SCHOOLS SKILLS AND SYNAPSES James J. Heckman

NBER Working Paper No. 14064June 2008

JEL No. A12

Elena Broccini

American Society is Becoming Polarized…

One aspect of the US increasing polarization is that:

• a greater percentage of American children is attending and graduating college: At the same time a greater percentage is dropping out of secondary school.

• This produces a growing underclass, neither working nor going to school.

• At the same time there is a recent growth in unskilled migration to the U.S. that increases the proportion of unskilled Americans in the workforce.

…the Workforce is Less Skilled and Productive

The increase in high school dropouts rate +

The recent growth in unskilled migration

These two trends reduce the growth in workforce productivity and produce more people with low skills in US:

• Annual growth in labour productivity has slowed by 0.17% to 0.35% per year.

• More than 20% of US workforce has so low rate of literacy that it cannot understand the instructions on vial of pills.

The Argument

• What forces produce these low levels and adverse trends?

• Are the public schools mainly responsible?

• Can we look to school reform to fix the problem?

• Are higher college tuition costs to blame?

The answer is “No” to all of these questions.

Contrary to prevailing views:

Tuition costs and Schooling Quality explain only trivial fractions of the gaps in educational attainment by socio economic status…

Cognitive and Non-cognitive Abilities Matter

• A substantial body of research shows that cognitive and non cognitive abilities are important determinants of schooling and socioeconomic success.

• By non cognitive abilities we mean socio-emotional regulation, time preferences, personality factors, the ability to work with others..

• They are both equally predictive of many social outcomes (i.e. earnings, labor force experience, college attendance, teenage pregnancy, participation in risky activities, participation in crime, etc).

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

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 (i.e. the red line shows the effect of increasing noncognitive ability after integrating the cognitive ability).

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

Probability of Teenage Pregancy (Females)

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 (i.e. the red line shows the effect of increasing noncognitive ability after integrating the cognitive ability).

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

Ability Gaps Opens Up at Early Ages and Persist

• Gaps in the abilities that play such an important role in determing diverse adult outcomes open up at early ages across socio economic groups.

• School plays a minor role in creating or perpetuating gaps.

• Even though American children go to very different schools, depending on their family background, test scores are remarkably parallel.

Average Percentile Rank on PIAT-Math Score, by Income Quartile - Unadjusted

Source: Carneiro and Heckman (2003).

The gaps in achievement at age 12 are mostly present at age 6 when children enter school. High scores are associated with higher socio-economic status.

Average Percentile Rank on PIAT-Math Score, by Income Quartile – Adjusted*

Source: Carneiro and Heckman (2003).

* When one controls for early family background factors (mother's education and ability) using regression analysis, the gaps greatly diminish.

Average Anti-Social Behavior Score Percentile, by Income Quartile - Unadjusted

In this figure an high score is an indicator of behaviour problems. Again gaps open up early and persist. High scores (worse behaviour problems) are associated with lower economic status.

Source: Carneiro and Heckman (2003).

Average Anti-Social Behavior Score Percentile, by Income Quartile- Adjusted*

Again: *controlling for family environments factors, using regression analysis, the gaps greatly diminish.

Source: Carneiro and Heckman (2003).

Family Environments matter• Such regression adjustment cannot a establish causality a

causal interpretation of this evidence, that is instead supported by experimental evidence.

• The regression adjustments establish the importance of family factors in explaining ability gaps.

• This is a source of concern becuase a growing fraction of all American children are born into disadvantaged families.

• Those born into disadvantaged environments are receiving relatively less stimulation and child development resources than those from advantaged families.

Enriching Early Environments Can Compensate for Early Adversity

• Recent evidence suggests that early environments play a powerful role in shaping adult outcomes.

• Even though a lot of children are growing up in adverse environments and this will have negative consequences for American Society, the good news is that environments can be enhanced to promote the quality of children

• American Society must not passively watch its own decline but policy can matter.

Experimental Evidence: Perry Program

The Perry Pre-school Program enriched the lives of low income black children, with initial IQs below 85 at age 3, in Ypsilanti-Michigan between 1962 and 1967.

