Integration Indexes of Third Country Nationals Methodological Contributions Gian Carlo Blangiardo

Integration Indexes of Third Country Nationals Methodological Contributions

Gian Carlo BlangiardoMilano-Bicocca University / Ismu Foundation

EUROPEAN FUND FOR THE INTEGRATION OF THIRD COUNTRY NATIONALSPAN-EUROPEAN CONFERENCE

Work: A Tool for Inclusion or a Reason for Exclusion?

Gian Carlo Blangiardo

to measure and compare integration level among migrant

populations (or sub-populations defined according to some specific features)

The ultimate purpose


The classical macro approach:by

statistical indicators of integration


• European Core Indicators of Migrant Integration• 1) Employment

• Employment rate• Unemployment rate• Activity rate• Over-qualification rate • Self-employment rate

• 2) Education• Highest educational attainment• Share of low-achieving 15-year-olds in reading, mathematics and science• Share of 30–34-year-olds with tertiary educational attainment • Share of early leavers from education and training

• 3) Social inclusion• Median disposable income • At-risk-of-poverty-or-social-exclusion rate (before and after social transfers)• Share of population perceiving their health status as good, fair, or poor• Ratio of property owners to non-property owners

• 4) Active citizenship• Share of immigrants that acquired citizenship• Share of immigrants with permanent or long-term residence, currently only EC long-term residence• Share of immigrants among elected representatives


Unemployment rate of persons aged 25-54 by groups of country of birth, gender and highest level of educational attainment, EU-27, 2008 (%)


Over-qualification rate differences between foreign-born and native-born tertiary educated persons aged 25-54, 2008 (%)


Macro data from statistical sources duly processed to produce indicators

• Labour Force Survey• EU Statistics on Income and Living Conditions• Census data• OECD PISA Survey• Etc.

WE NEED


Main sources

The alternative micro approach: by

individual scores of integration Very apt to investigate differential aspects of the integration corresponding

to local areas or to specific sub-populations& to control the effects of local or targeted policies


Individual data-base from statistical surveys

duly processed• 1) Representative samples of the target

population• 2) A methodology able to assign an integration

score, according to a preliminary definition of integration, to every statistical unit of the sample

WE NEED


a representative samples of the target populations

AS REGARDS METHODS TO HAVE

see:

Baio G., Blangiardo G.C. and Blangiardo M., Centre Sampling Thecnique in Foreign Migration Surveys, Journal of Official Statistics, Vol.27, No.3, 2011, pp.451-465.

And for its numerous applications since early 90s

www.ismu.orgORIM – Regional Observatory for Integration and Multiethnicity


http://www.ismu.org/

HOW TO

assign an integration score, according to a preliminary definition of integration, to every statistical unit of the sample ?

the following steps are required

REMARKIn this example we shall consider the sole topic of labor market integration of TCNs. Anyway a similar the procedure can be followed in order to assign individual integration scores regarding both other specific dimensions (education, social exclusion, etc.) and the integration level as a whole


A new approach to measure integration: by individual integration scores

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

• STEP1 Selection of a set of indicators according to a definition of integration in the labor market

• STEP2 Choice of the variables of sample dataset available to give the requested indicators

• STEP3 Identification of integration scores by processing the frequencies of the sample distribution of the variables selected

• STEP4 Assignment the scores to each statistical unit according to its modality of the variables under consideration

• STEP5 Attribution of the average score of integration at each statistical unit (additive variable to the sample dataset)

• STEP6 Processing the integration score together with structural data (personal features, education, social inclusion, etc.)


7Selection of a set of indicators according to a definition of integration in the labor market

4 dimensions

EmploymentStability &

job security

Net income from work

Over qualification

Source: PerLa Survey 2009 - Percorsi Lavorativi (Labor Path)13,006 sample units;Target population: migrants living in Italy who have or had a legal job since 12 months before the surveyMethodology: Centre sampling

Definition: “a migrant who is employed with a stable/secured job that gives good income and is adequate to his education level can be considered fully integrated into the labor market”

Example of the application of the procedure

Steps 1&2


8

lowest highest

-1 0 1Employment integration index (score)

(for each of the 4 dimensions)

Identification of integration scores by processing the frequencies of the sample distribution of the variables selected

Step 3


Step 3 (cont’d)

