the economics of investing in children: the role of cognitive and

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The Economics of Investing in Children: The Role of Cognitive and Non-Cognitive Skills Duke University March 29, 2010 James J. Heckman, University of Chicago

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Page 1: The Economics of Investing in Children: The Role of Cognitive and

The Economics of Investing in Children: The Role of Cognitive and Non-Cognitive SkillsDuke University March 29, 2010

James J. Heckman, University of Chicago

Page 2: The Economics of Investing in Children: The Role of Cognitive and

Polarization

Argument

Skills

Evidence

Critical and Sensitive Periods

Environment

Intuitive

Estimates

Illustration

Summary

American Society is Becoming Polarized and Less Productive

Page 3: The Economics of Investing in Children: The Role of Cognitive and

Polarization

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Skills

Evidence

Critical and Sensitive Periods

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Intuitive

Estimates

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Summary

American Society is Becoming Polarized and Less ProductiveIn the past 30 years, American society has polarized.

A greater percentage of children attending and graduating college.

At the same time, a greater percentage dropping out of secondary school producing a growing underclass, neither working nor going to school.

Page 4: The Economics of Investing in Children: The Role of Cognitive and

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American Society is Becoming Polarized and Less Productive75% of American youth who apply to the military are ineligible to serve because of low cognitive capacities, criminal records, or obesity.

20% of the U.S. work force has such a low rate of literacy that it cannot understand the instructions on a vial of pills.

The slowdown in the growth of the skills of the workforce is reducing U.S. productivity and competitiveness.

Page 5: The Economics of Investing in Children: The Role of Cognitive and

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American Society is Becoming Polarized and Less ProductiveThese problems are usually discussed separately, in a piecemeal fashion.

Analysts blame the public schools, rising tuition costs, or the failure of a number of other social institutions.

This has produced an array of competing proposals that lack coherence or a firm grounding in science and social science.

Page 6: The Economics of Investing in Children: The Role of Cognitive and

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American Society is Becoming Polarized and Less ProductiveToday, I want to articulate a coherent approach to addressing these problems that is rooted in the economics, psychology, and biology of human development.

There is a strong economic case for investing in early childhood.

Page 7: The Economics of Investing in Children: The Role of Cognitive and

Polarization

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Skills

Evidence

Critical and Sensitive Periods

Environment

Intuitive

Estimates

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Summary

The Argument

Page 8: The Economics of Investing in Children: The Role of Cognitive and

Polarization

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Critical and Sensitive Periods

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Summary

The Argument

Many major economic and social problems such as crime, teenage pregnancy, obesity, high school dropout rates, and adverse health conditions can be traced to low levels of skill and ability in society.

In analyzing ability, society needs to recognize its multiple facets.

Page 9: The Economics of Investing in Children: The Role of Cognitive and

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Skills

Evidence

Critical and Sensitive Periods

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The Argument

Current public policy discussions focus on promoting and measuring cognitive ability through IQ and achievement tests.

For example, in the U.S. the accountability standards in the No Child Left Behind Act concentrate attention on achievement test scores, not evaluating a range of other factors that promote success in school and life.

Cognitive abilities are important determinants of socioeconomic success.

Page 10: The Economics of Investing in Children: The Role of Cognitive and

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Critical and Sensitive Periods

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The Argument

So are socioemotional abilities, physical and mental health, perseverance, attention, motivation, and self confidence.

They contribute to performance in society at large and even help determine scores on the very tests that are used to monitor cognitive achievement.

Ability gaps between the advantaged and disadvantaged open up early in the lives of children.

Page 11: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Family environments of young children are major predictors of cognitive and socioemotional abilities, as well as crime, health and obesity.

More than genetics is at work.

The evidence that documents a powerful role of early family influence is a source of concern because family environments in the U.S. and many other countries around the world have deteriorated over the past 40 years.

Page 12: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Experimental evidence on the effectiveness of early interventions in disadvantaged families is consistent with a large body of non-experimental evidence that adverse family environments, especially adverse parenting, substantially impair child outcomes.

If society intervenes early enough, it can raise the cognitive and socioemotional abilities and the health of disadvantaged children.

Page 13: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Early interventions reduce inequality by promoting schooling, reducing crime, and reducing teenage pregnancy.

They also foster workforce productivity.

These interventions have high benefit-cost ratios and rates of return.

Page 14: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Early interventions have much higher economic returns than later interventions such as reduced pupil-teacher ratios, public job training, convict rehabilitation programs, adult literacy programs, tuition subsidies or expenditure on police, or a variety of programs recently funded under ARRA.

Page 15: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Life cycle skill formation is dynamic in nature. Skill begets skill; motivation begets motivation.

If a child is not motivated and stimulated to learn and engage early on in life, the more likely it is that when the child becomes an adult, it will fail in social and economic life.

The longer society waits to intervene in the life cycle of a disadvantaged child, the more costly it is to remediate disadvantage.

Page 16: The Economics of Investing in Children: The Role of Cognitive and

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The Argument

Similar dynamics appear to be at work in creating child health and mental health.

A major refocus of policy is required to understand the life cycle of skill and health formation and the importance of the early years in creating inequality and opportunity, and in producing skills for the workforce.

