University access for socio-economically disadvantaged children: A comparison across Anglophone countries

1. University access for socio-economically disadvantaged children: A comparison across Anglophone countries John Jerrim Anna Vignoles Ross Finnie

2. Background • Social mobility has emerged as one of the key academic and political topics over the past decade • Large economic literature on the link between fathers’ and sons’ incomes. • There has been a suggestion by economists that this association is stronger in the US/UK than other countries • ……..though some sociologists would disagree (Erickson and Goldthorpe 1992, Breen 2004) • Recent evidence suggests that, despite similar levels of income inequality, US and UK less socially mobile than Canada and Australia

3. Inequality versus intergenerational income mobility Anglophone countries (broadly) similar in terms of income inequality….. ….. but intergenerational income elasticity bigger in UK/ US than Australia or Canada

4. Background • Small, but growing, literature attempting to explain why US/UK less socially mobile then Canada / Australia • Bradbury et al (2012), Blanden et al (2012), Haveman et al (2012) some recent examples. Focus on the early years. • We attempt to add to this debate by investigating how the link between family background and access to university varies across these four countries.

5. Why is university access important for social mobility? • University is one of the main mechanisms by which skills developed in school converted into valued labour market qualifications • Large economic returns to university (particularly UK/US) • Large socio-economic differences in access • Hence university considered to be a key driver of intergenerational persistence

6. Why are there SES differences in access to university?

7. Two broad schools of thought..... 2. Towards point of decision • Credit constraints • Relative risk aversion • Lack of information • Peer influences • Educational aspirations • Influence university entry over and above school achievement 1. Childhood inputs • In-uteri experiences • Parent-child interactions • Child care • Heredity • Pre-school • Schools Influence university entry via impact upon school achievement

8. STAGE 1 (Early investments) STAGE 2 (Point of decision) STAGE 3 (Labour market entry) Heredity Labour market outcomes Time inputs Goods inputs university graduation university entry Family background Child’s teenage skills A model of intergenerational persistence(adapted from Haveman and Wolfe 1995) NOTE: Key role of prior achievement in determining university entry (and thus social mobility)

9. Why might SES gaps in university access differ across countries?

10. 1. Differences in childhood inputs • Schooling systems • Child care support • Teenage pregnancy / age of parenthood • Pre-school support / child care • Healthcare • Maternity leave • School segregation Leads to cross-national variation in school achievement towards end of secondary school (+ size of SES gaps)

11. Socio-economic gaps in prior achievement (PISA test scores)

12. 2. Differences in structure of higher education systems • Tuition fee levels • Private sector provision • Financial support (e.g. Loans and scholarships) • Provision of information about university • Distance to education institutions • School – to – university pathways (e.g. decision points) • Entry criteria (e.g. school grades, SAT tests) • Length of degree courses Lead to SES differences in university access over and aboverole of secondary school achievement

13. HE systems – key features United Kingdom (before September 2012) Fees: Maximum ≈ $4,800 per year (no variation by institution). Typical tuition fee cost of 3 year degree ≈ $14,000. Finance: Income contingent loans + grants for poor students. Pathways: TWO school leaving decisions (age 16 AND age 18). Study 3/4 subjects of choice between 16 and 18. Decisions: Both subject and institution at age 18. Entry criteria: Based upon predicted school grades at age 18.

14. HE systems – key features United States Fees: Large variation by institution (Issue “net” vs “sticker” price). Typical tuition fee cost of 4-year degree ≈ $47,000. Finance: Mortgage-style loans (no income contingency). Also grants / scholarship programmes. Pathways: Single school leaving decision (graduate high school). Decisions: Institution only at age 18. Two-tier HE system (Community vs 4-year college). Entry criteria: GPA , SAT / ACT scores, Carnegie units

15. HE systems – key features Australia Fees: Large variation by subject (little by institution). E.g. $4,000 for sciences. $9,000 for Law. Typical cost 4- year degree ≈ $18,000 Finance: Income contingent loans + grants for poor students Pathways: Single school leaving decision (graduate high school). Entry criteria: Tertiary entry rank (a scaling of school grades)

16. Implications: 1. There is clear SES inequality in academic achievement, and the extent of this inequality varies across countries. 2. Higher education systems (e.g. Fees, finance, entry criteria etc) also differ dramatically across countries. Hence university access for socio-economically disadvantaged children could vary across countries because of both of the above.

17. Research questions

18. Research questions 1. Is the SES gap in university participation greater in England and the United States than in Canada and Australia? 2. Do disadvantaged children in England/US have particularly low chances of entering a “selective” university? 3. To what extent can each of the above be explained by differences in children’s academic achievement at age 15? • Do schools play a role in explaining SES inequality in university access (beyond their role in developing young people’s academic ability)? 5. Does any SES difference in university access remain once school grades (at age 18) have been controlled?

