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Explaining intergenerational income persistence

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Title: 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 lions
    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).
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