Page 17: The Economics of Investing in Children: The Role of Cognitive and

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Critical and Sensitive Periods

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The Importance of Cognitive and Noncognitive Skills

Page 18: The Economics of Investing in Children: The Role of Cognitive and

Polarization

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Evidence

Critical and Sensitive Periods

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Density of Age Adjusted AFQT Scores, GED Recipients and High School Graduates with Twelve Years of Schooling35

30

25

15

5

20

10

0

High School Graduates

-2.5 -2 -1.5 -1 -0.5 0 00.5 1 1.5 2.52 -2.5 -2 -1.5 -1 -0.5 0.5 1 1.5 2.52

White Males White Females

Source: Heckman, Hsee and Rubinstein (2001)

Page 19: The Economics of Investing in Children: The Role of Cognitive and

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Critical and Sensitive Periods

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Density of Age Adjusted AFQT Scores, GED Recipients and High School Graduates with Twelve Years of Schooling35

30

25

15

5

20

10

0

GEDsHigh School Graduates

-2.5 -2 -1.5 -1 -0.5 0 00.5 1 1.5 2.52 -2.5 -2 -1.5 -1 -0.5 0.5 1 1.5 2.52

White Males White Females

Source: Heckman, Hsee and Rubinstein (2001)

Page 20: The Economics of Investing in Children: The Role of Cognitive and

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The Importance of Cognitive and Noncognitive SkillsGEDs earn at the rate of high school dropouts.

GEDs are as “smart” as high school graduates who complete education by classtime and not by taking tests.

They lack noncognitive skills.

Page 21: The Economics of Investing in Children: The Role of Cognitive and

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The Importance of Cognitive and Noncognitive SkillsThe GEDs are the wise guys who can’t finish anything.

Most branches of the U.S. military recognize this in their recruiting strategies.

GEDs too violent and undisciplined to be in the Marines.

Page 22: The Economics of Investing in Children: The Role of Cognitive and

Polarization

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Evidence

Critical and Sensitive Periods

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Summary

.15

.05

.10

.00

Cognitive

0 – 20 21 – 40 41 – 60 61 – 80 81 – 100

Prob

abili

ty

Percentile

Note: This figure plots the probability of a given behavior associated with moving up in one ability distribution for someone after integrating out the other distribution. For example, the lines with markers show the effect of increasing noncognitive ability after integrating the cognitive ability.

Ever Been in Jail by Age 30, by Ability (Males)

Source: Heckman, Stixrud, and Urzua (2006).

Page 23: The Economics of Investing in Children: The Role of Cognitive and

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.15

.05

.10

.00

NoncognitiveCognitive

0 – 20 21 – 40 41 – 60 61 – 80 81 – 100

Prob

abili

ty

Percentile

Note: This figure plots the probability of a given behavior associated with moving up in one ability distribution for someone after integrating out the other distribution. For example, the lines with markers show the effect of increasing noncognitive ability after integrating the cognitive ability.

Ever Been in Jail by Age 30, by Ability (Males)

Source: Heckman, Stixrud, and Urzua (2006).

Page 24: The Economics of Investing in Children: The Role of Cognitive and

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Probability of Being Single With Children (Females)

.10

.08

.04

.06

.02

Cognitive

0 – 20 21 – 40 41 – 60 61 – 80 81 – 100

Prob

abili

ty

Percentile

Note: This figure plots the probability of a given behavior associated with moving up in one ability distribution for someone after integrating out the other distribution. For example, the lines with markers show the effect of increasing noncognitive ability after integrating the cognitive ability.

Source: Heckman, Stixrud, and Urzua (2006).

Page 25: The Economics of Investing in Children: The Role of Cognitive and

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Probability of Being Single With Children (Females)

.08

.04

.06

.02

.10

NoncognitiveCognitive

0 – 20 21 – 40 41 – 60 61 – 80 81 – 100

Prob

abili

ty

Percentile

Note: This figure plots the probability of a given behavior associated with moving up in one ability distribution for someone after integrating out the other distribution. For example, the lines with markers show the effect of increasing noncognitive ability after integrating the cognitive ability.

Source: Heckman, Stixrud, and Urzua (2006).

Page 26: The Economics of Investing in Children: The Role of Cognitive and

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Probability of Being a 4-year College Graduate by Age 30 (Males)

Notes: The data are simulated from the estimates of the model and our NLSY79 sample. We use the standard convention that higher deciles are associated with higher values of the variable. The confidence intervals are computed using bootstrapping (200 draws).

2 3 4 5 6 7 8 9 101

0.6

0.2

0.8

0.4

0.0

2 3 4 5 6 7 8 9 101

By Decile of Cognitive Factor By Decile of Noncognitive FactorPr

obab

ility

and

Con

fiden

ce In

terv

al (

2.5

– 97

.5%

)

Decile

Page 27: The Economics of Investing in Children: The Role of Cognitive and

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Illustration

Summary

Probability of Daily Smoking by Age 18 (Males)

Prod Interp Skills Evid Critical Evidence Intuitive Est Illustration Sum

Probability of daily smoking by age 18 (males)

24

68

10

24

68

10

0

0.2

0.4

0.6

0.8

1

Decile of Noncognitive

Figure 1F. Probability Of Daily Smoking By Age 18 - Malesi. By Decile of Cognitive and Noncognitive Factor

Decile of Cognitive

Pro

bab

ilit

y

1 2 3 4 5 6 7 8 9 100

0.2

0.4

0.6

0.8

1ii. By Decile of Cognitive Factor

Decile

Pro

bab

ilit

y a

nd

Co

nfid

en

ce I

nte

rval (2

.5-9

7.5

%)

Notes: The data are simulated from the estimates of the model and our NLSY79 sample. We use the standard convention that higher deciles are associated with higher values of the variable.The confidence intervals are computed using bootstrapping (200 draws).

1 2 3 4 5 6 7 8 9 100

0.2

0.4

0.6

0.8

1iii. By Decile of Noncognitive Factor

Decile

Page 28: The Economics of Investing in Children: The Role of Cognitive and

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Summary

Mean Log Wages by Age 30 (Males)

Prod Interp Skills Evid Critical Evidence Intuitive Est Illustration Sum

Mean log wages by age 30 (males)

24

68

10

123456789102

2.2

2.4

2.6

2.8

3

Decile of Non-Cognitive

Mean Log Wages by Age 30 - Males i. By Decile of Cognitive and Non-Cognitive Factors

Decile of Cognitive

Log

Wag

es

Page 29: The Economics of Investing in Children: The Role of Cognitive and

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Mean Log Wages by Age 30 (Males)

2.0

3.0

2.5

By Decile of Cognitive Factor By Decile of Noncognitive FactorLo

g W

ages

and

Con

fiden

ce In

terv

al (

2.75

– 9

7.5%

)

2 4 6 8 102 4 6 8 10

Notes: The data are simulated from the estimates of the model and our NLSY79 sample. We use the standard convention that higher deciles are associated with higher values of the variable. The confidence intervals are computed using bootstrapping (50 draws).

