Download Chapter 3 - School of Business and Social Sciences

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Internationalization wikipedia , lookup

Development theory wikipedia , lookup

International factor movements wikipedia , lookup

Development economics wikipedia , lookup

Economic globalization wikipedia , lookup

Transcript
FACTORS INFLUENCING
MIGRATION FLOWS
PhD defence
Mariola Pytlikova
Aarhus, February 20th, 2006
Department of Economics, Aarhus School of Business
2 phenomena driving migration
flows over the last decades:
1. Growing migration from less developed countries
lower social mobility, skill transferability and
skill acquisition
immigrants have difficulties entering the
destinations’ labor markets and integrate
2 phenomena driving migration
flows over the last decades:
2. Fall of Iron Curtain – emigration from Central and
Eastern Europe
Given geographical and cultural proximity and the large
economic differences, Western Europe fear mass migration,
EU enlargement towards the East:
• 10 new countries joined EU15 in May 2004,
• UK, Ireland and Sweden have opened, majority of “old”
members imposes restrictions to free movement of workers,
• In 2006 decision about extending the ”transition period”
Migration pressures will
continue in the future


Growing globalization – improvements in
communication, Internet, transportations
Demographic projections
Demographic projections –
European Union
2000
2050
(Population: 451.4 million)
(Population: 401 million)
100+
95-99
100+
95-99
90-94
85-89
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
90-94
85-89
80-84
Males
75-79
Females
Males
70-74
65-69
Females
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
60
40
20
0
20
40
60
60
Source: Cohen (2003): Human Population: The Next Half Century
40
20
0
20
40
60
Demographic projections –
North Africa and West Asia
2000
2050
(Population: 587.3 million)
(Population: 1,298 million)
100+
95-99
90-94
100+
95-99
90-94
85-89
85-89
80-84
75-79
80-84
75-79
70-74
65-69
Males
60-64
55-59
50-54
45-49
40-44
Males
Females
70-74
65-69
60-64
Females
55-59
50-54
45-49
40-44
35-39
30-34
35-39
30-34
25-29
20-24
25-29
20-24
15-19
15-19
10-14
5-9
0-4
10-14
5-9
0-4
60
40
20
0
20
40
60
Source: Cohen (2003): Human Population: The Next Half Century
60
40
20
0
20
40
60
Migration pressures will
continue in the future


Growing globalization – improvements in
communication, Internet, transportations
Demographic projections
Immigration policy must adjust to the migration
pressures and to the aging populations.
DETERMINANTS OF MIGRATION FLOWS IMPORTANT
FROM THE POLICY MAKERS POINT OF VIEW.
WHY DO PEOPLE MIGRATE?
Theory I

ECONOMIC FACTORS:

Wage differences (Hicks, 1932),

“Human capital investment” (Sjaastad, 1962; Becker,
1964),


Income expectations conditioned on being employed (Harris
& Todaro, 1970; Hatton, 1995),
Family or households decision (Mincer, 1978; Holmlund,
1984),

Risk-diversifying strategy of families (Stark, 1991),

Relative deprivation approach (Stark, 1984),

“Welfare magnet” (Borjas, 1999).
WHY DO PEOPLE MIGRATE?
Theory II

MIGRATION NETWORKS:
– migration networks: “…sets of interpersonal ties that connect
migrants, former migrants, and non-migrants in origin and
destination areas through ties of kinship, friendship, and shared
community origin” (Massey, 1993)
– help to explain persistence in migration
– “herd behavior” effect (Bauer et al. 2002),


NON-ECONOMIC FACTORS: war, love/marriage, taste
for adventure
OTHER (UN)OBSERVABLE COUNTRY SPECIFIC FACTORS
WHY DO PEOPLE NOT MIGRATE?
Theory
But only around 2 percent of the world’s population resided in a
country other than they were born.
??? WHY THERE IS NOT THAT MUCH MIGRATION ???
BARRIERS TO MIGRATION:

Immigration policies
out-of-pocket expenses

Costs of migration
psychological costs

Cultural distance

Language barriers
WHO MIGRATES??


