Transcript Martin Kahanec

Inclusion of Immigrants into Welfare: The
Myths and the Veracity in the EU
Martin Kahanec
Central 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
25
20
15
Other
EUN
EU12
EU15+EFTA
10
5
CY
IE
BE
AT
SE
UK
FR
LV
EE
IT
GR
NL
SI
ES
DK
PT
LT
FI
CZ
HU
SK
PL
BG
RO
0
Highest shares CY, IE, BE, AT, SE, UK; lowest RO, BG, PL, SK, HU, CZ.
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
35%
30%
25%
20%
15%
10%
5%
0%
LU
BE
CY
FI
GR SE
FR
AT
UK
NO
CZ
ES
-5%
-10%
Non-EU
Source: EU-SILC (2008).
Notes: *All migrants for Germany.
EU
IT
IE
DK
NL
PT DE* IS
PL
Unskilled immigrants?
c) Percent high-educated EUN immigrants
and natives
60
d) Percent high-educated other immigrants
and natives
60
CY
IE
RO
Percent high skilled, EUN
Percent high skilled, other origin
IE
50
40
EE
PT
HU
30
LV
CZ
20
PL LT
UK
SE DK
SK
FR NL
SI
10
IT
AT
FI
BE
ES
SK
50
EE
RO
40
UK
SE
BE
LTFR
DK
DE
CY
NL
PL
FI
LV
ES
GR
BG
SI
HU
30
AT
20
PT
10
CZ
IT
GR DE
0
0
0
10
20
30
40
50
Percent high skilled, natives
60
0
10
20
30
40
50
60
Percent high skilled, natives
Non-EU immigrants well-educated, especially in NMSs. Less skilled than natives are
EUNs in the EU15, other immigrants in eg ES and FI.
Tertiary education. Source: Kahanec, 2012. EU LFS 2010
Brain waste?
c) Percent high-skilled EUN immigrants
and natives
d) Percent high-skilled other immigrants
and natives
70
65
65
60
60
High-skiled share, other origin
70
High-skiled share, EUN
55
50
RO
45
40
35
HU
BG
30
25
SK
20
15
10
PT
5
0
10
15
LT
UK
CY IE
FR
LV
CZ
PL
SI BE
FI EE
GR
DE
AT
IT
ES
20
25
30
High-skilled share, natives
NL
DK
SE
55
50
SI
45
SK
40
RO
35
BG
30
EE
25
AT
PT
20
15
PL
10
CZ
LT
FR
LV
FI
GR
CY
ES
5
UK
IE
HU
NL
BE
DK
DE
SE
IT
0
35
40
10
15
20
25
30
35
40
High-skilled share, natives
Non-EU immigrants more often work in less-skilled occupations (especially ES, IT, AT,
DE< SE, NL), except for some NMSs.
ISCO 1-3. Source: Kahanec, 2012. EU LFS 2010
Ratio of proportions of immigrants and natives:
Unemployment support
5
4
3
2
1
0
NO
FI
IS
PL
AT
UK
IT
GR
LU
FR
DK
Non-EU
SE
EU
DE* BE
PT
NL
ES
CY
IE
CZ
Estimated marginal impact of immigrant status on
support receipt: unemployment, sickness and
disability
25%
20%
15%
10%
5%
0%
FI
DK AT
FR NO LU DE* IT
GR NL
BE
IS
-5%
-10%
-15%
Non-EU
EU
UK SE
PT ES
PL
IE
CY CZ
Ratio of proportions of immigrants and natives:
Unemployment support for those who are unemployed
60%
50%
40%
30%
20%
10%
0%
-10%
LU
DK
GR
UK
IT
CZ
IS
DE* PL
AT
FI
FR
-20%
-30%
-40%
-50%
Non-EU
EU
PT
ES
BE
NO
CY
SE
IE
NL
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 welfareheterogeneous 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 19932008
Econometric model
mit     xit 1  z
'
it 1
γ   i   t   it
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), percapita 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.
