Download - The Economics and Econometrics of Human Development

Transcript
Page 1: The Economics and Econometrics of Human Development

The Economics and the Econometrics

of Human Development

James J. HeckmanUniversity of Chicago

March 31, 2014Institute of Economic Growth

New Delhi

Econ and Ecom of Hum Dev

Page 2: The Economics and Econometrics of Human Development

Intergenerational Mobility and Inequality:The “Great Gatsby Curve”IGE: lnY1︸︷︷︸

Income in currentgeneration

= α + βlnY0︸︷︷︸Income of

parents

+ ε

India

Source: Corak 2011, Inequality from generation to generation: the United States in Comparison.Notes: Inequality is measured post-taxes and transfers. Gini index defined on household income. IGE measured by pre-taxand transfer income of individual fathers and sons. The IGE estimate for India is taken from Hnatkovska et al. (2013).

Econ and Ecom of Hum Dev

Page 3: The Economics and Econometrics of Human Development

Link to Appendix I

Econ and Ecom of Hum Dev

Page 4: The Economics and Econometrics of Human Development

(a) Should there be policies that attempt to lower the IGE?

(b) If so, what form should they take?

Econ and Ecom of Hum Dev

Page 5: The Economics and Econometrics of Human Development

Becker-Tomes-Solon

Heritability ↑ β ↑

Efficiency of parental investment ↑ β ↑

Inequality in wages ↑ β ↑

Inequality of public provision of investment ↑ β ↑

Econ and Ecom of Hum Dev

Page 6: The Economics and Econometrics of Human Development

• As a purely statistical matter, the more heterogeneity acrossunits within an area the greater the estimated β.

Econ and Ecom of Hum Dev

Page 7: The Economics and Econometrics of Human Development

• Main findings of the empirical literature

Econ and Ecom of Hum Dev

Page 8: The Economics and Econometrics of Human Development

Hart & Risley, 1995

Children enter school with “meaningful differences” in vocabulary knowledge.1. Emergence of the ProblemIn a typical hour, the average child hears:

Family Actual Differences in Quantity Actual Differences in QualityStatus of Words Heard of Words HeardWelfare 616 words 5 affirmatives, 11 prohibitions

Working Class 1,251 words 12 affirmatives, 7 prohibitionsProfessional 2,153 words 32 affirmatives, 5 prohibitions

2. Cumulative Vocabulary at Age 3

Cumulative Vocabulary at Age 3Children from welfare families: 500 wordsChildren from working class families: 700 wordsChildren from professional families: 1,100 words

Econ and Ecom of Hum Dev

Page 9: The Economics and Econometrics of Human Development

Hart & Risley, 1995

Children enter school with “meaningful differences” in vocabulary knowledge.1. Emergence of the ProblemIn a typical hour, the average child hears:

Family Actual Differences in Quantity Actual Differences in QualityStatus of Words Heard of Words HeardWelfare 616 words 5 affirmatives, 11 prohibitions

Working Class 1,251 words 12 affirmatives, 7 prohibitionsProfessional 2,153 words 32 affirmatives, 5 prohibitions

2. Cumulative Vocabulary at Age 3

Cumulative Vocabulary at Age 3Children from welfare families: 500 wordsChildren from working class families: 700 wordsChildren from professional families: 1,100 words

Econ and Ecom of Hum Dev

Page 10: The Economics and Econometrics of Human Development

Understanding Mechanisms

Econ and Ecom of Hum Dev

Page 11: The Economics and Econometrics of Human Development

Capabilities, the Technology of Capability Formation, andthe Essential Ingredients of a Life Cycle Model of Human

Development

Econ and Ecom of Hum Dev

Page 12: The Economics and Econometrics of Human Development

• Capabilities are multiple in nature.

• They encompass cognition, noncognitive and social preferencesand personality and preference traits, as well as health.

• Vector of capabilities at age t: θt.

• Capacities to act.

• Capabilities affect (a) resource constraints, (b) agentinformation sets and expectations, (c) parental information andexpectations and (d) preferences.

• They are stable across situations but evolve over time.

Econ and Ecom of Hum Dev

Page 13: The Economics and Econometrics of Human Development

Define relationships Mt mapping θt to outcomes Yt at stage t ofthe life cycle as:

Mt : θt → Yt. (1)

A core low-dimensional set of capacities generates a variety ofdiverse outcomes.

Econ and Ecom of Hum Dev

Page 14: The Economics and Econometrics of Human Development

Technology of Capability FormationCunha and Heckman (2007), Cunha (2007)

θt: a vector

θt+1 = ft( θt︸︷︷︸self productivityand cross effects

, It︸︷︷︸investment

broadly defined(parents, environment)

, θP ,t︸︷︷︸parental

capabilities

) (2)

Econ and Ecom of Hum Dev

Page 15: The Economics and Econometrics of Human Development

Complementarity Increases with Age

∂2θt+1

∂θt∂I ′t↑ t ↑ .

Econ and Ecom of Hum Dev

Page 16: The Economics and Econometrics of Human Development

Positive at later stages (t > t∗) of childhood

∂2θt+1

∂θt∂I ′t> 0, t > t∗.

Some evidence suggesting

∂2θt+1

∂θt∂I ′t≤ 0, t < t∗,

But even if positive, still smaller than at t > t∗.

Econ and Ecom of Hum Dev

Page 17: The Economics and Econometrics of Human Development

Complementarity coupled with self-productivity ⇒Dynamic Complementarity

It ↑ θt+1 ↑θt+1 ↑ ⇒ θt+s ↑ s > 1

∴∂2θt+s+1

∂It∂I ′t+s

> 0

Econ and Ecom of Hum Dev

Page 18: The Economics and Econometrics of Human Development

Family Preferences for Child Outcomes

Different versions of altruism, paternalism and beliefs about“proper” child rearing

Econ and Ecom of Hum Dev

Page 19: The Economics and Econometrics of Human Development

Family Resources Broadly Defined:Parental and Child Interactions

with Financial Markets and Access to Support from ExternalInstitutions

(a) Restrictions on transfers across generations

(b) Restrictions on transfers within generations (parental lifetimeliquidity constraints)

(c) Public provision of investment; public policy towards children

Econ and Ecom of Hum Dev

Page 20: The Economics and Econometrics of Human Development

Other Constraints on The Family Actively Being Investigated

(a) Information on parenting and other aspects of life acrossgenerations

(b) Genes

(c) Structure of household and assortative matching patterns(marriage markets)

Econ and Ecom of Hum Dev

Page 21: The Economics and Econometrics of Human Development

The Empirical and Theoretical ChallengeA Life Cycle Framework for Organizing Studies and Integrating Evidence

θt : Capacities at t; It: investment at t; θP ,t: Parental environmental variablesθt+1 = ft(θt, It,θP ,t): Technology of Skill Formation

θ−1

θ0

θ1

θ2

θT

θT+1

I−1

I0

I1

I2

IT

θP ,−1

θP ,0

θP ,1

θP ,2

θP ,T

Prenatal

Birth

EarlyChildhood, 0–3

LaterChildhood, 3–6

Adulthoodand Beyond

Econ and Ecom of Hum Dev

Page 22: The Economics and Econometrics of Human Development

A Bare-Bones Model of Parental Investment

Econ and Ecom of Hum Dev

Page 23: The Economics and Econometrics of Human Development

The Problem of the Parent

Link to Appendix II

Econ and Ecom of Hum Dev

Page 24: The Economics and Econometrics of Human Development

Life lasts four periods:

• Two periods as a passive child who makes no economicdecisions (and whose consumption is ignored) but who receivesinvestment in the form of goods.

• Two periods as a parent.

Econ and Ecom of Hum Dev

Page 25: The Economics and Econometrics of Human Development

Denote by θ1 the initial capability level of a child drawn from thedistribution J(θ1).(For notational simplicity, denote θP,t = θP = h.)Denoting by h′ the human capital of the child when child reachesadulthood

Econ and Ecom of Hum Dev

Page 26: The Economics and Econometrics of Human Development

Simplified parameterization of technology:

θt+1 = δt

γ1,tθ

φtt + γ2,t I

φtt︸ ︷︷ ︸

investment

+ γ3,thφt︸ ︷︷ ︸

parentalhumancapital

ρtφt

with 0 < γ1,t , γ2,t , γ3,t , ρt ≤ 1, φt ≤ 1,∑

k γk,nt = 1.

Econ and Ecom of Hum Dev

Page 27: The Economics and Econometrics of Human Development

Final Form Representation

If T = 2, ρ1 = ρ2 = 1, δ1 = 1, and φ1 = φ2 = φ ≤ 1, skills atadulthood, h′ = θ3 = θT+1 can be written as

h′ = δ2

γ1,2γ1,1θφ1 + γ1,2γ2,1︸ ︷︷ ︸

“Multiplier”

I φ1 + γ2,2Iφ2 + (γ3,2 + γ1,2γ3,1) hφ

.

Econ and Ecom of Hum Dev

Page 28: The Economics and Econometrics of Human Development

• If φ = 1, then investments at different periods are (almost)perfect substitutes.

Econ and Ecom of Hum Dev

Page 29: The Economics and Econometrics of Human Development

• Polar example arises in the Leontief case where φ→ −∞:

h′ = m2

(h, θ0,min(I1, I2)

)(3)

Econ and Ecom of Hum Dev

Page 30: The Economics and Econometrics of Human Development

• u(·): parental utility function

• β: discount factor

• r : real interest rate

• υ: parental altruism

• c1, c2 are consumption in parental life cycle periods 1 and 2

Econ and Ecom of Hum Dev

Page 31: The Economics and Econometrics of Human Development

The goal of the parent is to optimize:

V (h, b, θ1) = maxc1,c2,I1,I2

{u (c1) + βu (c2) + β2υE [V (h′, b′, θ′1)]

}(4)

subject to technology and budget constraints.

