The Economics and Econometrics of Human Development

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The Economics and the Econometrics of Human Development James J. Heckman University of Chicago March 31, 2014 Institute of Economic Growth New Delhi Econ and Ecom of Hum Dev

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A talk by Prof James Heckman, 2000 Nobel laureate in economics

Transcript of The Economics and Econometrics of Human Development

  • The Economics and the Econometrics of Human Development James J. Heckman University of Chicago March 31, 2014 Institute of Economic Growth New Delhi Econ and Ecom of Hum Dev
  • Intergenerational Mobility and Inequality: The Great Gatsby Curve IGE: ln Y1 Income in current generation = + ln Y0 Income of parents + India Source: Corak 2011, Inequality from generation to generation: the United States in Comparison. Notes: Inequality is measured post-taxes and transfers. Gini index dened on household income. IGE measured by pre-tax and 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
  • Link to Appendix I Econ and Ecom of Hum Dev
  • (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
  • Becker-Tomes-Solon Heritability Eciency of parental investment Inequality in wages Inequality of public provision of investment Econ and Ecom of Hum Dev
  • As a purely statistical matter, the more heterogeneity across units within an area the greater the estimated . Econ and Ecom of Hum Dev
  • Main ndings of the empirical literature Econ and Ecom of Hum Dev
  • Hart & Risley, 1995 Children enter school with meaningful dierences in vocabulary knowledge. 1. Emergence of the Problem In a typical hour, the average child hears: Family Actual Dierences in Quantity Actual Dierences in Quality Status of Words Heard of Words Heard Welfare 616 words 5 armatives, 11 prohibitions Working Class 1,251 words 12 armatives, 7 prohibitions Professional 2,153 words 32 armatives, 5 prohibitions Econ and Ecom of Hum Dev
  • Hart & Risley, 1995 Children enter school with meaningful dierences in vocabulary knowledge. 1. Emergence of the Problem In a typical hour, the average child hears: Family Actual Dierences in Quantity Actual Dierences in Quality Status of Words Heard of Words Heard Welfare 616 words 5 armatives, 11 prohibitions Working Class 1,251 words 12 armatives, 7 prohibitions Professional 2,153 words 32 armatives, 5 prohibitions 2. Cumulative Vocabulary at Age 3 Cumulative Vocabulary at Age 3 Children from welfare families: 500 words Children from working class families: 700 words Children from professional families: 1,100 words Econ and Ecom of Hum Dev
  • Understanding Mechanisms Econ and Ecom of Hum Dev
  • Capabilities, the Technology of Capability Formation, and the Essential Ingredients of a Life Cycle Model of Human Development Econ and Ecom of Hum Dev
  • Capabilities are multiple in nature. They encompass cognition, noncognitive and social preferences and personality and preference traits, as well as health. Vector of capabilities at age t: t. Capacities to act. Capabilities aect (a) resource constraints, (b) agent information sets and expectations, (c) parental information and expectations and (d) preferences. They are stable across situations but evolve over time. Econ and Ecom of Hum Dev
  • Dene relationships Mt mapping t to outcomes Yt at stage t of the life cycle as: Mt : t Yt. (1) A core low-dimensional set of capacities generates a variety of diverse outcomes. Econ and Ecom of Hum Dev
  • Technology of Capability Formation Cunha and Heckman (2007), Cunha (2007) t: a vector t+1 = ft( t self productivity and cross eects , It investment broadly dened (parents, environment) , P ,t parental capabilities ) (2) Econ and Ecom of Hum Dev
  • Complementarity Increases with Age 2 t+1 tIt t . Econ and Ecom of Hum Dev
  • Positive at later stages (t > t ) of childhood 2 t+1 tIt > 0, t > t . Some evidence suggesting 2 t+1 tIt 0, t < t , But even if positive, still smaller than at t > t . Econ and Ecom of Hum Dev
  • Complementarity coupled with self-productivity Dynamic Complementarity It t+1 t+1 t+s s > 1 2 t+s+1 ItIt+s > 0 Econ and Ecom of Hum Dev
  • Family Preferences for Child Outcomes Dierent versions of altruism, paternalism and beliefs about proper child rearing Econ and Ecom of Hum Dev
  • Family Resources Broadly Dened: Parental and Child Interactions with Financial Markets and Access to Support from External Institutions (a) Restrictions on transfers across generations (b) Restrictions on transfers within generations (parental lifetime liquidity constraints) (c) Public provision of investment; public policy towards children Econ and Ecom of Hum Dev
  • Other Constraints on The Family Actively Being Investigated (a) Information on parenting and other aspects of life across generations (b) Genes (c) Structure of household and assortative matching patterns (marriage markets) Econ and Ecom of Hum Dev
  • The Empirical and Theoretical Challenge A Life Cycle Framework for Organizing Studies and Integrating Evidence t: Capacities at t; It: investment at t; P ,t: Parental environmental variables t+1 = ft(t, It, P ,t): Technology of Skill Formation 1 0 1 2 T T +1 I1 I0 I1 I2 IT P ,1 P ,0 P ,1 P ,2 P ,T Prenatal Birth Early Childhood, 03 Later Childhood, 36 Adulthood and Beyond Econ and Ecom of Hum Dev
  • A Bare-Bones Model of Parental Investment Econ and Ecom of Hum Dev
  • The Problem of the Parent Link to Appendix II Econ and Ecom of Hum Dev
  • Life lasts four periods: Two periods as a passive child who makes no economic decisions (and whose consumption is ignored) but who receives investment in the form of goods. Two periods as a parent. Econ and Ecom of Hum Dev
  • Denote by 1 the initial capability level of a child drawn from the distribution J(1). (For notational simplicity, denote P,t = P = h.) Denoting by h the human capital of the child when child reaches adulthood Econ and Ecom of Hum Dev
  • Simplied parameterization of technology: t+1 = t 1,tt t + 2,tIt t investment + 3,tht parental human capital t t with 0 < 1,t, 2,t, 3,t, t 1, t 1, k k,nt = 1. Econ and Ecom of Hum Dev
  • Final Form Representation If T = 2, 1 = 2 = 1, 1 = 1, and 1 = 2 = 1, skills at adulthood, h = 3 = T+1 can be written as h = 2 1,21,1 1 + 1,22,1 Multiplier I 1 + 2,2I 2 + (3,2 + 1,23,1) h 1 . Econ and Ecom of Hum Dev