Decile

Page 30: The Economics of Investing in Children: The Role of Cognitive and

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The Importance of Cognitive and Noncognitive SkillsControlling for ability measured at the school-going age, in the U.S. minorities are more likelyto attend college than others despite their lower family incomes (Cameron and Heckman, 2001).

Deficits in college going across minority and majority groups are not caused by high tuition costs or family income at the age children are deciding to go to college.

Page 31: The Economics of Investing in Children: The Role of Cognitive and

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Can ability differences explain racial-ethnic schooling gaps?

High School Completion Gap

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .06 (.01) .14 (.02)Ability Adjusted Gap -.14 (.03) -.12 (.04)

Source: Cameron and Heckman (2001)

Page 32: The Economics of Investing in Children: The Role of Cognitive and

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Can ability differences explain racial-ethnic schooling gaps?

Source: Cameron and Heckman (2001)

High School Completion Gap

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .06 (.01) .14 (.02)Ability Adjusted Gap -.14 (.03) -.12 (.04)

College Entry Probabilities Given High School Completion

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .11 (.02) .07 (.02)Ability Adjusted Gap -.14 (.02) -.14 (.04)

Page 33: The Economics of Investing in Children: The Role of Cognitive and

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Critical and Sensitive Periods

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Illustration

Summary

Can ability differences explain racial-ethnic schooling gaps?

High School Completion Gap

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .06 (.01) .14 (.02)Ability Adjusted Gap -.14 (.03) -.12 (.04)

College Entry Probabilities Given High School Completion

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .11 (.02) .07 (.02)Ability Adjusted Gap -.14 (.02) -.14 (.04)

Population College Entry Gap (Not Conditioning on HS Completion)

White-Black Gap White-Hispanic Gap

Actual White-Minority Gap .12 (.02) .14 (.02)Ability Adjusted Gap -.16 (.03) -.15 (.04)

Source: Cameron and Heckman (2001)

Page 34: The Economics of Investing in Children: The Role of Cognitive and

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The Importance of Cognitive and Noncognitive SkillsGaps in the abilities that play such an important role in determining diverse adult labor market and health outcomes open up early across socioeconomic groups.

Schooling after the second grade plays only a minor role in alleviating these gaps.

Page 35: The Economics of Investing in Children: The Role of Cognitive and

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The Importance of Cognitive and Noncognitive SkillsMeasures of schooling quality (teacher/pupil ratios and teacher salaries) that receive so much attention in public forums play only minor roles in creating or eliminating the gaps after the first few years of schooling.

Schooling quality and school resources have relatively small effects on ability deficits and only marginally account for any divergence by age in test scores across children from different socioeconomic groups.

Page 36: The Economics of Investing in Children: The Role of Cognitive and

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Trend in Mean by Age for Cognitive Score by Maternal Education

Source: Brooks-Gunn et al. (2006).

Each score standardized within observed sample. Using all observations and assuming data missing at random.

0.0

0.5

1.0

-0.5

College Graduate

3 5 8 18

Mea

n Co

gniti

ve S

core

Age in Years

Page 37: The Economics of Investing in Children: The Role of Cognitive and

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Trend in Mean by Age for Cognitive Score by Maternal Education

Source: Brooks-Gunn et al. (2006).

Each score standardized within observed sample. Using all observations and assuming data missing at random.

0.0

0.5

1.0

-0.5

Some College EducationCollege Graduate

3 5 8 18

Mea

n Co

gniti

ve S

core

Age in Years

Page 38: The Economics of Investing in Children: The Role of Cognitive and

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Critical and Sensitive Periods

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Trend in Mean by Age for Cognitive Score by Maternal Education

Source: Brooks-Gunn et al. (2006).

High School Graduate

Each score standardized within observed sample. Using all observations and assuming data missing at random.

0.0

0.5

1.0

-0.5

Some College EducationCollege Graduate

3 5 8 18

Mea

n Co

gniti

ve S

core

Age in Years

Page 39: The Economics of Investing in Children: The Role of Cognitive and

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Trend in Mean by Age for Cognitive Score by Maternal Education

Source: Brooks-Gunn et al. (2006).

High School Graduate

Each score standardized within observed sample. Using all observations and assuming data missing at random.

0.0

0.5

1.0

-0.5

Some College EducationCollege Graduate

Less than High School

3 5 8 18

Mea

n Co

gniti

ve S

core

Age in Years

Page 40: The Economics of Investing in Children: The Role of Cognitive and

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Average Percentile Rank on Anti-Social Behavior Score, by Income Quartile

55

30

35

45

40

50

25

20

Lowest Income Quartile

4 Yrs 6 Yrs 12 Yrs

Scor

e Pe

rcen

tile

8 Yrs 10 Yrs

Age

Page 41: The Economics of Investing in Children: The Role of Cognitive and

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Average Percentile Rank on Anti-Social Behavior Score, by Income Quartile

55

30

35

45

40

50

25

20

Second Income Quartile Lowest Income Quartile

4 Yrs 6 Yrs 12 Yrs

Scor

e Pe

rcen

tile

8 Yrs 10 Yrs

Age

Page 42: The Economics of Investing in Children: The Role of Cognitive and

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Average Percentile Rank on Anti-Social Behavior Score, by Income Quartile

Third Income Quartile

55

30

35

45

40

50

25

20

Second Income Quartile Lowest Income Quartile

4 Yrs 6 Yrs 12 Yrs

Scor

e Pe

rcen

tile

8 Yrs 10 Yrs

Age

Page 43: The Economics of Investing in Children: The Role of Cognitive and

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Average Percentile Rank on Anti-Social Behavior Score, by Income Quartile

Third Income Quartile

55

30

35

45

40

50

25

20

Second Income Quartile Lowest Income Quartile

Highest Income Quartile

4 Yrs 6 Yrs 12 Yrs

Scor

e Pe

rcen

tile

8 Yrs 10 Yrs

Age

Page 44: The Economics of Investing in Children: The Role of Cognitive and

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Gaps Also Emerge in Health. They Diverge with Age.