Econ and Ecom of Hum Dev

Page 32: The Economics and Econometrics of Human Development

Budget constraint is:

c1 + I1 +c2 + I2(1 + r)

+b′

(1 + r)2 = wh +wh

(1 + r)+ b. (5)

Econ and Ecom of Hum Dev

Page 33: The Economics and Econometrics of Human Development

• Tractable final form technology:

h′ = m2

h, θ0,

γ︸︷︷︸investmentmultiplier

(I1)φ + (1− γ) (I2)φ

ρφ

, (6)

for φ ≤ 1 and 0 ≤ γ ≤ 1, ρ ≤ 1.

Econ and Ecom of Hum Dev

Page 34: The Economics and Econometrics of Human Development

I1I2

=

(1− γ) (1 + r)

] ρ1−φ

. (7)

I1I2↑ as γ ↑, φ ↑, ρ ↑ and r ↓.

Econ and Ecom of Hum Dev

Page 35: The Economics and Econometrics of Human Development

• Important policy question: How easy (costly) is it to remediatelow I1 with high I2?

Econ and Ecom of Hum Dev

Page 36: The Economics and Econometrics of Human Development

Implications of the Model

Econ and Ecom of Hum Dev

Page 37: The Economics and Econometrics of Human Development

Borrowing Limits

Econ and Ecom of Hum Dev

Page 38: The Economics and Econometrics of Human Development

Liquidity Constraints Within the Life Cycles of Parents

• The parent, within his/her lifetime, faces a sequence ofconstraints at each stage of the life of the child.

Econ and Ecom of Hum Dev

Page 39: The Economics and Econometrics of Human Development

Denoting parental financial assets by a and allowing parental labormarket productivity to grow at exogenous rate g , these budgetconstraints can be represented by a sequence of constraints:

c1 + I1 +a

(1 + r)= wh + b (8)

and

c2 + I2 +b′

(1 + r)= w (1 + g) h + a (9)

and the borrowing constraints a ≥ a and b′ ≥ 0.Assume that a ≥ 0: parents cannot borrow against their own futureincome.Child investments at different ages are not perfect substitutes(φ < 1).

Econ and Ecom of Hum Dev

Page 40: The Economics and Econometrics of Human Development

Parental utility: u (c) =(cλ − 1

)/λ.

I1I2

=

(1− γ) (1 + r)

) 11−φ

︸ ︷︷ ︸unconstrained ratio

[β(1 + r)]1

1−φ

(c1

c2

) 1−λ1−φ

︸ ︷︷ ︸=1 if unconstrained,<1 if constrained

.(10)

λ ≤ 1

Econ and Ecom of Hum Dev

Page 41: The Economics and Econometrics of Human Development

• Cunha, Heckman, and Schennach (2010):1/(1− φ) = .3 (φ

.= −2).

• Attanasio and Browning (1995): λ ∈ [−3,−1.5]

• (1− λ)/(1− φ) ∈ [0.83, 1.3]. Family resource influence onrelative investment.

• Dynamic complementarity coupled with borrowing constraintsin the early years raises a potentially serious marketimperfection.

Econ and Ecom of Hum Dev

Page 42: The Economics and Econometrics of Human Development

Introducing income uncertainty

Econ and Ecom of Hum Dev

Page 43: The Economics and Econometrics of Human Development

Empirical Estimates of Credit Constraints and the Effects ofFamily Income on Child Outcomes

Econ and Ecom of Hum Dev

Page 44: The Economics and Econometrics of Human Development

Recent Evidence on the Importance of Credit Constraintsand Family Income

Econ and Ecom of Hum Dev

Page 45: The Economics and Econometrics of Human Development

College attendance by AFQT and Family Income Quartiles (1979)

Source: Belley and Lochner (2007).

Econ and Ecom of Hum Dev

Page 46: The Economics and Econometrics of Human Development

College attendance by AFQT and Family Income Quartiles (1997)

Source: Belley and Lochner (2007).

Econ and Ecom of Hum Dev

Page 47: The Economics and Econometrics of Human Development

College attendance by AFQT and Family Income Quartiles (1979 and1997 placed on one graph)

Lochner 1979

Lochner 1997

Source: Belley and Lochner (2007).

Econ and Ecom of Hum Dev

Page 48: The Economics and Econometrics of Human Development

• More people going to college at virtually all quartiles ofability and income.

• Increases in college going is strongest for the lowest abilitygroup, especially less able children with richer parents.

Econ and Ecom of Hum Dev

Page 49: The Economics and Econometrics of Human Development

• This provides no firm evidence for or against credit constraints.

Econ and Ecom of Hum Dev

Page 50: The Economics and Econometrics of Human Development

Studies on the role of income on children’s outcomes and oncredit constraints

Link to Appendix III

Econ and Ecom of Hum Dev

Page 51: The Economics and Econometrics of Human Development

Summary of the Evidence on Family Income, CreditConstraints, and Child Development

• The literature on credit constraints and family income shows that higherlevels of parental resources, broadly defined, promote child outcomes.

• However, a clear separation of parental resources into pure income flows,parental environmental variables and parental investment has not yet beendone.

• It is premature to advocate pure income transfer policies as effective waysfor promoting child welfare and promoting social mobility.

• What studies exist suggest very weak effects of income transfers onchildhood test scores.

• The evidence from the structural models supports this conclusion.

• Many of the studies show effects of prices, not constraints or pure income.

Econ and Ecom of Hum Dev

Page 52: The Economics and Econometrics of Human Development

Structural Models of Parental Investment

Link to Appendix IV

Econ and Ecom of Hum Dev

Page 53: The Economics and Econometrics of Human Development

Recent Extensions

(a) Parental time (mother and father) (Del Boca et al., 2013; Gayleet al., 2013)

(b) Role of multiple parents (Del Boca et al., 2013; Gayle et al.,2013)

(c) Multiple children (Del Boca et al., 2013; Gayle et al., 2013)

(d) Parental learning about technology (Badev and Cunha, 2012;Cunha, 2012; Cunha et al., 2013)

(e) Fertility (Gayle et al., 2013)

(f) Marriage market (Gayle et al., 2013)

(g) Multiple capabilities (Cunha and Heckman, 2008; Cunha,Heckman, and Schennach, 2010)

Econ and Ecom of Hum Dev

Page 54: The Economics and Econometrics of Human Development

Estimates of the Technology of Capability Formation in theLiterature

(a) Most of literature focuses on cognitive skill technology

(b) Noncognitive skills recently introduced (Cunha and Heckman)

(c) Noncognitive skills foster production of cognitive skills

(d) Most analysts use linear technologies

(e) Nonlinearity essential to capture dynamic complementarity

(f) When estimated complementarity increases with the stage ofthe life cycle (dynamic complementarity)

(g) Measurement error empirically important

Econ and Ecom of Hum Dev

Page 55: The Economics and Econometrics of Human Development

Table 1: Capability Production Functions

Skill Output FunctionalCognitivea Non-cognitivea Health Form Anchoring

Todd and Wolpin (2003) X X X Linear XBernal and Keane (2010) X X X Linear X

Cunha and Heckman (2008) X X X Linear Xb

Cunha et al. (2010) X X X CES XTodd and Wolpin (2007) X X X Linear XCunha (2007) X X X CES XDel Boca et al. (2013) X X X Log-Linear X

Caucutt and Lochner (2012) X X X CES Xj

Bernal (2008) X X X Linear XGayle et al. (2013) Xg Xg X N/S XBernal and Keane (2011) X X X Linear X

Econ and Ecom of Hum Dev

Page 56: The Economics and Econometrics of Human Development

Table 1 (continued): Capability Production Functions

Self Productivitya Cross Productivitya Increasing Investments / Skill

Cognitive Non-cognitive Cognitive Non-cognitive Complementarity over Timeh

Todd and Wolpin (2003) X- N/A X X UBernal and Keane (2010) X- N/A X X UCunha and Heckman (2008) 0.977 0.884 0.003 0.028 UCunha et al. (2010) 0.487/0.902c 0.649/0.868c 0.000/0.008c 0.083/0.011c XTodd and Wolpin (2007) 0.21 - 0.34d X X U

Cunha (2007) 0.735/0.799 /0.872f X X XDel Boca et al. (2013) (0.14, 0.503)/(0.172, 0.922)f X X N/ACaucutt and Lochner (2012) X- N/A X X N/ABernal (2008) X- N/A N/A X UGayle et al. (2013) N/S N/S X N/SBernal and Keane (2011) X- N/A X X U

Econ and Ecom of Hum Dev

Page 57: The Economics and Econometrics of Human Development

Investment with Multiple Children

Econ and Ecom of Hum Dev

Page 58: The Economics and Econometrics of Human Development

Representation for the utility parents receive from N children:

V c =

(N∑

k=1

ωkVσk

) 1σ

(11)

where Vk represents the relevant outcome for each child which isvalued by parents Behrman et al. (1982).

Econ and Ecom of Hum Dev

Page 59: The Economics and Econometrics of Human Development

Targeting Relatively More Investment Toward DisadvantagedChildren Can Be Socially Efficient

Link to Appendix V

Econ and Ecom of Hum Dev

Page 60: The Economics and Econometrics of Human Development

In a one period of childhood problem where parents (or socialplanners) seek to maximize the aggregate of adult skills (θ2):

θA2 + θB2

subject to E = p1(IA1 + IB1 ),

the first order condition is

F.O.C.: f(1)

2

(γθB1 , I

A1

)= f

(1)2

(θB1 , I

B1

).

Econ and Ecom of Hum Dev

Page 61: The Economics and Econometrics of Human Development

sign

(∂IA1∂γ

)= sign

(f

(1)12 (·)

)γ=1

.

Parents (social planners) invest more in the disadvantaged if inputsare substitutes with initial endowments and they invest less if theyare complements.

Econ and Ecom of Hum Dev

Page 62: The Economics and Econometrics of Human Development

Suppose that parents (or social planners) seek to maximize

θA3 + θB3

subject toE = p1(IA1 + IB1 ) + p2(IA2 + IB2 ).

Econ and Ecom of Hum Dev

Page 63: The Economics and Econometrics of Human Development

Consider the following two-stage model of childhood investment.

θ3 = f (2)(θ2, I2) (12)

θ2 = f (1)(θ1, I1) (13)

where θ3 represents the level of skill at the beginning of adulthood.

