Slajd 1 - Uniwersytet Warszawski
Download
Report
Transcript Slajd 1 - Uniwersytet Warszawski
Migration and development
Paweł Kaczmarczyk
Centre of Migration Research / Faculty of Economics
University of Warsaw
„Once upon a time…” seminar
November, 5th 2010
Outline
Instead of introduction
Migration and development – basic issues
Migration in the 21. century – a global picture
Potential impacts / developmental aspects
Receiving countries
Sending countries
Policy implications
Instead of introduction
Case study 1:
1960s, newly-independent Kenya high and raising
unemployment in Nairobi
Solution: Tripartite Agreement reached in which private and public
employers agreed to increase the number of jobs while holding
wages at constant level
Outcome: further increase in urban unemployment…
Harris and Todaro model (1970):
Urban wages are higher than rural ones
In order to be employed it was necessary to be physically present
in the urban areas
Why people are moving? Due to difference in the expected wages
(including probability of finding a job)
As a consequence: more workers search for jobs than are hired )
rise in urban unemployment
Instead of introduction
Case study 1…:
Policy results:
The solution to urban unemployment is not necessary the
urban employment creation
The solution would be rather rural development…
Generally:
one of the first models based on solid micro-foundations
showing close relationships between migration (rural-urban)
and development
one of the principal alternative frameworks for policy analysis
conditions in one (labour) market may reflect conditions
(demand, supply, institutional conditions) in other markets.
Migration and development – basic issues
Traditional approach to development (and migration):
Focus on monetary income and economic growth (mostly on the
national level)
Narrow view of development as a process of incorporation into
the capitalist system (entailing industrialisation and urbanisation)
Rural-urban migration as an integral part of development
Mainstream migration theory entrenched in a ‘modernist ideology’
concept of progress
This concept of progress can be understand as a response to
chaotic and very rapid urbanisation and industrialisation in the
18th century rural migration perceived as a threat to already
established lifestyles
Additionally: ‘methodological nationalism’ focus on nation
states
Bias towards control of migration and imposing barriers to
mobility, believe in the power of migration policies.
Migration and development – basic issues
New agenda?
Structure vs. agency
Structural conditions mobility (agency) potential force for
structural change
The meaning of human development:
Sen (1999): development as a ‘process of expanding the substantive freedoms
that people enjoy’
Mahbub ul Haq (1995): ‘The basic purpose of development is to enlarge
people’s choices’
Human capability approach migration as an integral part of
human development (exercising of freedom, enhancing
opportunities)
Coherent with trends in migration studies: emphasis on
individual agents and households migration as a livelihood
strategy
Migration in the 21. century – a global picture
Basic data (HDR 2009):
Number of internal migrants: 740 million
Number of international migrants: 200 million
Number of South – North migrants: < 70 million
Number of South – South / North – North migrants: ~130 million
Number of refugees: 14 million
Number of internally displaced persons: 26 million
Source: WB 2009
Migration in the 21. century – a global picture
Source: HDR 2009
Why do people migrate?
Source: HDR 2009
Why do people not migrate?
Source: HDR 2009
Why do people not migrate?
Source: HDR 2009
Why do people not migrate?
Free migration that equalized the marginal productivity of
labour and had all workers fully employed is estimated to
potentially more than double global GDP from USD 8 trillion
(1977) to USD 16 trillion (Hamilton and Whalley, 1984).
Dani Rodrik (2001): ‘if international policy makers were really
interested in maximizing worldwide efficiency, they would
spend little of their energies on a new trade round or on the
international financial architecture. They would all be busy […]
liberalizing immigration restrictions’.
Philip Martin (2005): ‘Even a marginal liberalization of
international labour flows would create gains for the world
economy that are far larger than prospective gains from trade
liberalization’.
Hatton and Williamson (2005) transcontinental mobility as
a key convergence factor in the 19th century…
20th century???
Labour mobility agenda for development?
Michael Clemens (2010) and three „big questions”:
Can migration do much to help development?
Must people at destinations suffer?
Is migration harmful for receiving countries and societies?
Potential impacts – sending countries
loss of labour / ‘export of unemployment’
loss of scarce human capital needed to maintain or increase
productivity in the sending country brain drain
remittances direct and indirect impacts
‘social remittances’
Labour market impacts
(E)migration as a shock to labour market loss of labour
labour shortages, pressure on wages
BUT: if there is an oversupply of labour the outflow will have
zero opportunity cost
Problem: in the case of high levels of out-migration the loss of
emigrant labour reduces the productivity of complementary
factors such as land and capital emigration produces a
deadweight welfare loss.
