IMMIGRANTS’ INTEGRATION IN OECD
COUNTRIES: DOES LABOUR MARKET
POLICY MATTER?
presented by Orsetta Causa (OECD Economics
Department and PSE)
The project
• Provide comparable cross-country estimates of
labour market integration of immigrants in OECD
countries. Use cross country comparable household
panel data.
• Identify labour market policies or institutions most
likely to influence labour market integration and
hence explain cross country differences in integration
Motivation (1/2)
• Performance gaps between comparable
immigrants and natives differ significantly
across countries. Cross country comparable
estimates are lacking.
– Few exceptions: Peracchi and de Palo, 2006;
Buchel and Frick, 2003, Adsera and Chiswick,
2004
Motivation (2/2)
• What drives cross country differences in immigrants
labour market integration?
• Premise: Role of History and Migrant related Policies.
Migration and integration policies, Migrant specific
policies
• Do framework conditions matter? do general labour
market policies (LMP) affect immigrants integration?
Existing literature is scant on the subject (exception
is Antecol et al.2006)
Outline
• The approach
• The Data
• Results by country
• Cross country results: the role of labour
market policies
• Conclusions
Integration. Literature: Main findings (1/2)
• Literature has mostly focused on the US (Chiswick, 1978,
Borjas, 1985, 1995). Literature on European countries is
scarce (see Zimmermann Constant eds. (2004))
• General view on wage gaps:
• Immigrants earn less than natives both at entry and
over time (estimated wage diff. in the US average 20% )
• There is a catch up of wages over time
• Assimilation through local human capital accumulation, e.g.
language skills (Chiswick and Miller, 1992, 1995), social
capital…
Integration. Literature: Main findings (2/2)
• Literature has mostly focused on wage gaps as opposed
to employment gap for the US - for European countries
the opposite holds
• General view on employment/ unemployment gaps:
• In European countries: immigrants display higher risk
of being unemployed, the gap varies across countries
(see OECD, 2005, Angrist and Kugler, 2003)
• Immigrants’ search methods are less effective than
natives’ (Frijtesr et al. (2005) , Olli Segendorf (2005) )
Integration. Empirical approach
• The outcome profile estimated form cross sectional
data is known to suffer from potential bias
• Changes in the unmeasured dimension of skill
(“quality”) of new immigrants cohort.
• Return Migration
• Recent research has focused on distinguishing
cohort effects from assimilation effects by relying
on the synthetic cohort approach (Borjas, 1994)
• Longitudinal data are important because they enable
to track individuals across time
LMP - Step1:
Why would LMP matter?
• Some immigrants’ characteristics- relative
to comparable natives- are likely to interact
with LMP:
– Productivity level - at arrival
– Worker-to-job matching capacities
– Reservation wage
– Bargaining power
– Labour market discrimination
LMP – Step2:
Imperfect substitutability in a wage bargaining
model (Jimeno and Rodriguez-Palenzuela ’s (2002))
• Basic Set up of the model
1)Production and Labour demand. Assume Imperfect substitutability
between two homogeneous categories of workers
uI  u N  ln 1  u N   ln 1  uI      (ln wI  ln wN )  ln LI  ln LN
2) Wage determination by collective bargaining. Assume lower
reservation wage and bargaining power for immigrants.
• Predictions:
– An increase in the relative bargaining power of natives increases
their relative wage, but also their relative unemployment rate
– An increase in the aggregate wage decreases the relative wage
of natives, while increasing the relative unemployment rates of
immigrants.
LMP – Step3:
Immigrants in a dual labour market (Blanchard
and Landier, 2002)
• Basic set up of the model
• Assumption: Consider two population, with the immigrant
population being characterized by a lower expected
productivity level
• Predictions:
-Immigrants are likely to be overrepresented among
outsiders on the labour market, as reflected in a higher
prevalence of short-term (and presumably low-pay) jobs
- The higher the strictness of the legislation on the use of
regular contracts, relative to temporary contracts, the
more pronounced immigrants’ overrepresentation among
outsiders, and therefore the wider the difference in the
share of short-term jobs, and in wages
The Data
• 1) EU15 Countries: ECHP DATA
• A standardised annual longitudinal survey carried out at
the level of the European union.