Econ and Ecom of Hum Dev

Page 64: The Economics and Econometrics of Human Development

Even if (f(1)

12 > 0), greater first period investment in the initiallydisadvantaged child may be optimal. This is more likely (ceterisparibus)

(a) the more steeply diminishing is the productivity of second period

skills (f(2)

22 );

(b) the greater the self productivity of the stock of skills in the first

period (f(1)

1 = ∂θ2

∂θ1);

(c) the smaller first period complementarity (f(1)

21 ) relative to secondperiod complementarity and absolutely

Econ and Ecom of Hum Dev

Page 65: The Economics and Econometrics of Human Development

(d) the more rapidly diminishing the marginal productivity of

θ1(f(1)

11 );

(e) the greater the second period complementarity (f(2)

12 );

(f) the greater the first period productivity of investment (f(1)

2 ) and

(g) the more rapidly diminishing the productivity of second period

investment (f(2)

22 ).

Econ and Ecom of Hum Dev

Page 66: The Economics and Econometrics of Human Development

An Example

Suppose that, for each child k , the outcome of interest for parentsare children’s earnings Ek and that they are function of children’sadult human capital determined by genes (θ1,k) and early (I1,k) andlate (I2,k) parental investments.

Ek = wf 2(θ2,k , I2,k) = τ 2(γ2θ

φ2

2,k + (1− γ2)I φ2

2,k

) ρ2φ2 (14)

with θ2,k = f 1(θ1,k , I1,k) = τ 1(γ1θ

φ1

1,k + (1− γ1)I φ1

1,k

) ρ1φ1 (15)

Econ and Ecom of Hum Dev

Page 67: The Economics and Econometrics of Human Development

w is common across families and siblings. Human capital is chosenso that w = 1. The budget constraint faced by the parents withtotal resources Re is:

p1

n∑k=1

I1 + p2

n∑k=1

I2 = Re . (16)

Econ and Ecom of Hum Dev

Page 68: The Economics and Econometrics of Human Development

Measure of parental compensation with respect to initial inequality.Define the parameter τ as:

τ ≡(Ei

Ej

)/(θ1,i

θ1,j

). (17)

If τ = 1, the parents perfectly translate initial differences intoearnings differences.

Econ and Ecom of Hum Dev

Page 69: The Economics and Econometrics of Human Development

Figure 1: Earnings Equalization

τ

ρ1

Notes: The parental preference parameters used in the simulation are σ = 1 and ωi = ωj = 0.5. Total resources are Re = 4.The technology of skill formation parameters, capturing increasing complementarity between skills and investments over time,are: γ1 = γ2 = 0.5, φ1 = 0.6, φ2 = −0.5, ρ2 = 1. The parameter ρ1 defines the degree of homogeneity of the first periodtechnology. We vary the value of ρ1 over the range [0.1, 1]. Child i has a skill endowment of 5 while child j of 1.

Econ and Ecom of Hum Dev

Page 70: The Economics and Econometrics of Human Development

Figure 2a: Parental Investments

Ratio Early to Late Investments

More endowed child

Less endowed child

1Notes: The solid line refers to the most endowed child, the dashed line to the least endowed child. The parameters used areas in Figure 1.

Econ and Ecom of Hum Dev

Page 71: The Economics and Econometrics of Human Development

Figure 2b: Parental Investments

Levels of Early Investments

More endowed child

Less endowed child

1

Notes: The solid line refers to the most endowed child, the dashed line to the least endowed child. The parameters used areas in Figure 1.

Econ and Ecom of Hum Dev

Page 72: The Economics and Econometrics of Human Development

Figure 2c: Parental Investments

Levels of Late Investments

More endowed child

Less endowed child

1Notes: The solid line refers to the most endowed child, the dashed line to the least endowed child. The parameters used areas in Figure 1.

Econ and Ecom of Hum Dev

Page 73: The Economics and Econometrics of Human Development

Testing and Operationalizing the Theory

Econ and Ecom of Hum Dev

Page 74: The Economics and Econometrics of Human Development

Capabilities as Determinants of Functionings

Econ and Ecom of Hum Dev

Page 75: The Economics and Econometrics of Human Development

Decompose the θt vector into three subvectors:

θt = (θC,t,θN ,t,θH,t) (18)

where θC,t is a vector of cognitive abilities (e.g., IQ) at age t, θN ,t

is a vector of noncognitive abilities (e.g., patience, self-control,temperament, risk aversion, discipline, and neuroticism) at age t,and θH,t is a vector of health stocks for mental and physical healthat age t.

Econ and Ecom of Hum Dev

Page 76: The Economics and Econometrics of Human Development

• Capabilities, combined with effort, incentives and purchasedinputs determine functionings.

Econ and Ecom of Hum Dev

Page 77: The Economics and Econometrics of Human Development

• Functionings (task j) at age t:

Yj ,t = ψj ,t(θt, ej ,t ,Xj,t), j ∈ {1, . . . , Jt} and t ∈ {1, . . . , 2T}(19)

• Yj ,t : outcome from activity j at time t

• θt is the vector of capabilities at age t

• Xj,t is a vector of purchased inputs that affect the functionings

• ej ,t is effort in task

• T is the length of childhood

• T is the length of adulthood

• 2T is total lifetime

Econ and Ecom of Hum Dev

Page 78: The Economics and Econometrics of Human Development

Effort: ej ,t

ej ,t = δj(θt,At,Xj,t,Raj,t(It−1) | u). (20)

• At : environment

• Raj,t : incentives

Econ and Ecom of Hum Dev

Page 79: The Economics and Econometrics of Human Development

Estimating and Interpreting the Distribution of Capabilities,the Maps Between Capabilities and Functionings and the

Technology of Capability Formation

Econ and Ecom of Hum Dev

Page 80: The Economics and Econometrics of Human Development

Nonparametric Factor Models Are Natural Frameworks forEstimating Capabilities and Determining Frontier Capability

Sets

Econ and Ecom of Hum Dev

Page 81: The Economics and Econometrics of Human Development

• Low dimensional capabilities (“factors”) generate a highdimensional set of functionings.

• Dimension and factor structures selected through a variety ofmethods.

• Exploratory factor analysis.

• Novel Bayesian procedures—avoid arbitrary methods inExploratory Factor Analysis.

Econ and Ecom of Hum Dev

Page 82: The Economics and Econometrics of Human Development

Technology of Skill Formation

•θk,t+1 = fs,k (θt , Ik,t , θP,t) (21)

for k ∈ {C ,N ,H}, t ∈ {1, 2, . . . ,T}.

Econ and Ecom of Hum Dev

Page 83: The Economics and Econometrics of Human Development

Identification of the Technology of Skill Formation

• To estimate the technology of skill formation: Have to solvethree problems.

1 Don’t observe (θt , Ik,t , θP,t) directly, but have manymeasurements on it. Measurement error in nonlinearsystems.

2 Don’t know which scale to use to measure components of θt.Anchor test scores on adult outcomes.

3 Investment Ik,t may be chosen by parents based on informationthat may be unobserved by the econometrician (ηk,t).Endogeneity of investment.

Econ and Ecom of Hum Dev

Page 84: The Economics and Econometrics of Human Development

Identification of the Technology of Skill Formation

• To estimate the technology of skill formation: Have to solvethree problems.

1 Don’t observe (θt , Ik,t , θP,t) directly, but have manymeasurements on it. Measurement error in nonlinearsystems.

2 Don’t know which scale to use to measure components of θt.Anchor test scores on adult outcomes.

3 Investment Ik,t may be chosen by parents based on informationthat may be unobserved by the econometrician (ηk,t).Endogeneity of investment.

Econ and Ecom of Hum Dev

Page 85: The Economics and Econometrics of Human Development

Estimating Functionings and Extracting Factors:Multiple Capabilities Shape Human Achievement Across a

Variety of Dimensions

Econ and Ecom of Hum Dev

Page 86: The Economics and Econometrics of Human Development

• The relationship between capabilities estimated in the recentliterature and traditional preference parameters (timepreference, leisure, risk aversion, etc.) is weak. Dohmen, Falk,et al. (2012)

• Suggests that a richer set of preference and constraintdescriptions may characterize choice behavior.

Econ and Ecom of Hum Dev

Page 87: The Economics and Econometrics of Human Development

Decile of Cognitive

1 2 3 4 5 6 7 8 9 10

Decile of Socio-Emotional12

34567

8910

Pro

bab

ility

0

0.2

0.4

0.6

0.8

1

Decile of Cognitive

1 2 3 4 5 6 7 8 9 10

Pro

bab

ility

0

0.2

0.4

0.6

0.8

1

Fra

ctio

n0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Probability

Decile of Socio-Emotional

1 2 3 4 5 6 7 8 9 10

Pro

bab

ility

0

0.2

0.4

0.6

0.8

1

Fra

ctio

n

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Probability

Figure 3: The Probability of Educational Decisions, by EndowmentLevels, Dropping from Secondary School vs. Graduating(Source: Heckman et al., 2011)

Econ and Ecom of Hum Dev

Page 88: The Economics and Econometrics of Human Development

The same low-dimensional vector of capabilities predicts a widevariety of outcomes for:

• Crime

• Wages

• Health

• Healthy behaviors (smoking, drug use)

• Trust

• Voting behavior

• Employment

• Participation in welfare

Econ and Ecom of Hum Dev

Page 89: The Economics and Econometrics of Human Development

Estimates of Technologies of Capability Formation and SomeImplications

Econ and Ecom of Hum Dev

Page 90: The Economics and Econometrics of Human Development

• Capabilities evolve over the life cycle

• Parental investments explain 34% of variance of educationalattainment

• Self-productivity becomes stronger as children become older,for both cognitive and noncognitive skill formation(i.e., ∂θt+1

∂θt↑ t).

• Strong cross effects (noncognitive skills foster cognitiveinvestment)

• Complementarity between cognitive skills and investmentbecomes stronger as children become older. The elasticity ofsubstitution for cognitive production is smaller in second stageproduction

Econ and Ecom of Hum Dev

Page 91: The Economics and Econometrics of Human Development

• Emerging dynamic complementarity.