Results (OLS, non-EU)
a - wihout UBS; b - with UBS; c - with other welfare components
(health, family, pension); d – no weights
(a)
UBS
Stock of non-EU immigrants
Per-capita GDP
Unemployment rate
Constant
R
2
0.141 ***
(0.028)
0.017 ***
(0.007)
-0.007
(0.018)
-0.056 ***
(0.023)
0.64
(b)
(c)
Non-EU immigrants
0.058 *
0.061 *
(0.028)
(0.031)
0.129 ***
0.123 ***
(0.026)
(0.028)
0.019 ***
0.018 ***
(0.007)
(0.007)
-0.015
-0.005
(0.017)
(0.016)
-0.063 ***
-0.053 ***
(0.024)
(0.021)
0.65
0.68
(d)
0.066 ***
(0.021)
0.079 *
(0.039)
0.007
(0.004)
-0.026
(0.015)
-0.02
(0.014)
0.52
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
immigration
A)
B)
Immigrants themselves directly increase UBS take up or decrease
average GDP
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?
0
.02
.04
.06
First stage: UBS on # of coalition parties
0
2
4
6
8
Results
EU immigrants
IV
GMM
UBS
Stock of immigrants
Per-capita GDP
Unemployment rate
Constant
N
0.040
(0.065)
0.133 ***
(0.018)
0.019 ***
(0.003)
-0.012
(0.011)
-0.068 ***
(0.012)
248
-0.013
(0.029)
0.115 ***
(0.011)
0.015 ***
(0.002)
-0.013 ***
(0.006)
-0.054 ***
(0.007)
248
Non-EU immigrants
IV
GMM
-0.003
(0.007)
0.075 ***
(0.009)
0.000
(0.001)
0.000
(0.001)
0.001
(0.002)
248
-0.004
(0.022)
0.073 ***
(0.014)
0.000
(0.001)
0.002
(0.003)
0.002
(0.005)
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.
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?
Percent
70
60
50
40
30
20
10
0
What Do Ethnic Minorities Want?
pa
rti
ci
pa
ti o
R
ep
n
re
se
nt
at
io
n
Po
l it
th
er
O
A
ul
tu
ra
l
C
Minorities at greatest risk
pa
ti o
Re
n
pr
es
en
ta
tio
n
At
ti t
ud
es
pa
rti
ci
li fe
Po
l it
Cu
l tu
ra
l
M
ob
i li t
y
Ho
us
ing
Ed
uc
at
io
So
n
c.
in
su
ra
nc
e
He
al
th
ca
re
em
pl
Se
l f-
em
pl
li f
e
ty
M
ob
i li
ou
si
ng
H
Ed
uc
at
io
So
n
c.
in
su
ra
nc
e
H
ea
l th
ca
re
em
pl
Se
l f-
Minorities in general
80
70
60
50
40
30
20
10
0
Pa
id
Percent
Pa
id
em
pl
• Almost all minorities want to change their situation
(86% of all respondents, 98% of minority respondents)
• Mainly in paid employment, education, attitudes and housing
Integration barriers and desired intervention
60
Percent
50
40
30
20
10
th
er
O
In
st
itu
ti o
na
l
In
te
rn
al
is
cr
im
in
at
io
n
D
In
fo
rm
at
io
n
Ed
uc
at
io
n
La
ng
ua
ge
N
on
e
0
Minorities in general
Minorities at greates t ris k
30
25
Percent
20
15
10
5
0
None
Ge ne ral public Spe cific public
All res pondents
Bus ine s s
Minority res pondents
NGOs
Othe r
Preferred policy principles
(minorities in general and at greatest risk)
• Equal treatment!
• But some room for
positive action
70
60
Percent
50
40
30
20
10
0
Equal tr e atm e nt
Spe cific pr ovis ions
All res pondents
Pos itive dis cr im .
Othe r
Minority res pondents
70
60
Percent
50
40
30
20
10
0
Equal tr e atm e nt
Spe cific pr ovis ions
All res pondents
Pos itive dis cr im .
Minority res pondents
Othe r
Germ any
Trend
3
ex-Soviet
Union
2
Africans
Turks
ex-Yugoslav
•Based on the Expert Opinion
Survey
• A tool to compare and scale
the situation of minorities
1
1
3
5
Risk
3
Asians
2
Ruthenians
and
Ukrainians
1
1
• The NE corner desires most
policy attention
Roma
Hungarians
3
Risk
• The four largest minorities
in each country
• Measuring the risk of labor
market exclusion and its
trend
Slovakia
Trend
Policy Matrix
5
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 3097
Email: [email protected]
Department of Public Policy
Central European University
Nador utca 9
Budapest 1051
Hungary
www.publicpolicy.ceu.hu