8Identification of integration scores by processing the frequencies of the sample distribution

Sample Frequency %Employment Unemployed 7.1

Employed 92.9Total 100

Stability & Low 0.1

job security Medium 38.6

High 61.3Total 100

Net income <500 € 3.1from work 500-800 € 28.5

800-1200 € 50.91200 – 1500 € 13.51500- 2000 € 2.9

2000- 3000 € 0.9> 3000 e 0.3

Total 100

Over qualification Severely inadequate 4.8(job compared Moderately inadequate 27.2to education) Adequate 68.0

Total 100


Step 3 (cont’d)

8 Example of identification of integration scores by processing the frequencies of the sample distribution

Sample Frequency % Corresponding Scores

Over qualification Severely inadequate 4.8 [ -27.2 -68.0 ] / 100 = -0.95

(job compared Moderately inadequate 27.2 [+4.8 – 68.0] /100 = -0.63to education) Adequate 68.0 [+4.8 +27.2] /100 = +32.0

Total 100

For each modality the corresponding score is obtained through the difference between the sum of the previous frequencies (relative) less the sum of the following ones. It can be remarked that, for any variable, the mean score for the whole set of sample units will be zero.


Set of scores(for each of the 4 dimensions)

Employment Unemployed -0.93

Employed +0.07

Stability & Low -0.99job security Medium -0.61

High +0.39< 500 € -0.97

Net income 500 – 800 € -0.65

from work 800 – 1200 € 0.141200 – 1500 € 0.781500 – 2000 € 0.952000 – 3000 € 0.99

> 3000 € 1.00

Over qualification Severely inadequate -0.95

(job compared Moderately inadequate -0.63

to education) Adequate 0.32


Assignment the scores to each statistical unit according to its modality of the variable under consideration (total 13,006 units) & Average of the 4 partial scores (Final Mean score)

Sample unitNo.

Employment Stability & job security (*)

Net income from work (*)

(*) Over qualification

Mean score

Modality Score Modality Score Modality Score Modality Score

1 Employed +0.07 Low -0.99 <500 € -0.97 Severely inadequate

-0.95 - 0.712 Unemployed -0.93 High +0.39 500-800€ -0.65 Moderately

inadequate-0.63 -0.45

3 Employed +0.07 Medium -0.61 1500-2000€ +0.95 Adequate +0.32 +0.184 Employed +0.07 Medium -0.61 2000-3000€ +0.99 Severely

inadequate-0.95 -0.12

… …

1,000 Unemployed -0.93 High +0.39 800-1200€ +0.14 Moderately inadequate

-0.63 -0.26… …

13,006 Employed +0.07 Low -0.99 >3000€ +1.00 Adequate +0.32 +0.10All sample

unitsMean Score

0.00 Mean Score

0.00 Mean Score

0.00 Mean Score

0.00

(*) Present or last job

Steps 4 & 5


Step 6 Processing the integration score together with structural data (personal features, education, social inclusion, etc.)

11

EmploymentStability &

job securityNet income from work

Over qualification

Mean score

Men -0.0005 +0.0144 +0.1205 +0.0291 +0.0406

Women +0.0004 -0.0154 -0.1291 -0.0312 -0.0433

Total 0.0000 0.0000 0.0000 0.0000 0.0000

Integration Index: mean scores by dimensions and gender

Source: Ismu-PerLa 2009


Step 6 (cont’d) Processing the integration scores together with structural data (personal features, education, social inclusion, etc.)

11

Integration Index: final mean scores by year of arrival to Italy and gender

Source: Ismu-PerLa 2009Gian Carlo Blangiardo

Positive integration scores seem to be associated to better work conditions

Work conditions Yes/No Final Mean integration score

Satisfaction for the present job Yes + 0.0341

No -0.1183

In the work place being the victim of aggression, threats, because foreign

Yes -0.0374

No +0.090

Aspects improved in the present work compared to the previous -

Salary / gain Yes +0.0513

No -0.1013

Type of job Yes +0.0429

No -0.0341

Responsibility Yes +0.0545

No -0.0259

Source: Ismu-PerLa 2009Gian Carlo Blangiardo

Additional remark

Thank you for your attention

Integration Indexes of Third Country Nationals Methodological Contributions Gian Carlo Blangiardo

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