1. Comments on: - Enclaves, peer effects and student learning outcomes in British Columbia – Friesen & Krauth - Reading skills of young Canadian immigrants: the effects of duration of residency, home language exposure and school Gluszynski & Dhawan-Biswal Lars Osberg CERF – May 2006

2. Similarities of Concern Learning of children Assimilation / Integration of immigrants  “Second Generation” & Problem of continuing social exclusion ?? Ghettos / enclaves ? Cumulative Disadvantage ?  Context: Slower or Never ? – how to interpret poorer relative outcomes for Canadian immigrants in 1990s ?

3. Similarities of Conclusion - “Not to Worry” Gluszynski & Dhawan-Biswal –  “most immigrants appeared to have caught up in five years through integration”  “First generations students – those born in Canada to parents born outside of the country – performed at the same level in reading as their native born peers” Friesen & Krauth –  “enclave effects are generally positive”: 12 out of 32 are statistically significant and positive,  “enclave effects are generally stronger in Grade 4 than in Grade 7

4. Similarities of Methodology (1) Cross – sectional Data  => School “value-added” not observable at individual level  Issue of interest – a time dependent process  Constraint of Data Can cohort size variation within schools identify linguistic effect – “”language of playground” – in BC data ?

5. Similarities of Methodology (2) Boys = Girls + Dummy  Much evidence on structural differences in learning between boys & girls Grade 7 & boy/girl differences ??? 15 year olds & boy/girl differences ??? In general, BAD PRACTICE to assume gender => only dummy shift to intercept & zero change to structural processes  Easy to test for & estimate separately if warranted

6. Similarities of Methodology (3) Focus on Mean outcomes / Conditional Expectation  Homogeneity of Impact presumed  Requires Cardinality of outcome measures  If A > B > C  Is (A + C) / 2 = B? Or are other monotonic transformations also plausible ? Is it average outcomes that concern us ?

7. Suppose: Suppose: Social Loss Function is Asymmetric  Main Issue: Social Exclusion is skill set “good enough” -i.e. A i > A* (once enter labour force, further learning is OTJ) Suppose: “Ability” is ordinal variable, with no natural units of measurement Observe test score Y i = f(A i ) + ε i  Where f is unknown monotonic function Issue: to identify Prob (A i > A* | X i )

8. Suggestions Separate regressions for boys & girls Quantile regressions can identify differences in structural influences at different percentile points in distribution of outcomes  Else: strong maintained hypothesis of impact homogeneity Uses all data points, requires cardinality Probit or Logit – can identify Prob (A i > A*) Requires identification of A*, no cardinality assumed