Evidence:
Migration usually does not involve more than 2-3% of labour
force
Turkey in 1973 had one million expatriates (6% of labour
force), Philipiness about 6% of the labour force abroad in
neither case could the migration solve the problem of
structural unemployment
Impact on wages: positive but moderate (Mishra 2007,
Hanson 2005, Aydemir and Borjas 2006).
Potential impacts – brain drain
Two distinctive parts of the literature on consequences of
highly skilled mobility:
‘traditional approach’ - Grubel and Scott (1966), Bhagwati and
Hamada (1974): a pessimistic view, emphasis on costs and
losses, i.e. fiscal effects, impact on factors’ productivity
brain drain;
‘modern approach’ - Stark et al. (1997), Mountford (1997),
Beine et al. (2001) new economics of brain drain: migration
as a probabilistic event, i.e. the outcome of a lottery where
the would-be migrant has a positive probability p of actually
migrating, where p<1 the decision to invest in education is
driven by the expected return to human capital a positive
probability p of migrating increases the expected return to
investment in human capital compared to the no-migration
situation an increase in the optimal level of human capital.
Potential impacts – brain drain
Additional effects:
a reduction in educational attainment in the areas
characterized by higher emigration rates possible as a
consequence of very low (or even zero) returns to human
capital in the destination countries - McKenzie and Rapoport
(2008)
brain waste - Mattoo et al. (2005)
brain overflow – Kaczmarczyk and Okólski (2008)
the scope for a beneficial brain drain should be substantially
reduced - Egger and Felbermayr (2007), Brücker et al. (2007)
A dynamic approach: Beine, Docquier and Rapoport (2001).
Brain drain model with "brain effect" and
"drain effect" – selected conclusions
From the theoretical model it follows that:
Share of well educated depends on migration prospects
Economic growth depends on the share of well educated
(in a positive way) and migration (negatively) –
outcome? (empirical issue)
Important:
Static effect – drain effect (ex post)
Dynamic effect – brain effect (ex ante)
Beneficial Brain Drain (BBD) emerges when the
brain effect dominates.
Problem: empirical strategies…
Case study 2: highly skilled mobility from the
NMS
Percentage of persons with tertiary education in the native and migrant population in the
NMS, 2006
35
Resident population
Migrant population
30
Migrant population, age adjusted
25
20
15
10
5
0
Bulgaria
Czech
Republic
Estonia
Hungary Lithuania
Latvia
Poland
Romania Slovenia
Slovak
Republic
Drain effect or brain overflow?
Unemployment rates in the NMS10: persons aged 15-39 with tertiary education - levels 5-6 (ISCED
1997), 2000-2007 (2nd quarter), in %
12
10
EU15
Bulgaria
8
Czech Republic
Estonia
6
Latvia
Lithuania
4
Hungary
Poland
2
Romania
Slovenia
Slovakia
2007q02
2006q02
2005q02
2004q02
2003q02
2002q02
2001q02
2000q02
0
Brain effect? accumulation of human capital
Percentages of students in the population aged 15-29, EU25 and NMS10, 2000-2007
30%
25%
EU25
Bulgaria
Czech
Republic
Estonia
20%
Latvia
Lithuania
15%
Hungary
Poland
10%
Romania
5%
2000
2001
2002
2003
2004
2005
2006
Factors influencing the brain effect – wage
premium
Average net earnings in selected group of workers according to Polish LFS, 2000-2006, by
education level, average = 1
Brain drain or brain waste?
Around 83%
Employment structure in the UK, by education, natives
Age left full-time education
Occupation
less than 16
16 or 17
18, 19 or 20
more than 20
Total
Managers and senior officials
9.01
13.12
19.07
19.79
14.33
Professionals
2.40
4.70
11.14
44.5
11.58
Associate professional and tech.
5.60
10.79
18.66
18.38
12.25
Admin and secretarial
12.93
19.02
20.76
7.91
16.33
Skilled trades
13.41
11.95
4.60
1.51
9.38
Personal services
12.88
10.68
10.38
2.95
9.86
8.82
8.69
7.64
2.88
7.62
Process, plant and machine oper.
16.23
10.37
3.13
0.87
8.85
Elementary occupations
18.71
10.67
4.62
1.21
9.80
Sales and customer services
Around
68%
Source: UK Quarterly Labour Force Survey 1993Q4-2007Q4
Employment structure in the UK, by education, post-2004 migrants from EU8 countries
Age left full-time education
Occupation
less than 16
16 or 17
18, 19 or 20
more than 20
Total
Managers and senior officials
0.00
0.85
0.74
2.77
1.43
Professionals
0.00
0.00
0.18
8.31
2.96
Associate professional and tech.
