Migrants from East/Central Europe: a new settlement pattern?

Mike Coombes CURDS Newcastle University

Acknowledgements

CURDS colleagues Tony Champion Simon RaybouldAlison Stenning Ranald Richardson Cheryl Conway Stuart Dawley Liz Dixon

Funding *preliminary results, not to be quoted* Office of the Deputy Prime Minister (New Horizons)

Data access Home Office

Structure of the talk

• Which migrants are the focus of the study?

• Outline of the statistical analysis….by area

• Establish ‘before’ pattern from Census data

• What can we know about the A8 migrants?

• CURDS results: A8 migrant LQs

• Overview of conclusions

Which migrants is the study about?

Migrants from the “A8”countries: 8 former eastern bloc

countries which joined the EU in 2003 (the 2 other

countries joining at the same time were Malta and

Cyprus and they had different immigration status)

Estimates of A8 migrant numbers (made before 2003)

proved to be far too low because the calculations

did not reckon on other western European countries

deciding not to admit A8 labour migrants

A8 migrants registered in the UK have all gained work

Migrant numbers reflect country size

Czech Rep

Estonia

Hungary

Latvia

Lithuania

Poland

Slovakia

Slovenia

The Observer Sunday April 23, 2006Heather Stewart, economics correspondent

Migrants boost UK's growth Eastern Europe migrants have brought powerful benefits to Britain's economy since 10 new countries joined the European Union in 2004, according to research by the Ernst & Young Item Club. Item, which uses the Treasury's forecasting model, says interest rates are half a percentage point lower than they would have been without the influx of low-cost workers From the new members of the EU club. It calculates that economic growth will be boosted by 0.2 per cent this year, and 0.4 per cent in 2007.

What of local impacts/implications?

“…people make places (the influx of new residents is

part of the construction of a new local uniqueness) …

bound into wider sets of social relations”

Doreen Massey & Pat Jess (1995 p.221)

A place in the world? Places, culture and

globalisation Oxford University Press

CURDS study for ODPM included both the summary

statistical analysis (as below), plus a brief look at the

detailed outcomes in Newcastle and Peterborough

Outline of statistical analysis by areaFor the total migrant flow, and sub-groups by

nationality / job type / with(out) dependents

~ place each migrant in a local authority (LA)

~ calculate location quotients (LQs): ratio produced by dividing LA share of group by LA share of jobs)

~ summarise these to indicate clustering (sum overall LAs, absolute differences between LQs and 1.0)

~ correlate them vs. LAs’ employment rates

and vs. LAs’ Urbanisation Index values

~ compare vs. earlier migrant groups’ patterns

~ summarise within a simple classification

Attraction of tighter labour markets?

Establish ‘before’ pattern (in 2001)

Where were there already people who were born in

east/central Europe (ECE)? (new ECE migrants

may be attracted to these areas through social

relations or due to unique local facilities)

What of more recent migrant groups who may be more

similar to the ECE migrants? (new ECE migrants

known to be mainly young and unattached, and may

be well qualified and staying relatively short periods)

E.Europe-born in 2001: ‘county’ LQs [ red = high blue = low ]

Selected comparator country-of-birth (CoB) group 2001 location indicators: clustering/urbanisation/employment%

-0.25

-0.15

-0.05

0.05

0.15

0.25

0.35

0.45

co

rre

lati

on

s (

ba

rs)

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

clu

ste

rin

g

Urban correlation Employment rate correlation clustering (LA)

employment rate correlation

-0.10 0.15urbanisation correlation

negative neutral positive

urban-concentrated

?   strong0.35

Bangladesh Pakistan

India Greece Turkey

 

scattered/dispersed

? slightPoland(pre-A8)

BalticStates(pre-A8)

Cyprus Spain Hong Kong

0.08

 

employ-ment linked neutral

or negativeAustralia

South Africa

BOLD = clustered @ > .8

Typology of selected CoB groups

Summary classification: 3 key types

Type Urban-isation

Employ-ment rate

Clust-ering

CoB examples

urban con-centrated

high low high South Asian groups; Turkey; Greece

employ-mentlinked

low high low Australia; S. Africa

scattered/dispersed

medium medium mixed Hong Kong; Cyprus; Spain; Baltic States (pre-A8); Poland (pre-A8)

What is known about A8 migrants?