  • If = 1, then investments at dierent periods are (almost) perfect substitutes. Econ and Ecom of Hum Dev
  • Polar example arises in the Leontief case where : h = m2 h, 0, min(I1, I2) (3) Econ and Ecom of Hum Dev
  • u(): parental utility function : discount factor r: real interest rate : parental altruism c1, c2 are consumption in parental life cycle periods 1 and 2 Econ and Ecom of Hum Dev
  • The goal of the parent is to optimize: V (h, b, 1) = max c1,c2,I1,I2 u (c1) + u (c2) + 2 E [V (h , b , 1)] (4) subject to technology and budget constraints. Econ and Ecom of Hum Dev
  • 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
  • Tractable nal form technology: h = m2 h, 0, investment multiplier (I1) + (1 ) (I2) , (6) for 1 and 0 1, 1. Econ and Ecom of Hum Dev
  • I1 I2 = (1 ) (1 + r) 1 . (7) I1 I2 as , , and r . Econ and Ecom of Hum Dev
  • Important policy question: How easy (costly) is it to remediate low I1 with high I2? Econ and Ecom of Hum Dev
  • Implications of the Model Econ and Ecom of Hum Dev
  • Borrowing Limits Econ and Ecom of Hum Dev
  • Liquidity Constraints Within the Life Cycles of Parents The parent, within his/her lifetime, faces a sequence of constraints at each stage of the life of the child. Econ and Ecom of Hum Dev
  • Denoting parental nancial assets by a and allowing parental labor market productivity to grow at exogenous rate g, these budget constraints 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 future income. Child investments at dierent ages are not perfect substitutes ( < 1). Econ and Ecom of Hum Dev
  • Parental utility: u (c) = c 1 /. I1 I2 = (1 ) (1 + r) 1 1 unconstrained ratio [(1 + r)] 1 1 c1 c2 1 1 =1 if unconstrained, 0), greater rst period investment in the initially disadvantaged child may be optimal. This is more likely (ceteris paribus) (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 rst period (f (1) 1 = 2 1 ); (c) the smaller rst period complementarity (f (1) 21 ) relative to second period complementarity and absolutely Econ and Ecom of Hum Dev
  • (d) the more rapidly diminishing the marginal productivity of 1(f (1) 11 ); (e) the greater the second period complementarity (f (2) 12 ); (f) the greater the rst 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
  • An Example Suppose that, for each child k, the outcome of interest for parents are childrens earnings Ek and that they are function of childrens adult human capital determined by genes (1,k) and early (I1,k) and late (I2,k) parental investments. Ek = wf 2 (2,k, I2,k) = 2 22 2,k + (1 2)I2 2,k 2 2 (14) with 2,k = f 1 (1,k, I1,k) = 1 11 1,k + (1 1)I1 1,k 1 1 (15) Econ and Ecom of Hum Dev
  • w is common across families and siblings. Human capital is chosen so that w = 1. The budget constraint faced by the parents with total resources Re is: p1 n k=1 I1 + p2 n k=1 I2 = Re . (16) Econ and Ecom of Hum Dev
  • Measure of parental compensation with respect to initial inequality. Dene the parameter as: Ei Ej 1,i 1,j . (17) If = 1, the parents perfectly translate initial dierences into earnings dierences. Econ and Ecom of Hum Dev
  • Figure 1: Earnings Equalization 1 Notes: The parental preference parameters used in the simulation are = 1 and i = j = 0.5. Total resources are Re = 4. The technology of skill formation parameters, capturing increasing complementarity between skills and investments over time, are: 1 = 2 = 0.5, 1 = 0.6, 2 = 0.5, 2 = 1. The parameter 1 denes the degree of homogeneity of the rst period technology. We vary the value of 1 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
  • Figure 2a: Parental Investments Ratio Early to Late 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 are as in Figure 1. Econ and Ecom of Hum Dev
  • 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 are as in Figure 1. Econ and Ecom of Hum Dev
  • Figure 2c: Parental Investments Levels of Late 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 are as in Figure 1. Econ and Ecom of Hum Dev
  • Testing and Operationalizing the Theory Econ and Ecom of Hum Dev
  • Capabilities as Determinants of Functionings Econ and Ecom of Hum Dev
  • Decompose the t vector into three subvectors: t = (C,t, N,t, H,t) (18) where C,t is a vector of cognitive abilities (e.g., IQ) at age t, N,t is a vector of noncognitive abilities (e.g., patience, self-control, temperament, risk aversion, discipline, and neuroticism) at age t, and H,t is a vector of health stocks for mental and physical health at age t. Econ and Ecom of Hum Dev
  • Capabilities, combined with eort, incentives and purchased inputs determine functionings. Econ and Ecom of Hum Dev
  • Functionings (task j) at age t: Yj,t = j,t(t, ej,t, Xj,t), j {1, . . . , Jt} and t {1, . . . , 2T} (19) Yj,t: outcome from activity j at time t t is the vector of capabilities at age t Xj,t is a vector of purchased inputs that aect the functionings ej,t is eort in task T is the length of childhood T is the length of adulthood 2T is total lifetime Econ and Ecom of Hum Dev
  • Eort: ej,t ej,t = j (t, At, Xj,t, Ra j,t(It1) | u). (20) At: environment Ra j,t: incentives Econ and Ecom of Hum Dev
  • 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
  • Nonparametric Factor Models Are Natural Frameworks for Estimating Capabilities and Determining Frontier Capability Sets Econ and Ecom of Hum Dev
  • Low dimensional capabilities (factors) generate a high dimensional set of functionings. Dimension and factor structures selected through a variety of methods. Exploratory factor analysis. Novel Bayesian proceduresavoid arbitrary methods in Exploratory Factor Analysis. Econ and Ecom of Hum Dev
  • Technology of Skill Formation k,t+1 = fs,k (t, Ik,t, P,t) (21) for k {C, N, H}, t {1, 2, . . . , T}. Econ and Ecom of Hum Dev
  • Identication of the Technology of Skill Formation To estimate the technology of skill formation: Have to solve three problems. Econ and Ecom of Hum Dev
  • Identication of the Technology of Skill Formation To estimate the technology of skill formation: Have to solve three problems. 1 Dont observe (t, Ik,t, P,t) directly, but have many measurements on it. Measurement error in nonlinear systems. 2 Dont know which scale to use to measure components of t. Anchor test scores on adult outcomes. 3 Investment Ik,t may be chosen by parents based on information that may be unobserved by the econometrician (k,t). Endogeneity of investment. Econ and Ecom of Hum Dev