0.00
0.00
2.03
7.20
3.54
Admin and secretarial
3.85
0.00
3.33
4.99
3.54
19.23
16.10
9.80
8.86
10.42
Personal services
0.00
5.08
8.32
12.47
9.18
Sales and customer services
3.85
0.85
1.85
2.22
1.91
Process, plant and machine oper.
15.38
33.05
24.03
17.17
22.47
Elementary occupations
57.69
44.07
49.72
36.01
44.55
Skilled trades
Source: UK Quarterly Labour Force Survey 1993Q4-2007Q4
Source: Brücker et al. 2009
Brain drain or brain waste?
Net weekly pay of full-time workers from NMS7 in the UK nominal and relative to the average (as per
cent, in bold)
Pre-accession migrants
Post-accession migrants
Age groups
Age groups
Age left fulltime education
Less than 15
16 to 17
18 to 20
15-20
21-29
31-45
45+
Total
15-20
21-29
31-45
45+
Total
-
227.00
150.00
187.50
182.43
-
162.50
-
216.14
204.22
-
82.3
54.4
67.9
66.1
-
76.7
-
102.0
96.3
-
240.20
217.50
279.30
252.33
171.40
195.77
176.78
182.00
184.14
-
87.0
78.8
101.2
91.4
80.9
92.4
83.4
85.9
86.9
138.33
232.37
250.26
257.06
238.05
180.57
210.06
198.25
213.56
207.23
50.1
84.2
90.7
93.1
86.3
85.2
99.1
93.5
100.8
97.8
226.77
430.46
423.11
350.63
-
217.05
251.89
323.73
255.18
82.2
156.0
153.3
127.1
-
102.4
118.8
152.7
120.4
163.00
219.00
471.00
-
284.33
-
251.00
-
195.00
223.00
59.1
79.4
170.7
-
103.0
-
118.4
-
92.0
105.2
144.50
230.98
321.33
315.72
275.96
176.75
209.27
206.59
226.37
211.97
52.4
83.7
116.4
114.4
100.0
83.4
98.7
97.5
106.8
100.0
More than 21
Students
Total
Source: own elaboration based on the LFS data
Brain drain or brain waste?
Net weekly pay of full-time workers from Poland in the UK
nominal and relative to the average (as per cent, in bold)
Pre-accession migrants
Age left full-time
education
Less than 15
16 to 17
18 to 20
15-20
-
31-45
174.00
45+
181.50
Total
192.00
15-20
-
Age groups
21-29
31-45
266.75
176.00
45+
219.50
Total
226.00
-
73.8
55.6
58.0
61.4
-
117.4
77.5
96.6
99.5
200.00
242.33
257.17
243.12
145.67
190.50
226.10
195.08
197.24
38.4
63.9
77.5
82.2
77.7
64.1
83.9
99.5
85.9
86.8
62.50
234.35
279.94
261.55
250.89
207.22
202.81
220.47
236.42
217.65
20.0
74.9
89.5
83.6
80.2
91.2
89.3
97.1
104.1
95.8
-
274.83
394.57
393.38
354.54
-
223.97
306.04
255.99
244.67
87.9
126.1
125.7
113.3
-
98.6
134.7
112.7
107.7
-
-
-
120.00
518.00
-
-
-
518.00
120.00
Total
21-29
231.00
120.00
More than 21
Students
Post-accession migrants
Age groups
38.4
-
-
-
38.4
228.1
-
-
-
228.1
91.25
260.45
352.77
334.35
312.83
212.95
212.36
249.97
240.42
227.14
29.2
83.3
112.8
106.9
100.0
93.8
93.5
110.1
105.8
100.0
Source: own elaboration based on the LFS data
Net weekly pay of full-time workers from EU14 in the UK
nominal and relative to the average (as per cent, in bold)
EU15 immigrants
Age groups
Age left full-time education
Less than 15
16 to 17
18 to 20
15-20
21-29
31-45
45+
Total
172.13
242.40
249.44
256.05
250.82
55.4
78.1
80.3
82.5
80.8
165.62
275.65
314.53
303.23
294.95
53.3
88.8
101.3
97.6
95.0
176.14
253.78
360.63
372.94
324.36
56.7
More than 21
224.00
Students
Total
81.7
116.1
120.1
104.5
348.29
523.33
519.99
464.66
112.2
168.5
167.5
149.6
220.28
385.00
342.67
240.07
72.1
70.9
124.0
110.3
77.3
114.40
270.01
359.05
306.48
310.53
36.8
87.0
115.6
98.7
100.0
Source: own elaboration based on the LFS data
Brain drain or brain waste?