• It is more difficult to compensate for the effects of adverseenvironments on cognitive endowments at later ages than it isat earlier ages. This pattern of the estimates helps to explainthe evidence on ineffective cognitive remediation strategies fordisadvantaged adolescents reported in Cunha et al. (2006),Cunha (2007), and later papers.

• Complementarity between noncognitive skills and investmentsstays roughly constant over the life cycle.

• Suggests that later life investments should be more focused onpromoting noncognitive—personality—skills.

• The evidence on which adolescent interventions are successfulis consistent with this evidence.

Econ and Ecom of Hum Dev

Page 92: The Economics and Econometrics of Human Development

The Implications of the Estimates for Design of Policy

• Targeted strategies

• Consider a policy for a social planner to optimize the stock ofeducation in society.

• Assume (for simplicity) full control of investment (ignoresparental responses)

• The bulk of the evidence in the child development literatureshows reinforcement of investment by parents.

• No consideration of social fairness, equality of opportunity orequality of final outcomes—just efficiency.

• Yet with these estimates the optimal policy invests the most inthe disadvantaged.

• As an empirical matter, social justice is enhanced by what isproductively efficient.

Econ and Ecom of Hum Dev

Page 93: The Economics and Econometrics of Human Development

Socially Optimal Early and Late Levels of Investment by InitialCapabilities

Child Initial Cognitive Skill

Child Initial Noncognitive Skill

Child Initial Noncognitive Skill

Child Initial Cognitive Skill

Source: Cunha et al. (2010). Optimal investments to maximize aggregate education in society.

Econ and Ecom of Hum Dev

Page 94: The Economics and Econometrics of Human Development

0.5 1 1.5 2 2.50

0.5

1

1.5

2

2.5

3

3.5

Figure 5Densities of Ratio of Early to Late Investments

Maximizing Aggregate Education Versus Minimizing Aggregate Crime

Ratio Early to Late Investment

EducationCrime

Econ and Ecom of Hum Dev

Page 95: The Economics and Econometrics of Human Development

Using Economics to Go Behind Estimated ProgramTreatment Effects and Beyond Meta-Analyses of Treatment

Effects:Linking the Program Evaluation Literature with

the Economics of the Family• Widely used “metanalyses” on early childhood do not recognizethat various interventions in early childhood previouslyimplemented differ.

1 The populations targeted differ.2 The objectives and curricula of the programs differ.3 The measurement systems for backgrounds and outcomes

differ among each other and also with observational studies.4 The methods of evaluation differ.5 Need to integrate the studies of family influence with the

intervention studies to understand how interventions affectfamily life.

6 Need to compare alternative policies in comparable metrics;i.e., rates of return to policies or cost-benefit analyses.

Econ and Ecom of Hum Dev

Page 96: The Economics and Econometrics of Human Development

Lessons From and Lessons For the Intervention Literature

Link to Appendix VI

Econ and Ecom of Hum Dev

Page 97: The Economics and Econometrics of Human Development

The Mechanisms Producing the Treatment Effects:A Case Study

Econ and Ecom of Hum Dev

Page 98: The Economics and Econometrics of Human Development

Cognitive Evolution by Age, Perry MalesMale Cognitive Dynamics

79.2 94.9 95.4 91.5 91.1 88.3 88.4 83.7

77.8 83.1 84.8 85.8 87.7 89.1 89.0 86.0

75

80

85

90

95

100

105

Treatment

Control

IQ

4 5 6 7 8 9 10EntryAge

Treatment

Control

Econ and Ecom of Hum Dev

Page 99: The Economics and Econometrics of Human Development

Personal Behavior Index by Treatment Group

Control Treatment

0.2

.4.6

.81

dens

ity

2 2.5 3 3.5 4 4.5 5

®

0.2

.4.6

.81

dens

ity

2 2.5 3 3.5 4 4.5 5

®

Econ and Ecom of Hum Dev

Page 100: The Economics and Econometrics of Human Development

Socio-Emotional Index by Treatment Group

Control Treatment

0.2

.4.6

.8

dens

ity

1 2 3 4 5

0

.2.4

.6.8

dens

ity1 2 3 4 5

Econ and Ecom of Hum Dev

Page 101: The Economics and Econometrics of Human Development

Decomposition of Treatment Effects, Males

32

THE

AMERIC

AN

ECONOMIC

REVIE

WMONTH

YEAR

0.056

0.149

0.077

0.013

0.130

0.085

0.136

0.046

0.089

0.062

0.071

0.071 0.557

0.499

0.403

0.086

0.161

0.032

0.018

0.204

0.088

0.141

0.027

0.144

0.246

0.114

0% 20% 40% 60% 80% 100%

Use heroin, age 40(-0.143*)

Employed, age 40 (0.200**)

# of lifetime arrests, age 40 (-4.20*)

# of adult arrests (misd.+fel.), age 40 (-4.26**)

# of felony arrests, age 40 (-1.14*)

# of misdemeanor arrests, age 40 (-3.13**)

Use tobacco, age 27 (-0.119*)

Monthly income, age 27 (0.876**)

# of adult arrests (misd.+fel.), age 27 (-2.33**)

# of felony arrests, age 27 (-1.12)

# of misdemeanor arrests, age 27 (-1.21**)

CAT total at age 14, end of grade 8 (0.566*)

Cognitive Factor Externalizing Behavior Academic Motivation Other Factors

Figure 6. Decompositions of Treatment Effects on Outcomes, Males

Note: The total treatment effects are shown in parentheses. Each bar represents the total treatment effect normalized to 100 percent. One-sided p-valuesare shown above each component of the decomposition. The figure is a slightly simplified visualization of Tables L.10 and L.14: small and statisticallyinsignificant contributions of the opposite sign are set to zero. See Web Appendix L for detailed information about the simplifications made to producethe figure. “CAT total” denotes California Achievement Test total score normalized to control mean zero and variance of one. Asterisks denote statisticalsignificance: * – 10 percent level; ** – 5 percent level; *** – 1 percent level. Monthly income is adjusted to thousands of year-2006 dollars using annualnational CPI. Econ and Ecom of Hum Dev

Page 102: The Economics and Econometrics of Human Development

Health OutcomesLink to Appendix VII

Econ and Ecom of Hum Dev

Page 103: The Economics and Econometrics of Human Development

Attachment, EngagementToward a Deeper Understanding of Parenting and Learning

• In both Perry and ABC (and many other interventions) a mainchannel of influence is on the parent-child interactions.

• Enhanced attachment and engagement of parents.

• This has important implications for how we model familyinfluence.

Econ and Ecom of Hum Dev

Page 104: The Economics and Econometrics of Human Development

Mechanisms—producing effects

(a) Information

(b) Changing preferences of parents

(c) Parental response to child’s curiosity and interest induced byparticipation in the program

Econ and Ecom of Hum Dev

Page 105: The Economics and Econometrics of Human Development

Parental response to Perry Preschool Program

1020

3040

5060

Pro

port

ion

−.015 −.01 −.005 0 .005 .01 .015Belief in Importance of Parenting

Control Treatment

Econ and Ecom of Hum Dev

Page 106: The Economics and Econometrics of Human Development

Table 2: Models of Parent-Child Interaction(“X” means present; “X” means absent)

ParentalMonetary

Investments

Discordance inPreferences

between Parentand Child

MultipleChildren

ParentalIncentives forChild Effort

Cosconati (2013) X Xa,b X Xc

Akabayashi (2006) X Xa X Xd,e

Hao et al. (2008) X Xb X Xe

Lizzeri and Siniscalchi (2008) X Xd X X

a Difference in discount factors. b Differences in utility functions. c Restrictions on leisure. d Differences in knowledge about

proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the

effects of time investments. h Implications from the model are empirically tested.

Econ and Ecom of Hum Dev

Page 107: The Economics and Econometrics of Human Development

Table 2 (continued): Models of Parent-Child Interaction(“X” means present; “X” means absent)

Effort ProducesGreater Capability

ParentalLearning aboutChild Quality

Parental ActionsFacilitate

Acquisition ofInformation

ParentalBeliefs CanDivergefrom Truth

Cosconati (2013) X X X X

Akabayashi (2006) X X X Xf

Hao et al. (2008) X X X X

Lizzeri and Siniscalchi (2008) X X X X

a Difference in discount factors. b Differences in utility functions. c Restrictions on leisure. d Differences in knowledge about

proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the

effects of time investments. h Implications from the model are empirically tested.

Econ and Ecom of Hum Dev

Page 108: The Economics and Econometrics of Human Development

Table 2 (continued): Models of Parent-Child Interaction(“X” means present; “X” means absent)

Child’s EffortObservable

Child’sHuman Capital

Observable

Model IsEstimated

Cosconati (2013) X X X

Akabayashi (2006) X X X

Hao et al. (2008) X X Xg

Lizzeri and Siniscalchi (2008) X X X

a Difference in discount factors. b Differences in utility functions. c Restrictions on leisure. d Differences in knowledge about

proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the

effects of time investments. h Implications from the model are empirically tested.

Econ and Ecom of Hum Dev

Page 109: The Economics and Econometrics of Human Development

An Economic Model of Mentoring and Scaffolding(Garcıa, Heckman, Mosso, and Wang, 2013)

Econ and Ecom of Hum Dev

Page 110: The Economics and Econometrics of Human Development

Mentor’s Problem

Yt : Measured output of child at age tθt : Capabilities at outsetθt : Parental targetsIt : Parental investment at age tat : Child effort at age tThe mentor’s problem is to minimize

Vt(Yt) = minIt ,...IN−1

E

[N−1∑τ=t

βτ(θτ′Q θτ + Iτ

′RIτ)

+ θN′Qf θN |Yt

]

where Q,Qf ,R ≥ 0.

Econ and Ecom of Hum Dev

Page 111: The Economics and Econometrics of Human Development

Technology: θt+1 = Aθt + BIt + F at + wt

θt+1 = Ψ(θt , It , at)

θt+1 = Ψ(θt , It , at)

Yt = C θt + Dat + vt

θt = θt − θtIt = It − It

at = at − at .

Econ and Ecom of Hum Dev

Page 112: The Economics and Econometrics of Human Development

Child’s Problem(with development of agency of the child)

• The child chooses a sequence of effort (a1, . . . , aN−1) tomaximize her utility in each period.