  • Estimating Functionings and Extracting Factors: Multiple Capabilities Shape Human Achievement Across a Variety of Dimensions Econ and Ecom of Hum Dev
  • The relationship between capabilities estimated in the recent literature and traditional preference parameters (time preference, leisure, risk aversion, etc.) is weak. Dohmen, Falk, et al. (2012) Suggests that a richer set of preference and constraint descriptions may characterize choice behavior. Econ and Ecom of Hum Dev
  • Decile of Cognitive 1 2 3 4 5 6 7 8 9 10 Decile of Socio-Emotional 1 2 34 5 67 8 9 10 Probability 0 0.2 0.4 0.6 0.8 1 Decile of Cognitive 1 2 3 4 5 6 7 8 9 10 Probability 0 0.2 0.4 0.6 0.8 1 Fraction 0 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 Probability 0 0.2 0.4 0.6 0.8 1 Fraction 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 Endowment Levels, Dropping from Secondary School vs. Graduating (Source: Heckman et al., 2011) Econ and Ecom of Hum Dev
  • The same low-dimensional vector of capabilities predicts a wide variety of outcomes for: Crime Wages Health Healthy behaviors (smoking, drug use) Trust Voting behavior Employment Participation in welfare Econ and Ecom of Hum Dev
  • Estimates of Technologies of Capability Formation and Some Implications Econ and Ecom of Hum Dev
  • Capabilities evolve over the life cycle Parental investments explain 34% of variance of educational attainment Self-productivity becomes stronger as children become older, for both cognitive and noncognitive skill formation (i.e., t+1 t t). Strong cross eects (noncognitive skills foster cognitive investment) Complementarity between cognitive skills and investment becomes stronger as children become older. The elasticity of substitution for cognitive production is smaller in second stage production Econ and Ecom of Hum Dev
  • Emerging dynamic complementarity. It is more dicult to compensate for the eects of adverse environments on cognitive endowments at later ages than it is at earlier ages. This pattern of the estimates helps to explain the evidence on ineective cognitive remediation strategies for disadvantaged adolescents reported in Cunha et al. (2006), Cunha (2007), and later papers. Complementarity between noncognitive skills and investments stays roughly constant over the life cycle. Suggests that later life investments should be more focused on promoting noncognitivepersonalityskills. The evidence on which adolescent interventions are successful is consistent with this evidence. Econ and Ecom of Hum Dev
  • The Implications of the Estimates for Design of Policy Targeted strategies Consider a policy for a social planner to optimize the stock of education in society. Assume (for simplicity) full control of investment (ignores parental responses) The bulk of the evidence in the child development literature shows reinforcement of investment by parents. No consideration of social fairness, equality of opportunity or equality of nal outcomesjust eciency. Yet with these estimates the optimal policy invests the most in the disadvantaged. As an empirical matter, social justice is enhanced by what is productively ecient. Econ and Ecom of Hum Dev
  • Socially Optimal Early and Late Levels of Investment by Initial Capabilities 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
  • 0.5 1 1.5 2 2.5 0 0.5 1 1.5 2 2.5 3 3.5 Figure 5 Densities of Ratio of Early to Late Investments Maximizing Aggregate Education Versus Minimizing Aggregate Crime Ratio Early to Late Investment Education Crime Econ and Ecom of Hum Dev
  • Using Economics to Go Behind Estimated Program Treatment Eects and Beyond Meta-Analyses of Treatment Eects: Linking the Program Evaluation Literature with the Economics of the Family Widely used metanalyses on early childhood do not recognize that various interventions in early childhood previously implemented dier. 1 The populations targeted dier. 2 The objectives and curricula of the programs dier. 3 The measurement systems for backgrounds and outcomes dier among each other and also with observational studies. 4 The methods of evaluation dier. 5 Need to integrate the studies of family inuence with the intervention studies to understand how interventions aect family life. 6 Need to compare alternative policies in comparable metrics; i.e., rates of return to policies or cost-benet analyses. Econ and Ecom of Hum Dev
  • Lessons From and Lessons For the Intervention Literature Link to Appendix VI Econ and Ecom of Hum Dev
  • The Mechanisms Producing the Treatment Eects: A Case Study Econ and Ecom of Hum Dev
  • Cognitive Evolution by Age, Perry Males Male 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 10Entry Age Treatment Control Econ and Ecom of Hum Dev
  • Personal Behavior Index by Treatment Group Control Treatment 0.2.4.6.81 density 2 2.5 3 3.5 4 4.5 5 0.2.4.6.81 density 2 2.5 3 3.5 4 4.5 5 Econ and Ecom of Hum Dev
  • Socio-Emotional Index by Treatment Group Control Treatment 0.2.4.6.8 density 1 2 3 4 5 0.2.4.6.8 density 1 2 3 4 5 Econ and Ecom of Hum Dev
  • Decomposition of Treatment Eects, Males 32THEAMERICANECONOMICREVIEWMONTHYEAR 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 eects are shown in parentheses. Each bar represents the total treatment eect normalized to 100 percent. One-sided p-values are shown above each component of the decomposition. The gure is a slightly simplied visualization of Tables L.10 and L.14: small and statistically insignicant contributions of the opposite sign are set to zero. See Web Appendix L for detailed information about the simplications made to produce the gure. CAT total denotes California Achievement Test total score normalized to control mean zero and variance of one. Asterisks denote statistical signicance: * 10 percent level; ** 5 percent level; *** 1 percent level. Monthly income is adjusted to thousands of year-2006 dollars using annual national CPI. Econ and Ecom of Hum Dev
  • Health Outcomes Link to Appendix VII Econ and Ecom of Hum Dev
  • Attachment, Engagement Toward a Deeper Understanding of Parenting and Learning In both Perry and ABC (and many other interventions) a main channel of inuence is on the parent-child interactions. Enhanced attachment and engagement of parents. This has important implications for how we model family inuence. Econ and Ecom of Hum Dev