Net weekly pay of full-time native workers in the UK nominal and relative to the average (as per cent,
in bold), 2002 and 2006
2002, 2nd quarter
Age left full-time
education
Less than 15
16 to 17
18 to 20
Age groups
Total
Age groups
15-20
150.00
21-29
246.14
31-45
256.29
45+
254.61
Total
253.00
15-20
21-29
31-45
45+
143.08
281.14
303.28
294.49
Total
293.48
47.9
78.6
81.9
81.3
80.8
40.4
79.3
85.5
83.1
82.8
158.53
245.59
297.77
310.96
283.04
166.50
269.44
330.91
335.33
314.90
50.6
78.4
95.1
99.3
90.4
47.0
76.0
93.3
94.6
88.8
166.72
257.02
356.45
369.97
316.42
187.90
272.45
392.81
414.18
354.21
53.0
53.3
82.1
113.9
118.2
101.1
76.8
110.8
116.8
99.9
325.44
510.08
474.45
438.32
361.92
530.41
550.13
480.74
103.9
162.9
151.5
140.0
102.1
149.6
155.2
135.6
154.00
188.14
-
-
176.76
187.30
226.13
300.00
-
209.58
49.2
60.1
56.5
52.8
63.8
84.6
159.91
271.48
343.04
321.44
313.07
171.26
304.20
383.30
367.79
354.54
51.1
86.7
109.6
102.7
100.0
48.3
85.8
108.1
103.7
100.0
More than 21
Students
2006, 2nd quarter
Source: own elaboration based on the LFS data
Outcomes of an econometric model
59.1
Brain drain or brain waste?
Estimated returns to education
PL 02
PL 06
Model
Variable
Education
(years)
Experience
(months)
Sex (female)
.0282
(26.48)
.0005
(10.76)
-.1784 (20.97)
.0019
(3.72)
.0918
(9.95)
-
PL
<04
in UK
PL >04
in UK
NMS7
<04
UK
in
NMS7
>04 in
UK
EU15
UK
in
NMS2 in
UK
.0248
(24.75)
.0006
(14.30)
-.2065
(-23.05)
.0011
(2.04)
.0930
(9.64)
-
.0433
.0200
.0459
.0486
.0485
.0185
(5.94)
(3.04)
(4.94)
(3.33)
(23.01)
(1.76)
.0011
.0062
.0009
.0057
.0010
.0002
(2.35)
(2.58)
(1.55)
(1.15)
(10.15)
(0.17)
-.3352
-.1701
-.2297
-.2138
-.1710
-.2180
(-6.49)
(-4.74)
(-3.06)
(-2.72)
(-11.73)
(-2.65)
Age
-.0032
.0042
-.0001
.0020
.0030
-.0095
(-1.05)
(1.44)
(-0.04)
(0.43)
(3.65)
(-1.87)
Marital status
.0488
.0366
.3790
-.0042
.1172
.2335
(partner)
(0.85)
(1.09)
(0.51)
(-0.04)
(7.37)
(1.93)
UK citizenship
-.0572
.1035
.0368
.1664
.2301
(-0.53)
(3.76)
(2.10)
(4.32)
(1.33)
Full time work
.7305
.7533
.9701
.6425
.7632
.7546
.8855
.8250
(33.01)
(31.16)
(14.70)
(7.58)
(8.74)
(4.92)
(40.87)
(7.33)
Student
-.2451
-.0938
-.5190
.5119
-.7677
-.4744
-.4885
-.4871
(-10.41)
(-4.50)
(-3.56)
(2.29)
(-2.97)
(-1.00)
(-9.96)
(-2.90)
Private sector
-.0681
-.0810
-.1735
-.0383
.0820
-.2811
-.0305
-.4190
(-6.66)
(-6.61)
(-1.73)
(-1.88)
(0.86)
(-1.30)
(-2.13)
(-3.14)
CDE sector
.0866
.1185
-.5337
.0309
.2059
-.0760
.0110
.3264
(3.54)
(4.14)
(-1.74)
(0.36)
(1.67)
(-0.51)
(0.15)
(1.86)
F sector
.0896
.1146
-.5374
.1702
.1805
-.0002
.5694
(3.16)
(3.45)
(-1.74)
(1.66)
(1.22)
(-0.00)
(3.03)
GHI sector
.0551
.0896
-.6651
.0156
-.0212
-.0527
-.1166
.3247
(2.20)
(3.07)
(-2.23)
(0.18)
(-0.17)
(-0.33)
(-1.60)
(2.06)
JK sector
.1592
.1833
-.3925
-.0112
.2260
.1763
.1216
.7306
(5.34)
(5.51)
(-1.29)
(-0.12)
(1.41)
(0.84)
(1.65)
(3.70)
LMNO sector
.0193
.1183
-.6031
-.0388
.0984
-.4563
-.0610
.2864
(0.75)
(3.90)
(-2.01)
(-0.42)
(0.71)
(-1.42)
(-0.84)
(1.87)
P sector
-.2992
-0.278
-.9346
-.4722
-.4313
-.2181
-.3983
(-1.87)
(-0.11)
(-2.57)
(-4.16)
(-2.41)
(-0.86)
(-3.15)
London/
.1540
.1670
.2128
.1135
.1711
-.3221
.1809
.1259
Warsaw
(16.79)
(16.31)
(3.93)
(1.53)
(2.48)
(-2.15)
(10.31)
(1.59)
Constant
4.21