• The ECHP has reached 7 waves (from 1994 to 2001).
• The target population consists of all private households
through the national territory of each country.
• The ECHP is based on a common questionnaire centrally
designed by Eurostat.
2) Other OECD countries:
• US:- PSID: longitudinal household data (1997-2001)
• Australia- HILDA: longitudinal household data (2001-2003)
• Canada: SLID: longitudinal household data (1996-2001)
Attrition
Attritors individual characteristics, by migration status
Non-attritor
Employed2
Germany
Denmark
Belgium
France
Italy
Spain
Portugal
Austria
Finland
Australia
US
Wage3
Germany
Denmark
Belgium
France
Italy
Spain
Portugal
Austria
Finland
Australia
US
Natives
Attritor
Ratio
Non-attritor
Migrant
Attritor
Ratio
0.94
0.95
0.95
0.91
0.87
0.83
0.96
0.97
0.90
0.95
0.95
0.94
0.94
0.93
0.85
0.88
0.82
0.94
0.96
0.90
0.92
0.95
1.00
1.01
1.02
1.07
0.99
1.01
1.02
1.01
1.00
1.03
1.00
0.82
0.83
0.89
0.88
0.86
0.75
0.94
0.93
0.83
0.93
0.92
0.86
0.83
0.89
0.75
0.86
0.77
0.94
0.90
0.77
0.91
0.94
0.95
1.00
1.00
1.17
1.00
0.97
1.00
1.03
1.08
1.02
0.98
11.51
13.33
11.90
10.06
9.22
8.87
5.45
10.22
9.66
19.59
19.28
10.87
12.04
11.14
9.33
9.36
8.17
5.46
9.67
9.50
17.91
19.21
1.06
1.11
1.07
1.08
0.99
1.09
1.00
1.06
1.02
1.09
1.00
9.79
12.70
12.01
9.26
8.91
7.59
6.40
9.15
10.18
21.20
13.63
8.93
11.88
11.60
8.74
8.28
7.48
6.01
8.25
9.84
18.93
13.08
1.10
1.07
1.04
1.06
1.08
1.01
1.06
1.11
1.03
1.12
1.04
The Framework (1/3)
• Analyses differences in activity rates,
employment rates, and wage rates, across
comparable immigrants and natives
• Control for human capital and socioeconomic
characteristics
• Immigrant specific variable:
– Country of birth criterion
– Exposure to the country of residence. Due to the
sample characteristics, separate immigrants based on
15 year duration threshold
– Distinguish EU 15, OECD English speaking.
The Framework (2/3)
•
•
1.
2.
3.
The econometric procedure corrects for non
random sample selection into activity and into
employment based on observables and
unobservable (see Heckman, 1979)
Three steps:
Activity rates among working age individuals (16-64).
Separate men and women.
Employment rates across active, correcting for sample
selection into activity
Wage rates across employed individuals, correcting for
sample selection into paid employment
The Framework (3/3)
•
Estimated equation (general specification):
yict   ct   c X ict  c I ict   ict
•
•
Where y is the labour market outcome indicator for individual i, in
country c, period t. X are socio economic controls and I indicates
immigrant dummy;  captures country-level, time-varying
unobservable characteristics.
The selection equation, omitted here,includes an additional
regressor, Z ijtc , categorical variable coding for household type for
individual i living in household j
Estimates by country (1/2)
Employment males nonEU, <15YSM
Employment gap among actives versus wage gap for immigrants
with less than 15 years residency
0.35
0.30
0.25
DNK(ns,***)
FRA_n(***,***)
FRA(***,***)
0.20
0.15
GER(*,***)
AUS(***,***)
0.10
FIN(ns,***)
CAN (***,***)
AUT(***,**)
SPA(**,ns)
AUT_n(***,**)
0.05
ITA(***,ns)
USA(***,ns)
0.00
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Wage males nonEU, <15YSM
Estimates by country (2/2)
Employment males nonEU, >15YSM
Employment gap among actives versus wage gap for immigrants with
more than 15 years residency
0.20
DNK(ns,**)
FRA_n(***,***)
0.15
FRA(ns,***)
BEL(**,**)
AUT_n(***,*)
0.10
GER(***,***)
0.05
AUT(ns,**)
AUS(ns,*)
0.00
FIN(*,ns)
SPA(ns,ns)
CAN (**,ns)
ITA(ns,ns)
PRT(ns,ns)
-0.05
-0.20
-0.10
0.00
0.10
USA(***,ns)
0.20
0.30
0.40
Wage males nonEU, >15YSM
Explaining cross country integration differences: the
role of labour market policies
• To what extent do labour market institutional differences across
European countries explain differences in immigrants’ varying
degree of absorption into the labour market?