  • Mechanismsproducing eects (a) Information (b) Changing preferences of parents (c) Parental response to childs curiosity and interest induced by participation in the program Econ and Ecom of Hum Dev
  • Parental response to Perry Preschool Program 102030405060 Proportion .015 .01 .005 0 .005 .01 .015 Belief in Importance of Parenting Control Treatment Econ and Ecom of Hum Dev
  • Table 2: Models of Parent-Child Interaction ( means present; X means absent) Parental Monetary Investments Discordance in Preferences between Parent and Child Multiple Children Parental Incentives for Child Eort Cosconati (2013) X a,b X c Akabayashi (2006) a X d,e Hao et al. (2008) b e Lizzeri and Siniscalchi (2008) X d X X a Dierence in discount factors. b Dierences in utility functions. c Restrictions on leisure. d Dierences in knowledge about proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the eects of time investments. h Implications from the model are empirically tested. Econ and Ecom of Hum Dev
  • Table 2 (continued): Models of Parent-Child Interaction ( means present; X means absent) Eort Produces Greater Capability Parental Learning about Child Quality Parental Actions Facilitate Acquisition of Information Parental Beliefs Can Diverge from Truth Cosconati (2013) X X X Akabayashi (2006) f Hao et al. (2008) X X X X Lizzeri and Siniscalchi (2008) X X X a Dierence in discount factors. b Dierences in utility functions. c Restrictions on leisure. d Dierences in knowledge about proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the eects of time investments. h Implications from the model are empirically tested. Econ and Ecom of Hum Dev
  • Table 2 (continued): Models of Parent-Child Interaction ( means present; X means absent) Childs Eort Observable Childs Human Capital Observable Model Is Estimated Cosconati (2013) X Akabayashi (2006) X X Hao et al. (2008) X X g Lizzeri and Siniscalchi (2008) X X a Dierence in discount factors. b Dierences in utility functions. c Restrictions on leisure. d Dierences in knowledge about proper task execution. e Time investments in the child. f Monetary investments in the child. g The authors analyze the eects of time investments. h Implications from the model are empirically tested. Econ and Ecom of Hum Dev
  • An Economic Model of Mentoring and Scaolding (Garca, Heckman, Mosso, and Wang, 2013) Econ and Ecom of Hum Dev
  • Mentors Problem Yt: Measured output of child at age t t: Capabilities at outset t: Parental targets It: Parental investment at age t at: Child eort at age t The mentors problem is to minimize Vt(Yt) = min It ,...IN1 E N1 =t Q + I RI + N Qf N |Yt where Q, Qf , R 0. Econ and Ecom of Hum Dev
  • Technology: t+1 = At + BIt + Fat + wt t+1 = (t, It, at) t+1 = (t, It, at) Yt = Ct + Dat + vt t = t t It = It It at = at at. Econ and Ecom of Hum Dev
  • Childs Problem (with development of agency of the child) The child chooses a sequence of eort (a1, . . . , aN1) to maximize her utility in each period. Her value function at time t is: Jt(Yt) = max at ,...,aN1 t(t)J1 t (Yt) + (1 t(t))J2 t (Yt) Econ and Ecom of Hum Dev
  • J1 t (Yt) = max at ,...,aN1 E N1 =t (h It) 2 (at a) (at a + It) |Yt J2 t (Yt) = max at ,...,aN1 E N1 =t h RP t (at) 2 (at a) (at a) + It |Yt RP t () is the best response function of the mentor Econ and Ecom of Hum Dev
  • Integrating Experimental Studies with Family Inuence Studies Econ and Ecom of Hum Dev
  • IGt : government investment IPt : private (family) investment Government technology: f G (t, Pt , IGt , IPt ) Private technology: f P (t, Pt , IGt , IPt ) Mixed technology: f M (t, Pt , IGt , IPt ) Econ and Ecom of Hum Dev
  • Studies under way doing this (Fan, Hai, Heckman, Wei, and Zhang, 2013) Econ and Ecom of Hum Dev
  • What about promoting education? Econ and Ecom of Hum Dev
  • Early development is as important as education in promoting wages, employment, and health. Econ and Ecom of Hum Dev
  • Disparities by Education (Post-compulsory Education) Education, Wages, Employment, and Health Note: Conti and Heckman (2010). Authors calculations using British Cohort Study, 1970. Econ and Ecom of Hum Dev
  • Disparities by Education (Post-compulsory Education) Education, Wages, Employment, and Health Note: Conti and Heckman (2010). Authors calculations using British Cohort Study, 1970. Econ and Ecom of Hum Dev
  • Disparities by Education (Post-compulsory Education) Education, Wages, Employment, and Health Note: Conti and Heckman (2010). Authors calculations using British Cohort Study, 1970. Econ and Ecom of Hum Dev
  • Summary Econ and Ecom of Hum Dev
  • The Empirical and Theoretical Challenge A Life Cycle Framework for Organizing Studies and Integrating Evidence t: Capacities at t; It: investment at t; P ,t: Parental environmental variables t+1 = ft(t, It, P ,t): Technology of Skill Formation 1 0 1 2 T T +1 I1 I0 I1 I2 IT P ,1 P ,0 P ,1 P ,2 P ,T Prenatal Birth Early Childhood, 03 Later Childhood, 36 Adulthood and Beyond Econ and Ecom of Hum Dev
  • Predistribution Not Simply Redistribution Econ and Ecom of Hum Dev
  • (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
  • Appendix I Econ and Ecom of Hum Dev
  • USA Canada Denmark Finland France Germany Norway Sweden UKItaly Japan 0.1.2.3.4.5 Intergen.ElasticityofEarnings(IGE) .2 .25 .3 .35 Gini Coefcient, After Taxes and Transfers Corak's Chosen IGE OLS Slope=2.19, p-value=.003 In Corak (2013), the Great Gatsby Curve has signicant, positive slope in OLS regression. Econ and Ecom of Hum Dev
  • USA Canada Denmark Finland France Germany Norway Sweden UKItaly Japan 0.1.2.3.4.5 Intergen.ElasticityofEarnings(IGE) .34 .38 .42 .46 Gini Coefcient, 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 coecients are compared to before tax-and-transfer IGE. Correcting this mistake makes the Great Gatsby Curve insignicantly sloped. Econ and Ecom of Hum Dev
  • USA Canada DenmarkFinland France Germany Norway Sweden UKItaly Japan 0.1.2.3.4.5 Intergen.ElasticityofEarnings(IGE) .2 .25 .3 .35 Gini Coefcient, 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), the slope of the Great Gatsby Curve is arbitrarily controlled by the partly subjective choice of USA IGE estimate. Econ and Ecom of Hum Dev