There is no data on the ‘stock’ of A8 migrants who are

in the UK at 1 point in time (ie. a Census equivalent)

Data available is from the Worker Registration Scheme

(WRS) and measures the ‘flow’ arriving to take jobs

There is no information on how long people stayed and

so many in the WRS data may have already left and,

in fact, may be in the data again having then returned

Some migrants from A8 countries are not in the WRS

(eg. they are self-employed or working illegally)

A8 migrants in WRS (by end 2005)

345,000 applicants (up to 30% in UK before May 2004)

83% of registered workers aged between 18 and 34

97% have no dependants living with them in the UK

57% male

seasonal labour – probably in agriculture-related and

hospitality sectors – suggested by the summer peak

each year has seen a higher peak than the one before

Concentration on London reducingWRS applications, by calendar quarter, May 2004 to September 2005, by region

(arranged by total applications for 17-month period)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

Lond

on

Anglia

Midl

ands

Centra

l

South

Wes

t

South

Eas

t

Scotla

nd

North

Wes

t

North

Eas

t

North

ern

Irelan

d

Wale

s

Not st

ated

Q2 2004 Q3 2004 Q4 2004 Q1 2005 Q2 2005 Q3 2005

WRS data: records of gate-keeping

CURDS analyses cover WRS data up to end June 2005

Postcode District (eg. PE4) of registration address

Gender Date of Birth Nationality

Outcome of Application

Number of Dependents (by whether under 16)

NOTHING on qualifications

Job Title & Job Description [not standard categories]

for example:other legal occupation – poultry catchermagician – production workerbarrister – waiter

Job types identified by CURDS

A8 job typen

(England)%

totalmanagers and (semi-)professional workers 3374 1.8

other office-based workers 8182 4.4

hospitality/leisure/retail/wholesale workers 57178 30.4

personal service and domestic workers 18232 9.7

mechanics and transport or construction workers 15159 8.1

manufacturing/process/other low skilled workers 57027 30.3

agricultural and food processing workers 28806 15.3

CURDS results: A8 migrant LQs

Total n LQ Boston 2645 12.2 E. Cambridgeshire 1694 8.1 S. Holland 1959 7.0 King's Lynn & W. Norfolk 2756 5.8 Peterborough 3999 5.3 Fenland 1312 4.9 Luton 3275 4.6 Northampton 4123 4.4 Arun 1620 4.2 Herefordshire 2690 4.1

A8 inflow to English LAs: top 10 LQs(‘best fit’ of postcode districts to LAs)

(2645 migrants to Boston represent a share of the total A8 migrant flow to England which is 12.2 times higher than Boston’s share of all 2001 jobs in the country)

Agriculture and food processing

Hospitality retail and leisure workers

Manufacturing/processing workers

A8 country group location indicators: clustering/urbanisation/employment%

-0.25

-0.15

-0.05

0.05

0.15

0.25

0.35

0.45

TotalA

8

women

Poland

Lithuan

ia

Slova

kia

Latvi

a

Czech

Rep

Hungary

Estonia

Slove

nia

co

rre

lati

on

s (

ba

rs)

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

clu

ste

rin

g (

lin

e)

Urban correlation Employment rate correlation clustering (LA)

Summary of results from analysisemployment rate correlation

-0.10 0.15 urbanisation correlationNegative neutral Positive

urban-concentrated

?  

strong0.35

   

 

scattered/dispersed

?

slightCzech Republic Slovenia 0.08

 

all A8 in-migrants all A8

women Poland

Baltic States

Hungary Slovakia

employment-linked neutral

or negative

 

BOLD = clustered @ > .8

Overview of conclusionsA new settlement pattern? Most similar to people from:

Baltic States / Poland (pre-2001 in-migrants)

Cyprus (‘A#9’) and Spain (previous Accession round)

Hong Kong (classic example of ‘scattered/dispersed’)

...BUT… less urban-focussed than most of these

more ‘white-collar’ workers more focussed on cities

Methodological issues and/or future research needs

Findings robust despite analysing flow and not stock?

Other data sources (NI records, LFS…?) allow analyses

of qualifications/pay/…? ABOVE ALL length of stay