SELECTION PROCESSES IN MIGRATION
“self-selection model” (Borjas, 1987) - skill differentials
between immigrants and natives in relation to the variance
in the wage distribution.
Positive selection
countries with big wage dispersion
Negative selection
countries with low wage dispersion
In line with the “Human capital investment” there are
higher “returns to migration” for young with greater abilities
(Chiswick, 2000).

WHAT DOES THE EMPIRICAL
EVIDENCE SAY???



There are many studies on determinants of international
migration – but mostly on migration into one country;
Evidence from a multi-country perspective has been in
general rather scarce, mostly due to the data limitations;
Previous studies on migration from Central and Eastern
Europe relied on out-of-sample data analysis, again due to
the data limitations.
DATASET
It is difficult to obtain a consistent database on international migration
Contact statistical offices in the 26 OECD countries
Detailed information on immigration flows and stock into 26
OECD countries from 129 particular countries of origin.
Period: 1989 to 2000.
Dataset unbalanced, i.e. missing observations for some
countries and some years
Given the lack of international migration databases - this new dataset
serves a great source for analyses of international migration behavior.
DATASET
Besides - many other variables, which can help us explain the
immigration behavior:
Economic variables
Demographic variables,
Distance variables: cultural, physical,
linguistic,
Welfare state variables,
Educational variables,
Violated political rights and civil liberties
variable
Sources: WB, ILO, OECD, IMF and national statistical offices of
particular OECD countries.
METHODOLOGY

Regression analysis
 ij
Gross flowsijt  1   2 X  ijt
Explanatory variables
CHALLENGES:
How to tackle unobserved
country-specific heterogeneity ?
Economic Dynamics
 ijt
Unobserved heterogeneity
Remaining error
SOLUTION:
Panel data models - Fixed or
Random effects estimators
Instrumental variable techniques
Arellano-Bond (1991) difference or the
Arellano-Bover (1995) system GMM
estimator
MIGRATION DETERMINANTS:
Aspects considered in my thesis




Chapter 2: How mobile are Central and Eastern Europeans?
Evidence from inter-regional migration in the Czech Republic
Chapter 3: Selection and network effects – migration flows
into OECD countries 1990-2000. (Joint with Peder J. Pedersen
and Nina Smith)
Chapter 4: Where did Central and Eastern Emigrants go and
why?
Chapter 5: EU enlargement: migration from new EU
countries.
MIGRATION DETERMINANTS:
Aspects considered in my thesis




Chapter 2: How mobile are Central and Eastern Europeans?
Evidence from inter-regional migration in the Czech Republic
Chapter 3: Selection and network effects – migration flows
into OECD countries 1990-2000. (Joint with Peder J. Pedersen
and Nina Smith)
Chapter 4: Where did Central and Eastern Emigrants go and
why?
Chapter 5: EU enlargement: migration from new EU
countries.
MIGRATION DETERMINANTS:
Aspects considered in my thesis