  • USACanada Denmark Finland France Germany Norway Sweden UK Italy Japan 0.1.2.3.4.5 Intergen.ElasticityofEarnings(IGE) .34 .38 .42 .46 Gini Coefcient, Before Taxes and Transfers Alternate IGE Choice OLS: Slope=-0.16, p-value=.869 By replacing only three of the countries IGE estimates with plausible alternates from the literature, we arrive at a negatively-sloped Great Gatsby Curve. Conclusion: Coraks Great Gatsby Curve is not robust. This does not disprove the hypothesis that inequality and IGE are positively related. Econ and Ecom of Hum Dev
  • USA Canada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity(FathertoSonEarnings) .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
  • USA Canada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity .2 .25 .3 .35 Gini Coefcient, 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
  • USACanada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity .2 .25 .3 .35 Gini Coefcient, 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
  • USA Canada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity(FathertoSonEarnings) .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
  • USA Canada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity .2 .25 .3 .35 Gini Coefcient, 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
  • USACanada Denmark Finland France Germany Norway Sweden UK 0.1.2.3.4.5 IntergenerationalElasticity .2 .25 .3 .35 Gini Coefcient, 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
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix II Econ and Ecom of Hum Dev
  • Dynastic Model of Parental Investment that Emphasizes the Interaction of Dynamic Complementarity and Credit Markets Econ and Ecom of Hum Dev
  • Parents face dierent constraints i Inability of the family to borrow against future income of child (Already in the BeckerTomesSolon model: BTS) ii Inability of parents to borrow against their own future income (new to literature) Econ and Ecom of Hum Dev
  • Capability Formation in an Economy with Idiosyncratic Uncertainty and Liquidity Constraints (New to Literature) Econ and Ecom of Hum Dev
  • Generational Structure Each agent lives for 2T periods (T = 1 in BTS). During the rst T years of life, the agent is a child and by assumption makes no economic decisions. Upon reaching age T + 1, the agent becomes an adult and gives birth to a child. (Exogenous fertility.) The agent dies at the end of the calendar year in which she completes 2T years of age and is replaced in the beginning of the next calendar year by the generation of her grandchild. Econ and Ecom of Hum Dev
  • The Technology of Skill Formation Econ and Ecom of Hum Dev
  • It is investment; t stock of child skills; h stock of parental skills (h P). T distinct stages of development. The technology for capability formation: t+1 = ft (t, It, h) (22) f : increasing in each of its arguments, strictly concave, and twice-continuously dierentiable. Econ and Ecom of Hum Dev
  • To develop some intuition about the skill formation process implied by the production function (22), consider the following parameterization: t+1 = t 1tt t + 2tIt t + 3tht t t with 0 < 1,t, 2,t, 3,t, t < 1, t 1, k k,nt = 1. Econ and Ecom of Hum Dev
  • If T = 2, 1 = 2 = 1, 1 = 1, and 1 = 2 = 1. Skills at adulthood, h = 3 = T+1: h = 2 1,21,1 1 + 1,22,1 Multiplier eect I 1 + 2,2I 2 + (3,2 + 1,23,1) h 1 . Econ and Ecom of Hum Dev
  • An extreme example arises in the Leontief case where , in which case we would write: 3 = 2 min {1, I1, I2, h} (23) Econ and Ecom of Hum Dev
  • The Problem of the Parent Econ and Ecom of Hum Dev
  • The Problem When the Child Is between 1 and T 1 Years Old Parental labor supply is perfectly inelastic. At each age t of the child, the parent is subject to productivity innovations t. Corresponding to labor market uncertainty. The shocks t are independently and identically distributed across parents. The shocks follow a rst-order Markov process: ln t+1 = ln t + t . (24) Parents are assumed to have positive earnings. Restrict productivity innovations such that there exists min with the property that t min > 0 for any t = T + 1, . . . , 2T. Labor income of the parent: wht w is the eciency wage r is risk-free discount rate Econ and Ecom of Hum Dev
  • Given the state variables, the parent chooses household consumption Ct, savings st+1, and investments It in the cognitive skill of the child. The savings of the parents are in a risk-free asset which pays a rate of interest r. p denotes the price of the investment goods in cognitive skill. Following Laitner (1992), the parents cannot leave debts to their children and have negative net worth, so savings are subject to the lower bound equal to whmin (1+r) . Econ and Ecom of Hum Dev
  • V (t, h, t, st, t): the value function of the parent of a child at age t, 1 t T 1. The problem of the parent: V (t, h, t, st, t) = max Ct ,It ,st+1 {u (Ct) + E [V (t + 1, h, t+1, st+1, t+1)| t]} subject to: Ct + pIt + st+1 = wht + (1 + r) st (25) st+1 (whmin) , It, Ct 0 (26) and the technology for capability formation (22). Econ and Ecom of Hum Dev
  • The Problem When the Child Is T Years Old: Go to College or Not? Econ and Ecom of Hum Dev
  • Steady State GE Firms producing nal output (CRS) Also child investment good (Produced) Can establish stochastic GE for steady state, extending Aiyagari and Laitner to include human capital Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix III Econ and Ecom of Hum Dev
  • Table 3a: Studies on the Role of Income on Childrens Outcomes Dataset Outcome Studied: Test Scores (T), Schooling (S) Timing of Income (Developmental Stage of the Child at Which Income Eects are Studied) Separate the Eect of Income from Changes in Labor Supply or Family Environment Carneiro and Heckman (2002) NLSY79 S Early (E) and Late (L) College Enrollment X Belley and Lochner (2007) NLSY79, NLSY97 S L High school completion and College Enrollment X Dahl and Lochner (2012) NLSY79, C- NLSY79 T E Preadolescence (ages 8 to 14) Xa Duncan et al. (1998) PSID Sd E and L Childhood and Preadolescence (ages 0 to 15) X Econ and Ecom of Hum Dev
