The statistical analysis of longer term historical trends in migration in South Eastern Europe since the 1950s Attila Melegh Demographic Research Institute.

The statistical analysis of longer term historical trends in migration in South Eastern Europe since the 1950sAttila MeleghDemographic Research InstituteHungarian Central Statistical Office

www.seemig.eu

Managing Migration and its Effects in the SEE countries

SEEMIGManaging Migration and its Effects in SEE –

Transnational Actions Towards Evidence Based Strategies

www.seemig.eu

The project is funded under the 3 rd call of the South-East Europe Programme.

Project duration: June 2012 – November 2014

Which countries?

www.seemig.eu

Managing Migration and its Effects in the SEE countries

Universities

Statistical Offices

Research Institutes

Local governments

•University of Vienna (AT) •University of Trento (IT)

•National Statistical Institute of the Republic of Bulgaria•Hungarian Central Statistical Office•Statistical Office of the Republic of Serbia•Institute of Informatics and Statistics (INFOSTAT, Slovakia)•Demographic Research Institute (Hungary)•Romanian Research Institute for Research on National Minorities (Romania)•Institute of Social Sciences (Serbia)•Institute for Economic Research (Slovenia)•Scientific Research Centre of the Slovenian Academy of Sciences and Arts Slovenia

•Municipality of Pécs (Hungary)•Harghita County Council (Romania)•Municipality of Sfântu Gheorghe (Romania)•District administration of Montana (Bulgaria)•Maribor Development Agency (Slovenia)•Town council Turčianske Teplice (Slovakia)•Municipality of Kanjiža (Serbia)

COUNTRIES

www.seemig.eu

Managing Migration and its Effects in the SEE countries

From what activities do we generate ideas?• Data system analysis

• Action plans

• Master classes

• Foresight exercise

• Population projections

• Migration policy documents

• Target is a relevant policy document on a national level

SEEMIG strategy background

www.seemig.eu

Managing Migration and its Effects in the SEE countries

Transnational strategyPolicy area Policy Recommendations

Policy area 1: Harmonization of data collection

- Harmonization of definitions and concepts - Continuation of mainstreaming of migration data - Harmonization of address registration

Policy area 2: Enhancement of data collection methodologies

- Improving the methodology of making flow estimates out of global stock data, transnational use of big data

- Improving the methodology of making emigrant stock estimates out of global migration flow and migrant stock data

- Improvement and integration of administrative data- systems Policy area 3: Increase of transnational partnerships and cooperation

- Establishing transnational dialogues between sending and receiving communities

- Collection and exchange of data on daily cross-border migration of labour between countries

- Improvement of transnational databases Policy area 4: Increase data collection on the local level

- Enhancement of local data development (top- down from EU level)

- Launching local surveys and identification of sensitive groups on transnational level

- Enhancement of institutional capacity of public administrations and public services & new forms of cooperation among different actors on local level

Problems and questions•What use we can make of new global

historical-statistical sources related to migration and its context?

•How to understand longer term developments in migratory patterns and societal links globally and in one region?

•What theories we can apply which can guide our research? How we can reflect on existing theories

•How to proceed in the future and what to suggest?

Major statistical challenge: Migration as a longer term linkage• Generally: It is observed individually and nationally:

major issues of comparability, definitions in space and time. Register problem, emigration not recorded

• It is not just an individual level phenomenon and it is cross national by definition. Just a proper global and historical structural perspective helps understanding it.

• Cumulative and multiple level causation. • It is embedded: family members, networks,

agencies, labor market processes and related social institutions, historical migratory links,

• Caused by, and plays out, and reinforces global inequalities

1. United nations: world population prospects, net migration rates, global scope

2. Net migration residuals. Net migration: the number of immigrants minus the number of emigrants over a period, divided by the person-years lived by the population of the receiving country over that period. It is expressed as the net number of migrants per 1,000 people. For most countries the figure is based on estimates of net international migration derived as the difference between overall population change and natural increase..

