Comments on: Higher Education and Social Mobility in the United States: A Glimpse Inside the Black Box? Lars Osberg Economics Department Dalhousie University January 26, 2007

Public Subsidies to Post-Secondary Education – who benefits ?  WSMH – subsidies increase = of opportunity tuition = access barrier to post-secondary Subsidy benefits students  ‘young adults with differing wealth/opportunities’  H A – subsidy to upper & middle class Educational streams separate before post-sec  Stratification in primary & secondary crucial  Especially for bottom 20% Subsidies primarily benefit affluent parents  Students = ‘children of unequal families’

What are the transmission mechanisms which link parents’ Socio-Economic Status (SES) and offspring SES?  parental SES (income, education, occupation) influences child’s income Indirectly – via child’s education & occupation Directly – given child’s job & schooling Which pathways matter more? Recursive model  SES => education; SES => job  Income <= education, job, SES Simulate impacts (direct & indirect) of SES

What is “parental SES” ?  1950s – single earner (male) Now a smallish minority  Divorce & remarriage - serial households  Dual earners + shifting gender balance in education – SES of parents & of kids ?  WSMH – when child age = Family income – ln (total 4 year total income) ‘prime earner’ – parent with higher occupation & education  Implication – assumed irrelevancy of: Earlier / later parental influences Spouse’s relative income/occupation/education Gender

Structural breaks in Mobility ? – suppose “middle churns but tails stay” child attainment parental SES

Suppose 3 classes identified – where to draw the line? child attainment SES child attainment SES

“Structural Breaks in Mobility” – crucial for equality of opportunity  How to partition mobility classes ? Crucial to detection of breaks  WSMH – 3 classes school / job / income Lower = <HS; routine/manual; bottom 25% Middle = HS only; intermediate; mid 50% Upper = attend post-sec; managerial /professional; top 25% Transition Matrix mingles 2 issues:  Up shift in distributions of education & occupation  Changing places in hierarchy of school & job

Intergenerational Regressions  Ordered Probit (3 classes ) Offspring Education i = a + B*Parental SES i + C*X i + e i Offspring Occupation i = δ + Θ*Parental SES i + Ω*X i + e i  ln(Offspring Income i ) = α + β*Parental SES i + Λ* Offspring Education i + Γ* Offspring Occupation i + C*X i + ε i Dummy variables for gender, race, immigrant  Conley results imply a different structure Simulations trace direct & indirect impacts of parent SES  Issues: Could compute inter-generational income elasticity & compare No test for similar structure: males/females, black/white  - 50% income if black; + 15% income if female ?? Why not use quantile regression?

OLS – presumes common impact of RHS variables on conditional mean  OLS – choose β to minimize sum squared residuals Outliers acquire greatest weight Symmetric loss function  Social Issue here is differential impacts for rich & poor Arguably different structural process

Quantile regressions – tests difference in impacts by outcome percentile  special case Τ = ½ is equivalent to median regression (which minimizes sum of absolute deviations)  the Τth regression quantile is a solution to the minimization problem Roger Koenker Quantile Regression, Cambridge University Press, New York (2005).

Example: Panel – Robust OLS & Quantile Regression Estimated Impact of Poverty on HAZ i

How to test for structurally different mobility processes? What to do?  Conley, Walters, Smith profound black/white differences in mobility processes  Smith & Conley Security of status – largely attainable at the (ambiguous) top  Changing gender roles  Changing structure of serial families not addressed

Accounting for Intergenerational Income Persistence: Noncognitive Skills, Ability and Education – Blanden, Gregg, Macmillan IZA DP No January 2007  UK boys borne 1958 & 1970 Intergenerational heritability high - increases from an elasticity of to  over 80% increase can be explained “strengthening influence of family income on non- cognitive traits, education and labour market attachment”  “Cognitive ability offers no substantive contribution to changes in mobility”  Diverging scores by age 16 important trend  Policy Issue – what type of reforms? UK – big shift in 1970s – away from ‘child centred’ to educational ‘accountability’, Test Score orientation negative impact on self-esteem, efficacy & non- cognitive traits – especially for vulnerable boys