• Her value function at time t is:

Jt(Yt) = maxat ,...,aN−1

(λt(θt)J

1t (Yt) + (1− λt(θt))J2

t (Yt))

Econ and Ecom of Hum Dev

Page 113: The Economics and Econometrics of Human Development

J1t (Yt) = max

at ,...,aN−1

E

[N−1∑τ=t

βτ(− (h′It)

η

2γ(at − a)′ (at − a + α′It)

)|Yt

]

J2t (Yt) = max

at ,...,aN−1

E

[N−1∑τ=t

βτ

(−(h′RP

t (at))η

2γ(at − a)′ (at − a) + α′It

)|Yt

]• RP

t (·) is the best response function of the mentor

Econ and Ecom of Hum Dev

Page 114: The Economics and Econometrics of Human Development

Integrating Experimental Studies with Family InfluenceStudies

Econ and Ecom of Hum Dev

Page 115: The Economics and Econometrics of Human Development

• IGt : government investment

• IPt : private (family) investment

• Government technology: f G (θt , θPt , IGt , IPt )

• Private technology: f P(θt , θPt , IGt , IPt )

• Mixed technology: f M(θt , θPt , IGt , IPt )

Econ and Ecom of Hum Dev

Page 116: The Economics and Econometrics of Human Development

• Studies under way doing this (Fan, Hai, Heckman, Wei, andZhang, 2013)

Econ and Ecom of Hum Dev

Page 117: The Economics and Econometrics of Human Development

What about promoting education?

Econ and Ecom of Hum Dev

Page 118: The Economics and Econometrics of Human Development

Early development is as important as education in promotingwages, employment, and health.

Econ and Ecom of Hum Dev

Page 119: The Economics and Econometrics of Human Development

Disparities by Education (Post-compulsory Education)

• Education, Wages, Employment, and Health

Note: Conti and Heckman (2010). Author’s calculations using British Cohort Study, 1970.

Econ and Ecom of Hum Dev

Page 120: The Economics and Econometrics of Human Development

Disparities by Education (Post-compulsory Education)

• Education, Wages, Employment, and Health

Note: Conti and Heckman (2010). Author’s calculations using British Cohort Study, 1970.

Econ and Ecom of Hum Dev

Page 121: The Economics and Econometrics of Human Development

Disparities by Education (Post-compulsory Education)

• Education, Wages, Employment, and Health

Note: Conti and Heckman (2010). Author’s calculations using British Cohort Study, 1970.

Econ and Ecom of Hum Dev

Page 122: The Economics and Econometrics of Human Development

Summary

Econ and Ecom of Hum Dev

Page 123: The Economics and Econometrics of Human Development

The Empirical and Theoretical ChallengeA Life Cycle Framework for Organizing Studies and Integrating Evidence

θt : Capacities at t; It: investment at t; θP ,t: Parental environmental variablesθt+1 = ft(θt, It,θP ,t): Technology of Skill Formation

θ−1

θ0

θ1

θ2

θT

θT+1

I−1

I0

I1

I2

IT

θP ,−1

θP ,0

θP ,1

θP ,2

θP ,T

Prenatal

Birth

EarlyChildhood, 0–3

LaterChildhood, 3–6

Adulthoodand Beyond

Econ and Ecom of Hum Dev

Page 124: The Economics and Econometrics of Human Development

Predistribution Not Simply Redistribution

Econ and Ecom of Hum Dev

Page 125: The Economics and Econometrics of Human Development

(a) Should there be policies that attempt to lower the IGE?

(b) If so, what form should interventions take?

Econ and Ecom of Hum Dev

Page 126: The Economics and Econometrics of Human Development

Appendix I

Econ and Ecom of Hum Dev

Page 127: The Economics and Econometrics of Human Development

USA

Canada

DenmarkFinland

France

Germany

Norway

Sweden

UKItaly

Japan0

.1.2

.3.4

.5In

terg

en. E

last

icity

of E

arni

ngs

(IGE)

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Corak's Chosen IGE OLS Slope=2.19, p-value=.003

• In Corak (2013), the Great Gatsby Curve has significant,positive slope in OLS regression.

Econ and Ecom of Hum Dev

Page 128: The Economics and Econometrics of Human Development

USA

Canada

Denmark

Finland

France

Germany

Norway

Sweden

UKItaly

Japan

0.1

.2.3

.4.5

Inte

rgen

. Ela

stici

ty o

f Ear

ning

s (IG

E)

.34 .38 .42 .46Gini Coefficient, Before Taxes and Transfers

Corak's Chosen IGE OLS Slope=1.82, p-value=.059

• However, there is a methodological mistake in Corak (2013):after tax-and-transfer Gini coefficients are compared to beforetax-and-transfer IGE.

• Correcting this mistake makes the Great Gatsby Curveinsignificantly sloped.

Econ and Ecom of Hum Dev

Page 129: The Economics and Econometrics of Human Development

USA

Canada

DenmarkFinland

FranceGermany

NorwaySweden

UKItaly

Japan

0.1

.2.3

.4.5

Inte

rgen

. Ela

stici

ty o

f Ear

ning

s (IG

E)

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Corak's Chosen IGE except USA OLS Slope=0.70, p-value=.003

• Due to the anchoring scheme employed by Corak (2013), theslope of the Great Gatsby Curve is arbitrarily controlled by thepartly subjective choice of USA IGE estimate.

Econ and Ecom of Hum Dev

Page 130: The Economics and Econometrics of Human Development

USACanada

Denmark

Finland

France

Germany

NorwaySweden

UK

Italy

Japan

0.1

.2.3

.4.5

Inte

rgen

. Ela

stici

ty o

f Ear

ning

s (IG

E)

.34 .38 .42 .46Gini Coefficient, Before Taxes and Transfers

Alternate IGE Choice OLS: Slope=-0.16, p-value=.869

• By replacing only three of the countries’ IGE estimates withplausible alternates from the literature, we arrive at anegatively-sloped Great Gatsby Curve.

• Conclusion: Corak’s Great Gatsby Curve is not robust. Thisdoes not disprove the hypothesis that inequality and IGE arepositively related.

Econ and Ecom of Hum Dev

Page 131: The Economics and Econometrics of Human Development

USA

Canada

Denmark

Finland

France

Germany

Norway

Sweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stic

ity (F

athe

r to

Son

Earn

ings

)

.2 .25 .3 .35

Corak's Preferred Data OLS (Slope=2.05, p-value=.008)

Corak's Great Gatsby Curve

Source: Corak, JEP(2013)

Econ and Ecom of Hum Dev

Page 132: The Economics and Econometrics of Human Development

USA

Canada

Denmark

Finland

France

GermanyNorway

Sweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stici

ty

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Corak's Preferred Data OLS (Slope=2.64, p-value=.016)

Great Gatsby Curve without Corak's Adjustments

Source: Bradley Setzler 2013

Econ and Ecom of Hum Dev

Page 133: The Economics and Econometrics of Human Development

USACanada

Denmark

Finland

France

Germany

NorwaySweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stici

ty

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Alternate Data Choice OLS (Slope=-0.02, p-value=.980)

Great Gatsby Curve using Alternate Elasticities

Source: Bradley Setzler 2013

Econ and Ecom of Hum Dev

Page 134: The Economics and Econometrics of Human Development

USA

Canada

Denmark

Finland

France

Germany

Norway

Sweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stic

ity (F

athe

r to

Son

Earn

ings

)

.2 .25 .3 .35

Corak's Preferred Data OLS (Slope=2.05, p-value=.008)

Corak's Great Gatsby Curve

Source: Corak, JEP(2013)

Econ and Ecom of Hum Dev

Page 135: The Economics and Econometrics of Human Development

USA

Canada

Denmark

Finland

FranceGermany

Norway

Sweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stici

ty

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Corak's Preferred Data except USA OLS (Slope=0.65, p-value=.008)

Great Gatsby Curve with Lower USA Choice

Source: Bradley Setzler 2013

Econ and Ecom of Hum Dev

Page 136: The Economics and Econometrics of Human Development

USACanada

Denmark

Finland

France

Germany

NorwaySweden

UK

0.1

.2.3

.4.5

Inte

rgen

erat

iona

l Ela

stici

ty

.2 .25 .3 .35Gini Coefficient, After Taxes and Transfers

Alternate Data Choice OLS (Slope=-0.02, p-value=.980)

Great Gatsby Curve using Alternate Elasticities

Source: Bradley Setzler 2013

Econ and Ecom of Hum Dev

Page 137: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 138: The Economics and Econometrics of Human Development

Appendix II

Econ and Ecom of Hum Dev

Page 139: The Economics and Econometrics of Human Development

Dynastic Model of Parental Investment that Emphasizes theInteraction of Dynamic Complementarity and Credit Markets

Econ and Ecom of Hum Dev

Page 140: The Economics and Econometrics of Human Development

• Parents face different constraints

i Inability of the family to borrow against future income of child(Already in the Becker–Tomes–Solon model: BTS)

ii Inability of parents to borrow against their own futureincome (new to literature)

Econ and Ecom of Hum Dev

Page 141: The Economics and Econometrics of Human Development

Capability Formation in an Economy withIdiosyncratic Uncertainty and Liquidity Constraints

(New to Literature)

Econ and Ecom of Hum Dev

Page 142: The Economics and Econometrics of Human Development

Generational Structure

• Each agent lives for 2T periods (T = 1 in BTS).

• During the first T years of life, the agent is a child and byassumption makes no economic decisions.

• Upon reaching age T + 1, the agent becomes an adult andgives birth to a child. (Exogenous fertility.)

• The agent dies at the end of the calendar year in which shecompletes 2T years of age and is replaced in the beginning ofthe next calendar year by the generation of her grandchild.

Econ and Ecom of Hum Dev

Page 143: The Economics and Econometrics of Human Development

The Technology of Skill Formation

Econ and Ecom of Hum Dev

Page 144: The Economics and Econometrics of Human Development

• It is investment; θt stock of child skills; h stock ofparental skills (h ≡ θP).

• T distinct stages of development.