3. Problems of enumeration, not a real category. Net flows.

4. Longer term development in a comparative way. Regional analysis

• Census problems: not there but counted in the census (Romania)

• If controlled by other historical estimates that Hungary seems to be zero or negative since 2008

Global statistics: net migration flows

Estimated global migration flows

Wittgenstein Centre Method

• Use of World Bank matrices (Abel)

• Europe is not the most important actorSEEMIG not a big global player

• increase of migration volume during 2000s (esp. inflows to Italy)

• flows from/to SEEMIG region concentrated within Europe

• This is not utilized according to merits

Source: Abel & Sander 2014Illustration: Sander & Bauer.

No overall pattern

-30

-25

-20

-15

-10

-5

0

5

10

Number

of

migrants

per

1000

Year

Net migration in selected countries1950-2010, WPP 2012

Austria

Bulgaria

Czech Republic

Hungary

Italy

Slovakia

Germany

Romania

Albania

Georgia

Major divergence and path

dependency even across political

regimes

No linear developmentNo migration

transition

Migration theory and change•Migration transition (Zelinsky): teleological

from net emigration to net immigration due to changes in the economic structure.

•Migration cycle: use of various contextual elements: labor market, demographic processes, state actions etc. (Fassmann et al 2013, 2014).

•Migration hump: first low level emigration, then high level and then low level plus immigration. Would be migrants could afford migration.

Migration theory and change• World-system theory or macro historical school.• Dependency, outmigration from previous

agrarian and colonial countries. • There is an idea of change: intrusion and “great

transformation”• What about state socialism and the move toward

capitalist semi-periphery from socialist semi periphery? Böröcz: remittance dependency after the collapse of state-socialism.

• What about path dependency?• We need to look for further ideas.

Relative economic inequality between SEE and major migratory targets

South Eastern Europe and global inequalities: long term perspective• Eastern and South Eastern Europe has not really

changed its position for the last 100 and 150 years even across political regimes. Use of proxies when data is not available (Good and Tongshou 1999)

• Global comparative and historical statistics: Maddison database. Use of 1990 Geary-Khamis USD and rely on purchasing power parities rather than exchange rates. Projects back and forward these 1990 levels of GDP with indexes checked by specialists

• The differentials are almost the same throughout: makes migration all the time „rational” and makes the already existing links „viable”:

Socialist and capitalist countries

had similar trajectories

Type 1: IncreaseNet Migration over Time, All datapoints in the "Increase" type, five-

year intervals marked by midpoints, 1950-2010Source:World Population Prospects, 2010 revision

R2 = 0,4781

-20,0

-15,0

-10,0

-5,0

0,0

5,0

10,0

15,0

20,0

1940 1950 1960 1970 1980 1990 2000 2010

Time

Pe

rso

n p

er

10

00

Transition model

Economic inequality and transition model

Net Migration rate and GDP/cap difference from world average In Greece 1950-2010, WPP and Maddision databank.

-6

-4

-2

0

2

4

6

8

10

1950-1955 1955-1960 1960-1965 1965-1970 1970-1975 1975-1980 1980-1985 1985-1990 1990-1995 1995-2000 2000-2005 2005-2010

Time

Pe

rso

n p

er

10

00

-20,00%

0,00%

20,00%

40,00%

60,00%

80,00%

100,00%

120,00%

% d

iffe

ren

ce

, G

ery

-Kh

am

is 1

99

0 d

oll

ar

Net migration rate GDP per cap difference

Net migration and GDP/capita difference in Bulgaria 1950-2010, WPP, 2010, Maddison

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1950-1955

1955-1960

1960-1965

1965-1970

1970-1975

1975-1980

1980-1985

1985-1990

1990-1995

1995-2000

2000-2005

2005-2010

Time

Per

son

per

100

0

-20,00%

-10,00%

0,00%

10,00%

20,00%

30,00%

40,00%

50,00%

% d

iffe

ren

ce f

rom

Wo

rld

A

vera

ge,

Gea

ry K

ham

is, 1

990

US

D

Net migration GDP/cap difference

Linking inequality and migration patterns•Those countries become recently

immigrant, which could shift categories (Austria, Germany, Italy). This can be a key in the migration patterns of the region.