4.3079
4.8638
4.3305
3.9722
4.3145
4.0468
4.6650
(98.33)
(95.40)
(13.74)
(23.59)
(14.56)
(9.84)
(47.05)
(21.26)
R2
0.3724
0.3990
0.6774
0.4023
0.5820
0.6774
0.5486
0.6596
Sample size
10177
9600
281
388
275
281
5408
127
1) In parentheses t-statistics calculated for robust standard errors
2) The reference groups for the respective variables are: male, without partner, non-UK citizen,
working part-time, not a student, employed in the AB, public sectors, and working outside of the
capital city. Data between the Polish LFS and UK LFS is not fully comparable.
Source: Own evaluation based on UK LFS (2000-2007) and Polish LFS (second quarters 2002 and 2006)
Labour market impacts
Case study 3: ‘crowding-out’ hypothesis and post-accession
mobility from Poland
Is an outflow needed to complete the modernisation of
economy? (Layard et al. 1994)
Postulates:
Population surpluses hamper or preclude the modernisation of
peripheries outflow or ‘redundant’ people constitute one of
major premises that undermine the completion of
modernisation process
Poland still remains a country with a large migration potential
number of people, their spatial distribution and human
capital characteristics do not match the needs of the labour
market
Until very recently the outflow from Poland had little impact
on its population and economy due to positive natural
increase the population on Poland was continuously on the rise,
outflow from Poland was limited to rather narrow groups (impact of
migrant networks)
Recent outflow (due to its scale and characteristics) gives a chance
for an outflow of redundant population (from rural areas and small
towns) and serious labour market reforms
Selectivity patterns of migration from Poland
Socio-demographic profile of Polish post-accession
migrants by destination country, selected features, in %
% males
70%
60%
50%
40%
% welfare benefit
% aged 20-29
30%
20%
10%
0%
% large cities inhabit.
% University graduates
% rural inhabitants
IE, SE, UK
other
Source: Fihel and Kaczmarczyk 2008
Structural features of recent migration from
Poland
Post-accession migration: more regular or legal than
irregular or clandestine, more of a long-term duration
than circular, more ‘individualistic’ than related to
household strategies, more ‘masculine’ than ‘feminine’
BUT:
At least two structurally different patterns of migration
observed:
Migration of the ‘youth’ persons under 35, mostly
without children, often single or in informal relationships,
relatively well educated, language and legality as an
important factor, UK and Ireland as leading destinations.
Migration of the ‘older’ persons with previous migration
experiences, no language skills, more ‘traditional’
destinations: Germany, Italy, Spain.
Case study 2: ‘crowding-out’ hypothesis and post-accession
mobility…
Selectivity indexes (SI) for post-secondary and vocational education after EU accession
(all migrants), by categories of settlement (migrants’ places of residence prior to
migration)
Category of settlement
Town, 100,000 or more
inhabitants
Post-secondary
0.27
Vocational
0.18
Town, up to 100,000 inhabitants
0.55
0.18
Village
1.10
0.46
All settlements
0.42
0.30
Source: Kaczmarczyk and Okólski, 2008.