• The technology for capability formation:

θt+1 = ft (θt , It , h) (22)

• f : increasing in each of its arguments, strictly concave, andtwice-continuously differentiable.

Econ and Ecom of Hum Dev

Page 145: The Economics and Econometrics of Human Development

• To develop some intuition about the skill formation processimplied by the production function (22), consider the followingparameterization:

θt+1 = δt

{γ1tθ

φtt + γ2t I

φtt + γ3th

φt} ρtφt

with 0 < γ1,t , γ2,t , γ3,t , ρt < 1, φt ≤ 1,∑

k γk,nt = 1.

Econ and Ecom of Hum Dev

Page 146: The Economics and Econometrics of Human Development

• If T = 2, ρ1 = ρ2 = 1, δ1 = 1, and φ1 = φ2 = φ ≤ 1.

• Skills at adulthood, h′ = θ3 = θT+1:

h′ = δ2

γ1,2γ1,1θφ1 + γ1,2γ2,1︸ ︷︷ ︸

“Multiplier effect”

I φ1 + γ2,2Iφ2 + (γ3,2 + γ1,2γ3,1) hφ

.

Econ and Ecom of Hum Dev

Page 147: The Economics and Econometrics of Human Development

• An extreme example arises in the Leontief case whereφ→ −∞, in which case we would write:

θ3 = δ2 min {θ1, I1, I2, h} (23)

Econ and Ecom of Hum Dev

Page 148: The Economics and Econometrics of Human Development

The Problem of the Parent

Econ and Ecom of Hum Dev

Page 149: The Economics and Econometrics of Human Development

The Problem When the Child Is between 1 and T − 1 YearsOld

• Parental labor supply is perfectly inelastic.• At each age t of the child, the parent is subject to productivity

innovations εt . Corresponding to labor market uncertainty.• The shocks εt are independently and identically distributed

across parents.• The shocks follow a first-order Markov process:

ln εt+1 = ρε ln εt + σηηεt . (24)

• Parents are assumed to have positive earnings.• Restrict productivity innovations such that there exists εmin with

the property that εt ≥ εmin > 0 for any t = T + 1, . . . , 2T .• Labor income of the parent: whεt• w is the efficiency wage• r is risk-free discount rate

Econ and Ecom of Hum Dev

Page 150: The Economics and Econometrics of Human Development

• Given the state variables, the parent chooses householdconsumption Ct , savings st+1, and investments It in thecognitive skill of the child.

• The savings of the parents are in a risk-free asset which pays arate of interest r .

• p denotes the price of the investment goods in cognitive skill.

• Following Laitner (1992), the parents cannot leave debts totheir children and have negative net worth, so savings aresubject to the lower bound equal to −whεmin

(1+r).

Econ and Ecom of Hum Dev

Page 151: The Economics and Econometrics of Human Development

• V (t, h, θt , st , εt): the value function of the parent of a child atage t, 1 ≤ t ≤ T − 1.

• The problem of the parent:

V (t, h, θt , st , εt)

= maxCt ,It ,st+1

{u (Ct) + βE [V (t + 1, h, θt+1, st+1, εt+1)| εt ]}

subject to:

Ct + pIt + st+1 = whεt + (1 + r) st (25)

st+1 ≥ − (whεmin) , It ,Ct ≥ 0 (26)

and the technology for capability formation (22).

Econ and Ecom of Hum Dev

Page 152: The Economics and Econometrics of Human Development

The Problem When the Child Is T Years Old:Go to College or Not?

Econ and Ecom of Hum Dev

Page 153: The Economics and Econometrics of Human Development

Steady State GE

• Firms producing final output (CRS)

• Also child investment good (Produced)

• Can establish stochastic GE for steady state, extending Aiyagariand Laitner to include human capital

Econ and Ecom of Hum Dev

Page 154: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 155: The Economics and Econometrics of Human Development

Appendix III

Econ and Ecom of Hum Dev

Page 156: The Economics and Econometrics of Human Development

Table 3a: Studies on the Role of Income on Children’s Outcomes

Dataset OutcomeStudied: Test

Scores (T),Schooling (S)

Timing of Income(Developmental Stageof the Child at Which

Income Effects areStudied)

Separate theEffect of Incomefrom Changes inLabor Supply or

FamilyEnvironment

Carneiro and Heckman(2002)

NLSY79∗ S Early (E) and Late(L)

College Enrollment

X

Belley and Lochner(2007)

NLSY79∗,NLSY97∗

S LHigh school

completion andCollege Enrollment

X

Dahl and Lochner(2012)

NLSY79∗,C-

NLSY79∗

T EPreadolescence(ages 8 to 14)

Xa

Duncan et al. (1998) PSID∗ Sd E and LChildhood andPreadolescence(ages 0 to 15)

X

Econ and Ecom of Hum Dev

Page 157: The Economics and Econometrics of Human Development

Table 3a (cont.): Studies on the Role of Income on Children’s Outcomes

Dataset Outcome Studied:Test Scores (T),

Schooling (S)

Timing of Income(Developmental Stage of the

Child at Which IncomeEffects are Studied)

Separate the Effect ofIncome from Changes inLabor Supply or Family

Environment

Duncan et al. (2011) RandomizedInterventionson Welfare

Support

T EEarly Childhood

(ages 2 to 5)

X

Loken (2010) NorwegianAdministrative

Data

S EChildhood

(ages 1 to 11)

Xc

Loken et al. (2012) NorwegianAdministrative

Data

S EChildhood

(ages 1 to 11)

X

Milligan and Stabile(2011)

CCTB∗∗,NCBS∗∗∗

T EChildhood

(ages 0 to 10)

X

Carneiro et al. (2013) NorwegianRegistry

Se E and LChildhood to Adolescence

(ages 0 to 17)

X

Econ and Ecom of Hum Dev

Page 158: The Economics and Econometrics of Human Development

Table 3b: Studies on the Role of Income on Children’s Outcomes

Distinguishes theEffects of

Contemporaneous vs.Permanent Income

Sources of IncomeWhose Effects are

Studied

Instrument Used

Carneiro and Heckman (2002) X Total family income None

Belley and Lochner (2007) X Total family income None

Dahl and Lochner (2012) Xb Total family income Policy variation in EITCeligibility

Duncan et al. (1998) X Total family income None

Econ and Ecom of Hum Dev

Page 159: The Economics and Econometrics of Human Development

Table 3b (continued): Studies on the Role of Income on Children’sOutcomes

Distinguishes theEffects of

Contemporaneous vs.Permanent Income

Sources of IncomeWhose Effects are

Studied

Instrument Used

Duncan et al. (2011) X Total family income Random assignment to programsoffering welfare transfers conditionalon employment or education related

activities, or full time work

Loken (2010) X Total family income Oil discovery (inducing regionalincrease in wages)

Loken et al. (2012) X Total family income Oil discovery (inducing regionalincrease in wages)

Milligan and Stabile (2011) X Child related tax benefitsand income transfers

Variation in benefits eligibility

Carneiro et al. (2013) X Total family income None

Econ and Ecom of Hum Dev

Page 160: The Economics and Econometrics of Human Development

Table 3c: Studies on the Role of Income on Children’s Outcomes

Effect of Income on Human Capital Investments

Carneiro and Heckman (2002) Percentage of people constrained = weighted gap in educational outcome to highestincome group: 5.1% are constrained in college enrollment (1.2% among low income, lowability, 0.2% low income high ability), 9% in completion of 2-year college (5.3% amonglow income, low ability, 0.3% low income high ability). No effect of timing of receipt offamily income on child outcomes.

Belley and Lochner (2007) High school completion: +8.4% for highest income quartile compared to lowest in 79,+6.7 in 97 cannot reject equal effect of income; college enrollment: +9.3% for highestincome quartile compared to lowest in 79, +16 in 97, cannot reject equal effect of income.

Dahl and Lochner (2012) $1,000 extra per year for 2 years: +6% of a standard deviation in math and readingcombined PIAT score.

Duncan et al. (1998) $10,000 increase in average (age 0-15) family income: +1.3 years of schooling in lowincome (¡$20,000) families, +0.13 in high income ones. Relevance of income is strongerin the early years (age 0-5): $10,000 increase in average (age 0-5) family income leads toextra 0.8 years of schooling in low income families, 0.1 in high income ones. Income atage 6-10 and 11-15: no significant effect. Similar results in a sibling differences model.

Econ and Ecom of Hum Dev

Page 161: The Economics and Econometrics of Human Development

Table 3c (continued): Studies on the Role of Income on Children’sOutcomes

Effect of Income on Human Capital Investments

Duncan et al. (2011) $1,000 extra per year for 2 to 5 years: +6% of a standard deviation in child’s achievementscore.

Loken (2010) OLS: positive relationship of average (age 1-13) family income on children’s education,IV: no causal effect. Results are robust to different specification and splitting the sampleby parental education.

Loken et al. (2012) Non-linear IV (quadratic model): increase of $17,414, +0.74 years of education for chil-dren in poor families, +0.05 for children in rich families.

Milligan and Stabile (2011) Low education mothers: positive effects of child benefits on cognitive outcomes for boys,on emotional outcomes for girls, weak on health. Results are non robust to the exclusionof Quebec.

Carneiro et al. (2013) All outcomes: monotone and concave relationship with permanent income. £100,000increase in permanent father’s earnings: +0.5 years of schooling. Timing of income: abalanced profile between early (age 0-5) and late childhood (age 6-11) is associated withthe best outcomes; shifting income to adolescence is associated with better outcomes indropping out of school, college attendance, earnings, IQ and teen pregnancy. Early andlate childhood income are complements in determining schooling attainment, early andadolescent income are substitutes.