Page 45: The Economics of Investing in Children: The Role of Cognitive and

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2.25

1.75

1.50

2.00

2.50H

ealth

Sta

tus*

1.25

Ages 0 – 3

*(Scale ranges from 1 = Excellent to 5 = Poor)

8 9 1110

LN (Family Income)

Ages 0 – 3f

Health and Income For Children and Adults, U.S. National Health Interview Survey 1986 – 1995*

* From Case, A., Lubotsky, D. & Paxson, C. (2002), American Economic Review, Vol. 92, 1308 – 1334.

Page 46: The Economics of Investing in Children: The Role of Cognitive and

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2.25

1.75

1.50

2.00

2.50H

ealth

Sta

tus*

1.25

Ages 4 – 8Ages 0 – 3

*(Scale ranges from 1 = Excellent to 5 = Poor)

8 9 1110

LN (Family Income)

Ages 0 – 3fAges 4 – 8f

Health and Income For Children and Adults, U.S. National Health Interview Survey 1986 – 1995*

* From Case, A., Lubotsky, D. & Paxson, C. (2002), American Economic Review, Vol. 92, 1308 – 1334.

Page 47: The Economics of Investing in Children: The Role of Cognitive and

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2.25

1.75

1.50

2.00

2.50H

ealth

Sta

tus*

Ages 9 – 12

1.25

Ages 4 – 8Ages 0 – 3

*(Scale ranges from 1 = Excellent to 5 = Poor)

8 9 1110

LN (Family Income)

Ages 0 – 3fAges 4 – 8f

Ages 9 – 12f

Health and Income For Children and Adults, U.S. National Health Interview Survey 1986 – 1995*

* From Case, A., Lubotsky, D. & Paxson, C. (2002), American Economic Review, Vol. 92, 1308 – 1334.

Page 48: The Economics of Investing in Children: The Role of Cognitive and

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2.25

1.75

1.50

2.00

2.50H

ealth

Sta

tus*

Ages 9 – 12

1.25

Ages 4 – 8Ages 0 – 3

Ages 13 – 17

*(Scale ranges from 1 = Excellent to 5 = Poor)

8 9 1110

LN (Family Income)

Ages 9 – 12fAges 4 – 8fAges 0 – 3f

Ages 13 – 17f

Health and Income For Children and Adults, U.S. National Health Interview Survey 1986 – 1995*

* From Case, A., Lubotsky, D. & Paxson, C. (2002), American Economic Review, Vol. 92, 1308 – 1334.

Page 49: The Economics of Investing in Children: The Role of Cognitive and

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Gaps Also Emerge in Health. They Diverge with Age. Evidence on the early emergence of gaps leaves open the question of which aspects of families are responsible for producing these gaps.

Is it due to genes?

Family environments?

Family investment decisions?

Page 50: The Economics of Investing in Children: The Role of Cognitive and

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The evidence from the intervention studies suggests an important role for investments and family environments in determining adult capacities above and beyond genes, and also in interactions with the genes.

Gaps Also Emerge in Health. They Diverge with Age.

Page 51: The Economics of Investing in Children: The Role of Cognitive and

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Family Environments

Page 52: The Economics of Investing in Children: The Role of Cognitive and

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10

15

35%

20

25

30

5

0

88 90 92 94 96 98 00 02 04 061968 70 7472 76 78 80 82 84 86

Perc

enta

ge o

f Chi

ldre

n U

nder

18

in S

ingl

e Pa

rent

Fam

ilies

Married, Spouse AbsentWidowedNever Married

Divorced

Percent of Children Under 18 Living with One Parent, By Marital Status of Single Parent

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0.05

Intact

0.01

0.03

0.02

0.04

0.00

BrokenSingle Mom

-2 -1.5 -.5-1 21.5.5 10

Den

sity

Cognitive Stimulation

Males

Cognitive Stimulation: Age 0 – 2, White, by Family Type

Source: Seong Hyeok Moon (2008) analysis of CNLSY data

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0.05

Intact

0.01

0.03

0.02

0.04

0.00

BrokenSingle Mom

-2 -1.5 -.5-1 21.5.5 10

Den

sity

Cognitive Stimulation

0.06 Females

Cognitive Stimulation: Age 10 – 11, White, by Family Type

Source: Seong Hyeok Moon (2008) analysis of CNLSY data

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There are Substantial Differences in Family Investment Across Income and Ethnic Groups

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Hispanic and Black PI in White Distribution: Full Sample, Age 0 – 3Hispanic and Black PI in White Distribution: full sample, age 0-3

Material Goods

xxxi

Figure .7.21: Hispanic and Black PI in White Distribution: full sample, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)Source: Moon (2010)

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Hispanic and Black PI in White Distribution: Full Sample, Age 0 – 3

Source: Moon (2010)

Hispanic and Black PI in White Distribution: full sample, age 0-3

Cognitive Stimulation

xxxi

Figure .7.21: Hispanic and Black PI in White Distribution: full sample, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)