The program consists on:

• 2.5 hours classroom session per day on weekday mornings

• A weekly 90 minutes home visits by teacher on weekdays afternoon

• The length of each preschool year was 30 weeks.

• The groups have beeen followed through age 40.

Experimental Evidence: Perry Program Results

IQ scores become stable by age 10, suggesting a sensitive period for their formation below age 10. On average, the later remediation is given to a disadvantaged child, the less effective it is.

Experimental Evidence: Abecedarian Program

The Abecedarian Program shows a similar pattern.

• The Program studied 111 disadvantaged children, born between 1972 and 1977, whose families scored high on a risk index.

• The mean age at entry was 4.4 months. • The program was a year-round, full-day intervention

that continued through age 8. • The children were followed through age 21, and an age

30 follow-up study is in preparation.

Experimental Evidence: Abecedarian Results

The first years are critical and sensitive periods as in the Perry Program

Observations on these empirical studies

1. Skills beget skills and capabilities foster future capabilities.

2. Early learning confers value on acquired skills, which leads to self-reinforcing motivation to learn more.

3. Early mastery of a range of cognitive, social, and emotional competencies makes learning at later ages more efficient and therefore easier and more likely to continue.

SELF-PRODUCTIVITY: the capabilities produced at one stage augment the capabilities attained at later stages.

DYNAMIC COMPLEMENTARITY: capabilities produced at one stage of the life cycle raise the productivity of investment at subsequent stage.

Return to a marginal increase in investment at different stages of the life cycle

This figure shows the return to a marginal increase in investment at different stages of life cycle starting from a position of low but equal initial investment at all ages.

Early investments have the highest return; due to dynamic complementarity they must be followed by later investment if maximum value is to be realized.

Later Remediation is Costly

What if we do not invest early?

• Remedial interventions for disadvantaged adolescents who do not receive e strong initial foundation of skills have low rates of return.

• As currently congured, public job training programs, adult literacy services, prisoner rehabilitation programs, and education programs for disadvantaged adults at current levels of expenditure produce low economic returns.

Remediation is costly, but it is not impossible, except when we get to very low levels of initial conditions.

Returns to one more euro of investment as perceived initially and at age 3

Return to an extra dollar of investment as viewed at age 3 if optimal investment is made in the first three years (complementarity not too strong) and a dollar of investment is made at all ages (and is assumed to be less than the equilibrium amount)

Return to an extra dollar of investment as viewed at age 3 if suboptimal investment is made in the first three years and a dollar of investment is made at all ages (and is assumed to be less than the equilibrium amount).

A Model of Investment in Human Capabilities

Cunha and Heckman(2008) and Cunha, Heckman and Schennach (2007) estimate atechnology of capability production to understand how the skills of the children evolve in response to:

1. The stock of skills children have already accumulated (θ)

2. The investment made by their parents (I)

3. The stock of skills accumulated by parents (h)

• When the child is t years old, the stock of capability is made by:

•Substituting for θt, θt-1,…, repeatedly, one can rewrite the stock of capabilities at stage t + 1, θt+1, as a function of all past investments:

A model of Investment in Human Capabilities

Dynamic complementarity arises when:

Self productivity arises when:

• The joint effects of self-productivity and dynamic complementarity help to explain the high productivity of investment in disadvantaged young children but the lower return to investment in disadvantaged adolescent.

• for those disadvantaged children the stock of capabilities is low and hence the complementarity effect is lower.

• Suppose, for analytical simplicity, that there are 2 stages of childhood, (T = 2). The adult stock outcome is given by:

A model of Investment in Human Capabilities

• A general technology is the CES (Constant Elasticity of Substitution) production function:

• for and is a measure of how well late inputs substitute for early inputs. It governs

how easy it is to compensate for low levels of stage 1 investment in producing later adult capabilities.

• γ is a capability multiplier. It captures the productivity of early investment not only in directly boosting h’ (through self-productivity) but also in raising the productivity of I2 by increasing θ2 through first period investments. Thus I1 directly increases θ2 which in turn affects the productivity of I2 in forming h’. It captures the net effect of I1 on h’ through both self-productivity and direct complementarity.