• Pool countries
• Estimate a “full” model- country specific parameters on every
control except immigrant dummies, policy variables and
interactions:
yict   c   ct   c X ict  I ict   Re gct   Re g ct  I ict   ict
– The estimated immigrant/ native gap is allowed to vary with
the level of regulation (variable denoted Reg)
Cross country differences: The role of labour
market policies
Policy
(in a univariate framework)
Activity
Women
Average replacement rate
Employment
Men
Wage
Women
_
Minimum Wage
_
Tax wedge
_
EPL Dualism
+
_
+
+
_
Note: Results refer to the sign, if significant
See text and annex for details on the specification .Years since migration controlled for.
Indicated sign denotes that the interaction is significant at least for one of the two categories (<15ysm or >15 ysm)
EPL Dualism is defined as follows: (EPLR-EPLT)/(EPLT)
Wage
Men
_
Labour market dualism and precariousnesssome evidence based on ECHP Data (1/3)
Proportion of non-EU15 born immigrants among individuals declaring
to hold fixed-term, short-term contracts, or casual work with no contract
Germany
Denmark
Belgium
France
Italy
Spain
Portugal
Austria
Finland
Native
Non EU
>15YSM
Non EU
<15YSM
0.10
0.11
0.09
0.10
0.10
0.33
0.14
0.05
0.14
0.07
0.13
0.12
0.07
0.10
0.32
0.18
0.10
0.11
0.18
0.16
0.12
0.17
0.10
0.48
0.17
0.16
0.15
Note:
Weighted
Data.
The
individuals
are
employed
working
in
paid
employment
more
than
15
hours
per
week.
Non-EU refers to individuals not born in EU15 countries except in the case of Germany where the nationality criterion is used. > or < 15 YSM refers to more or less than 15 years since migration.
Source: Author’s calculations based on ECHP.
Labour market dualism and precariousnesssome evidence based on ECHP Data (2/3)
Impact of migration status on the probability of holding a precarious employment contract – crosscountry estimates
Male
nonEU/nonESC <15YSM (1)
0.079 ***
(3.95)
nonEU/nonESC >15YSM (1)
0.036 **
Female
0.068 ***
(3.09)
0.021
(2.00)
(0.91)
Observations
117547
88280
Nb of cluster
28745
23009
Log likelihood
-39208
-33350
Labour market dualism and precariousnesssome evidence based on ECHP Data (3/3)
Estimated interaction between institutional labour market dualism and immigrants’ probability of
holding a precarious contract, relative to comparable natives
Men
nonEU/nonESC <15YSM (1)
Women
(1)
(2)
0.423 ***
0.278 ***
(5.79)
nonEU/nonESC >15YSM (1)
0.178 **
(2.65)
0.043
(2.31)
(0.51)
0.281 *
0.070
(1.95)
(0.39)
Interaction terms:
EPL differences x (<15YSM) (3)
EPL differences x (>15YSM) (3)
Observations
R-squared
N_clust
df_m
-0.018
0.258 **
(0.15)
(2.00)
117,547
28,745
-36,762
114
88,280
23,009
-32,084
114
Conclusions
• Immigrants’ labor market integration remains a
challenge
• General-purpose labour market policies matter
in this respect:
– Given their specificities, immigrants tend to be
especially sensitive to the effect of some policies,
such as unemployment benefits and the tax
wedge, and most of all to labour market dualism.
• Further investigation would be useful to
understand better the links between labour
market policies and immigrants’ integration in
the host labour market.