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Migration hump - Human Development Reports

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Migration hump - Human Development Reports Powered By Docstoc
					Migration transitions and the
     migration hump
 A theoretical inquiry and empirical test

               Hein de Haas
            hein.dehaas@qeh.ox.ac.uk
                www.imi.ox.ac.uk
                   The core issue
• Will development in poor countries lead to less migration ?


• The relation between development and net out-migration is
  non-linear.


• Human development leads to increased emigration in the short
  to medium term.


• Development is associated with generally higher levels of
  mobility
                           Background
• Concerns on (regular and irregular) migration of (low) skilled
  migrants from poor countries to Europe and North America
• Generally perceived as a problem in need of control (in
  contrast to high skilled migration).
• Policy response: Restrictive policies and increasing border
  controls
• However, given the sustained labour market demand,
  migration has not stopped, but rather changed its face
   - Paradox: Increased tendency towards permanent settlement
   - Reliance of de facto labor migrants on other legal migration channels
   - Increasing irregular character of migration
   - Diversifying migration methods and migration routes
       Received Knowledge on
      African Migration to Europe

• Image of “desperate migrants” fleeing African
  misery
• Poverty, war and climate change as the main
  cause
• Alarmist discourse: Europe and North Africa
  risk being “inundated” by “waves” of sub-
  Saharan immigrants (aquatic metaphors)
        Doomsday scenarios
  African hordes are “on their way”
“population pressures, opportunity gradients and conditions of
tyranny will … generate waves of migration towards the North …
Our successors are likely to see mass migration on an
unprecedented scale . . . . it is not difficult to imagine innumerable
immigrants landing on the Northern shores of the Mediterranean
and consisting of the hungry and the desperate.” (King and
Schneider 1991:62-3).

“In their desperation, these people feel they have no alternative but
to seek sanctuary elsewhere, however hazardous the attempt …
Today's stream will surely come to be regarded as a trickle when
compared with the floods that will ensue in decades ahead.” (Myers
2005)
     Shaky empirical foundations
• Media and policy discourses tends to be alarmist and
  anecdotal

• Exaggeration of the actual magnitude; apocalyptic
  representations are highly misleading

• Lack of historical contextualisation of the
  phenomenon (e.g., how “new” is this migration?)

• Lack of theoretical undertanding of the phenomenon
  (is poverty the main cause of migration?)
                 Smart solutions?
The argument: The only way to reduce migration from
poor countries is to address its “root causes” by
promoting development.

    “if you don’t help the third world . . . then you will have these
    poor people in our society” (Prime Minister Rasmussen of
    Denmark, 1995)

    “Broad-based and rapid development will induce potential
    poverty migrants to stay at home” (IOM and UNCTAD, 1996).

    “The problem of immigration, the dramatic consequences of
    which we are witnessing, can only be addressed effectively [. . .]
    through an ambitious and coordinated development [plan] to
    fight its root causes” (José Manuel Barrosso, 2005)
              Smart solutions?
Perceived policy instruments
   – Aid (“Marshall plan for Africa”)
   – Trade
   – Circular migration as a “win-win-win” strategy
     (remittances, co-développement)
   – Return migration and “Diaspora involvement”
                   Practical concerns
Aid
• Limited scope and effectiveness of aid.
• Limited credibility of ‘aid instead of migration’ policies

Trade
• Protectionist policies are often inconsistent with development aims.

Return migration and remittances as a medicine against migration?
• Enforcing return? (“Safeguards which prevent overstaying and ensure
    return are key elements” – EC Council Nov 07)
• Are temporary migrants better ‘development actors’?
• Reinvention of guest workers  Back to the future (Castles)
• Chicken is to egg as development is to migration (Agunias)
              Fundamental concerns
Underlying assumption


       ”Development will lead to less migration”