Econ and Ecom of Hum Dev

Page 162: The Economics and Econometrics of Human Development

Table 4a: Studies on Tests of Credit Constraints

Dataset OutcomeStudied:School-

ing(S)

Timing of Income(Developmental

Stage of the Childat Which

Constraints areStudied)

ExplicitDynamic

Model

Who is Affectedby Constraints:Parent of the

Agent (P), Agent/ Child (C)

Keane andWolpin(2001)

NLSY79∗ S LCollege

Enrollment

X C

Carneiro andHeckman(2002)

NLSY79∗,C-

NLSY79∗

S E and LCollege

Enrollment,Comple-

tion,Delayed

Entry

X P

Econ and Ecom of Hum Dev

Page 163: The Economics and Econometrics of Human Development

Table 4a (continued): Studies on Tests of Credit Constraints

Dataset OutcomeStudied:School-

ing(S)

Timing of Income(Developmental

Stage of the Childat Which

Constraints areStudied)

ExplicitDynamic

Model

Who is Affectedby Constraints:Parent of the

Agent (P), Agent/ Child (C)

Cameron andTaber (2004)

NLSY79∗ S LAdolescence and

College Enrollment

X C

Caucutt andLochner(2012)

NLSY79∗,C-NLSY79∗

Ta E and LChildhood and

Adolescence

X P

Econ and Ecom of Hum Dev

Page 164: The Economics and Econometrics of Human Development

Table 4b: Studies on Tests of Credit Constraints

Method to Test forCredit Constraints

Find Presence of CreditConstraints

Effect of Income or Constraints on HumanCapital Investments

Keane and Wolpin(2001)

Structural estimation ofthe lower bound on asset

level

YESBut irrelevant for

schooling decisions

Increase borrowing limit to $3,000 (3× max es-timated): no change in mean highest grade com-pleted; +0.2% in college enrollment; -0.2$ on meanhourly wage rate; increase in consumption and re-duction in market hours; moderate reduction inparental transfers especially for the least educatedparents.

Carneiro andHeckman (2002)

(1) Gap to students fromhighest income quartile.(2) Timing of income.

(3) Difference in IV andOLS estimates of Mincer

coefficient

YESBut affecting at most

8% of students

(1) Conditioning on ability and family backgroundfactors, the role of income in determining school-ing decisions is minimal. The strongest evidence isin the low ability group. The test is not robust toaccounting for parental preferences and paternal-ism. Observed differences in attendance might bedue to a consumption value of child’s schooling forparents.(2) There is no evidence of a independent effecton college enrollment of early or late income oncepermanent income is accounted for.(3) The claim that higher IV than OLS estimates ofthe Mincer coefficient implies credit constraints areincorrect: instruments used are invalid, the qualitymargin is ignored and self selection and compara-tive advantage can produce the result also in ab-sence of financial constraints.

Econ and Ecom of Hum Dev

Page 165: The Economics and Econometrics of Human Development

Table 4b (continued): Studies on Tests of Credit Constraints

Method to Test forCredit Constraints

Find Presence of CreditConstraints

Effect of Income or Constraints on HumanCapital Investments

Cameron andTaber (2004)

IV estimation of“returns” to schooling

using costs of schoolingor foregone earnings as

instruments

NO Theoretical prediction: if borrowing constraints,IV estimates using direct costs of schooling higherthan using opportunity costs. Data: IV estimatesusing the presence of a local college are smallerthan the ones using foregone earnings. Regressionswhich interact college costs and characteristics po-tentially related to credit availability: no evidenceof excess sensitivity to costs for potentially con-strained sample. Structural model: almost 0% ofthe population is found to borrow at a rate higherthan the market one.

Caucutt andLochner (2012)

Structural estimation ofthe lower bound on asset

level

YESStronger effect on high

skilled parents

50% of young parents are constrained: high schooldropouts (50%), high school graduates (38%), col-lege dropouts (60%), college graduates (68%); and12% of old parents are constrained. Families withcollege graduate parents benefit the most from areduction in credit constraints.

Econ and Ecom of Hum Dev

Page 166: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 167: The Economics and Econometrics of Human Development

Appendix IV

Econ and Ecom of Hum Dev

Page 168: The Economics and Econometrics of Human Development

Table 5: Structural Models of Parental Investments(“X” means present; “X” means absent)

OLG Model Dynastic Links ExplicitModels ofParental

Preferences,Altruism (A)

or Paternalism(P)

ModelEstimated

Cunha and Heckman (2007) X A,B,C, Xi (A) X

Cunha (2007) X A,B,C Xi (A) XCaucutt and Lochner (2012) X B,C Xi (A) XDel Boca et al. (2013) X X Xj(P) XGayle et al. (2013) X A,C Xj(P) XCunha et al. (2013) X X Xj(P) XBernal (2008) X X Xj(P) X

AThrough parental skills, BThrough asset transfers, COnly through genes (initialconditions), DNatural borrowing limit, ELimits can be more stringent than naturallimit.

Econ and Ecom of Hum Dev

Page 169: The Economics and Econometrics of Human Development

Table 5: Structural Models of Parental Investments(“X” means present; “X” means absent)

ParentalGoods

Investment

Parental TimeInvestment

TechnologyDepends on

Parental Skill

Self-productivity

Cunha and Heckman (2007) X X X XCunha (2007) X X X XCaucutt and Lochner (2012) X X X XDel Boca et al. (2013) X X X XGayle et al. (2013) X X X XCunha et al. (2013) X X X XBernal (2008) X X X X

AThrough parental skills, BThrough asset transfers, COnly through genes (initialconditions), DNatural borrowing limit, ELimits can be more stringent than naturallimit.

Econ and Ecom of Hum Dev

Page 170: The Economics and Econometrics of Human Development

Table 5: Structural Models of Parental Investments(“X” means present; “X” means absent)

ParentalLearning

AboutTechnology

Bequests IntragenerationalBorrowing

Multiple Skillsof Children

Cunha and Heckman (2007) X X XE X

Cunha (2007) X X XD X

Caucutt and Lochner (2012) X X XE XDel Boca et al. (2013) X X X XGayle et al. (2013) X X X XCunha et al. (2013) X X X XBernal (2008) X X X X

AThrough parental skills, BThrough asset transfers, COnly through genes (ini-tial conditions), DNatural borrowing limit, ELimits can be more stringent thannatural limit.

Econ and Ecom of Hum Dev

Page 171: The Economics and Econometrics of Human Development

Table 5: Structural Models of Parental Investment(“X” means present; “X” means absent)

MultichildFamilies

(Preferences forEquity vs.Efficiency)

EndogenousFertility

Decisions

MultipleParents

EndogenousMating

Decisions

Cunha and Heckman (2007) X X X XCunha (2007) X X X XCaucutt and Lochner (2012) X X X XDel Boca et al. (2013) X X X XGayle et al. (2013) X X X XCunha et al. (2013) X X X XBernal (2008) X X X X

AThrough parental skills, BThrough asset transfers, COnly through genes (initialconditions), DNatural borrowing limit, ELimits can be more stringent than naturallimit.

Econ and Ecom of Hum Dev

Page 172: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 173: The Economics and Econometrics of Human Development

Appendix V

Econ and Ecom of Hum Dev

Page 174: The Economics and Econometrics of Human Development

Targeting Relatively More Investment Toward DisadvantagedChildren Can Be Socially Efficient

Econ and Ecom of Hum Dev

Page 175: The Economics and Econometrics of Human Development

In a one period of childhood problem where parents (or socialplanners) seek to maximize the aggregate of adult skills (θ2):

θA2 + θB2

subject to E = p1(IA1 + IB1 ),

the first order condition is

F.O.C.: f(1)

2

(γθB1 , I

A1

)= f

(1)2

(θB1 , I

B1

).

Econ and Ecom of Hum Dev

Page 176: The Economics and Econometrics of Human Development

Notice that

sign

(∂IA1∂γ

)= sign

(f

(1)12 (·)

)γ=1

,

where f(1)

12 (·) is the value of f (12) in the neighborhood of (·).Parents (social planners) invest more in the disadvantaged if inputsare substitutes with initial endowments and they invest less if theyare complements.

Econ and Ecom of Hum Dev

Page 177: The Economics and Econometrics of Human Development

Suppose that parents (or social planners) seek to maximize

θA3 + θB3

subject toE = p1(IA1 + IB1 ) + p2(IA2 + IB2 ).

Econ and Ecom of Hum Dev

Page 178: The Economics and Econometrics of Human Development

Even if (f(1)

12 > 0), greater first period investment in the initiallydisadvantaged child may be optimal. This is more likely (ceterisparibus)

(a) the more steeply diminishing is the productivity of second period

skills (f(2)

22 );

(b) the greater the self productivity of the stock of skills in the first

period (f(1)

1 = ∂θ2

∂θ1);

(c) the smaller first period complementarity (f(1)

21 ) relative to secondperiod complementarity and absolutely

Econ and Ecom of Hum Dev

Page 179: The Economics and Econometrics of Human Development

(d) the more rapidly diminishing the marginal productivity of

θ1(f(1)

11 );

(e) the greater the second period complementarity (f(2)

12 );

(f) the greater the first period productivity of investment (f(1)

2 ) and

(g) the more rapidly diminishing the productivity of second period

investment (f(2)

22 ).

Econ and Ecom of Hum Dev

Page 180: The Economics and Econometrics of Human Development

Roughly speaking, the more concave are the technologies in terms ofstocks of skills, the more favorable is the case for investing relativelymore in the disadvantaged child. The greater the second periodcomplementarity (f

(2)12 ), the greater the case for investing more in

the initially disadvantaged child to allow the child to benefit fromgreater second period complementarity of the stock of skills withsecond period investment. In general, even when investment isgreater in the first period for the disadvantaged child, second periodinvestment is greater for the initially advantaged child. It isgenerally not efficient to make the initially disadvantaged childwhole as it enters the second period when the effect of greatersecond period complementarity kicks in.

