1. Integration Indexes of Third Country Nationals Methodological Contributions Gian Carlo Blangiardo Milano-Bicocca University / Ismu Foundation EUROPEAN FUND FOR THE INTEGRATION OF THIRD COUNTRY NATIONALS PAN-EUROPEAN CONFERENCE Work: A Tool for Inclusion or a Reason for Exclusion? Gian Carlo Blangiardo

2. to measure and compare integration level among migrant populations (or sub-populations defined according to some specific features) The ultimate purpose Gian Carlo Blangiardo

3. The classical macro approach: by statistical indicators of integration Gian Carlo Blangiardo

4. 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 Gian Carlo Blangiardo

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

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

7. 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 Gian Carlo Blangiardo Main sources

8. 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 Gian Carlo Blangiardo

9. 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 Gian Carlo Blangiardo

10. 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.org ORIM – Regional Observatory for Integration and Multiethnicity Gian Carlo Blangiardo

11. 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 REMARK In 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 Gian Carlo Blangiardo

12. 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 STEP2Choice of the variables of sample dataset available to give the requested indicators STEP3Identification of integration scores by processing the frequencies of the sample distribution of the variables selected STEP4Assignment the scores to each statistical unit according to its modality of the variables under consideration STEP5Attribution of the average score of integration at each statistical unit (additive variable to the sample dataset) STEP6Processing the integration score together with structural data (personal features, education, social inclusion, etc.) Gian Carlo Blangiardo

13. 7 Selection of a set of indicators according to a definition of integration in the labor market 4 dimensions Employment Stability & 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 survey Methodology: 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 Gian Carlo Blangiardo

14. 8 lowest highest 01 Employment 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 Gian Carlo Blangiardo

15. Step 3 (cont’d) 8 Identification of integration scores by processing the frequencies of the sample distribution Sample Frequency % Employment Unemployed7.1 Employed92.9 Total100 Stability & Low0.1 job security Medium38.6 High61.3 Total100 Net income <500 €3.1 from work 500-800 €28.5 800-1200 €50.9 1200 – 1500 €13.5 1500- 2000 €2.9 2000- 3000 €0.9 > 3000 e0.3 Total100 Over qualification Severely inadequate4.8 (job compared Moderately inadequate27.2 to education) Adequate68.0 Total100 Gian Carlo Blangiardo

16. 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 inadequate4.8 [ -27.2 -68.0 ] / 100 = -0.95 (job compared Moderately inadequate27.2 [+4.8 – 68.0] /100 = -0.63 to education) Adequate68.0 [+4.8 +27.2] /100 = +32.0 Total100 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. Gian Carlo Blangiardo

17. Set of scores (for each of the 4 dimensions) Employment Unemployed-0.93 Employed+0.07 Stability & Low -0.99 job security Medium -0.61 High +0.39 < 500 € -0.97 Net income 500 – 800 € -0.65 from work 800 – 1200 € 0.14 1200 – 1500 € 0.78 1500 – 2000 € 0.95 2000 – 3000 € 0.99 > 3000 € 1.00 Over qualification Severely inadequate -0.95 (job compared Moderately inadequate -0.63 to education) Adequate 0.32 Gian Carlo Blangiardo

18. 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 unit No. Employment Stability & job security (*) Net income from work (*) (*) Over qualification Mean score ModalityScoreModalityScoreModalityScoreModalityScore 1Employed+0.07Low-0.99<500 €-0.97Severely inadequate -0.95 - 0.71 2Unemployed-0.93High+0.39500-800€-0.65Moderately inadequate -0.63 -0.45 3Employed+0.07Medium-0.611500-2000€+0.95Adequate+0.32 +0.18 4Employed+0.07Medium-0.612000-3000€+0.99Severely inadequate -0.95 -0.12 …… 1,000Unemployed-0.93High+0.39800-1200€+0.14Moderately inadequate -0.63 -0.26 …… 13,006Employed+0.07Low-0.99>3000€+1.00Adequate+0.32 +0.10 All sample units Mean Score 0.00Mean Score 0.00Mean Score 0.00Mean Score 0.00 (*) Present or last job Steps 4 & 5 Gian Carlo Blangiardo

19. Step 6 Processing the integration score together with structural data (personal features, education, social inclusion, etc.) 11 Employment Stability & job security Net 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 Total0.0000 Integration Index: mean scores by dimensions and gender Source: Ismu-PerLa 2009 Gian Carlo Blangiardo

20. 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 2009 Gian Carlo Blangiardo

21. Positive integration scores seem to be associated to better work conditions Work conditionsYes/NoFinal Mean integration score Satisfaction for the present jobYes+ 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 / gainYes+0.0513 No-0.1013 Type of jobYes+0.0429 No-0.0341 ResponsibilityYes+0.0545 No-0.0259 Source: Ismu-PerLa 2009 Gian Carlo Blangiardo Additional remark

22. Thank you for your attention