• Migration as development failure
• Primary cause of migration is poverty and human misery
• Migration is primarily a function of income gaps
• Theoretical foundations: neo-classical, place utility, gravity
  and “push-pull” models
• Development and economic growth (whether through aid,
  trade, remittances, or otherwise) is a substitute to migration
              Fundamental concerns
• Sedentary assumptions are fundamentally flawed (immobility
  as natural state; mobility as an anomaly).
• Non-randomness of real-world migration patterns
• Limited understanding of the relation between development
  and migration: the process of capitalist development is
  conditional on transfer of labour from rural to urban sectors.
• Failure to see migration as integral part of “development”
  rather than as a problem to be solved.
• Casual empirical observations:
   - Micro: most migrants are not amongst the poorest
   - Macro: most non-OECD migrants in OECD countries from middle
     income countries
                                   Origins of African migrants
                                       in OECD countries
                              1,800,000                                                                                                                                  6
                              1,600,000
emigrants in OECD countries




                                                                                                                                                                         5
                              1,400,000




                                                                                                                                                                             % population
                              1,200,000                                                                                                                                  4
                              1,000,000
                                                                                                                                                                         3
                               800,000
                               600,000                                                                                                                                   2
                               400,000
                                                                                                                                                                         1
                               200,000
                                     0                                                                                                                                   0
                                                                              Cote d'Ivoire

                                                                                              Ghana




                                                                                                                                                               Tunisia
                                                  Burkina Faso




                                                                                                                                    Mali

                                                                                                                                           Morocco

                                                                                                                                                     Algeria
                                          Benin




                                                                                                      Nigeria

                                                                                                                Liberia

                                                                                                                          Senegal
                                                                 Cameroon




                                                                            Emigrants                 % Population
    “Non-linear” migration theories
•   Non-linear migration theories conceptualise migration as constituent
    part of more broader processes of economic and demographic change
    and restructuring

•   Spatio-temporal models (long term): Migration systems theory
    (Mabogunje 1970) mobility transition (Zelinsky 1971), further
    elaborated by Skeldon (1997); Hatton and Williamson (1998; 2002);

       Draw links between (parallel) demographic and economic transitions on the
       one hand and migration trends on the other

•   Migration hump (short term) (Martin and Taylor 1996)
•   in wake of trade and other structural political economic reforms
Migration transitions
        Migration and development as
                 substitutes?
•   The relationship between development and net emigration is neither linear
    nor inversely proportional.

•   Social and economic development is generally associated with increased
    mobility and migration because it increases people’s (1) capability and (2)
    aspirations to migrate
•   Beyond a hypothesized threshold level, migration gains its own
    momentum due to “internal processes” (e.g., networks, remittances,
    inequalities)  accelerates migration between specific places and
    countries despite declining wage gaps
•   Capabilities and relative deprivation
•   Only after income gaps narrow significantly and networks disintegrate,
    migration tends to decrease and immigration to increase
         Critique on prior theories
1.   Based on rather narrow definitions of development
2.   Focus on income and demographic variables, and non-
     inclusion of theoretically relevant variables like
     education and political freedoms
3.   Unilinear character (reversibility, relative poverty and
     opportunity gaps)
4.   Questionable causality assumptions (e.g. portrayal of
     demographic factors as “cause”)
5.   Lack of formal empirical tests
                   An empirical test
• Lack of empirical tests, partly due to lack of appropriate data.

• Recent advances
       - OECD database on immigrants and expatriates
       - Bilateral migration matrix created by the University of Sussex and the
          World Bank.


• Aim: To provide a multivariate test for migration transition
  theory by assessing the effect of the levels of economic and
  human development on emigration and immigration patterns.

• Data: Bilateral migration matrix (N=226), World Bank,
  UNDP, Freedom House
                                    Variables
Dependent
• Emigration, Immigration, net migration, migration to OECD countries (proxy values based on
   bilateral stock data – Sussex/WorldBank database)

Main independent variables
• Log GDP per capita PPP
• Fertility (average 20-40 years ago)
• GDP per capita Growth over the last 20 years
• Literacy (and squared value)
• Island state (dummy)
• Border OECD country (dummy)
• Political rights (Freedom House)
• Human Development Index (UNDP)

Considered, but excluded from regression analysis (due to multicollinearity)
• Life expectancy
• School enrolment
30

25

20
                                                  Emigration (%
                                                  population)
15
                                                  Immigration (%
                                                  population)
10