Potential impacts - remittances
Scale of the phenomenon:
Registered remittances:
1990 $31.1 billion
2000 $76.8 billion
2007 $240 billion
Registered remittances are close to tripling the value of
ODA (Official Development Assistance) (Glytsos 2002)
Remittances as portion of
the GDP, 2004
Remittances as share of
export, 2003
Potential impacts - remittances
Macro effects:
Remittances and GDP, export revenues, costs of import,
negative balance of payments
General conclusion: in some cases migrant remittances may
constitute a large and important source of capital for
developing countries (e.g. Moldova, Albania, former
Yugoslavia)
But:
have only limited positive long-term effects on economic
growth and development in sending countries
migration fail to increase production and investments
it has often negative consequences: inflationary pressure,
undesirable currency appreciation, disincentives for domestic
savings, private consumption of imported goods etc.
Potential impacts - remittances
Indirect effects
they result from expenditures by migrant households
if households spend remittances on goods and services
produced within given economy, than remittances generate
positive, multiplier effects.
Adelman and Taylor: for every dollar sent or brought into
Mexico, GNP increases by an amount between $2.69 and $3.17,
depending on household group
Cumulated macro effects:
South Korea: between 3 and 7% of 1976-1981 GNP growth may
be attributed to migrant remittances (directly and indirectly)
Bangladesh: money remitted to Bangladesh in 1983 gave rise to
an additional final demand of 351 million USD, which generated
almost 600,000 jobs; through expenditures on current
consumption, housing, education each migrant created an average
of three job.
General comment: impact of remittances strongly depends
on structures in which they become embedded.
Potential impacts - remittances
Evolution: Structure agency: Migration as a survival
strategy?
Migration as risk diversification strategy
Remittances as a means towards consumption smoothing
Outcomes of surveys on the local and regional scale:
bulk of remittances are spent on consumption: everyday
consumption often absorb 90% or more of remittances
Rempel and Lobdell (1978): 50 remittance-use studies (ILO
survey) – conclusion: most of the money remitted is used for
increased consumption, education and better housing;
Mexico: over 90% of remittances and about 70% of savings were
spent on consumption, primarily on food, clothing, consumer
goods and housing
remittances as a source of capital needed to finance basic
needs – necessary to survive
remittances are targeted overwhelmingly to housing,
purchase of other real property, very little is left for
productive investment.
Potential impacts - remittances
Controversies – impact on investment activity?
Should we really expect an investment effect of remittances?
Poor public services and infrastructure plus market failures
opportunities’ structure…
A lack of well-functioning factor markets (rural credit market!)
migrants as a kind of financial intermediaries.
Massey (1990): to ‘expect migrants to be proficient at turning
savings into production is unrealistic. Migration will have larger
effect when local institutions exist to gather savings and make
them available for producers’.
And:
Massey and Durand found that always under 50% was spent on
production but in many places the effect on production was
substantial
Remittances enabled many communities to overcome capital
constraints and finance public goods (parks, churches, shools)
Remittances have been critical to the capitalization of migrant
owned businesses. E.g. 31% of migrants in Guadalajara used
remittances from USA to set up a business; sometimes the share
of companies granted by immigrants is higher than 60%
Potential impacts - remittances
Migration and inequality:
A study covering 74 low and middle income countries (Adams
and Page): positive correlation between remittances and
poverty alleviation a 10% increase in the share of
remittances in country GDP would lead to 1.2 percentage point
decrease in the persons living on less than 1 USD per day and
also reduce the depth of poverty.
Stark, Taylor and Yitzhaki (1986): migration initially entails
costs and risks - pioneer migrants tend to come from
households at the upper-middle or top of the income
distribution income sent home will likely widen income
inequalities. Over time migrants win access to migrant labour
markets, due to networks migration is less and less selective –
migration may have an equalizing effect on income distribution
positive impact on equality in the long-term.
Additional effects: internal vs. international mobility; structure
of migration.
Potential impacts – social remittances
Socio-cultural impacts of migration:
impact on socio-economic structures in sending communities:
hierarchy, prestige… consequences for social, class and ethnic hierarchies
impact on traditional care arrangements
impact on families structure
impact on gender relations but rather limited, process of ‘selective
asssimilation’ (Parrado and Flippen 2005)
impact on modes of behaviour e.g. influence on life rhythm
and seasonality in Morocco (from traditional harvest seasons to
summer holidays of migrants – de Haas 2009)
impact on cultural structures culture of migration
flow of ideas, norms etc. e.g. enterpreneurship see post2004 migration from the NMS.
Potential impacts – sending countries
Case study 4: Migration instead of development?