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Hispanic and Black PI in White Distribution: Full Sample, Age 0 – 3

Source: Moon (2010)

Hispanic and Black PI in White Distribution: full sample, age 0-3

Emotional Support

xxxi

Figure .7.21: Hispanic and Black PI in White Distribution: full sample, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)

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Hispanic and Black PI in White Distribution: Intact Family, Adjusted For Mother’s Education Age 0 – 3

Source: Moon (2010)

Hispanic and Black PI in White Distribution: intact family, adjusted formother’s education, age 0-3

Material Goods

xxxv

Figure .7.25: Hispanic and Black PI in White Distribution: intact family, adjustedfor mother’s education, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)

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Hispanic and Black PI in White Distribution: Intact Family, Adjusted For Mother’s Education Age 0 – 3

Source: Moon (2010)

Hispanic and Black PI in White Distribution: intact family, adjusted formother’s education, age 0-3

Cognitive Stimulation

xxxv

Figure .7.25: Hispanic and Black PI in White Distribution: intact family, adjustedfor mother’s education, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)

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Hispanic and Black PI in White Distribution: Intact Family, Adjusted For Mother’s Education Age 0 – 3

Source: Moon (2010)

Hispanic and Black PI in White Distribution: intact family, adjusted formother’s education, age 0-3

Emotional Support

xxxv

Figure .7.25: Hispanic and Black PI in White Distribution: intact family, adjustedfor mother’s education, age 0-3

(a) Material Goods (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(b) Material Goods (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(c) Cognitive Stimulation (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(d) Cognitive Stimulation (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(e) Emotional Support (Females).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

(f) Emotional Support (Males).

0.1

.2.3

.4Fractions

1 2 3 4 5 6 7 8 9 10

Hispanic Black

Source: Moon (2010)

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Evidence

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Experience Gets Embodied in the Biology of the Organism

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Experience Gets Embodied in the Biology of the OrganismEvidence of gene-environment interactions: – How experience gets under and stays

under the skin.

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Methylation Patterns In Young and Old Twins

Source: Fraga, Ballestar et. al. (2005)

3-year-old twins 50-year-old twins

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Childhood Maltreatment:Age 3 –11 in Dunedin Cohort

Source: Moffitt, “Gene-Environment Interaction in Problematic and Successful Aging,” NIA Meeting Feb 12, 2008.

Maternal Rejection (14%)

Harsh Discipline (10%)

Caregiver Changes (6%)

Physical Abuse (4%)

Sexual Abuse (12%)

No Probable

≥2

Definite

None 1 type

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Childhood Maltreatment and Adult Inflammation

Danese et al. 2007 (PNAS)

CHILDHOOD MALTREATMENT AND ADULT INFLAMMATIONADULT INFLAMMATION

50

40ag

e 32y

20

30

mg/L(

%) a

t a

10

20

hsCR

P>3m

0Non-maltreated Maltreated

Danese et al. 2007 (PNAS)

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IL6 Genotype x Maltreatment > Adult Inflammation: Gene x Environment Interaction

Danese et al. (in preparation)

IL6 GENOTYPE x MALTREATMENT > ADULT INFLAMMATION:Gene x Environment interaction Gene x Environment interaction

50

40

50

ccg carrierse 3

2yIL6 promoter SNP

30

g-carriers

g/L(%

) at a

g

10

20

hsCR

P>3m

g

0Non-maltreated Maltreated

h

Danese et al. (in preparation)

Non-maltreated Maltreated

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Changes in Methylation Over Time

Source: Champagne (2008)

Changes in Methylation Over Time

offspring of Low LG damLow LG dam

Degree of methylation offspring of

High LG dam

late birth postnatal weaning adulthoodlategestation

birth postnatalday 6

weaning adulthood

Source: Champagne (2008)

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Transmission of Maternal Care andStress Responsivity Across GenerationsTransmission of maternal care and

stress responsivity across generationsstress responsivity across generations

Maternal LG

Maternal LG

Maternal LGStress

responsivity

StressStressresponsivity

Champagne & Curley, Current Opinion in Neurobiology, 2005

Champagne & Curley, Current Opinion in Neurobiology, 2005

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Evidence of Environmental Role on Gene Expression inMonkey Studies

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Evidence of Environmental Role on Gene Expression in Monkey StudiesRemodeling of the basal leukocyte gene expression profile in 4 month-old rhesus monkeys (Macaca mulatta) rearedunder adverse social conditions.

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Evidence of Environmental Role on Gene Expression in Monkey StudiesDisadvantaged (peer-reared; surrogate-reared) monkeys exhibit leukocytes showing enhanced expression of genes involved in:

– Inflammation– T lymphocyte activation– Cell proliferation– Suppression of genes involved in Type I

interferon antiviral response and immunoglobulin production of B lymphocytes

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Evidence of Environmental Role on Gene Expression in Monkey StudiesSurrogate mothers partly reverse some of the adverse effects.

Social conditions become embedded in basal transcriptional stance of primate immune systems.

Sympathetic nervous system-linked signal transduction and transcriptional control pathways are candidate mediators of these effects.

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Distribution of Leukocyte Gene Expression in Surrogate/Peer-Reared Macaques on the 500-Gene Expression Vector DiscriminatingMother-Reared from Peer-Reared Animals

Prod Interp Skills Evid Critical Evidence Intuitive Est Illustration Sum

Distribution of Leukocyte Gene Expression in Surrogate/Peer-RearedMacaques on the 500-Gene Expression Vector DiscriminatingMother-Reared from Peer-Reared Animals

239261

Surrogate/peerd

239261

Mother reared

reared

Peer reared

Source: Cole, Arevalo, Ruggiero, Heckman, and Suomi (2009)

Source: Cole, Arevalo, Ruggiero, Heckman, and Suomi (2009)

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Evidence of Environmental Role on Gene Expression in Monkey StudiesMeaney, Suomi and Szyf (2009) show that early peer rearing affects methylation in 22% of rhesus monkey genes.