 5

 0
     <2083   2083-     5000-     9032-   >22273
             5000      9032      22273
                 GDP per capita PPP
20

18

16

14

12
                                                         Emigrants
10
                                                         Immigrants
 8

 6

 4

 2

 0
     <2083   2083-5000   5000-9032 9032-22273   >22273
20
18
16
14
12
                                                    P_emi
10
                                                    P_imm
 8
 6
 4
 2
 0
     <2083   2083-5000 5000-9032   9032-   >22273
                                   22273
                     16


                     14

                     12
% total population




                     10

                                                                                             Emigrants
                     8
                                                                                             Immigrants

                     6

                     4

                     2

                     0
                          < .5336   .5336 - .7286   .7286 - .7974   .7974 - .8744   >.8744
                                                     HDI score
10                                                                     25

 8

 6                                                                     20

 4

 2                                                                     15
                                                                            P_NetImm
 0
                                                                            P_Mobile
      < .5336   .5336 - .7286 .7286 - .7974   .7974 - .8744   >.8744
 -2                                                                    10

 -4

 -6                                                                    5

 -8

-10                                                                    0
                     14


                     12


                     10
% total population




                      8


                      6                                                      Migrants to OECD
                                                                             countries

                      4
                                                                             Migrants to non-
                                                                             OECD countries
                      2


                      0
                          < .5336   .5336 -    .7286 -    .7974 -   >.8744
                                     .7286      .7974      .8744
                                              HDI score
16

14

12

10
                                                      Imm_OECD
8
                                                      Imm_NonOECD
6

4

2

0
     < .5336   .5336 -   .7286 -   .7974 -   >.8744
                 .7286    .7974     .8744
                   Standardized Coefficient




-2,5
            -1,5
                                  -0,5
                                                 0,5
                                                           1,5
                                                                     2,5




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           Standardized Coefficient




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                                                             Net migration (% population)




                     y_
                             SQ



                     Is
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            Standardized Coefficient




     -1,5
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                         Is
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                                                               Migration to OECD countries (% population)




                        Bo
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                 Po
                    lR
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                        ht
                                   s
                                                      % of all migrants in OECD countries
                                            (from non-OECD countries, including Turkey and Mexico)

                             2

                           1,5
Standardized Coefficient




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                Conclusions
• First results seem to confirm hypotheses of
  transitional migration theory
• Inclusion of HDI increases correlations and
  statistical significance
• Apparent dominance of economic factors
• Significant, but complex role of literacy and
  schooling (disentangling problem)
• Caveat: Migration transitions neither inevitable
  nor unidirectional (relative deprivation!)
                 Limitations
• Caution is warranted in making claims on causality
  based on limited, cross-sectional data
• Correlations on macro-level do not provide a
  behavioral explanation at the micro-level (e.g.,
  how to measure aspirations?).
• Difficulty of disentangling the effects of different
  components of human development (e.g., unclear
  role of education)
Migration transitions revisited
  Further improvements (ongoing)
Multi-level empirical assessment of macro and
meso (migrant group or country-to-country)
determinants of migration

– Disaggregating analysis to the bilateral level
– Simultaneous assessment of sending and receiving country
  and country-to-country migrant group variables
  (development gaps, role of distance, networks, policies)
– Improved operationalisation of political and policy
  variables
– Analyse time series data to study bilateral migration flows
  instead of stocks
               Policy implications
• Take-off development in the least developed countries is likely
  to lead to take-off emigration (e.g., sub-Saharan Africa)
• Rather than a result of development failure, migration is
  integral part of broader development processes, increasing (1)
  capabilities, (2) aspirations and (3) opportunities to migrate
• Learn to see migration as an integral part of development
  processes rather than as problem to be “solved”
• The limited effects of migration policies compared to more
  general policies affecting human development (macro-
  economic, trade, education, labour market, health).
Migration transitions and the
     migration hump
 A theoretical inquiry and empirical test

               Hein de Haas
            hein.dehaas@qeh.ox.ac.uk
                www.imi.ox.ac.uk
www.worldmapper.org

				
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