•Institutional change, EU membership and better transportation enhances this.

•Below average countries (poorer semi-periphery) is remaining emigrant or close to an emigrant patterns.

1. Ozden et al, Abel 1960 till 2000, UN matrices since 1990

2. Stocks by country of birth (sometimes foreign citizenship, sometimes ethnicity, sometimes estimated) in pairs, disaggregated by gender

3. Based on censuses but partially estimated. SEE censuses no data or very problematic till the mid 1990s

4. Hungary no census question. Soviet Union ethnicity.

5. Very problematic data for some countries even within SEE. Need to be controlled nationally.

6. Immigrant stocks are not okay till the 1990s

7. Most key target countries (USA, Canada, Germany, Australia have usable censuses)

World Bank and UN migration matrices

External outward links: SEE countries and major (top 5) destination countries (Country of birth stock, WB matrices)

Receiving centers (at least 3): USA, GermanyCanadaTurkeyAustraliaFranceArgentinaHungary

Russia/SU?

Source: WB, 2013Illustration: Ági Tátrai-Pap.

Semi-periphery countries

also play a role

SEE countries and their major destination countries (Country of birth stock, WB matrices)

Russia/SU?

Source: WB, 2013Illustration: Ági Tátrai-Pap.

Receiving centers (at least 3): GermanyUSA, CanadaTurkeyAustraliaAustriaFranceIsrael

SEE countries and their major destination countries (Country of birth stock, WB matrices)

Russia/SU?

Source: WB, 2013Illustration: Ági Tátrai-Pap.

Receiving centers (at least 3): GermanyUSA, CanadaTurkeyAustraliaAustriaIsraelSwitzerland

SEE countries and their major destination countries (Country of birth stock, UN matrices)

Source: UN, 2013Illustration: Ági Tátrai-Pap.

Receiving centers (at least 3): GermanyUSA, CanadaAustraliaAustriaItaly

Reduction and Europeanizati

onLoss of semi-

periphery

SEE countries and their major destination countries (Country of birth stock, UN matrices

Source: UN, 2013Illustration: Ági Tátrai-Pap.

Receiving centers (at least 3): GermanyUSA, CanadaAustraliaAustriaItaly

East/West slope

SEE countries and their major destination countries (Country of birth, stock, UN matrices)

Source: UN, 2013Illustration: Ági Tátrai-Pap.

Receiving centers (at least 3): GermanyUSA, CanadaAustriaItalySwitzerlandAustralia

Major sources

Source: un, 2013Illustration: Ági Tátrai-Pap.

Region not united

Major sources

Source: un, 2013Illustration: Ági Tátrai-Pap.

Major sources

Source: un, 2013Illustration: Ági Tátrai-Pap.

Region united andInternal sourcesOften emigration partners send migrants

On these bases what do we learn about migration?•Path dependency and political change is not

so crucial. •State socialism and capitalism and

migration links survive. Resilience of historical connections.

•Global comparative perspective and overall integration of societies

•Outmigration to the ”West” while sources within the region mainly

•Abel (2014) estimated flows: similar observation. Latin American and Eastern Europe are “emptied”. Issues of dependency

Argument•There is much stability in macro economic

structures and related migratory links. •There have been sweeping changes in some

countries concerning net migration, no overall pattern, theory of change is still missing.

•We need to think in terms of not continuous, not homogenous space (some geographic models are to be corrected, new models created)

•We need to think in terms of pairs, matrices even in the economy, not just migration

•Stable migration links are to be studied carefully (Cost project)

Net migration rate and GDP/cap difference from the world average, in Hungary between 1950–

2010

Pair differences and ethnic links

Net migration flow and GDP per capita ratios

between Germany and Hungary, 1954–1999

. Immigration from Romania to Hungary 1995–2005

Thanks

[email protected]