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Critical and Sensitive Periods

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Human Brain Development

Source: Thompson and Nelson (2001)

-9 MonthsConception

-6 -3

70 YearsDeath

10 12 14 16 18 30 50

20 Years

Age (Months) Age (Years) Age (Decades)

Neurulation18–24 prenatal

days g

Myelination-2 months to5–10 years

g

9 12

1 Year

63 2 4 6 8

0 MonthsBirth

Cell Migration 6–24 prenatal weeksg

Prefrontal Cortex

Neurogenesis in the Hippocampus

Experience-dependent Synapse Formation

Synaptogenesis -3 months to 15–18 years?

Seeing /Hearing

Visual Cortex /Auditory Cortex

g

Receptive Language /Speech ProductionAngular Gyrus / Broca's Areag

Higher Cognitive FunctionsPrefrontal Cortexg

Adult levels of Synapses

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Key Policy Issues

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From the point of view of social policy, the key question is how easy is it to remediate the effect of early disadvantage?

How costly is delay in addressing early disadvantage?

How critical are the early years and for what traits?

What is the optimal time for intervention in different capacities?

Key Policy Issues

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Environment

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Environment

Enriched early environments can compensate in part for risk features of disadvantaged environments.

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Early Intervention Programs for Disadvantaged Children

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The Perry Program is the best studied of all of these intervention programs.

The Perry Program was an intensive preschool program that was administered to 58 disadvantaged, black children in Ypsilanti, Michigan between 1962 and 1967.

Early Intervention Programs for Disadvantaged Children

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The treatment consisted of a daily 2.5 hour classroom session on weekday mornings and a weekly 90 minute home visit by the teacher on weekday afternoons. The length of each preschool year was 30 weeks.

The control and treatment groups have been followed through age 40.

Early Intervention Programs for Disadvantaged Children

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Perry did not raise IQ.

It raised noncognitive skills.

Early Intervention Programs for Disadvantaged Children

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Perry Preschool Program: IQ, by Age and Treatment Group

Source: Perry Preschool Program. IQ measured on the Stanford Binet Intelligence Scale (Terman & Merrill, 1960). Test was administered at program entry and each of the ages indicated.

90

85

80

95

100

5 7 9 10Entry 6 84

IQ

Treatment Group

75

Age

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Perry Preschool Program: IQ, by Age and Treatment Group

Source: Perry Preschool Program. IQ measured on the Stanford Binet Intelligence Scale (Terman & Merrill, 1960). Test was administered at program entry and each of the ages indicated.

90

85

80

95

100

5 7 9 10Entry 6 84

IQ

Control GroupTreatment Group

75

Age

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Contribution of Noncognitive Capacities to Perry Treatment

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Figure 1: Decompositions of Treatment Effects, Males

90 100%0 10 3020 40 50 60 70 80

CAT total*, age 14(+)

Employed, age 19 (+)

Monthly Income, age 27 (+)

No tobacco use, age 27 (+)

# of adult arrests, age 27 (-)

Jobless for more than 2 years, age 40 (-)

Ever on welfare (-)

Total charges of viol.crimes with victim costs, age 40, (-)

Total charges of all crimes, age 40 (-)

Total # of lifetime arrests, age 40 (-)

Total # of adult arrests, age 40 (-)

Total # of misdemeanor arrests, age 40 (-)

Total charges of all crimes with victim costs, age 40 (-)

Any charges of a crime with victim cost, age 40 (-)

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Figure 1: Decompositions of Treatment Effects, Males

90 100%0 10 3020 40 50 60 70 80

Cognitive Factors

CAT total*, age 14(+)

Employed, age 19 (+)

Monthly Income, age 27 (+)

No tobacco use, age 27 (+)

# of adult arrests, age 27 (-)

Jobless for more than 2 years, age 40 (-)

Ever on welfare (-)

Total charges of viol.crimes with victim costs, age 40, (-)

Total charges of all crimes, age 40 (-)

Total # of lifetime arrests, age 40 (-)

Total # of adult arrests, age 40 (-)

Total # of misdemeanor arrests, age 40 (-)

Total charges of all crimes with victim costs, age 40 (-)

Any charges of a crime with victim cost, age 40 (-)

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Figure 1: Decompositions of Treatment Effects, Males

90 100%0 10 3020 40 50 60 70 80

Personal Behavior

Cognitive Factors

CAT total*, age 14(+)

Employed, age 19 (+)

Monthly Income, age 27 (+)

No tobacco use, age 27 (+)

# of adult arrests, age 27 (-)

Jobless for more than 2 years, age 40 (-)

Ever on welfare (-)

Total charges of viol.crimes with victim costs, age 40, (-)

Total charges of all crimes, age 40 (-)

Total # of lifetime arrests, age 40 (-)

Total # of adult arrests, age 40 (-)

Total # of misdemeanor arrests, age 40 (-)

Total charges of all crimes with victim costs, age 40 (-)

Any charges of a crime with victim cost, age 40 (-)

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Figure 1: Decompositions of Treatment Effects, Males

90 100%0 10 3020 40 50 60 70 80

Personal Behavior

Cognitive Factors Socio-Emotional State

CAT total*, age 14(+)

Employed, age 19 (+)

Monthly Income, age 27 (+)

No tobacco use, age 27 (+)

# of adult arrests, age 27 (-)

Jobless for more than 2 years, age 40 (-)

Ever on welfare (-)

Total charges of viol.crimes with victim costs, age 40, (-)

Total charges of all crimes, age 40 (-)

Total # of lifetime arrests, age 40 (-)

Total # of adult arrests, age 40 (-)

Total # of misdemeanor arrests, age 40 (-)

Total charges of all crimes with victim costs, age 40 (-)