The Philippines (de Haas 2009)
Since 1970s governments have encouraged emigration of
workers
Active role of the state Philippine Overseas Employment
Administration, the Overseas Workers’ Welfare Administration,
the Commission on Filipino Overseas
One of the biggest labour exporter: 8 million Filipinos staying
abroad, 10% of the population
Culture of migration even 10-12 year-old children do expect to
leave the country
Remittances (2006): $12.8 billion, around 12% of the GDP
Migrants as ‘the countries new heroes’ (bagong bayani)
But:
Little sign of development impacts (compare to Korea, Thailand,
Malaysia)
Growing dependence on labour export and remittances.
Potential impacts – receiving countries
Public debate on the impact of immigration on the
labour market:
immigrants compete with native workers on the labour market
influx of foreign workers reduces the number of jobs available
to native workers, and thus increases the risk of
unemployment
immigrants contribute to the reduction of wage level and thus
make the income situation of the receiving society worse
immigrants may be burden to the welfare system.
Immigration and labour market
Homogenous, unregulated labour market
w
LF
LF’
w*
w’
LD
L
Immigration and the labour market
But:
1) Foreign and native workers may be
complementary – increase in the number of
foreign workers may raise the demand for
indigenous labour.
2) Labour market should not be described in
competitive terms as perfectly competitive and
homogenous:
-
rigidities – e.g. impact of trade unions
-
segmentation of the labour market – foreigners
concentrate in the secondary sector with relatively low
vertical mobility.
Immigration and labour market
Heterogenous labour market – native labour force
w
w
LF
w’
LF
w’
w*
w*
LD’
LD’
LD
LD
L
L
Qualified workers
Unqualified workers
Immigration and labour market
Heterogenous labour market - secondary sector (with large
share of foreigners)
w
LF
LF’
w*
w’
LD
L
Potential impacts – receiving countries
Economic theory?
Only in the model of perfectly competitive labour market, with
homogenous labour, the inflow of foreigners may affect
negatively situation on the labour market
The outcome strongly depends on the structure of labour
markets, capital/labour ratios, speed of adjustment and
immigrants’ characteristics
Key issue: are foreigners complements or substitutes in
relation to the natives?
Empirical verification is needed…
Potential impacts – receiving countries
Evidence:
US labour market:
Borjas 1987, Grossman 1982: the impact of immigrants on
the employment opportunities of native workers was very
small, and similarly, the flexibility of wages was also small
Papademetriou et al. 1989: the impact of immigration has
been positive, inflow of foreign labour not only improved the
competitiveness of American economy but it also saved many
industries and sectors of the economy
Card 2001: the impact of immigration on the situation on the
labour market was very low, negative effects were noted only
for young and poorly educated people and that solely in a few
cities, where the share of immigrants in the total population
was particularly big.
Potential impacts – receiving countries
Evidence:
EU labour markets:
Bauer and Zimmermann 1997: simulation for Germany with
assumption that labour market is heterogenous and the inflow of
immigrants may include both low and highly skilled workers
Outcomes:
inflow of low skilled immigrants on a scale of 10% of the labour
force leads to the reduction of wages of the equivalent group of
native workers by nearly 3%. If wage rates are flexible enough
the effect of increased unemployment will not appear (the wage
rate fills a regulatory role on the labour market). The wages of
qualified workers will grow by about 2.5%;
effects depend on the skills structure of immigrants but the net
gain for German economy as a whole is positive in both cases;
in the case of inflow of low skilled workers the gain is at the level
of 0.8% of national income, and if in the case of highly skilled the
gain is at the level of 0.24% of national income.