  • Table 3a (cont.): Studies on the Role of Income on Childrens Outcomes Dataset Outcome Studied: Test Scores (T), Schooling (S) Timing of Income (Developmental Stage of the Child at Which Income Eects are Studied) Separate the Eect of Income from Changes in Labor Supply or Family Environment Duncan et al. (2011) Randomized Interventions on Welfare Support T E Early Childhood (ages 2 to 5) X Loken (2010) Norwegian Administrative Data S E Childhood (ages 1 to 11) c Loken et al. (2012) Norwegian Administrative Data S E Childhood (ages 1 to 11) X Milligan and Stabile (2011) CCTB , NCBS T E Childhood (ages 0 to 10) X Carneiro et al. (2013) Norwegian Registry Se E and L Childhood to Adolescence (ages 0 to 17) X Econ and Ecom of Hum Dev
  • Table 3b: Studies on the Role of Income on Childrens Outcomes Distinguishes the Eects of Contemporaneous vs. Permanent Income Sources of Income Whose Eects are Studied Instrument Used Carneiro and Heckman (2002) Total family income None Belley and Lochner (2007) X Total family income None Dahl and Lochner (2012) Xb Total family income Policy variation in EITC eligibility Duncan et al. (1998) Total family income None Econ and Ecom of Hum Dev
  • Table 3b (continued): Studies on the Role of Income on Childrens Outcomes Distinguishes the Eects of Contemporaneous vs. Permanent Income Sources of Income Whose Eects are Studied Instrument Used Duncan et al. (2011) X Total family income Random assignment to programs oering welfare transfers conditional on employment or education related activities, or full time work Loken (2010) X Total family income Oil discovery (inducing regional increase in wages) Loken et al. (2012) X Total family income Oil discovery (inducing regional increase in wages) Milligan and Stabile (2011) X Child related tax benets and income transfers Variation in benets eligibility Carneiro et al. (2013) Total family income None Econ and Ecom of Hum Dev
  • Table 3c: Studies on the Role of Income on Childrens Outcomes Eect of Income on Human Capital Investments Carneiro and Heckman (2002) Percentage of people constrained = weighted gap in educational outcome to highest income group: 5.1% are constrained in college enrollment (1.2% among low income, low ability, 0.2% low income high ability), 9% in completion of 2-year college (5.3% among low income, low ability, 0.3% low income high ability). No eect of timing of receipt of family 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 eect of income; college enrollment: +9.3% for highest income quartile compared to lowest in 79, +16 in 97, cannot reject equal eect of income. Dahl and Lochner (2012) $1,000 extra per year for 2 years: +6% of a standard deviation in math and reading combined PIAT score. Duncan et al. (1998) $10,000 increase in average (age 0-15) family income: +1.3 years of schooling in low income ($20,000) families, +0.13 in high income ones. Relevance of income is stronger in the early years (age 0-5): $10,000 increase in average (age 0-5) family income leads to extra 0.8 years of schooling in low income families, 0.1 in high income ones. Income at age 6-10 and 11-15: no signicant eect. Similar results in a sibling dierences model. Econ and Ecom of Hum Dev
  • Table 3c (continued): Studies on the Role of Income on Childrens Outcomes Eect 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 childs achievement score. Loken (2010) OLS: positive relationship of average (age 1-13) family income on childrens education, IV: no causal eect. Results are robust to dierent specication and splitting the sample by 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 eects of child benets on cognitive outcomes for boys, on emotional outcomes for girls, weak on health. Results are non robust to the exclusion of Quebec. Carneiro et al. (2013) All outcomes: monotone and concave relationship with permanent income. 100,000 increase in permanent fathers earnings: +0.5 years of schooling. Timing of income: a balanced prole between early (age 0-5) and late childhood (age 6-11) is associated with the best outcomes; shifting income to adolescence is associated with better outcomes in dropping out of school, college attendance, earnings, IQ and teen pregnancy. Early and late childhood income are complements in determining schooling attainment, early and adolescent income are substitutes. Econ and Ecom of Hum Dev
  • Table 4a: Studies on Tests of Credit Constraints Dataset Outcome Studied: School- ing (S) Timing of Income (Developmental Stage of the Child at Which Constraints are Studied) Explicit Dynamic Model Who is Aected by Constraints: Parent of the Agent (P), Agent / Child (C) Keane and Wolpin (2001) NLSY79 S L College Enrollment C Carneiro and Heckman (2002) NLSY79, C- NLSY79 S E and L College Enrollment, Comple- tion, Delayed Entry X P Econ and Ecom of Hum Dev
  • Table 4a (continued): Studies on Tests of Credit Constraints Dataset Outcome Studied: School- ing (S) Timing of Income (Developmental Stage of the Child at Which Constraints are Studied) Explicit Dynamic Model Who is Aected by Constraints: Parent of the Agent (P), Agent / Child (C) Cameron and Taber (2004) NLSY79 S L Adolescence and College Enrollment X C Caucutt and Lochner (2012) NLSY79, C-NLSY79 Ta E and L Childhood and Adolescence P Econ and Ecom of Hum Dev
  • Table 4b: Studies on Tests of Credit Constraints Method to Test for Credit Constraints Find Presence of Credit Constraints Eect of Income or Constraints on Human Capital Investments Keane and Wolpin (2001) Structural estimation of the lower bound on asset level YES But 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 mean hourly wage rate; increase in consumption and re- duction in market hours; moderate reduction in parental transfers especially for the least educated parents. Carneiro and Heckman (2002) (1) Gap to students from highest income quartile. (2) Timing of income. (3) Dierence in IV and OLS estimates of Mincer coecient YES But aecting at most 8% of students (1) Conditioning on ability and family background factors, the role of income in determining school- ing decisions is minimal. The strongest evidence is in the low ability group. The test is not robust to accounting for parental preferences and paternal- ism. Observed dierences in attendance might be due to a consumption value of childs schooling for parents. (2) There is no evidence of a independent eect on college enrollment of early or late income once permanent income is accounted for. (3) The claim that higher IV than OLS estimates of the Mincer coecient implies credit constraints are incorrect: instruments used are invalid, the quality margin is ignored and self selection and compara- tive advantage can produce the result also in ab- sence of nancial constraints. Econ and Ecom of Hum Dev