Any charges of a crime with victim cost, age 40 (-)

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Figure 1: Decompositions of Treatment Effects, Males

90 100%0 10 3020 40 50 60 70 80

Personal Behavior

Cognitive Factors

Other Factors

Socio-Emotional State

CAT total*, age 14(+)

Employed, age 19 (+)

Monthly Income, age 27 (+)

No tobacco use, age 27 (+)

# of adult arrests, age 27 (-)

Jobless for more than 2 years, age 40 (-)

Ever on welfare (-)

Total charges of viol.crimes with victim costs, age 40, (-)

Total charges of all crimes, age 40 (-)

Total # of lifetime arrests, age 40 (-)

Total # of adult arrests, age 40 (-)

Total # of misdemeanor arrests, age 40 (-)

Total charges of all crimes with victim costs, age 40 (-)

Any charges of a crime with victim cost, age 40 (-)

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A Developmental Focus: Capacities

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Capacities at stage t of the lifecycle

θt = ( θc,t , θn,t , θh,t )

A Developmental Focus: Capacities

i cognition

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Capacities at stage t of the lifecycle

θt = ( θc,t , θn,t , θh,t )

A Developmental Focus: Capacities

i personality

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Capacities at stage t of the lifecycle

θt = ( θc,t , θn,t , θh,t )

A Developmental Focus: Capacities

i health

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Expression of Capacities: Behavior at stage t

Yj,t = ψ

j ( θt , Rt )

A Developmental Focus: Capacities

i capacities

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Expression of Capacities: Behavior at stage t

Yj,t = ψ

j ( θt , Rt )

A Developmental Focus: Capacities

i incentives to use capacities

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Capacities can be produced. Technology of capacity formation:

θt+1 = ft ( θt , It , θt,P )

A Developmental Focus: Capacities

i capacities

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Capacities can be produced. The technology of capacity formation:

θt+1 = ft ( θt , It , θt,P )

A Developmental Focus: Capacities

iinvestment(parenting, schools)

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Capacities can be produced. The technology of capacity formation:

θt+1 = ft ( θt , It , θt,P )

A Developmental Focus: Capacities

i parental and social environmental influences (traits of parents; values and motivations)

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A central question for public policy is what is the most effective way to promote high achievement in outcomes and reduce inequality that recognizes the way capacities are expressed and produced over the life cycle?

A Developmental Focus: Capacities

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A Life Cycle Framework for Organizing Studies and Integrating Evidence

Prod Interp Skills Evid Critical Evidence Intuitive Est Illustration Sum

A Life Cycle Framework for Organizing Studies and Integrating Evidenceθt = (θC , θN , θH) capacities at t

It : investment at tθt+1 = ft (θt , It , θt,P)

I-1

0H

I0

C NC 1H

I1

C NC 2H

C NC TH

I2

PRENATAL

BIRTH

LATE CHILDHOOD3-6

ADULTHOOD

EARLY CHILDHOOD 0-3

P-1

0P

1P

2P

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Cunha and Heckman (2008) and Cunha, Heckman, and Schennach (2007) estimate technologies of skill formation to understand how the skills of the children evolve in response to:– the stock of skills children have already

accumulated;

– the investments made by their parents; and

– the stock of skills accumulated by the parents themselves.

A Developmental Focus: Capacities

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Two Polar Cases Summarize the Literature

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Let h be adult human capital:

h = γI1 + ( 1- γ ) I2I1 is early investment; I2 is late investment.

Two Polar Cases Summarize the Literature (Example One)

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This extreme case states that remediation is always possible. (However, it may not be cost effective.)

This is at odds with the evidence from Neuroscience and Developmental Psychology.

It is the standard model in economics.

Two Polar Cases Summarize the Literature (Example One)

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The Technology in an Intuitive Framework

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The Technology in an Intuitive FrameworkThis technology suggests that the timing of investment is not an important issue. As a consequence, remediation is possible.

However, even though it may be feasible to remediate, it may be very costly (especially if γ is close to 1).

Even if it is technologically feasible to remediate, it is not necessarily economically feasible.

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The Technology in an Intuitive Framework

If:

E.g., if γ = 1/2, invest later.

All depends on γ.

May be more efficient to give the child a bank account to finance its schooling.

γ−−−−1+ r

< 1- γ invest later

> 1- γ invest earlier

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Polar Opposite Case

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Let h be adult human capital:

h = min { I1 , I2 }

In this case, if investments in period one are very low, no remediation is possible.

For early investment to work, later investments must be made.

The empirical truth is in-between.

Polar Opposite Case (Example Two)

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CapabilityFormation Process

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The capability formation process is governed by a multistage technology.

Each stage corresponds to a period in the life cycle of a child.

The technology of capability formation (Cunha and Heckman, 2007; Heckman, 2007) captures essential features of development.

Capability Formation Process

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It expresses the stock of period t + 1 capabilities ( θt+1 ) in terms of period t capabilities, ( θt ), investments, ( It ), and parental environments ( θ P

t ):

(1) θt+1 = ft ( θt , It , θtP ).

θ0 is the vector of initial endowments determined at birth or at conception.

Capability Formation Process

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The framework allows analysts:– To organize the evidence on outcomes and

interventions from diverse literatures within a common framework;

– Identify synergies among capabilities: how health, cognition and personality traits produce outcomes and interact in the production of capabilities; and

– Recognize gaps in the literature and the possibilities for a variety of interventions to promote health.

Capability Formation Process

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Estimates

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These technologies have been estimated.

The major findings from analyses based on them are:– Self-productivity becomes stronger as

children become older, for both cognitive and noncognitive capability formation.

– It is much more difficult to compensate for the effects of adverse environments on cognitive endowments in adolescence than it is at very young ages.

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– This helps to explain the large body of evidence on ineffective cognitive remediation strategies for disadvantaged adolescents.

