models are estimated by fixed effects and contain year dummies. All regressions are weighted by the counts of individuals in each country in the year 2000. Instrument is the number of parties in the winning parliamentary coalition. IV estimates are computed using the Stata command xtivreg2 developed by M.E. Schaffer. GMM estimates are obtained using the Stata command xtabond2 developed by D. Roodman.

Results

Interpretations

• Immigrants are more likely to be poor• They are not necessarily less educated, but their skills are not

transferable (LM problem)• They are more likely to be in welfare take up, but not because

there is something special about migrants.• And also not because they would abuse welfare• Rather, they seem to be at higher risk due to their characteristics

and they face barriers to access to welfare (welfare problem)• Integration and selection of immigrants!• What should we do?

What Do Ethnic Minorities Want?

01020304050607080

Per

cent

• Almost all minorities want to change their situation (86% of all respondents, 98% of minority respondents)

• Mainly in paid employment, education, attitudes and housing

01020304050607080

Minorities in general Minorities at greatest risk

0

10

20

30

40

50

60

Perc

ent

Minorities in general Minorities at greatest risk

Integration barriers and desired intervention

0

5

10

15

20

25

30

None General public Specific public Business NGOs Other

Perc

ent

All respondents Minority respondents

0

10

20

30

40

50

60

70

Equal treatment Specific provisions Positive discrim. Other

Percent

All respondents Minority respondents

Preferred policy principles(minorities in general and at greatest risk)

0

10

20

30

40

50

60

70

Equal treatment Specific provisions Positive discrim. Other

Percent

All respondents Minority respondents

• Equal treatment!

• But some room for positive action

Germany

Turks

ex-Soviet Union

ex-Yugoslav

Africans

1

2

3

1 3 5

Risk

Tre

nd

Slovakia

Hungarians

Roma

Ruthenians and

Ukrainians

Asians

1

2

3

1 3 5

Risk

Tre

nd

Policy Matrix •Based on the Expert Opinion Survey

• A tool to compare and scale the situation of minorities

• The four largest minorities in each country

• Measuring the risk of labor market exclusion and its trend

• The NE corner desires most policy attention

Conclusions

• Serious demographic challenges

• Severe ethnic divides in the EU (LM, downskilling, poverty)

• Welfare state helps but the discussion is misguided (lack of access rather than abuse, no welfare magnet etc)

• Ethnic minorities want change (attitudes, labor market access, etc)

• Missed opportunities

• Policy action needed

Martin Kahanec  Tel/Fax: +36 1 235 3097Email: kahanecm@ceu.hu

Department of Public PolicyCentral European UniversityNador utca 9Budapest 1051Hungarywww.publicpolicy.ceu.hu