Econ and Ecom of Hum Dev

Page 181: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 182: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 183: The Economics and Econometrics of Human Development

Appendix VI

Econ and Ecom of Hum Dev

Page 184: The Economics and Econometrics of Human Development

Table 6a: Summary of Effects for Main Interventions

Participant/Evaluation Characteristics

Program Age

Dur

atio

n

Tar

get

Sel

ecti

on

Fol

low

-Up

Sam

ple

RC

TE

val

Elementary

LA’s Best 5–6 6Y SES Schl 12Y 19,320 NoCSP 5–13 5Y Behav Refer 35Y 510 YesSSDP 6–7 6Y Crime Prgrm 21Y 610 Yes

Adolescence

BBBS 10-16 1Y SES Self 1Y 960 YesIHAD 11–12 7Y SES Prgrm 8Y 180 YesEPIS 13–15 3Y Schl Schl 2Y 45,070 Noxl club 14 2Y Schl Schl 2Y 261,420 No

SAS 14–15 5Y Schl, SES Schl 6Y 430 NoSTEP 14–15 2Y Schl, SES Self 4Y 4,800 YesQOP 14–15 5Y Schl Prgrm 10Y 1,070 YesAcademies 13–16 4Y Schl, SES Self 12Y 1,460 Yes

ChalleNGe 16–18 1Y Dropout Self 3Y 1,200 YesJob Corps 16–24 1Y SES Self 9Y 15,300 YesYear-Up 18–24 1Y SES Self 2Y 200 Yes

Econ and Ecom of Hum Dev

Page 185: The Economics and Econometrics of Human Development

Table 6b: Summary of Effects for Main Interventions

Components

Program Hom

e

Hea

lth

Par

enta

l

On

Sit

e

Gro

up

Elementary

LA’s BestCSPSSDP

Adolescence

BBBSIHADEPISxl club

SASSTEPQOPAcademies

ChalleNGeJob CorpsYear-Up

Econ and Ecom of Hum Dev

Page 186: The Economics and Econometrics of Human Development

Table 6c: Summary of Effects for Main Interventions

Effects on Outcomes Return/Benefits

Program IQ Sch

ool

Cha

ract

er

Edu

cati

on

Hea

lth

Cri

me

Ear

ning

s

Ret

urn

Ben

efit

Cos

t

Elementary

LA’s Best 0.9CSPSSDP 3.1

Adolescence

BBBS 1.0IHADEPIS 0.9–3.0xl club

SASSTEPQOP 0.42Academies

ChalleNGe 6.4 2.66Job Corps 0.22Year-Up

Econ and Ecom of Hum Dev

Page 187: The Economics and Econometrics of Human Development

Table 6d: Summary of Effects for Main Interventions

Participant/Evaluation Characteristics

Program Age

Dur

atio

n

Tar

get

Sel

ecti

on

Fol

low

-Up

Sam

ple

RC

TE

val

Early

NFP < 0 2Y SES Prgrm 19Y 640 YesABC 0 5Y SES Refer 30Y 90 YesIHDP 0 3Y Health Prgrm 18Y 640 YesFDRP 0 5Y SES Prgrm 15Y 110 No

PCDC 1 2Y SES Prgrm 15Y 170 YesJSS 1–2 2Y Health Prgrm 22Y 160 YesPerry 3 2Y SES, IQ Prgrm 37Y 120 YesHead Start 3 2Y SES Prnt 23Y 4,170 Yes

CPC 3–4 2Y SES Prnt 25Y 1,290 NoTEEP 3,5 2Y SES Prgrm 22Y 260 YesSTAR 5–6 4Y SES Prgrm 22Y 11,000 Yes

Econ and Ecom of Hum Dev

Page 188: The Economics and Econometrics of Human Development

Table 6e: Summary of Effects for Main Interventions

Components

Program

Hom

e

Hea

lth

Par

enta

l

On

Sit

e

Gro

up

Early

NFPABCIHDPFDRP

PCDCJSS

PerryHead Start

CPCTEEPSTAR

Econ and Ecom of Hum Dev

Page 189: The Economics and Econometrics of Human Development

Table 6f: Summary of Effects for Main Interventions

Effects on Outcomes Return/Benefits

Program IQ Sch

ool

Cha

ract

er

Edu

cati

on

Hea

lth

Cri

me

Ear

ning

s

Ret

urn

Ben

efit

Cos

t

Early

NFP 2.9ABC 3.8IHDPFDRP

PCDCJSSPerry 7–10 7.1–12.2Head Start

CPC 18 10.8TEEPSTAR 6.2

Return to main text

Econ and Ecom of Hum Dev

Page 190: The Economics and Econometrics of Human Development

Appendix VII

Econ and Ecom of Hum Dev

Page 191: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 192: The Economics and Econometrics of Human Development

Appendix VIII

Econ and Ecom of Hum Dev

Page 193: The Economics and Econometrics of Human Development

Closing the Gap: Perry Program Applied to Disadvantaged BlackPopulation: Males

Econ and Ecom of Hum Dev

Page 194: The Economics and Econometrics of Human Development

Closing the Gap: Perry Program Applied to Disadvantaged BlackPopulation: Females

Return to main text

Econ and Ecom of Hum Dev

Page 195: The Economics and Econometrics of Human Development

Appendix IX

Econ and Ecom of Hum Dev

Page 196: The Economics and Econometrics of Human Development

Simulation

Econ and Ecom of Hum Dev

Page 197: The Economics and Econometrics of Human Development

Results

Econ and Ecom of Hum Dev

Page 198: The Economics and Econometrics of Human Development

Setup 1: Fixed Target Between Disadvantaged andAdvantaged Children

Econ and Ecom of Hum Dev

Page 199: The Economics and Econometrics of Human Development

Scenario 1: Constant Complementarity

Econ and Ecom of Hum Dev

Page 200: The Economics and Econometrics of Human Development

Scenario 2: Increasing Complementarity

Econ and Ecom of Hum Dev

Page 201: The Economics and Econometrics of Human Development

Scenario 3: Complementarity and Substitutability

Econ and Ecom of Hum Dev

Page 202: The Economics and Econometrics of Human Development

Table 1, Setup 1: Fixed Targets between Advantaged and Disadvantaged ChildrenInitial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period

Scenario 1: Fixed Complementarityt=1 t=2 t=3 t=4

0.01 1.51 2.18 3.14 4.52 11.36 10 2.630.05 1.55 2.23 3.21 4.63 11.62 10 2.86

Scenario 2: Increasing Complementarity0.01 1.33 2.17 3.24 4.66 11.41 10 2.940.05 1.30 2.16 3.26 4.69 11.41 10 3.01

Scenario 3: First Substitutes and Then Complements0.01 0.69 1.58 3.25 4.68 10.19 10 2.970.05 0.67 1.57 3.25 4.68 10.16 10 2.98

Econ and Ecom of Hum Dev

Page 203: The Economics and Econometrics of Human Development

Setup 2: Higher Skill Target for Advantaged Child

Econ and Ecom of Hum Dev

Page 204: The Economics and Econometrics of Human Development

Scenario 1: Constant Complementarity

Econ and Ecom of Hum Dev

Page 205: The Economics and Econometrics of Human Development

Scenario 2: Increasing Complementarity

Econ and Ecom of Hum Dev

Page 206: The Economics and Econometrics of Human Development

Scenario 3: Complementarity and Substitutability

Econ and Ecom of Hum Dev

Page 207: The Economics and Econometrics of Human Development

Table 2, Setup 2: Higher Target for the Advantaged ChildInitial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period

Scenario 1: Fixed Complementarityt=1 t=2 t=3 t=4

0.01 1.36 1.97 2.83 4.08 10.24 9 2.380.05 1.70 2.45 3.53 5.09 12.77 11 3.13

Scenario 2: Increasing Complementarity0.01 1.20 1.96 2.92 4.21 10.29 9 2.670.05 1.43 2.37 3.57 5.15 12.52 11 3.28

Scenario 3: First Substitutes and Then Complements0.01 0.64 1.42 2.94 4.23 9.23 9 2.730.05 0.72 1.73 3.56 5.12 11.12 11 3.22

Econ and Ecom of Hum Dev

Page 208: The Economics and Econometrics of Human Development

Setup 3: Greater Target for Disadvantaged Kid

Econ and Ecom of Hum Dev

Page 209: The Economics and Econometrics of Human Development

Scenario 1: Constant Complementarity

Econ and Ecom of Hum Dev

Page 210: The Economics and Econometrics of Human Development

Scenario 2: Increasing Complementarity

Econ and Ecom of Hum Dev

Page 211: The Economics and Econometrics of Human Development

Scenario 3: Complementarity and Substitutability

Econ and Ecom of Hum Dev

Page 212: The Economics and Econometrics of Human Development

Table3, Setup 3: Higher Target for the Disadvantaged ChildInitial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period

Scenario 1: Fixed Complementarityt=1 t=2 t=3 t=4

0.01 1.66 2.40 3.45 4.97 12.48 11 2.880.05 1.40 2.01 2.90 4.17 10.48 9 2.59

Scenario 2: Increasing Complementarity0.01 1.46 2.39 3.55 5.12 12.52 11 3.210.05 1.18 1.95 2.94 4.23 10.30 9 2.74

Scenario 3: First Substitutes and Then Complements0.01 0.75 1.74 3.55 5.12 11.16 11 3.210.05 0.61 1.41 2.94 4.23 9.19 9 2.74

Econ and Ecom of Hum Dev

Page 213: The Economics and Econometrics of Human Development

Return to main text

Econ and Ecom of Hum Dev

Page 214: The Economics and Econometrics of Human Development

Appendix X

Econ and Ecom of Hum Dev

Page 215: The Economics and Econometrics of Human Development

Comparing Perry Intervention to Effect of Changing FamilyEnvironments

Econ and Ecom of Hum Dev

Page 216: The Economics and Econometrics of Human Development

Disadvantaged Children: First Decile in the Distribution ofCognitive and Non-Cognitive Skills at Age 6

Mothers are in First Decile in the Distributionof Cognitive and Non-Cognitive Skills at Ages 14–21

Changing initial Adolescent Changingconditions: moving intervention: Moving initial conditionschildren to the 4th investments at last and performing

decile of distribution transition from 1st a balancedof skills only through to 9th decile intervention

Baseline early investments

High School Graduation 0.4109 0.6579 0.6391 0.9135Enrollment in College 0.0448 0.1264 0.1165 0.3755Conviction 0.2276 0.1710 0.1733 0.1083Probation 0.2152 0.1487 0.1562 0.0815Welfare 0.1767 0.0905︸ ︷︷ ︸

Perry Treatment Effects

0.0968 0.0259

The adolescent-only and balanced intervention programscost 35% more than the Perry program.Source: Cunha and Heckman (2007)

Return to main text

Econ and Ecom of Hum Dev