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Transcript of 1 /14 The Persistence of Persistent Inequality – A Review RC28 Spring meeting, Brmo May 2006 Yossi...
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1 /14
The Persistence of Persistent Inequality – A
Review
RC28 Spring meeting, Brmo May 2006
Yossi ShavitMeir YaishEyal Bar Haim
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Mare’s Model of Educational Transitions
Mare’s model has served as an industry standard in research on educational stratification.
Mare designed his model to yield margin-free estimates of educational stratification.
Mare’s sought to disentangle two confounded aspects of educational stratification Dispersion. Stratification (social selection)
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A Reminder
s
isjsjij
ij xp
p)
1ln(
The association between X and the progression from educational level j-1 to j.
The model is written as:
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– The probability that person i will continue from educational level j-1 to level j
ijiss
jsjij eXbbp 0
)1( ijijjsjs ppb
Mare shows that
The association between X and the progression from educational level j-1 to j.
In words, the additive linear effect of X on pij is a function of and of educational expansion.
• Note that bjs is at a maximum for p=0.5
• Therefore, an expansion of j can reduce or increase bjs even if remains stable.
ijP
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Following Mare
Despite the importance of educational expansion in the public and theoretical debate concerning IEO, it is usually ignored by empirical research.
Rather, it is treated as a nuisance to be adjusted for.
NOTE: Mare himself paid a great deal of attention to expansion.
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Persistent Inequality? Mare’s model has been replicated in a large
number of studies (including Shavit & Blossfeld).
Main Findings: Declining effects, over time, of social
origins at lower educational transitions, Stability/increasing effects of origins on
the odds of higher transition points I.E., Persistent Inequality (PI)
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Challenges to Mare’s Model
Main Challenge: PI is due to dynamic sample selection. SES effects are stable (or even increase)
over time because the risk-set of transitions grow ever more heterogeneous
Secondary Challenges: Myopia (C&H) Educational choices are rarely binary (B&J)
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Log Linear Alternatives to Mare’s Model
These models discard the notion of educational transitions.
Estimates of the association between origins and educational attainment is not biased by dynamic sample selection.
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Log Linear Findings RE: PI
Jonsson, Mills and Müller (1996): Sweden and Germany:
The association between class and education declined slightly over time (6% in the first half of 20th Century)
Britain - no change.
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Log Linear Findings II
Breen, Luijkx, Müller and Pollak, (2005): The origin-education association
declined significantly across cohorts. Importantly however, the decline was
not linear Pronounced in the post-WWII years; Persistence since then.
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Log Linear Findings III
Vallet (2004): In France, too, the decline in the origin –
education association is not linear in time.
It increased for cohorts born between 1908 and the late 1920s;
Declined sharply for those born between the late-1930s and the late 1940s, and
declined weakly thereafter.
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Log Linear Findings IV
Barone (2006): In Italy the origin-education association
declined for cohorts born during the 1930s and 1940s and increased thereafter.
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Persistent Inequality?
Yes! In a weak version: Modest declines in IEO. Much of the decline seems to have
occurred during, or soon after WWII
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Expansion and IEO
Expansion is a very common educational policy.
Can expansion reduce IEO? The answer depends on how we define IEO.
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Expansion (cont.)
As seen earlier, under the linear probability model, expansion can reduce IEO once the attainment probability has exceeded 0.5.
However, most RC28 research on IEO can not inform policy because it employs margin-free models (either transition or log-linear models).
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Examples and Critique of Research on Expansion
and IEO
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Raftery and Hout (1993):
A quasi-experimental design:
IEO Before IEO After
Educational reform that expanded
participation
Findings: IEO decreased at the lower levels of education.
Critique: Changes in IEO, or lack thereof, may have resulted from factors other than educational expansion.
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Ganzeboom, Treiman and Reijkin (2003)
Multi-level linear analysis 30 countries Units of analysis: cohort x country combinations. Expansion is measured as average school years in
each cohort x country combination. Findings: negative effect of “expansion” on
the correlation between socio-economic background and educational attainment.
Critique: Expansion should be measured as a process rather than in cross-section
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Arum, Gamoran and Shavit (2007)
15 Countries Expansion measured longitudinally (process). Saturation measured in cross-section. AGS estimate effects of expansion and saturation
on effects of origins on the log odds of transitions from secondary to higher education.
Findings: Saturation reduces IEO in transition to higher education, expansion neither enhances nor reduces IEO.
Critique: AGS’s analysis is an informal meta-analysis. No formal tests are employed
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New Research: Bar-Haim, Shavit and Ayalon.
Work in progress: “Educational Expansion and Inequality of Educational Opportunity.” Submitted to the Montreal Meeting of RC28.
ISSP Data 24 countries 1992, 1993, 1999 Multi-level Logistic Regression
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Individual-Level Variables Father’s education Gender Birth Cohort (1940s, 1950s).
Country-Level Variables Expansion is defined as the proportionate
change, between cohorts, in % attending higher education.
Saturation is a dummy representing 80+% higher education among children in the first cohort whose fathers were highly educated themselves.
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Intercept -3.27*(0.22)
Mean Father Education X Cohort 1950-59
0.01(0.16)
Expansion -0.25(0.20)
Saturation 0.89*(0.26)
Male 0.18*(0.05)
Cohort 1950-59 0.28*(0.10)
Father Education 0.51*(0.03)
Father Education X Cohort 1950-59
Intercept 0.01(0.02)
Expansion 0.21*(0.03)
Saturation -0.05*(0.01)
Male X Cohort 1950-59 -0.16*(0.05)
Table1: Coefficients (standard errors), of multi-level logistic regression model on higher education
* p<0.05
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Summary of Results:
IEO is defined as the effect of father’s education on the log odds of entering higher education: Expansion enhances IEO between
cohorts. Saturation reduces IEO between cohorts.
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Summary Persistent Inequality persists, albeit in a
weak version: Declining IEO at lower levels (saturation
effects) Declining IEO during mid-century. PI otherwise.
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Question: Is there a distinct War (WWII) effect (e.g., Sorokin)?
Could the decline have been due to the resumption of normality after the War rather than to long term modernization processes?
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Can Policy Affect IEO? Effective egalitarian educational policy
increases participation (expansion). However, much of our collective work
ignores expansion and thus, misses an important beneficial outcome.
Let’s bring expansion back into our models.