Chapter 2: How mobile are Central and Eastern Europeans?
Evidence from inter-regional migration in the Czech Republic
Chapter 3: Selection and network effects – migration flows
into OECD countries 1990-2000. (Joint with Peder J. Pedersen
and Nina Smith)
Chapter 4: Where did Central and Eastern Emigrants go and
why?
Chapter 5: EU enlargement: migration from new EU
countries.
FACTORS INFLUENCING
MIGRATION FLOWS – findings I
EFFECT ON GROSS
MIGRATION
FLOWS:
THEORY:
FINDINGS:
Economic factors:
Income
destination
+
+
Chapter 3
-
Inverted U-shape
Chapter 3, Faini and
Venturini,1994
+
+
Chapters 2, 4 and 5
Unemployment
destination
-
-
Unemployment
source
+
-
Welfare magnet
+
-
Income source
Income ratio
or no effect/
insignificant
or no effect/
insignificant
Chapters 2,3, 4 and 5
Chapters 2,3, 4 and 5
Chapter 3
FACTORS INFLUENCING
MIGRATION FLOWS – findings II
EFFECT ON GROSS
MIGRATION FLOWS:
NETWORKS
THEORY:
+
FINDINGS:
+
Chapters 3, 4 and 5
Other factors – human capital:
Tertiary enrollment
rate source
+
+
Chapter 4
Illiteracy rate source
+
+
Chapter 3
Language in
destinations
Chapter 4
Non-economic factors
Freedom House
Index
Other unobservable
country-spec. effects
+
+/insign.
Important
Chapter 3
Chapters 2, 3, 4 and 5
FACTORS INFLUENCING
MIGRATION FLOWS– findings III
EFFECT ON GROSS
MIGRATION FLOWS:
THEORY:
FINDINGS:
Barriers to migration:
Distance
-
-
Chapters 2, 3, 4 and 5
Cultural distance
Neighboring dummy
+
Common history
+
Linguistic Distance
Business ties
+
+
-
or no effect/ Chapters 3 and 4
insignificant
+
+
+
Chapter 3
Chapter 3
Chapter 3
SELECTIVITY IN MIGRATION
FLOWS– findings
Selectivity in migration:
No direct indications of “country based
selectivity” effects.
Some selectivity through “networks” –
“networks” more important for immigrants
coming from low-income countries than for
immigrants coming from high-income
source countries.
Chapter 3
Chapter 3
PREDICTIONS OF MIGRATION



The obtained coefficients of the migration determinants can be
used for prediction of migration potential.
Application to a prediction of migration potential from the new EU
members into the “old” EU countries in years after the 2004 EU
enlargement, 2004–2015. (chapter 5)
3 assumed scenarios concerning the future economic convergence
of the countries.
Predicted gross migration flows from 7 new EU
members into the 12 EEA/EU countries.
Average flow 2004-2015, medium convergence scenario
350000
321866
300000
274494
250000
200000
150000
100000
50000
1610
680
1805
3925
4069
4238
4318
4623
5257
6452
10395
-1
2
/E
U
EE
A
an
y
er
m
G
Ita
ly
*
Fi
nl
an
d
D
en
m
ar
N
k
et
he
rla
nd
s
er
la
nd
Sw
itz
el
gi
um
B
ai
n*
*
Sp
ed
en
Sw
N
or
w
ay
ce
re
e
G
Ic
el
an
d
0
*For Italy, only numbers of Poles are shown. ** For Spain, only numbers of Poles and
Czechs are shown.
Predicted migration stocks from 7 new EU
members residing in the 13 EEA/EU countries.
Year 2000 and 2015, medium convergence scenario.
1240148
1200000
Year 2000
Year 2015
1000000
800000
617372
600000
400000
133224
200000
110257
2452
85726
51692 68505
21449 25182 26918 28642 28723 40006
A
/E
U
-1
3
EE
er
m
an
y
G
U
K
ed
en
Sw
Ita
ly
an
N
d
et
he
rla
nd
s
itz
er
l
ar
k
Sw
D
en
m
Sp
ai
n
Fi
nl
an
d
B
el
gi
um
re
ec
e
G
Ic
el
an
d
N
or
w
ay
0
For Spain, only numbers of Poles and Czechs are shown. UK numbers do not contain
Baltic countries: Estonia, Latvia and Lithuania.
FACTORS INFLUENCING
MIGRATION FLOWS
summary of the findings

some policy recommendations for – Europe and Denmark:
– Shift towards economically based selective immigration
policy :
– for Denmark - the point system idea of the welfare
commission might be beneficial
– Emigration from Central and Eastern Europe – forecast for
EU, prediction for Denmark – no “migration floods”