IFSThe Role of Credit Constraints

in Educational Choices

Lorraine Dearden, Leslie McGranahan and Barbara Sianesi

IFS

Evidence from two British cohorts

© Institute for Fiscal Studies, 2005

Research questions

1. Extent to which short-term ‘credit constraints’ affect individual educational choices– Staying on in FT education past 16– Completing HE

2. Has this changed over time?– 1958 cohort (NCDS) – 1970 cohort (BCS)

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Who stays on in school?

Proportion staying on by parental income quartiles – BCS70

Females Males

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Who completes HE?

Females Males

Proportion achieving HE by parental income quartiles – BCS70

© Institute for Fiscal Studies, 2005

Is this evidence of credit constraints?

Family Income

Education

© Institute for Fiscal Studies, 2005

Is this evidence of credit constraints?

Family Income

Education

Credit Constraints

© Institute for Fiscal Studies, 2005

Is this evidence of credit constraints?

Family Income

Education

Credit Constraints

Cognitive abilityNon-cognitive ability

ExpectationsTastes …

Early + long-term factors- Family inputs- Environmental inputs

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Is this evidence of credit constraints?

• Observed correlation between family income and educational outcomes could be due to:

a) short-run credit constraints

b) long-run family background and environmental effects correlated with family income and educational outcomes

• Our aim is to single out a)

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How do we do this?

• Apply methodology of Carneiro and Heckman (2003) to the UK

• To estimate the share of individuals affected by short-term ‘credit constraints’

© Institute for Fiscal Studies, 2005

Operational definition of ‘credit constrained’

• Individuals from the top quartile of the income. distribution are not, by assumption, credit constrained

• All others are potentially credit constrained.

• Share who is credit constrained = Any residual gap in educational attainment between top income children and all other children with the same ability and the same early family and environmental factors

• NB: if we don’t manage to capture all family effects, estimates will be an upper bound.

© Institute for Fiscal Studies, 2005

Approach

• Split family income at 16 into quartiles• Split ability at 10/11 into tertiles

– math, verbal and non-cognitive measures

• Within each ability group work out the proportion of ‘credit constrained’ individuals after controlling for long-run family background characteristics: – mother’s and father’s education, family size and

structure, father’s social status at 16, race and region of residence at 16

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Results: Staying On – BCS

Males

Raw 22.0%

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Results: Staying On – BCS

Males

Raw 22.0%

+ Ability 13.1%

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Stay On Rates: Males – BCS70

Males

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Unadjusted

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Adjusted

© Institute for Fiscal Studies, 2005

Results: Staying On – BCS

Males

Raw 22.0%

+ Ability 13.1%

+ Fam. background, region 7.2%

Only stat. significant gaps 7.0%

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Results: Staying On – BCS

Males Females

Raw 22.0% 19.8%

© Institute for Fiscal Studies, 2005

Results: Staying On – BCS

Males Females

Raw 22.0% 19.8%

+ Ability 13.1% 14.0%

© Institute for Fiscal Studies, 2005

Stay On Rates: Females – BCS70

Females

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Unadjusted

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Adjusted

© Institute for Fiscal Studies, 2005

Results: Staying On – BCS

Males Females

Raw 22.0% 19.8%

+ Ability 13.1% 14.0%

+ Fam. background, region 7.2% 7.1%

Only stat. significant gaps 7.0% 6.2%

© Institute for Fiscal Studies, 2005

Results: Staying On – NCDS

Males

Raw 15.0%

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Results: Staying On – NCDS

Males

Raw 15.0%

+ Ability 8.9%

© Institute for Fiscal Studies, 2005

Stay On Rates: Males – NCDS

Males

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Unadjusted

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Adjusted

© Institute for Fiscal Studies, 2005

Results: Staying On – NCDS

Males

Raw 15.0%

+ Ability 8.9%

+ Fam. background, region 1.3%

Only stat. significant gaps 0.0%

© Institute for Fiscal Studies, 2005

Results: Staying On – NCDS

Males Females

Raw 15.0% 14.2%

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Results: Staying On – NCDS

Males Females

Raw 15.0% 14.2%

+ Ability 8.9% 9.3%

© Institute for Fiscal Studies, 2005

Stay On Rates: Females – NCDS

Females

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Unadjusted

0.1

.2.3

.4.5

.6.7

.8.9

1

Bottom Middle Top

Low 2nd 3rd Top Low 2nd 3rd Top Low 2nd 3rd Top

Adjusted

© Institute for Fiscal Studies, 2005

Results: Staying On – NCDS

Males Females

Raw 15.0% 14.2%

+ Ability 8.9% 9.3%

+ Fam. background, region 1.3% 2.3%

Only stat. significant gaps 0.0% 0.0%

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HE Completion

• Target groups:– HE vs Anything Less– HE vs at least Level 2

• key marginal group who could access / would benefit from HE

• Attainment– Credit constraints might affect dropping out

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Summary (stat. significant gaps - pp)

1958 1970

Stay-on – Males 0 7

Stay-on – Females 0 6

Males

HE vs Less 0 <3

HE vs ≥Level 2 0 <2

Females

HE vs Less <3 <2

HE vs ≥Level 2 6 3

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Conclusions

• Short term ‘credit constraints’ have more impact on staying-on decisions for our younger cohort– Is 6-7% a large fraction?

• Upper bound• Conceptual policy experiment

– But: emerged between the two cohorts

• Less evidence of effect on HE completion– ‘Convergence’ for males and females to 2-3%

• Reduced for females• Emerged for males

• Policies earlier on may be well placed.