  • Table 4b (continued): Studies on Tests of Credit Constraints Method to Test for Credit Constraints Find Presence of Credit Constraints Eect of Income or Constraints on Human Capital Investments Cameron and Taber (2004) IV estimation of returns to schooling using costs of schooling or foregone earnings as instruments NO Theoretical prediction: if borrowing constraints, IV estimates using direct costs of schooling higher than using opportunity costs. Data: IV estimates using the presence of a local college are smaller than the ones using foregone earnings. Regressions which interact college costs and characteristics po- tentially related to credit availability: no evidence of excess sensitivity to costs for potentially con- strained sample. Structural model: almost 0% of the population is found to borrow at a rate higher than the market one. Caucutt and Lochner (2012) Structural estimation of the lower bound on asset level YES Stronger eect on high skilled parents 50% of young parents are constrained: high school dropouts (50%), high school graduates (38%), col- lege dropouts (60%), college graduates (68%); and 12% of old parents are constrained. Families with college graduate parents benet the most from a reduction in credit constraints. Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix IV Econ and Ecom of Hum Dev
  • Table 5: Structural Models of Parental Investments ( means present; X means absent) OLG Model Dynastic Links Explicit Models of Parental Preferences, Altruism (A) or Paternalism (P) Model Estimated Cunha and Heckman (2007) A,B,C, i (A) X Cunha (2007) A,B,C i (A) Caucutt and Lochner (2012) B,C i (A) Del Boca et al. (2013) X X j (P) Gayle et al. (2013) A,C j (P) Cunha et al. (2013) X X j (P) Bernal (2008) X X j (P) AThrough parental skills, BThrough asset transfers, COnly through genes (initial conditions), DNatural borrowing limit, ELimits can be more stringent than natural limit. Econ and Ecom of Hum Dev
  • Table 5: Structural Models of Parental Investments ( means present; X means absent) Parental Goods Investment Parental Time Investment Technology Depends on Parental Skill Self- productivity Cunha and Heckman (2007) X Cunha (2007) X Caucutt and Lochner (2012) X X Del Boca et al. (2013) X Gayle et al. (2013) X Cunha et al. (2013) X Bernal (2008) AThrough parental skills, BThrough asset transfers, COnly through genes (initial conditions), DNatural borrowing limit, ELimits can be more stringent than natural limit. Econ and Ecom of Hum Dev
  • Table 5: Structural Models of Parental Investments ( means present; X means absent) Parental Learning About Technology Bequests Intragenerational Borrowing Multiple Skills of Children Cunha and Heckman (2007) X E X Cunha (2007) X D X Caucutt and Lochner (2012) X X E X Del Boca et al. (2013) X X X X Gayle et al. (2013) X X X X Cunha et al. (2013) X X X Bernal (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 than natural limit. Econ and Ecom of Hum Dev
  • Table 5: Structural Models of Parental Investment ( means present; X means absent) Multichild Families (Preferences for Equity vs. Eciency) Endogenous Fertility Decisions Multiple Parents Endogenous Mating Decisions Cunha and Heckman (2007) X X X X Cunha (2007) X X X X Caucutt and Lochner (2012) X X X X Del Boca et al. (2013) X X Gayle et al. (2013) Cunha et al. (2013) X X X X Bernal (2008) X X X X AThrough parental skills, BThrough asset transfers, COnly through genes (initial conditions), DNatural borrowing limit, ELimits can be more stringent than natural limit. Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix V Econ and Ecom of Hum Dev
  • Targeting Relatively More Investment Toward Disadvantaged Children Can Be Socially Ecient Econ and Ecom of Hum Dev
  • In a one period of childhood problem where parents (or social planners) seek to maximize the aggregate of adult skills (2): A 2 + B 2 subject to E = p1(IA 1 + IB 1 ), the rst order condition is F.O.C.: f (1) 2 B 1 , IA 1 = f (1) 2 B 1 , IB 1 . Econ and Ecom of Hum Dev
  • Notice that sign IA 1 = sign f (1) 12 () =1 , where f (1) 12 () is the value of f (12) in the neighborhood of (). Parents (social planners) invest more in the disadvantaged if inputs are substitutes with initial endowments and they invest less if they are complements. Econ and Ecom of Hum Dev
  • Suppose that parents (or social planners) seek to maximize A 3 + B 3 subject to E = p1(IA 1 + IB 1 ) + p2(IA 2 + IB 2 ). Econ and Ecom of Hum Dev
  • Even if (f (1) 12 > 0), greater rst period investment in the initially disadvantaged child may be optimal. This is more likely (ceteris paribus) (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 rst period (f (1) 1 = 2 1 ); (c) the smaller rst period complementarity (f (1) 21 ) relative to second period complementarity and absolutely Econ and Ecom of Hum Dev
  • (d) the more rapidly diminishing the marginal productivity of 1(f (1) 11 ); (e) the greater the second period complementarity (f (2) 12 ); (f) the greater the rst 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
  • Roughly speaking, the more concave are the technologies in terms of stocks of skills, the more favorable is the case for investing relatively more in the disadvantaged child. The greater the second period complementarity (f (2) 12 ), the greater the case for investing more in the initially disadvantaged child to allow the child to benet from greater second period complementarity of the stock of skills with second period investment. In general, even when investment is greater in the rst period for the disadvantaged child, second period investment is greater for the initially advantaged child. It is generally not ecient to make the initially disadvantaged child whole as it enters the second period when the eect of greater second period complementarity kicks in. Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix VI Econ and Ecom of Hum Dev
