Explaining intergenerational income persistence

1. Explaining intergenerational income persistence Jo Blanden Paul Gregg Lindsey Macmillan Family Background and Child Development: The Emerging Story CMPO/CASE 18th July 2006

2. Intergenerational Mobility in socio-economic circumstances • Literature has mostly been concerned with measurement, i.e. the strength of the correlation between income across generations. • More recently comparisons across countries and across time have begun to emerge • 2 interesting findings: • UK relatively immobile • Mobility in UK has declined between 1958 and 1970 birth cohorts • But why?

3. Possible explanations • Those characteristics influenced by parental income that lead to higher earnings in later life. • Several avenues are suggested by the literature. • Physical Health (birth weight, obesity, childhood height etc.) • Cognitive skills • Behavioural and Non-cognitive skills • Education • Labour market experience

4. Plan of the Paper • Consider the routes through which income persists for the 1970 (BCS) cohort. The objective is to understand the level of persistence. • Analysis is restricted to sons at this stage. • Make comparisons between the 1958 (NCDS) and 1970 cohorts in an attempt to understand why intergenerational transmissions have strengthened.

5. Modelling approach (1)

6. Modelling approach (2) • Measure relationship between all mediating factors and family income. • Measure returns to these characteristics in an earnings equations. • Estimating sequential earnings equations enables the relationships between the mediating factors to be made clear.

7. Data – British Cohort Study (1) • Parental income data available at ages 10 and 16, average these. • Sons’ earnings at age 33. • Cognitive tests at age 5 and 10. • Mother reports on behaviour age 5. • Teacher reports on behaviour and self-reported measures at age 10. • Detailed education information including exam results. • Work history records from age 30 enable the construction of number of months unemployed and out of labour force.

8. Data – British Cohort Study (2) • Cognitive tests • Age 5: copying and english picture vocab test • Age 10: reading, maths, British ability scale • Non-cognitive measures • Mum, age 5: neurotic, anti-social • Teacher, age 10: application, clumsiness, extroversion, hyper-activity, anxious. • Child, age 10: locus of control, self-confidence. • Child, age 16: malaise. • All cognitive and non-cognitive measures are normalised to mean 0, standard deviation 1.

9. Family income relationships

10. Earnings Equations

11. Understanding persistence in the 1970 cohort (1) • Estimated beta is .320. • All the mediating factors have a strong relationship with family income. • A number of non-cognitive traits are strongly related to earnings. • Cognitive tests also affect earnings, cognitive and non-cognitive skills predict earnings in a similar way. • Main impact of cog and non-cog is through education. • Education extremely important in determining earnings. • Labour market attachment also important.

12. Understanding persistence in the 1970 cohort (2) • On their own non-cognitive skills explain 22 percent of intergenerational persistence. Locus of control and application contribute the lion’s share of this. • Adding cognitive tests explains 30 percent. • Education important, especially achievement at age 16. Cog and non-cog measures work through helping kids get better education. • Intermittent early labour market attachment of poorer kids contributes about 10 percent. • All factors taken together can account for more than half of total persistence.

13. Decompositions

14. Decompositions

15. Data – Cross cohort comparison • Income is only available at age 16 in NCDS. Earnings are from age 33. • Cognitive tests for reading, maths and general ability at 11, similar to BCS. • Non-cognitive tests are different between the cohorts, use Bristol social adjustment scales for NCDS. • unforthcoming, withdrawn, depressed, anxious for acceptance adults, hostile to adults, ‘writing off’ adults, anxious for acceptance kids, hostility to kids, restless, inconsequential behaviour, misc. • For both cohorts mother reports generate two measures from rutter scales at age 10, internalising and externalising. • Concerns about attrition and non-response in both cohorts, no evidence that this is responsible for cross-cohort differences.

16. The change in intergenerational mobility

17. Comparative family income relationships (1)

18. Comparative family income relationships (2)

19. Comparative analysis • Stronger relationships in the second cohort between family income and non-cognitive skills, education and unemployment. • Not much change for cognitive ability. • Suggests possible explanations for the rise in persistence. • How traits impact on intergenerational mobility depends also on their changing returns in the labour market. Results mixed on this. • To see how changes affect intergenerational mobility need to look at decompositions.

20. Comparative decompositions (1)

21. Comparative decompositions (2)

22. Findings from decompositions • Non-cognitive traits explain more of intergenerational relationship in the second cohort, due to their stronger relationship with family income. • Education is also more important for the same reason (some of this is explained by non-cog). • The strengthened relationship between early unemployment and family income also has a role to play in higher intergenerational persistence. • Can explain .066 of the .086 rise in the intergenerational coefficient.3/4 of the change.

23. Policy implications • Fall in mobility is explained by growing relationship between family income and non-cognitive skills, education and early unemployment. • Not due to IQ or cognitive skills. • 3 possible policy routes • Close gap in non-cognitive skills (especially personal efficacy and concentration). • Educational performance at age 16 and beyond. • Help in early career (policies to avoid NEET).