– The productivity of investment is much greater at younger ages than at older ages for all types of investments. This is due to the plasticity of the young.

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– If society waits until adolescence to invest in children in disadvantaged environments, it is costly. At that stage of the life cycle, investments in noncognitive skills are more effective than investments in cognitive skills.

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The optimal policy toward disadvantaged children is to invest much more than we currently do in the early years of childhood.

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Optimal Early (L) and Late (R) Investments by Child Initial Conditions of Cognitive and Noncognitive Capacities Maximizing Aggregate EducationOptimal Early (Left) and Late (Right) Investments by Child Initial Conditions of Cognitive and

Noncognitive Capacities Maximizing Aggregate Education

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

1

0.9

0.95

1

1.05

1.1

1.15

1.2

-1

-0.5

0

0.5

1

-1

-0.5

0

0.5

1

0.9

0.95

1

1.05

1.1

1.15

1.2

Child InitialCognitive Capability

Child InitialCognitive Capability

Child InitialNoncognitive Capability

Child InitialNoncognitive Capability

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Optimal Early (L) and Late (R) Investments by Maternal Cognitive and Noncognitive Capacities Maximizing Aggregate EducationOptimal Early (Left) and Late (Right) Investments by Maternal Cognitive and Noncognitive

Capacities Maximizing Aggregate Education

-1

-0.5

0

0.5

1

-1-0.5

00.5

1

0.99

1

1.01

1.02

1.03

1.04

1.05

1.06

-1

-0.5

0

0.5

1

-1-0.5

00.5

1

0.9

0.95

1

1.05

1.1

MaternalCognitive Capability

MaternalCognitive Capability

MaternalNoncognitive Capability

MaternalNoncognitive Capability

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Illustration

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Returns to a Unit Dollar Invested

0–3 4–5 School Post-school

Preschool programs

Programs targeted towards the earliest years

Job training

Schooling

Rat

e of

Ret

urn

to In

vest

men

t in

Hum

an C

apita

l

Returns Per Annum to a Unit Dollar Invested

Source: Heckman and LaFontaine (2007).

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Returns to a Unit Dollar Invested

0–3 4–5 School Post-school

Preschool programs

Programs targeted towards the earliest years

Job training

Schooling

Rat

e of

Ret

urn

to In

vest

men

t in

Hum

an C

apita

l

Returns Per Annum to a Unit Dollar Invested

Source: Heckman and LaFontaine (2007).

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Returns to a Unit Dollar Invested

0–3 4–5 School Post-school

Preschool programs

Programs targeted towards the earliest years

Job training

Schooling

Rat

e of

Ret

urn

to In

vest

men

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Hum

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l

Returns Per Annum to a Unit Dollar Invested

Source: Heckman and LaFontaine (2007).

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Returns to a Unit Dollar Invested

0–3 4–5 School Post-school

Preschool programs

Programs targeted towards the earliest years

Job training

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Rat

e of

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Returns Per Annum to a Unit Dollar Invested

Source: Heckman and LaFontaine (2007).

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Practical Issues

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Whom to Target?

With What Programs?

Who Should Provide the Programs?

Who Should Pay for Them?

Issues of Compliance

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Whom to Target?– Returns higher to disadvantaged.– What is the proper measure of disadvantage?

Is it poverty? Measures of childhood home life?– Evidence suggests quality of parenting is the key.– Parenting is the scarce resource.– Not always closely linked to family income or

even parental education.– Explains in part why certain culture groups

produce successful children and others do not.

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With What Programs?– Programs that target the early years seem to

have the greatest promise.– Nurse Family Partnership Program /

Abecedarian / Perry.– Home visits affect the lives of the parents, create

a permanent change in the home environment.– Programs that build character and motivation —

not just cognition — are essential.

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Who Should Provide the Programs?– Respect the sanctity of early family life.– Respect cultural diversity.– Create a base of common skills and traits

but do so within a culturally diverse settings.– Engage private industry and other social

groups that: Draw in private resources.

Create community support.

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Who Should Pay for Them?– Can make it universal to avoid stigmatization.– Offer a sliding fee schedule to avoid

deadweight losses.– Mobilize private resources to support

the subsidy.

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Issues of Compliance– Many successful programs change the values

and motivation of the child.– This may run counter to the values of parents

(e.g., James Dobson).– There may be serious tension between the need

of the child and the acceptance of intervention by the parent.

– Then there is a basic conflict between values of society (as it seeks to develop the potential of the child) and the values of the family.

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Summary

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Many current social problems have their roots in deficits in abilities.

Ability deficits open up early in life and persist. They produce inequality and reduce productivity.

Evidence from human and animal studies shows critical and sensitive periods for development.

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Critical and sensitive periods come earlier for cognitive traits; later for noncognitive traits.

Associated with slower development of the prefrontal cortex.

Noncognitive traits stimulate production of cognitive traits (cross complementarity) but not vice versa.

Accords with evidence from animal studies.

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Later investment (associated with resilience) is possible but less efficient — consistent with the evidence from Neuroscience.

Later investment is more efficient if early investment is made.

Balanced portfolio weighted toward the early years is optimal.

Early investments create a base for enhancing the productivity of later investment.

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Children from advantaged environments by and large receive substantial early investment.

Children from disadvantaged environments typically do not.

There is a strong case for public support for funding interventions in early childhood for disadvantaged children.

The measurement of disadvantage is the quality of parenting, not income per se.

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The knowledge base needs to be expanded. A fruitful symbiosis of science and policy. Science guides policy and policy problems motivate scientific research.

Schools and tuition do not matter as much as is often thought.

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Late remediation not very effective. Remediation can work, but is costly.

Social policy should be directed toward the malleable early years, if we want to successfully reduce inequality and promote productivity in American society.

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HeckmanEquation.org