  • Table 6a: Summary of Eects for Main Interventions Participant/Evaluation Characteristics Program Age Duration Target Selection Follow-Up Sample RCTEval Elementary LAs Best 56 6Y SES Schl 12Y 19,320 No CSP 513 5Y Behav Refer 35Y 510 Yes SSDP 67 6Y Crime Prgrm 21Y 610 Yes Adolescence BBBS 10-16 1Y SES Self 1Y 960 Yes IHAD 1112 7Y SES Prgrm 8Y 180 Yes EPIS 1315 3Y Schl Schl 2Y 45,070 No xl club 14 2Y Schl Schl 2Y 261,420 No SAS 1415 5Y Schl, SES Schl 6Y 430 No STEP 1415 2Y Schl, SES Self 4Y 4,800 Yes QOP 1415 5Y Schl Prgrm 10Y 1,070 Yes Academies 1316 4Y Schl, SES Self 12Y 1,460 Yes ChalleNGe 1618 1Y Dropout Self 3Y 1,200 Yes Job Corps 1624 1Y SES Self 9Y 15,300 Yes Year-Up 1824 1Y SES Self 2Y 200 Yes Econ and Ecom of Hum Dev
  • Table 6b: Summary of Eects for Main Interventions Components Program Home Health Parental OnSite Group Elementary LAs Best CSP SSDP Adolescence BBBS IHAD EPIS xl club SAS STEP QOP Academies ChalleNGe Job Corps Year-Up Econ and Ecom of Hum Dev
  • Table 6c: Summary of Eects for Main Interventions Eects on Outcomes Return/Benets Program IQ School Character Education Health Crime Earnings Return BenetCost Elementary LAs Best 0.9 CSP SSDP 3.1 Adolescence BBBS 1.0 IHAD EPIS 0.93.0 xl club SAS STEP QOP 0.42 Academies ChalleNGe 6.4 2.66 Job Corps 0.22 Year-Up Econ and Ecom of Hum Dev
  • Table 6d: Summary of Eects for Main Interventions Participant/Evaluation Characteristics Program Age Duration Target Selection Follow-Up Sample RCTEval Early NFP < 0 2Y SES Prgrm 19Y 640 Yes ABC 0 5Y SES Refer 30Y 90 Yes IHDP 0 3Y Health Prgrm 18Y 640 Yes FDRP 0 5Y SES Prgrm 15Y 110 No PCDC 1 2Y SES Prgrm 15Y 170 Yes JSS 12 2Y Health Prgrm 22Y 160 Yes Perry 3 2Y SES, IQ Prgrm 37Y 120 Yes Head Start 3 2Y SES Prnt 23Y 4,170 Yes CPC 34 2Y SES Prnt 25Y 1,290 No TEEP 3,5 2Y SES Prgrm 22Y 260 Yes STAR 56 4Y SES Prgrm 22Y 11,000 Yes Econ and Ecom of Hum Dev
  • Table 6e: Summary of Eects for Main Interventions Components Program Home Health Parental OnSite Group Early NFP ABC IHDP FDRP PCDC JSS Perry Head Start CPC TEEP STAR Econ and Ecom of Hum Dev
  • Table 6f: Summary of Eects for Main Interventions Eects on Outcomes Return/Benets Program IQ School Character Education Health Crime Earnings Return BenetCost Early NFP 2.9 ABC 3.8 IHDP FDRP PCDC JSS Perry 710 7.112.2 Head Start CPC 18 10.8 TEEP STAR 6.2 Return to main text Econ and Ecom of Hum Dev
  • Appendix VII Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix VIII Econ and Ecom of Hum Dev
  • Closing the Gap: Perry Program Applied to Disadvantaged Black Population: Males Econ and Ecom of Hum Dev
  • Closing the Gap: Perry Program Applied to Disadvantaged Black Population: Females Return to main text Econ and Ecom of Hum Dev
  • Appendix IX Econ and Ecom of Hum Dev
  • Simulation Econ and Ecom of Hum Dev
  • Results Econ and Ecom of Hum Dev
  • Setup 1: Fixed Target Between Disadvantaged and Advantaged Children Econ and Ecom of Hum Dev
  • Scenario 1: Constant Complementarity Econ and Ecom of Hum Dev
  • Scenario 2: Increasing Complementarity Econ and Ecom of Hum Dev
  • Scenario 3: Complementarity and Substitutability Econ and Ecom of Hum Dev
  • Table 1, Setup 1: Fixed Targets between Advantaged and Disadvantaged Children Initial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period Scenario 1: Fixed Complementarity t=1 t=2 t=3 t=4 0.01 1.51 2.18 3.14 4.52 11.36 10 2.63 0.05 1.55 2.23 3.21 4.63 11.62 10 2.86 Scenario 2: Increasing Complementarity 0.01 1.33 2.17 3.24 4.66 11.41 10 2.94 0.05 1.30 2.16 3.26 4.69 11.41 10 3.01 Scenario 3: First Substitutes and Then Complements 0.01 0.69 1.58 3.25 4.68 10.19 10 2.97 0.05 0.67 1.57 3.25 4.68 10.16 10 2.98 Econ and Ecom of Hum Dev
  • Setup 2: Higher Skill Target for Advantaged Child Econ and Ecom of Hum Dev
  • Scenario 1: Constant Complementarity Econ and Ecom of Hum Dev
  • Scenario 2: Increasing Complementarity Econ and Ecom of Hum Dev
  • Scenario 3: Complementarity and Substitutability Econ and Ecom of Hum Dev
  • Table 2, Setup 2: Higher Target for the Advantaged Child Initial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period Scenario 1: Fixed Complementarity t=1 t=2 t=3 t=4 0.01 1.36 1.97 2.83 4.08 10.24 9 2.38 0.05 1.70 2.45 3.53 5.09 12.77 11 3.13 Scenario 2: Increasing Complementarity 0.01 1.20 1.96 2.92 4.21 10.29 9 2.67 0.05 1.43 2.37 3.57 5.15 12.52 11 3.28 Scenario 3: First Substitutes and Then Complements 0.01 0.64 1.42 2.94 4.23 9.23 9 2.73 0.05 0.72 1.73 3.56 5.12 11.12 11 3.22 Econ and Ecom of Hum Dev
  • Setup 3: Greater Target for Disadvantaged Kid Econ and Ecom of Hum Dev
  • Scenario 1: Constant Complementarity Econ and Ecom of Hum Dev
  • Scenario 2: Increasing Complementarity Econ and Ecom of Hum Dev
  • Scenario 3: Complementarity and Substitutability Econ and Ecom of Hum Dev
  • Table3, Setup 3: Higher Target for the Disadvantaged Child Initial Endowment Investment in each Period Total Investment Target Level of Skill in the Last Period Scenario 1: Fixed Complementarity t=1 t=2 t=3 t=4 0.01 1.66 2.40 3.45 4.97 12.48 11 2.88 0.05 1.40 2.01 2.90 4.17 10.48 9 2.59 Scenario 2: Increasing Complementarity 0.01 1.46 2.39 3.55 5.12 12.52 11 3.21 0.05 1.18 1.95 2.94 4.23 10.30 9 2.74 Scenario 3: First Substitutes and Then Complements 0.01 0.75 1.74 3.55 5.12 11.16 11 3.21 0.05 0.61 1.41 2.94 4.23 9.19 9 2.74 Econ and Ecom of Hum Dev
  • Return to main text Econ and Ecom of Hum Dev
  • Appendix X Econ and Ecom of Hum Dev
  • Comparing Perry Intervention to Eect of Changing Family Environments Econ and Ecom of Hum Dev
  • Disadvantaged Children: First Decile in the Distribution of Cognitive and Non-Cognitive Skills at Age 6 Mothers are in First Decile in the Distribution of Cognitive and Non-Cognitive Skills at Ages 1421 Changing initial Adolescent Changing conditions: moving intervention: Moving initial conditions children to the 4th investments at last and performing decile of distribution transition from 1st a balanced of skills only through to 9th decile intervention Baseline early investments High School Graduation 0.4109 0.6579 0.6391 0.9135 Enrollment in College 0.0448 0.1264 0.1165 0.3755 Conviction 0.2276 0.1710 0.1733 0.1083 Probation 0.2152 0.1487 0.1562 0.0815 Welfare 0.1767 0.0905 Perry Treatment Eects 0.0968 0.0259 The adolescent-only and balanced intervention programs cost 35% more than the Perry program. Source: Cunha and Heckman (2007) Return to main text Econ and Ecom of Hum Dev