A Model of Investment in Human Capabilities

When

• I1 and I2 are perfect substitutes

• Early deficits can be perfectly remedied by later intervention.

• However it may be not cost effective.

When

• I1 and I2 are perfect complements

• Early deficits cannot be remedied.• If investment in period 1 are very

low, no remediation is possible. • Adult human capital and

consequently adult succes is defined in the first period of life.

Consider 2 polar cases:

A Model of Investment in Human Capabilities

More generally, when is small:

• Low levels of early investment I1 are not easily remediated by later investment I2.

• High early investment should be followed with high late investment if the early investment is to be harvested.

Technology explains why returns to education are low in the adolescent years for disadvantaged adolescents (low h, low I1, low θ1).Without the proper foundation for learning (high levels of θ2) in technology adolescent interventions have low returns.

Conclusions

• The optimal policy is to invest relatively more in the early years. But early investment must be followed up to be effective.

• Later remediation is possible but to attain what is accomplished by early investment is much more costly.

• If society intervenes too late and individuals are at too low a level, later investment can be economically inefficient.

Practical Issues• Who should be targeted? Disadvantages children who do

not receive substantial amounts of parental investment in the early years.

• With what programs? Those targeted the early years.

• Who should provide the programs? Engage private industry and other social groups that: a) draw in private resources; b) create community support; c) represent diverse points of view.

• Who should pay for them? Programmes should be universal to avoid stigmatization, even though a problem of compliance can persist.

Not Only in the US...Young males not in employment, education or training in the OECD

Source: OECD social indicators, 2009Young females not in employment, education or training in the OECD

Source: OECD social indicators, 2009

2002 2006 Variation

Australia 7,2 7,4 0,2Austria 4,4 6,0 1,6Belgium 6,4 6,7 0,3Canada 7,2 6,7 -0,5Czech Republic 6,3 4,3 -2,0Denmark 2,4 4,1 1,6Finland .. 3,0 …France 3,2 6,2 3,0Germany 5,1 4,3 -0,9Greece 7,5 9,8 2,3Hungary 7,8 5,6 -2,2Ireland 4,5 4,7 0,2Italy 10,3 11,4 1,1Japan 10,6 10,5 -0,1Luxembourg .. …Netherlands 3,7 2,6 -1,1New Zealand .. 8,9 …Norway .. 3,4 …Poland 2,6 3,7 1,1Portugal 6,8 7,7 0,9Slovak Republic 13,5 6,8 -6,6Spain 7,5 10,6 3,1Sweden 3,3 4,3 1,1Switzerland 5,8 7,5 1,6UK 8,9 10,3 1,4USA 7,5 6,7 -0,8

2002 2006 Variation

Australia 6,9 6,7 -0,1Austria 8,1 7,1 …Belgium 7,3 7,5 0,2Canada 8,7 8,0 -0,7Czech Republic 5,8 4,7 -1,1Denmark 2,4 4,8 2,4Finland .. 4,1 …France 3,7 6,7 3,0Germany 4,3 4,1 -0,1Greece 5,2 7,9 2,7Hungary 8,3 6,4 -1,9Ireland 5,2 5,3 0,1Italy 10,8 12,2 1,4Japan 8,3 7,5 -0,8Luxembourg .. 4,4 ..Netherlands 4,0 3,3 -0,7New Zealand .. 7,7 …Norway .. 3,5 …Poland 3,5 3,8 0,4Portugal 7,7 7,8 0,1Slovak Republic 17,7 6,5 -11,2Spain 6,9 9,6 2,7Sweden 5,9 6,2 0,3Switzerland 5,8 7,7 1,9UK 8,2 11,5 3,2USA 6,4 6,0 -0,4

…but no (or little) emphasis on early years and skill formation policy

• As in the USA in many OECD countries there is an increasing young underclass neither working nor going to school.

• Currently in the OECD conuntries there is substantial spending on active labor market programs: ALMP.

• A large array of studies surveyed in Heckman, LaLonde, and Smith (1999) and Martin and Grubb (2001), as well as more recent studies, show that:

• Few ALMP lift most participants out of poverty.• They are primarily focused on older workers (older than 25).