Potential impacts – receiving countries
The macroeconomic impact of migration from the NMS-8, 2004-2007
GDP
Change of
labour force
Short-run
GDP per capita
Long-run
Short-run
Long-run
Factor income
per native
Short-run
Long-run
Unemployment
Short-run
Long-run
Wages
Short-run
Long-run
Changes in per cent (unemployment rate: changes in percentage points)
AT
BE
DE
DK
ES
FI
FR
GR
IE
IT
LU
NL
SE
UK
0.42
0.22
0.10
0.23
0.19
0.09
0.01
-0.01
4.87
0.11
1.00
0.14
0.38
1.28
0.31
0.11
0.04
0.13
0.03
0.03
0.01
0.00
0.80
0.04
0.81
0.09
0.25
0.50
0.34
0.17
0.10
0.20
0.11
0.08
0.01
-0.01
2.93
0.08
1.13
0.12
0.33
0.89
0.00
-0.08
-0.03
-0.08
-0.08
-0.06
0.00
0.01
-2.07
-0.03
0.23
-0.03
-0.01
-0.28
0.02
-0.02
0.02
-0.01
-0.01
-0.01
0.00
0.00
-0.02
0.01
0.55
-0.01
0.07
0.10
0.12
0.01
-0.01
0.00
-0.04
-0.02
0.00
0.00
-0.77
0.00
0.34
0.02
0.05
-0.05
0.15
0.07
0.04
0.07
0.04
0.04
0.00
-0.01
1.31
0.04
0.65
0.04
0.12
0.34
0.02
0.07
0.03
0.02
0.05
0.03
0.00
0.00
0.87
0.02
0.12
0.02
0.05
0.21
0.02
0.05
0.01
0.00
0.02
0.01
0.00
0.00
0.37
0.01
0.05
0.01
0.03
0.11
-0.02
-0.04
-0.03
-0.05
-0.04
-0.03
0.00
0.00
-1.61
-0.03
-0.25
-0.02
-0.06
-0.29
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
CZ
EE
HU
LT
LV
PL
SI
SK
-0.08
-0.21
-0.44
-1.14
-0.43
-1.77
0.26
-1.34
-0.07
-0.09
-0.34
-0.55
-0.26
-0.88
0.15
-0.53
-0.11
-0.19
-0.49
-1.15
-0.46
-1.94
0.21
-1.51
0.01
0.12
0.10
0.61
0.17
0.90
-0.10
0.82
-0.03
0.02
-0.04
-0.01
-0.03
-0.18
-0.05
-0.18
0.01
0.12
0.10
0.61
0.17
0.90
-0.10
0.82
-0.03
0.02
-0.04
-0.01
-0.03
-0.18
-0.05
-0.18
-0.02
-0.04
-0.04
-0.32
-0.09
-0.59
0.02
-0.55
0.00
0.00
0.00
-0.01
0.00
0.03
0.00
0.00
0.03
0.06
0.11
0.31
0.12
0.43
-0.04
0.43
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
EU-151)
NMS-8
Total
0.36
-1.16
0.11
0.13
-0.52
0.11
0.26
-1.10
0.20
-0.09
0.65
0.11
0.03
0.05
0.20
-0.02
0.65
0.16
0.10
0.05
0.25
0.06
-0.42
-0.03
0.02
-0.02
0.00
-0.09
0.25
-0.07
0.00
0.00
0.00
1) Without Portugal.
Source: Own estimates and simulation, see text.
Source: Brücker et al. 2009
Potential impacts – receiving countries
Summary:
The impact of immigrants on employment is weak or ambiguous
In western Europe there are at least 3 categories of jobs where
foreigners cannot be easily replace by natives:
Dirty, difficult and dangerous (3-D) jobs
Services
Low-skilled jobs in underground economy – estimated to be
about 10-20 million workers in EU
Does immigrants raise welfare costs?
UK: 1999-2000 – migrants contributed GBP 2.5 billion more in
taxes than they received in benefits
Germany – without the contribution from immigrants who came in
1988-1991 the German social welfare system would have
collapsed
structure of the welfare system matters
Conclusions
Migration has a significant development potential
Real impacts of migration strongly depend on contextual
issues migration impacts tend to be strongly heterogenous
Migration alone cannot remove structural development
constraints and trigger-off development, particularly in
unattractive environments.
However:
Recent barriers to mobility seem to:
increase selectivity of migration,
put migrants in a highly handicaped position (particularly
illegal ones)
have negative impact on development potential of migration.
Policy recommendations
HDR 2009 Policies to enhance human development
outcomes:
Liberalizing and simplifying regular channels that allow
people to seek work abroad (with emphasis on low-skilled
workers’ mobility, mechanisms of circular mobility)
Ensuring basis rights for migrants (earned naturalisation as
an element of the core package, legalise instead of penalise!)
Reducing transaction costs associated with migration
(intermediaries?, role of networks and other institutions)
Improving outcomes for migrants and destination
communities (allow people to work! But: recession,
discrimination, xenophobia…)
Enabling benefits from internal mobility (how to address
regional differences?)
Making mobility an integral part of national development
strategies mobility to be seen as a component of human
development rather than an isolated cause or effect of it
migration for development and not instead of
development.
Labour mobility agenda for development?
Michael Clemens (2010) and three „big questions”:
Can migration do much to help development?
Must people at destinations suffer?
Is migration harmful for receiving countries and societies?