19. Model

20. Model Where: Π (E) = Probability of the child going to university F = Socio – economic status (measured by parental education level) A = Children’s academic achievement as teenagers C = A vector of basic control variables (dummy variables for gender and language) G = School grades at age 18 µ = School level fixed effect K = Country K Estimated via linear probability model (response = 1 if entered university , 0 otherwise)

21. Model Specification • Four specifications • Specification 1 = No control for prior achievement (γ, δ, µ constrained to equal 0). Raw socio-economic gap in university access. • Specification 2 = Prior achievement controlled. Socio-economic gap in university access, conditional upon teenage skills. • Specification 3 = Also include a school fixed effect. • Specification 4 = Also include school grades at age 18 • Each specification estimated for each of the four countries • How do the SES parameters (β’s) change once controls included?

22. Data

23. Datasets • UK = LSYPE 2004 (n ≈ 8,000) • US = ELS 2002 (n ≈ 13,000) • Australia = LSAY 2003 (n ≈ 6,500) • Canada = YITS 2000 (n ≈ 11,000) Sample and design • Nationally representative • Similar sample designs and response rates • Longitudinal follow-up of 15/16 year old children into university (age 20) • Sample sizes several thousand in each study

24. Measures – Family background • Family background = Highest parental education level. Low = Below ISCED 3 = Below high school Medium = ISCED 3 – 5B = High school to associates degree High = ISCED 5A / 6 = Bachelor ‘s degree or higher

25. Measures • Academic achievement = PISA math and reading test scores at age 15 (NOTE: proxies for England)…… • university access = Enrolled on a bachelor's degree course by age 20 (refers to a 4 year university degree in the US).

26. “Selective” universities • All university degrees not necessarily of equal value. • Some evidence that returns vary by institutional quality. Maybe higher returns at “elite” universities (e.g. Oxford, Yale, Melbourne). • Probability of graduation also tends to be higher. • Socio-economically disadvantaged children may have particular difficulties accessing these institutions (e.g. higher costs, less geographically accessible etc). • Hence want to consider “elite” university access in paper

27. Definition of “Elite” • UK = “Russell Group” universities. • Self-selected alliance of the top 20 research universities • 10% of the population attend • Australia = “Group of 8” universities • Self-selected alliance of the top 8 research universities • 12% of the population attend • Canada = “U15” universities - Self-selected alliance of the top 15 research universities • US = “Highly selective” (Carnegie classification) • Based upon entry test scores • 13% of the population attend

28. ResultsAccess to a bachelor’s (“four year”) degree

29. Raw SES gap (specification 1) SES gap in university access notably smaller in Australia than other countries Top – Middle gap greater than the Bottom – Middle gap in all countries (though particularly Australia)

30. PISA controls included (specification 2) Middle –Top gap has been reduced, but still quite large. Australia still significantly different to England / US Bottom – Middle gap now small in each of the countries. England / US now very similar to Australia.

31. School fixed effect (specification 3) Little change in results once school FE is included. School-level factors play a relatively modest role in explaining SES inequality in university access (over and above influence on cognitive skills)

32. School grades at age 18 (specification 4) Remains a sizeable and statistically significant difference between most advantaged and other groups Difference between low and middle SES now statistically insignificant

33. Access to selective HE institutionsConditionalupon university attendance

34. Raw SES gap (Unconditional on uni entry)

35. Raw SES gap (Conditional on uni entry) Little difference between low and middle SES groups in access to elite institutions

36. Conditional (PISA test scores controlled)

37. Conditional (School grades controlled)

38. Conclusions • Large SES gaps in university access in each country, though particularly in England and US • Roughly half the SES gap can be explained by academic skill at age 15 (as measured by PISA test scores) • School level factors explain a rather modest amount of the SES gap in each of the three countries • Almost no difference in university access between low and middle SES groups once academic achievement has been controlled (based upon the definitions used) • High SES children still much more likely to enter university (including selective institutions) even once academic achievement taken into account

39. Policy recommendations • Reducing SES gap in school achievement important for reducing SES gap in university access. • Particularly important to raise low SES children’s skills to close gap with middle class peers • Interventions at the point of entry should not focus solely upon the most disadvantaged children – there is a large SES gap (conditional upon achievement) between high SES children and everyone else

40. Questions??

41. Appendix – proxy PISA scores for England

42. My predictions vs actual PISA 2006

43. Males (Predictions vs actual 2006)

44. Females (Predictions vs actual 2006)