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

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 ?

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

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 ?

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

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 ?

Suppose:

Suppose: Social Loss Function is Asymmetric Main Issue: Social Exclusion

is skill set “good enough” -i.e. Ai > A* (once enter labour force, further learning is OTJ)

Suppose: “Ability” is ordinal variable, with no natural units of measurement

Observe test score Yi = f(Ai) + εi

Where f is unknown monotonic function

Issue: to identify Prob (Ai > A* | Xi )

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 (Ai > A*) Requires identification of A*, no cardinality assumed